Search

Abstract The optimization of floating bifacial solar panels (FBS PV) in tropical freshwater systems is explored by employing response surface methodology (RSM) and central composite design (CCD). Previous studies have yet to explore the long-term durability, environmental impact, economic viability, and performance of FBS PV systems under various climatic conditions. This study addresses this gap by focusing on panel height, water depth, and tilt angle to improve performance. The quadratic model reveals significant non-linear relationships impacting FBS PV power generation with freshwater cooling. Our models demonstrate high explanatory power, with R-squared values of 0.9831 for output power and 0.9900 for Bi-Facial gain. Experimental validation using conventional white surface (CWS) and proposed freshwater surface (PFS) indicates notable improvements in power generation, achieving a 4.34 to 4.86% gain in bifacial efficiency across various irradiation levels. Under 950 W/m2 irradiation, freshwater cooling achieves a 3.19% higher bifacial gain compared to CWS cooling. Panel temperature analysis shows consistent reductions with freshwater cooling, ranging from 1.43 to 2.72 °C, enhancing overall efficiency and longevity. This research highlights the potential of freshwater cooling in optimizing bifacial solar systems, offering actionable insights for sustainable energy solutions in tropical regions.

IntroductionMore than half of the world’s population consumes rice as their primary food. The majority of rice production is concentrated in Asia, with the top 10 rice-growing countries accounting for 84% of the world’s total rice cultivation. However, rice production is also strongly linked to environmental changes. Among all the global sources of greenhouse gas (GHG) emissions, paddy cultivation stands out as a significant contributor to global methane (CH4) and nitrous oxide (N2O) emissions. This contribution is expected to increase further with the projected increase of 28% in global rice output by 2050. Hence, modifications to rice management practices are necessary both to increase yield and mitigate GHG emissions.MethodsWe investigated the effect of seedling treatment, soil application, and foliar application of a methane-derived microbial biostimulant on grain yield and GHG emissions from rice fields over three seasons under 100% fertilizer conditions. Further, microbial biostimulant was also tested under 75% nitrogen (N) levels to demonstrate its effect on grain yield. To understand the mechanism of action of microbial biostimulant on crop physiology and yield, a series of physiological, transcript, and metabolite analyses were also performed.ResultsOur three-season open-field studies demonstrated a significant enhancement of grain yield, up to 39%, with a simultaneous reduction in CH4 (31%–60%) and N2O (34%–50%) emissions with the use of methane-derived microbial biostimulant. Under 75% N levels, a 34% increase in grain yield was observed with microbial biostimulant application. Based on the physiological, transcript, and metabolite analyses data, we were further able to outline the potential mechanisms for the diverse synergistic effects of methane-derived microbial biostimulant on paddy, including indole-3-acetic acid production, modulation of photosynthesis, tillering, and panicle development, ultimately translating to superior yield.ConclusionThe reduction in GHG emission and enhanced yield observed under both recommended and reduced N conditions demonstrated that the methane-derived biostimulant can play a unique and necessary role in the paddy ecosystem. The consistent improvements seen across different field trials established that the methane-derived microbial biostimulant could be a scalable solution to intensify rice productivity with a lower GHG footprint, thus creating a win–win–win solution for farmers, customers, and the environment.

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.

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird’s eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies.

The clinical management of oral cancer is often frequented with challenges that arise from relapse, recurrence, invasion and resistance towards the cornerstone chemo and radiation therapies. The recent conceptual advancement in oncology has substantiated the role of cancer stem cells (CSC) as a predominant player of these intricacies. CSC are a sub-group of tumor population with inherent adroitness to self-renew with high plasticity. During tumor evolution, the structural and functional reprogramming persuades the cancer cells to acquire stem-cell like properties, thus presenting them with higher survival abilities and treatment resistance. An appraisal on key features that govern the stemness is of prime importance to confront the current challenges encountered in oral cancer. The nurturing niche of CSC for maintaining its stemness characteristics is thought to be modulated by complex multi-layered components encompassing neoplastic cells, extracellular matrix, acellular components, circulatory vessels, various cascading signaling molecules and stromal cells. This review focuses on recapitulating both intrinsic and extrinsic mechanisms that impart the stemness. There are contemplating evidences that demonstrate the role of transcription factors (TF) in sustaining the neoplastic stem cell’s pluripotency and plasticity alongside the miRNA in regulation of crucial genes involved in the transformation of normal oral mucosa to malignancy. This review illustrates the interplay between miRNA and various known TF of oral cancer such as c-Myc, SOX, STAT, NANOG and OCT in orchestrating the stemness and resistance features. Further, the cross-talks involved in tumor micro-environment inclusive of cytokines, macrophages, extra cellular matrix, angiogenesis leading pathways and influential factors of hypoxia on tumorigenesis and CSC survival have been elucidated. Finally, external factorial influence of oral microbiome gained due to the dysbiosis is also emphasized. There are growing confirmations of the possible roles of microbiomes in the progression of oral cancer. Given this, an attempt has been made to explore the potential links including EMT and signaling pathways towards resistance and stemness. This review provides a spectrum of understanding on stemness and progression of oral cancers at various regulatory levels along with their current therapeutic knowledge. These mechanisms could be exploited for future research to expand potential treatment strategies.

In this study, the pristine MgO, MgO/CNT and Ni-MgO/CNT nanocomposites were processed using the impregnation and chemical vapor deposition methods and analyzed for hydrogen evolution reaction (HER) using the electrochemical water splitting process. Furthermore, the effect of nickel on the deposited carbon was systematically elaborated in this study. The highly conductive carbon nanotubes (CNTs) deposited on the metal surface of the Ni-MgO nanocomposite heterostructure provides a robust stability and superior electrocatalytic activity. The optimized Ni-MgO/CNT nanocomposite exhibited hierarchical, helical-shaped carbon nanotubes adorned on the surface of the Ni-MgO flakes, forming a hybrid metal–carbon network structure. The catalytic HER was carried out in a 1M alkaline KOH electrolyte, and the optimized Ni-MgO/CNT nanocomposite achieved a low (117 mV) overpotential value (ɳ) at 10 mA cm−2 and needed a low (116 mV/dec) Tafel value, denotes the Volmer–Heyrovsky pathway. Also, the high electrochemical active surface area (ECSA) value of the Ni-MgO/CNT nanocomposite attained 515 cm2, which is favorable for the generation of abundant electroactive species, and the prepared electrocatalyst durability was also performed using a chronoamperometry test for the prolonged duration of 20 h at 10 mA cm−2 and exhibited good stability, with a 72% retention. Hence, the obtained results demonstrate that the optimized Ni-MgO/CNT nanocomposite is a highly active and cost-effective electrocatalyst for hydrogen energy production.

Treating chronic tenosynovitis of the extensor carpi ulnaris (ECU) in the wrist and making the individuals return to their previous work or job is challenging. The tenosynovectomy and sixth compartment release may destabilize the ECU tendon and cause instability. This article describes extensor retinaculum flap reconstruction for chronic ECU tenosynovitis in a 34-year-old woman.

Background: High intra- and interobserver variability in the follicular assessment using two-dimensional (2D) ultrasound (US) is still a concern. To solve this issue, we have developed a novel software solution, which automatically provides follicles' count and their diameters using 2D US images obtained by a manual sweep of an ovary. The primary objective of this study was to compare the result of the automated solution with a manual 2D US-based assessment. Methods: In the first phase, multiple follicular US sweeps were collected from 54 subjects; these sweeps were used to develop the software. In the second phase, data from 10 subjects were collected for validation of the developed solution. During each phase, for follicles ≥5 mm, their count and diameters were recorded by the sonologist using 2D US. Results: For the total follicle count, a high correlation (0.787) was observed between the solution and manual assessment. The 95% limits of agreement between the two methods were in the range of 4.232 to −4.258. The two methods had an excellent correlation (0.817) for the measurement of mean follicular diameter. However, the solution had a tendency to underestimate the mean diameter by an average of 1.725 mm (±2.16 mm). The limits of agreement between the two methods for mean diameter measurement were from 2.508 to −5.960 mm. Conclusion: This study validates the feasibility of our solution for automatic assessment of follicle count and diameter with accuracy comparable to the 2D US-based manual assessment. We further observed that the solution's performance is better than known intra- and interobserver variability of the manual assessment. We recommend further validation of the solution to confirm these initial results and potential time gain with an automated assessment.

Abstract Persimmon leaves are known to have some beneficial effects, including ROS elimination, lipid circulation, and neuronal protection. However, their anti-cancer properties and the underlying mechanisms remain unclear. Herein, we show that treatment with the ethanol extract of persimmon, Diospyros kaki, leaves (EEDK) induces cancer cell death and inhibits cell proliferation. Using fluorescence resonance energy transfer (FRET) technology with genetically-encoded biosensors, we first found that EEDK stimulates a PDGFR-Rac signaling cascade in live cells. Moreover, we found that downstream of the PDGFR-Rac pathway, JNKs are activated by EEDK. In contrast, JNK-downstream inhibitors, such as CoCl2, T-5224, and pepstatin A, attenuated EEDK-induced cell death. Thus, we illustrate that the PDGFR-Rac-JNK signaling axis is triggered by EEDK, leading to cancer cell death, suggesting the extract of persimmon leaves may be a promising anti-cancer agent.

Background: Evidence based medicine helps in improving medical decision and service conveyance to patients. Experience based medicine depends on the unequivocal and verifiable learning regulated by the past clinical encounters other than the other social, lawful, and moral systems of the practice. The aim of our study is to find out the evidence-based practice amongst the orthopaedic fraternity and to compare the magnitude of evidence-based practice in different groups allotted based on the experience in the field. Materials and Method: It is a Prospective study done amongst Orthopaedic surgeon in two cities in Tamilnadu Madurai and Chennai. The study populations were Orthopaedics practicing doctors with minimum of 3-year experience. The Orthopaedic Surgeons were given a questionnaire and were asked to fill it. The questionnaire was self-explanatory and they have to tick the best response, which they think was the most appropriate. Questionnaire was prepared based on the AAOS guidelines of clinical orthopaedic practice. The AAOS strong recommendation guidelines were considered as gold standard and the response from the Orthopaedicians were collected and corrected. The main emphasis was given to the second component only. Out of the 120 doctors 14 of them had either one or more wrong answer and only 106 orthopaedicians had given correct answer and their answers only were evaluated. Results: The total percentage of evidence-based practice in our study was 43.4% and experience-based practice was 56.6%. Conclusion: Experienced based practice is comparably more amongst the practicing orthopaedic surgeons. Upcoming Orthopaedic surgeons rely more on evidence to treat their patients than their experience.

Breast cancer (BC) prevention remains the ultimate cost-effective method to reduce the global burden of invasive breast cancer (IBC). To date, surgery and chemoprevention remain the main risk-reducing modalities for those with hereditary cancer syndromes, as well as high-risk non-hereditary breast lesions such as ADH, ALH, or LCIS. Ductal carcinoma in situ (DCIS) is a preinvasive malignant lesion of the breast that closely mirrors IBC and, if left untreated, develops into IBC in up to 50% of lesions. Certain high-risk patients with DCIS may have a 25% risk of developing recurrent DCIS or IBC, even after surgical resection. The development of breast cancer elicits a strong immune response, which brings to prominence the numerous advantages associated with immune-based cancer prevention over drug-based chemoprevention, supported by the success of dendritic cell vaccines targeting HER2-expressing BC. Vaccination against BC to prevent or interrupt the process of BC development remains elusive but is a viable option. Vaccination to intercept preinvasive or premalignant breast conditions may be possible by interrupting the expression pattern of various oncodrivers. Growth factors may also function as potential immune targets to prevent breast cancer progression. Furthermore, neoantigens also serve as effective targets for interception by virtue of strong immunogenicity. It is noteworthy that the immune response also needs to be strong enough to result in target lesion elimination to avoid immunoediting as it may occur in IBC arising from DCIS. Overall, if the issue of vaccine targets can be solved by interrupting premalignant lesions, there is a potential to prevent the development of IBC.

Heterogeneous regions present in tissue with respect to cancer cells are of various types. This study aimed to analyze and classify the morphological features of the nucleus and cytoplasm regions of tumor cells. This tissue morphology study was established through invasive ductal breast cancer histopathology images accessed from the Databiox public dataset. Automatic detection and classification was carried out by means of the computer analytical tool of deep learning algorithm. Residual blocks with short skip were employed with hidden layers of preserved spatial information. A ResNet-based convolutional neural network was adapted to perform end-to-end segmentation of breast cancer nuclei. Nuclei regions were identified through color and tubular structure morphological features. Based on the segmented and extracted images, classification of benign and malignant breast cancer cells was done to identify tumors. The results indicated that the proposed method could successfully segment and classify breast tumors with an average Dice score of 90.68%, sensitivity = 98.64, specificity = 98.68, and accuracy = 98.82.

The study aimed to deprescribe inappropriate consumption among Proton Pump Inhibitor (PPI) users and assess the clinical consequences of deprescribing. This is a prospective interventional study carried out among patients aged >18 years and consuming PPI. The “potentially inappropriate” patients were counselled on harms of inappropriate PPI usage, impact of healthy dietary and lifestyle habits employing a Patient Information Leaflet (PIL). The patients deprescribed were followed up through telephonic communication. Global Overall Symptom scale (GOS) was utilized to assess gastric discomfort before and after deprescribing. From 745 patients recruited, 226 (30.33%) were classified under “potentially inappropriate”, out of which 113 (15.16%) were deprescribed. When paired t-test was applied, GOS scale indicated significant difference in symptoms before and after deprescribing (P- value

Current success of immunotherapy in cancer has drawn attention to the subsets of TH cells in the tumor which are critical for activation of anti-tumor response either directly by themselves or by stimulating cytotoxic T cell activity. However, presence of immunosuppressive pro-tumorigenic TH subsets in the tumor milieu further contributes to the complexity of regulation of TH cell-mediated immune response. In this review, we present an overview of the multifaceted positive and negative effects of TH cells, with an emphasis on regulation of different TH cell subtypes by various immune cells, and how a delicate balance of contradictory signals can influence overall success of cancer immunotherapy. We focus on the regulatory network that encompasses dendritic cell-induced activation of CD4+ TH1 cells and subsequent priming of CD8+ cytotoxic T cells, along with intersecting anti-inflammatory and pro-tumorigenic TH2 cell activity. We further discuss how other tumor infiltrating immune cells such as immunostimulatory TH9 and Tfh cells, immunosuppressive Treg cells, and the duality of TH17 function contribute to tip the balance of anti- vs pro-tumorigenic TH responses in the tumor. We highlight the developing knowledge of CD4+ TH1 immune response against neoantigens/oncodrivers, impact of current immunotherapy strategies on CD4+ TH1 immunity, and how opposing action of TH cell subtypes can be explored further to amplify immunotherapy success in patients. Understanding the nuances of CD4+ TH cells regulation and the molecular framework undergirding the balancing act between anti- vs pro-tumorigenic TH subtypes is critical for rational designing of immunotherapies that can bypass therapeutic escape to maximize the potential of immunotherapy.

The gut microbiota has been known to modulate the immune responses in chronic liver diseases. Recent evidence suggests that effects of dietary foods on health care and human diseases are related to both the immune reaction and the microbiome. The gut-microbiome and intestinal immune system play a central role in the control of bacterial translocation-induced liver disease. Dysbiosis, small intestinal bacterial overgrowth, translocation, endotoxemia, and the direct effects of metabolites are the main events in the gut-liver axis, and immune responses act on every pathways of chronic liver disease. Microbiome-derived metabolites or bacteria themselves regulate immune cell functions such as recognition or activation of receptors, the control of gene expression by epigenetic change, activation of immune cells, and the integration of cellular metabolism. Here, we reviewed recent reports about the immunologic role of gut microbiotas in liver disease, highlighting the role of diet in chronic liver disease.

Patients with metastatic HER2 breast cancer (MBC) often become resistant to HER 2 targeted therapy and have recurrence of disease. The Panacea trial suggested that HER2 MBC patients were more likely to respond to checkpoint therapy if TIL were present or if tumor expressed PD-L1. We assessed whether type I polarized dendritic cells (DC1) could improve checkpoint therapy in a preclinical model of HER2+ breast cancer. TUBO bearing mice were vaccinated with either MHC class I or class II HER2 peptide pulsed DC1 (class I or class II HER2-DC1) concurrently or sequentially with administration of anti-PD-1 or anti-PDL1. Infiltration of tumors by immune cells, induction of anti-HER2 immunity and response to therapy was evaluated. Class I or class II HER2-DC1 vaccinated mice generated anti-HER2 CD8 or CD4+ T cell immune responses and demonstrated delayed tumor growth. Combining both MHC class I and II HER2-pulsed DC1 did not further result in inhibition of tumor growth or enhanced survival compared to individual administration. Interestingly class II HER2-DC1 led to both increased CD4 and CD8 T cells in the tumor microenvironment while class I peptides typically resulted in only increased CD8 T cells. Anti-PD-1 but not anti-PD-L1 administered sequentially with class I or class II HER2-DC1 vaccine could improve the efficacy of HER2-DC1 vaccine as measured by tumor growth, survival, infiltration of tumors by T cells and increase in systemic anti-HER2 immune responses. Depletion of CD4+ T cells abrogated the anti-tumor efficacy of combination therapy with class II HER2-DC1 and anti-PD-1, suggesting that tumor regression was CD4 dependent. Since class II HER2-DC1 was as effective as class I, we combined class II HER2-DC1 vaccine with anti-rat neu antibodies and anti-PD-1 therapy. Combination therapy demonstrated further delay in tumor growth, and enhanced survival compared to control mice. In summary, Class II HER2-DC1 drives both a CD4 and CD8 T cell tumor infiltration that leads to increased survival, and in combination with anti-HER2 therapy and checkpoint blockade can improve survival in preclinical models of HER2 positive breast cancer and warrants exploration in patients with HER2 MBC.

Abstract Context Osteoporosis is a silent disease until it is complicated by trivial fall fractures. There is an increasing interest within the orthopaedic community in the noninvasive cost-effective measurement of the bone mineral density. Aims The aim of the study is to assess whether urinary N-telopeptide level can be a new diagnostic tool in diagnosing osteoporosis. Methods and Material This prospective study was done at Sri Ramachandra Medical Centre (SRMC) hospital from October 2015 to October 2017. The study was conducted among patients who comes to SRMC as inpatient or outpatient with suspected osteoporosis and underwent dual-energy X-ray absorptiometry (DXA) scan and urinary N-telopeptide. The inclusion criteria were women aged 65 or older, women aged less than 65 with risk factors, younger postmenopausal women with one or more risk factors, men aged 70 or older, men less than 70 with risk factors, and any above group patients who comes within 24 hours following trivial fall fractures. The exclusion criteria were pathological fracture, history of any illness affecting bone metabolism. The results from DXA scan were taken as gold standard against urinary N-telopeptide. Then the patients were divided into two groups control and study. The control group contains patients who had normal DXA, while study group contains patients having either osteopenia or osteoporosis. Based on our inclusion and exclusion criteria, 110 persons were included in the study. We had 60 study and 50 controls patients. We had 88 females and 22 males. The results obtained were statistically analyzed. Statistical Analysis Used The collected data were analyzed with IBM SPSS statistics software 23.0 version. To describe about the data descriptive statistics frequency analysis, percentage analysis was used for categorical variables and the mean and standard deviation were used for continuous variables. To find the significant difference between the bivariate samples in independent groups, the unpaired sample t-test was used. To find the significance in categorical data, chi-square test was used. In both the earlier statistical tools, the probability value of 0.05 is considered as significant level. Results In our study, we had 18.2% osteopenic and 36.4% osteoporotic patients. The mean value of urinary N-telopeptide in control was 49.8 and in case was 182.5. The standard deviation of urinary N-telopeptide value in case was 159.9. Conclusion Urinary N-telopeptide can give reproducible results and be able to assist in the evaluation of the quantity as well as the quality and be a good judge of someone's risk of fracture. Hence, urinary N-telopeptide can be used as a diagnostic tool for diagnosing osteoporosis.

Mucosal-associated invariant T (MAIT) cells are a subset of T lymphocytes expressing a semi-invariant T-cell receptor (TCR) present as TCR Vα7.2-Jα33 in humans and TCR Vα19-Jα33 in mice. They are activated by ligands produced during microbial biosynthesis of riboflavin that is presented by major histocompatibility complex class I-related (MR1) molecules on antigen-presenting cells. MAIT cells also possess interleukin (IL)-12 and IL-18 receptors and can be activated by the respective cytokines released from microbially stimulated antigen-presenting cells. Therefore, MAIT cells can be involved in bacterial and viral defenses and are a significant part of the human immune system. They are particularly abundant in the liver, an organ serving as the second firewall of gut microbes next to the intestinal barrier. Therefore, the immune functions of MAIT cells are greatly impacted by changes in the gut-microbiota and play important roles in the gut-liver pathogenesis axis. In this review, we discuss the nature and mechanisms of MAIT cell activation and their dynamics during different types of liver pathogenesis conditions. We also share our perspectives on important aspects that should be explored further to reveal the exact roles that MAIT cells play in liver pathogenesis in the context of the gut microbiota.

Malnutrition and cognitive dysfunction are typical features of alcoholic liver disease (ALD) and are correlated with the development of complications. The aim of this study is to explore the effect of nutritional state and diet on cognitive function in ALD. A total of 43 patients with compensated alcoholic cirrhosis were enrolled, and a neuropsychological test was assessed according to body mass index (BMI, n = 9/group; normal liquid, 5% EtOH + regular liquid, 5% EtOH + high-carbohydrate liquid, 5% EtOH + high-fat liquid, and 5% EtOH + high-protein liquid diet) and fed the same calories for eight weeks. To assess cognitive function, we performed T-maze studies weekly before/after alcohol binging. In cognitive function (BMI < 22/≥22), language score of Korea mini-mental state (7.4 ± 1.4/7.9 ± 0.4), Boston naming (11.7 ± 2.7/13.0 ± 1.8), forward digit span (6.7 ± 1.8/7.5 ± 1.6), Korean color word stroop (24.2 ± 26.5/43.6 ± 32.4), and interference score (33.9 ± 31.9/52.3 ± 33.9) revealed significant differences. In the T-maze test, alcohol significantly delayed the time to reach food, and binge drinking provided a temporary recovery in cognition. The alcohol-induced delay was significantly reduced in the high-carbohydrate and high-fat diet groups. Synaptic function exhibited no changes in all groups. Cognitive dysfunction is affected by nutritional status and diet in ALD.

Advances in high-throughput screening of metabolic stability in liver and gut microbiota are able to identify and quantify small-molecule metabolites (metabolome) in different cellular microenvironments that are closest to their phenotypes. Metagenomics and metabolomics are largely recognized to be the “-omics” disciplines for clinical therapeutic screening. Here, metabolomics activity screening in liver disease (LD) and gut microbiomes has significantly delivered the integration of metabolomics data (i.e., a set of endogenous metabolites) with metabolic pathways in cellular environments that can be tested for biological functions (i.e., phenotypes). A growing literature in LD and gut microbiomes reports the use of metabolites as therapeutic targets or biomarkers. Although growing evidence connects liver fibrosis, cirrhosis, and hepatocellular carcinoma, the genetic and metabolic factors are still mainly unknown. Herein, we reviewed proof-of-concept mechanisms for metabolomics-based LD and gut microbiotas’ role from several studies (nuclear magnetic resonance, gas/lipid chromatography, spectroscopy coupled with mass spectrometry, and capillary electrophoresis). A deeper understanding of these axes is a prerequisite for optimizing therapeutic strategies to improve liver health.

BACKGROUND:Netrin-1, a secreted laminin-like protein identified as an axon guidance molecule, has been shown to be of critical importance in the cardiovascular system. Recent studies have revealed pro-angiogenic, anti-apoptotic and anti-inflammatory properties of netrin-1 as well as cardioprotective actions against myocardial injury in diabetic mice. AIM:To examine the role of netrin-1 in diabetes-and high glucose (HG)-induced vascular endothelial dysfunction (VED) using netrin-1 transgenic mice (Tg3) and cultured bovine aortic endothelial cells (BAEC). MAIN OUTCOME:Overexpression of netrin-1 prevented diabetes-induced VED in aorta from diabetic mice and netrin-1 treatment attenuated HG-induced impairment of nitric oxide synthase (NOS) function in BAECs. METHODS AND RESULTS:Experiments were performed in Tg3 and littermate control (WT) mice rendered diabetic with streptozotocin (STZ) and in BAECs treated with HG (25 mmol/L). Levels of netrin-1 and its receptor DCC, markers of inflammation and apoptosis and vascular function were assessed in aortas from diabetic and non-diabetic Tg3 and WT mice. Vascular netrin-1 in WT mice was reduced under diabetic conditions. Aortas from non-diabetic Tg3 and WT mice showed similar maximum endothelium-dependent relaxation (MEDR) (83% and 87%, respectively). MEDR was markedly impaired in aorta from diabetic WT mice (51%). This effect was significantly blunted in Tg3 diabetic aortas (70%). Improved vascular relaxation in Tg3 diabetic mice was associated with increased levels of phospho-ERK1/2 and reduced levels of oxidant stress, NFκB, COX-2, p16INK4A, cleaved caspase-3 and p16 and p53 mRNA. Netrin-1 treatment prevented the HG-induced decrease in NO production and elevation of oxidative stress and apoptosis in BAECs. CONCLUSIONS:Diabetes decreases aortic levels of netrin-1. However, overexpression of netrin-1 attenuates diabetes-induced VED and limits the reduction of NO levels, while increasing expression of p-ERK1/2, and suppressing oxidative stress and inflammatory and apoptotic processes. Enhancement of netrin-1 function may be a useful therapeutic means for preventing vascular dysfunction in diabetes.

Linear formulations are insufficient to take into account the effect of large deflections that occur after initial buckling. This effect can only be considered in the non-linear buckling analysis. In the present work, the non-linear analysis is carried out using the finite element method based on first-order shear deformation shell theories. Two non-linear shell theories, Donnel’s and Sanders’ theories, are used in the analysis. Based on the first-ply failure analysis and non-linear buckling analysis, the critical sizes and parameters of the tapered curved plates that will not fail before global buckling are determined. A parametric study that encompasses the effects of taper angle, critical length-to-height ratio, radius, radius-to-thickness ratio and geometric parameters of the plates is conducted.

Cisplatin is a widely used and highly effective cancer chemotherapeutic agent. One of the limiting side effects of cisplatin use is nephrotoxicity. Research over the past 10 years has uncovered many of the cellular mechanisms which underlie cisplatin-induced renal cell death. It has also become apparent that inflammation provoked by injury to renal epithelial cells serves to amplify kidney injury and dysfunction in vivo. This review summarizes recent advances in our understanding of cisplatin nephrotoxicity and discusses how these advances might lead to more effective prevention.

Acute kidney injury (AKI) is a common problem in the hospital setting and intensive care unit. Despite improved understanding, there are no effective therapies available to treat AKI. A large body of evidence strongly suggests that ischemia reperfusion injury is an inflammatory disease mediated by both adaptive and innate immune systems. Cell migration also plays an important role in embryonic development and inflammation, and this process is highly regulated to ensure tissue homeostasis. One such paradigm exists in the developing nervous system, where neuronal migration is mediated by a balance between chemoattractive and chemorepulsive signals. The ability of the guidance molecule netrin-1 to repulse or abolish attraction of neuronal cells expressing the UNC5B receptor makes it an attractive candidate for the regulation of inflammatory cell migration. Recent identification of netrin-1 as regulators of immune cell migration has led to a large number of studies looking into how netrin-1 controls inflammation and inflammatory cell migration. This review will focus on recent advances in understanding netrin-1 mediated regulation of inflammation during acute and chronic kidney disease and whether netrin-1 and its receptor activation can be used to treat acute and chronic kidney disease.

Acute kidney injury (AKI) is a serious complication after liver transplantation. Currently there are no validated biomarkers available for early diagnosis of AKI. The current study was carried out to determine the usefulness of the recently identified biomarkers netrin-1 and semaphorin 3A in predicting AKI in liver transplant patients. A total of 63 patients' samples were collected and analyzed. AKI was detected at 48 hours after liver transplantation using serum creatinine as a marker. In contrast, urine netrin-1 (897.8 ± 112.4 pg/mg creatinine), semaphorin 3A (847.9 ± 93.3 pg/mg creatinine) and NGAL (2172.2 ± 378.1 ng/mg creatinine) levels were increased significantly and peaked at 2 hours after liver transplantation but were no longer significantly elevated at 6 hours after transplantation. The predictive power of netrin-1, as demonstrated by the area under the receiver-operating characteristic curve for diagnosis of AKI at 2, 6, and 24 hours after liver transplantation was 0.66, 0.57 and 0.59, respectively. The area under the curve for diagnosis of AKI was 0.63 and 0.65 for semaphorin 3A and NGAL at 2 hr respectively. Combined analysis of two or more biomarkers for simultaneous occurrence in urine did not improve the AUC for the prediction of AKI whereas the AUC was improved significantly (0.732) only when at least 1 of the 3 biomarkers in urine was positive for predicting AKI. Adjusting for BMI, all three biomarkers at 2 hours remained independent predictors of AKI with an odds ratio of 1.003 (95% confidence interval: 1.000 to 1.006; P = 0.0364). These studies demonstrate that semaphorin 3A and netrin-1 can be useful early diagnostic biomarkers of AKI after liver transplantation.

Semaphorin 3A is a secreted protein that regulates cell motility and attachment in axon guidance, vascular growth, immune cell regulation and tumor progression. However, nothing is known about its role in kidney pathophysiology. Here, we determined whether semaphorin3A is induced after acute kidney injury (AKI) and whether urinary semaphorin 3A can predict AKI in humans undergoing cardiopulmonary bypass (CPB).In animals, semaphorin 3A is localized in distal tubules of the kidney and excretion increased within 3 hr after reperfusion of the kidney whereas serum creatinine was significantly raised at 24 hr. In humans, using serum creatinine, AKI was detected on average only 48 hours after CPB. In contrast, urine semaphorin increased at 2 hours after CPB, peaked at 6 hours (2596±591 pg/mg creatinine), and was no longer significantly elevated 12 hours after CPB. The predictive power of semaphorin 3A as demonstrated by area under the receiver-operating characteristic curve for diagnosis of AKI at 2, 6, and 12 hours after CPB was 0.88, 0.81, and 0.74, respectively. The 2-hour urine semaphorin measurement strongly correlated with duration and severity of AKI, as well as length of hospital stay. Adjusting for CPB time and gender, the 2-hour semaphorin remained an independent predictor of AKI, with an odds ratio of 2.19.Our results suggest that semaphorin 3A is an early, predictive biomarker in experimental and pediatric AKI, and may allow for the reliable early diagnosis and prognosis of AKI after CPB, much before the rise in serum creatinine.

Netrin-1 is a laminin-related secreted protein, is highly induced after tissue injury, and may serve as a marker of injury. However, the regulation of netrin-1 production is not unknown. Current study was carried out in mouse and mouse kidney cell line (TKPTS) to determine the signaling pathways that regulate netrin-1 production in response to injury.Ischemia reperfusion injury of the kidney was induced in mice by clamping renal pedicle for 30 minutes. Cellular stress was induced in mouse proximal tubular epithelial cell line by treating with pervanadate, cisplatin, lipopolysaccharide, glucose or hypoxia followed by reoxygenation. Netrin-1 expression was quantified by real time RT-PCR and protein production was quantified using an ELISA kit. Cellular stress induced a large increase in netrin-1 production without increase in transcription of netrin-1 gene. Mitogen activated protein kinase, ERK mediates the drug induced netrin-1 mRNA translation increase without altering mRNA stability.Our results suggest that netrin-1 expression is suppressed at the translational level and MAPK activation leads to rapid translation of netrin-1 mRNA in the kidney tubular epithelial cells.

Abstract Cotyledonoid dissecting leiomyoma of the uterus is a recently described rare variant of benign uterine leiomyoma. We report a case of cotyledonoid dissecting leiomyoma in a 52 year old woman who presented with menorrhagia and abdominal pain. An ultrasound scan showed a bulky uterus and a cystic heterogenous mass near the left ovary. At hysterectomy, the left broad ligament mass was removed. This was continuous with an ill-defined nodular area in the myometrial fundus. Microscopy revealed a benign smooth muscle proliferation in the myometrium that extended beyond the uterus and into the broad ligament. The lesion appeared to be dissecting the myometrial fibres and showed areas of oedema, hyalinisation and perinodular hydropic change. Cellular atypia, mitoses and coagulative necrosis were absent. The patient is alive and well 18 months after surgery. It is important to recognize this benign and unusual appearing variant of leiomyoma in order to prevent inappropriate treatment.

High-order interactions are required across brain regions to accomplish specific cognitive functions. These functional interdependencies are reflected by synergistic information that can be obtained by combining the information from all the sources considered and redundant information (i.e., common information provided by all the sources). However, electroencephalogram (EEG) functional connectivity is limited to pairwise interactions thereby precluding the estimation of high-order interactions. In this multicentric study, we used measures of synergistic and redundant information to study in parallel the high-order interactions between five EEG electrodes during three non-ordinary states of consciousness (NSCs): Rajyoga meditation (RM), hypnosis, and auto-induced cognitive trance (AICT). We analyzed EEG data from 22 long-term Rajyoga meditators, nine volunteers undergoing hypnosis, and 21 practitioners of AICT. We here report the within-group changes in synergy and redundancy for each NSC in comparison with their respective baseline. During RM, synergy increased at the whole brain level in the delta and theta bands. Redundancy decreased in frontal, right central, and posterior electrodes in delta, and frontal, central, and posterior electrodes in beta1 and beta2 bands. During hypnosis, synergy decreased in mid-frontal, temporal, and mid-centro-parietal electrodes in the delta band. The decrease was also observed in the beta2 band in the left frontal and right parietal electrodes. During AICT, synergy decreased in delta and theta bands in left-frontal, right-frontocentral, and posterior electrodes. The decrease was also observed at the whole brain level in the alpha band. However, redundancy changes during hypnosis and AICT were not significant. The subjective reports of absorption and dissociation during hypnosis and AICT, as well as the mystical experience questionnaires during AICT, showed no correlation with the high-order measures. The proposed study is the first exploratory attempt to utilize the concepts of synergy and redundancy in NSCs. The differences in synergy and redundancy during different NSCs warrant further studies to relate the extracted measures with the phenomenology of the NSCs., Competing Interests: Declaration of competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. C.S. is the founder of TranceScience Research Institute in Paris., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Using a single EOG channel, sleep-wake states of patients with different sleep disorders are accurately classified. We used polysomnography data of 27 patients (mixed apnea, periodic limb movement syndrome, sleep apnea-hypopnea syndrome, and dyssomnia) from DRMS-PAT and 20 healthy subjects from DRMS-SUB databases. We extracted a 67-dimensional feature vector, involving statistical features derived from ensemble empirical mode decomposition, approximate entropy, and relative powers in different frequency bands. Of these, the most relevant features are selected by exploiting mutual information between the features and corresponding labels. RUSBoost classifier is deployed to take care of the unbalanced data distribution. We achieved a high sensitivity of 97.5% and 95.3% as well as high specificity of 96.4% and 93.3% for sleep state in healthy and patients' groups, respectively. Ten-fold crossvalidation accuracies of 91.6% and 95% are achieved for patients and healthy individuals, respectively, using a single EOG channel. Clinical relevance-Accurate detection of sleep-wake states is crucial for the diagnosis of various sleep disorders including apnea-hypopnea syndrome and insomnia. Automated sleep-wake classification using EOG facilitates easy and convenient long-term sleep monitoring of patients without disturbing their sleep, thereby assisting the clinicians to analyze their sleeping patterns.

This work proposes a method utilizing only the submentalis EMG channel for the classification of sleep and wake states among the healthy individuals and patients with various sleep disorders such as sleep apnea hypopnea syndrome, dyssomnia, etc. We extracted autoregressive model parameters, discrete wavelet transform coefficients, Hjorth's complexity and mobility, relative bandpowers, Poincaré plot descriptors and statistical features from the EMG signal. We also used the energy of each epoch as a feature to distinguish between the sleep and wake states. Mutual information based feature selection approach was considered to obtain the top 25 features which provided maximum accuracy. For classification, we employed an ensemble of decision trees with random undersampling and boosting technique to deal with the class-imbalance problem in the sleep data. We achieved an overall accuracy of about 85% for the healthy population and about 70% on an average across different pathological groups. This work shows the potential of EMG chin activity for sleep analysis. Clinical Relevance- Automatic and reliable sleep-wake classification can reduce the burden of sleep experts in analyzing overnight sleep data (~ 8 hours) and also assist them to diagnose various neurological disorders at an early stage. Utilizing EMG channel provides an easier and convenient long-term recording of data without causing much disturbance in sleepunlike EEG which is inconvenient and hampers the natural sleep.

This work proposes a method utilizing the fusion of graph-based and temporal features for sleep stage identification. EEG epochs are transformed into visibility graphs from which mean degrees and degree distributions are obtained. In addition, autoregressive model parameters, Higuchi fractal dimension, multi-scale entropy, and Hjorth's parameters are calculated. All these features extracted from a single EEG channel (Pz-Oz) are fed to an ensemble classifier called random undersampling with boosting technique. Two different approaches i.e. 10-fold crossvalidation and 50%-holdout are utilized to evaluate the performance of the model. Cross-validation accuracies of 91.0% and 97.3%, and kappa coefficients of 0.82 and 0.94 are achieved for 6- and 2-state classifications, respectively, which are higher than those of existing studies.Clinical relevance- Automatic and reliable sleep stage classification can reduce the burden of sleep experts in analyzing overnight sleep data (~ 8 hours). It can also assist them to find specific traits of interest such as spindle density, by providing annotated sleep data (hypnogram), thereby eliminating the need for tedious and expensive manual scoring. An accurate 2-state (wake/sleep) classification is also crucial for the patients with disorders of consciousness, where stimulation during wake state is considered more effective than that in sleep state.

In 47 patients with Parkinson's disease, we studied the visual evoked potential (VEP) using the pattern-reversal checkerboard (CBVEP) and the grating (GVEP) stimuli before and after 3 months of L-dopa therapy. The P100 latency in both CBVEP and GVEP was prolonged before L-dopa therapy, usually commensurate with the degree of motor disability. Clinical improvement of the parkinsonian state after L-dopa therapy was associated with shortening of the P100 latency in CBVEP, but not significantly in GVEP.