The Neurological Implications of COVID-19: A Comprehensive Narrative Review.

The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 revealed a huge number of problems as well as discoveries in medicine, notably, regarding the effects of the virus on the central nervous system (CNS) and peripheral nervous system (PNS). This paper is a narrative review that takes a deep dive into the complex interactions between COVID-19 and the NS. Therefore, this paper explains the broad range of neurological manifestations and neurodegenerative diseases caused by the virus. It carefully considers the routes through which SARS-CoV-2 reaches the NS, including the olfactory system and of course, the hematogenous route, which are also covered when discussing the virus's direct and indirect mechanisms of neuropathogenesis. Besides neurological pathologies such as stroke, encephalitis, Guillain-Barré syndrome, Parkinson's disease, and multiple sclerosis, the focus area is also given to the challenges of making diagnosis, treatment, and management of these conditions during the pandemic. The review also examines the strategic and interventional approaches utilized to prevent these disorders, as well as the ACE2 receptors implicated in the mediation of neurological effects caused by COVID-19. This detailed overview, which combines research outputs with case data, is directed at tackling this pandemic challenge, with a view toward better patient care and outcomes in the future.

Advancing Perioperative Neurocognitive Health: A Critical Review of Predictive Tools, Diagnostic Methods, and Interventional Strategies.

Perioperative neurocognitive disorders (PNDs) affect a large percentage of people who undergo surgeries that need general anesthesia. There is an increased risk of death and a major disruption to postoperative self-care as a result of this. This study compiles all the relevant materials that the authors have found to investigate postnatal depression and its causes, as well as the methods used to determine the probability and severity of PNDs and how to reduce their risk before surgery. Postnatal depression can have many causes, and this text explores some of them. These include a history of alcohol or opiate use, immunological dysregulation, advanced age, educational background, infections, neurocognitive impairment, and pre-existing chronic inflammatory disorders. It also delves into various methods used to gauge the likelihood and severity of postpartum depression. The following assessment tools were covered: the Clock Drawing Test, Domain-Specific Tests, the Mini-Mental State Examination, and the Montreal Cognitive Assessment. In addition to biochemical markers, neuroimaging techniques play an important role in diagnosis. The Frailty Fried assessment, which measures inertia, sluggishness, lack of physical activity, fatigue, and unintentional weight loss, is a key prognostic sign that is highlighted. There is strong evidence that the index, which is derived from these five characteristics, may accurately predict the likelihood of PNDs. Risk mitigation strategies are also covered in this research. Preoperative brain plasticity-based therapies, such as physical exercise and intensive cognitive training, can significantly reduce the incidence and severity of postoperative neurocognitive disorders. A peripheral nerve block, monitoring cerebral oxygen saturation, dexmedetomidine, and a reduction in anesthesia depth are all ways to improve anesthetic procedures. Methods that lower blood pressure should be avoided, the body temperature should be kept down during surgery, or the time without liquids should be lengthened; all of these raise the risk of postoperative nausea and vomiting and make it worse. Potential approaches include a Mediterranean diet, physical activity, cognitive stimulation, smoking cessation, alcohol reduction, avoidance of anticholinergic medications, and non-steroidal anti-inflammatory drug stewardship, although there is no definitive evidence for successful postoperative neurocognitive rehabilitation procedures. More standardized diagnostic criteria, evaluation methods, and PND classification are urgently needed, according to this study. Different cases of PNDs are characterized by different combinations of tests, cutoff values, and methods because there is a broad variety of diagnostic tests used to make the diagnosis. Until now, PNDs and pre-existing neurocognitive disorders have been diagnosed using the Diagnostic and Statistical Manual of Mental Disorders (DSM-V). With an aging population comes an increase in the occurrence and prevalence of PNDs, which calls for a specific way to classify and describe the condition.

Effectiveness of functional ingredients to enhance gill disease in Atlantic salmon (Salmo salar, L.).

The development and application of functional feed ingredients represents a great opportunity to advance fish growth and health, boost the immune system, and induce physiological benefits beyond those provided by traditional feeds. In the present study, we looked at the feasibility of in vitro methods for screening the qualities of functional feed ingredients using the fish cell line RTgill-W1, which has never been used in fish nutrition, and the culture of Paramoeba perurans. Five functional feed ingredients (arginine, ß-glucan, vitamin C, and two phytogenic feed additives) were selected to investigate their effects on cell viability and reactive oxygen species production. Three of the selected ingredients (arginine and two phytogenic feed additives) were additionally tested to assess their potential amoebicidal activity. As these functional ingredients are the core of a commercially available feed (Protec Gill, Skretting AS), their beneficial effects were further assessed in a field trial in fish affected by complex gill disease. Here, the analyzed parameters included the evaluation of macroscopic and histopathological gill conditions, pathogen detections, and analyses of plasma parameters. RTgill-W1 cell line assays were a good tool for screening functional ingredients and provided information about the optimal ingredient concentration ranges, which can be helpful for adjusting the concentrations in future feed diets. Through the culture of P. perurans, the tested ingredients showed a clear amoebicidal activity, suggesting that their inclusions in dietary supplements could be a viable way to prevent microbial infections. A three-week period of feeding Protec Gill slowed the disease progression, by reducing the pathogen load and significantly improving gill tissue conditions, as revealed by histological evaluation. The use of diets containing selected functional ingredients may be a feasible strategy for preventing or mitigating the increasingly common gill diseases, particularly in cases of complex gill disease, as documented in this study.

Utilization of organic-residues as potting media: Physico-chemical characteristics and their influence on vegetable production.

Soilless agriculture is acknowledged worldwide because it uses organic leftovers as a means of supporting intensive and efficient plant production. However, the quality of potting media deteriorates because of lower nutrient content and excessive shrinkage of most organic materials. A current study was undertaken to identify the optimal blend of locally available organic materials with desirable qualities for use as potting media. Therefore, different ingredients, viz., Pinus roxburghii needles, sugarcane bagasse, and farmyard manure were used alone or in combination as potting media to test their suitability by growing spinach as a test crop. Results showed that an increase in Pinus roxburghii needles and sugarcane bagasse decreased medium pH and electrical conductivity. Higher pH and electrical conductivity were recorded for the treatments having a higher farmyard manure ratio (≥50%) in combination. Except for pine needles 100%, pH and electrical conductivity were in the recommended range. The growth attributes include, leaves plant-1, shoot length, fresh- and dry shoot weight along with plant macronutrients (nitrogen, phosphorous, and potassium) and micronutrients (iron, copper, manganese, and zinc) content were higher in treatment pine needles 50%+farmyard manure 50% followed by pine needles 25%+farmyard manure 50%+sugarcane bagasse 25%. Moreover, the particular treatment of pine needles 50%+farmyard manure 50% exhibited the highest concentrations of macro- (nitrogen, phosphorus, and potassium) as well as micronutrients (iron, copper, manganese, and zinc) in the potting media following the harvest. This study highlights the potential of utilizing agro-industrial litter/waste as a soilless growing medium for spinach production under greenhouse conditions. When employed in appropriate proportions, this approach not only addresses disposal concerns but also proves effective for sustainable cultivation. Further research is needed to investigate the use of these wastes as potting media by mixing various particle-size ingredients.

Deep learning guided prediction modeling of dengue virus evolving serotype.

Evolution remains an incessant process in viruses, allowing them to elude the host immune response and induce severe diseases, impacting the diagnostic and vaccine effectiveness. Emerging and re-emerging diseases are among the significant public health concerns globally. The revival of dengue is mainly due to the potential for naturally arising mutations to induce genotypic alterations in serotypes. These transformations could lead to future outbreaks, underscoring the significance of studying DENV evolution in endemic regions. Predicting the emerging Dengue Virus (DENV) genome is crucial as the virus disrupts host cells, leading to fatal outcomes. Deep learning has been applied to predict dengue fever cases; there has been relatively less emphasis on its significance in forecasting emerging DENV serotypes. While Recurrent Neural Networks (RNN) were initially designed for modeling temporal sequences, our proposed DL-DVE generative and classification model, trained on complete genome data of DENV, transcends traditional approaches by learning semantic relationships between nucleotides in a continuous vector space instead of representing the contextual meaning of nucleotide characters. Leveraging 2000 publicly available DENV complete genome sequences, our Long Short-Term Memory (LSTM) based generative and Feedforward Neural Network (FNN) based classification DL-DVE model showcases proficiency in learning intricate patterns and generating sequences for emerging serotype of DENV. The generated sequences were analyzed along with available DENV serotype sequences to find conserved motifs in the genome through MEME Suite (version 5.5.5). The generative model showed an accuracy of 93 %, and the classification model provided insight into the specific serotype label, corroborated by BLAST search verification. Evaluation metrics such as ROC-AUC value 0.818, accuracy, precision, recall and F1 score, all to be around 99.00 %, demonstrating the classification model's reliability. Our model classified the generated sequences as DENV-4, exhibiting 65.99 % similarity to DENV-4 and around 63-65 % similarity with other serotypes, indicating notable distinction from other serotypes. Moreover, the intra-serotype divergence of sequences with a minimum of 90 % similarity underscored their uniqueness.

Thrombocytopenia 4 (THC4): Six novel families with mutations of the cytochrome c gene.

Thrombocytopenia 4 (THC4) is an autosomal-dominant thrombocytopenia caused by mutations in CYCS, the gene encoding cytochrome c (CYCS), a small haeme protein essential for electron transport in mitochondria and cell apoptosis. THC4 is considered an extremely rare condition since only a few patients have been reported so far. These subjects presented mild thrombocytopenia and no or mild bleeding tendency. In this study, we describe six Italian families with five different heterozygous missense CYCS variants: p.Gly42Ser and p.Tyr49His previously associated with THC4, and three novel variants (p.Ala52Thr, p.Arg92Gly, and p.Leu99Val), which have been classified as pathogenic by bioinformatics and segregation analyses. Moreover, we supported functional effects of p.Ala52Thr and p.Arg92Gly on oxidative growth and respiratory activity in a yeast model. The clinical characterization of the 22 affected individuals, the largest series of THC4 patients ever reported, showed that this disorder is characterized by mild-to-moderate thrombocytopenia, normal platelet size, and function, low risk of bleeding, and no additional clinical phenotypes associated with reduced platelet count. Finally, we describe a significant correlation between the region of CYCS affected by mutations and the extent of thrombocytopenia, which could reflect different degrees of impairment of CYCS functions caused by different pathogenetic variants.

Factors influencing pregnancy rate and loss after laparoscopic artificial insemination with frozen-thawed semen in Lohi sheep under sub-tropical conditions.

This study evaluates factors influencing pregnancy rates per artificial insemination (P/AI) and pregnancy loss in Lohi ewes undergoing laparoscopic AI with frozen-thawed semen under sub-tropical conditions. Data from three experiments comprising ewes (n = 358) of mixed parity (nulliparous; NP and parous; P), various body condition score (BCS) and assigned to long-term (LTP, 11 days) and short-term (STP, 5 days) oestrus synchronization regimen across high breeding season (HBS) and low breeding season (LBS) were analysed. Laparoscopic insemination was conducted 54 h post-sponge removal. Pregnancy diagnosis and loss were evaluated on days 35 and 90 post-insemination via ultrasonography. Results showed parity significantly influenced P/AI, with nulliparous ewes achieving higher pregnancy ratios than parous ewes (p = .001). BCS significantly influenced P/AI (p < .05), with a quadratic relationship observed between BCS and season (BCS*BCS*Season; p = .07). Progestin treatment did not significantly influence the ratio of pregnant ewes (p = .07). Pregnancy losses were significantly higher during LBS than HBS (p < .05), irrespective of progestin treatment. In conclusion, parity and BCS significantly influenced P/AI, with BCS demonstrating a quadratic association with season. Ewes bred during LBS experienced higher pregnancy losses than HBS, irrespective of progestin treatment.

Drug repurposing: identification of SARS-CoV-2 potential inhibitors by virtual screening and pharmacokinetics strategies.

INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic caused global health, economic, and population loss. Variants of the coronavirus contributed to the severity of the disease and persistent rise in infections. This study aimed to identify potential drug candidates from fifteen approved antiviral drugs against SARS-CoV-2 (6LU7), SARS-CoV (5B6O), and SARS-CoV-2 spike protein (6M0J) using virtual screening and pharmacokinetics to gain insights into COVID-19 therapeutics. METHODOLOGY: We employed drug repurposing approach to analyze binding performance of fifteen clinically approved antiviral drugs against the main protease of SARS-CoV-2 (6LU7), SARS-CoV (5B6O), and SARS-CoV-2 spike proteins bound to ACE-2 receptor (6M0J), to provide an insight into the therapeutics of COVID-19. AutoDock Vina was used for docking studies. The binding affinities were calculated, and 2-3D structures of protein-ligand interactions were drawn. RESULTS: Rutin, hesperidin, and nelfinavir are clinically approved antiviral drugs with high binding affinity to proteins 6LU7, 5B6O, and 6M0J. These ligands have excellent pharmacokinetics, ensuring efficient absorption, metabolism, excretion, and digestibility. Hesperidin showed the most potent interaction with spike protein 6M0J, forming four H-bonds. Nelfinavir had a high human intestinal absorption (HIA) score of 0.93, indicating maximum absorption in the body and promising interactions with 6LU7. CONCLUSIONS: Our results indicated that rutin, hesperidin, and nelfinavir had the highest binding results against the proposed drug targets. The computational approach effectively identified SARS-CoV-2 inhibitors. COVID-19 is still a recurrent threat globally and predictive analysis using natural compounds might serve as a starting point for new drug development against SARS-CoV-2 and related viruses.

Antibiotic Resistance in Salmonella typhi Strains Isolated From Patients in Pakistan: A Hospital Database Study.

BACKGROUND: The surge in antibiotic-resistant Salmonella enterica serotype Typhi strains has led to heightened morbidity, mortality, and treatment expenses. This study aims to assess the resistance patterns of Salmonella Typhi to diverse antibiotics among patients seeking care at a tertiary hospital in Pakistan. METHODS: A database from a tertiary care hospital in Pakistan was reviewed, and data on blood cultures that isolated Salmonella enterica serotype Typhi were collected. Data were collected and analyzed using Microsoft Excel (Microsoft Corporation, USA) and IBM SPSS software (IBM Corp., Armonk, NY). RESULTS: Demographic information of the selected data was retrieved from the hospital database, and the results showed that 63.7% were male, 36.1% were female, and 0.2% were categorized as neutered. Regarding antibiotic resistance, ampicillin exhibited the highest resistance rate (91.50%), while meropenem demonstrated the lowest (3.00%). Antibiotic sensitivity patterns also varied across different age groups, although statistical analysis indicated no significant differences. Significant associations were found between antibiotic resistance and comorbidities, as well as previous antibiotic use. CONCLUSION:  Salmonella enterica serotype Typhi showed a high resistance to ampicillin and fluoroquinolones, such as ciprofloxacin. The emergence of resistance and decreased sensitivity to current first-line antibiotics necessitates a shift towards alternative options, such as third-generation cephalosporins, azithromycin, and newer antibiotics like meropenem.

Comparison of oxidative stress, lipid peroxidation and inflammatory markers between rheumatoid arthritis and ankylosing spondylitis patients.

Objectives: To measure the levels of superoxide dismutase and malondialdehyde along with erythrocyte sedimentation rate and C-reactive protein in patients of rheumatoid arthritis and ankylosing spondylitis. METHODS: The comparative, cross-sectional study was conducted from February 2 to December 30, 2022, at the Centre for Research in Experimental and Applied Medicine laboratory of the Department of Biochemistry and Molecular Biology, Army Medical College, Rawalpindi, Pakistan, in collaboration with the Department of Rheumatology, Pak Emirates Military Hospital, Rawalpindi. The sample comprised healthy controls in group 1, patients of rheumatoid arthritis in group 2 and patients of ankylosing spondylitis in group 3. Blood samples were assessed for levels of superoxide dismutase, malondialdehyde, erythrocyte sedimentation rate and C-reactive protein. Data was analysed using SPSS 25. RESULTS: Of the 180 subjects, 60(33.3%) were in group 1; 32(53.3%) females and 28(46.7%) males with mean age 34.9±6.4 years. There were 60(33.3%) patients in group 2; 35(58.3%) females and 25(41.7%) males with mean age 46.0±11.1 years. There were 60(33.3%) patients in group 3, and all 60(100%) were males with mean age 35.9±6.9 years. Superoxide dismutase level was significantly low and malondialdehyde level was significantly high in groups 2 and 3 compared to group 1 (p<0.05). Erythrocyte sedimentation rate was the highest in group 2, followed by group 3 (p<0.05). C-reactive protein levels were the highest in group 2 and the lowest in group 3 (p<0.05). A significantly negative correlation (p<0.001) was found between superoxide dismutase and malondialdehyde. CONCLUSIONS: Oxidative stress played a pivotal role in chronic inflammatory rheumatic diseases, like rheumatoid arthritis and ankylosing spondylitis.

Impact of frailty on endoscopic retrograde cholangiopancreatography outcomes in nonagenarians: A United States national experience.

BACKGROUND: Endoscopic retrograde cholangiopancreatography (ERCP) is an essential therapeutic tool for biliary and pancreatic diseases. Frail and elderly patients, especially those aged ≥ 90 years are generally considered a higher-risk population for ERCP-related complications. AIM: To investigate outcomes of ERCP in the Non-agenarian population (≥ 90 years) concerning Frailty. METHODS: This is a cohort study using the 2018-2020 National Readmission Database. Patients aged ≥ 90 were identified who underwent ERCP, using the international classification of diseases-10 code with clinical modification. Johns Hopkins's adjusted clinical groups frailty indicator was used to classify patients as frail and non-frail. The primary outcome was mortality, and the secondary outcomes were morbidity and the 30 d readmission rate related to ERCP. We used univariate and multivariate regression models for analysis. RESULTS: A total of 9448 patients were admitted for any indications of ERCP. Frail and non-frail patients were 3445 (36.46%) and 6003 (63.53%) respectively. Indications for ERCP were Choledocholithiasis (74.84%), Biliary pancreatitis (9.19%), Pancreatico-biliary cancer (7.6%), Biliary stricture (4.84%), and Cholangitis (1.51%). Mortality rates were higher in frail group [adjusted odds ratio (aOR) = 1.68, P = 0.02]. The Intra-procedural complications were insignificant between the two groups which included bleeding (aOR = 0.72, P = 0.67), accidental punctures/lacerations (aOR = 0.77, P = 0.5), and mechanical ventilation rates (aOR = 1.19, P = 0.6). Post-ERCP complication rate was similar for bleeding (aOR = 0.72, P = 0.41) and post-ERCP pancreatitis (aOR = 1.4, P = 0.44). Frail patients had a longer length of stay (6.7 d vs 5.5 d) and higher mean total charges of hospitalization ($78807 vs $71392) compared to controls (P < 0.001). The 30 d all-cause readmission rates between frail and non-frail patients were similar (P = 0.96). CONCLUSION: There was a significantly higher mortality risk and healthcare burden amongst nonagenarian frail patients undergoing ERCP compared to non-frail. Larger studies are warranted to investigate and mitigate modifiable risk factors.

Exploring dermoscopic structures for melanoma lesions' classification.

Background: Melanoma is one of the deadliest skin cancers that originate from melanocytes due to sun exposure, causing mutations. Early detection boosts the cure rate to 90%, but misclassification drops survival to 15-20%. Clinical variations challenge dermatologists in distinguishing benign nevi and melanomas. Current diagnostic methods, including visual analysis and dermoscopy, have limitations, emphasizing the need for Artificial Intelligence understanding in dermatology. Objectives: In this paper, we aim to explore dermoscopic structures for the classification of melanoma lesions. The training of AI models faces a challenge known as brittleness, where small changes in input images impact the classification. A study explored AI vulnerability in discerning melanoma from benign lesions using features of size, color, and shape. Tests with artificial and natural variations revealed a notable decline in accuracy, emphasizing the necessity for additional information, such as dermoscopic structures. Methodology: The study utilizes datasets with clinically marked dermoscopic images examined by expert clinicians. Transformers and CNN-based models are employed to classify these images based on dermoscopic structures. Classification results are validated using feature visualization. To assess model susceptibility to image variations, classifiers are evaluated on test sets with original, duplicated, and digitally modified images. Additionally, testing is done on ISIC 2016 images. The study focuses on three dermoscopic structures crucial for melanoma detection: Blue-white veil, dots/globules, and streaks. Results: In evaluating model performance, adding convolutions to Vision Transformers proves highly effective for achieving up to 98% accuracy. CNN architectures like VGG-16 and DenseNet-121 reach 50-60% accuracy, performing best with features other than dermoscopic structures. Vision Transformers without convolutions exhibit reduced accuracy on diverse test sets, revealing their brittleness. OpenAI Clip, a pre-trained model, consistently performs well across various test sets. To address brittleness, a mitigation method involving extensive data augmentation during training and 23 transformed duplicates during test time, sustains accuracy. Conclusions: This paper proposes a melanoma classification scheme utilizing three dermoscopic structures across Ph2 and Derm7pt datasets. The study addresses AI susceptibility to image variations. Despite a small dataset, future work suggests collecting more annotated datasets and automatic computation of dermoscopic structural features.

Impact of multiple isolation procedures on the differentiation potential of adipose derived canine mesenchymal stem cells.

OBJECTIVE: In regenerative biology, the most commonly used cells are adipose tissue-derived mesenchymal stem cells (AD-MSCs). This is due to the abundance and easy accessibility of AD-MSCs. METHODS: In this study, canine AD-MSCs were harvested from different anatomical locations, i.e., subcutaneous (SC), omental (OM), and perirenal (PR). Various isolation techniques namely explants (TRT-I), collagenase-digestion (TRT-II), collagenase-digested explants (TRT-III), and trypsin-digested explants (TRT-IV) were used to segregate the MSCs to evaluate cell doubling time, viability, and adipogenic/osteogenic lineage differentiation potential. RESULTS: The study showed that the SC stem cells had superior growth kinetics compared to other tissues, while the cells isolated through TRT-II performed better than the other cell isolation procedures. The metabolic status of cells isolated from dog adipose tissue indicated that all cells had adequate metabolic rates. However, SC-MSCs derived from TRT-III and TRT-IV outperformed those derived from TRT-I and TRT-II. The differentiation analysis revealed that cells differentiate into adipogenic and osteogenic lineage regardless of treatment, as demonstrated by positive oil red O (ORO) and Alizarin Red S (ALZ) stain. It is worth mentioning that cells derived from TRT-III had larger and more intracellular droplets compared to the other treatments. The TRT-I, -II, and -III showed greater osteogenic differentiation in cells isolated from PR and OM regions compared to SC-derived cells. However, the TRT-IV resulted in better osteogenic differentiation in cells from SC, followed by the OM and PR-derived cells. CONCLUSION: It is concluded that all methods of MSCs isolation from adipose tissues are successful; however, the TRT-II had the highest rate of cell re-assortment from the SC, while, TRT-II and -IV are most suitable for isolating cells from PR and OM adipose tissue.

Investigation of the dynamical structures of double-chain deoxyribonucleic acid model in biological sciences.

The present research investigates the double-chain deoxyribonucleic acid model, which is important for the transfer and retention of genetic material in biological domains. This model is composed of two lengthy uniformly elastic filaments, that stand in for a pair of polynucleotide chains of the deoxyribonucleic acid molecule joined by hydrogen bonds among the bottom combination, demonstrating the hydrogen bonds formed within the chain's base pairs. The modified extended Fan sub equation method effectively used to explain the exact travelling wave solutions for the double-chain deoxyribonucleic acid model. Compared to the earlier, now in use methods, the previously described modified extended Fan sub equation method provide more innovative, comprehensive solutions and are relatively straightforward to implement. This method transforms a non-linear partial differential equation into an ODE by using a travelling wave transformation. Additionally, the study yields both single and mixed non-degenerate Jacobi elliptic function type solutions. The complexiton, kink wave, dark or anti-bell, V, anti-Z and singular wave shapes soliton solutions are a few of the creative solutions that have been constructed utilizing modified extended Fan sub equation method that can offer details on the transversal and longitudinal moves inside the DNA helix by freely chosen parameters. Solitons propagate at a consistent rate and retain their original shape. They are widely used in nonlinear models and can be found everywhere in nature. To help in understanding the physical significance of the double-chain deoxyribonucleic acid model, several solutions are shown with graphics in the form of contour, 2D and 3D graphs using computer software Mathematica 13.2. All of the requisite constraint factors that are required for the completed solutions to exist appear to be met. Therefore, our method of strengthening symbolic computations offers a powerful and effective mathematical tool for resolving various moderate nonlinear wave problems. The findings demonstrate the system's potentially very rich precise wave forms with biological significance. The fundamentals of double-chain deoxyribonucleic acid model diffusion and processing are demonstrated by this work, which marks a substantial development in our knowledge of double-chain deoxyribonucleic acid model movements.

Berberine ameliorates the progression of primary sclerosing cholangitis by activating farnesoid X receptor.

Primary sclerosing cholangitis (PSC) is a rare cholestatic disease characterized by biliary infiltration, hepatic fibrosis and bile duct destruction. To date, treatment options for PSC are very limited. Therefore, the current study is aimed to investigate the therapeutic potential of berberine (BBR) against PSC. The disease was induced by feeding the mice with 3,5-diethoxycarbonyl-1,4-dihydro-2,4,6-collidine (DDC) for four weeks. The serum biochemistry and liver histology were analyzed. Furthermore, the expression of farnesoid X receptor (FXR) was also evaluated by real-time PCR. The results indicated that berberine prevents the progression of PSC by modulating the expression of FXR which ultimately regulates other genes (including Cyp7A1 and BSEP) thus maintaining bile acids homeostasis. Furthermore, the docking analysis showed that berberine interacts with the binding pocket of FXR to activate the protein thus acting as an FXR agonist. In conclusion, data indicate that berberine protects the liver from PSC-related injury. This effect might be due to the modulation of FXR activity.

Se-p Orbitals Induced "Strong d-d Orbitals Interaction" Enable High Reversibility of Se-Rich ZnSe/MnSe@C Electrode as Excellent Host for Sodium-Ion Storage.

The heterostructure of transition-metal chalcogenides is a promising approach to boost alkali ion storage due to fast charge kinetics and reduction of activation energy. However, cycling performance is a paramount challenge that is suffering from poor reversibility. Herein, it is reported that Se-rich particles can chemically interact with local hexagonal ZnSe/MnSe@C heterostructure environment, leading to effective ions insertion/extraction, enabling high reversibility. Enlightened by theoretical understanding, Se-rich particles endow high intrinsic conductivities in term of low energy barriers (1.32 eV) compared with those without Se-rich particles (1.50 eV) toward the sodiation process. Moreover, p orbitals of Se-rich particles may actively participate and further increase the electronegativity that pushes the Mn d orbitals (dxy and dx2 -y2 ) and donate their electrons to dxz and dyz orbitals, manifesting strong d-d orbitals interaction between ZnSe and MnSe. Such fundamental interaction will adopt a well-stable conducive electronic bridge, eventually, charges are easily transferred from ZnSe to MnSe in the heterostructure during sodiation/desodiation. Therefore, the optimized Se-rich ZnSe/MnSe@C electrode delivered high capacity of 576 mAh g-1 at 0.1 A g-1 after 100 cycles and 384 mAh g-1 at 1 A g-1 after 2500 cycles, respectively. In situ and ex situ measurements further indicate the integrity and reversibility of the electrode materials upon charging/discharging.

Dynamics of soil biota and nutrients at varied depths in a Tamarix ramosissima-dominated natural desert ecosystem: Implications for nutrient cycling and desertification management.

The underground community of soil organisms, known as soil biota, plays a critical role in terrestrial ecosystems. Different ecosystems exhibit varied responses of soil organisms to soil physical and chemical properties (SPCPs). However, our understanding of how soil biota react to different soil depths in naturally established population of salinity tolerant Tamarix ramosissima in desert ecosystems, remains limited. To address this, we employed High-Throughput Illumina HiSeq Sequencing to examine the population dynamics of soil bacteria, fungi, archaea, protists, and metazoa at six different soil depths (0-100 cm) in the naturally occurring T. ramosissima dominant zone within the Taklimakan desert of China. Our observations reveal that the alpha diversity of bacteria, fungi, metazoa, and protists displayed a linear decrease with the increase of soil depth, whereas archaea exhibited an inverse pattern. The beta diversity of soil biota, particularly metazoa, bacteria, and protists, demonstrated noteworthy associations with soil depths through Non-Metric Dimensional Scaling analysis. Among the most abundant classes of soil organisms, we observed Actinobacteria, Sordariomycetes, Halobacteria, Spirotrichea, and Nematoda for bacteria, fungi, archaea, protists, and metazoa, respectively. Additionally, we identified associations between the vertical distribution of dominant biotic communities and SPCPs. Bacterial changes were mainly influenced by total potassium, available phosphorus (AP), and soil water content (SWC), while fungi were impacted by nitrate (NO3-) and available potassium (AK). Archaea showed correlations with total carbon (TC) and AK thus suggesting their role in methanogenesis and methane oxidation, protists with AP and SWC, and metazoa with AP and pH. These correlations underscore potential connections to nutrient cycling and the production and consumption of greenhouse gases (GhGs). This insight establishes a solid foundation for devising strategies to mitigate nutrient cycling and GHG emissions in desert soils, thereby playing a pivotal role in the advancement of comprehensive approaches to sustainable desert ecosystem management.