Novel EDGE encoding method enhances ability to identify genetic interactions.

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)-rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Infusion reactions to adeno-associated virus (AAV)-based gene therapy: Mechanisms, diagnostics, treatment and review of the literature.

The use of adeno-associated virus (AAV) vectors in gene therapy has demonstrated great potential in treating genetic disorders. However, infusion-associated reactions (IARs) pose a significant challenge to the safety and efficacy of AAV-based gene therapy. This review provides a comprehensive summary of the current understanding of IARs to AAV therapy, including their underlying mechanisms, clinical presentation, and treatment options. Toll-like receptor activation and subsequent production of pro-inflammatory cytokines are associated with IARs, stimulating neutralizing antibodies (Nabs) and T-cell responses that interfere with gene therapy. Risk factors for IARs include high titers of pre-existing Nabs, previous exposure to AAV, and specific comorbidities. Clinical presentation ranges from mild flu-like symptoms to severe anaphylaxis and can occur during or after AAV administration. There are no established guidelines for pre- and postadministration tests for AAV therapies, and routine laboratory requests are not standardized. Treatment options include corticosteroids, plasmapheresis, and supportive medications such as antihistamines and acetaminophen, but there is no consensus on the route of administration, dosage, and duration. This review highlights the inadequacy of current treatment regimens for IARs and the need for further research to improve the safety and efficacy of AAV-based gene therapy.

Dynamic assessment of the COVID-19 vaccine acceptance leveraging social media data.

Vaccination is the most effective way to provide long-lasting immunity against viral infection; thus, rapid assessment of vaccine acceptance is a pressing challenge for health authorities. Prior studies have applied survey techniques to investigate vaccine acceptance, but these may be slow and expensive. This study investigates 29 million vaccine-related tweets from August 8, 2020 to April 19, 2021 and proposes a social media-based approach that derives a vaccine acceptance index (VAI) to quantify Twitter users' opinions on COVID-19 vaccination. This index is calculated based on opinion classifications identified with the aid of natural language processing techniques and provides a quantitative metric to indicate the level of vaccine acceptance across different geographic scales in the U.S. The VAI is easily calculated from the number of positive and negative Tweets posted by a specific users and groups of users, it can be compiled for regions such a counties or states to provide geospatial information, and it can be tracked over time to assess changes in vaccine acceptance as related to trends in the media and politics. At the national level, it showed that the VAI moved from negative to positive in 2020 and maintained steady after January 2021. Through exploratory analysis of state- and county-level data, reliable assessments of VAI against subsequent vaccination rates could be made for counties with at least 30 users. The paper discusses information characteristics that enable consistent estimation of VAI. The findings support the use of social media to understand opinions and to offer a timely and cost-effective way to assess vaccine acceptance.

HaCYC2c regulating the heteromorphous development and functional differentiation of florets by recognizing HaNDUA2 in sunflower.

KEY MESSAGE: The overexpression of HaCYC2c and its regulation on HaNDUA2 through transcriptional recognition are important for regulating the heteromorphous development and functional differentiation of ray and disc florets in sunflower. Flower symmetry is closely related to pollinator recruitment and individual fecundity for higher plants and is the main feature used to identify flower type in angiosperms. In sunflower, HaCYC2c regulates floral organ development and floral symmetry, but the specific detail remains unclear. In this study, sunflower long petal mutant (lpm) with HaCYC2c insertion mutation was used to investigate the regulating role of HaCYC2c in the morphogenesis of florets and the transformation of floral symmetry through phenotype, transcriptome, qRT-PCR, and possible protein-gene interactions analyses. Results showed that HaCYC2c was overexpressed after an insertion into the promoter region. This gene could recognize the cis-acting element GGTCCC in the promoter region of HaNDUA2 that might regulate HaNDUA2 and affect other related genes. As a consequence, the abnormal elongation of disc petals and the degradation of male reproductive system occurred at the early development of floral organ in sunflower. Furthermore, this insertion mutation resulted in floral symmetry transformation, from actinomorphy to zygomorphy, thereby making the tubular disc florets transformed into ray-like disc florets in sunflower lpm. The findings suggested that the overexpression of HaCYC2c and its control of HaNDUA2 through transcriptional recognition might be an important regulating node of the heteromorphous development and functional differentiation for ray and disc florets in sunflower. This node contributes to the understanding of the balance between pollinator recruitment capacity of ray florets and fertility of disc florets for the optimization of reproductive efficiency and enhancement of species competitiveness in sunflower.

miR-205-5p in exosomes divided from chondrogenic mesenchymal stem cells alleviated rheumatoid arthritis via regulating MDM2 in fibroblast-like synoviocytes.

OBJECTIVE: To explore the role and mechanism of chondrogenic bone marrow mesenchymal stem cells (BMSCs)-derived exosomes on Rheumatoid arthritis (RA). METHODS: The chondrogenesis of BMSCs was induced by chondrogenic medium. Exosomes from BMSCs and chondrogenic BMSCs were isolated and characterized by transmission electron microscope (TEM), laser particle size analyzer and western blot. ELISA was used to analyze the expression levels of pro-inflammatory cytokines and matrix metalloproteinases (MMPs). Western bolt was performed to assess MAPK and NF-κB pathways expression. The inflammation score and the pathological damage of RA mice were evaluated. Luciferase reporter assay and RIP were carried out to examine the relationship between microRNA-205-5p (miR-205-5p) and mouse double minute 2 (MDM2). RESULTS: Chondrogenic BMSCs-derived exosomes suppressed pro-inflammatory cytokines, MMPs and MAPK and NF-κB pathways in RA-FLSs. miR-205-5p had a high expression in chondrogenic BMSCs-derived exosomes. Functionally, exosomal miR-205-5p also played the anti-inflammation effects. Besides, MDM2 was a direct target of miR-205-5p. Additionally, chondrogenic BMSCs-secreted exosomal miR-205-5p suppressed the inflammation score, joint destruction, and inflammatory response in collagen-induced arthritis (CIA) mice through MDM2. CONCLUSION: Chondrogenic BMSCs-derived exosomal miR-205-5p suppressed inflammatory response, MAPK and NF-κB pathways through MDM2 in RA, indicating exosomal miR-205-5p might be a potential target for RA treatment.

Lignin degradation by water buffalo.

So far, few animals with the ability of lignin degradation have been reported except termite and longicorn. In this study, it was found that the crude fiber and acid detergent lignin (ADL) of rice straw can be degraded dramatically higher by buffalo than those by cattle. In order to further study this ability of buffalo, the digestion of roughages in buffalo rumen was studied using rumen nylon bag experiment, scanning electron microscopy (SEM), and Van Soest fiber analysis. The SEM results showed that the degradation degree of rice straw was dramatically higher in buffalo than that in cattle. The digestibility of crude fiber was significantly higher in buffalo than that in cattle (P < 0.01). The digestibility of ADL, cellulose, hemicellulose, acid detergent, fiber, and neutral detergent fiber of rice straw in buffalo rumen was significantly higher than that in cattle (P < 0.05). The ADL degradation rate of rice straw in buffalo rumen was significantly higher than that in cattle rumen, indicating that buffalo was capable of utilizing lignin and had superior utilizing capability than cattle. It was observed that various roughages can be dramatically digested by buffalo rumen with the ranking of ADL degradation rate: peanut vine (15.04%) > rice silage > maize silage > rice straw > corn stover > wheat stalk > bract leaf > potato vine (7.22%), verifying that buffalo rumen possessed the ability to digest universal roughages. In conclusion, this study revealed that buffalo was more efficient in ADL degradation compared with cattle.

Effects of Obstructive Sleep Apnea-Hypopnea Syndrome on Serum Carcinoembryonic Antigen Levels in Patients with Type 2 Diabetes Mellitus.

BACKGROUND Type 2 diabetes mellitus (T2DM) is related to the serum carcinoembryonic antigen (CEA) level, which is used as a marker of colorectal cancer. Obstructive sleep apnea-hypopnea syndrome (OSAS) has been recently reported to have cancer-promoting effects. The aim of our study was to observe the effect of OSAS on serum levels of CEA in patients with T2DM. MATERIAL AND METHODS We enrolled 401 T2DM patients in this study. There were 244 patients with OSAS and 157 patients without OSAS. RESULTS The CEA level in T2DM patients with OSAS was higher than that in those without OSAS (p<0.05). The participants with AHI scores ≥30 had higher CEA levels than those with 5≤ AHI scores <30 (p<0.05). The AHI score and ODI score were independently associated with increased risk of high CEA level in T2DM patients (odds ratio [OR]=1.052, 95% confidence interval [CI]: 1.011~1.095) and (OR=1.214, 95% CI: 1.070~1.377). Moreover, among male T2DM patients, the AHI score and ODI score had a linear correlation with the CEA level; this association was also observed in T2DM patients who smoked, had an HbA1c level ≥7%, or had a BMI ≥28 kg/m2 (all p<0.05). CONCLUSIONS The AHI score and ODI score were positively associated with the CEA level in T2DM patients. The relationship was stronger in male T2DM patients and in those who smoked, were obese, or had poor glycemic control. The mechanism may be related to metabolic disorders, and the potential increased risk of colorectal cancer should be investigated in a prospective study.

Characterization of PYL gene family and identification of HaPYL genes response to drought and salt stress in sunflower.

In the context of global climate change, drought and soil salinity are some of the most devastating abiotic stresses affecting agriculture today. PYL proteins are essential components of abscisic acid (ABA) signaling and play critical roles in responding to abiotic stressors, including drought and salt stress. Although PYL genes have been studied in many species, their roles in responding to abiotic stress are still unclear in the sunflower. In this study, 19 HaPYL genes, distributed on 15 of 17 chromosomes, were identified in the sunflower. Fragment duplication is the main cause of the expansion of PYL genes in the sunflower genome. Based on phylogenetic analysis, HaPYL genes were divided into three subfamilies. Members in the same subfamily share similar protein motifs and gene exon-intron structures, except for the second subfamily. Tissue expression patterns suggested that HaPYLs serve different functions when responding to developmental and environmental signals in the sunflower. Exogenous ABA treatment showed that most HaPYLs respond to an increase in the ABA level. Among these HaPYLs, HaPYL2a, HaPYL4d, HaPYL4g, HaPYL8a, HaPYL8b, HaPYL8c, HaPYL9b, and HaPYL9c were up-regulated with PEG6000 treatment and NaCl treatment. This indicates that they may play a role in resisting drought and salt stress in the sunflower by mediating ABA signaling. Our findings provide some clues to further explore the functions of PYL genes in the sunflower, especially with regards to drought and salt stress resistance.

The global clinical studies of long COVID.

People with long COVID are those who still have symptoms, signs, and conditions after the initial phase of infection of SARS-CoV-2. The incidence of long COVID varies among regions-31% in North America, 44% in Europe, and 51% in Asia, which is challenging the healthcare system, but there is limited guidelines for its treatment. With more and more nationwide projects funded by the government such as the RECOVER initiative in the United States and National Institute for Health Research funding in the United Kingdom, an increasing number of ongoing clinical trials are investigating the efficacy of diverse therapies on reversing long COVID. After searching the World Health Organization International Clinical Trial Registry Platform, 587 clinical studies are identified as long COVID studies. Among these, 312 studies (53.2%) are testing potential therapies. Most of the long COVID trials were conducted in the United States (58 trials [18.6%]), followed by India (55 trials [17.6%]), and Spain (20 trials [6.4%]). Interventions in these clinical trials include physical exercise, rehabilitation therapy, behavioral therapy, and pharmacological therapies including herbs, paxlovid, and fluvoxamine. These trials are aiming to deal with these long COVID symptoms and signs including fatigue, decreased pulmonary function, reduced cognitive function, and others. To date, only 11 of these 312 studies have published their results that were not confirmative, unfortunately. Future studies should be designed to address sleep disorders which were seldomly included in registered clinical studies. Moreover, interventions aimed at treating the underlying pathophysiology of long COVID are also necessary but currently lacking.

Large Language Models in Biomedical and Health Informatics: A Review with Bibliometric Analysis.

Large language models (LLMs) have rapidly become important tools in Biomedical and Health Informatics (BHI), potentially enabling new ways to analyze data, treat patients, and conduct research. This study aims to provide a comprehensive overview of LLM applications in BHI, highlighting their transformative potential and addressing the associated ethical and practical challenges. We reviewed 1698 research articles from January 2022 to December 2023, categorizing them by research themes and diagnostic categories. Additionally, we conducted network analysis to map scholarly collaborations and research dynamics. Our findings reveal a substantial increase in the potential applications of LLMs to a variety of BHI tasks, including clinical decision support, patient interaction, and medical document analysis. Notably, LLMs are expected to be instrumental in enhancing the accuracy of diagnostic tools and patient care protocols. The network analysis highlights dense and dynamically evolving collaborations across institutions, underscoring the interdisciplinary nature of LLM research in BHI. A significant trend was the application of LLMs in managing specific disease categories, such as mental health and neurological disorders, demonstrating their potential to influence personalized medicine and public health strategies. LLMs hold promising potential to further transform biomedical research and healthcare delivery. While promising, the ethical implications and challenges of model validation call for rigorous scrutiny to optimize their benefits in clinical settings. This survey serves as a resource for stakeholders in healthcare, including researchers, clinicians, and policymakers, to understand the current state and future potential of LLMs in BHI.

Plasma proteomics and carotid intima-media thickness in the UK biobank cohort.

Background and aims: Ultrasound derived carotid intima-media thickness (cIMT) is valuable for cardiovascular risk stratification. We assessed the relative importance of traditional atherosclerosis risk factors and plasma proteins in predicting cIMT measured nearly a decade later. Method: We examined 6,136 UK Biobank participants with 1,461 proteins profiled using the proximity extension assay applied to their baseline blood draw who subsequently underwent a cIMT measurement. We implemented linear regression, stepwise Akaike Information Criterion-based, and the least absolute shrinkage and selection operator (LASSO) models to identify potential proteomic as well as non-proteomic predictors. We evaluated our model performance using the proportion variance explained (R 2). Result: The mean time from baseline assessment to cIMT measurement was 9.2 years. Age, blood pressure, and anthropometric related variables were the strongest predictors of cIMT with fat-free mass index of the truncal region being the strongest predictor among adiposity measurements. A LASSO model incorporating variables including age, assessment center, genetic risk factors, smoking, blood pressure, trunk fat-free mass index, apolipoprotein B, and Townsend deprivation index combined with 97 proteins achieved the highest R 2 (0.308, 95% C.I. 0.274, 0.341). In contrast, models built with proteins alone or non-proteomic variables alone explained a notably lower R 2 (0.261, 0.228-0.294 and 0.260, 0.226-0.293, respectively). Chromogranin b (CHGB), Cystatin-M/E (CST6), leptin (LEP), and prolargin (PRELP) were the proteins consistently selected across all models. Conclusion: Plasma proteins add to the clinical and genetic risk factors in predicting a cIMT measurement. Our findings implicate blood pressure and extracellular matrix-related proteins in cIMT pathophysiology.

PAGER: A novel genotype encoding strategy for modeling deviations from additivity in complex trait association studies.

BACKGROUND: The additive model of inheritance assumes that heterozygotes (Aa) are exactly intermediate in respect to homozygotes (AA and aa). While this model is commonly used in single-locus genetic association studies, significant deviations from additivity are well-documented and contribute to phenotypic variance across many traits and systems. This assumption can introduce type I and type II errors by overestimating or underestimating the effects of variants that deviate from additivity. Alternative genotype encoding strategies have been explored to account for different inheritance patterns, but they often incur significant computational or methodological costs. To address these challenges, we introduce PAGER (Phenotype Adjusted Genotype Encoding and Ranking), an efficient pre-processing method that encodes each genetic variant based on normalized mean phenotypic differences between diallelic genotype classes (AA, Aa, and aa). This approach more accurately reflects each variant's true inheritance model, improving model precision while minimizing the costs associated with alternative encoding strategies. RESULTS: Through extensive benchmarking on SNPs simulated with both binary and continuous phenotypes, we demonstrate that PAGER accurately represents various inheritance patterns (including additive, dominant, recessive, and heterosis), achieves levels of statistical power that meet or exceed other encoding strategies, and attains computation speeds up to 55 times faster than a similar method, EDGE. We also apply PAGER to publicly available real-world data and identify a novel, relevant putative QTL associated with body mass index in rats (Rattus norvegicus) that is not detected with the additive model. CONCLUSIONS: Overall, we show that PAGER is an efficient genotype encoding approach that can uncover sources of missing heritability and reveal novel insights in the study of complex traits while incurring minimal costs.

Per- and poly-fluoroalkyl substances (PFAS) accelerate biological aging mediated by increased C-reactive protein.

Unhealthy biological aging is related to higher incidence of varied age-related diseases, even higher all-cause mortality. Previous small sample size study suggested that Per- and poly-fluoroalkyl substances (PFAS) was associated with biological aging, but the evidence of exposure-response relationships, potential effect modifiers, and potential mediators were not investigated. Therefore, we conducted a cross-sectional analysis of national study including 14, 865 adults in the US from 8 survey cycles of NHANES from 2003 to 2018, to investigate the associations of PFAS compounds in body serum, including perfluorooctanoic acid (PFOA), perfluorooctane sulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorohexane sulfonic acid (PFHxS), with biological aging. Generalized linear models showed that higher human exposure to PFAS was associated with accelerated biological aging. Importantly, human exposure to PFOA, PFOS, PFNA, and PFHxS with detected level (above 0.10 ng/mL) was associated with an average of 3.3 year (95 %CI: 2.7, 3.9, P < 0.001), 14.9 year (95 %CI: 7.2, 22.7, P < 0.001), 10.9 years (95 %CI: 3.9, 17.7, P < 0.001), and 8.8 years (95 %CI: 4.8, 12.9, P < 0.001) of biological aging acceleration. Cubic spline models indicated exposure-response relationships where there was no safe threshold of PFAS level regarding harms to human healthy aging. The weighted sum regression model found the significant associations of PFAS compound mixture with biological aging acceleration, and PFOA was the dominant contributor among 4 PFAS compounds. Mediation analysis suggested that C-reactive protein, one of the inflammation biomarkers, might play as mediator in PFAS-induced accelerated biological aging, but not Triglyceride-glucose index. In summary, our study suggests that the effects of PFAS on biological aging acceleration should be of concern and more action plans to address their negative impact on human health should be launched.

Plasma proteomic signatures for type 2 diabetes mellitus and related traits in the UK Biobank cohort.

Aims/hypothesis: The plasma proteome holds promise as a diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of plasma proteins to predict type 2 diabetes mellitus (T2DM) and related traits. Methods: Clinical, genetic, and high-throughput proteomic data from three subcohorts of UK Biobank participants were analyzed for association with dual-energy x-ray absorptiometry (DXA) derived truncal fat (in the adiposity subcohort), estimated maximum oxygen consumption (VO2max) (in the fitness subcohort), and incident T2DM (in the T2DM subcohort). We used least absolute shrinkage and selection operator (LASSO) regression to assess the relative ability of non-proteomic and proteomic variables to associate with each trait by comparing variance explained (R2) and area under the curve (AUC) statistics between data types. Stability selection with randomized LASSO regression identified the most robustly associated proteins for each trait. The benefit of proteomic signatures (PSs) over QDiabetes, a T2DM clinical risk score, was evaluated through the derivation of delta (Δ) AUC values. We also assessed the incremental gain in model performance metrics using proteomic datasets with varying numbers of proteins. A series of two-sample Mendelian randomization (MR) analyses were conducted to identify potentially causal proteins for adiposity, fitness, and T2DM. Results: Across all three subcohorts, the mean age was 56.7 years and 54.9% were female. In the T2DM subcohort, 5.8% developed incident T2DM over a median follow-up of 7.6 years. LASSO-derived PSs increased the R2 of truncal fat and VO2max over clinical and genetic factors by 0.074 and 0.057, respectively. We observed a similar improvement in T2DM prediction over the QDiabetes score [Δ AUC: 0.016 (95% CI 0.008, 0.024)] when using a robust PS derived strictly from the T2DM outcome versus a model further augmented with non-overlapping proteins associated with adiposity and fitness. A small number of proteins (29 for truncal adiposity, 18 for VO2max, and 26 for T2DM) identified by stability selection algorithms offered most of the improvement in prediction of each outcome. Filtered and clustered versions of the full proteomic dataset supplied by the UK Biobank (ranging between 600-1,500 proteins) performed comparably to the full dataset for T2DM prediction. Using MR, we identified 4 proteins as potentially causal for adiposity, 1 as potentially causal for fitness, and 4 as potentially causal for T2DM. Conclusions/Interpretation: Plasma PSs modestly improve the prediction of incident T2DM over that possible with clinical and genetic factors. Further studies are warranted to better elucidate the clinical utility of these signatures in predicting the risk of T2DM over the standard practice of using the QDiabetes score. Candidate causally associated proteins identified through MR deserve further study as potential novel therapeutic targets for T2DM.

A plasma proteomic signature for atherosclerotic cardiovascular disease risk prediction in the UK Biobank cohort.

Background: While risk stratification for atherosclerotic cardiovascular disease (ASCVD) is essential for primary prevention, current clinical risk algorithms demonstrate variability and leave room for further improvement. The plasma proteome holds promise as a future diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of plasma proteins to predict ASCVD. Method: Clinical, genetic, and high-throughput plasma proteomic data were analyzed for association with ASCVD in a cohort of 41,650 UK Biobank participants. Selected features for analysis included clinical variables such as a UK-based cardiovascular clinical risk score (QRISK3) and lipid levels, 36 polygenic risk scores (PRSs), and Olink protein expression data of 2,920 proteins. We used least absolute shrinkage and selection operator (LASSO) regression to select features and compared area under the curve (AUC) statistics between data types. Randomized LASSO regression with a stability selection algorithm identified a smaller set of more robustly associated proteins. The benefit of plasma proteins over standard clinical variables, the QRISK3 score, and PRSs was evaluated through the derivation of Δ AUC values. We also assessed the incremental gain in model performance using proteomic datasets with varying numbers of proteins. To identify potential causal proteins for ASCVD, we conducted a two-sample Mendelian randomization (MR) analysis. Result: The mean age of our cohort was 56.0 years, 60.3% were female, and 9.8% developed incident ASCVD over a median follow-up of 6.9 years. A protein-only LASSO model selected 294 proteins and returned an AUC of 0.723 (95% CI 0.708-0.737). A clinical variable and PRS-only LASSO model selected 4 clinical variables and 20 PRSs and achieved an AUC of 0.726 (95% CI 0.712-0.741). The addition of the full proteomic dataset to clinical variables and PRSs resulted in a Δ AUC of 0.010 (95% CI 0.003-0.018). Fifteen proteins selected by a stability selection algorithm offered improvement in ASCVD prediction over the QRISK3 risk score [Δ AUC: 0.013 (95% CI 0.005-0.021)]. Filtered and clustered versions of the full proteomic dataset (consisting of 600-1,500 proteins) performed comparably to the full dataset for ASCVD prediction. Using MR, we identified 11 proteins as potentially causal for ASCVD. Conclusion: A plasma proteomic signature performs well for incident ASCVD prediction but only modestly improves prediction over clinical and genetic factors. Further studies are warranted to better elucidate the clinical utility of this signature in predicting the risk of ASCVD over the standard practice of using the QRISK3 score.

Insights into Metabolic Reprogramming in Tumor Evolution and Therapy.

Background: Cancer remains a global health challenge, characterized not just by uncontrolled cell proliferation but also by the complex metabolic reprogramming that underlies its development and progression. Objectives: This review delves into the intricate relationship between cancer and its metabolic alterations, drawing an innovative comparison with the cosmological concepts of dark matter and dark energy to highlight the pivotal yet often overlooked role of metabolic reprogramming in tumor evolution. Methods: It scrutinizes the Warburg effect and other metabolic adaptations, such as shifts in lipid synthesis, amino acid turnover, and mitochondrial function, driven by mutations in key regulatory genes. Results: This review emphasizes the significance of targeting these metabolic pathways for therapeutic intervention, outlining the potential to disrupt cancer's energy supply and signaling mechanisms. It calls for an interdisciplinary research approach to fully understand and exploit the intricacies of cancer metabolism, pointing toward metabolic reprogramming as a promising frontier for developing more effective cancer treatments. Conclusion: By equating cancer's metabolic complexity with the enigmatic nature of dark matter and energy, this review underscores the critical need for innovative strategies in oncology, highlighting the importance of unveiling and targeting the "dark energy" within cancer cells to revolutionize future therapy and research.

The mediting role of psychological resilience on the negative effect of pain in patients with rheumatoid arthritis: A cross-sectional study.

The objective of this study was to investigate the direct effects of pain-induced depression and anxiety, as well as the mediating role of psychological resilience, on the psychological distress associated with rheumatoid arthritis. The method involved a sample of 196 patients with rheumatoid arthritis and applied the Hospital Anxiety and Depression Scale, Connor-Davidson Resilience Scale, and visual analog scale for pain. Bivariate and path analyses were performed, and a multiple mediational model was utilized. Results showed that all correlations among study variables were significant (p < 0.01). A partial mediation effect of psychological resilience was observed, and direct effects among the variables (pain, psychological resilience, anxiety, and depression) were statistically significant, including the direct effect of psychological resilience on depression and anxiety. The indirect effects of pain through psychological resilience on depression and anxiety were also significant. Thus, the results suggest that psychological resilience partially mediates the effects of pain-induced anxiety and depression in patients with rheumatoid arthritis.

Fucoidan alleviates the hepatorenal syndrome through inhibition organic solute transporter α/ß to reduce bile acids reabsorption.

The high levels of bile acids are a critical factor in hepatorenal syndrome. Organic solute transporter α/ß (Ostα/ß) participate in bile acids reabsorption in the kidney. Fucoidan has the great potential in protecting against liver and kidney injury. However, whether Ostα/ß increase bile acids reabsorption in bile duct ligature (BDL)-induced hepatorenal syndrome and the blockade of fucoidan are still not clear. Male mice that received BDL were given to fucoidan (at 12.5, 25 and 50 â€‹mg/kg) through intraperitoneal injection once daily for three weeks. The serum, liver and kidney samples of these experimental mice were collected to carry out biochemical, pathological and Western blot analysis. In this study, fucoidan significantly lowered serum activities of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), decreased serum levels of uric acid, creatinine and uric nitrogen, restored the deregulation of the renal urate transporter 1 (URAT1), organic anion transporter 1 (OAT1), and organic cation/carnitine transporter 1/2 (OCTN1/2), consistence with alleviation BDL-induced liver and kidney dysfunction, inflammation and fibrosis in mice. Furthermore, fucoidan significantly hampered Ostα/ß and reduced bile acids reabsorption in BDL-induced mice, protected against AML12 and HK-2 â€‹cells injury in vitro. These results demonstrate that fucoidan alleviates BDL-induced hepatorenal syndrome through inhibition Ostα/ß to reduce bile acids reabsorption in mice. Therefore, suppression of Ostα/ß by fucoidan may be a novel strategy for attenuating hepatorenal syndrome.

Isolation and identification of ligninolytic bacterium (Bacillus cereus) from buffalo (Bubalus bubalis) rumen and its effects on the fermentation quality, nutrient composition, and bacterial community of rape silage.

This study aimed to isolate and identify a ligninolytic bacterium from the rumen of buffalo (Bubalus bubalis) and investigate its effects as a silage additive for whole-plant rape. Three lignin-degradation strains were isolated from the buffalo rumen, with AH7-7 being chosen for further experiments. Strain AH7-7, with acid tolerance and a 51.4% survival rate at pH 4, was identified as Bacillus cereus. It exhibited a lignin-degradation rate of 20.5% after being inoculated in a lignin-degrading medium for 8 days. We divided the rape into four groups according to the various additive compositions to examine the fermentation quality, nutritional value, and bacterial community after ensiling: Bc group (inoculated with B. cereus AH7-7 3.0 × 106 CFU g FW-1), Blac group (inoculated with B. cereus AH7-7 1.0 × 106 CFU g FW-1, L. plantarum 1.0 × 106 CFU g FW-1, and L. buchneri 1.0 × 106 CFU g FW-1), Lac group (inoculated with L. plantarum 1.5 × 106 CFU g FW-1 and L. buchneri 1.5 × 106 CFU g FW-1), and Ctrl group (no additives). After 60 days of fermentation, the application of B. cereus AH7-7 was potent in modulating the fermentation quality of silage, especially when combined with L. plantarum and L. buchneri, as indicated by lower dry matter loss and higher contents of crude protein, water-soluble carbohydrate, and lactic acid. Furthermore, treatments with the B. cereus AH7-7 additive decreased the contents of acid detergent lignin, cellulose, and hemicellulose. The B. cereus AH7-7 additive treatments reduced the bacterial diversity and optimized the bacterial community compositions of silage, with an increase in the relative abundance of beneficial Lactobacillus and a decrease in the relative abundance of undesirable Pantoea and Erwinia. Functional prediction revealed that inoculation with B. cereus AH7-7 could increase the cofactors and vitamins metabolism, amino acid metabolism, translation, replication and repair, and nucleotide metabolism, while decreasing the carbohydrate metabolism, membrane transport, and energy metabolism. In brief, B. cereus AH7-7 improved the microbial community, fermentation activity, and ultimately the quality of silage. The ensiling with B. cereus AH7-7, L. plantarum, and L. buchneri combination is an effective and practical strategy to improve the fermentation and nutrition preservation of rape silage.

Comprehensive analysis of nanoplastic effects on growth phenotype, nanoplastic accumulation, oxidative stress response, gene expression, and metabolite accumulation in multiple strawberry cultivars.

Nanoplastics (NPs) have emerged as a novel environmental threat due to their potential impacts on both animals and plants. Currently, research on the ecotoxicity of NPs has mainly focused on marine aquatic organisms and freshwater algae, with very limited investigations conducted on horticultural plants. This study examined the effects of varying concentrations (0, 1, 10, 50 mg·L-1) of polystyrene NPs (PS-NPs) on strawberry growth. The findings revealed that low concentrations of PS-NPs stimulated strawberry growth, whereas high concentrations impeded it. Notably, diverse strawberry cultivars displayed considerable differences in their sensitivity to PS-NP exposure. Laser scanning confocal microscopy confirmed the absorption of PS-NPs by strawberry roots, with variations in PS-NP accumulation observed across different cultivars. Comparative transcriptomics analysis suggested that the differential expression of genes responsible for calcium ion transport played a significant role in the observed intervarietal differences in PS-NP accumulation among strawberry cultivars. Furthermore, distinct variations in endogenous oxidative responses were observed in different strawberry cultivars under PS-NP treatment. Further analysis indicated that the down-regulation of peroxidase (POD) gene expression and terpenoid compounds accumulation were responsible for heightened endogenous oxidative stress observed in certain strawberry cultivars under PS-NP treatment. Transcriptomic and metabolomic analyses were performed on six strawberry cultivars to investigate their response to PS-NPs in terms of endogenous gene expression and metabolite accumulation. The results identified one commonly up-regulated gene (wall-associated receptor kinase-like) and sixteen commonly down-regulated genes associated with lipid metabolism and carbohydrate metabolism. In addition, a significant reduction in fatty acid metabolite accumulation was observed in the six strawberry cultivars under PS-NP treatment. These findings have significant implications for understanding the effects of NPs on strawberry growth, metabolism, and antioxidant responses, as well as identifying marker genes for monitoring and evaluating the impact of NP pollution on strawberry.