An RNAi screen to identify proteins required for cohesion rejuvenation during meiotic prophase in Drosophila oocytes.

Accurate chromosome segregation during meiosis requires maintenance of sister chromatid cohesion, initially established during premeiotic S phase. In human oocytes, DNA replication and cohesion establishment occur decades before chromosome segregation and deterioration of meiotic cohesion is one factor that leads to increased segregation errors as women age. Our previous work led us to propose that a cohesion rejuvenation program operates to establish new cohesive linkages during meiotic prophase in Drosophila oocytes and depends on the cohesin loader Nipped-B and the cohesion establishment factor Eco. In support of this model, we recently demonstrated that chromosome-associated cohesin turns over extensively during meiotic prophase and failure to load cohesin onto chromosomes after premeiotic S phase results in arm cohesion defects in Drosophila oocytes. To identify proteins required for prophase cohesion rejuvenation but not S phase establishment, we conducted a Gal4-UAS inducible RNAi screen that utilized two distinct germline drivers. Using this strategy, we identified 29 gene products for which hairpin expression during meiotic prophase, but not premeiotic S phase, significantly increased segregation errors. Prophase knockdown of Brahma or Pumilio, two positives with functional links to the cohesin loader, caused a significant elevation in the missegregation of recombinant homologs, a phenotype consistent with premature loss of arm cohesion. Moreover, fluorescence in situ hybridization confirmed that Brahma, Pumilio and Nipped-B are required during meiotic prophase for maintenance of arm cohesion. Our data support the model that Brahma and Pumilio regulate Nipped-B dependent cohesin loading during rejuvenation. Future analyses will better define the mechanism(s) that govern meiotic cohesion rejuvenation and whether additional prophase-specific positives function in this process.

Discovery of Novel Small Molecule Dual Inhibitor Targeting Toll-Like Receptors 7 and 9.

The aberrant secretion of proinflammatory cytokines by immune cells is the principal cause of inflammatory diseases, such as systemic lupus erythematosus and rheumatoid arthritis. Toll-like receptor 7 (TLR7) and TLR9, sequestered to the endosomal compartment of dendritic cells and macrophages, are closely associated with the initiation and progression of these diseases. Therefore, the development of drugs targeting dysregulated endosomal TLRs is imperative to mitigate systemic inflammation. Here, we applied the principles of computer-aided drug discovery to identify a novel low-molecular-weight compound, TLR inhibitory compound 10 (TIC10), and its potent derivative (TIC10g), which demonstrated dual inhibition of TLR7 and TLR9 signaling pathways. Compared to TIC10, TIC10g exhibited a more pronounced inhibition of the TLR7- and TLR9-mediated secretion of the proinflammatory cytokine tumor necrosis factor-α in a mouse macrophage cell line and mouse bone marrow dendritic cells in a concentration-dependent manner. While TIC10g slightly prevented TLR3 and TLR8 activation, it had no impact on cell surface TLRs (TLR1/2, TLR2/6, TLR4, or TLR5), indicating its selectivity for TLR7 and TLR9. Additionally, mechanistic studies suggested that TIC10g interfered with TLR9 activation by CpG DNA and suppressed downstream pathways by directly binding to TLR9. Western blot analysis revealed that TIC10g downregulated the phosphorylation of the p65 subunit of nuclear factor κ-light-chain-enhancer of activated B cells (NF-κB) and mitogen-activated protein kinases (MAPKs), including extracellular-signal-regulated kinase, p38-MAPK, and c-Jun N-terminal kinase. These findings indicate that the novel ligand, TIC10g, is a specific dual inhibitor of endosomal TLRs (TLR7 and TLR9), disrupting MAPK- and NF-κB-mediated proinflammatory gene expression.

Chromatin-associated cohesin turns over extensively and forms new cohesive linkages in Drosophila oocytes during meiotic prophase.

In dividing cells, accurate chromosome segregation depends on sister chromatid cohesion, protein linkages that are established during DNA replication. Faithful chromosome segregation in oocytes requires that cohesion, first established in S phase, remain intact for days to decades, depending on the organism. Premature loss of meiotic cohesion in oocytes leads to the production of aneuploid gametes and contributes to the increased incidence of meiotic segregation errors as women age (maternal age effect). The prevailing model is that cohesive linkages do not turn over in mammalian oocytes. However, we have previously reported that cohesion-related defects arise in Drosophila oocytes when individual cohesin subunits or cohesin regulators are knocked down after meiotic S phase. Here, we use two strategies to express a tagged cohesin subunit exclusively during mid-prophase in Drosophila oocytes and demonstrate that newly expressed cohesin is used to form de novo linkages after meiotic S phase. Cohesin along the arms of oocyte chromosomes appears to completely turn over within a 2-day window during prophase, whereas replacement is less extensive at centromeres. Unlike S-phase cohesion establishment, the formation of new cohesive linkages during meiotic prophase does not require acetylation of conserved lysines within the Smc3 head. Our findings indicate that maintenance of cohesion between S phase and chromosome segregation in Drosophila oocytes requires an active cohesion rejuvenation program that generates new cohesive linkages during meiotic prophase.

Vibration assisted electron tunnelling in COVID-19 infection using quantum state diffusion.

The spread of the COVID-19 virus has become a global health crisis, and finding effective treatments and preventions is a top priority. The field of quantum biology primarily focuses on energy or charge transfer, with a particular emphasis on photosynthesis. However, there is evidence to suggest that cellular receptors such as olfactory or neural receptors may also use vibration-assisted electron tunnelling to enhance their functions. Quantum tunnelling has also been observed in enzyme activity, which is relevant to the invasion of host cells by the SARS-CoV-2 virus. Additionally, COVID-19 appears to disrupt receptors such as olfactory receptors. These findings suggest that quantum effects could provide new insights into the mechanisms of biological systems and disease, including potential treatments for COVID-19. We have applied the open quantum system approach using Quantum State Diffusion to solve the non-linear stochastic Schrödinger equation (SSE) for COVID-19 virus infection. Our model includes the mechanism when the spike protein of the virus binds with an ACE2 receptor is considered as dimer. These two entities form a system and then coupled with the cell membrane, which is modelled as a set of harmonic oscillators (bath). By simulating the SSE, we find that there is vibration-assisted electron tunnelling happening in certain biological parameters and coupling regimes. Furthermore, our model contributes to the ongoing research to understand the fundamental nature of virus dynamics. It proposes that vibration-assisted electron tunneling could be a molecular phenomenon that augments the lock-and-key process for olfaction. This insight may enhance our understanding of the underlying mechanisms governing virus-receptor interactions and could potentially lead to the development of novel therapeutic strategies.

A superabsorbent and pH-responsive copolymer-hydrogel based on acemannan from Aloe vera (Aloe barbadensis M.): A smart material for drug delivery.

Combining natural polysaccharides with synthetic materials improves their functional properties which are essential for designing sustained-release drug delivery systems. In this context, the Aloe vera leaf mucilage/hydrogel (ALH) was reacted with acrylic acid (AA) to synthesize a copolymerized hydrogel, i.e., ALH-grafted-Polyacrylic acid (ALH-g-PAA) through free radical copolymerization. Concentrations of the crosslinker N,N'-methylene-bis-acrylamide (MBA), and the initiator potassium persulfate (KPS) were optimized to study their effects on ALH-g-PAA swelling. The FTIR and solid-state NMR (CP/MAS 13C NMR) spectra witnessed the formation of ALH-g-PAA. Scanning electron microscopy (SEM) analysis revealed superporous nature of ALH-g-PAA. The gel fraction (%) of ALH-g-PAA was directly related to the concentrations of AA and MBA whereas the sol fraction was inversely related to the concentrations of AA and MBA. The porosity (%) of ALH-g-PAA directly depends on the concentration of AA and MBA. The ALH-g-PAA swelled admirably at pH 7.4 and insignificantly at pH 1.2. The ALH-g-PAA offered on/off switching properties at pH 7.4/1.2. The metoprolol tartrate was loaded on different formulations of ALH-g-PAA. The ALH-g-PAA showed pH, time, and swelling-dependent release of metoprolol tartrate (MT) for 24 h following the first-order kinetic and Korsmeyer-Peppas model. Haemocompatibility studies ascertained the non-thrombogenic and non-hemolytic behavior of ALH-g-PAA.

Semaglutide vs Endoscopic Sleeve Gastroplasty for Weight Loss.

Importance: Obesity is a disease with a large socioeconomic burden. Endoscopic sleeve gastroplasty (ESG) is a minimally invasive endoscopic bariatric procedure with wide global adoption. More recently, new weight-loss medications, such as glucagon-like peptide-1 receptor agonists (eg, semaglutide), have attracted increased attention due to their efficacy. However, their cost-effectiveness over an extended period compared with ESG is a critical gap that needs to be better explored for informed health care decision-making. Objective: To assess the cost-effectiveness of semaglutide compared with ESG over 5 years for individuals with class II obesity. Design, Setting, and Participants: This economic evaluation study, conducted from September 1, 2022, to May 31, 2023, used a Markov cohort model to compare ESG and semaglutide, with a no-treatment baseline strategy. The study comprised adult patients in the US health care system with class II obesity (body mass index [BMI] of 35-39.9). The base case was a 45-year-old patient with class II obesity (BMI of 37). Patients undergoing ESG were subjected to risks of perioperative mortality and adverse events with resultant costs and decrement in quality of life. Interventions: Strategies included treatment with semaglutide and ESG. Main Outcomes and Measures: Costs (2022 US dollars), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) with a willingness-to-pay threshold of $100 000/QALY. A 5-year time horizon with a cycle length of 1 month with a 3% discount rate was used. Probabilities, costs, and quality-of-life estimates of the model were derived from published literature. One-way, 2-way, and probabilistic sensitivity analyses were also performed. Results: The model found that ESG was more cost-effective than semaglutide over a 5-year time horizon, with an ICER of -$595 532/QALY. Endoscopic sleeve gastroplasty added 0.06 QALYs and reduced total cost by $33 583 relative to semaglutide. The results remained robust on 1-way and probabilistic sensitivity analyses. Endoscopic sleeve gastroplasty sustained greater weight loss over 5 years vs semaglutide (BMI of 31.7 vs 33.0). To achieve nondominance, the annual price of semaglutide, currently $13 618, would need to be $3591. Conclusions and Relevance: This study suggests that ESG is cost saving compared with semaglutide in the treatment of class II obesity. On price threshold analyses, a 3-fold decrease in the price of semaglutide is needed to achieve nondominance.

Citric acid cross-linking of a hydrogel from Aloe vera (Aloe barbadensis M.) engenders a pH-responsive, superporous, and smart material for drug delivery.

The current research work is based on the evaluation of a citric acid (CA) cross-linked Aloe vera (Aloe barbadensis M.) leaf hydrogel (CL-ALH) for pH-dependent and sustained drug release application. The CA was used in different concentrations (1.25, 2.5, 5.0, and 10.0%) to cross-link the ALH using homogenous reaction conditions. The synthesis of CL-ALH was confirmed through Fourier transform and nuclear magnetic resonance spectroscopic studies. The thermal analysis indicated that the ALH and CL-ALH were stable and decomposed in two steps. The scanning electron microscopic images of CL-ALH confirmed its porous nature due to the presence of interconnected channeling. The swelling of CL-ALH was evaluated at pH 1.2, 6.8, and 7.4 as well as in deionized water (DW). High swelling of CL-ALH was observed in DW, and at pH 7.4 and 6.8 whereas, less swelling of CL-ALH was witnessed at pH 1.2. CL-ALH also exhibited swelling/deswelling behavior in DW and ethanol, DW and normal saline, and at pH 7.4 and 1.2. Tablets were prepared from CL-ALH as a release retarding agent demonstrating the sustained release of venlafaxine hydrochloride (VFX) for 8 h. Whereas, VFX was released within 4 h from the ALH-based tablet formulation (un-cross-linked material) indicating the prolonged and sustained release behavior of CL-ALH. The VFX was released from CL-ALH tablets and followed zero-order kinetics. The mechanism followed by VFX release from CL-ALH tablets was non-Fickian diffusion. The in vivo fate of the tablet formulation was observed through an X-ray study. The CL-ALH-based tablet safely passed through the stomach of a stray dog without any significant erosion and then disintegrated in the small intestine and colon. These findings confirmed that the CL-ALH is an effective excipient for designing a sustained-release drug delivery system for the small intestine and colon.

Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses.

The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.

Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases.

Electrocardiography (ECG), improved by artificial intelligence (AI), has become a potential technique for the precise diagnosis and treatment of cardiovascular disorders. The conventional ECG is a frequently used, inexpensive, and easily accessible test that offers important information about the physiological and anatomical state of the heart. However, the ECG can be interpreted differently by humans depending on the interpreter's level of training and experience, which could make diagnosis more difficult. Using AI, especially deep learning convolutional neural networks (CNNs), to look at single, continuous, and intermittent ECG leads that has led to fully automated AI models that can interpret the ECG like a human, possibly more accurately and consistently. These AI algorithms are effective non-invasive biomarkers for cardiovascular illnesses because they can identify subtle patterns and signals in the ECG that may not be readily apparent to human interpreters. The use of AI in ECG analysis has several benefits, including the quick and precise detection of problems like arrhythmias, silent cardiac illnesses, and left ventricular failure. It has the potential to help doctors with interpretation, diagnosis, risk assessment, and illness management. Aside from that, AI-enhanced ECGs have been demonstrated to boost the identification of heart failure and other cardiovascular disorders, particularly in emergency department settings, allowing for quicker and more precise treatment options. The use of AI in cardiology, however, has several limitations and obstacles, despite its potential. The effective implementation of AI-powered ECG analysis is limited by issues such as systematic bias. Biases based on age, gender, and race result from unbalanced datasets. A model's performance is impacted when diverse demographics are inadequately represented. Potentially disregarded age-related ECG variations may result from skewed age data in training sets. ECG patterns are affected by physiological differences between the sexes; a dataset that is inclined toward one sex may compromise the accuracy of the others. Genetic variations influence ECG readings, so racial diversity in datasets is significant. Furthermore, issues such as inadequate generalization, regulatory barriers, and interpretability concerns contribute to deployment difficulties. The lack of robustness in models when applied to disparate populations frequently hinders their practical applicability. The exhaustive validation required by regulatory requirements causes a delay in deployment. Difficult models that are not interpretable erode the confidence of clinicians. Diverse dataset curation, bias mitigation strategies, continuous validation across populations, and collaborative efforts for regulatory approval are essential for the successful deployment of AI ECG in clinical settings and must be undertaken to address these issues. To guarantee a safe and successful deployment in clinical practice, the use of AI in cardiology must be done with a thorough understanding of the algorithms and their limits. In summary, AI-enhanced electrocardiography has enormous potential to improve the management of cardiovascular illness by delivering precise and timely diagnostic insights, aiding clinicians, and enhancing patient outcomes. Further study and development are required to fully realize AI's promise for improving cardiology practices and patient care as technology continues to advance.

A versatile dataset for intrinsic plagiarism detection, text reuse analysis, and author clustering in Urdu.

Plagiarism detection (PD) is a process of identifying instances where someone has presented another person's work or ideas as their own. Plagiarism detection is categorized into two types (i) Intrinsic plagiarism detection primarily concerns the assessment of authorship consistency within a single document, aiming to identify instances where portions of the text may have been copied or paraphrased from elsewhere within the same document. Author clustering, closely related to intrinsic plagiarism detection, involves grouping documents based on their stylistic and linguistic characteristics to identify common authors or sources within a given dataset. On the other hand, (ii) extrinsic plagiarism detection delves into the comparative analysis of a suspicious document against a set of external source documents, seeking instances of shared phrases, sentences, or paragraphs between them, which is often referred to as text reuse or verbatim copying. Detection of plagiarism from documents is a long-established task in the area of NLP with remarkable contributions in multiple applications. A lot of research has already been conducted in the English and other foreign languages but Urdu language needs a lot of attention especially in intrinsic plagiarism detection domain. The major reason is that Urdu is a low resource language and unfortunately there is no high-quality benchmark corpus available for intrinsic plagiarism detection in Urdu language. This study presents a high-quality benchmark Corpus comprising 10,872 documents. The corpus is structured into two granularity levels: sentence level and paragraph level. This dataset serves multifaceted purposes, facilitating intrinsic plagiarism detection, verbatim text reuse identification, and author clustering in the Urdu language. Also, it holds significance for natural language processing researchers and practitioners as it facilitates the development of specialized plagiarism detection models tailored to the Urdu language. These models can play a vital role in education and publishing by improving the accuracy of plagiarism detection, effectively addressing a gap and enhancing the overall ability to identify copied content in Urdu writing.

Adjuvant Radiofrequency Ablation Along With Stenting Versus Stenting Alone for Biliary Tree Drainage in Patients With Malignant Biliary Strictures: A Systemic Review and Meta-analysis.

OBJECTIVE: This metanalysis aims to assess the efficacy and safety of biliary stenting along with radiofrequency ablation compared with stents alone to treat malignant biliary obstruction (MBO) due to extrahepatic biliary strictures secondary to cholangiocarcinoma, pancreatic cancer, and metastatic cancer. METHODS: A systemic search of major databases through April 2022 was done. All original studies were included comparing radiofrequency ablation with stenting versus stenting alone for treating malignant biliary strictures. The primary outcomes of interest were the difference in the mean stent patency and overall survival (OS) days between the 2 groups. The secondary outcome was to compare the adverse events of the 2 groups. The mean difference in the stent patency and OS days was pooled by using a random-effect model. We calculated the odds ratio to compare the adverse events between the 2 groups. RESULTS: A total of 13 studies with 1339 patients were identified. The pooled weighted mean difference in stent patency was 43.50 days (95% CI, 25.60-61.41), favoring the RFA plus stenting. Moreover, the pooled weighted mean difference in OS was 90.53 days (95% CI, 49.00-132.07), showing improved survival in the RFA group. Our analysis showed no statistically significant difference in adverse events between the 2 groups OR 1.13 (95% CI, 0.90-1.42). CONCLUSION: Our analysis showed that RFA, along with stent, is safe and is associated with improved stent patency and overall patient survival in malignant biliary strictures. More robust prospective studies should assess this association further.

The European Nucleotide Archive in 2023.

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena) is maintained by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI). The ENA is one of the three members of the International Nucleotide Sequence Database Collaboration (INSDC). It serves the bioinformatics community worldwide via the submission, processing, archiving and dissemination of sequence data. The ENA supports data types ranging from raw reads, through alignments and assemblies to functional annotation. The data is enriched with contextual information relating to samples and experimental configurations. In this article, we describe recent progress and improvements to ENA services. In particular, we focus upon three areas of work in 2023: FAIRness of ENA data, pandemic preparedness and foundational technology. For FAIRness, we have introduced minimal requirements for spatiotemporal annotation, created a metadata-based classification system, incorporated third party metadata curations with archived records, and developed a new rapid visualisation platform, the ENA Notebooks. For foundational enhancements, we have improved the INSDC data exchange and synchronisation pipelines, and invested in site reliability engineering for ENA infrastructure. In order to support genomic surveillance efforts, we have continued to provide ENA services in support of SARS-CoV-2 data mobilisation and have adapted these for broader pathogen surveillance efforts.

Safety and adverse events of EUS-guided gallbladder drainage using lumen-apposing metal stents and percutaneous cholecystostomy tubes: a systematic review and meta-analysis.

BACKGROUND AND AIMS: EUS-guided gallbladder drainage using lumen-apposing metal stents (EUS-GBD-LAMSs) and percutaneous cholecystostomy for gallbladder drainage (PTGBD) are the alternative treatment modalities in high-risk surgical patients with acute cholecystitis (AC). The aim of this study was to compare the safety of these procedures for AC in surgically suboptimal candidates. METHODS: Six studies compared the 2 groups' early, delayed, and overall adverse events; they also compared length of hospital stay, re-interventions, and re-admissions rate. A random effect model calculated odds ratios (ORs) with a 95% confidence interval (CI). RESULTS: The 2 groups had similar early adverse events; however, EUS-GBD-LAMS was associated with a lower rate of delayed (OR, .21; 95% CI, .07-.61; P ≤ .01) and overall (OR, .43; 95% CI, .30-.61; P ≤ .01) adverse events. Patients with EUS-GBD-LAMSs had a shorter hospital stay than PTGBD. CONCLUSIONS: EUS-GBD-LAMS is a safer option than PTGBD and is associated with a shorter hospital stay in nonsurgical candidates with AC.

Fabrication and optimization of febuxostat-loaded chitosan nanocarriers for better pharmacokinetics profile.

The current research was planned to enhance the bioavailability of hydrophobic drug after oral administration through the development of a nanoparticle drug delivery system (DDS). Therefore, febuxostat-loaded chitosan nanoparticles (FLC NPs) were prepared using a modified ionic gelation method and optimized the reaction conditions through the design of experiments. Design expert software was used to check the desirability of the central composite design and the interactive effects of the independent variables (chitosan concentration, ratio of chitosan to linker, and pH of the medium) on the response variables (size distribution, zeta potential, polydispersity index (PDI), and entrapment efficiency (EE)) of FLC NPs. All ingredients of the optimized formulation (formulation Q) were compatible with each other as evident from FTIR, PXRD, and TGA studies, and displayed 234.7 nm particle size, 0.158 PDI, 25.8 mV zeta potential, and 76.9 % EE. TEM, SEM, and AFM exhibited a smooth, dense, and uniform structure without any visible pores in the structure of FLC NPs. The in vitro and in vivo drug release studies described a sustained release pattern of febuxostat and increased relative bioavailability by 286.63 %. Considering these findings, this chitosan nanoparticle DDS can further be used for improving the EE and bioavailability of hydrophobic drugs.

Mask exhibits trxG-like behavior and associates with H3K27ac marked chromatin.

The Trithorax group (trxG) proteins counteract the repressive effect of Polycomb group (PcG) complexes and maintain transcriptional memory of active states of key developmental genes. Although chromatin structure and modifications appear to play a fundamental role in this process, it is not clear how trxG prevents PcG-silencing and heritably maintains an active gene expression state. Here, we report a hitherto unknown role of Drosophila Multiple ankyrin repeats single KH domain (Mask), which emerged as one of the candidate trxG genes in our reverse genetic screen. The genome-wide binding profile of Mask correlates with known trxG binding sites across the Drosophila genome. In particular, the association of Mask at chromatin overlaps with CBP and H3K27ac, which are known hallmarks of actively transcribed genes by trxG. Importantly, Mask predominantly associates with actively transcribed genes in Drosophila. Depletion of Mask not only results in the downregulation of trxG targets but also correlates with diminished levels of H3K27ac. The fact that Mask positively regulates H3K27ac levels in flies was also found to be conserved in human cells. Strong suppression of Pc mutant phenotype by mutation in mask provides physiological relevance that Mask contributes to the anti-silencing effect of trxG, maintaining expression of key developmental genes. Since Mask is a downstream effector of multiple cell signaling pathways, we propose that Mask may connect cell signaling with chromatin mediated epigenetic cell memory governed by trxG.

Chemical modification of Aloe vera leaf hydrogel for efficient cadmium-removal from spiked high-hardness groundwater.

Herein, the hydrogel from the leaf of the Aloe vera plant (ALH) was succinylated (SALH) and saponified (NaSALH). The FTIR, solid-state CP/MAS 13C NMR, and SEM-EDX spectroscopic analyses witnessed the formation of SALH and NaSALH from ALH. The pHZPC for NaSALH was found to be 4.90, indicating the presence of -ve charge on its surface. The Cd2+ sorption efficiency of NaSALH was found to be dependent on pH, NaALH dose, Cd2+ concentration, contact time, and temperature. The maximum Cd2+ removal from DW and HGW was found to be 227.27 and 212.77 mg g-1 according to the Langmuir isothermal model (>0.99) at pH of 6, NaSALH dose of 40 mg g-1, Cd2+ concentration of 90 mg L-1, contact time of 30 min, and temperature of 298 K. The kinetic analysis of Cd2+ sorption data witnessed that the Cd2+ removal by chemisorption mechanism and followed pseudo-second-order kinetics (>0.99). The -ve values of ΔG° and ΔH° assessed the spontaneous and exothermic nature of sorption of Cd2+ by NaSALH. The regeneration and sorption/desorption studies indicated that the sorbent NaSALH is regenerable.

Spatial soil loss prediction impacted by long-term land use/land cover change: a case study of Swat District.

Soil erosion is a destructive consequence of land degradation caused by deforestation, improper farming practices, overgrazing, and urbanization. This irreversible effect negatively impacts the limited renewable soil resource, causing soil truncation, reduced fertility, and unstable slopes. To address the anticipation of erosion modulus resulting from long-term land use and land cover (LULC) changes, a study was conducted in the Swat District of Khyber Pakhtunkhwa (Kpk), Pakistan. The study aimed to predict and evaluate soil erosion concerning these changes using remote sensing (RS), geographic information systems (GIS), and the Revised Universal Soil Loss Equation (RUSLE) model. We also evaluated the impact of the Billion Tree Tsunami Project (BTTP) on soil erosion in the region. Model inputs, such as rainfall erosivity factor, topography factor, land cover and management factor, and erodibility factor, were used to calculate soil erosion. The results revealed that significant soil loss occurred under 2001, 2011, and 2021 LULC conditions, accounting for 67.26%, 61.78%, and 65.32%, falling within the category of low erosion potential. The vulnerable topographical features of the area indicated higher erosion modulus. The maximum soil loss rates observed in 2001, 2011, and 2021 were 80 t/ha-1/year-1, 120 t/ha-1/year-1, and 96 t/ha-1/year-1, respectively. However, the observed reduction in soil loss in 2021 as compared to 2001 and 2011 suggests a positive influence of the BTTP on soil conservation efforts. This study underscores the potential of afforestation initiatives like the BTTP in mitigating soil erosion and highlights the significance of environmental conservation programs in regions with vulnerable topography.

PLGA-Encapsulated Haemonchus contortus Antigen ES-15 Augments Immune Responses in a Murine Model.

Haemonchus contortus is a gastrointestinal parasite that adversely impacts small ruminants, resulting in a notable reduction in animal productivity. In the current investigation, we developed a nanovaccine by encapsulating the recombinant protein rHcES-15, sourced from the excretory/secretory products of H. contortus, within biodegradable poly (D, L-lactide-co-glycolide) (PLGA) nanoparticles (NPs). The development of this nanovaccine involved the formulation of PLGA NPs using a modified double emulsion solvent evaporation technique. Scanning electron microscopy (SEM)verified the successful encapsulation of rHcES-15 within PLGA NPs, exhibiting a size range of 350-400 nm. The encapsulation efficiency (EE) of the antigen in the nanovaccine was determined to be 72%. A total of forty experimental mice were allocated into five groups, with the nanovaccine administered on day 0 and the mice euthanized at the end of the 14-day trial. The stimulation index (SI) from the mice subjected to the nanovaccine indicated heightened lymphocyte proliferation (*** p < 0.001) and a noteworthy increase in anti-inflammatory cytokines (IL-4, IL-10, and IL-17). Additionally, the percentages of T-cells (CD4+, CD8+) and dendritic cell phenotypes (CD83+, CD86+) were significantly elevated (** p < 0.01, *** p < 0.001) in mice inoculated with the nanovaccine compared to control groups and the rHcES-15 group. Correspondingly, higher levels of antigen-specific serum immunoglobulins (IgG1, IgG2a, IgM) were observed in response to the nanovaccine in comparison to both the antigenic (rHcES-15) and control groups (* p < 0.05, ** p < 0.01). In conclusion, the data strongly supports the proposal that the encapsulation of rHcES-15 within PLGA NPs effectively triggers immune cells in vivo, ultimately enhancing the antigen-specific adaptive immune responses against H. contortus. This finding underscores the promising potential of the nanovaccine, justifying further investigations to definitively ascertain its efficacy.

GPU-acceleration of the distributed-memory database peptide search of mass spectrometry data.

Database peptide search is the primary computational technique for identifying peptides from the mass spectrometry (MS) data. Graphical Processing Units (GPU) computing is now ubiquitous in the current-generation of high-performance computing (HPC) systems, yet its application in the database peptide search domain remains limited. Part of the reason is the use of sub-optimal algorithms in the existing GPU-accelerated methods resulting in significantly inefficient hardware utilization. In this paper, we design and implement a new-age CPU-GPU HPC framework, called GiCOPS, for efficient and complete GPU-acceleration of the modern database peptide search algorithms on supercomputers. Our experimentation shows that the GiCOPS exhibits between 1.2 to 5[Formula: see text] speed improvement over its CPU-only predecessor, HiCOPS, and over 10[Formula: see text] improvement over several existing GPU-based database search algorithms for sufficiently large experiment sizes. We further assess and optimize the performance of our framework using the Roofline Model and report near-optimal results for several metrics including computations per second, occupancy rate, memory workload, branch efficiency and shared memory performance. Finally, the CPU-GPU methods and optimizations proposed in our work for complex integer- and memory-bounded algorithmic pipelines can also be extended to accelerate the existing and future peptide identification algorithms. GiCOPS is now integrated with our umbrella HPC framework HiCOPS and is available at: https://github.com/pcdslab/gicops .

Type 1 Autoimmune Pancreatitis Masquerading as Pancreatic Head Carcinoma.

Obstructive jaundice is a joint clinical presentation with many etiologies, including pancreatic cancer and autoimmune pancreatitis (AIP). Differentiating between these two conditions is pivotal due to the divergent management approaches and prognoses. In this case report, we present a case of a 49-year-old female patient who presented with weight loss, intermittent chronic abdominal pain, and jaundice. She was initially suspected of having pancreatic cancer because of clinical presentation and imaging findings. However, she was ultimately diagnosed with Type 1 AIP due to histopathology findings and elevated immunoglobulin G4. This case highlights the complexities in diagnosis, the role of advanced imaging techniques and tissue sampling, and the lessons learned regarding managing this challenging clinical scenario.