Management strategies of translocated pondweed Monochoria hastata and its ecological and economic impacts.

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.

Screening of differential gene expression patterns through survival analysis for diagnosis, prognosis and therapies of clear cell renal cell carcinoma.

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.

Uncontrolled blood pressure among the established hypertensive elderly people in Jashore, Bangladesh: A cross-sectional type of observational study.

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.

Soil pollution and elemental sources along Barapukuria coal mine, Bangladesh: Implications for eco-environmental and health risk assessment.

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.

Bioinformatics analysis to disclose shared molecular mechanisms between type-2 diabetes and clear-cell renal-cell carcinoma, and therapeutic indications.

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.

Identification of most representative hub-genes for diagnosis, prognosis, and therapies of hepatocellular carcinoma.

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.

Polyaromatic Hydrocarbon-Functionalized 2D MXene-Based 3D Porous Antifouling Nanocomposite with Long Shelf Life for High-Performance Electrochemical Immunosensor Applications.

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.

Design and Optimization of High-Performance Novel RbPbBr3-Based Solar Cells with Wide-Band-Gap S-Chalcogenide Electron Transport Layers (ETLs).

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 (RbPbBr3)-based hybrid perovskite solar cells (HPSCs) with several high-band-gap chalcogenide electron transport layers (ETLs) of In2S3, WS2, and SnS2 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 (SnS2) layer was performed systematically. Finally, a comparative study of different reported heterostructures was performed to explore the benchmark of the most recent efficient RbPbBr3-based photovoltaics. The highest power conversion efficiency (PCE) was 29.75% for the SnS2 ETL with Voc of 0.9789 V, Jsc 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 In2S3 and WS2 ETLs, respectively. The electron-hole generation, recombination rates, and quantum efficiency (QE) characteristics were also investigated in detail. Thus, the SnS2 ETL shows strong potential for use in RbPbBr3-based hybrid perovskite high-performance photovoltaic devices.

Multi-omics data integration and drug screening of AML cancer using Generative Adversarial Network.

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_codes?fbclid=IwAR1-/stuffmlE0hyWgSu2wlXo6dYlKUei3faLdlvpxTOOUPVlmYCloXf4Uk9ejK4I.

Reduced graphene oxide-functionalized polymer microneedle for continuous and wide-range monitoring of lactate in interstitial fluid.

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-1cm-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.

Metformin Hydrochloride Loaded Mucoadhesive Microspheres and Nanoparticles for Anti-Hyperglycemic and Anticancer Effects Using Factorial Experimental Design.

Background: 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.

Pharmacophore mapping approach to find anti-cancer phytochemicals with metformin-like activities against transforming growth factor (TGF)-beta receptor I kinase: An in silico study.

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.

An in vivo and in silico evaluation of the hepatoprotective potential of Gynura procumbens: A promising agent for combating hepatotoxicity.

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-ß1) 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.

Corrigendum: Identification of circRNA biomarker for gastric cancer through integrated analysis.

[This corrects the article DOI: 10.3389/fmolb.2022.857320.].

An oxygen-insensitive and minimally invasive polymeric microneedle sensor for continuous and wide-range transdermal glucose monitoring.

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.

Evaluation of Biological Variation of Different Clinical Laboratory Analytes in the Blood of Healthy Subjects.

Background Biological variation (BV) as a prognostic marker implies that each individual has a "subject mean" or central tendency, control level, or "set point" concentration for maintaining homeostasis regulation, which is influenced by factors such as genes, diet, exercise, and age. Uses for information on BV include determining the value of population-based reference intervals, assessing the importance of variation in serial findings, and establishing criteria for judging correct analysis. Aims We focused on the assessment of BV parameters for these elements as within-subject BV (CVW), between subject BV (CVG), the index of individuality (II), and the reference change value (RCV) of important biochemical analytes in the Bangladeshi adult population. Methodology This is a cross-sectional analytical study of a representative sample in the population of Bangladesh to determine BV in clinical laboratory analytes. For the study, 758 people were requested to take part; among those 730 (ages 18-65) apparently, healthy adults were blood donors, hospital staff, laboratory personnel, or any individuals who presented themselves for health screening at a tertiary hospital in Dhaka, Bangladesh. Results The CVW for blood sugar, creatinine, urea, uric acid, sodium, potassium, chloride, calcium, magnesium, and phosphate were calculated as 5.10 %, 4.64%, 10.72%, 5.71%, 0.69%, 4.35%, 0.75%, 3.69%, 4.57%, and 4.72%, respectively. The CVG for blood sugar, creatinine, urea, uric acid, sodium, potassium, chloride, calcium, magnesium, and phosphate was 10.70%, 21.46%, 31.47%, 23.52%, 1.95%, 9.74%, 2.56%, 4.64%, 9.96 %, and 17.45%, respectively. The index of individuality (II) for blood sugar, creatinine, urea, uric acid, sodium, potassium, chloride, calcium, magnesium, and phosphate were 0.48, 0.22, 0.34, 0.24, 0.35, 0.45, 0.29, 0.79, 0.46, and 0.27, respectively. The RCV for blood sugar, creatinine, urea, uric acid, sodium, potassium, chloride, calcium, magnesium, and phosphate was 14.75%, 14.10%, 30.58%, 16.13%, 2.82%, 12.58%, 3.54%, 10.62%, 13.62 %, and 15.80%, respectively. Conclusions Nine serum biochemistry analytes (blood sugar, creatinine, urea, uric acid, sodium, potassium, chloride, magnesium, and phosphate) had low individuality, indicating that subject-based reference intervals are appropriate, only one analyte (calcium) had high individuality and, therefore, population-based reference intervals are more appropriate.

Exploring Core Genes by Comparative Transcriptomics Analysis for Early Diagnosis, Prognosis, and Therapies of Colorectal Cancer.

Colorectal cancer (CRC) is one of the most common cancers with a high mortality rate. Early diagnosis and therapies for CRC may reduce the mortality rate. However, so far, no researchers have yet investigated core genes (CGs) rigorously for early diagnosis, prognosis, and therapies of CRC. Therefore, an attempt was made in this study to explore CRC-related CGs for early diagnosis, prognosis, and therapies. At first, we identified 252 common differentially expressed genes (cDEGs) between CRC and control samples based on three gene-expression datasets. Then, we identified ten cDEGs (AURKA, TOP2A, CDK1, PTTG1, CDKN3, CDC20, MAD2L1, CKS2, MELK, and TPX2) as the CGs, highlighting their mechanisms in CRC progression. The enrichment analysis of CGs with GO terms and KEGG pathways revealed some crucial biological processes, molecular functions, and signaling pathways that are associated with CRC progression. The survival probability curves and box-plot analyses with the expressions of CGs in different stages of CRC indicated their strong prognostic performance from the earlier stage of the disease. Then, we detected CGs-guided seven candidate drugs (Manzamine A, Cardidigin, Staurosporine, Sitosterol, Benzo[a]pyrene, Nocardiopsis sp., and Riccardin D) by molecular docking. Finally, the binding stability of four top-ranked complexes (TPX2 vs. Manzamine A, CDC20 vs. Cardidigin, MELK vs. Staurosporine, and CDK1 vs. Riccardin D) was investigated by using 100 ns molecular dynamics simulation studies, and their stable performance was observed. Therefore, the output of this study may play a vital role in developing a proper treatment plan at the earlier stages of CRC.

Bioinformatics-based investigation on the genetic influence between SARS-CoV-2 infections and idiopathic pulmonary fibrosis (IPF) diseases, and drug repurposing.

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.

Identification of Drug Targets and Agents Associated with Hepatocellular Carcinoma through Integrated Bioinformatics Analysis.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death globally. The mechanisms underlying the development of HCC are mostly unknown till now. OBJECTIVE: The main goal of this study was to identify potential drug target proteins and agents for the treatment of HCC. METHODS: The publicly available three independent mRNA expression profile datasets were downloaded from the NCBI-GEO database to explore common differentially expressed genes (cDEGs) between HCC and control samples using the Statistical LIMMA approach. Hub-cDEGs as drug targets highlighting their functions, pathways, and regulators were identified by using integrated bioinformatics tools and databases. Finally, Hub-cDEGs-guided top-ranked drug agents were identified by molecular docking study for HCC. RESULTS: We identified 160 common DEGs (cDEGs) from three independent mRNA expression datasets in which ten cDEGs (CDKN3, TK1, NCAPG, CDCA5, RACGAP1, AURKA, PRC1, UBE2T, MELK, and ASPM) were selected as Hub-cDEGs. The GO functional and KEGG pathway enrichment analysis of Hub-cDEGs revealed some crucial cancer-stimulating biological processes, molecular functions, cellular components, and signaling pathways. The interaction network analysis identified three TF proteins and five miRNAs as the key transcriptional and post-transcriptional regulators of HubcDEGs. Then, we detected the proposed Hub-cDEGs guided top-ranked three anti-HCC drug molecules (Dactinomycin, Vincristine, Sirolimus) that were also highly supported by the already published top-ranked HCC-causing Hub-DEGs mediated receptors. CONCLUSION: The findings of this study would be useful resources for diagnosis, prognosis, and therapies of HCC.