Search

Amina Alam Kotha,1,* Shihab Uddin Ahmad,2,3,* Irin Dewan,2 Mohiuddin Ahmed Bhuiyan,2 Fahad Imtiaz Rahman,1 Isa Naina Mohamed,3 Md Selim Reza1 1Department of Pharmaceutical Technology, Faculty of Pharmacy, University of Dhaka, Dhaka, 1000, Bangladesh; 2Department of Pharmacy, School of Medicine, University of Asia Pacific, Dhaka, 1215, Bangladesh; 3Department of Pharmacology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Kuala Lumpur, 56000, Malaysia*These authors contributed equally to this workCorrespondence: Md Selim Reza, Department of Pharmaceutical Technology, Faculty of Pharmacy, University of Dhaka, Dhaka, 1000, Bangladesh, Email selimreza@du.ac.bd Isa Naina Mohamed, Department of Pharmacology, Faculty of Medicine, Universiti Kebangsaan Malaysia, Jalan Yaacob Latif, Bandar Tun Razak, Cheras, Kuala Lumpur, 56000, Malaysia, Email isanaina@ppukm.ukm.edu.myBackground: Metformin hydrochloride (HCl) microspheres and nanoparticles were formulated to enhance bioavailability and minimize side effects through sustained action and optimized drug-release characteristics. Initially, the same formulation design with different ratios of metformin HCl and Eudragit RSPO was used to formulate four batches of microspheres and nanoparticles using solvent evaporation and nanoprecipitation methods, respectively.Methods: The produced formulations were evaluated based on particle size and shape (particle size distribution (PSD), scanning electron microscope (SEM)), incompatibility (differential scanning calorimetry (DSC), Fourier-transform infrared (FTIR)), drug release pattern, permeation behavior, in vivo hypoglycemic effects, and in vitro anticancer potential.Results: Compatibility studies concluded that there was minimal interaction between metformin HCl and the polymer, whereas SEM images revealed smoother, more spherical nanoparticles than microspheres. Drug release from the formulations was primarily controlled by the non-Fickian diffusion process, except for A1 and A4 by Fickian, and B3 by Super case II. Korsmeyer-Peppas was the best-fit model for the maximum formulations. The best formulations of microspheres and nanoparticles, based on greater drug release, drug entrapment, and compatibility characteristics, were attributed to the study of drug permeation by non-everted intestinal sacs, in vivo anti-hyperglycemic activity, and in vitro anticancer activity.Conclusion: This study suggests that the proposed metformin HCl formulation can dramatically reduce hyperglycemic conditions and may also have anticancer potential.Keywords: microsphere, nanoparticles, permeability, anti-hyperglycemic, anticancer

The average life expectancy of the Bangladeshi population has risen over the last decade due to economic growth and improved medical care. Although the increased number of older adults and their health is a significant concern, there is scarce of data regarding that. A community-based cross-sectional study was conducted to analyze the association between nutritional status and functional ability among selected Bangladeshi geriatric populations living in their homes. Of 400 participants, the prevalence of malnutrition, and people at risk of malnutrition was 25.4% and 58.8%, respectively. Furthermore, almost 80% of participants are dependent in terms of activities of daily living. High risk of falling ( OR = 10.82; 95% CI: 5.85–20.37; p ≤ .001), limited activities of daily living (IADL) ( OR = 6.21; 95% CI: 4.02–9.58; p ≤ .001), along with dependency in performing IADL ( OR = 4.48; 95% CI: 2.83–7.06; p ≤ .001) are significantly associated with malnutrition. Geriatric malnutrition can accelerate disability conditions, leading to early functional aging.

Vascular endothelial growth factor receptor-2 (VEGFR2) plays a pivotal role in promoting angiogenesis and contributing to the growth and progression of renal cancer. Hence, the current investigation was undertaken with the aim of identifying safe and potent phytochemicals from Aeginetia indica whole plant extract (AiWE) that can efficiently suppress the overexpression of VEGFR2. HPLC analysis identified and quantified 11 polyphenols in considerable amounts in AiWE. All the compounds showed good binding energies with VEGFR2 in the molecular docking study, except catechin hydrate and rutin hydrate. However, among the polyphenols, myricetin exhibited an almost similar hydrogen bonding pattern with the active site of VEGFR2. The all-atom molecular dynamic simulation revealed that myricetin showed a very stable interaction with the active site of VEGFR2 throughout the simulation. Based on these results, it is suggested that myricetin may inhibit angiogenesis by suppressing the VEGFR2 signaling, thereby impeding the growth and progression of renal cancer., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2025 The Authors.)

Background: Perinatal mental disorders of women have an impact on their pregnancy and their child's brain development across low and middle-income countries. However, to address this issue, there are no specific guidelines for community-level service providers in Bangladesh. Therefore, we aimed to develop a community-based mental healthcare (CBMHC) service package and test its effectiveness in reducing depression, anxiety, and stress among mothers during the perinatal period., Methods: A cluster-randomized controlled trial (cRCT) was applied to test the CBMHC package in 2017 and 2018. It was provided to one group of mothers along with routine maternal care while another group received only routine maternal care. Paired sample t-test was applied to assess mean changes at baseline and endline in the Depression, Anxiety, and Stress Scales-21 (DASS-21) and EuroQol-5 Dimension and 3 Level (EQ5D3L) scales. A linear mixed-effects model was used to assess the relationship between the DASS-21 score and EQ5D3L., Results: 1215 participants were enrolled, including 605 in the intervention group and 610 in the control group. Measures of depression, anxiety, and stress were significantly decreased in both groups. Reduction in the levels of stress, as measured by changes in the stress score, were significantly greater in the intervention than in the control group (diff: 1.2, 95 % CI: 0.1, 2.2). The EQ5D3L index improved significantly, 0.02 units more at endline in the intervention group than in the control group (diff: 0.02, 95 % CI: 0.007, 0.03). The levels of mobility, usual activities, pain or discomfort, depression, and anxiety improved by 1.4 %, 7.6 %, 4.4 %, 2.6 %, and 0.4 % more, respectively, in the intervention group compared to the control groups. These improvements were statistically significant. The DASS-21 score was negatively and significantly correlated with both the EQ-5D3L index and the Visual Analogue Scale (VAS) score for the intervention group as well as for the usual care group, indicating that EQ5D3L improved when common mental disorders decreased., Conclusion: Although the improvements were modest, a CBMHC service package was effective in reducing perinatal levels of stress among Bangladeshi rural women., Trial Registration: ClinicalTrials.gov ID: NCT03678415., Competing Interests: Declaration of Competing Interest The authors declare there are no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The most frequent endocrine cancer of the head and neck is thyroid carcinoma (THCA). Although there is increasing evidence linking THCA to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. There is still much to learn about THCA's molecular roots and genetic biomarkers. Though drug therapies are the best choice after metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving them for a few years. Therefore, multi-targeted different variants of therapeutic drugs may be essential for effective treatment against THCA. To understand molecular mechanisms of THCA development and progression and explore multi-targeted different variants of therapeutic drugs, we detected 80 common differentially expressed genes (cDEGs) between THCA and non-THCA samples from six microarray gene expression datasets using the statistical LIMMA approach. Through protein-protein interaction (PPI) network analysis, we identified the top-ranked eight differentially expressed genes (TIMP1, FN1, THBS1, RUNX2, SHANK2, TOP2A, LRP2, and ACTN1) as the THCA-causing key genes (KGs), where 6 KGs (TIMP1, TOP2A, FN1, ACTN1, RUNX2, THBS1) are upregulated and 2 KGs (LRP2, SHANK2) are downregulated. The expression pattern analysis of KGs with the independent TCGA database by Box plots also confirmed their upregulated and downregulated patterns. The expression analysis of KGs in different stages of THCA development indicated that these KGs might be utilized as early diagnostic and prognostic biomarkers. The pan-cancer analysis of KGs indicated a substantial correlation of KGs with multiple cancers, including THCA. Some transcription factors (TFs) and microRNAs were detected as the key transcriptional and post-transcriptional regulators of KGs using gene regulatory network (GRN) analysis. The enrichment analysis of the cDEGs revealed several key molecular functions, biological processes, cellular components, and pathways significantly associated with THCA. These findings highlight critical mechanisms influenced by the identified key genes (KGs), providing deeper insight into their roles in THCA development. Then we detected 6 repurposable drug molecules (Entrectinib, Imatinib, Ponatinib, Sorafenib, Retevmo, and Pazopanib) by molecular docking with KGs-mediated receptor proteins, ADME/T analysis, and cross-validation with the independent receptors. Therefore, these findings might be useful resources for wet lab researchers and clinicians to consider an effective treatment strategy against THCA., Competing Interests: Declaration of Competing Interest We can confirm that the work entitled “Gene-Expression Profile Analysis to Disclose Diagnostics and Therapeutics Biomarkers for Thyroid Carcinoma” is an original work and neither this nor any similar manuscript, in whole or in part, is under consideration, in a press, published, or reported elsewhere. All co-authors have seen and agreed with the contents of the manuscript. We would like to declare that we have no any conflict of interest for this work. Anyone can use any information from our manuscript., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The study looks into how Sr 3 PBr 3 and Sr 3 NCl 3 double perovskite materials can be used as absorbers in perovskite solar cells (PSCs). Computational Sr 3 PBr 3 and Sr 3 NCl 3 simulations were employed to assess the performance of each absorber together with electron transport layers (ETL), with a particular emphasis on optimizing ETL thickness to improve charge transport and synchronize current outputs. The simulations yielded valuable insights into the electronic and optical characteristics of the individual absorbers. Subsequently, a tandem simulation was performed to adjust each layer's thickness, ensuring that both devices' current outputs were aligned for maximum system efficiency. The findings revealed that the tandem configuration of Sr 3 PBr 3 and Sr 3 NCl 3 surpassed the performance of the individual absorber setups, attributed to the optimized ETL thicknesses that enhanced charge transport and facilitated effective current matching. This study makes a significant contribution to the design and optimization of tandem PSCs utilizing Sr 3 PBr 3 and Sr 3 NCl 3 absorbers, paving the way for improved overall device efficiency. We investigated three device configurations to find the optimum structure. FTO/SnS 2 /Sr 3 PBr 3 /Ni, FTO/SnS 2 /Sr 3 NCl 3 /Ni, and FTO/SnS 2 /Sr 3 PBr 3 /Sr 3 NCl 3 /Ni are considered as Device-I, II, and III. In Device-I, the execution parameters are power conversion efficiency (PCE) of 24.26%, an open-circuit voltage ( V OC ) of 1.23 V, a short-circuit current density ( J SC ) of 24.65 mA cm -2 , and a fill factor (FF) of 87.42%. For Device-II, PCE, FF, V OC , and J SC are correspondingly 20.35%, 87.91%, 1.28 V, and 18.07 mA cm -2 . The further refined tandem configuration achieved a PCE of 30.32%, with a V OC of 1.27 V, an FF of 90.14%, and a J SC of 26.44 mA cm -2 , demonstrating the potential of this methodology in enhancing PSC performance., Competing Interests: The authors have no conflicts of interest., (This journal is © The Royal Society of Chemistry.)

This research aims to isolate, characterize, and analyze pure compounds from Leea macrophylla leaf extract to investigate its antibacterial, antidiabetic, cytotoxic, and phytotoxic effects. Fresh leaves were collected, dried, and subjected to methanol extraction to obtain a crude extract. From the petroleum ether fraction (PEF) of this extract, three fractions-designated LM1, LM2, and LM3-were prepared using column chromatography. The fractions were tried to be characterized in search for single compound by instrumental technique like ATR-FTIR, 1 H NMR and 13 C NMR but the 1 H NMR and 13 C NMR spectra were found complex which were difficult to interpret. To dispel the doubt and get clear idea about the structure, GC-MS analysis of the compounds was carried out whose result showed that all the three extracts were decomposed to several small organic compounds that made the structure elucidation difficult. For this complication, the characterization of the extracts was not possible. Numerous compounds were identified in the methanol extract of L. through GC-MS analysis. Among these compounds, Benzene, 1,2,3-trimethyl- and Undecane were found in higher percentages in LM1. LM2 contained Azulene and Bicyclo [4.4.1]undeca-1,3,5,7,9-pentaene, while LM3 was characterized by the presence of 9,9-Dimethoxybicyclo [3.3.1]nona-2,4-dione and 11-(2-Cyclopenten-1-yl)undecanoic acid, among others. The antibacterial activity of these fractions was evaluated against various bacterial strains, demonstrating broad-spectrum effectiveness. LM1 fraction showed the highest antibacterial activity against macrophylla through GC-MS analysis. Among these compounds, Benzene, 1,2,3-trimethyl- and Undecane were found in higher percentages in LM1. LM2 contained Azulene and Bicyclo [4.4.1]undeca-1,3,5,7,9-pentaene, while LM3 was characterized by the presence of 9,9-Dimethoxybicyclo [3.3.1]nona-2,4-dione and 11-(2-Cyclopenten-1-yl)undecanoic acid, among others. The antibacterial activity of these fractions was evaluated against various bacterial strains, demonstrating broad-spectrum effectiveness. LM1 fraction showed the highest antibacterial activity against Proteus sp. With zone of inhibition 25 mm and weak activity against S. sonnei with zone of inhibition 5 mm. LM2 showed the highest activity to both E. cocci and P. aeruginosa with the zone of inhibition of 18 mm and comparatively lower but significant against Proteus sp. LM3 was highly active to S. sonnei with zone of inhibition 20 mm and lower but quite significant against Proteus sp. Moreover, the anti-diabetic potential was assessed, with LM1 showing the strongest α-amylase inhibitory activity, outperforming quercetin (standard). The IC50 values of LM1, LM2, LM3, and quercetin were 57.36 μg/mL, 100.66 μg/mL, 164.92 μg/mL, and 97.45 μg/mL, respectively. In addition, cytotoxicity was assessed using a brine shrimp lethality bioassay, and phytotoxicity was evaluated through seed germination and growth assays. The results suggest that L. macrophylla leaf extracts have potential applications in antimicrobial, antidiabetic, and anti-cancer contexts. This comprehensive study bridges gaps in knowledge surrounding L. macrophylla's multifaceted properties, offering insights into its therapeutic and ecological potential for healthcare and environmental management., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 The Authors.)

Understanding the impacts of, and options for, controlling invasive species is crucial to their management. Wetlands are a widely invaded ecosystem, since dispersal of aquatic species is facilitated by seasonal flooding. This study evaluated the effects of the translocated pondweed Monochoria hastata on fish and rice production in two wetlands of Bangladesh over six years (2017-2022). Fish and rice production were compared between control (negligible M. hastata) and three treatments under different M. hastata management methods comprising manual-, herbicide- and mechanical-treatment. Density of M. hastata increased significantly in all treatment groups over time in both wet and dry seasons. However, M. hastata density was lower by 270% in the dry season than the wet season. For fishes, a negative relationship between M. hastata density and fish production was recorded for snakeheads and catfishes, the most saleable fishes, whereas a mixed pattern was recorded for barbs and minnows across treatments. A positive relationship occurred between the density of M. hastata and production of the most common fish, mud eel, and therefore, the overall fish production increased in all treatment groups. Compared to control plots, rice production was lower in M. hastata infested plot groups. Among the M. hastata infested plot groups, rice production in herbicide-and mechanical-treatment groups was similar but lower than the manual-treatment group. Although manual-treatment plots yielded greater rice production, the weed management cost was also higher. This study provides evidence that translocated M. hastata can be of an invasive nature and impact rice production, not only by reducing yield but also by increasing the production costs through additional management for M. hastata control. Its presence in wetlands in Bangladesh can increase overall fish production due to the overriding influence of increased mud eel yield which has little demand locally but can decrease the species of high demand (e.g. snakehead and catfish). None of the existing control measures are effective in controlling M. hastata. Further research is needed on better management approaches for both agricultural and fish production in areas invaded by M. hastata., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Food contamination by heavy metals is a concerning issue worldwide. The presence of elevated levels of heavy metals in commonly consumed rice has emerged as a critical issue in ensuring food safety. This research encompassed the collection of 44 rice samples, representing seven distinct varieties, through a randomized sampling approach across various retail markets within Dhaka city. The investigation of heavy metal content (including Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Cd, Hg, and Pb) within the rice samples was carried out employing Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The findings disclosed substantial disparities in heavy metal concentrations among the different rice varieties. Notably, the concentrations of Cr (0.99 mg/kg), Fe (8.35 mg/kg), Pb (0.49 mg/kg), and Co (0.02 mg/kg) were observed to exceed the established maximum permissible limits. This contamination of the rice varieties may stem from either natural processes or human activities. Utilizing these metal concentrations, this study employed Monte-Carlo simulation to calculate health risk and probabilistic health risk. The Target Hazard Quotients (THQs) for Cr, Fe, and As exceeded the threshold of 1 in each rice variety, particularly in Amon and Lal Biroi in Mymensingh, Najirshail in Bogra, 28 in Sherpur and Kushtia, Miniket in Bogra and Rajshahi, and lastly, paijam in Rangpur and Tangail. Furthermore, the Hazard Index (HI) exceeded 1 in all rice varieties, implying that the consumption of these selected rice grains may have a substantial impact on overall food quality and its potential health consequences. Both carcinogenic risk and probabilistic risk for As, Ni, Cd, Cr, and Pb were found to surpass the threshold levels and safe limits, respectively. This suggests that individuals who have regularly consumed these rice varieties may face a heightened probability of developing cancer in the future, as predicted. According to sensitivity analysis, metal concentration and food ingestion rate (FIR) are the most relevant components that contribute to the significant impact of carcinogenic health hazards. Finally, the study concluded that heavy metal intake from food poses a risk to human health, necessitating the effective monitoring based on each geographic location and identify the source of this heavy metal to limit its exposure., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of kidney cancer. Although there is increasing evidence linking ccRCC to genetic alterations, the exact molecular mechanism behind this relationship is not yet completely known to the researchers. Though drug therapies are the best choice after the metastasis, unfortunately, the majority of the patients progressively develop resistance against the therapeutic drugs after receiving it for almost 2 years. In this case, multi-targeted different variants of therapeutic drugs are essential for effective treatment against ccRCC. To understand molecular mechanisms of ccRCC development and progression, and explore multi-targeted different variants of therapeutic drugs, it is essential to identify ccRCC-causing key genes (KGs). In order to obtain ccRCC-causing KGs, at first, we detected 133 common differentially expressed genes (cDEGs) between ccRCC and control samples based on nine (9) microarray gene-expression datasets with NCBI accession IDs GSE16441, GSE53757, GSE66270, GSE66272, GSE16449, GSE76351, GSE66271, GSE71963, and GSE36895. Then, we filtered these cDEGs through survival analysis with the independent TCGA and GTEx database and obtained 54 scDEGs having significant prognostic power. Next, we used protein-protein interaction (PPI) network analysis with the reduced set of 54 scDEGs to identify ccRCC-causing top-ranked eight KGs (PLG, ENO2, ALDOB, UMOD, ALDH6A1, SLC12A3, SLC12A1, SERPINA5). The pan-cancer analysis with KGs based on TCGA database showed the significant association with different subtypes of kidney cancers including ccRCC. The gene regulatory network (GRN) analysis revealed some crucial transcriptional and post-transcriptional regulators of KGs. The scDEGs-set enrichment analysis significantly identified some crucial ccRCC-causing molecular functions, biological processes, cellular components, and pathways that are linked to the KGs. The results of DNA methylation study indicated the hypomethylation and hyper-methylation of KGs, which may lead the development of ccRCC. The immune infiltrating cell types (CD8+ T and CD4+ T cell, B cell, neutrophil, dendritic cell and macrophage) analysis with KGs indicated their significant association in ccRCC, where KGs are positively correlated with CD4+ T cells, but negatively correlated with the majority of other immune cells, which is supported by the literature review also. Then we detected 10 repurposable drug molecules (Irinotecan, Imatinib, Telaglenastat, Olaparib, RG-4733, Sorafenib, Sitravatinib, Cabozantinib, Abemaciclib, and Dovitinib.) by molecular docking with KGs-mediated receptor proteins. Their ADME/T analysis and cross-validation with the independent receptors, also supported their potent against ccRCC. Therefore, these outputs might be useful inputs/resources to the wet-lab researchers and clinicians for considering an effective treatment strategy against ccRCC., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ajadee et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Objectives: Hypertension is one of the major modifiable risk factors for cardiovascular mortality and morbidity throughout the world. Increased life expectancy leads to increase prevalence of non-communicable diseases among the elderly people including Bangladesh. However, different studies reported high prevalence of uncontrolled hypertension ranging from 52.6% to 67.9% among the elderly people in different countries. With this view, we aimed to assess the frequency of uncontrolled blood pressure (BP) among the elderly hypertensive people and its associated risk factors and treatment pattern in Bangladesh., Methodology: This cross-sectional type of observational study recruited 246 eligible hypertensive elderly patients attending in 250 Bedded General Hospital, Jashore, Bangladesh dated from 1st July to 31st December 2022. A structured questionnaire was developed and data on associated risk factors, treatment pattern and current blood pressure (BP) measurement were collected by face-to-face interview for the purposive sampling technique., Results: The mean age of our study patients was 72 ± 7 years with a male and female ratio nearly 1:1. Of the total hypertensive patients aged over 65 years or more, 56.5% remained with uncontrolled hypertension even on their prescribed antihypertensive medications. The mean systolic (SBP) and diastolic (DBP) blood pressure were significantly high ( P  < 0.001) as 167 ± 22 mm Hg and 95 ± 11 mm Hg, respectively, among the uncontrolled hypertensive patients. However, we noticed the mean SBP and DBP among the total hypertensive patients were also significantly high ( P  < 0.001) as 148 ± 27 mm Hg and 87 ± 13 mm Hg, respectively. In this study, we reported that the mean number of last prescribed antihypertensive medications used by the total patients was 2 ± 1 ( P =0.224) which was similar among the controlled and uncontrolled hypertensive patient groups. Among the elderly hypertensive patients, the most commonly prescribed antihypertensive medications were Amlodipine 39.8% ( P =0.006), Olmesartan 29.3% ( P  = 0.186), Losartan 24.4% ( P  = 0.127), Bisoprolol 15.0% ( P  = 0.266) and Atenolol 14.6% ( P  = 0.224)., Conclusion: We noticed high frequency of uncontrolled blood pressure among the elderly hypertensive patients, despite of using multiple antihypertensive medications in Jashore, Bangladesh., Competing Interests: There are no conflicts of interest of any author., (© 2024 The Author(s). Aging Medicine published by Beijing Hospital and John Wiley & Sons Australia, Ltd.)

Type 2 diabetes (T2D) and Clear-cell renal cell carcinoma (ccRCC) are both complicated diseases which incidence rates gradually increasing. Population based studies show that severity of ccRCC might be associated with T2D. However, so far, no researcher yet investigated about the molecular mechanisms of their association. This study explored T2D and ccRCC causing shared key genes (sKGs) from multiple transcriptomics profiles to investigate their common pathogenetic processes and associated drug molecules. We identified 259 shared differentially expressed genes (sDEGs) that can separate both T2D and ccRCC patients from control samples. Local correlation analysis based on the expressions of sDEGs indicated significant association between T2D and ccRCC. Then ten sDEGs (CDC42, SCARB1, GOT2, CXCL8, FN1, IL1B, JUN, TLR2, TLR4, and VIM) were selected as the sKGs through the protein-protein interaction (PPI) network analysis. These sKGs were found significantly associated with different CpG sites of DNA methylation that might be the cause of ccRCC. The sKGs-set enrichment analysis with Gene Ontology (GO) terms and KEGG pathways revealed some crucial shared molecular functions, biological process, cellular components and KEGG pathways that might be associated with development of both T2D and ccRCC. The regulatory network analysis of sKGs identified six post-transcriptional regulators (hsa-mir-93-5p, hsa-mir-203a-3p, hsa-mir-204-5p, hsa-mir-335-5p, hsa-mir-26b-5p, and hsa-mir-1-3p) and five transcriptional regulators (YY1, FOXL1, FOXC1, NR2F1 and GATA2) of sKGs. Finally, sKGs-guided top-ranked three repurposable drug molecules (Digoxin, Imatinib, and Dovitinib) were recommended as the common treatment for both T2D and ccRCC by molecular docking and ADME/T analysis. Therefore, the results of this study may be useful for diagnosis and therapies of ccRCC patients who are also suffering from T2D., (© 2024. The Author(s).)

Objective: Electroencephalography (EEG) has evolved into an indispensable instrument for estimating cognitive workload in various domains. ML and DL techniques have been increasingly employed to develop accurate workload estimation and classification models based on EEG data. The goal of this systematic review is to compile the body of research on EEG workload estimation and classification using ML and DL approaches., Methods: The PRISMA procedures were followed in conducting the review, searches were conducted through databases at SpringerLink, ACM Digital Library, IEEE Explore, PUBMED, and Science Direct from the beginning to the end of February 16, 2024. Studies were selected based on predefined inclusion criteria. Data were extracted to capture study design, participant demographics, EEG features, ML/DL algorithms, and reported performance metrics., Results: Out of the 125 items that emerged, 33 scientific papers were fully evaluated. The study designs, participant demographics, and EEG workload measurement and categorization techniques used in the investigations differed. SVM, CNN, and hybrid networks are examples of ML and DL approaches that were often used. Analyzing the accuracy scores achieved by different ML/DL models. Furthermore, a relationship was noted between sample frequency and model accuracy, with higher sample frequencies generally leading to improved performance. The percentage distribution of ML/DL methods revealed that SVMs, CNNs, and RNNs were the most commonly utilized techniques, reflecting their robustness in handling EEG data., Significance: The comprehensive review emphasizes how ML may be used to identify mental workload across a variety of disciplines using EEG data. Optimizing practical applications requires multimodal data integration, standardization efforts, and real-world validation studies. These systems will also be further improved by addressing ethical issues and investigating new EEG properties, which will improve human-computer interaction and performance assessment., (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Affinity-based electrochemical (AEC) biosensors have gained more attention in the field of point-of-care management. However, AEC sensing is hampered by biofouling of the electrode surface and degradation of the antifouling material. Therefore, a breakthrough in antifouling nanomaterials is crucial for the fabrication of reliable AEC biosensors. Herein, for the first time, we propose 1-pyrenebutyric acid-functionalized MXene to develop an antifouling nanocomposite to resist biofouling in the immunosensors. The nanocomposite consisted of a 3D porous network of bovine serum albumin cross-linked with glutaraldehyde with functionalized MXene as conductive nanofillers, where the inherited oxidation resistance property of functionalized MXene improved the electrochemical lifetime of the nanocomposite. On the other hand, the size-extruded porous structure of the nanocomposite inhibited the biofouling activity on the electrode surface for up to 90 days in real samples. As a proof of concept, the antifouling nanocomposite was utilized to fabricate a multiplexed immunosensor for the detection of C-reactive protein (CRP) and ferritin biomarkers. The fabricated sensor showed good selectivity over time and an excellent limit of detection for CRP and ferritin of 6.2 and 4.2 pg/mL, respectively. This research successfully demonstrated that functionalized MXene-based antifouling nanocomposites have great potential to develop high-performance and low-cost immunosensors.

For the first time, different pollution indices and a receptor model have been used to quantify eco-environmental and health risk assessments as well as identify the sources of potentially toxic elements in soil along the Barapukuria Coal Mine (BCM). Individual indices include enrichment and contamination factors showing the soil samples are moderately to highly contaminated by arsenic, cobalt, chromium, copper, lead, and zinc and heavily contaminated by sulfur. According to the geo-accumulation index, there is significant pollution with arsenic (1.24 ± 0.38), lead (1.49 ± 0.58), cobalt (1.49 ± 0.58), and sulfur (1.63 ± 0.38). Modified hazard quotient and ecological risk factor values also suggest low to moderate environmental risk hazards from the same elements. The nemerow pollution index, pollution load index, nemerow risk index, ecological risk index, and toxic risk index of soil range from 1.65 to 3.03, 0.82-1.23, 11-26, 77-165, and 6.82-11.76 suggest low toxic risk and moderate pollution, among other synergistic indices. Health risk assessment indicates that iron poses lower cancer risk for children than adults, while both face unacceptable cancer risks from inhaling chromium, cobalt, or arsenic. Principal component and phylogenetic cluster analysis extracted by the multiple linear regression with the absolute principal component score (APCS-MLR) model refer to the fact that manganese, iron, titanium, and nickel have originated from geogenic sources, while coal mine effluents enrich elements like arsenic, chromium, zinc, lead, uranium, sulfur, thorium, and zinc and phosphorous sourced from agriculture. In addition, geogenic and anthropogenic sources, including mine and agriculture activities, could potentially pollute the soil and ecosystem. The findings are crucial for regional and national planners in devising strategies to mitigate potentially toxic element pollution in soil along coal mine areas., Competing Interests: We declare that this manuscript is original, has not been published before, and is not currently being considered for publication elsewhere. We know of no conflict of interest associated with this publication, and there has been no significant financial support for this work that could have influenced the outcome. As corresponding authors, we confirm that the manuscript has been read and approved by all the names of the authors., (© 2024 The Authors.)

In the era of precision medicine, accurate disease phenotype prediction for heterogeneous diseases, such as cancer, is emerging due to advanced technologies that link genotypes and phenotypes. However, it is difficult to integrate different types of biological data because they are so varied. In this study, we focused on predicting the traits of a blood cancer called Acute Myeloid Leukemia (AML) by combining different kinds of biological data. We used a recently developed method called Omics Generative Adversarial Network (GAN) to better classify cancer outcomes. The primary advantages of a GAN include its ability to create synthetic data that is nearly indistinguishable from real data, its high flexibility, and its wide range of applications, including multi-omics data analysis. In addition, the GAN was effective at combining two types of biological data. We created synthetic datasets for gene activity and DNA methylation. Our method was more accurate in predicting disease traits than using the original data alone. The experimental results provided evidence that the creation of synthetic data through interacting multi-omics data analysis using GANs improves the overall prediction quality. Furthermore, we identified the top-ranked significant genes through statistical methods and pinpointed potential candidate drug agents through in-silico studies. The proposed drugs, also supported by other independent studies, might play a crucial role in the treatment of AML cancer. The code is available on GitHub; https://github.com/SabrinAfroz/omicsGAN&#95;codes?fbclid=IwAR1-/stuffmlE0hyWgSu2wlXo6dYlKUei3faLdlvpxTOOUPVlmYCloXf4Uk9ejK4I., Competing Interests: Declaration of Competing Interest We declare no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths globally. To reduce HCC-related mortality, early diagnosis and therapeutic improvement are essential. Hub differentially expressed genes (HubGs) may serve as potential diagnostic and prognostic biomarkers, also offering therapeutic targets for precise therapies. Therefore, we aimed to identify top-ranked hub genes for the diagnosis, prognosis, and therapy of HCC., Methods: Through a systematic literature review, 202 HCC-related HubGs were derived from 59 studies, yet consistent detection across these was lacking. Then, we identified top-ranked HubGs (tHubGs) by integrated bioinformatics analysis, highlighting their functions, pathways, and regulators that might be more representative of the diagnosis, prognosis, and therapies of HCC., Results: In this study, eight HubGs (CDK1, AURKA, CDC20, CCNB2, TOP2A, PLK1, BUB1B, and BIRC5) were identified as the tHubGs through the protein-protein interaction (PPI) network and survival analysis. Their differential expression in different stages of HCC, validated using The Cancer Genome Atlas (TCGA) Program database, suggests their potential as early HCC markers. The enrichment analyses revealed some important roles in HCC-related biological processes (BPs), molecular functions (MFs), cellular components (CCs), and signaling pathways. Moreover, the gene regulatory network analysis highlighted key transcription factors (TFs) and microRNAs (miRNAs) that regulate these tHubGs at transcriptional and post-transcriptional. Finally, we selected three drugs (CD437, avrainvillamide, and LRRK2-IN-1) as candidate drugs for HCC treatment as they showed strong binding with all of our proposed and published protein receptors., Conclusions: The findings of this study may provide valuable resources for early diagnosis, prognosis, and therapies for HCC.

Inorganic cubic rubidium-lead-halide perovskites have attracted considerable attention owing to their structural, electronic, and unique optical properties. In this study, novel rubidium-lead-bromide (RbPbBr 3 )-based hybrid perovskite solar cells (HPSCs) with several high-band-gap chalcogenide electron transport layers (ETLs) of In 2 S 3 , WS 2 , and SnS 2 were studied by density functional theory (DFT) and using the SCAPS-1D simulator. Initially, the band gap and optical performance were computed using DFT, and these results were utilized for the first time in the SCAPS-1D simulator. Furthermore, the impact of different major influencing parameters, that is, the thickness of the layer, bulk defect density, doping concentration, and defect density of interfaces, including the working temperature, were also investigated and unveiled. Further, a study on an optimized device with the most potential ETL (SnS 2 ) layer was performed systematically. Finally, a comparative study of different reported heterostructures was performed to explore the benchmark of the most recent efficient RbPbBr 3 -based photovoltaics. The highest power conversion efficiency (PCE) was 29.75% for the SnS 2 ETL with V oc of 0.9789 V, J sc of 34.57863 mA cm -2 , and fill factor (FF) of 87.91%, while the PCEs of 21.15 and 24.57% were obtained for In 2 S 3 and WS 2 ETLs, respectively. The electron-hole generation, recombination rates, and quantum efficiency (QE) characteristics were also investigated in detail. Thus, the SnS 2 ETL shows strong potential for use in RbPbBr 3 -based hybrid perovskite high-performance photovoltaic devices., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Despite substantial developments in minimally invasive lactate monitoring microneedle electrodes, most such electrode developments have focused on either sensitivity or invasiveness while ignoring a wide range of detection, which is the most important factor in measuring the normal range of lactate in interstitial fluid (ISF). Herein, we present a polymer-based planar microneedle electrode fabrication using microelectromechanical and femtosecond laser technology for the continuous monitoring of lactate in ISF. The microneedle is functionalized with two-dimensional reduced graphene oxide (rGO) and electrochemically synthesized platinum nanoparticles (PtNPs). A particular quantity of Nafion (1.25 wt%) is applied on top of the lactate enzyme to create a diffusion-controlled membrane. Due to the combined effects of the planar structure of the microneedle, rGO, and membrane, the biosensor exhibited excellent linearity up to 10 mM lactate with a limit of detection of 2.04 μM, high sensitivity of 43.96 μA mM -1 cm -2 , a reaction time of 8 s and outstanding stability, selectivity, and repeatability. The feasibility of the microneedle is evaluated by using it to measure lactate concentrations in artificial ISF and human serum. The results demonstrate that the microneedle described here has great potential for use in real-time lactate monitoring for use in sports medicine and treatment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Non-communicable diseases, such as cardiovascular disease, cancer, chronic respiratory diseases, and diabetes, are responsible for approximately 71% of all deaths worldwide. Stroke, a cerebrovascular disorder, is one of the leading contributors to this burden among the top three causes of death. Early recognition of symptoms can encourage a balanced lifestyle and provide essential information for stroke prediction. To identify a stroke patient and risk factors, machine learning (ML) is a key tool for physicians. Due to different data measurement scales and their probability distributional assumptions, ML-based algorithms struggle to detect risk factors. Furthermore, when dealing with risk factors with high-dimensional features, learning algorithms struggle with complexity. In this study, rigorous statistical tests are used to identify risk factors, and PCA-FA (Integration of Principal Components and Factors) and FPCA (Factor Based PCA) approaches are proposed for projecting suitable feature representations for improving learning algorithm performances. The study dataset consists of different clinical, lifestyle, and genetic attributes, allowing for a comprehensive analysis of potential risk factors associated with stroke, which contains 5110 patient records. Using significant test ( P -value <0.05), chi-square and independent sample t -test identified age, heart&#95;disease, hypertension, work&#95;type, ever&#95;married, bmi, and smoking&#95;status as risk factors for stroke. To develop the predicting model with proposed feature extraction techniques, random forests approach provides the best results when utilizing the PCA-FA method. The best accuracy rate for this approach is 92.55%, while the AUC score is 98.15%. The prediction accuracy has increased from 2.19% to 19.03% compared to the existing work. Additionally, the prediction results is robustified and reproducible with a stacking ensemble-based classification algorithm. We also developed a web-based application to help doctors diagnose stroke risk based on the findings of this study, which could be used as an additional tool to help doctors diagnose., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Diabetes mellitus, a chronic metabolic disorder, continues to be a major public health issue around the world. It is estimated that one in every two diabetics is undiagnosed. Early diagnosis and management of diabetes can also prevent or delay the onset of complications. With the help of a variety of machine learning and deep learning models, stacking algorithms, and other techniques, our study's goal is to detect diseases early. In this study, we propose two stacking-based models for diabetes disease classification using a combination of the PIMA Indian diabetes dataset, simulated data, and additional data collected from a local healthcare facility. We use both the classical and deep neural network stacking ensemble methods to combine the predictions of multiple classification models and improve classification accuracy and robustness. In the evaluation protocol, we used both the train-test and cross-validation (CV) techniques to validate our proposed model. The highest accuracy is obtained by stacking ensemble with three NN architectures, resulting in an accuracy of 95.50 %, precision of 94 %, recall of 97 %, and f1-score of 96 % using 5-fold CV on simulation study. The stacked accuracy obtained from ML algorithms for the Pima Indian Diabetes dataset is 75.03 % using the train-test split protocol, while the accuracy obtained from the CV protocol is 77.10 % on the stacked model. The range of performance scores that outperformed the CV protocol 2.23 %-12 %. Our proposed method achieves a high accuracy range from 92 % to 95 %, precision, recall, and F1-score ranges from 88 % to 96 % using classical and deep neural network (NN)-based stacking method on the primary dataset. The proposed dataset and ensemble method could be useful in the early detection and treatment of diabetes, as well as in the advancement of machine learning and data analysis techniques in the healthcare industry., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

In recent times, high-performance wearable electronic devices that can transform mechanical force into electrical energy for biomedical monitoring applications are receiving an increasing amount of attention. In the present study, we focused on a flexible, self-powered and wearable triboelectric nanogenerator (TENG) based on electrospun polyvinylidene fluoride (PVDF)/aromatic hyperbranched polyester of 4th generation (Ar.HBP-G4, 0-40 wt.-% w.r.t. PVDF content) blend nanoweb as tribo-negative layer and melt-blown thermoplastic polyurethane (TPU) as tribo-positive layer for energy harvesting and human health monitoring applications. Among the varying Ar.HBP-G4 content used, incorporation of Ar.HBP-G4 (10 wt.-%) in PVDF (P-Ar.HBP-G4-10) showed higher increase in the triboelectric output voltage when compared to pristine PVDF and other Ar.HBP-G4 weight ratios. The optimized P-Ar.HBP-G4-10/TPU based TENG exhibited a peak-to-peak voltage (V p-p ) of 124.4 V under an applied load of 9.8 N and frequency 1 Hz which is superior to many other TENGs reported elsewhere. Higher triboelectric performance of P-Ar.HBP-G4 blend based TENG compared to that of neat PVDF is attributed to the effect of Ar.HBP-G4-10 in enhancing the degree of crystallinity and polar β-crystalline phase content (98.3%) in PVDF. The ability of the TENG to power up portable electronic devices is demonstrated when it is powered for 750 s while connected through a capacitor and a rectifier, and the TENG was able to operate 45 light-emitting diodes directly. Evaluation of the triboelectric output of the TENG device attached to different parts of the human body reveal significantly better output voltage and sensitivity for human health monitoring. The results of this work pave a new way to develop TENG based on P-Ar.HBP-G4 nanowebs for sustainable energy generation and wearable healthcare monitoring systems., (© 2023. The Author(s).)

The most frequently prescribed first-line treatment for type II diabetes mellitus is metformin. Recent reports asserted that this diabetes medication can also shield users from cancer. Metformin induces cell cycle arrest in cancer cells. However, the exact mechanism by which this occurs in the cancer system is yet to be elucidated. Here, we investigated the impact of metformin on cell cycle arrest in cancer cells utilizing transforming growth factor (TGF)-beta pathway. TGF-ß pathway has significant effect on cell progression and growth. In order to gain an insight on the underlying molecular mechanism of metformin's effect on TGF beta receptor 1 kinase, molecular docking was performed. Metformin was predicted to interact with transforming growth factor (TGF)-beta receptor I kinase based on molecular docking and molecular dynamics simulations. Furthermore, pharmacophore was generated for metformin-TGF-ßR1 complex to hunt for novel compounds having similar pharmacophore as metformin with enhanced anti-cancer potentials. Virtual screening with 29,000 natural compounds from NPASS database was conducted separately for the generated pharmacophores in Ligandscout® software. Pharmacophore mapping showed 60 lead compounds for metformin-TGF-ßR1 complex. Molecular docking, molecular dynamics simulation for 100 ns and ADMET analysis were performed on these compounds. Compounds with CID 72473, 10316977 and 45140078 showed promising binding affinities and formed stable complexes during dynamics simulation with aforementioned protein and thus have potentiality to be developed into anti-cancer medicaments., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Reza et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Strontium antimony iodide (Sr 3 SbI 3 ) is one of the emerging absorbers materials owing to its intriguing structural, electronic, and optical properties for efficient and cost-effective solar cell applications. A comprehensive investigation on the structural, optical, and electronic characterization of Sr 3 SbI 3 and its subsequent applications in heterostructure solar cells have been studied theoretically. Initially, the optoelectronic parameters of the novel Sr 3 SbI 3 absorber, and the possible electron transport layer (ETL) of tin sulfide (SnS 2 ), zinc sulfide (ZnS), and indium sulfide (In 2 S 3 ) including various interface layers were obtained by DFT study. Afterward, the photovoltaic (PV) performance of Sr 3 SbI 3 absorber-based cell structures with SnS 2 , ZnS, and In 2 S 3 as ETLs were systematically investigated at varying layer thickness, defect density bulk, doping density, interface density of active materials including working temperature, and thereby, optimized PV parameters were achieved using SCAPS-1D simulator. Additionally, the quantum efficiency (QE), current density-voltage ( J - V ), and generation and recombination rates of photocarriers were determined. The maximum power conversion efficiency (PCE) of 28.05% with J SC of 34.67 mA cm -2 , FF of 87.31%, V OC of 0.93 V for SnS 2 ETL was obtained with Al/FTO/SnS 2 /Sr 3 SbI 3 /Ni structure, while the PCE of 24.33%, and 18.40% in ZnS and In 2 S 3 ETLs heterostructures, respectively. The findings of this study contribute to in-depth understanding of the physical, electronic, and optical properties of Sr 3 SbI 3 absorber perovskite and SnS 2 , ZnS, and In 2 S 3 ETLs. Additionally, it provides valuable insights into the potential of Sr 3 SbI 3 in heterostructure perovskite solar cells (PSCs), paving the pathway for further experimental design of an efficient and stable PSC devices., Competing Interests: The authors have no conflicts of interest., (This journal is © The Royal Society of Chemistry.)

Despite significant advances in diabetes management, particularly with the introduction of the most recent continuous glucose monitoring devices (CGMDs) that can monitor glucose actively in the transdermal interstitial fluid (ISF) in vivo, CGMDs still have significant disadvantages in terms of accuracy, low interference effect, precision, and stability. This is mostly because they detect hydrogen peroxide at higher potentials and require an oxygen-rich environment. First in its class, we developed an oxygen-insensitive polymeric glucose microneedle (MN) that was functionalized using a new electron-transfer mediator, 3-(3'-phenylimino)-3H-phenothiazinesulfonic acid-based enzyme cocktail for the NAD-GDH system. The inclusion of reduced graphene oxide aided in the absorption of the cocktail via the π-π interaction and enhanced the conductivity and sensor performance. The MN exhibited a dynamic linear range (1-30 mM) with a low detection limit of 26 μM, high sensitivity (18.05 μAmM -1 cm -2 ), stability (up to 7 days), high selectivity (due to a low oxidation potential of 0.15 V), and a fast response time (∼3 s). In vivo, deployment of the MN in a rabbit model demonstrated that the ISF glucose concentrations measured with the MN for up to 24 h correlate very well with the blood glucose concentrations measured with a commercial glucometer., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Introduction: The liver, the most important metabolic organ of the body, performs a wide variety of vital functions. Hepatic cell injury occurs by the activation of reactive oxygen species (ROS) that are generated by carbon tetrachloride (CCl4), xenobiotics, and other toxic substances through cytochrome P450-dependent steps resulting from the covalent bond formation with lipoproteins and nucleic acids. Observing the urgent state of hepatotoxic patients worldwide, different medicinal plants and their properties can be explored to combat such free radical damage to the liver. In vivo and in silico studies were designed and conducted to evaluate the antioxidant and hepatoprotective properties of Gynura procumbens in rats., Materials and Methods: Gynura procumbens leaves were collected and extracted using 70% ethanol. The required chemicals CCl4, standard drug (silymarin), and blood serum analysis kits were stocked. The in vivo tests were performed in 140 healthy Wister albino rats of either sex under well-controlled parameters divided into 14 groups, strictly maintaining Institutional Animal Ethics Committee (IEAC) protocols. For the histopathology study, 10% buffered neutral formalin was used for organ preservation. Later the specimens were studied under a fluorescence microscope. In silico molecular docking and absorption, distribution, metabolism, excretion, and toxicity (ADMET) studies were performed, and the results were analyzed statistically., Results and Discussion: Gynura procumbens partially negate the deleterious effect of carbon tetrachloride on normal weight gain in rats. The elevated level of serum glutamate pyruvate transaminase (SGPT), serum glutamate oxaloacetate transaminase (SGOT), alkaline phosphatase (ALP), creatinine, LDH, total cholesterol (TC), low-density lipoprotein (LDL), triglycerides (TG), malondialdehyde (MDA), deoxyribonucleic acid (DNA) fragmentation ranges, gamma-glutamyl transferase (γ-GT) in CCl4 treated groups were decreased by both standard drug silymarin and G. procumbens leaf extract. We have found significant & highly significant changes statistically for different doses, here p<0.05 & p<0.01, respectively. On the other hand, G. procumbens and silymarin displayed Statistically significant (p<0.05) and high significant(p<0.01) increased levels of HDL, CAT SOD (here p<0.05 & p<0.01 for different doses) when the treatment groups were compared with the disease control group. Because the therapeutic activity imparted by plants and drugs accelerates the movement of the disturbed pathophysiological state toward the healthy state. In the molecular docking analysis, G. procumbens phytoconstituents performed poorly against transforming growth factor-beta 1 (TGF-β1) compared to the control drug silymarin. In contrast, 26 phytoconstituents scored better than the control bezafibrate against peroxisome proliferator-activated receptor alpha (PPAR-α). The top scoring compounds for both macromolecules were observed to form stable complexes in the molecular dynamics simulations. Flavonoids and phenolic compounds performed better than other constituents in providing hepatoprotective activity. It can, thus, be inferred that the extract of G. procumbens showed good hepatoprotective properties in rats., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Tithi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study aims to find base materials for dry electrode fabrication with high accuracy and without reducing electrode performance for long-term bioelectric potential monitoring after electroless silver plating. Most applications of dry electrodes that have been developed in the past few decades are restricted by low accuracy compared to commercial Ag/AgCl gel electrodes, as in our previous study of PVDF-based dry electrodes. In a recent study, however, nanoweb-based chlorinated polyisoprene (CPI) and poly(styrene- b -butadiene- b -styrene) (SBS) rubber were selected as promising candidates due to their excellent elastic properties, as well as their nanofibril nature, which may improve electrode durability and skin contact. The electroless silver plating technique was employed to coat the nanofiber web with silver, and silver nanoweb(AgNW)-based dry electrodes were fabricated. The key electrode properties (contact impedance, step response, and noise characteristics) for AgNW dry electrodes were investigated thoroughly using agar phantoms. The dry electrodes were subsequently tested on human subjects to establish their realistic performance in terms of ECG, EMG monitoring, and electrical impedance tomography (EIT) measurements. The experimental results demonstrated that the AgNW dry electrodes, particularly the SBS-AgNW dry electrodes, performed similarly to commercial Ag/AgCl gel electrodes and were outperformed in terms of long-term stability.

The study aims to investigate the effects of different drying methods on the changes in functional properties, physicochemical composition, bioactive compounds, antioxidant activity, sensory attributes, and microstructural quality of the banana flours. Two local banana cultivars, Mehersagar and Sabri, were dried to produce flour using four distinct drying methods: freeze drying (FD), cabinet drying (CD), microwave oven drying (MOD), and forced air oven drying (FOD). The functional properties of the developed banana flours were observed where the findings were as water holding capacity (0.93 ± 0.06-2.74 ± 0.04 g water/g dry sample), oil absorption capacity (0.87 ± 0.06-2.22 ± 0.10 g oil/g dry sample), swelling capacity (4.62 ± 0.02-5.05 ± 0.03 g paste/g dry sample), bulk density (0.54 ± 0.04-0.81 ± 0.02 g/ml), tapped density (0.62 ± 0.04-0.93 ± 0.03 g/ml) and Carr's Index (9.38 ± 0.47-13.58 ± 0.43%). Freeze-dried Mehersagar cultivar's flour showed the leading functional properties with good flowability and cohesiveness. The physicochemical parameters of the flours also revealed significant differences (p < 0.05) in lightness (L*) (50.51 ± 1.49-72.21 ± 1.05), moisture content (3.96 ± 0.09-7.74 ± 0.13%), protein (2.72 ± 0.07-3.93 ± 0.06%), crude fat (0.11 ± 0.01-0.36 ± 0.04%), crude fiber (0.64 ± 0.03-1.22 ± 0.03%), carbohydrate (84.15 ± 0.24-88.26 ± 0.15%) and energy content (354.25 ± 0.57-370.02 ± 0.39 kcal/g). Total flavonoid content (21.44 ± 0.04-34.34 ± 0.03 mgQE/100g) and phenolic content (29.91 ± 0.01-71.46 ± 0.03 mgGAE/100g) was observed, while the highest retention of bioactive compounds was exhibited in Mehersagar cultivar's flour. In terms of appearance, fineness, taste, flavor, color, and overall acceptability, the dried banana flour of both the cultivars obtained from freeze-dried scored overall acceptability 8.04 ± 0.02 and 7.92 ± 0.17, respectively. The scanning electron microscopy analysis of the microstructure of flour granules from each sample revealed a diverse morphological configuration in particle size and shape. According to the findings of this study, the freeze-drying technology is superior to others, and the Mehersagar banana cultivar is more satisfactory in terms of quality characteristics. Moreover, the quality parameters of banana flour may facilitate the formulation of different flour-based gluten-free baked products and food supplements., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Since the last decade, hyperbranched polymers (HBPs) have gained wider theoretical interest and practical applications in sensor technology due to their ease of synthesis, highly branched structure but dimensions within nanoscale, a larger number of modified terminal groups and lowering of viscosity in polymer blends even at higher HBP concentrations. Many researchers have reported the synthesis of HBPs using different organic-based core-shell moieties. Interestingly, silanes, as organic-inorganic hybrid modifiers of HBP, are of great interest as they resulted in a tremendous improvement in HBP properties like increasing thermal, mechanical and electrical properties compared to that of organic-only moieties. This review focuses on the research progress in organofunctional silanes, silane-based HBPs and their applications since the last decade. The effect of silane type, its bi-functional nature, its influence on the final HBP structure and the resultant properties are covered in detail. Methods to enhance the HBP properties and challenges that need to be overcome in the near future are also discussed.

A flexible and portable triboelectric nanogenerator (TENG) based on electrospun polyvinylidene fluoride (PVDF) doped with copper oxide (CuO) nanoparticles (NPs, 2, 4, 6, 8, and 10 wt.-% w.r.t. PVDF content) was fabricated. The structural and crystalline properties of the as-prepared PVDF-CuO composite membranes were characterized using SEM, FTIR, and XRD. To fabricate the TENG device, the PVDF-CuO was considered a tribo-negative film and the polyurethane (PU) a counter-positive film. The output voltage of the TENG was analyzed using a custom-made dynamic pressure setup, under a constant load of 1.0 kgf and 1.0 Hz frequency. The neat PVDF/PU showed only 1.7 V, which further increased up to 7.5 V when increasing the CuO contents from 2 to 8 wt.-%. A decrease in output voltage to 3.9 V was observed for 10 wt.-% CuO. Based on the above results, further measurements were carried out using the optimal sample (8 wt.-% CuO). Its output voltage performance was evaluated as a function of varying load (1 to 3 kgf) and frequency (0.1 to 1.0 Hz) conditions. Finally, the optimized device was demonstrated in real-time wearable sensor applications, such as human motion and health-monitoring applications (respiration and heart rate).

Flexible pressure sensors have played an increasingly important role in the Internet of Things and human-machine interaction systems. For a sensor device to be commercially viable, it is essential to fabricate a sensor with higher sensitivity and lower power consumption. Polyvinylidene fluoride (PVDF)-based triboelectric nanogenerators (TENGs) prepared by electrospinning are widely used in self-powered electronics owing to their exceptional voltage generation performance and flexible nature. In the present study, aromatic hyperbranched polyester of the third generation (Ar.HBP-3) was added into PVDF as a filler (0, 10, 20, 30 and 40 wt.% w.r.t. PVDF content) to prepare nanofibers by electrospinning. The triboelectric performances (open-circuit voltage and short-circuit current) of PVDF-Ar.HBP-3/polyurethane (PU)-based TENG shows better performance than a PVDF/PU pair. Among the various wt.% of Ar.HBP-3, a 10 wt.% sample shows maximum output performances of 107 V which is almost 10 times that of neat PVDF (12 V); whereas, the current slightly increases from 0.5 μA to 1.3 μA. The self-powered TENG is also effective in measuring human motion. Overall, we have reported a simpler technique for producing high-performance TENG using morphological alteration of PVDF, which has the potential for use as mechanical energy harvesters and as effective power sources for wearable and portable electronic devices.

Some recent studies showed that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and idiopathic pulmonary fibrosis (IPF) disease might stimulate each other through the shared genes. Therefore, in this study, an attempt was made to explore common genomic biomarkers for SARS-CoV-2 infections and IPF disease highlighting their functions, pathways, regulators and associated drug molecules. At first, we identified 32 statistically significant common differentially expressed genes (cDEGs) between disease (SARS-CoV-2 and IPF) and control samples of RNA-Seq profiles by using a statistical r-package (edgeR). Then we detected 10 cDEGs (CXCR4, TNFAIP3, VCAM1, NLRP3, TNFAIP6, SELE, MX2, IRF4, UBD and CH25H) out of 32 as the common hub genes (cHubGs) by the protein-protein interaction (PPI) network analysis. The cHubGs regulatory network analysis detected few key TFs-proteins and miRNAs as the transcriptional and post-transcriptional regulators of cHubGs. The cDEGs-set enrichment analysis identified some crucial SARS-CoV-2 and IPF causing common molecular mechanisms including biological processes, molecular functions, cellular components and signaling pathways. Then, we suggested the cHubGs-guided top-ranked 10 candidate drug molecules (Tegobuvir, Nilotinib, Digoxin, Proscillaridin, Simeprevir, Sorafenib, Torin 2, Rapamycin, Vancomycin and Hesperidin) for the treatment against SARS-CoV-2 infections with IFP diseases as comorbidity. Finally, we investigated the resistance performance of our proposed drug molecules compare to the already published molecules, against the state-of-the-art alternatives publicly available top-ranked independent receptors by molecular docking analysis. Molecular docking results suggested that our proposed drug molecules would be more effective compare to the already published drug molecules. Thus, the findings of this study might be played a vital role for diagnosis and therapies of SARS-CoV-2 infections with IPF disease as comorbidity risk., (© 2023. The Author(s).)