Search results for: drug property prediction

Authors: Syed Beenish Rufai, Sarman Singh

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Background: Performance of Genotype MTBDRsl (Hain Life science GmbH Germany) for detection of mutations associated with second-line drug resistance is well known. However, less evidence regarding the association of mutations and genetic background of strains is known which, in the future, is essential for clinical management of anti-tuberculosis drugs in those settings where the probability of particular genotype is predominant. Material and Methods: During this retrospective study, a total of 259 MDR-TB isolates obtained from pulmonary TB patients were tested for second-line drug susceptibility testing (DST) using Genotype MTBDRsl VER 1.0 and compared with BACTEC MGIT-960 as a reference standard. All isolates were further characterized using spoligotyping. The spoligo patterns obtained were compared and analyzed using SITVIT_WEB. Results: Of total 259 MDR-TB isolates which were screened for second-line DST by Genotype MTBDRsl, mutations were found to be associated with gyrA, rrs and emb genes in 82 (31.6%), 2 (0.8%) and 90 (34.7%) isolates respectively. 16 (6.1%) isolates detected mutations associated with both FQ as well as to AG/CP drugs (XDR-TB). No mutations were detected in 159 (61.4%) isolates for corresponding gyrA and rrs genes. Genotype MTBDRsl showed a concordance of 96.4% for detection of sensitive isolates in comparison with second-line DST by BACTEC MGIT-960 and 94.1%, 93.5%, 60.5% and 50% for detection of XDR-TB, FQ, EMB, and AMK/CAP respectively. D94G was the most prevalent mutation found among (38 (46.4%)) OFXR isolates (37 FQ mono-resistant and 1 XDR-TB) followed by A90V (23 (28.1%)) (17 FQ mono-resistant and 6 XDR-TB). Among AG/CP resistant isolates A1401G was the most frequent mutation observed among (11 (61.1%)) isolates (2 AG/CP mono-resistant isolates and 9 XDR-TB isolates) followed by WT+A1401G (6 (33.3%)) and G1484T (1 (5.5%)) respectively. On spoligotyping analysis, Beijing strain (46%) was found to be the most predominant strain among pre-XDR and XDR TB isolates followed by CAS (30%), X (6%), Unique (5%), EAI and T each of 4%, Manu (3%) and Ural (2%) respectively. Beijing strain was found to be strongly associated with D94G (47.3%) and A90V mutations by (47.3%) and 34.8% followed by CAS strain by (31.6%) and 30.4% respectively. However, among AG/CP resistant isolates, only Beijing strain was found to be strongly associated with A1401G and WT+A1401G mutations by 54.5% and 50% respectively. Conclusion: Beijing strain was found to be strongly associated with the most prevalent mutations among pre-XDR and XDR TB isolates. Acknowledgments: Study was supported with Grant by All India Institute of Medical Sciences, New Delhi reference No. P-2012/12452.

Keywords: tuberculosis, line probe assay, XDR TB, drug susceptibility

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Authors: Ramesh Subramani, Mathivanan Narayanasamy, William Aalbersberg

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It is well accepted by last 35 years of research and on-going programmes that marine environment harbours abundant and unique biodiversity, which is currently playing as an important source in bioprospecting. It has become apparent that marine microorganisms are lead in the biodiscovery. Among marine organisms, actinobacteria are a target phylum for discovering novel antibiotics against increasing the multi-drug resistant human pathogens because of these taxa representing for novel genera and species. Marine actinomycetes are a proven source of new antibiotic leads and novel enzymes with important industrial applications. A total of 183 streptomycete and 25 non-streptomycete strains were isolated from different marine samples collected from north-eastern part of the Indian Ocean. Among them, 111 isolates displayed antibacterial activity against human pathogens and 151 exhibited antifungal activity against phytopathogens. Importantly, most of them produced various extracellular enzymes and 58 of them produced exopolysaccharides. Totally eight small bioactive compounds and a thermostable alkaline protease have been purified from a selected strain, Streptomyces fungicidicus. Besides, our on-going studies on non-streptomycete strains (rare actinomycetes) are most likely promising resource for new and unique compounds against current emerging drug-resistant pathogens. We have just recognised the chemical diversity in marine microorganisms. Therefore it is worthwhile to continue the exploration of marine microorganisms for new drug leads, novel enzymes and other bioprospecting research.

Keywords: bioactive compounds, industrial enzymes, marine actinobacteria, microbial metabolites, marine natural products

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Authors: Richa Mardianingrum, Srie R. N. Endah

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In this research, we have designed four isoniazid derivatives i.e., isonicotinohydrazide (1-isonicotinoyl semicarbazide, 1-thiosemi isonicotinoyl carbazide, N '-(1,3-dimethyl-1 h-pyrazole-5-carbonyl) isonicotino hydrazide, and N '-(1,2,3- 4-thiadiazole-carbonyl) isonicotinohydrazide. The docking and molecular dynamic have performed to them in order to study its interaction with Mycobacterium tuberculosis Enoyl-Acyl Carrier Protein Reductase (InhA). Based on this research, all of the compounds were predicted to have a stable interaction with Mycobacterium tuberculosis Enoyl-Acyl Carrier Protein Reductase (INHA) receptor, so they could be used as an anti-tuberculosis drug candidate.

Keywords: anti-tuberculosis, docking, Inhibin alpha subunit, InhA, inhibition, synthesis, isonicotinohydrazide

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Authors: Sutapa Som Chaudhury, Chitrangada Das Mukhopadhyay

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Alzheimer’s disease is a well-known form of dementia since its discovery in 1906. Current Food and Drug Administration approved medications e.g. cholinesterase inhibitors, memantine offer modest symptomatic relief but do not play any role in disease modification or recovery. In last three decades many small molecules, chaperons, synthetic peptides, partial β-secretase enzyme blocker have been tested for the development of a drug against Alzheimer though did not pass the 3rd clinical phase trials. Here in this study, we designed a PEGylated, aminogenic, tripeptidic polymer with two different molecular weights based on the aggregation prone amino acid sequence 17-20 in amyloid beta (Aβ) 1-42. Being conjugated with poly-ethylene glycol (PEG) which self-assembles into hydrophilic nanoparticles, these PEGylated tripeptides constitute a very good drug delivery system crossing the blood brain barrier while the peptide remains protected from proteolytic degradation and non-specific protein interactions. Moreover, being completely aminogenic they would not raise any side effects. These peptide inhibitors were evaluated for their effectiveness against Aβ42 fibrillation at an early stage of oligomer to fibril formation as well as preformed fibril clearance via Thioflavin T (ThT) assay, dynamic light scattering analyses, atomic force microscopy and scanning electron microscopy. The inhibitors were proved to be safe at a higher concentration of 20µM by the reduction assay of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) dye. Moreover, SHSY5Y neuroblastoma cells have shown a greater survivability when treated with the inhibitors following Aβ42 fibril and oligomer treatment as compared with the control Aβ42 fibril and/or oligomer treated neuroblastoma cells. These make the peptidic inhibitors a promising compound in the aspect of the discovery of alternative medication for Alzheimer’s disease.

Keywords: Alzheimer’s disease, alternative medication, amyloid beta, PEGylated peptide

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Authors: Leila Fozouni, Anahita Mazandarani

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Background: Maternal infections are the most common cause of infections in infants, and the level of infection and its severity highly depends on the degree of colonization of the bacteria in the mother; so, the occurrence of aggressive diseases is not unpredictable in mothers with very high colonization. Group B Streptococcus is part of the normal flora of the gastrointestinal and genital tracts in women and is the leading cause of septicemia and meningitis in newborns. Today Zinc oxide nanoparticle is regarded as one of the most commonly used and safest nanoparticles for defeating Gram-positive and Gram-negative bacteria. This study aims to determine the antibacterial effects of Zinc oxide on the growth of drug-resistant group B Streptococcus strains isolated from pregnant women. Materials and Methods: This cross-sectional study was conducted on 150 pregnant women of 28–37 weeks admitted to seven hospitals and maternity wards in Golestan province, northeast of Iran. For bacterial identification, rectovaginal swabs were firstly inoculated to the Todd-Hewitt Broth and cultured in blood agar (containing 5% sheep blood). Then microbiologic and PCR methods were performed to detect group B Streptococci. Disk diffusion and broth microdilution tests were used to determine the bacterial susceptibility to antibiotics according to CLSI M100(2021) criteria. The antibacterial properties of Zinc oxide nanoparticles were evaluated using the agar well-diffusion method. Results: The prevalence of group B Streptococcus was 18% in pregnant women. Out of twenty-seven positive cultures, 62.96% were higher than thirty years old. Ninety percent and 45% of isolates were resistant to clindamycin and erythromycin, respectively, and susceptibility to cefazolin was 71%. In addition, susceptibility to ampicillin and penicillin were 74% and 55%, respectively. The results showed that 82% of erythromycin-resistant, 92% clindamycin-resistant, and 78% of cefazolin-resistant isolates were eliminated by zinc oxide nanoparticles at a concentration of 100 mg/L of the nanoparticle. Furthermore, ZnONPs could inhibit all drug-resistant isolates at a concentration of 200 mg/mL (MIC90 ≥ 200). Conclusion: Since the drug resistance of group B streptococci against various antibiotics is increasing, determining and investigating the drug-resistance pattern of this bacterium to different antibiotics in order to prevent arbitrary consumption of antibiotics by pregnant women and ultimately prevent Infant mortality seems necessary. Generally, ZnONPs showed a high antimicrobial effect, and it was revealed that the bactericide effect increases upon the increase in the concentration of the nanoparticle.

Keywords: group B beta-hemolytic streptococcus, pregnant women, zinc oxide nanoparticles, drug resistance

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Authors: Eslam Dabbish, Fortuna Ponte, Stefano Scoditti, Emilia Sicilia, Gloria Mazzone

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The medical techniques based on the use of light for activating the drug are occupying a prominent place in the cancer treatment due to their selectivity that contributes to reduce undesirable side effects of conventional chemotherapy. Among these therapeutic treatments, photodynamic therapy (PDT) and photoactivated chemotherapy (PACT) are emerging as complementary approaches for selective destruction of neoplastic tissue through direct cellular damage. Both techniques rely on the employment of a molecule, photosensitizer (PS), able to absorb within the so-called therapeutic window. Thus, the exposure to light of otherwise inert molecules promotes the population of excited states of the drug, that in PDT are able to produce the cytotoxic species, such as 1O2 and other ROS, in PACT can be responsible of the active species release or formation. Following the success of cisplatin in conventional treatments, many other transition metal complexes were explored as anticancer agents for applications in different medical approaches, including PDT and PACT, in order to improve their chemical, biological and photophysical properties. In this field, several crucial characteristics of candidate PSs can be accurately predicted from first principle calculations, especially in the framework of density functional theory and its time-dependent formulation, contributing to the understanding of the entire photochemical pathways involved which can ultimately help in improving the efficiency of a drug. A brief overview of the outcomes on some platinum and ruthenium-based PSs proposed for the application in the two phototherapies will be provided.

Keywords: TDDFT, metal complexes, PACT, PDT

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Authors: Sara Assi, Berthe Hayar, Claudio Pisano, Nadine Darwiche, Walid Saad

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Nanomedicine, the application of nanotechnology to medicine, is an emerging discipline that has gained significant attention in recent years. Current breakthroughs in nanomedicine have paved the way to develop effective drug delivery systems that can be used to target cancer. The use of nanotechnology provides effective drug delivery, enhanced stability, bioavailability, and permeability, thereby minimizing drug dosage and toxicity. As such, the use of nanoparticle (NP) formulations in drug delivery has been applied in various cancer models and have shown to improve the ability of drugs to reach specific targeted sites in a controlled manner. Cancer is one of the major causes of death worldwide; in particular, colorectal cancer (CRC) is the third most common type of cancer diagnosed amongst men and women and the second leading cause of cancer related deaths, highlighting the need for novel therapies. Retinoids, consisting of natural and synthetic derivatives, are a class of chemical compounds that have shown promise in preclinical and clinical cancer settings. However, retinoids are limited by their toxicity and resistance to treatment. To overcome this resistance, various synthetic retinoids have been developed, including the adamantyl retinoid ST1926, which is a potent anti-cancer agent. However, due to its limited bioavailability, the development of ST1926 has been restricted in phase I clinical trials. We have previously investigated the preclinical efficacy of ST1926 in CRC models. ST1926 displayed potent inhibitory and apoptotic effects in CRC cell lines by inducing early DNA damage and apoptosis. ST1926 significantly reduced the tumor doubling time and tumor burden in a xenograft CRC model. Therefore, we developed ST1926-NPs and assessed their efficacy in CRC models. ST1926-NPs were produced using Flash NanoPrecipitation with the amphiphilic diblock copolymer polystyrene-b-ethylene oxide and cholesterol as a co-stabilizer. ST1926 was formulated into NPs with a drug to polymer mass ratio of 1:2, providing a stable formulation for one week. The contin ST1926-NP diameter was 100 nm, with a polydispersity index of 0.245. Using the MTT cell viability assay, ST1926-NP exhibited potent anti-growth activities as naked ST1926 in HCT116 cells, at pharmacologically achievable concentrations. Future studies will be performed to study the anti-tumor activities and mechanism of action of ST1926-NPs in a xenograft mouse model and to detect the compound and its glucuroconjugated form in the plasma of mice. Ultimately, our studies will support the use of ST1926-NP formulations in enhancing the stability and bioavailability of ST1926 in CRC.

Keywords: nanoparticles, drug delivery, colorectal cancer, retinoids

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Authors: Sun-Young Jang, Sung-Ah Kim, Dongyoun Shin

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The Intelligent transportation system is essential to build smarter cities. Machine learning based transportation prediction could be highly promising approach by delivering invisible aspect visible. In this context, this research aims to make a prototype model that predicts transportation network by using big data and machine learning technology. In detail, among urban transportation systems this research chooses bus system.  The research problem that existing headway model cannot response dynamic transportation conditions. Thus, bus delay problem is often occurred. To overcome this problem, a prediction model is presented to fine patterns of bus delay by using a machine learning implementing the following data sets; traffics, weathers, and bus statues. This research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data are gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is designed by the machine learning tool (RapidMiner Studio) and conducted tests for bus delays prediction. This research presents experiments to increase prediction accuracy for bus headway by analyzing the urban big data. The big data analysis is important to predict the future and to find correlations by processing huge amount of data. Therefore, based on the analysis method, this research represents an effective use of the machine learning and urban big data to understand urban dynamics.

Keywords: big data, machine learning, smart city, social cost, transportation network

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Authors: Itze Coronel Salomon

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The rise of organized crime and violence related to drug cartels in Mexico has created serious challenges for the authorities to provide security to those who live within its borders. However, to achieve a significant improvement in security is absolute respect for fundamental human rights by the authorities. Irregular migrants in Mexico are at serious risk of abuse. Research by Amnesty International as well as reports of the NHRC (National Human Rights) in Mexico, have indicated the major humanitarian crisis faced by thousands of migrants traveling in the shadows. However, the true extent of the problem remains invisible to the general population. The fact that federal and state governments leave no proper record of abuse and do not publish reliable data contributes to ignorance and misinformation, often spread by the media that portray migrants as the source of crime rather than their victims. Discrimination and intolerance against irregular migrants can generate greater hostility and exclusion. According to the modus operandi that has been recorded criminal organizations and criminal groups linked to drug trafficking structures deprive migrants of their liberty for forced labor and illegal activities related to drug trafficking, even some have been kidnapped for be trained as murderers . If the victim or their family cannot pay the ransom, the kidnapped person may suffer torture, mutilation and amputation of limbs or death. Migrant women are victims of sexual abuse during her abduction as well. In 2011, at least 177 bodies were identified in the largest mass grave found in Mexico, located in the town of San Fernando, in the border state of Tamaulipas, most of the victims were killed by blunt instruments, and most seemed to be immigrants and travelers passing through the country. With dozens of small graves discovered in northern Mexico, this may suggest a change in tactics between organized crime groups to the different means of obtaining revenue and reduce murder profile methods. Competition and conflict over territorial control drug trafficking can provide strong incentives for organized crime groups send signals of violence to the authorities and rival groups. However, as some Mexican organized crime groups are increasingly looking to take advantage of income and vulnerable groups, such as Central American migrants seem less interested in advertising his work to authorities and others, and more interested in evading detection and confrontation. This paper pretends to analyze the introduction of this new trend of kidnapping migrants for forced labors by drug cartels in Mexico into the forms of contemporary slavery and its implications.

Keywords: international law, migration, transnational organized crime

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Authors: Sai AKhila Budaraju

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Heritage sites are an integral part of cities and carry a sense of identity to the cities/ towns, but the process of urbanization is a carrying potential threat for the loss of these heritage sites/monuments. Both Central and State Governments listed the historic Golconda fort as National Important Monument and the Heritage precinct with eight heritage-listed buildings and two historical sites respectively, for conservation and preservation, due to the presence of IT Corridor 6kms away accommodating more people in the precinct is under constant pressure. The heritage precinct possesses high property values, being a prime location connecting the IT corridor and CBD (central business district )areas. The primary objective of the study was to assess and identify the factors that are affecting the heritage precinct through Mapping and documentation, Identifying and assessing the factors through empirical analysis, Ordinal regression analysis and Hedonic Pricing Model. Ordinal regression analysis was used to identify the factors that contribute to the changes in the precinct due to urbanization. Hedonic Pricing Model was used to understand and establish a relation whether the presence of historical monuments is also a contributing factor to the property value and to what extent this influence can contribute. The above methods and field visit indicates the Physical, socio-economic factors and the neighborhood characteristics of the precinct contributing to the property values. The outturns and the potential elements derived from the analysis of the Development Control Rules were derived as recommendations to Integrate both Old and newly built environments.

Keywords: heritage planning, heritage conservation, hedonic pricing model, ordinal regression analysis

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Authors: Trina Isabel D. Santiago, Juan Raphael M. Perez, Maria Angelica O. Soriano, Teresita B. Suing, Jumee F. Tayaban

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To achieve universal healthcare for everyone, the World Health Organization has emphasized the importance of National Medicines Policies for increased accessibility and utilization of high-quality and affordable medications. In the Philippines, significant challenges have been identified surrounding the sustainability of essential medicines, resulting in limited access such as high cost and dominance and market dominance and monopoly of multinational companies (MNCs) in the Philippine pharmaceutical industry. These identified challenges have been addressed by several initiatives, such as the Philippine National Drug Policy and Generics Act of 1988 (Republic Act 6675), to attempt to reduce drug prices. Despite these efforts, the concerns with drug accessibility and affordability continue to persist; hence, Republic Act 9502 was enacted. This paper attempts to review RA 9502 in the pursuit of making medicines more affordable for Filipinos, analyze and critique the problems and challenges associated with the law, and provide recommendations to address identified problems and challenges. A literature search and review, as well as an analysis of the law, has been done to evaluate the policy. RA 9502 recognizes the importance of market competition in drug price reduction and quality medicine accessibility. Contentious issues prior to enactment of the law include 1) parallel importation, pointing out that the drug price will depend on the global market price, 2) contrasting approaches in the drafting of the law as the House version focused on medicine price control while the Senate version prioritized market competition, and 3) MNCs opposing the amendments with concerns on discrimination, constitutional violations, and noncompliance with international treaty obligations. There are also criticisms and challenges with the implementation of the law in terms of content or modeling, interpretation and implementation, and other external factors or hindrances. The law has been criticized for its narrow scope as it only covers specific essential medicines with no cooperation with the national health insurance program. Moreover, the law has sections taking advantage of the TRIPS flexibilities, which disallow smaller countries to reap the benefits of flexibilities. The sanctions and penalties have an insignificant role in implementation as they only ask for a small portion of the income of MNCs. Proposed recommendations for policy improvement include aligning existing legislation through strengthened price regulation and expanded law coverage, strengthening penalties to promote law adherence, and promoting research and development to encourage and support local initiatives. Through these comprehensive recommendations, the issues surrounding the policy can be addressed, and the goal of enhancing the affordability and accessibility of medicines in the country can be achieved.

Keywords: drug accessibility, drug affordability, price regulation, Republic Act 9502

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Authors: Rady A., Elsheshai A., Eltawel M.

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Introduction and Aim of work: Literature suggest that antipsychotic medications may decrease cortisol level, an effect that seems to be more present with second generation antipsychotic. Our study aims at assessing effect of long term use of antipsychotics on cortisol level Subjects and Methods: 30 chronic schizophrenic patients on antipsychotics compared to 20 drug naive schizophrenic patients as regards serum cortisol level Results: Cortisol level was significantly lower in chronic schizophrenic patients receiving antipsychotics compared to drug naive patients (P=0.002 <0.05) Conclusion: Antipsychotic medications seem to have the potential to decrease cortisol level in blood. Among hypothesis proposed in literature is the good control of pseudo stress due to psychotic features.

Keywords: schizophrenia, antipsychotic, cortisol, HPA

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Authors: Hui Zhang, Sherif Beskhyroun

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Structural Health monitoring systems (SHM) are commonly used to identify and assess structural damage. In terms of damage detection, SHM needs to periodically collect data from sensors placed in the structure as damage-sensitive features. This includes abnormal changes caused by the strain field and abnormal symptoms of the structure, such as damage and deterioration. Currently, deploying sensors on a large scale in a building structure is a challenge. In this study, a highly stretchable strain sensors are used in this study to collect data sets of strain generated on the surface of full-size reinforced concrete (RC) frames under extreme cyclic load application. This sensing sheet can be switched freely between the test bending strain and the axial strain to achieve two different configurations. On this basis, the deep neural network prediction model of the frame beam and frame column is established. The training results show that the method can accurately predict the strain value and has good generalization ability. The two deep neural network prediction models will also be deployed in the SHM system in the future as part of the intelligent strain sensor system.

Keywords: strain sensing sheets, deep neural networks, strain measurement, SHM system, RC frames

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Authors: Leandra Prempeh, Emily Malugen

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Prenatal drug exposure can have a molecular impact on the hypothalamic and reward genes that regulate feeding behavior. This can impact feeding regulation, resulting in feeding difficulties and growth failure. This was potentially seen in “McKayla,” a 19- month old girl with a history of in-utero drug exposure, patent ductus arteriosus, and gastroesophageal reflux disease who presented for intensive day treatment feeding therapy. She was diagnosed with Avoidant Restrictive Food Intake Disorder, described as total food refusal and meeting 100% of her caloric needs from a gastrostomy tube. The primary goals during intensive feeding therapy were to increase her oral intake and decrease her reliance on supplementation with formula. Several behavioral antecedent manipulations were implemented to establish consistent responding and make progress towards treatment goals. This included multiple modified bolus placements (using underloaded and Nuk brush), reinforcement contingencies, and variety fading before stability was finally achieved. Following, increasing retention of bites then increasing volume and variety were goals targeted. From treatment onset to the last 3 days of treatment, McKayla's rate of rapid acceptance of bite presentations increased significantly from 33.33% to 93.13%, rapid swallowing went from 0.00% to 92.32%, and her percentage of inappropriate mealtime behavior and expels decreased from 58.33% and 100% to 2.31% and 7.68%, respectively. Overall, the treatment team successfully introduced and increased the bite size of 7 pureed foods, generalize the treatment to caregivers with high integrity, and began facilitating tube weaning. She was receiving about 33.42% of her needs by mouth at the time of discharge. Other nutritional concerns addressed during treatment included drinking a nutritionally complete drink out of an open cup and age appropriate growth. McKayla continued to have emesis almost daily, as was her baseline before starting treatment; however, the frequency during mealtime decreased. Overall, McKayla responded well to treatment. She had a very slow response to treatment and required a lot of antecedent manipulations to establish consistent responding. As the literature suggests, [drug]-exposed neonates, like McKayla, may be at increased risk for nutritional and growth challenges that may persist throughout development. This supports the need for longterm follow-up of infant growth.

Keywords: behavioral intervention, feeding problems, in-utero drug exposure, intensive multidisciplinary intervention

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Authors: Maryam Beiranvand

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Multi-drug resistance in various microorganisms has increased globally in many healthcare facilities. Less effective antimicrobial activity of drug therapies for infection control becomes trouble. Since 1980, no new type of antimicrobial drug has been identified, even though combinations of antibiotic drugs have been discovered almost every decade. Between 1981 and 2006, over 70% of novel pharmaceuticals and chemical agents came from natural sources. Microorganisms have yielded almost 22,000 natural compounds. The identification of antimicrobial components from endophytes bacteria could help overcome the threat posed by multi-drug resistant strains. The project aims to analyze and identify antimicrobial peptides isolated from entophytic bacteria and their activity against multidrug-resistant Gram-negative bacteria in South Korea. Endophytic Paenibacillus polymyxa. 4G3 isolated from the plant, Gynura procumbery exhibited considerable antimicrobial activity against Methicillin-resistant Staphylococcus aureus, and Escherichia coli. The Rapid Annotations using Subsystems Technology showed that the total size of the draft genome was 5,739,603bp, containing 5178 genes with 45.8% G+C content. Genome annotation using antiSMASH version 6.0.0 was performed, which predicted the most common types of non-ribosomal peptide synthetase (NRPS) and polyketide synthase (PKS). In this study, diethyl aminoethyl cellulose (DEAEC) resin was used as the first step in purifying for unknown peptides, and then the target protein was identified using hydrophilic and hydrophobic solutions, optimal pH, and step-by-step tests for antimicrobial activity. This crude was subjected to C18 chromatography and elution with 0, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100% methanol, respectively. Only the fraction eluted with 20% -60% methanol demonstrated good antimicrobial activity against MDR E. coli. The concentration of the active fragment was measured by the Brad-ford test, and Protein A280 - Thermo Fisher Scientific at the end by examining the SDS PAGE Resolving Gel, 10% Acrylamide and purity were confirmed. Our study showed that, based on the combined results of the analysis and purification. P polymyxa. 4G3 has a high potential exists for producing novel functions of polymyxin E and bacitracin against bacterial pathogens.

Keywords: endophytic bacteria, antimicrobial activity, antimicrobial peptide, whole genome sequencing analysis, multi -drug resistance gram negative bacteria

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Authors: M. H. Pazandeh, M. Doudi, S. Barahimi, L. Rahimzadeh Torabi

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The use of antibiotics is essential in reducing the occurrence of adverse effects and inhibiting the emergence of antibiotic resistance in microbial populations. The necessity for a novel methodology concerning local administration of antibiotics has arisen, with particular focus on dealing with localized infections prompted by bacterial colonization of medical devices or implant materials. Bioactive glasses (BG) are extensively employed in the field of regenerative medicine, encompassing a diverse range of materials utilized for drug delivery systems. In the present investigation, various drug carriers for imipenem and tetracycline, namely single systems BG/SnO2, BG/NiO with varying proportions of metal oxide, and nanocomposite BG/SnO2/NiO, were synthesized through the sol-gel technique. The antibacterial efficacy of the synthesized samples was assessed through the utilization of the disk diffusion method with the aim of neutralizing Staphylococcus aureus as the bacterial model. The current study involved the examination of the bioactivity of two samples, namely BG10SnO2/10NiO and BG20SnO2, which were chosen based on their heightened bacterial inactivation properties. This evaluation entailed the employment of two techniques: the measurement of the pH of simulated body fluid (SBF) solution and the analysis of the sample tablets through X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared (FTIR) spectroscopy. The sample tablets were submerged in SBF for varying durations of 7, 14, and 28 days. The bioactivity of the composite bioactive glass sample was assessed through characterization of alterations in its surface morphology, structure, and chemical composition. This evaluation was performed using scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, and X-ray diffraction spectroscopy. Subsequently, the sample was immersed in simulated liquids to simulate its behavior in biological environments. The specific body fat percentage (SBF) was assessed over a 28-day period. The confirmation of the formation of a hydroxyapatite surface layer serves as a distinct indicator of bioactivity. The infusion of antibiotics into the composite bioactive glass specimen was done separately, and then the release kinetics of tetracycline and imipenem were tested in simulated body fluid (SBF). Antimicrobial effectiveness against various bacterial strains have been proven in numerous instances using both melt and sol-gel techniques to create multiple bioactive glass compositions. An elevated concentration of calcium ions within a solution has been observed to cause an increase in the pH level. In aqueous suspensions, bioactive glass particles manifest a significant antimicrobial impact. The composite bioactive glass specimen exhibits a gradual and uninterrupted release, which is highly desirable for a drug delivery system over a span of 72 hours. The reduction in absorption, which signals the loss of a portion of the antibiotic during the loading process from the initial phosphate-buffered saline solution, indicates the successful bonding of the two antibiotics to the surfaces of the bioactive glass samples. The sample denoted as BG/10SnO2/10NiO exhibits a higher loading of particles compared to the sample designated as BG/20SnO2 in the context of bioactive glass. The enriched sample demonstrates a heightened bactericidal impact on the bacteria under investigation while concurrently preserving its antibacterial characteristics. Tailored bioactive glass that incorporates hydroxyapatite, with a regulated and efficient release of drugs targeting bacterial infections, holds promise as a potential framework for bone implant scaffolds following rigorous clinical evaluation, thereby establishing potential future biomedical uses. During the modification process, the introduction of metal oxides into bioactive glass resulted in improved antibacterial characteristics, particularly in the composite bioactive glass sample that displayed the highest level of efficiency.

Keywords: antibacterial, bioactive glasses, implant infections, multi drug resistant

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Authors: Sarah Crawford, Gerry Lesley

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This research is a pre-clinical assessment of anti-cancer effects of novel non-steroidal diethyl stilbestrol-like estrogen analogs in estrogen-receptor positive/ progesterone-receptor positive human breast cancer microtumors of MCF 7 cell line. Tamoxifen analog formulation (Tam A1) was used as a single agent or in combination with therapeutic concentrations of 4-hydroxytamoxifen, currently used as a long-term treatment for the prevention of breast cancer recurrence in women with estrogen receptor positive/ progesterone receptor positive malignancies. At concentrations ranging from 30-50 microM, Tam A1 induced microtumor disaggregation and cell death. Incremental cytotoxic effects correlated with increasing concentrations of Tam A1. Live tumor microscopy showed that microtumos displayed diffuse borders and substrate-attached cells were rounded-up and poorly adherent. A complete cytotoxic effect was observed using 40-50 microM Tam A1 with time course kinetics similar to 4-hydroxytamoxifen. Combined treatment with TamA1 (30-50 microM) and 4-hydroxytamoxifen (10-15 microM) induced a highly cytotoxic, synergistic combined treatment response that was more rapid and complete than using 4-hydroxytamoxifen as a single agent therapeutic. Microtumors completely dispersed or formed necrotic foci indicating a highly cytotoxic combined treatment response. Moreover, breast cancer microtumors treated with both 4-hydroxytamoxifen and Tam A1 displayed lower levels of long-term post-treatment regrowth, a critical parameter of primary drug resistance, than observed for 4-hydroxytamoxifen when used as a single agent therapeutic. Tumor regrowth at 6 weeks post-treatment with either single agent 4-hydroxy tamoxifen, Tam A1 or a combined treatment was assessed for the development of drug resistance. Breast cancer cells treated with both 4-hydroxytamoxifen and Tam A1 displayed significantly lower levels of post-treatment regrowth, indicative of decreased drug resistance, than observed for either single treatment modality. The preclinical data suggest that combined treatment involving the use of tamoxifen analogs may be a novel clinical approach for long-term maintenance therapy in patients with estrogen-receptor positive/progesterone-receptor positive breast cancer receiving hormonal therapy to prevent disease recurrence. Detailed data on time-course, IC50 and tumor regrowth assays post- treatment as well as a proposed mechanism of action to account for observed synergistic drug effects will be presented.

Keywords: 4-hydroxytamoxifen, tamoxifen analog, drug-resistance, microtumors

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Authors: Danilo López, Johana Hernández, Edwin Rivas

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The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: cognitive radio, neural network, prediction, primary user

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Authors: Sudhir Kumar, V. R. Sinha

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Background: The topical and systemic toxicity associated with present nonmelanoma skin cancer (NMSC) treatment therapy using 5-Fluorouracil (5-FU) make it necessary to develop a novel delivery system having lesser toxicity and better control over drug release. Solid lipid nanoparticles offer many advantages like: controlled and localized release of entrapped actives, nontoxicity, and better tolerance. Aim:-To investigate safety and efficacy of 5-FU loaded solid lipid nanoparticles as a topical delivery system for the treatment of nonmelanoma skin cancer. Method: Topical solid lipid nanoparticles of 5-FU were prepared using Compritol 888 ATO (Glyceryl behenate) as lipid component and pluronic F68 (Poloxamer 188), Tween 80 (Polysorbate 80), Tyloxapol (4-(1,1,3,3-Tetramethylbutyl) phenol polymer with formaldehyde and oxirane) as surfactants. The SLNs were prepared with emulsification method. Different formulation parameters viz. type and ratio of surfactant, ratio of lipid and ratio of surfactant:lipid were investigated on particle size and drug entrapment efficiency. Results: Characterization of SLNs like–Transmission Electron Microscopy (TEM), Differential Scannig calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR), Particle size determination, Polydispersity index, Entrapment efficiency, Drug loading, ex vivo skin permeation and skin retention studies, skin irritation and histopathology studies were performed. TEM results showed that shape of SLNs was spherical with size range 200-500nm. Higher encapsulation efficiency was obtained for batches having higher concentration of surfactant and lipid. It was found maximum 64.3% for SLN-6 batch with size of 400.1±9.22 nm and PDI 0.221±0.031. Optimized SLN batches and marketed 5-FU cream were compared for flux across rat skin and skin drug retention. The lesser flux and higher skin retention was obtained for SLN formulation in comparison to topical 5-FU cream, which ensures less systemic toxicity and better control of drug release across skin. Chronic skin irritation studies lacks serious erythema or inflammation and histopathology studies showed no significant change in physiology of epidermal layers of rat skin. So, these studies suggest that the optimized SLN formulation is efficient then marketed cream and safer for long term NMSC treatment regimens. Conclusion: Topical and systemic toxicity associated with long-term use of 5-FU, in the treatment of NMSC, can be minimized with its controlled release with significant drug retention with minimal flux across skin. The study may provide a better alternate for effective NMSC treatment.

Keywords: 5-FU, topical formulation, solid lipid nanoparticles, non melanoma skin cancer

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Authors: Eunji Choi, Borang Park, Youngjae Choi, Jinwoo Moon

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In this study, a predictive model for estimating the metabolism (MET) of human body was developed for the optimal control of indoor thermal environment. Human body images for indoor activities and human body joint coordinated values were collected as data sets, which are used in predictive model. A deep learning algorithm was used in an initial model, and its number of hidden layers and hidden neurons were optimized. Lastly, the model prediction performance was analyzed after the model being trained through collected data. In conclusion, the possibility of MET prediction was confirmed, and the direction of the future study was proposed as developing various data and the predictive model.

Keywords: deep learning, indoor quality, metabolism, predictive model

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Authors: Ranjot Kaur, Om P. Katare, Anupama Sharma, Sarah R. Dennison, Kamalinder K. Singh, Bhupinder Singh

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Respiratory microbial infections being among the top leading cause of death worldwide are difficult to treat as the microbes reside deep inside the airways, where only a small fraction of drug can access after traditional oral or parenteral routes. As a result, high doses of drugs are required to maintain drug levels above minimum inhibitory concentrations (MIC) at the infection site, unfortunately leading to severe systemic side-effects. Therefore, delivering antimicrobials directly to the respiratory tract provides an attractive way out in such situations. In this context, current study embarks on the systematic development of lung lia pid-modified chitosan nanoparticles for inhalation of voriconazole. Following the principles of quality by design, the chitosan nanoparticles were prepared by ionic gelation method and further coated with major lung lipid by precipitation method. The factor screening studies were performed by fractional factorial design, followed by optimization of the nanoparticles by Box-Behnken Design. The optimized formulation has a particle size range of 170-180nm, PDI 0.3-0.4, zeta potential 14-17, entrapment efficiency 45-50% and drug loading of 3-5%. The presence of a lipid coating was confirmed by FESEM, FTIR, and X-RD. Furthermore, the nanoparticles were found to be safe upto 40µg/ml on A549 and Calu-3 cell lines. The quantitative and qualitative uptake studies also revealed the uptake of nanoparticles in lung epithelial cells. Moreover, the data from Spraytec and next-generation impactor studies confirmed the deposition of nanoparticles in lower airways. Also, the interaction of nanoparticles with DPPC monolayers signifies its biocompatibility with lungs. Overall, the study describes the methodology and potential of lipid-coated chitosan nanoparticles in futuristic inhalation nanomedicine for the management of pulmonary aspergillosis.

Keywords: dipalmitoylphosphatidylcholine, nebulization, DPPC monolayers, quality-by-design

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Authors: Ilham Zaidi, P. Sankara Sarma, Quazi Taufique Ahmed, V. Raman Kutty, Khalid Umer Khayyam, Gurpreet Singh, Abhishek Royal

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Introduction: Tuberculosis is a global public health emergency, but it is particularly acute in India, which has the world's highest tuberculosis burden. Due to overpopulation, lack of sanitation, malnutrition, low living standards, and poor socioeconomic status, among other factors, it is India's most common infectious disease. The long period of treatment is one of the main reasons for considering it as a public health emergency. Consequently, there is an increase in patient noncompliance, which leads to treatment failure, adverse treatment outcomes, and deaths. This could lead to the growth of anti-TB drug resistance. According to the WHO, approximately 558 thousand new cases of Multi-Drug Resistance Tuberculosis were diagnosed worldwide, with 8.5 percent developed Extensively Drug Resistance Tuberculosis. Methodology: This study is a program-based cross-sectional descriptive survey of adult tuberculosis patients enrolled in the Delhi-based Revised National Tuberculosis Program. The study setting was 27 NTEP districts of Delhi. (N=65,893) and Sample size- was 200; the sampling method which is used in the study was the systemic random sampling method. Results: Most of the demographic factors (age, gender, residence, and family type) were not significantly associated with adherence; marital status was found statistically significant with the treatment compliance. Hesitation while telling people about the disease and motivation to strictly follow drug schedule by healthcare workers were other factors where a significant association with drug adherence was observed. The study findings also suggest that provision of food, minimal financial and other moral support from family, counseling, discussion and politeness by healthcare providers might also facilitate adherence. Discussion and Conclusions: For TB treatment, adherence, age, sex, socioeconomic status, types of accommodations, malnutrition, and personal hygiene should all be considered; similar results were observed in previous studies. In the care of TB patients, DOTS services, health workers, and family support play a significant role. According to the country's National Strategic Plan, the Indian government has set a goal of eliminating tuberculosis by 2025 and patients' compliance with TB care and treatment adherence is very crucial to achieve this aim. A cohort study will be able to give a better understanding of factors associated with adherence since this study may have missed some defaulters who were absconding and could not be reached. Important Terms: RNTCP, NTEP, DOTS, DS-TB, DR-TB, RR-TB, MDR-TB, XDR-TB, Treatment failure, Treatment relapse, Treatment adherence.

Keywords: treatment adherence, treatment relapse, treatment failure, drug resistance tuberculosis

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Authors: Carmen Georgeta Dumitrache

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Measurements of terrestrial science aims to study the totality of operations and computing, which are carried out for the purposes of representation on the plan or map of the land surface in a specific cartographic projection and topographic scale. With the development of society, the metrics have evolved, and they land, being dependent on the achievement of a goal-bound utility of economic activity and of a scientific purpose related to determining the form and dimensions of the Earth. For measurements in the field, data processing and proper representation on drawings and maps of planimetry and landform of the land, using topographic and geodesic instruments, calculation and graphical reporting, which requires a knowledge of theoretical and practical concepts from different areas of science and technology. In order to use properly in practice, topographical and geodetic instruments designed to measure precise angles and distances are required knowledge of geometric optics, precision mechanics, the strength of materials, and more. For processing, the results from field measurements are necessary for calculation methods, based on notions of geometry, trigonometry, algebra, mathematical analysis and computer science. To be able to illustrate topographic measurements was established for the lifting of property located near the locality of Gircov, Romania. We determine this total surface of the plan (T30), parcel/plot, but also in the field trace the coordinates of a parcel. The purpose of the removal of the planimetric consisted of: the exact determination of the bounding surface; analytical calculation of the surface; comparing the surface determined with the one registered in the documents produced; drawing up a plan of location and delineation with closeness and distance contour, as well as highlighting the parcels comprising this property; drawing up a plan of location and delineation with closeness and distance contour for a parcel from Dave; in the field trace outline of plot points from the previous point. The ultimate goal of this work was to determine and represent the surface, but also to tear off a plot of the surface total, while respecting the first surface condition imposed by the Act of the beneficiary's property.

Keywords: topography, surface, coordinate, modeling

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Authors: Shazia Mannan, Zunera Khalid, Hammad-Ul-Mubeen

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Wingless type Mouse mammary tumor virus (MMTV) Integration site-10B (Wnt10B) is an important member of the Wnt protein family that functions as cellular messenger in paracrine manner. Aberrant Wnt10B activity is the cause of several abnormalities including cancers of breast, cervix, liver, gastric tract, esophagus, pancreas as well as physiological problems like obesity, and osteoporosis. The objective of this study was to determine the possible inhibitors against aberrant expression of Wnt10B in order to prevent and treat the physiological disorders associated with it. Wnt10B3D structure was predicted by using comparative modeling and then analyzed by PROCHECK, Verify3D, and Errat. The model having 84.54% quality value was selected and acylated to satisfy the hydrophobic nature of Wnt10B. For search of inhibitors, virtual screening was performed on Natural Products (NP) database. The compounds were filtered and ligand-based screening was performed using the antagonist for mouse Wnt-3A. This resulted in a library of 272 unique compounds having most potent drug like activities for Wnt-4. Out of the 271 molecules analyzed three small molecules ZINC35442871, ZINC85876388, and ZINC00754234 having activity against Wnt4 abbarent expression were found common through docking experiment of Wnt10B. It is concluded that the three molecules ZINC35442871, ZINC85876388, and ZINC00754234 can be considered as lead compounds for performing further drug designing experiments against aberrant Wnt expressions.

Keywords: Wnt10B inhibitors, comparative computational studies, proto-oncogene, molecular docking

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Authors: Rosa Tsegaye Aga, Xuan Jiang, Pavel Vazquez Faci, Siqing Liu, Simon Rayner, Endalkachew Alemu, Markos Abebe

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Tuberculosis (TB) is a major cause of disease globally. In most cases, TB is treatable and curable, but only with the proper treatment. There is a time when drug-resistant TB occurs when bacteria become resistant to the drugs that are used to treat TB. Current strategies to identify drug-resistant TB bacteria are laboratory-based, and it takes a longer time to identify the drug-resistant bacteria and treat the patient accordingly. But machine learning (ML) and data science approaches can offer new approaches to the problem. In this study, we propose to develop an ML-based model to predict the antibiotic resistance phenotypes of TB isolates in minutes and give the right treatment to the patient immediately. The study has been using the whole genome sequence (WGS) of TB isolates as training data that have been extracted from the NCBI repository and contain different countries’ samples to build the ML models. The reason that different countries’ samples have been included is to generalize the large group of TB isolates from different regions in the world. This supports the model to train different behaviors of the TB bacteria and makes the model robust. The model training has been considering three pieces of information that have been extracted from the WGS data to train the model. These are all variants that have been found within the candidate genes (F1), predetermined resistance-associated variants (F2), and only resistance-associated gene information for the particular drug. Two major datasets have been constructed using these three information. F1 and F2 information have been considered as two independent datasets, and the third information is used as a class to label the two datasets. Five machine learning algorithms have been considered to train the model. These are Support Vector Machine (SVM), Random forest (RF), Logistic regression (LR), Gradient Boosting, and Ada boost algorithms. The models have been trained on the datasets F1, F2, and F1F2 that is the F1 and the F2 dataset merged. Additionally, an ensemble approach has been used to train the model. The ensemble approach has been considered to run F1 and F2 datasets on gradient boosting algorithm and use the output as one dataset that is called F1F2 ensemble dataset and train a model using this dataset on the five algorithms. As the experiment shows, the ensemble approach model that has been trained on the Gradient Boosting algorithm outperformed the rest of the models. In conclusion, this study suggests the ensemble approach, that is, the RF + Gradient boosting model, to predict the antibiotic resistance phenotypes of TB isolates by outperforming the rest of the models.

Keywords: machine learning, MTB, WGS, drug resistant TB

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Authors: Kuo-Wei Liao, Jessica Gitomarsono

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Bridge reliability against natural hazards such as floods or earthquakes is an interdisciplinary problem that involves a wide range of knowledge. Moreover, due to the global climate change, engineers have to design a structure against the multi-hazard threats. Currently, few of the practical design guideline has included such concept. The bridge foundation in Taiwan often does not have a uniform width. However, few of the researches have focused on safety evaluation of a bridge with a complex pier. Investigation of the scouring depth under such situation is very important. Thus, this study first focuses on investigating and improving the scour prediction formula for a bridge with complicated foundation via experiments and artificial intelligence. Secondly, a probabilistic design procedure is proposed using the established prediction formula for practical engineers under the multi-hazard attacks.

Keywords: bridge, reliability, multi-hazards, scour

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Authors: Mostafa Sefidgar, Sohrab Zendehboudi, Hossein Bazmara, Madjid Soltani

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Based on findings from clinical applications, most drug treatments fail to eliminate malignant tumors completely even though drug delivery through systemic administration may inhibit their growth. Therefore, better understanding of tumor formation is crucial in developing more effective therapeutics. For this purpose, nowadays, solid tumor modeling and simulation results are used to predict how therapeutic drugs are transported to tumor cells by blood flow through capillaries and tissues. A solid tumor is investigated as a porous media for fluid flow simulation. Most of the studies use Darcy model for porous media. In Darcy model, the fluid friction is neglected and a few simplified assumptions are implemented. In this study, the effect of these assumptions is studied by considering Brinkman model. A multi scale mathematical method which calculates fluid flow to a solid tumor is used in this study to investigate how neglecting fluid friction affects the solid tumor simulation. In this work, the mathematical model in our previous studies is developed by considering two model of momentum equation for porous media: Darcy and Brinkman. The mathematical method involves processes such as fluid flow through solid tumor as porous media, extravasation of blood flow from vessels, blood flow through vessels and solute diffusion, convective transport in extracellular matrix. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network. Finally, the two models of porous media are used for modeling fluid flow in normal and tumor tissues in three different shapes of tumors. Simulations of interstitial fluid transport in a solid tumor demonstrate that the simplifications used in Darcy model affect the interstitial velocity and Brinkman model predicts a lower value for interstitial velocity than the values that Darcy model does.

Keywords: solid tumor, porous media, Darcy model, Brinkman model, drug delivery

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Authors: Khaled Elbehiery, Hussam Elbehiery

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Smart cities are a framework of technologies along with sustainable infrastructure to provide their citizens an improved quality of life, safer environment, affordability, and more, which in turn helps with the society's economic growth. The proposed research will focus on the primary building block of the smart city; the infrastructure of the house itself. The traditional method of building houses has been, for a long time, nothing but a costly manufacturing process, and consequently, buying a house becomes not an option for everyone anymore. The smart cities' Modular Houses are not using traditional building construction materials; the design reduces the common lengthy construction times and associated high costs. The Modular Houses are technological homes, low-cost and customizable based on a family's requirements. In addition, the Modular Houses are environmentally friendly and healthy enough to assist with the pandemic situation.

Keywords: smart cities, modular houses, single-unit property, multi-unit property, mobility features, chain-supply, livable environment, carbon footprint

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Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: audit, machine learning, assessment, metrics

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Authors: Peifang Hsieh

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The prevention of child abuse has aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported child abuse cases that doubled over the past decade and the scarcity of social workers. New Taipei city, with the most population in Taiwan and over 70% of its 4 million citizens are migrant families in which the needs of children can be easily neglected due to insufficient support from relatives and communities, sees urgency for a social support system, by preemptively identifying and outreaching high-risk families of child abuse, so as to offer timely assistance and preventive measure to safeguard the welfare of the children. Big data analysis is the inspiration. As it was clear that high-risk families of child abuse have certain characteristics in common, New Taipei city decides to consolidate detailed background information data from departments of social affairs, education, labor, and health (for example considering status of parents’ employment, health, and if they are imprisoned, fugitives or under substance abuse), to cross-reference for accurate and prompt identification of the high-risk families in need. 'The Service Center for High-Risk Families' (SCHF) was established to integrate data cross-departmentally. By utilizing the machine learning 'random forest method' to build a risk prediction model which can early detect families that may very likely to have child abuse occurrence, the SCHF marks high-risk families red, yellow, or green to indicate the urgency for intervention, so as to those families concerned can be provided timely services. The accuracy and recall rates of the above model were 80% and 65%. This prediction model can not only improve the child abuse prevention process by helping social workers differentiate the risk level of newly reported cases, which may further reduce their major workload significantly but also can be referenced for future policy-making.

Keywords: child abuse, high-risk families, big data analysis, risk prediction model

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