Search

Despite many recent studies on non-alcoholic fatty liver disease (NAFLD) therapeutics, the optimal treatment has yet to be determined. In this unfinished project, we combined secondary metabolites (SMs) from the gut microbiota (GM) and Hordeum vulgare (HV) to investigate their combinatorial effects via network pharmacology (NP). Additionally, we analyzed GM or barley – signalling pathways – targets – metabolites (GBSTMs) in combinatorial perspectives (HV, and GM). A total of 31 key targets were analysed via a protein-protein interaction (PPI) network, and JUN was identified as the uppermost target in NAFLD. On a bubble plot, we revealed that apelin signalling pathway, which had the lowest enrichment factor antagonize NAFLD. Holistically, we scrutinized GBSTM to identify key components (GM, signalling pathways, targets, and metabolites) associated with the Apelin signalling pathway. Consequently, we found that the primary GMs (Eubacterium limosum, Eggerthella sp. SDG-2, Alistipes indistinctus YIT 12060, Odoribacter laneus YIT 12061, Paraprevotella clara YIT 11840, Paraprevotella xylaniphila YIT 11841) to ameliorate NAFLD. The molecular docking test (MDT) suggested that tryptanthrin-JUN is an agonist, conversely, dihydroglycitein-HDAC5, 1,3-diphenylpropan-2-ol-NOS1, and (10[(Acetyloxy)methyl]-9-anthryl)methyl acetate-NOS2, which are antagonistic conformers in the apelin signalling pathway. Overall, these results suggest that combination therapy could be an effective strategy for treating NAFLD.

Background/Aims Shifts in the gut microbiota and metabolites are interrelated with liver cirrhosis progression and complications. However, causal relationships have not been evaluated comprehensively. Here, we identified complication-dependent gut microbiota and metabolic signatures in patients with liver cirrhosis. Methods Microbiome taxonomic profiling was performed on 194 stool samples (52 controls and 142 cirrhosis patients) via V3-V4 16S rRNA sequencing. Next, 51 samples (17 controls and 34 cirrhosis patients) were selected for fecal metabolite profiling via gas chromatography mass spectrometry and liquid chromatography coupled to time-of-flight mass spectrometry. Correlation analyses were performed targeting the gut-microbiota, metabolites, clinical parameters, and presence of complications (varices, ascites, peritonitis, encephalopathy, hepatorenal syndrome, hepatocellular carcinoma, and deceased). Results Veillonella bacteria, Ruminococcus gnavus, and Streptococcus pneumoniae are cirrhosis-related microbiotas compared with control group. Bacteroides ovatus, Clostridium symbiosum, Emergencia timonensis, Fusobacterium varium, and Hungatella_uc were associated with complications in the cirrhosis group. The areas under the receiver operating characteristic curve (AUROCs) for the diagnosis of cirrhosis, encephalopathy, hepatorenal syndrome, and deceased were 0.863, 0.733, 0.71, and 0.69, respectively. The AUROCs of mixed microbial species for the diagnosis of cirrhosis and complication were 0.808 and 0.847, respectively. According to the metabolic profile, 5 increased fecal metabolites in patients with cirrhosis were biomarkers (AUROC >0.880) for the diagnosis of cirrhosis and complications. Clinical markers were significantly correlated with the gut microbiota and metabolites. Conclusions Cirrhosis-dependent gut microbiota and metabolites present unique signatures that can be used as noninvasive biomarkers for the diagnosis of cirrhosis and its complications.

Abstract Cornus kousa fruit (CKF) has been utilized as anti‐obesity supplementation in East Asia, including Korea, and gut microbiota (GM) might have synergistic effects on obesity (OB) via its interplay. We aimed to decode molecule(s), mechanism(s), and target(s) on interplay between CKF and GM via network pharmacology analysis. The final targets were analyzed by protein–protein interaction (PPI) networks and a bubble plot. The GM interacted with significant targets identified by the gutMGene database. The relationships among CKF or GM, signaling pathways, targets, and molecules (CGSTM) were plotted by R package. Finally, molecular docking assay and density functional theory (DFT) were performed to validate its affinity. The final targets (22) were selected on OB‐responded targets, indicating that interleukin‐6 (IL6) was the most crucial protein‐coding target on PPI networks. A bubble plot and CGSTM networks suggested that the advanced glycation end‐receptor for advanced glycation end products signaling pathway in diabetic complications is inhibited by CKF and peroxisome proliferator–activated receptor (PPAR) signaling pathway is activated by GM. As the most stable conformers, IL6‐equol complex was attributed to GM, and PPAR alpha‐linoleic acid, PPAR delta‐stearic acid, and fatty acid–binding protein 4‐dimethyl 2,3‐bis(1,3‐dimethylindol‐2‐yl) fumarate complex were attributed to CKF. Noticeably, stearic acid was removed by DFT analysis; all other three molecules were proposed as good electron donators with the higher electronegativity compared with a standard drug (Orlistat). This study shows that integrated pharmacological analysis can enable to decode the unknown relationships between CKF and GM. Overall, this study reveals that the combination of CKF and favorable GM might exert dual therapeutic effects on OB.

Abstract Biological neural systems operate on multiple time scales, enabling real-time interaction with their environment. However, replicating this in electronic systems is challenging, as scalable devices that operate on similar time scales, particularly from seconds to minutes, are lacking. This study addresses this gap by exploiting proton dynamics to achieve volatile resistance changes over long time scales, and developed a neuromorphic system that can predict biomedical data, such as blood glucose levels, in real time. By applying a low voltage (below 1 V) to a two-terminal device, the Pd electrode hydrogenates or dehydrogenates the mixed conductor WO3, resulting in significant changes in electronic resistance. The device is scalable due to the uniform proton distribution, leading to high impedance and minimal power consumption. Utilizing these volatile protons for short-term memory in an Echo State Network (ESN), this approach demonstrates low-power, efficient real-time information processing, paving the way for future neuromorphic computing applications.

Abstract Due to the excessive growth of PM 2.5 in aerosol, the cases of lung cancer are increasing rapidly and are most severe among other types as the highest mortality rate. In most of the cases, lung cancer is detected with least symptoms at its later stage. Hence, clinical records may play a vital role to diagnose this disease at the correct stage for suitable medication to cure it. To detect lung cancer an accurate prediction method is needed which is significantly reliable. In the digital clinical record era with advancement in computing algorithms including machine learning techniques opens an opportunity to ease the process. Various machine learning algorithms may be applied over realistic clinical data but the predictive power is yet to be comprehended for accurate results. This paper envisages to compare twelve potential machine learning algorithms over clinical data with eleven symptoms of lung cancer along with two major habits of patients to predict a positive case accurately. The result has been found based on classification and heat map correlation. K-Nearest Neighbor Model and Bernoulli Naive Bayes Model are found most significant methods for early lung cancer prediction.

The one-dimensional Two-Fluid concept uses an area-average approach to simplify the time and phase-averaged Two-Fluid conservation equations, making it more suitable for addressing difficulties at an industrial scale. Nevertheless, the mathematical framework has inherent weaknesses due to the loss of details throughout the averaging procedures. This limitation makes the conventional model inappropriate for some flow regimes, where short-wavelength perturbations experience uncontrolled amplification, leading to solutions that need to be physically accurate. The critical factor in resolving this problem is the integration of closure relations. These relationships play a crucial function in reintroducing essential physical characteristics, thus correcting the loss that occurs during averaging and guaranteeing the stability of the model. To improve the accuracy of predictions, it is essential to assess the stability and grid dependence of one-dimensional formulations, which are particularly affected by closure relations and numerical schemes. The current research presented in the text focuses on improving the well-posedness of the TFM, specifically within the TRACE code, which is widely utilized for nuclear reactor safety assessments. Incorporating a bubble collision model in the momentum equations is demonstrated to enhance the TFM's resilience, especially in scenarios with high void fractions where conventional TFMs may face challenges. The analysis presents a linear stability analysis performed for the transient one-dimensional Two-Fluid Model of system code TRACE within the framework of vertically dispersed flows. The main emphasis is on evaluating the stability characteristics of the model while also acknowledging its susceptibility to closure relations and numerical techniques.

Introduction: Diabetic foot is a common complication of diabetes mellitus, affecting approximately 15–20% of individuals with diabetes. It is a comorbid condition that significantly impacts the routine life of patients. This study aimed to assess multidisciplinary management strategies and their impact on the outcomes of patients with diabetic foot. Methods: A prospective observational study was conducted on 56 patients with diabetic foot. Outcome measures included the type of surgery, frequency of surgery, morbidity, mortality, patient satisfaction, return to work, and the number of patients using prostheses Results: The majority of the patients (87%) received surgical treatment. The most common type of surgery performed was debridement (55%), followed by minor amputations (toes amputation/forefoot amputation) (28%) and major amputations (below-knee (B/K) or above-knee (A/K)) (15%). More than 70% of patients had multiple surgeries. The mortality rate was low (7%), and 71% of surviving patients were satisfied with their treatment. Sixty-seven percent of patients had an early return to work. The number of patients using prostheses was also high (73% of major amputation cases). Conclusion: Multidisciplinary management is the most effective approach for diabetic foot patients. These patients may experience less morbidity and an early return to work. A specialized care clinic for diabetic foot patients is essential to prevent treatment failure, loss of follow-up records, permanent limb loss, and economic burdens on society.

Introduction and objectives: It is challenging to adopt a policy of ABO identical platelet transfusion in hemato-oncological patients because of the high demand. Moreover, there are no global standards for the management of ABO non-identical platelet transfusions due to limited evidence. The current study compared the impact of dose and storage duration of platelets on percent platelet recovery (PPR) at 1 h and 24 h between ABO identical and ABO non-identical platelet transfusions in hemato-oncological conditions. The other objectives were to assess the clinical efficacy and compare adverse reactions between the two groups. Methods: A total of 130 random donor platelet transfusion episodes (81 ABO identical and 49 ABO non-identical) were evaluated in 60 eligible patients with different malignant, as well as non–malignant, hematological conditions. All analysis was performed using two-sided tests, and p-values

Lightweight high-entropy alloys (LWHEAs) present new opportunities for exploring innovative, low-cost materials with a high strength-to-weight ratio, thanks to their expansive alloy-design space. This study introduces the newly designed AlMgxTiSnZn HEAs to examine the relationship between microstructure, phase stability, and functional properties (including mechanical, thermal, and electrochemical properties alongside oxidation resistance). These alloys were produced by mechanically mixing them in a high-energy ball mill (HEBM), followed by heating with spark plasma sintering (SPS). Thermodynamic calculations were utilized to ascertain the phase structure. XRD studies revealed a predominant ordered BCC phase with minor peaks indicating a tetragonal structure. The correlation between microhardness (Hv) and fracture strength (σf) with Mg content indicates that the HEA sample featuring the highest microhardness concurrently exhibits the highest fracture strength (AlMgTiSnZn). This AlMgTiSnZn HEA sample, noted for its high corrosion resistance and distinct properties (such as favorable over-potential, low corrosion current density (Icorr), and minimal corrosion rate), is particularly promising for high-temperature applications.

Receptor-induced tyrosine phosphorylation of spleen tyrosine kinase (Syk) has been studied extensively in hematopoietic cells. Metabolic mapping and high-resolution mass spectrometry, however, indicate that one of the most frequently detected phosphorylation sites encompassed S297 (S291 in mice) located within the linker B region of Syk. It has been reported that Protein kinase C (PKC) phosphorylates Syk S297, thus influencing Syk activity. However, conflicting studies suggest that this phosphorylation enhances as well as reduces Syk activity. To clarify the function of this site, we generated Syk S291A knock-in mice. We used platelets as a model system as they possess Glycoprotein VI (GPVI), a receptor containing an immunoreceptor tyrosine-based activation motif (ITAM) which transduces signals through Syk. Our analysis of the homozygous mice indicated that the knock-in platelets express only one isoform of Syk, while the wild-type expresses two isoforms at 69 and 66 kDa. When the GPVI receptor was activated with collagen-related peptide (CRP), we observed an increase in functional responses and phosphorylations in Syk S291A platelets. This potentiation did not occur with AYPGKF or 2-MeSADP, although they also activate PKC isoforms. Although there was potentiation of platelet functional responses, there was no difference in tail bleeding times. However, the time to occlusion in the FeCl3 injury model was enhanced. These data indicate that the effects of Syk S291 phosphorylation represent a significant outcome on platelet activation and signaling in vitro but also reveals its multifaceted nature demonstrated by the differential effects on physiological responses in vivo.

ABSTRACTMetabolic dysfunction-associated steatotic liver disease (MASLD) is the most common chronic liver disease, and its prevalence has increased worldwide in recent years. Additionally, there is a close relationship between MASLD and gut microbiota-derived metabolites. However, the mechanisms of MASLD and its metabolites are still unclear. We demonstrated decreased indole-3-propionic acid (IPA) and indole-3-acetic acid (IAA) in the feces of patients with hepatic steatosis compared to healthy controls. Here, IPA and IAA administration ameliorated hepatic steatosis and inflammation in an animal model of WD-induced MASLD by suppressing the NF-κB signaling pathway through a reduction in endotoxin levels and inactivation of macrophages. Bifidobacterium bifidum metabolizes tryptophan to produce IAA, and B. bifidum effectively prevents hepatic steatosis and inflammation through the production of IAA. Our study demonstrates that IPA and IAA derived from the gut microbiota have novel preventive or therapeutic potential for MASLD treatment.

PURPOSEGene fusions are critical oncogenic mutations that drive cancer development and serve as diagnostic and prognostic biomarkers. Despite the increasing cancer burden in India, large-scale analyses of molecular landscapes, particularly gene fusions, have been relatively scarce.MATERIALS AND METHODSThis retrospective study used RNA-exome data from 1,392 Indian patients with cancer across 15 major cancer types to explore gene fusions. The study used a comprehensive framework that integrated open-source and proprietary tools to detect gene fusions from formalin-fixed paraffin-embedded tumor samples. The process involved RNA extraction, RNA-exome library preparation, and analysis using tools such as FastQC, DRAGEN RNA Pipeline, STAR-Fusion, and FusionInspector. We validated and filtered potential false-positive fusion calls using AGFusion and FusionAnnotator to annotate fusion breakpoints and their functional impact through various in silico tools.RESULTSThe study found a notable prevalence of FGFR fusions across cancer types, especially FGFR3, with FGFR3::TACC3 as the most recurrent. Kinase fusions were prevalent in the cohort accounting for 37% of incidence in the patients. We also identified 91 novel potential driver fusions, including those involving FGFR2, MET, ESR1, and PDGFRA.CONCLUSIONThis study underscores the critical role of gene fusions as biomarkers in cancer, extending beyond fusion-driven malignancies to encompass all cancer types. Gene fusions serve as both diagnostic markers and tumor-agnostic therapeutic targets within the current cancer treatment paradigm. Our insights into the prevalence of oncogenic drivers and novel targets expand the understanding of gene fusions, shedding new light on their mechanisms and clinical implications.

This retrospective study investigates the prevalence and epidemiological factors associated with renal insufficiency in dogs within Patna, Bihar, India. Out of 5,700 dogs with various illnesses, 317 were diagnosed with renal insufficiency, identified by serum creatinine levels exceeding 5 mg/dL. The study assessed the incidence of renal insufficiency across different demographics, including age, sex, breed, and season. The highest incidence was observed in dogs aged 8-10 years, with males showing a higher prevalence than females. Pomeranians (32.18%), Labrador Retrievers (25.55%), and German Shepherds (20.82%) were the most affected breeds. Seasonally, the post-monsoon period (September-November) exhibited the highest incidence (37.85%) of renal disorders. Laboratory investigations revealed significant haematological and biochemical alterations in affected dogs, including lower haemoglobin, total erythrocyte count, and packed cell volume, alongside elevated serum levels of blood urea nitrogen (BUN), creatinine, potassium, and phosphorus. Ultrasonography indicated decreased renal size and increased echogenicity in dogs with renal insufficiency. The study concludes that renal insufficiency in dogs is most prevalent in older males and certain breeds, particularly during the post-monsoon season. Regular monitoring of serum BUN and creatinine levels is recommended for early diagnosis and management of this condition.

Introduction Pneumococcal diseases pose a significant public health concern in India, with substantial morbidity and mortality, with the elderly and those with coexisting medical conditions being most at risk. Pneumococcus was also seen to be one of the main reasons for co-infection, pneumonia and complications in COVID. Current guidelines recommend vaccination for specific adult populations, but there is a lack of uniformity and guidance on risk stratification, prioritisation and optimal timing. Methods Nation Against Pneumococcal Infections – Expert Panel Opinion (NAP-EXPO) is a panel convened to review and update recommendations for adult pneumococcal vaccination in India. The panel of 23 experts from various medical specialties engaged in discussions and evidence-based reviews, discussed appropriate age for vaccination, risk stratification for COPD and asthma patients, vaccination strategies for post-COVID patients, smokers and diabetics, as well as methods to improve vaccine awareness and uptake. Outcome The NAP-EXPO recommends the following for adults: All healthy individuals 60 years of age and above should receive the pneumococcal vaccine; all COPD patients, regardless of severity, high-risk asthma patients, post-COVID cases with lung fibrosis or significant lung damage, should be vaccinated with the pneumococcal vaccine; all current smokers and passive smokers should be educated and offered the pneumococcal vaccine, regardless of their age or health condition; all diabetic individuals should receive the pneumococcal vaccine, irrespective of their diabetes control. Strategies to improve vaccine awareness and uptake should involve general practitioners (GPs), primary health physicians (PHPs) and physicians treating patients at high risk of pneumococcal disease. Advocacy campaigns should involve media, including social media platforms. Conclusion These recommendations aim to enhance pneumococcal vaccination coverage among high-risk populations in India in order to ensure a reduction in the burden of pneumococcal diseases, in the post-COVID era. There is a need to create more evidence and data to support the recommendations that the vaccine will be useful to a wider range of populations, as suggested in our consensus.

Abstract Soluble lead redox flow battery (SLRFB) is an emergent energy storage technology appropriate for integrating solar and wind energy into the primary grid. It is an allied technology of conventional lead‐acid batteries. This appraisal compares lead‐acid batteries and SLRFB apropos their general characteristics. SLRFBs can overcome the inadequate cycle‐life of Lead‐Acid batteries as the electrodes of SLRFB do not participate in the reaction, which helps extending its durability. However, SLRFB has challenges of dendrite formation, oxygen evolution reaction, passivation of PbO2 and shunt current. These problems need to be resolved before SLRFBs can be projected for large‐scale energy storage applications. In this technical update, we have reviewed the recent studies pertinent to dendrite formation, mechanism of the lead electrode, and reversibility of the PbO2 electrode in the state‐of‐art of SLRFB along with progress in advances while developing a 12 V – 250 Wh 8‐cell SLRFB stack.

Emission and performance parameters of a 4-stroke CI engine operated on a blend of catalytic co-pyrolysis oil with pure diesel, produced through Azadirachta indica seed, waste LDPE (low-density polyethylene), and aluminium oxide (Al2O3) as a catalyst, are modelled in the current work using an Artificial Neural Network (ANN). At 500°C temperature, the highest oil output obtained was 93.91 wt%. The produced liquid fuel possessed similar physical features to that of pure diesel, including density (794 kg/m3) and heating value (44.42 MJ/kg), but lower flash and fire points that would assist in a better and complete combustion of the fuel blend resulting in a better performance and combustion characteristics. Using inputs including brake mean effective pressure, load, brake power, and torque, a developed ANN model was applied to forecast the performance (Brake Thermal Efficiency and Brake Specific Fuel Consumption) along with emission characteristics (Smoke and NOx). The Levenberg-Marquardt back-propagation training technique was applied for emissions and performance characteristics prediction having the best accuracy. Regression coefficients (R2) for predicting BTE, BSFC, NOx, and smoke were all very near to 1: 0.99801, 0.9983, 0.95753, and 0.97467. The study determines that the proposed alternative fuel could be utilized in blend with the pure diesel to in an unmodified diesel engine. It has also been found that artificial neural networks (ANN) could prove to be useful to model and forecast the performance or emissions of renewable fuels in diesel engines, with the potential for these fuels to be employed in transportation.

Background: The cabbage webworm, Hellula undalis (Fabricius) (Lepidoptera: Pyralidae), is a significant pest of brassicas and other cruciferous plants in warm regions worldwide. Transcriptome analysis is valuable for investigation of molecular mechanisms underlying the insect development and reproduction. De novo assembly is particularly useful for acquiring complete transcriptome information of insect species when there is no reference genome available. In case of Hellula undalis, only 17 nucleotide records are currently available throughout NCBI nucleotide database. Genes associated with metabolic processes, general development, reproduction, defense and functional genomics were not previously predicted in the Hellula undalis at the genomic level. Methods & Results: To address this issue, we constructed Hellula undalis transcriptome using Illumina NovaSeq6000 technology. Approximately 48 million 150 bp paired-end reads were obtained from sequencing. A total of 30,451 contigs were generated by de novo assembly of sample and were compared with the sequences in the NCBI non-redundant protein database (Nr). In total, 71 % of contigs were matched to known proteins in public databases including Nr, Gene Ontology (GO), and Cluster Orthologous Gene Database (COG), and then, contigs were mapped to 123 via functional annotation against the Kyoto Encyclopedia of Genes and Genomes pathway database (KEGG). In addition, we compared the ortholog gene family of the Hullula undalis, transcriptome to Spodoptera frugiperda, spodotera litura and spodoptera littoralis and found that 391 orthologous gene families are specific to Hullula undalis. A total of 1,913 potential SSRs was discovered in Hullula undalis contigs. Conclusions: This study is the first transcriptome data for Hullula undalis. Additionally, it serves as a valuable resource for identifying target genes and developing effective and environmentally friendly strategies for pest control.

Background: For patients with severe aortic stenosis, transcatheter aortic valve implantation (TAVI) is a less invasive but equally effective treatment option compared with surgical aortic valve replacement (SAVR). In 2019, we reported low rates of TAVI in the UK compared with other countries in western Europe and highlighted profound geographical variation in TAVI care. Here, we provide contemporary data on access to aortic valve replacement by either TAVI or SAVR across clinical commissioning groups in England. Methods: We obtained aggregated data from the UK TAVI registry and the National Adult Cardiac Surgery Audit between 2019 and 2023. Rates of TAVI and SAVR procedures per million population were reported by clinical commissioning groups. The relationship between TAVI and SAVR rates was determined using Pearson correlation coefficients. Results: In 2022/23, the rates of TAVI and SAVR in England were 136 per million population and 60 per million population, respectively. The observed increase in TAVI rates since 2019/20 corresponded with a decline in SAVR rates. There remains substantial variation in access to both procedures, with an over tenfold variation in TAVI rates, and an over fourfold variation in SAVR rates across clinical commissioning groups in England. No relationship was identified between the rates of TAVI and those for SAVR (correlation coefficient 0.06). Conclusion: Geographical heterogeneity in access to TAVI persists over time, with the low rates of TAVI in many areas not compensated for by higher rates of SAVR, indicating an overall inequality in the treatment of severe aortic stenosis.

Antimicrobial resistance presents a formidable challenge to contemporary medicine, necessitating innovative therapeutic solutions. Azo dyes and their metal complexes have emerged as promising candidates due to their notable antimicrobial properties. This review comprehensively examines the synthesis and application of azo dyes and metal complexes for emerging antimicrobial therapies. Through various synthetic strategies and metallation, the chemical structure of azo derivatives allows for modifications that enhance their antimicrobial efficacy, making them promising candidates for pharmaceutical development against microbial infections. The study provides a comprehensive understanding of the mechanisms of antimicrobial action, including DNA intercalation, enzyme inhibition, membrane disruption, and reactive oxygen species generation. The role of metal ions is particularly significant, enhancing structural stability, reactivity, and the ability to target microbial enzymes effectively. Chelation effects, such as reduced polarity and increased lipophilicity, facilitate the penetration of microbial cell membranes and the disruption of enzyme activity. The review highlights novel azo-metal complexes’ significant antifungal and antibacterial activities, particularly their efficacy against pathogens such as Mycobacterium tuberculosis. The importance of structure-activity relationships is detailed, showing how specific functional groups and metal ions influence antimicrobial efficacy. Additionally, their potential sensing ability to detect and identify microorganisms highlights the multifaceted role of azo dye derivatives in infection management.

Abstract Microglial Na/H exchanger-1 (NHE1) protein, encoded by Slc9a1, plays a role in white matter demyelination of ischemic stroke brains. To explore underlying mechanisms, we conducted single cell RNA-seq transcriptome analysis in conditional Slc9a1 knockout (cKO) and wild-type (WT) mouse white matter tissues at 3 days post-stroke. Compared to WT, Nhe1 cKO brains expanded a microglial subgroup with elevated transcription of white matter myelination genes including Spp1, Lgals3, Gpnmb, and Fabp5. This subgroup also exhibited more acidic pHi and significantly upregulated CREB signaling detected by ingenuity pathway analysis and flow cytometry. Moreover, the Nhe1 cKO white matter tissues showed enrichment of a corresponding oligodendrocyte subgroup, with pro-phagocytosis and lactate shuffling gene expression, where activated CREB signaling is a likely upstream regulator. These findings demonstrate that attenuation of NHE1-mediated H+ extrusion acidifies microglia/macrophage and may underlie the stimulation of CREB1 signaling, giving rise to restorative microglia-oligodendrocyte interactions for remyelination.

The study is carried out to investigate the surface runoff depth with changing precipitation due to climate change in the study area where sandy loam and loamy soil are dominant. In this study, future rainfall is projected by a statistical downscaling model (SDSM) using a set of predictors derived from a Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model (GCM) [the Norwegian Earth System Model (NorESM)] with updated scenarios SSP 4.5 and SSP 8.5. Daily rainfall values for the observed period (1981 to 2014) are validated using statistical learning and evaluated with matrices, namely, root mean square error (RMSE), coefficient of correlation, and Nash–Sutcliffe efficiency (NSE), which are found to be valid for further predictions. Rainfall projections show a decrease in rainfall trend of 50% from 2030 to 2040 for scenario SSP 4.5 and an increase of 7% from 2040 to 2050. Predicted rainfall for scenario SSP 8.5 shows a similar trend of decreasing rainfall of 24% for the period 2030–2040 and an increase of 19% in the period 2040–2050. Furthermore, these rainfall values are spatially modelled in a geographic information system (GIS) and rainfall maps are obtained. The obtained rainfall map, land-use map, and soil map are overlaid to compute curve numbers and runoff depths. A similar trend of decrease in runoff is observed for the period 2030–2050. The overall trend of climate change shows a water-stressed scenario. HIGHLIGHTS The study downscaled a CMIP6 GCM to evaluate the effect of climate change on rainfall.; The study conducts hydrological assessments to predict surface runoff for future scenarios.; The SDSM model, when subjected to statistical learning analysis, shows good performance in simulating rainfall values.; The study predicts a decrease in rainfall and runoff in the years 2030, 2040, and 2050.; Machine learning-boosted SDSM is a strong tool.;

Brain state classification by applying deep learning techniques on neuroimaging data has become a recent topic of research. However, unlike domains where the data is low dimensional or there are large number of available training samples, neuroimaging data is high dimensional and has few training samples. To tackle these issues, we present a sparse feedforward deep neural architecture for encoding and decoding the structural connectome of the human brain. We use a sparsely connected element-wise multiplication as the first hidden layer and a fixed transform layer as the output layer. The number of trainable parameters and the training time is significantly reduced compared to feedforward networks. We demonstrate superior performance of this architecture in encoding the structural connectome implicated in Alzheimer’s disease (AD) and Parkinson’s disease (PD) from DTI brain scans. For decoding, we propose recursive feature elimination (RFE) algorithm based on DeepLIFT, layer-wise relevance propagation (LRP), and Integrated Gradients (IG) algorithms to remove irrelevant features and thereby identify key biomarkers associated with AD and PD. We show that the proposed architecture reduces 45.1% and 47.1% of the trainable parameters compared to a feedforward DNN with an increase in accuracy by 2.6 % and 3.1% for cognitively normal (CN) vs AD and CN vs PD classification, respectively. We also show that the proposed RFE method leads to a further increase in accuracy by 2.1% and 4% for CN vs AD and CN vs PD classification, while removing approximately 90% to 95% irrelevant features. Furthermore, we argue that the biomarkers (i.e., key brain regions and connections) identified are consistent with previous literature. We show that relevancy score-based methods can yield high discriminative power and are suitable for brain decoding. We also show that the proposed approach led to a reduction in the number of trainable network parameters, an increase in classification accuracy, and a detection of brain connections and regions that were consistent with earlier studies.

The presence of small-sized (

The effect of carbohydrate source on nutrient digestibility, bile acid balance, faecal waste production and characteristics were investigated in yellowtail kingfish (Seriola lalandi). A starch diet and two non-starch polysaccharides (NSP) diets with different NSP sources were used in this study. A diet containing 12 % gelatinized wheat flour as the starch diet, and two diets with distinct non-starch polysaccharides (NSP) sources: soybean hulls (SH) and sugar beet pulp (SBP) at an inclusion level of 10 %, were studied. Each diet was tested in triplicate fish tanks. To determine if feeding level affects diet, restricted and satiation feeding levels were used. After four weeks of restrictive feeding, fish were fed satiation for two weeks. The dietary effect on nutrient digestibility and faecal waste production was dependent on feeding level, whereas the dietary effect on faecal waste characterises was independent of feeding level. SBP diet protein and fat digestibility was highest during restricted and satiation feeding. Satiation feeding reduced nutrient digestibility in all diets, most pronounced in SH and least in SBP. Faecal bile acid loss did not explain fat digestibility differences between the three diets. Both NSP diets increased faecal waste production but decreased bile acid content, resulting in similar bile acid loss to the starch diet. SBP had the highest faecal removal efficiency and the lowest non-removed faeces despite high waste production SH resulted in similar amount of non-removed faeces compared to the starch diet. To conclude, NSP type affected nutrient digestibility, bile acid balance, faecal waste production, and faecal characteristics differently than starch in yellowtail kingfish. Starch resulted in higher FCR and thus lower growth performance in yellowtail kingfish compared to NSP despite higher organic matter digestibility. Adding NSP to their RAS diet may improve faecal integrity without affecting macronutrient digestibility. However, different NSP forms affect nutrient digestion and faeces integrity differently.

Primary cardiac tumors are rare. The cardiac sarcomas are the most common malignant cardiac tumors. These tumors have a dismal prognosis with an overall median survival of 25 months. Clinical features include dyspnea, arrhythmias, pericardial effusions, heart failure, and sudden cardiac death. The diagnosis is often challenging. Therefore, the cardiac imaging workup plays a central role in addition to a high clinical suspicion in the setting of atypical presentations that do not respond to standard therapies. The echocardiography, computed tomography, and cardiac MRI are crucial in clinching the diagnosis. Multimodal treatment with surgery, chemotherapy, and radiotherapy has been shown to improve outcomes, as opposed to using either of these modalities alone. We describe the case of a 30-year-old gentleman with COVID-19 infection who developed recurrent hemorrhagic pericardial effusions refractory to standard treatment and was eventually diagnosed as a case of pericardial angiosarcoma after his biopsy revealed the diagnosis and staging was performed using PET–CT–FDG scan. Our case re-emphasizes the importance of considering a malignant etiology early in the course of the disease presentation, especially in recurrent hemorrhagic effusions despite an inflammatory cytologic diagnosis of fluid. It also highlights the place for cardiac CT and MRI to ascertain the location and spread and to plan the further course of treatment. If diagnosed early, the estimated survival time can be prolonged by instituting a multimodal approach.

Pyrolysis conversion offers the advantages of significant waste reduction and potential energy recovery. This work examined the potential of combining plastic and agricultural wastes as pyrolysis feedstocks. The mixture of waste low-density polyethylene and Pongamia pinnata seeds was analysed using differential and thermogravimetric methods. In addition to the Coats-Redfern (CR) method, Kissinger-Akahira-Sunose (KAS), Flynn-Wall-Ozawa (FWO), Friedman (FRM), and Kissinger (KN) model-free methods were also applied to calculate the kinetic parameters. The apparent activation energy (Ea) calculation demonstrated that the co-pyrolysis conversion required Ea values of 125–154 kJ mol−1. The artificial neural network (ANN) model was considered to validate thermogravimetric data. The R2 values were near unity in training, validation, and testing conditions, with the minimum possible value for mean square error obtained for the considered heating rates. The Pongamia pinnata seeds and waste plastic mixture could surely be utilized to lessen environmental degradation, add value to leftover seeds and waste low-density polyethylene by extracting fuel for transportation and other commercial activities, and produce industrial chemicals, as found through the kinetic modelling, thermodynamic parameters, and ANN modelling.

Yellowtail kingfish (Seriola lalandi), a marine species, has recently been cultured in recirculation aquaculture systems (RAS). A challenge regarding faecal waste management of farming yellowtail kingfish in RAS is their poor faecal integrity. One approach to improve faecal waste management is to enhance nutrient digestibility and thus faecal waste production, which can be achieved through the addition of emulsifiers to the feed. We assessed the effect of emulsifier supplementation on nutrient digestibility, bile acid balance, faecal waste production and characteristics of yellowtail kingfish. This was investigated by using four experimental diets differing in emulsifier supplementation, where fish were fed restrictively (36 days). One diet without emulsifying supplements served as control. Three types of emulsifiers were tested (1) E484, composed of Glyceryl polyethyleneglycol ricinoleate; (2) Lysophospholipids (LPL) combined with lecithin; (3) Sodium taurocholate (STC). The results showed that the STC diet numerically improved fat digestibility and had a positive bile acid balance, which indicated an accumulation of dietary bile acids in the body bile acid pool. Despite a negative bile acid balance, the LPL diet improved fat digestibility as well. A negative bile acid balance shows that the daily amount of faecal bile acid loss exceeds the daily amount of dietary bile acid intake. Fish fed the E484 diet had more faeces removed than the other diets, whilst non-recovered faeces or faecal characteristics were not affected. In conclusion, the current study shows that supplementing both sodium taurocholate (STC), and the combination of Lysophospholipids (LPL) and lecithin can improve fat digestibility in yellowtail kingfish, but emulsifier supplementation does not improve faecal waste management.

Currently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered a challenging task because of inappropriate features existing in the input data and the slow training process. In order to address these issues, an effective meta heuristic based feature selection and deep learning techniques are developed for enhancing the IDS. The Osprey Optimization Algorithm (OOA) based feature selection is proposed for selecting the highly informative features from the input which leads to an effective differentiation among the normal and attack traffic of network. Moreover, the traditional sigmoid and tangent activation functions are replaced with the Exponential Linear Unit (ELU) activation function to propose the modified Bi-directional Long Short Term Memory (Bi-LSTM). The modified Bi-LSTM is used for classifying the types of intrusion attacks. The ELU activation function makes gradients extremely large during back-propagation and leads to faster learning. This research is analysed in three different datasets such as N-BaIoT, Canadian Institute for Cybersecurity Intrusion Detection Dataset 2017 (CICIDS-2017), and ToN-IoT datasets. The empirical investigation states that the proposed framework obtains impressive detection accuracy of 99.98 %, 99.97 % and 99.88 % on the N-BaIoT, CICIDS-2017, and ToN-IoT datasets, respectively. Compared to peer frameworks, this framework obtains high detection accuracy with better interpretability and reduced processing time.

Background Essential to a patient‐centered approach to imaging individuals with chest pain is knowledge of differences in radiation effective dose across imaging modalities. Body mass index (BMI) is an important and underappreciated predictor of effective dose. This study evaluated the impact of BMI on estimated radiation exposure across imaging modalities. Methods and Results This was a retrospective analysis of patients with concern for cardiac ischemia undergoing positron emission tomography (PET)/computed tomography (CT), cadmium zinc telluride single‐photon emission CT (SPECT) myocardial perfusion imaging, or coronary CT angiography (CCTA) using state‐of‐the‐art imaging modalities and optimal radiation‐sparing protocols. Radiation exposure was calculated across BMI categories based on established cardiac imaging–specific conversion factors. Among 9046 patients (mean±SD age, 64.3±13.1 years; 55% men; mean±SD BMI, 30.6±6.9 kg/m2), 4787 were imaged with PET/CT, 3092 were imaged with SPECT/CT, and 1167 were imaged with CCTA. Median (interquartile range) radiation effective doses were 4.4 (3.9–4.9) mSv for PET/CT, 4.9 (4.0–6.3) mSv for SPECT/CT, and 6.9 (4.0–11.2) mSv for CCTA. Patients at a BMI 45 kg/m2 compared with

The protein-ligand interactions play critical roles in targeted therapies including viral and cancer therapies. Hence in recent years several experimental and computational methods have been developed to address the mechanism of selectivity, swift binding, and enzyme functions. Furthermore big data, neural networks and artificial intelligence techniques are becoming increasingly important while combinatorial and graph theoretical methods are important arms of such techniques. Experimental methods such as isothermal titration calorimetry and surface plasmon resonance are used frequently to measure the binding affinity. Some of the computational methods used to examine the protein-ligand interactions are electrostatic calculations, molecular dynamics simulation, hybrid dynamics methods, etc., which shed light on structural stability, binding, protein functions etc. In this review we describe applications of a few selected experimental, computational and artificial intelligence tools with focus on graph theory to predict protein-ligand, metal-ligand interactions with implications in various types of malignancies and computational toxicology with focus on protein-heavy metal ion interactions and complexes of heavy metal ions with various ligands of biomedical relevance.

AbstractWe comprised metabolites of gut microbiota (GM; endogenous species) and dietary plant-derived natural flavonoids (DPDNFs; exogenous species) were known as potent effectors against non-alcoholic fatty liver disease (NAFLD) via network pharmacology (NP). The crucial targets against NAFLD were identified via GM and DPDNFs. The protein interaction (PPI), bubble chart and networks of GM or natural products- metabolites-targets-key signalling (GNMTK) pathway were described via R Package. Furthermore, the molecular docking test (MDT) to verify the affinity was performed between metabolite(s) and target(s) on a key signalling pathway. On the networks of GNMTK, Enterococcus sp. 45, Escherichia sp.12, Escherichia sp.33 and Bacterium MRG-PMF-1 as key microbiota; flavonoid-rich products as key natural resources; luteolin and myricetin as key metabolites (or dietary flavonoids); AKT Serine/Threonine Kinase 1 (AKT1), CF Transmembrane conductance Regulator (CFTR) and PhosphoInositide-3-Kinase, Regulatory subunit 1 (PIK3R1) as key targets are promising components to treat NAFLD, by suppressing cyclic Adenosine MonoPhosphate (cAMP) signalling pathway. This study shows that components (microbiota, metabolites, targets and a key signalling pathway) and DPDNFs can exert combinatorial pharmacological effects against NAFLD. Overall, the integrated pharmacological approach sheds light on the relationships between GM and DPDNFs.

AbstractWe intended to identify favourable metabolite(s) and pharmacological mechanism(s) of gut microbiota (GM) for liver regeneration (LR) through network pharmacology. We utilized the gutMGene database to obtain metabolites of GM, and targets associated with metabolites as well as LR-related targets were identified using public databases. Furthermore, we performed a molecular docking assay on the active metabolite(s) and target(s) to verify the network pharmacological concept. We mined a total of 208 metabolites in the gutMGene database and selected 668 targets from the SEA (1,256 targets) and STP (947 targets) databases. Finally, 13 targets were identified between 61 targets and the gutMGene database (243 targets). Protein–protein interaction network analysis showed that AKT1 is a hub target correlated with 12 additional targets. In this study, we describe the potential microbe from the microbiota (E. coli), chemokine signalling pathway, AKT1 and myricetin that accelerate LR, providing scientific evidence for further clinical trials.

Abstract The outer membrane (OM) in diderm, or Gram-negative, bacteria must be tethered to peptidoglycan for mechanical stability and to maintain cell morphology. Most diderm phyla from the Terrabacteria group have recently been shown to lack well-characterised OM attachment systems, but instead have OmpM, which could represent an ancestral tethering system in bacteria. Here, we have determined the structure of the most abundant OmpM protein from Veillonella parvula (diderm Firmicutes) by single particle cryogenic electron microscopy. We also characterised the channel properties of the transmembrane β-barrel of OmpM and investigated the structure and PG-binding properties of its periplasmic stalk region. Our results show that OM tethering and nutrient acquisition are genetically linked in V. parvula, and probably other diderm Terrabacteria. This dual function of OmpM may have played a role in the loss of the OM in ancestral bacteria and the emergence of monoderm bacterial lineages.

Abstract We have synthesized carbon nanoparticles using mandarin juice via green synthesis rout. We have doped carbon nanoparticles in liquid crystal media and studied the surface effect on self-assembly of carbon nanoclusters on ITO coated glass surface and on graphene sheet. The purpose of this study is to construct uniform nano-micro droplets for novel applications and to understand and explore the underlying science behind molecular scale reorganization in the presence of functional surfaces like graphene. We have used density functional theory approach to confirm that the carbon nanoparticles in globular structures are dispersed in presence of graphene sheet due to chemical interaction of carbon rings (or say carbon nanoparticles) with graphene carbon atoms. In order to minimize the free energy, the carbon nanoparticles leave the carbon globular structures and are dispersed to form rectangular structures in presence of LC media at graphene surface. The carbon nanoparticles are dispersed to increase contact area with graphene surface. The results are useful in construction of desired nano-micro structures for possible novel purposes in medical field since carbon nanoparticles are biocompatible. Optical microscopy, FESEM, NMR and UV spectra verifies the droplet formation and its effect on the surface and electronic properties of carbon nanoparticles.

Synchronization capability of two identical chaotic systems can be used for constructing the secure communication systems where the chaotic signal is used as the information carrier. In this paper, a secure communication system is designed by using the bi-directionally synchronized identical Chua’s circuits in LC parallel coupling. LC parallel circuit is used as the new coupling element instead of using a single resistor or capacitor or inductor as the coupling element. This makes the complete synchronization of Chua’s circuits possible for many different sets of coupling inductance and capacitance values so that the flexibility of constructing the secure communication systems is realized. Both the synchronized Chua’s circuits in LC parallel coupling and the corresponding secure communication system are constructed by using the LTspice software. The simulation results show that the secure communication system proposed in the present paper is very efficient for the message transmission for different pairs of coupling inductance and coupling capacitance values where the complete synchronization of Chua’s circuits is observed occur. The two essential properties of an ideal secure communication system - perfect message masking and recovery are observed when compared to other secure communication systems already proposed and constructed previously. So, the simulation results of the present study can be used for practically constructing the efficient communication systems in future.

While monoclonal antibodies have shown success in cancer immunotherapy, their limitations prompt exploration of alternative approaches such as aptamers and peptides targeting programmed death ligand 1 (PD-L1). Despite the significance of these biotechnological tools, a comprehensive review encompassing both aptamers and peptides for PD-L1 targeting is lacking. Addressing this gap is crucial for consolidating recent advancements and insights in this field. Biotechnological advances leveraging aptamers and peptides represent a cutting-edge approach in refining the targeting proteins. Our review aims to provide valuable guidance for researchers and clinicians, highlighting the biotechnological advances utilizing aptamers and peptides refining PD-L1 targeting.

Abstract Peste des petits ruminants (PPR) is an infectious viral disease, primarily of small ruminants such as sheep and goats, but is also known to infect a wide range of wild and domestic Artiodactyls including African buffalo, gazelle, saiga and camels. The livestock-wildlife interface, where free-ranging animals can interact with captive flocks, is the subject of scrutiny as its role in the maintenance and spread of PPR virus (PPRV) is poorly understood. As seroconversion to PPRV indicates previous infection and/or vaccination, the availability of validated serological tools for use in both typical (sheep and goat) and atypical species is essential to support future disease surveillance and control strategies. The virus neutralisation test (VNT) and enzyme-linked immunosorbent assay (ELISA) have been validated using sera from typical host species. Still, the performance of these assays in detecting antibodies from atypical species remains unclear. We examined a large panel of sera (n = 793) from a range of species from multiple countries (sourced 2015–2022) using three tests: VNT, ID VET N-ELISA and AU-PANVAC H-ELISA. A sub-panel (n = 30) was also distributed to two laboratories and tested using the luciferase immunoprecipitation system (LIPS) and a pseudotyped virus neutralisation assay (PVNA). We demonstrate a 75.0–88.0% agreement of positive results for detecting PPRV antibodies in sera from typical species between the VNT and commercial ELISAs, however this decreased to 44.4–62.3% in sera from atypical species, with an inter-species variation. The LIPS and PVNA strongly correlate with the VNT and ELISAs for typical species but vary when testing sera from atypical species.

Introduction: The knowledge of clinicians regarding blood transfusion services may impact patient care and transfusion outcome. The wide variation in transfusion practices among clinicians leads to inappropriate blood product usage and jeopardizes patient safety. Hence, this survey study aimed to assess knowledge, attitude and practice among the residents and interns of safe blood transfusion. Methods: The online survey was based on self-administered questionnaires of three sections: 1. Demography; 2. Knowledge, and; 3. Attitude and Practice. One point was assigned for the correct response of each question in every section. The knowledge score was further categorized into three categories, depending on the points obtained. The participants were also divided into four groups, depending on their experience. The Kruskal-Wallis test was applied to determine the difference of knowledge and practice scores in three designated groups of residents and interns. A p-value of less than 0.05 was considered to be significant. Result: A total of 247 residents and interns participated in this study. Thirteen participants had an incomplete response. Out of 234 participants, Senior Residents (SR), Junior Residents (JR), and interns were 70, 96 and 68 participants, respectively. The knowledge scores of interns were significantly low, as compared to SRs and JRs. Practice scores of interns were also significantly low, compared to the JRs. However, most of the residents and interns (85%) were aware of the pre-transfusion testing. Conclusion: Therefore, the mandatory incorporation of the transfusion medicine subject in the undergraduate curriculum can help the young budding doctors to better implement the patient blood management.

Abstract Persea americana fruit (PAF) is a favorable nutraceutical resource that comprises diverse unsaturated fatty acids (UFAs). UFAs are significant dietary supplementation, as they relieve metabolic disorders, including obesity (OB). In another aspect, this study was focused on the anti‐OB efficacy of the non‐fatty acids (NFAs) in PAF through network pharmacology (NP). Natural product activity & species source (NPASS), SwissADME, similarity ensemble approach (SEA), Swiss target prediction (STP), DisGeNET, and online Mendelian inheritance in man (OMIM) were utilized to gather significant molecules and its targets. The crucial targets were adopted to construct certain networks: protein–protein interaction (PPI), PAF‐signaling pathways‐targets‐compounds (PSTC) networks, a bubble chart, molecular docking assay (MDA), and density function theory (DFT). Finally, the toxicities of the key compounds were validated by ADMETlab 2.0 platform. All 41 compounds in PAF conformed to Lipinski's rule, and the key 31 targets were identified between OB and PAF. On the bubble chart, PPAR signaling pathway had the highest rich factor, suggesting that the pathway might be an agonism for anti‐OB. Conversely, estrogen signaling pathway had the lowest rich factor, indicating that the mechanism might be antagonism against OB. Likewise, the PSTC network represented that AKT1 had the greatest degree value. The MDA results showed that AKT1‐gamma‐tocopherol, PPARA‐fucosterol, PPARD‐stigmasterol, (PPARG)‐fucosterol, (NR1H3)‐campesterol, and ILK‐alpha‐tocopherol formed the most stable conformers. The DFT represented that the five molecules might be promising agents via multicomponent targeting. Overall, this study suggests that the NFAs in PAF might play important roles against OB.

Signal regulatory protein-α (SIRPα, SHPS-1, CD172a) expressed on myeloid cells transmits inhibitory signals when it engages its counter-receptor CD47 on an adjacent cell. Elevated CD47 expression on some cancer cells thereby serves as an innate immune checkpoint that limits phagocytic clearance of tumor cells by macrophages and antigen presentation to T cells. Antibodies and recombinant SIRPα constructs that block the CD47-SIRPα interaction on macrophages exhibit anti-tumor activities in mouse models and are in ongoing clinical trials for treating several human cancers. Based on prior evidence that engaging SIRPα can also alter CD47 signaling in some nonmalignant cells, we compared direct effects of recombinant SIRPα-Fc and a humanized CD47 antibody that inhibits CD47-SIRPα interaction (CC-90002) on CD47 signaling in cancer stem cells derived from the MDA-MB- 231 triple-negative breast carcinoma cell line. Treatment with SIRPα-Fc significantly increased the formation of mammospheres by breast cancer stem cells as compared to CC-90002 treatment or controls. Furthermore, SIRPα-Fc treatment upregulated mRNA and protein expression of ALDH1 and altered the expression of genes involved in epithelial/mesenchymal transition pathways that are associated with a poor prognosis and enhanced metastatic activity. This indicates that SIRPα-Fc has CD47-mediated agonist activities in breast cancer stem cells affecting proliferation and metastasis pathways that differ from those of CC-90002. This SIRPα-induced CD47 signaling in breast carcinoma cells may limit the efficacy of SIRPα decoy therapeutics intended to stimulate innate antitumor immune responses.

Purpose Soil fertility management requires a precise assessment of nutrient release from organic amendments to decide the rates and frequency of application. Method Time-dependent release of some macro- and micro-nutrients from farmyard manure, mushroom compost, poultry manure, vermi-compost, biogas slurry and biochar of Lantana sp. was studied during 120 days incubation through entrapment of released nutrients on ion exchange resins. Results Highest total concentration of K, Ca, Mg and S was in farmyard manure, Fe and Mn in mushroom compost, P, Zn and Cu in biogas slurry and B in biochar. Farmyard manure had the highest C:N ratio (34.2), while other organic amendment had C:N ratioâ

The paper traces the origin of the Middle East conflict and discusses the gradual evolution of the Israel-Palestine conflict from a historical perspective. The paper discusses the peace negotiations undertaken for the region during different periods and the contribution of the international community in reaching a compromise formula. The paper discusses the emergence and the role of Hamas and how it gained political legitimacy. The paper concludes with the views of Israel and India perspective.

Textile dye effluents have been reported for many deleterious effects; therefore, it is essential to remove before releasing into waterbodies. A two-step agro-waste-based technology for the remediation of a textile dye Lanasyn olive was developed in this study. The first step involved the chemical modification of agro-waste sugarcane bagasse (SCB) with a natural acid (alginic acid). The modified SCB was used for the column bed preparation and adsorptive removal of the dye. In the second step, SCB used for dye removal was decolorized through a fungus Pleurotus sp. to produce a dye-free SCB with a potential for application as manure. To evaluate the efficacy of the column device, parameters like removal percentage, and adsorption capacity were determined. There was 90% removal of dye in aqueous dye solution and 83% removal in dye spiked textile industry effluent. To comprehend the column properties, three non-equilibrium models—Thomas, Yoon-Nelson, and Adams-Bohart—were used. Among the models applied, Adams-Bohart fitted well with the obtained data. Dye bioremediation efficiency by Pleurotus sp. was assessed by studying the deviation in absorption maxima, dye decolorization on the agar plate, Fourier-transform infrared spectroscopy (FTIR). The fungus-treated SCB showed no signs of residual toxicity towards alga Chlorella vulgaris. The carbon, hydrogen, nitrogen, sulfur (CHNS) profile examination of spent SCB revealed significantly improved nitrogen content after the treatment (from 0.35% to 0.69%). The prototype of the column, chemical valorization of SCB, and degradation of dye-adsorbed SCB through Pleurotus sp. provides a green solution for the safe disposal of textile dye through a novel agro waste-based treatment process.