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Atrophy of cerebellum Crus I indicates poor outcome of cochlear implantation in the elderly

Expanded non-invasive prenatal testing offers better detection of fetal copy number variations but not chromosomal aneuploidies

Purpose To evaluate the clinical performance of expanded non-invasive prenatal testing (NIPT-plus) and compare its effectiveness in screening for chromosomal aneuploidies with that of NIPT. Methods Screening results, confirmatory invasive testing results, and follow-up data from pregnant women who underwent either NIPT (6792 cases) or NIPT-Plus (5237 cases) testing at Luohe Central Hospital, China, from January 2019 to June 2023 were collected. The positive predictive value (PPV), sensitivity, specificity, and other indicators for different types of chromosomal abnormalities in NIPT/NIPT-plus screening were calculated. The willingness of pregnant women with various types of abnormalities to undergo confirmatory invasive testing and the proportion of pregnancy terminations were investigated. Results The average number of unique reads in NIPT-plus samples was 5.26 times greater than that in NIPT samples. There was no significant difference in the PPV or positive rate between NIPT-plus and NIPT for screening chromosomal aneuploidies. Compared with the low-risk group, the high-risk group had a greater PPV; however, in the NIPT-plus group, there was no significant disparity in the PPV between the low-risk and high-risk groups. Compared with rare autosomal aneuploidies (RAAs), pregnant women had a higher rate of confirmatory invasive testing for common trisomies, sex chromosomal abnormalities (SCAs), and copy number variations (CNVs). However, the rate of pregnancy termination for common trisomies, RAAs, and CNVs was higher than that for SCAs. Conclusion By enhancing sequencing data, NIPT-plus can effectively screen for CNVs as well as chromosomal aneuploidies. However, NIPT-plus does not have an advantage over standard NIPT in screening for chromosomal aneuploidies.

Machine learning to identify environmental drivers of phytoplankton blooms in the Southern Baltic Sea

Abstract Phytoplankton blooms exhibit varying patterns in timing and number of peaks within ecosystems. These differences in blooming patterns are partly explained by phytoplankton:nutrient interactions and external factors such as temperature, salinity and light availability. Understanding these interactions and drivers is essential for effective bloom management and modelling as driving factors potentially differ or are shared across ecosystems on regional scales. Here, we used a 22-year data set (19 years training and 3 years validation data) containing chlorophyll, nutrients (dissolved and total), and external drivers (temperature, salinity, light) of the southern Baltic Sea coast, a European brackish shelf sea, which constituted six different phytoplankton blooming patterns. We employed generalized additive mixed models to characterize similar blooming patterns and trained an artificial neural network within the Universal Differential Equation framework to learn a differential equation representation of these pattern. Applying Sparse Identification of Nonlinear Dynamics uncovered algebraic relationships in phytoplankton:nutrient:external driver interactions. Nutrients availability was driving factor for blooms in enclosed coastal waters; nutrients and temperature in more open regions. We found evidence of hydrodynamical export of phytoplankton, natural mortality or external grazing not explicitly measured in the data. This data-driven workflow allows new insight into driver-differences in region specific blooming dynamics.

Probiotics interventions modulating gut microbiota composition in individuals with intestinal constipation: Protocol of a systemic review and meta-analysis of randomized controlled trials

Introduction Intestinal constipation is a substantive global health concern, significantly impairing patient quality of life. An emerging view is that the gut microbiota plays a critical role in intestinal function, and probiotics could offer therapeutic benefits. This study aims to consolidate evidence from randomized controlled trials (RCTs) that assess the effectiveness of probiotics in modulating microbiota and ameliorating symptoms of constipation. Methods We will execute a systematic evidence search across Medline (via PubMed), Embase, Cochrane CENTRAL, Web of Science, Scopus, and CINAHL, employing explicit search terms and further reference exploration. Two independent reviewers will ensure study selection and data integrity while assessing methodological quality via the Cochrane Collaboration’s Risk of Bias-2 tool. Our primary goal is to outline changes in microbiota composition, with secondary outcomes addressing symptom relief and stool characteristics. Meta-analyses will adopt a random-effects model to quantify the effects of interventions, supplemented by subgroup analyses and publication bias assessments to fortify the rigor of our findings. Discussion This study endeavors to provide a rigorous, synthesized overview of the probiotics interventions evidence for modulating gut microbiota in individuals with intestinal constipation. The insights derived could inform clinical guidelines, nurture the creation of novel constipation management strategies, and direct future research in this field. Ethics and dissemination As this study aggregates and analyzes existing data without direct human subject involvement, no ethical approval is required. We will disseminate the study’s findings through scientific forums and seek publication in well-regarded, peer-reviewed journals. Trial registration OSF registration number: 10.17605/OSF.IO/MEAHT.

Deformation behavior of additive manufactured 316 L stainless steel using in situ neutron diffraction

Insights into the representativeness of biodiversity assessment in large reservoir through eDNA metabarcoding

Monitoring biodiversity on a large scale, such as in hydropower reservoirs, poses scientific challenges. Conventional methods such as passive fishing gear are prone to various biases, while the utilization of environmental DNA (eDNA) metabarcoding has been restricted. Most eDNA studies have primarily focused on replicating results from traditional methods, which themselves have limitations regarding representativeness and bias. In our study, we employed eDNA metabarcoding with three markers (12SrRNA, COI, and 16SrRNA) to evaluate the biodiversity of an 800 km 2 reservoir. We utilized hydrodynamic modeling to determine water flow velocity and the water renewal ratio throughout the study area. Additionally, we conducted statistical comparisons—rarefaction curves and multivariate methods—among samples as an alternative approach to assess biodiversity representation. The eDNA identified taxa previously documented in the reservoir by traditional monitoring methods, as well as revealed 29 –nine fishes and 20 non-fish—previously unreported species. These results highlight the robustness of eDNA as a biodiversity monitoring technique. Our findings also indicated that by randomly sampling 30% of the original number of samples, we could effectively capture the same biodiversity. This approach enabled us to comprehend the reservoir’s biodiversity profile and propose a straightforward, cost-effective monitoring protocol for the future based on eDNA.

Thermal buffering-controlled temperature variation between Mg–Al-rich rocks and migmatites

Effects of Cinnamomum zeylanicum (Ceylon cinnamon) extract on lipid profile, glucose levels and its safety in adults: A randomized, double-blind, controlled trial

Background Cinnamon has been studied as a possible way to control blood glucose and serum cholesterol levels. However, there are no well-conducted randomized controlled trials that can accurately measure the lipid and glucose-lowering effects of Cinnamomum zeylanicum (C. zeylanicum) extract. This study primarily aimed to evaluate the effect of a standardized C. zeylanicum extract on serum low-density lipoprotein cholesterol (LDL-C) levels and secondarily on other lipid parameters (high-density lipoprotein cholesterol (HDL-C), total cholesterol and triglycerides), glucose levels, anthropometric measures, blood pressure, and safety outcomes in individuals with an LDL level between 100-190mg/dL. Materials and methods This was a randomized, double-blinded, placebo-controlled clinical trial. Participants were allocated to either C. zeylanicum extract or placebo group (1:1 allocation ratio). They were advised to take two capsules per day (1000 mg/day, a dose based on prior clinical studies suggesting potential efficacy and safety). Reduction in LDL-C at 12 weeks (from the baseline value) was compared between the two groups using ANCOVA. A complete-case analysis was adhered to in analyzing the outcome data. Results The mean age (SD) of the 150 participants was 50.4 (10.52) years, and 66% were females. Among the 127 participants assessed at 12 weeks, those in the C. zeylanicum extract arm had a lower LDL-C value than the placebo arm but the difference was not significant (the baseline adjusted mean difference was 6.05mg/dL; 95% CI: -2.43 to 14.52; p = 0.161). However, participants in the C. zeylanicum extract group showed significantly greater reductions in fasting blood sugar (FBS) levels (the baseline adjusted mean difference was 8.59mg/dL; 95% CI: 0.59 to 16.59; p = 0.036). There was a significant interaction effect between the supplement and participants’ glycemic status, with individuals with type 2 diabetes mellitus (T2DM) who received C. zeylanicum extract experiencing a notable reduction in FBS levels (standardized coefficient: -63, 95% CI: -102 to -25; p = 0.002). Conclusions C. zeylanicum extract did not have significantly reduce LDL-C but demonstrated a significant FBS-lowering effect, particularly in individuals with T2DM, with a favorable safety profile. Trials registration The trial was registered with the Sri Lanka Clinical Trials Registry: SLCTR/2021/011.

Insect frass fertilizer as soil amendment for improved forage and soil health in circular systems

Nebulization of 2% lidocaine has no detectable impact on the healthy equine respiratory microbiota

Glucocorticosteroids remain the most common pharmaceutical approach for the treatment of equine asthma but can be associated with significant side effects, including respiratory microbiome alterations. The goal of the study was to assess the impact of 2% lidocaine nebulization, a projected alternative treatment of equine asthma, on the healthy equine respiratory microbiota. A prospective, randomized, controlled, blinded, 2-way crossover study was performed, to assess the effect of 1 mg/kg 2% lidocaine (7 treatments over 4 days) on the equine respiratory microbiota compared to control horses (saline and no treatment). Clinical assessments and respiratory samples, including nasal wash, endoscopic tracheal aspirate and bronchoalveolar lavage fluid, were obtained at each sample collection timepoint. The profile of the respiratory bacterial microbiota was evaluated using 16S amplicon sequencing, and clinical data compared using related samples analyses, based on data normality. The treatment did not affect the clinical data or alter the tracheal and nasal microbiota in healthy horses. However, time explained 12.6% of microbiota variation among samples. A significant difference in bacterial composition was observed between nasal and tracheal samples, showing the greatest relative abundance of Actinobacteria and Firmicutes, respectively. Bacterial DNA from bronchoalveolar lavage fluid did not amplify with generic primers targeting the V4 variable region of the prokaryotic small subunit ribosomal RNA gene, despite attempting multiple DNA extraction methods and PCR protocols, and after excluding PCR inhibition. This observation indicates that bronchoalveolar lavage fluid of healthy horses has a low bacterial load.

siRNA-mediated inhibition of hTERT enhances the effects of curcumin in promoting cell death in precursor-B acute lymphoblastic leukemia cells: an in silico and in vitro study

Measurement properties of instruments to assess insight in psychosis: A systematic review protocol

Introduction Insight in psychosis, defined as a patient’s awareness and judgment of their mental illness, is a complex and evolving concept. Historically, the absence of insight was considered a defining characteristic of psychosis, but recent decades have seen the development of structured tools for its assessment. This systematic review aims to critically appraise the measurement properties of instruments used to assess insight in individuals with schizophrenia spectrum, bridging the gap between theoretical conceptualization and clinical practice. Methods This protocol is reported following the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) guidelines. Eligible studies will evaluate instruments measuring insight in psychosis, including self-report, observer ratings, behavioral measurements, and semi-structured interviews. The psychometric properties assessed will encompass reliability, validity, responsiveness, interpretability, and clinical utility. We will include primary quantitative studies published in peer-reviewed journals and available in English. Results Two reviewers will conduct data extraction and quality assessment independently, with discrepancies resolved through consensus or a third reviewer. The COSMIN Risk of Bias checklist and the GRADE approach will be used to evaluate each measure’s methodological quality and overall strength of evidence. Discussion This systematic review will synthesize current evidence on insight measurement in psychosis, providing a comprehensive overview of the strengths and limitations of existing instruments. The findings will inform future research and clinical practice, facilitating the selection of the most appropriate tools for assessing insight and ultimately contributing to improved care for individuals with psychosis. The findings will provide clinicians and researchers with robust tools for assessing insight, ultimately enhancing treatment outcomes for individuals with psychosis.

Development of a checklist for cognitive assessment requirements (CARE) based on a Delphi consensus study

Low agreement and frequent invalid controls in two SARS-CoV-2 T-cell assays in people with compromised immune function

T-cell response plays an important role in SARS-CoV-2 immunogenicity. For people living with HIV (PWH) and solid organ transplant (SOT) recipients there is limited evidence on the reliability of commercially available T-cell tests. We assessed 173 blood samples from 81 participants (62 samples from 35 PWH; 111 samples from 46 SOT recipients [lung and kidney]) with two commercial SARS-CoV-2 Interferon-γ (IFN-γ) release assays (IGRA; SARS-CoV-2 IGRA by Euroimmun, and IGRA SARS-CoV-2 by Roche). The reliability between the tests was judged as low (Cohen’s kappa [κ] = 0.20; overall percent agreement [OPA] = 66%). A high proportion of tests were invalid (22% Euroimmun; 8% Roche). When excluding these invalid tests, the agreement was higher (κ  =  0.43; OPA = 90%). The low reliability between the two T-cell tests indicates that results should be interpreted with caution in SOT recipients and PWH and that SARS-CoV-2 T-cell tests need to be optimized and further validated for use in vulnerable patient populations.

The association between the dietary inflammatory index and multiple myeloma: a case–control study

Identification of hypertension gene expression biomarkers based on the DeepGCFS algorithm

Hypertension is a critical risk factor and cause of mortality in cardiovascular diseases, and it remains a global public health issue. Therefore, understanding its mechanisms is essential for treating and preventing hypertension. Gene expression data is an important source for obtaining hypertension biomarkers. However, this data has a small sample size and high feature dimensionality, posing challenges to biomarker identification. We propose a novel deep graph clustering feature selection (DeepGCFS) algorithm to identify hypertension gene biomarkers with more biological significance. This algorithm utilizes a graph network to represent the interaction information between genes, builds a GNN model, designs a loss function based on link prediction and self-supervised learning ideas for training, and allows each gene node to obtain a feature vector representing global information. The algorithm then uses hybrid clustering methods for gene module detection. Finally, it combines integrated feature selection methods to determine the gene biomarkers. The experiment revealed that all the ten identified hypertension biomarkers were significantly differentiated, and it was found that the classification performance of AUC can reach 97.50%, which is better than other literature methods. Six genes (PTGS2, TBXA2R, ZNF101, KCNJ2, MSRA, and CMTM5) have been reported to be associated with hypertension. By using GSE113439 as the validation dataset, the AUC value of classification performance was to be 95.45%, and seven of the genes (LYSMD3, TBXA2R, KLC3, GPR171, PTGS2, MSRA, and CMTM5) were to be significantly different. In addition, this algorithm’s performance of gene feature vector clustering was better than other comparative methods. Therefore, the proposed algorithm has significant advantages in selecting potential hypertension biomarkers.

Disrupted HIV care during COVID-19 pandemic associated with increased disabilities among people living with HIV in Belize

The impact of a commercial lower extremity exoskeleton on metabolic load, perceived exertion, and physiological response to a challenging military relevant task: A randomized cross-over design pilot study

Purpose To assess physiological metrics during the use of a commercially available bilateral active ankle exoskeleton during a challenging military-relevant task and if use of the exoskeleton during this task influences: metabolic load, physiological measures or rate of perceived exertion. Methods Nine healthy volunteers (5M, 4F) completed this randomized cross-over design trial, with a baseline visit and two randomized test sessions (with/without the exoskeleton). Variables included impact on time to exhaustion during walking on a treadmill at varying speeds and gradients (0–15%) at 26.7°C, 50% humidity with a loaded rucksack (30% body weight). The primary outcome measure was change in metabolic cost with/without the exoskeleton (O2 consumption, metabolic equivalents); secondary outcomes were change in heart rate and perceived exertion between conditions. Results Participants averaged 22.4 ± 4.5 years old, 173.7 ± 7.4 cm tall, weighed 80.9 ± 13.9 kg, and VO2max of 43.8 ± 10.6 mL/kg/min. Total kcals did not differ between conditions (with/without exoskeleton; t = 0.98; p = 0.357). Kcals/min were significantly lower (1.06 kcals/min) with the exoskeleton (t = 3.94; p = 0.004). Average oxygen consumption (VO2) was significantly lower (2.36 mL/kg/min) with the exoskeleton (t = 2.81; p = 0.023), and peak VO2 was 3.33 mL/kg/min lower with the exoskeleton (t = 2.37; p = 0.045). Peak and Average METS were also lower with the exoskeleton by 0.98 (t = 2.61; p = 0.031) and 1.23 (t = 2.39; p = 0.044) respectively. Conclusions Results suggest a powered ankle exoskeleton may decrease energy consumption during military relevant tasks when conducted in a laboratory environment. There may also be physiological benefits such as reduced core temperate and heart rate. Replication of this work in the field environment is warranted.

Modeling of historical and future changes in temperature and precipitation in the Panj River Basin in Central Asia under the CMIP5 RCP and CMIP6 SSP scenarios

Influences of roughness and filling degree on the shear strength and damage evolution characteristics of cement-filled joints

The shear resistance of filling joints is an important factor affecting the stability of rock joints. Pressure-shear tests of cement-filled joints were carried out. Combined with the acoustic emission (AE) technique, the effects of normal stress, roughness and filling degree on the shear strength, damage morphology and damage evolution of cement-filled joints were investigated. The results show that with the increase of roughness, the failure mode is more complicated. When the roughness is low, only the bonding surface of the interface between the filler and the joint surface is damaged, and the filling degree has a weak effect on the failure mode. When the roughness is high, with the increase of normal stress and filling degree, the failure of the filled joint is from the joint failure of the bonding surface and the filling material to the serious failure of the bonding surface, the filling material and the joint. The peak shear strength of filled joints is positively correlated with roughness and negatively correlated with filling degree. With the increase of filling degree, the influence of roughness will be weakened by filling material, and the normal stress will amplify the effect of roughness. The evolution characteristics of AE show that the damage degree of filled joints is positively correlated with normal stress and roughness, and negatively correlated with filling degree. The joint surface is damaged locally at first, then failure near the main raised body of the joint, and finally spreads to the whole joint surface.