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The Covid-19 pandemic in Indonesia, including Yogyakarta, has created a psychological impact on the community. One of the psychological impacts is depression. This issue can be overcome by early detecting depression using an instrument called the World Health Organization-Five Well-Being Index (WHO-5). Unfortunately, this instrument is currently unavailable in the Indonesian version. Therefore, this study aims to obtain a valid and reliable Indonesian version of the WHO-5, which can later be used by pharmacists as an instrument to early detect depression in Indonesia, especially in Yogyakarta. This research employed a cross-sectional design. The research subjects were people who visited Apotek UAD 1 and 2, who met the inclusion and were not included in the exclusion criteria. The WHO-5 questionnaire proceeded through a translation process from the English version to the Indonesian version. The original version of the WHO-5 questionnaire, which was the final translated version, was tested on 40 respondents to gain its validity and reliability. The analysis of the validity test using the Pearson Correlation of five questions on the WHO-5 questionnaire has revealed an average value of r = 1, indicating that the questionnaire is valid. The result of the reliability test with Cronbach Alpha is 0.853. In conclusion, the Indonesian version of the WHO-5 questionnaire meets the validity and reliability criteria so that the questionnaire can apply to the community.

Abstract Diabetic foot ulcers (DFUs) are a common complication of diabetes and can lead to severe disability and even amputation. Despite advances in treatment, there is currently no cure for DFUs and available drugs for treatment are limited. This study aimed to identify new candidate drugs and repurpose existing drugs to treat DFUs based on transcriptomics analysis. A total of 31 differentially expressed genes (DEGs) were identified and used to prioritize the biological risk genes for DFUs. Further investigation using the database DGIdb revealed 12 druggable target genes among 50 biological DFU risk genes, corresponding to 31 drugs. Interestingly, we highlighted that two drugs (urokinase and lidocaine) are under clinical investigation for DFU and 29 drugs are potential candidates to be repurposed for DFU therapy. The top 5 potential biomarkers for DFU from our findings are IL6ST, CXCL9, IL1R1, CXCR2, and IL10. This study highlights IL1R1 as a highly promising biomarker for DFU due to its high systemic score in functional annotations, that can be targeted with an existing drug, Anakinra. Our study proposed that the integration of transcriptomic and bioinformatic-based approaches has the potential to drive drug repurposing for DFUs. Further research will further examine the mechanisms by which targeting IL1R1 can be used to treat DFU.

Hemorrhoids are a prevalent medical condition that necessitates effective treatment options. The current options for treatment consist of oral medications, topical applications, or surgery, yet a scarcity of highly effective drugs still exists. Genetic markers provide promising avenues for investigating the treatment of hemorrhoids, as they may reveal intricate biological mechanisms and targeted drug therapies, ultimately enhancing more precise treatment tailored to the patient. This study aims to identify new drug candidates for treating hemorrhoids through a meticulous bioinformatics approach and integrated with genomic network analysis. After extracting 21 druggable target genes using DrugBank from 293 genes connected to hemorrhoids, 87 possible drugs were selected. Three of these drugs (ketamine, methylene blue, and fulvestrant) hold potential in addressing issues associated with hemorrhoids and have been supported by clinical or preclinical studies. Eighty-four compounds present new therapeutic possibilities for managing hemorrhoids. We highlight that our findings indicate that NOX1 and NOS3 genes are promising biomarkers, with NOS3 gaining significance owing to its robust systemic functional annotations. Sapropterin, an existing drug, is closely associated with NOS3, providing a clear target for biomarker-driven interventions. This study illustrates the potential of combining genomic network analysis with bioinformatics to repurpose drugs for treating hemorrhoids. Subsequent research will explore the mechanisms for utilizing NOS3 targeting in the treatment of hemorrhoids.

In terms of bibliometric analysis, there are no studies related to the impact of social support on breast cancer survivors' quality of life. Therefore, this study aims to provide a bibliometric assessment of results on social support in quality of life in breast cancer patients. The studies for the dataset were selected from Scopus published in the year 2001–2021 based on their relevancy to the established subjects. The VOSviewer software was used for bibliometric analysis to represent the performance of publications covering annual outputs, mainstream journals leading countries, institutions, research tendencies, and hotspots. The analysis of the findings indicated only 45 articles over the range of 2001-2021. The highest number of publications was published in 2021, and the lowest was in 2002-2004 and 2006. Social support strongly correlates with the psychological adjustment of adherence to cancer treatment. Only one study failed to find an association between social support and suicide after a cancer diagnosis. Meanwhile, China, the United States, and Hong Kong contributed to social support. Instrumental, financial, information, and emotional support were reported as domains needed to support breast cancer patients. This bibliometric analysis provides the results of thoughts and insights about the development needed by breast cancer patients to prolong survival.

Psoriasis is an autoimmune disease that causes inflammation on the skin's surface, characterized by the appearance of pink plaques covered with white scales. Currently, the availability of psoriasis vulgaris therapy is still limited. Therefore, considering the discovery of new drug candidates by utilizing genetic variations, such as single nucleotide polymorphisms (SNP) through drug repurposing, is a profitable method. The SNP associated with psoriasis was obtained from Genome-Wide Association Studies (GWAS) and Phenom Wide Association Studies (PheWAS) databases. We identified 245 SNPs associated with psoriasis vulgaris with criteria of r2 >0.8. To prioritize the candidate of a gene associated with psoriasis, we used five criteria of functional annotation (missense/nonsense, cis-eQTL, PPI, KEGG, Ko mice) where if there were more than two criteria of assessment, they were defined as the risk gene of psoriasis vulgaris. Fifty-two genes were identified as the risk gene of psoriasis vulgaris, then expanded using the STRING database to obtain more gene candidates of drug targets. The result is 104 genes candidates for drug targets, of which 24 overlapped with 96 drugs, according to DrugBank. Of the 96 drugs that have been approved for other indications, we found that five drugs (ustekinumab, tildrakizumab, riszankizumab, guselkumab, and etanercept) are currently in clinical trials for the treatment of psoriasis that target two genes (IL23A and TNF). We argue that these two genes are the most promising targets based on their high target scores on functional annotations. This research explains the potential that utilizing genomic variation can contribute to drug discovery.

One of the important outcomes to define the success of cancer treatment is the health-related quality of life (HRQoL) that can be measured using generic and/or specific instruments. Our study aims to define the cancer patients’ HRQoL in some hospitals in Indonesia as measured by the European Organization for Research and Treatment for Cancer (EORTC QLQ-C30) and the EQ-5D-5L, to define the differences of cancer patients’ HRQoL referring to patients’ characteristics, and to explore determinants of cancer patients’ HRQoL. We recruited 451 cancer patients using a cross-sectional design in two referral hospitals in Central Java, Indonesia, using the purposive sampling technique. All subjects, recruited from July 2020 to October 2021, met the inclusion criteria, namely, adult patients diagnosed with cancers in all stages who willingly participated in the study. The Indonesian value set was used to obtain the EQ-5D-5L index score. We further analyzed the data based on cancer stages and compared two questionnaires using independent t test. We highlighted that most of the cancer patients are female (69.4%), young (86%), and at advanced stages of cancer (54.1%). The physical and role functions and global health status of the cancer patients are poor, and the most severe symptom is fatigue. Moreover, most of them experience severe pain and perform daily activities with difficulties. Some patients’ characteristics show significant influences on the HRQoL domains in both questionnaires (p

According to the National Comprehensive Cancer Network and the American Society of Clinical Oncology, the standard treatment for pancreatic cancer (PC) is gemcitabine and fluorouracil. Other chemotherapeutic agents have been widely combined. However, drug resistance remains a huge challenge, leading to the ineffectiveness of cancer therapy. Therefore, we are trying to discover new treatments for PC by utilizing genomic information to identify PC-associated genes as well as drug target genes for drug repurposing. Genomic information from a public database, the cBio Cancer Genomics Portal, was employed to retrieve the somatic mutation genes of PC. Five functional annotations were applied to prioritize the PC risk genes: Kyoto Encyclopedia of Genes and Genomes; biological process; knockout mouse; Gene List Automatically Derived For You; and Gene Expression Omnibus Dataset. DrugBank database was utilized to extract PC drug targets. To narrow down the most promising drugs for PC, CMap Touchstone analysis was applied. Finally, ClinicalTrials.gov and a literature review were used to screen the potential drugs under clinical and preclinical investigation. Here, we extracted 895 PC-associated genes according to the cBioPortal database and prioritized them by using five functional annotations; 318 genes were assigned as biological PC risk genes. Further, 216 genes were druggable according to the DrugBank database. CMap Touchstone analysis indicated 13 candidate drugs for PC. Among those 13 drugs, 8 drugs are in the clinical trials, 2 drugs were supported by the preclinical studies, and 3 drugs are with no evidence status for PC. Importantly, we found that midostaurin (targeted PRKA) and fulvestrant (targeted ESR1) are promising candidate drugs for PC treatment based on the genomic-driven drug repurposing pipelines. In short, integrated analysis using a genomic information database demonstrated the viability for drug repurposing. We proposed two drugs (midostaurin and fulvestrant) as promising drugs for PC.

Multiple sclerosis (MS) is a chronic autoimmune disease in the central nervous system (CNS) marked by inflammation, demyelination, and axonal loss. Currently available MS medication is limited, thereby calling for a strategy to accelerate new drug discovery. One of the strategies to discover new drugs is to utilize old drugs for new indications, an approach known as drug repurposing. Herein, we first identified 421 MS-associated SNPs from the Genome-Wide Association Study (GWAS) catalog (p-value < 5 × 10−8), and a total of 427 risk genes associated with MS using HaploReg version 4.1 under the criterion r2 > 0.8. MS risk genes were then prioritized using bioinformatics analysis to identify biological MS risk genes. The prioritization was performed based on six defined categories of functional annotations, namely missense mutation, cis-expression quantitative trait locus (cis-eQTL), molecular pathway analysis, protein-protein interaction (PPI), genes overlap with knockout mouse phenotype, and primary immunodeficiency (PID). A total of 144 biological MS risk genes were found and mapped into 194 genes within an expanded PPI network. According to the DrugBank and the Therapeutic Target Database, 27 genes within the list targeted by 68 new candidate drugs were identified. Importantly, the power of our approach is confirmed with the identification of a known approved drug (dimethyl fumarate) for MS. Based on additional data from ClinicalTrials.gov, eight drugs targeting eight distinct genes are prioritized with clinical evidence for MS disease treatment. Notably, CD80 and CD86 pathways are promising targets for MS drug repurposing. Using in silico drug repurposing, we identified belatacept as a promising MS drug candidate. Overall, this study emphasized the integration of functional genomic variants and bioinformatic-based approach that reveal important biological insights for MS and drive drug repurposing efforts for the treatment of this devastating disease.

Dermatomyositis (DM) is an autoimmune disease that is classified as a type of idiopathic inflammatory myopathy, which affects human skin and muscles. The most common clinical symptoms of DM are muscle weakness, rash, and scaly skin. There is currently no cure for DM. Genetic factors are known to play a pivotal role in DM progression, but few have utilized this information geared toward drug discovery for the disease. Here, we exploited genomic variation associated with DM and integrated this with genomic and bioinformatic analyses to discover new drug candidates. We first integrated genome-wide association study (GWAS) and phenome-wide association study (PheWAS) catalogs to identify disease-associated genomic variants. Biological risk genes for DM were prioritized using strict functional annotations, further identifying candidate drug targets based on druggable genes from databases. Overall, we analyzed 1239 variants associated with DM and obtained 43 drugs that overlapped with 13 target genes (JAK2, FCGR3B, CD4, CD3D, LCK, CD2, CD3E, FCGR3A, CD3G, IFNAR1, CD247, JAK1, IFNAR2). Six drugs clinically investigated for DM, as well as eight drugs under pre-clinical investigation, are candidate drugs that could be repositioned for DM. Further studies are necessary to validate potential biomarkers for novel DM therapeutics from our findings.

Background: One of the main challenges in personalized medicine is to establish and apply a large number of variants from genomic databases into clinical diagnostics and further facilitate genome-driven drug repurposing. By utilizing biological chronic hepatitis B infection (CHB) risk genes, our study proposed a systematic approach to use genomic variants to drive drug repurposing for CHB. Method: The genomic variants were retrieved from the Genome-Wide Association Study (GWAS) and Phenome-Wide Association Study (PheWAS) databases. Then, the biological CHB risk genes crucial for CHB progression were prioritized based on the scoring system devised with five strict functional annotation criteria. A score of ≥ 2 were categorized as the biological CHB risk genes and further shed light on drug target genes for CHB treatments. Overlapping druggable targets were identified using two drug databases (DrugBank and Drug-Gene Interaction Database (DGIdb)). Results: A total of 44 biological CHB risk genes were screened based on the scoring system from five functional annotation criteria. Interestingly, we found 6 druggable targets that overlapped with 18 drugs with status of undergoing clinical trials for CHB, and 9 druggable targets that overlapped with 20 drugs undergoing preclinical investigations for CHB. Eight druggable targets were identified, overlapping with 25 drugs that can potentially be repurposed for CHB. Notably, CD40 and HLA-DPB1 were identified as promising targets for CHB drug repurposing based on the target scores. Conclusion: Through the integration of genomic variants and a bioinformatic approach, our findings suggested the plausibility of CHB genomic variant-driven drug repurposing for CHB.

Multi-drug resistant (MDR) bacteria are becoming a worldwide problem due to limited options for treatment. Moreover, patients infected by MDR with highly virulent accessories are worsening the symptoms, even to the point of causing death. In this study, we isolated bacteria from 14 inanimate surfaces that could potentially be reservoirs for the spread of bacterial infections in the medical university. Blood agar media was used for bacterial isolation. The bacterial colony that showed hemolytic activities on each surface was tested for antimicrobial susceptibility against eight different antibiotics. We found that MDR bacterium, namely TB1, which was isolated from a toilet bowl, was non-susceptible to ampicillin, imipenem, chloramphenicol, amoxicillin-clavulanic acid, gentamicin, and tetracycline. Another MDR bacterium isolated from the mobile phone screen of security officers, namely HSO, was resistant to chloramphenicol, gentamicin, tetracycline, and cefixime. An in vivo virulence test of bacterial isolates used Omphisa fuscidentalis larvae as an alternative to Galleria mellonella larvae for the infection model. A virulence test of TB1 in O. fuscidentalis larvae revealed 20% survival in the bacterial density of 104 and 105 CFU/larvae; and 0% survival in the bacterial density of 106 CFU/larvae at 24 h after injection. Bacterial identification was performed for TB1 as a potential virulent isolate. Bacterial identification using partial 16s rRNA gene showed that TB1 exhibited 99.84% identity to Escherichia fergusonii 2611. This study concludes that TB1 is a potentially virulent MDR E. fergusonii isolated from toilet bowls at a medical university.

Atopic Dermatitis (AD) is a chronic and relapsing skin disease. The medications for treating AD are still limited, most of them are topical corticosteroid creams or antibiotics. The current study attempted to discover potential AD treatments by integrating a gene network and genomic analytic approaches. Herein, the Single Nucleotide Polymorphism (SNPs) associated with AD were extracted from the GWAS catalog. We identified 70 AD-associated loci, and then 94 AD risk genes were found by extending to proximal SNPs based on r2 > 0.8 in Asian populations using HaploReg v4.1. Next, we prioritized the AD risk genes using in silico pipelines of bioinformatic analysis based on six functional annotations to identify biological AD risk genes. Finally, we expanded them according to the molecular interactions using the STRING database to find the drug target genes. Our analysis showed 27 biological AD risk genes, and they were mapped to 76 drug target genes. According to DrugBank and Therapeutic Target Database, 25 drug target genes overlapping with 53 drugs were identified. Importantly, dupilumab, which is approved for AD, was successfully identified in this bioinformatic analysis. Furthermore, ten drugs were found to be potentially useful for AD with clinical or preclinical evidence. In particular, we identified filgotinub and fedratinib, targeting gene JAK1, as potential drugs for AD. Furthermore, four monoclonal antibody drugs (lebrikizumab, tralokinumab, tocilizumab, and canakinumab) were successfully identified as promising for AD repurposing. In sum, the results showed the feasibility of gene networking and genomic information as a potential drug discovery resource.

The advancement of high-throughput sequencing and genomic analysis revealed that acute lymphoblastic leukemia (ALL) is a genetically heterogeneous disease. The abundance of such genetic data in ALL can also be utilized to identify potential targets for drug discovery and even drug repurposing. We aimed to determine potential genes for drug development and further guide the identification of candidate drugs repurposed for treating ALL through integrated genomic network analysis. Genetic variants associated with ALL were retrieved from the GWAS Catalog. We further applied a genomic-driven drug repurposing approach based on the six functional annotations to prioritize crucial biological ALL-related genes based on the scoring system. Lastly, we identified the potential drugs in which the mechanisms overlapped with the therapeutic targets and prioritized the candidate drugs using Connectivity Map (CMap) analysis. Forty-two genes were considered biological ALL-risk genes with ARID5B topping the list. Based on potentially druggable genes that we identified, palbociclib, sirolimus, and tacrolimus were under clinical trial for ALL. Additionally, chlorprothixene, sirolimus, dihydroergocristine, papaverine, and tamoxifen are the top five drug repositioning candidates for ALL according to the CMap score with dasatinib as a comparator. In conclusion, this study determines the practicability and the potential of integrated genomic network analysis in driving drug discovery in ALL.

Childhood asthma represents a heterogeneous disease resulting from the interaction between genetic factors and environmental exposures. Currently, finding reliable biomarkers is necessary for the clinical management of childhood asthma. However, only a few biomarkers are being used in clinical practice in the pediatric population. In the long run, new biomarkers for asthma in children are required and would help direct therapy approaches. This study aims to identify potential childhood asthma biomarkers using a genetic-driven biomarkers approach. Herein, childhood asthma-associated Single Nucleotide Polymorphisms (SNPs) were utilized from the GWAS database to drive and facilitate the biomarker of childhood asthma. We uncovered 466 childhood asthma-associated loci by extending to proximal SNPs based on r2 > 0.8 in Asian populations and utilizing HaploReg version 4.1 to determine 393 childhood asthma risk genes. Next, the functional roles of these genes were subsequently investigated using Gene Ontology (GO) term enrichment analysis, a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and a protein–protein interaction (PPI) network. MCODE and CytoHubba are two Cytoscape plugins utilized to find biomarker genes from functional networks created using childhood asthma risk genes. Intriguingly, 10 hub genes (IL6, IL4, IL2, IL13, PTPRC, IL5, IL33, TBX21, IL2RA, and STAT6) were successfully identified and may have been identified to play a potential role in the pathogenesis of childhood asthma. Among 10 hub genes, we strongly suggest IL6 and IL4 as prospective childhood asthma biomarkers since both of these biomarkers achieved a high systemic score in Cytohubba’s MCC algorithm. In summary, this study offers a valuable genetic-driven biomarker approach to facilitate the potential biomarkers for asthma in children.

From inadequate prior antidepressants that targeted monoamine neurotransmitter systems emerged the discovery of alternative drugs for depression. For instance, drugs targeted interleukin 6 receptor (IL6R) in inflammatory system. Genomic analysis-based drug repurposing using single nucleotide polymorphism (SNP) inclined a promising method for several diseases. However, none of the diseases was depression. Thus, we aimed to identify drug repurposing candidates for depression treatment by adopting a genomic-analysis-based approach. The 5885 SNPs obtained from the machine learning approach were annotated using HaploReg v4.1. Five sets of functional annotations were applied to determine the depression risk genes. The STRING database was used to expand the target genes and identify drug candidates from the DrugBank database. We validated the findings using the ClinicalTrial.gov and PubMed databases. Seven genes were observed to be strongly associated with depression (functional annotation score = 4). Interestingly, IL6R was auspicious as a target gene according to the validation outcome. We identified 20 drugs that were undergoing preclinical studies or clinical trials for depression. In addition, we identified sarilumab and satralizumab as drugs that exhibit strong potential for use in the treatment of depression. Our findings indicate that a genomic-analysis-based approach can facilitate the discovery of drugs that can be repurposed for treating depression.

Asthma is a common and heterogeneous disease characterized by chronic airway inflammation. Currently, the two main types of asthma medicines are inhaled corticosteroids and long-acting β2-adrenoceptor agonists (LABAs). In addition, biological drugs provide another therapeutic option, especially for patients with severe asthma. However, these drugs were less effective in preventing severe asthma exacerbation, and other drug options are still limited. Herein, we extracted asthma-associated single nucleotide polymorphisms (SNPs) from the genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) catalog and prioritized candidate genes through five functional annotations. Genes enriched in more than two categories were defined as “biological asthma risk genes.” Then, DrugBank was used to match target genes with FDA-approved medications and identify candidate drugs for asthma. We discovered 139 biological asthma risk genes and identified 64 drugs targeting 22 of these genes. Seven of them were approved for asthma, including reslizumab, mepolizumab, theophylline, dyphylline, aminophylline, oxtriphylline, and enprofylline. We also found 17 drugs with clinical or preclinical evidence in treating asthma. In addition, eleven of the 40 candidate drugs were further identified as promising asthma therapy. Noteworthy, IL6R is considered a target for asthma drug repurposing based on its high target scores. Through in silico drug repurposing approach, we identified sarilumab and satralizumab as the most promising drug for asthma treatment.

BACKGROUND: Increasing community awareness about the transmission and treatment of COVID-19 will stop the spread of the virus. Pharmacy students are the potential facilitator to give community education about COVID-19 treatment. The objective of this study is to evaluate the pharmacy students' knowledge of COVID-19 treatment, behavior, and attitude of providing the information about COVID-19 treatment. MATERIALS AND METHODS: We conducted cross-sectional study, recruiting 429 pharmacy students from three schools of pharmacy in Indonesia. The questionnaire about the knowledge of COVID-19 treatment, behavior, and attitude of providing the information on COVID-19 treatment met the validity and reliability criteria. We defined the proportion of knowledge, behavior, and attitude of the students using SPSS® version 22. RESULTS: Most of the students are in the earlier years (46.63%), female (84.15%), find the information about COVID-19 from many sources of media (85.08%) including scientific articles and know information about COVID-19 transmission around their life area (76.46%). The students' knowledge about antiviral and plasma convalescent is good (>70%), the positive behaviors are related to the COVID-19 treatment information regarding to the antiviral and the provision of Vitamin C (>50%), and the positive attitude are related to giving information about the use of avigan®, plasma convalescent, chloroquine, hydroxychloroquine, and immunomodulator (>50%). CONCLUSIONS: As a future pharmacist, the knowledge of pharmacy students about COVID-19 treatment needs to be improved since earlier years. Furthermore, using the good knowledge about COVID-19 treatment, the positive behavior and attitude of providing information of the students, the community behavior and attitude will be improved. The high year students have a tendency for the good knowledge and positive behavior and attitude of providing the information.

Hepatocellular carcinoma (HCC) often develops from chronic hepatitis B (CHB) through replication of hepatitis B virus (HBV) infection. Calcium (Ca2+) signaling plays an essential role in HBV replication. Store-operated calcium (SOC) channels are a major pathway of Ca2+ entry into non-excitable cells such as immune cells and cancer cells. The basic components of SOC signaling include the STIM1 and ORAI1 genes. However, the roles of STIM1 and ORAI1 in HBV-mediated HCC are still unclear. Thus, long-term follow-up of HBV cohort was carried out in this study. This study recruited 3631 patients with chronic hepatitis (345 patients with HCC, 3286 patients without HCC) in a Taiwanese population. Genetic variants of the STIM1 and ORAI1 genes were detected using an Axiom CHB1 genome-wide array. Clinical associations of 40 polymorphisms were analyzed. Three of the STIM1 single-nucleotide polymorphisms (SNPs) (rs6578418, rs7116520, and rs11030472) and one SNP of ORAI1 (rs6486795) showed a trend of being associated with HCC disease (p < 0.05). However, after correction for multiple testing, none of the SNPs reached a significant level (q > 0.05); in contrast, neither STIM1 nor ORAI1 showed a significant association with HCC progression in CHB patients. Functional studies by both total internal reflection fluorescence images and transwell migration assay indicated the critical roles of SOC-mediated signaling in HCC migration. In conclusion, we reported a weak correlation between STIM1/ORAI1 polymorphisms and the risk of HCC progression in CHB patients.

This preliminary study evaluated the biocompatibility of a novel degradable intravaginal plug contraceptive composed of PEG 4000 and chitosan in cats using haematological profiling and vaginal cytology. Five healthy, non-pregnant female cats were fully anaesthetised and fitted with an intravaginal plug (10 × 0.3 mm) using an applicator, following oestrogen administration 3 h prior. Blood samples were collected from the cephalic vein on days 0 (pre-insertion) and 3 and 7 (post-insertion). Vaginal cytology examinations were conducted on day 0 (pre- and post-oestrogen injection) and days 1, 3 and 7 post-insertion. Haematological parameters, including red blood cell count, haemoglobin levels, haematocrit values, total white blood cell count and differentiation, showed no significant changes after contraceptive insertion (p > 0.05). Vaginal cytology indicated an acute inflammatory response in one out of five subjects on day three post-insertion. The distribution of vaginal epithelial cells (parabasal, intermediate and superficial) remained unaffected by contraception. Oestrogen injection resulted in the dominance of superficial cells up to day 7 of observation (p < 0.05). Overall, PEG 4000 and chitosan-based intravaginal plug contraceptives demonstrated sufficient biocompatibility, indicating their potential as viable contraceptive options for feline use., (© 2024 Wiley‐VCH GmbH.)

Background: An intravaginal device (IVD) made from polyethylene plastic and copper wire, integrated with a radio frequency identification (RFID) chip, was developed as a biocompatible contraceptive and identity device for cats., Aim: This study evaluates the local and systemic biocompatibility of IVD in five non-pregnant female cats., Methods: The IVD was successfully inserted into the vaginal lumen after estrogen administration. Radiographic imaging confirmed the IVD's position, which lasted up to two days post-insertion., Results: Systemic response, assessed through hematological examinations on days 0, 1, and 3 post-insertion, showed no significant changes in erythrogram and leukogram parameters. Local response, evaluated through vulvar inspection and vaginal cytology on days 0, 1, 3, and 7, revealed no neutrophil infiltration in 4 out of 5 cats, indicating compatibility with vaginal tissue. Furthermore, epithelial cell profile changes were observed, showing an increase in superficial cells, which is typical during the estrus phase., Conclusion: These findings suggest that the IVD is biocompatible and suitable for use as a contraceptive and identity device in cats. However, further long-term studies are necessary to evaluate the device's prolonged efficacy and potential for contraception failure prevention by mating trials., Competing Interests: The authors have no conflicts of interest to declare.

Drug-resistant tuberculosis (TB), which results mainly from the selection of naturally resistant strains of Mycobacterium tuberculosis (MTB) due to mismanaged treatment, poses a severe challenge to the global control of TB. Therefore, screening novel and unique drug targets against this pathogen is urgently needed. The metabolic pathways of Homo sapiens and MTB were compared using the Kyoto Encyclopedia of Genes and Genomes tool, and further, the proteins that are involved in the metabolic pathways of MTB were subtracted and proceeded to protein-protein interaction network analysis, subcellular localization, drug ability testing, and gene ontology. The study aims to identify enzymes for the unique pathways for further screening to determine the feasibility of the therapeutic targets. The qualitative characteristics of 28 proteins identified as drug target candidates were studied. The results showed that 12 were cytoplasmic, 2 were extracellular, 12 were transmembrane, and 3 were unknown. Furthermore, druggability analysis revealed 14 druggable proteins, of which 12 were novel and responsible for MTB peptidoglycan and lysine biosynthesis. The novel targets obtained in this study are used to develop antimicrobial treatments against pathogenic bacteria. Future studies should further shed light on the clinical implementation to identify antimicrobial therapies against MTB., Competing Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)