Artificial neural networks in soil quality prediction: Significance for sustainable tea cultivation.

In today's era artificial intelligence is quite popular, one of the most effective algorithms used is Artificial Neural Networks (ANN). In this study, the determination of soil quality using the Soil Management Assessment Framework (SMAF) model in areas where tea cultivation is carried out at the micro-watershed scale and the predictability of soil quality using ANN were evaluated. According to the results, the soil quality indices of tea-growing areas were generally classified as "medium" between 55 and 70 %. Among the evaluated features for determining soil quality, the highest relative importance value was for soil organic carbon content (13 %) and potential mineralizable nitrogen (13 %), whereas the lowest values were for exchangeable potassium (4 %) and sodium adsorption ratio (SAR) (4 %). In addition, when comparing the actual and predicted values for soil quality prediction using ANN, the Lin's concordance correlation coefficient (LCCC), ratio of performance to deviation (RPD), and R2 values were found to be 0.93, 2.95, and 0.89, respectively. Significant properties for the determined values within a 90 % predicted interval were found to be organic matter, microbial biomass carbon, bulk density, and aggregate stability of the soils. Moreover, the uncertainty values (standard deviation) in the model predictions were determined to be within the range of 1.01-4.56 %. Consequently, the Soil Quality Index (SQI) obtained from the SMAF model using 12 soil properties in tea-growing areas could be accurately predicted using ANN. As a result of this study, digital maps showing the spatial distribution of SQI and the predicted uncertainties can help monitor SQI levels in this area.

Proceedings of the EuBIC-MS developers meeting 2023.

The 2023 European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Developers Meeting was held from January 15th to January 20th, 2023, in Congressi Stefano Franscin at Monte Verità in Ticino, Switzerland. The participants were scientists and developers working in computational mass spectrometry (MS), metabolomics, and proteomics. The 5-day program was split between introductory keynote lectures and parallel hackathon sessions focusing on "Artificial Intelligence in proteomics" to stimulate future directions in the MS-driven omics areas. During the latter, the participants developed bioinformatics tools and resources addressing outstanding needs in the community. The hackathons allowed less experienced participants to learn from more advanced computational MS experts and actively contribute to highly relevant research projects. We successfully produced several new tools applicable to the proteomics community by improving data analysis and facilitating future research.

A rapid and multi-endpoint ecotoxicological test using Mychonastes afer for efficient screening of metals and herbicides.

Microalgal growth-based tests are international standards for ecotoxicity assessment; however, their long exposure times, large sample volumes, and reliance on a single growth-endpoint make them inadequate for rapid toxicity screening. Here, we aimed to develop a rapid and simple ecotoxicological test using the fast-growing green alga Mychonastes afer, with multiple endpoints-growth, lipid content, and photosynthesis. We exposed M. afer to two metals-silver and copper-and two herbicides-atrazine and diuron-for 24 h and identified the most sensitive and reliable endpoints for each toxicant: the maximum electron transport rate (ETRmax) for Ag, Cu and atrazine, and the lipid content for diuron. Lipid content was found to be both a sensitive and reliable biomarker, meeting the effluent limit guidelines in both the Republic of Korea and the USA. The sensitivity of M. afer to Ag and atrazine also closely matched the HC5 values derived from the species sensitivity distribution approach, confirming its reliability for setting regulatory concentrations of these contaminants. Our calculated predicted no-effect concentration (PNEC) values were similar to established European Union PNECs for Ag, Cu, atrazine, and diuron, underlining the utility of these biological endpoints for ecological risk assessment and regulatory decision making. This method required lower sample volume (2 mL vs 100 mL) and exposure time (24 h vs 72-120 h) than conventional green algal tests, and eliminated the need for labour-intensive cell counting, expensive equipment, and chlorophyll fluorescence measurement expertise. Overall, this M. afer test can be a valuable tool for the rapid screening of wastewater for metals and herbicides, contributing to environmental protection and management practices.

Dissecting loci that underpin the genetic correlations between production, fertility, and urea traits in Australian Holstein cattle.

Unfavorable genetic correlations between milk production, fertility, and urea traits have been reported. However, knowledge of the genomic regions associated with these unfavorable correlations is limited. Here, we used the correlation scan method to identify and investigate the regions driving or antagonizing the genetic correlations between production vs. fertility, urea vs. fertility, and urea vs. production traits. Driving regions produce an estimate of correlation that is in the same direction as the global correlation. Antagonizing regions produce an estimate in the opposite direction of the global estimates. Our dataset comprised 6567, 4700, and 12,658 Holstein cattle with records of production traits (milk yield, fat yield, and protein yield), fertility (calving interval) and urea traits (milk urea nitrogen and blood urea nitrogen predicted using milk-mid-infrared spectroscopy), respectively. Several regions across the genome drive the correlations between production, fertility, and urea traits. Antagonizing regions were confined to certain parts of the genome and the genes within these regions were mostly involved in preventing metabolic dysregulation, liver reprogramming, metabolism remodeling, and lipid homeostasis. The driving regions were enriched for QTL related to puberty, milk, and health-related traits. Antagonizing regions were mostly related to muscle development, metabolic body weight, and milk traits. In conclusion, we have identified genomic regions of potential importance for dairy cattle breeding. Future studies could investigate the antagonizing regions as potential genomic regions to break the unfavorable correlations and improve milk production as well as fertility and urea traits.

Localized Path Planning for Mobile Robots Based on a Subarea-Artificial Potential Field Model.

The artificial potential field method has efficient obstacle avoidance ability, but this traditional method suffers from local minima, unreasonable paths, and sudden changes in heading angles during obstacle avoidance, leading to rough paths and increased energy consumption. To enable autonomous mobile robots (AMR) to escape from local minimum traps and move along reasonable, smooth paths while reducing travel time and energy consumption, in this paper, an artificial potential field method based on subareas is proposed. First, the optimal virtual subgoal was obtained around the obstacles based on the relationship between the AMR, obstacles, and goal points in the local environment. This was done according to the virtual subgoal benefit function to solve the local minima problem and select a reasonable path. Secondly, when AMR encountered an obstacle, the subarea-potential field model was utilized to solve problems such as path zigzagging and increased energy consumption due to excessive changes in the turning angle; this helped to smooth its planning path. Through simulations and actual testing, the algorithm in this paper demonstrated smoother heading angle changes, reduced energy consumption, and a 10.95% average reduction in movement time when facing a complex environment. This proves the feasibility of the algorithm.

Right Ventricular Sizing and Pulmonary Vascular Resistance: How Much Mass Do You Need?

OBJECTIVE: Right ventricular (RV) donor-recipient sizing has been demonstrated to be a sensitive predictor for mortality after heart transplantation. We sought to understand the relationship between donor-recipient RV mass (RVM) ratio and pulmonary vascular resistance (PVR) on outcomes after heart transplantation. METHODS: Adult heart transplant recipients from the UNOS database were included (N=42,594). The impact of RVM ratio and PVR on 1-year mortality was assessed by logistic regression after multivariable adjustment. RESULTS: Among transplant recipients, median PVR was 2.4 (1.7-3.3) WU and median RVM ratio was 1.2 (1.0-1.3). Without considering PVR, RVM ratio was highly associated with postoperative dialysis (OR=0.49, P<0.001) and 1-year mortality (OR=0.64, P<0.001). Without considering RVM ratio, PVR was highly associated with 1-year mortality (OR=1.05, P<0.001), but not postoperative dialysis (OR=0.98, P=0.156). When considering both RVM ratio and PVR, the risk associated with each remained significant, but PVR did not modify the effect of RVM ratio on 1-year mortality (RVM ratio*PVR: OR=0.99, P=0.858). In order to maintain a consistent predicted 1-year mortality, RVM ratio would need to increase by 0.12 for each WU increase in PVR. Secondary analyses found that a 1 WU change in PVR was associated with an 11% increase in mortality risk in RVM ratio mismatched patients (RVM ratio <1; P=0.001), but only a 5% increase in RVM ratio matched patients (RVM ratio ≥1; P=0.003). CONCLUSION: RVM ratio and recipient PVR are independent predictors of 1-year mortality. Still, a larger RV mass may be utilized to mediate the effects of an elevated PVR.

The Relationship between the Measured Blood Concentration of Rocuronium in Stable Muscle Relaxation with a Closed-Loop Control and the Estimated Blood Concentration from a Pharmacokinetic Simulation.

We developed a system to adjust the rate of a continuous rocuronium (Rb) infusion to achieve 3 ≤ %T1 ≤ 10 with a closed-loop control. Samples were collected from 15 patients, and Rb blood concentrations were measured at the following time points: (1) when %T1 recovered to 3% or more after the initial Rb infusion; (2) when %T1 stabilized within the target range; (3) at the cessation of the Rb infusion; (4) 5 min after the sugammadex administration. The predicted Rb blood concentration at each time point was calculated and recorded using the pharmacokinetic parameters of Wierda et al. At time points (1), (2), and (3), the predicted blood concentrations were in good agreement with the measured values, but after the administration of sugammadex, the blood concentrations were higher than the predicted values because the Rb distributed in the tissues migrated into the blood. From the above, it was confirmed that the predicted blood concentration of Rb can be a good indicator for the automatic Rb administration control.

Brain age as a biomarker for pathological versus healthy ageing - a REMEMBER study.

OBJECTIVES: This study aimed to evaluate the potential clinical value of a new brain age prediction model as a single interpretable variable representing the condition of our brain. Among many clinical use cases, brain age could be a novel outcome measure to assess the preventive effect of life-style interventions. METHODS: The REMEMBER study population (N = 742) consisted of cognitively healthy (HC,N = 91), subjective cognitive decline (SCD,N = 65), mild cognitive impairment (MCI,N = 319) and AD dementia (ADD,N = 267) subjects. Automated brain volumetry of global, cortical, and subcortical brain structures computed by the CE-labeled and FDA-cleared software icobrain dm (dementia) was retrospectively extracted from T1-weighted MRI sequences that were acquired during clinical routine at participating memory clinics from the Belgian Dementia Council. The volumetric features, along with sex, were combined into a weighted sum using a linear model, and were used to predict 'brain age' and 'brain predicted age difference' (BPAD = brain age-chronological age) for every subject. RESULTS: MCI and ADD patients showed an increased brain age compared to their chronological age. Overall, brain age outperformed BPAD and chronological age in terms of classification accuracy across the AD spectrum. There was a weak-to-moderate correlation between total MMSE score and both brain age (r = -0.38,p < .001) and BPAD (r = -0.26,p < .001). Noticeable trends, but no significant correlations, were found between BPAD and incidence of conversion from MCI to ADD, nor between BPAD and conversion time from MCI to ADD. BPAD was increased in heavy alcohol drinkers compared to non-/sporadic (p = .014) and moderate (p = .040) drinkers. CONCLUSIONS: Brain age and associated BPAD have the potential to serve as indicators for, and to evaluate the impact of lifestyle modifications or interventions on, brain health.

Enlarged perivascular spaces are associated with brain microangiopathy and aging in multiple sclerosis.

BACKGROUND: Growing evidence links brain-MRI enlarged perivascular spaces (EPVS) and multiple sclerosis (MS), but their role remains unclear. OBJECTIVE: This study aimed to investigate the cross-sectional associations of EPVS with several neuroinflammatory and neurodegenerative features in a large multicentric-MS cohort. METHODS: In total, 207 patients underwent 3T axial-T2-weighted brain-MRI for EPVS assessment (EPVS dichotomized into high/low according to ⩾ 2/< 2 rating categories). MRI biomarkers included brain-predicted age and brain-predicted age difference (brain-PAD), central vein sign (CVS)-positive lesion percentage (CVS%), paramagnetic rim and cortical lesions, T2-lesion load, and brain volumetry. The variable relative importance for EPVS-category prediction was explored using a classification random forest approach. RESULTS: High EPVS patients were older (49 vs 44 years, p = 0.003), had ⩾ 1 vascular risk factors (VRFs; p = 0.005), lower CVS% (67% vs 78%, p < 0.001), reduced brain volumes (whole brain: 0.63 vs 0.73, p = 0.01; gray matter: 0.36 vs 0.40; p = 0.002), and older brain-predicted age (58 vs 50 years, p < 0.001). No differences were found for neuroinflammatory markers. After adjusting for age and VFRs (multivariate analyses), the high EPVS category correlated with lower CVS% (odds ratio (OR) = 0.98, 95% confidence interval (CI) = 0.96-0.99; p = 0.02), lower whole brain (OR = 0.01, 95% CI = 0.0003-0.5; p = 0.02), gray matter (OR = 0.0004, 95% CI = 0.0000004-0.4; p = 0.03) volumes, and higher brain-PAD (OR = 1.05, 95% CI = 1.01-1.09; p = 0.02). Random forest identified brain-PAD as the most important predictor of high EPVS. CONCLUSION: EPVS in MS likely reflect microangiopathic disease rather than neuroinflammation, potentially contributing to accelerated neurodegeneration.

Haemodynamic and clinical outcomes at 5 years according to predicted prosthesis-patient mismatch after transcatheter aortic valve replacement.

BACKGROUND/PURPOSE: Although the impact of predicted prosthesis-patient mismatch (PPMP) on outcomes after surgical aortic valve replacement is well established, studies on PPMP in transcatheter aortic valve replacement (TAVR) are limited. This study investigated the effects of PPMp on haemodynamic and 5-year clinical outcomes after TAVR. METHODS/MATERIALS: We analysed 1733 patients who underwent TAVR. PPMp was defined using two different methods: 1) normal reference values of the effective orifice area for each valve type and size indexed to body surface area (PPMp1; n = 1733) and 2) reference values for aortic annulus area or perimeter assessed with pre-procedural computed tomography indexed to body surface area (PPMp2; n = 1227). The primary endpoint was the composite of all-cause death and/or rehospitalisation for heart failure at 5 years. RESULTS: The incidence of PPMp1 was 11.7 % and 0.8 % in moderate and severe cases, respectively. PPMp2 was classified as either moderate (3.8 %) or severe (0 %). Rates of residual mean aortic gradient ≥20 mmHg significantly increased depending on PPMp1 severity (no PPMp1: 3.1 % vs. moderate PPMp1: 26.8 % vs. severe PPMp1: 53.9 %, p < 0.0001) and PPMp2 (no PPMp2: 4.1 % vs. moderate PPMp2: 12.8 %, p = 0.0049). Neither of PPMP methods were associated with the composite outcome in total cohort; however, PPMP1 was significantly related to worse clinical outcomes at 5 years among patients with reduced left ventricular ejection fraction (LVEF) in multivariate analysis (HR: 1.87; 95 % CI: 1.02-3.43). CONCLUSIONS: The impact of PPMP on TAVR clinical outcomes may not be negligible in patients with low LVEF.

Identification of an inflammatory response-related gene prognostic signature and immune microenvironment for cervical cancer.

Background: Cervical cancer (CC) is the fourth most common cancer among women worldwide. As part of the brisk cross-talk between the host and the tumor, prognosis can be affected through inflammatory responses or the tumor microenvironment. However, further exploration of the inflammatory response-related genes that have prognostic value, microenvironment infiltration, and chemotherapeutic therapies in CC is needed. Methods: The clinical data and mRNA expression profiles of CC patients were downloaded from a public database for this study. In the TCGA cohort, a multigene prognostic signature was constructed by least absolute shrinkage and selection operator (LASSO) and Cox analyses. CC patients from the GEO cohort were used for validation. K‒M analysis was used to compare overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors of OS. The immune cell infiltration and immune-related functional score were calculated by single-sample gene set enrichment analysis (GSEA). Immunohistochemistry was utilized to validate the protein expression of prognostic genes in CC tissues. Results: A genetic signature model associated with the inflammatory response was built by LASSO Cox regression analysis. Patients in the high-risk group had a significantly lower OS rate. The predictive ability of the prognostic genes was evaluated by means of receiver operating characteristic (ROC) curve analysis. The risk score was confirmed to be an independent predictor of OS by univariate and multivariate Cox analyses. The immune status differed between the high-risk and low-risk groups, and the cancer-related pathways were enriched in the high-risk group according to functional analysis. The risk score was significantly related to tumor stage and immune infiltration type. The expression levels of five prognostic genes (LCK, GCH1, TNFRSF9, ITGA5, and SLC7A1) were positively related to sensitivity to antitumor drugs. Additionally, the expression of prognostic genes was significantly different between CC tissues and myoma patient cervix (non-tumorous) tissues in the separate sample cohort. Conclusion: A model consisting of 5 inflammation-related genes can be used to predict prognosis and influence immune status in CC patients. Furthermore, the inhibition or enhancement of these genes may become a novel alternative therapy.

Experimental Data on PIRCHE and T-Cell Reactivity: HLA-DPB1-Derived Peptides Identified by PIRCHE-I Show Binding to HLA-A*02:01 in vitro and T-Cell Activation in vivo.

Introduction: Human leukocyte antigen (HLA)-DPB1 mismatches during hematopoietic stem cell transplantation (HSCT) with an unrelated donor result in an increased risk for the development of graft-versus-host disease (GvHD). The number of CD8+ T-cell epitopes available for indirect allorecognition as predicted by the PIRCHE algorithm has been shown to be associated with GvHD development. As a proof of principle, PIRCHE-I predictions for HLA-DPB1 mismatches were validated in vitro and in vivo. Methods: PIRCHE-I analysis was performed to identify HLA-DPB1-derived peptides that could theoretically bind to HLA-A*02:01. PIRCHE-I predictions for HLA-DPB1 mismatches were validated in vitro by investigating binding affinities of HLA-DPB1-derived peptides to the HLA-A*02:01 in a competition-based binding assay. To investigate the capacity of HLA-DPB1-derived peptides to elicit a T-cell response in vivo, mice were immunized with these peptides. T-cell alloreactivity was subsequently evaluated using an interferon-gamma ELISpot assay. Results: The PIRCHE-I algorithm identified five HLA-DPB1-derived peptides (RMCRHNYEL, YIYNREEFV, YIYNREELV, YIYNREEYA, and YIYNRQEYA) to be presented by HLA-A*02:01. Binding of these peptides to HLA-A*02:01 was confirmed in a competition-based peptide binding assay, all showing an IC50 value of 21 µm or lower. The peptides elicited an interferon-gamma response in vivo. Conclusion: Our results indicate that the PIRCHE-I algorithm can identify potential immunogenic HLA-DPB1-derived peptides present in recipients of an HLA-DPB1-mismatched donor. These combined in vitro and in vivo observations strengthen the validity of the PIRCHE-I algorithm to identify HLA-DPB1 mismatch-related GvHD development upon HSCT.

Influence of antipsychotic drugs on microRNA expression in schizophrenia patients - A systematic review.

Schizophrenia (SCZ) is a severe psychiatric disorder with unclear pathophysiology. Moreover, there is no specific biological marker to help clinicians to define a diagnosis, and medication is decided according to the psychiatrist's experience. In this scenario, microRNAs (miRNAs), which are small noncoding RNA molecules that regulate several genes, emerge as potential peripheral biomarkers to help not only the evaluation of the disease state but also the treatment response. Here, we systematically reviewed indexed literature and evaluated follow-up studies investigating the changes in miRNA expression due to antipsychotic treatment. We also assessed target genes and performed pathway enrichment analysis of miRNAs listed in this systematic review. A total of 11 studies were selected according to research criteria, and we observed that 28 miRNAs play a relevant role in schizophrenia pathogenesis or response to antipsychotic treatment, seven of those of extreme interest as possible biomarkers either for condition or treatment. Predicted targets of the miRNAs reviewed here were previously associated with schizophrenia in genome-wide studies, and pathway analysis showed enrichment for genes related to neural processes. With this review, we expect to highlight the importance of miRNAs in schizophrenia pathogenesis and its treatment and point out interesting miRNAs to future studies.

Biped Gait Stability Classification Based on the Predicted Step Viability.

In this paper, we address the challenge of ensuring stability in bipedal walking robots and exoskeletons. We explore the feasibility of real-time implementation for the Predicted Step Viability algorithm (PSV), a complex multi-step optimization criterion for planning future steps in bipedal gait. To overcome the high computational cost of the PSV algorithm, we performed an analysis using 11 classification algorithms and a stacking strategy to predict if a step will be stable or not. We generated three datasets of increasing complexity through PSV simulations to evaluate the classification performance. Among the classifiers, k Nearest Neighbors, Support Vector Machine with Radial Basis Function Kernel, Decision Tree, and Random Forest exhibited superior performance. Multi-Layer Perceptron also consistently performed well, while linear-based algorithms showed lower performance. Importantly, the use of stacking did not significantly improve performance. Our results suggest that the feature vector applied with this approach is applicable across various robotic models and datasets, provided that training data is balanced and sufficient points are used. Notably, by leveraging classifiers, we achieved rapid computation of results in less than 1 ms, with minimal computational cost.

Adding Letrozole to Growth Hormone and Gonadotropin-Releasing Hormone Analog Increases Height in Girls With Short Stature: A Hospital Record-Based Retrospective Study.

OBJECTIVE: There have been rare data on letrozole for height improvement in girls. This study aimed to clarify the efficacy and safety of combination therapy with recombinant human growth hormone (rhGH), GnRHa, and letrozole in improving the height of girls with short stature and advanced bone age. METHODS: This was a hospital record-based retrospective study. Follow-up was conducted on girls with short stature who received treatment with rhGH, GnRHa, and letrozole in our hospital. The treatment group included a total of 29 participants. Before treatment, the mean age of the patients was 11.17 years, and the mean treatment duration was 17.31 months. The control group consisted of 29 short-statured girls who received rhGH/GnRHa treatment, with the mean age and treatment duration of 12.43 years and 16.59 months, respectively. RESULTS: The predicted adult heights (PAHs) before and after treatment were 155.38 and 161.32 cm (P < .001). The ΔPAH in the treatment group was 4 cm higher than that in the control group (5.85 vs 1.82 cm, P < .001). Significant differences were noted in the height standard deviation scores of bone age (P < .001) and chronological age (P = .003) before and after treatment. There was an increasing body mass index during therapy (P = .039). The height gain was 8.71 ± 4.46 cm, and the growth rate was 6.78 ± 3.84 cm per year. CONCLUSION: Combined treatment with GH, GnRHa, and letrozole can enhance the adult height and PAH in short-statured girls, and no significant side effects have been reported.

Coping strategies and brain activity in table tennis players faced with discrepancies between predicted and actual outcomes.

Prior studies have shown that experts possess an excellent ability for action anticipation. However, it is not clear how experts process the discrepancies between predicted outcomes and actual outcomes. Based on Bayesian theory, Experiment 1 in the current study explored this question by categorizing unexpected outcomes into gradually increasing discrepancies and comparing the performance of experts and novices on a congruence discrimination task. Our behavioral analysis revealed that experts outperformed novices significantly in detecting these discrepancies. The following electroencephalogram study in Experiment 2 was conducted focused exclusively on experts to examine the role of theta wave oscillations within the mid-frontal cortex in processing varying levels of discrepancy. The results showed that reaction time and theta oscillations gradually increased as the magnitude of discrepancy increased. These findings indicate that compared to the novices, experts have a better ability to perceptual the discrepancy. Also, the magnitude of discrepancies induced an increase in mid-frontal theta in experts, providing greater flexibility in their response strategies.

Spatial and temporal characteristics of microbial communities in the Seine river in the greater Paris area under anthropogenic perturbation.

Microorganisms play an important role in maintaining the proper functioning of river ecosystems and are promising candidates for environmental indicators. They are also highly sensitive to environmental changes. It is necessary to have basic knowledge about them in order to know the ecological status of river ecosystem. To our knowglege, there is very little information on the status of microorganisms in surface water of the Seine River, although the Seine River is one of the rivers that suffers the greatest impact from humain activities in the world due to a weak dilution effect. It is therefore necessary to carry out a microbial analysis to assess the ecological status of the Seine River and to use it as a reference to compare with the future state when, for instance, new disinfection technologies of wastewater are implemented. To this end, the microbial communities of the Seine surface water were analyzed, taking into account the spatial effect, including the tributaries, and from upstream to downstream of the Paris conurbation and the temporal aspect, with a monitoring over 4 seasons. The results showed that the microbiome of the water is highly diverse and involved a variety of functions. The main phyla making up the surface water microbiome were Proteobacteria, Actinobacteriota, Firmicutes, Bacteroidota, while other minor phyla were Deinococcota, Patescibacteria, Gemmatimonadota, Cyanobacteria, Bdellovibrionota, Acidobacteriota, Campilobacterota, Myxococcota, and Desulfobacterota. Overall, the microbial community did not change spatially (with the exception of some minor differences between upstream and downstream), but did vary seasonally. The main factors influencing this microbiome were temperature, nitrate and orthophosphate concentrations. The main predicted functions were related to cell metabolism, in particular carbohydrates, amino acids, lipids, energy, vitamins and cofactors, and cell mobility. The microbial compositions showed a strong balance between microbial groups and were involved in the degradation of recalcitrant compounds.

Identification of ROS and KEAP1-related genes and verified targets of α-hederin induce cell death for CRC.

In this study, we analyzed and verified differentially expressed genes (DEGs) in ROS and KEAP1 crosstalk in oncogenic signatures using GEO data sets (GSE4107 and GSE41328). Multiple pathway enrichment analyses were finished based on DEGs. The genetic signature for colorectal adenocarcinoma (COAD) was identified by using the Cox regression analysis. Kaplan-Meier survival and receiver operating characteristic curve analysis were used to explore the prognosis value of specific genes in COAD. The potential immune signatures and drug sensitivity prediction were also analyzed. Promising small-molecule agents were identified and predicted targets of α-hederin in SuperPred were validated by molecular docking. Also, expression levels of genes and Western blot analysis were conducted. In total, 48 genes were identified as DEGs, and the hub genes such as COL1A1, CXCL12, COL1A2, FN1, CAV1, TIMP3, and IGFBP7 were identified. The ROS and KEAP1-associated gene signatures comprised of hub key genes were developed for predicting the prognosis and evaluating the immune cell responses and immune infiltration in COAD. α-hederin, a potential anti-colorectal cancer (CRC) agent, was found to enhance the sensitivity of HCT116 cells, regulate CAV1 and COL1A1, and decrease KEAP1, Nrf2, and HO-1 expression significantly. KEAP1-related genes could be an essential mediator of ROS in CRC, and KEAP1-associated genes were effective in predicting prognosis and evaluating individualized CRC treatment. Therefore, α-hederin may be an effective chemosensitizer for CRC treatments in clinical settings.

Wrist Circumference Cutoff Points for Determining Excess Weight Levels and Predicting Cardiometabolic Risk in Adults.

(1) Background: An elevated wrist circumference may indicate excess weight and cardiometabolic risk. The present study aims to identify wrist circumference cutoff points (WrC) to determine excess weight levels and predict cardiometabolic risk in adults. (2) Methods: A cross-sectional study was conducted with adults aged 20 to 59 years old, attending the outpatient clinic at University Hospital/Federal University of Sergipe HU/UFS-EBSERH. Demographic, anthropometric, biochemical, and blood pressure (BP) data were collected. Cardiometabolic risk was assessed, according to the global risk score (ERG) and Framingham score criteria. The descriptive analysis included calculating medians and frequencies of anthropometric, demographic, biochemical, and blood pressure variables. The gender and age of adult groups were compared using the Mann-Whitney test. Spearman's correlation coefficient and multiple regression analysis were used to assess the association between wrist circumference (WrC) and the variables mentioned above. The predictive validity of WrC in identifying excess weight levels and cardiometabolic risk was analyzed using the ROC curve. The sample consisted of 1487 adults aged 20 to 59 years, 55.7% of whom were female; (3) Results: WrC correlated positively with other adiposity indicators such as waist circumference and Body Mass Index. WrC was the anthropometric indicator most significantly associated with cardiometabolic risk factors. WrC cutoff points identified by the study for determining excess weight were categorized by gender and age group. For males aged 20 to 40 years and >40 years, respectively, the cutoff points for overweight were 17.1 cm and 17.3 cm, and for obesity, 17.9 cm and 17.5 cm. For females aged 20 to 40 years and >40 years, respectively, the cutoff points for overweight were 15.6 cm and 15.4 cm, and for obesity, 16.1 cm and 16 cm (4). Conclusions: Wrist circumference showed a significant correlation with other adiposity indicators and can be used to identify adults with excess weight and predict cardiometabolic risk.

Ecological impact of pharmaceutical pollutants and options of river health improvements - A risk analysis-based approach.

Pharmaceuticals are one of the emerging pollutants (EPs) in river waters across the world. Due to their toxic effects on aquatic organisms, they have drawn the global attention of the scientific community concerned with river ecosystems. This paper reviews the existing occurrence data for various pharmaceutical pollutants (PPs) reported in river waters in some part of the world and their ecological impacts. Using algae, macroinvertebrates (MI), and fish as biotic indicator groups in water to reflect river health conditions, an attempt has been made to assess the ecological risk due to the presence of PPs in the water environment. After ascertaining the predicted no-effect concentration (PNEC) of PPs for selected groups of aquatic organisms, the risk quotient (RQ) is estimated based on their measured environmental concentration (MEC). When MEC > PNEC and RQ > 1 for any of the biotic indicator, ecologically it is 'high risk' condition. The determination of PNEC uses a minimum assessment factor (AF) of 10 due to uncertainty in data over the no observed effect level (NOEL) or lowest observed effect level (LOEL). Accordingly, MEC 10 times higher than PNEC, (RQ = 10) represents a threshold risk concentration (RCT) beyond which adverse effects may start showing observable manifestations. In the present study, a new classification system of 'high risk' conditions for RQ = 1-10 has been proposed, starting from 'moderately high' to 'severely high'. For RQ > 10, the ecological condition of the river is considered 'impaired'. For river health assessment, in the present study, the whole range of physico-chemical characteristics of river water quality has been divided into three groups based on their ease of measurement and frequency of monitoring. Dissolved oxygen related parameters (DORPs), nutrients (NTs), and EPs. PPs represent EPs in this study. A framework for calculating separate indicator group score (IGS) and the overall river health index (RHI) has been developed to predict indicator group condition (IGC) and river health condition (RHC), respectively. Color-coded hexagonal pictorial forms representing IGC and RHC provide a direct visible perception of the existing aquatic environment and a scientific basis for prioritization of corrective measures in terms of treatment technology selection for river health improvements. The analyses indicate that many rivers across the world are under 'high risk' conditions due to PPs having MEC > PNEC and RQ > 1. Up to RCT, (where RQ = 10), the 'high risk' condition varies from 'moderately high' to 'severely high'. In many instances, RQ is found much more higher than 10, indicating that the ecological condition of river may be considered as 'impaired'. Algae is the most frequently affected group of biotic indicators, followed by MI and fish. A review of treatment methods for selection of appropriate technology to reduce the pollution load, especially PPs from the wastewater streams has been summarized. It appears that constructed wetlands (CWs) are at present the most suitable nature-based solutions, particularly for the developing economies of the world, to reduce the concentrations of PPs within limits to minimize the ecological impacts of pharmaceutical compounds on biotic indicators and restore the river health condition. Some suggestive design guidelines for the CWs have also been presented to initiate the process.