Effects of genetically proxied lipid-lowering drugs on acute myocardial infarction: a drug-target mendelian randomization study.

OBJECTIVE: High low-density-lipoprotein (LDL) cholesterol has been associated with an increased risk of coronary artery diseases (CAD) including acute myocardial infarction (AMI). However, whether lipids lowering drug treatment is causally associated with decreased risk of AMI remains largely unknown. We used Mendelian randomization (MR) to evaluate the influence of genetic variation affecting the function of lipid-lowering drug targets on AMI. METHODS: Single-nucleotide polymorphisms (SNPs) associated with lipids as instruments were extracted from the Global Lipids Genetics Consortium (GLGC). The genome-wide association study (GWAS) data for AMI were obtained from UK Biobank. Two sample MR analysis was used to study the associations between high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG) with AMI (n = 3,927). Genetic variants associated with LDL cholesterol at or near drug target gene were used to mimic drug effects on the AMI events in drug target MR. RESULTS: Genetically predicted higher LDL-C (per one SD increase in LDL-C of 38.67 mg/dL, OR 1.006, 95% CI 1.004-1.007) and TG (per one SD increase in TG of 90.72 mg/dL, 1.004, 1.002-1.006) was associated with increased risk of AMI, but decreased risk for higher HDL-C (per one SD increase in HDL-C of 15.51 mg/dL, 0.997, 0.995-0.999) in univariable MR. Association remained significant for LDL-C, but attenuated toward the null for HDL-C and TG in multivariable MR. Genetically proxied lower LDL-C with genetic variants at or near the PCSK9 region (drug target of evolocumab) and NPC1L1 (drug target of ezetimibe) were associated with decreased risk of AMI (0.997, 0.994-0.999 and 0.986, 0.975-0.998, respectively), whereas genetic variants at HMGCR region (drug target of statin) showed marginal association with AMI (0.995, 0.990-1.000). After excluding drug target-related SNPs, LDL-C related SNPs outside the drug target region remained a causal effect on AMI (0.994, 0.993-0.996). CONCLUSIONS: The findings suggest that genetically predicted LDL-C may play a predominant role in the development of AMI. The drug MR results imply that ezetimibe and evolocumab may decrease the risk of AMI due to their LDL-C lowering effect, and there are other non-drug related lipid lowering pathways that may be causally linked to AMI.

Genetically determined blood pressure, antihypertensive drug classes, and frailty: A Mendelian randomization study.

Observational studies have suggested that the use of antihypertensive drugs was associated with the risk of frailty; however, these findings may be biased by confounding and reverse causality. This study aimed to explore the effect of genetically predicted lifelong lowering blood pressure (BP) through different antihypertensive medications on frailty. One-sample Mendelian randomization (MR) and summary data-based MR (SMR) were applied. We utilized two kinds of genetic instruments to proxy the antihypertensive medications, including genetic variants within or nearby drugs target genes associated with systolic/diastolic BP, and expression level of the corresponding gene. Among 298,618 UK Biobank participants, one-sample MR analysis observed that genetically proxied BB use (relative risk ratios, 0.76; 95% CI, 0.65-0.90; p = 0.001) and CCB use (0.83; 0.72-0.95; p = 0.007), equivalent to a 10-mm Hg reduction in systolic BP, was significantly associated with lower risk of pre-frailty. In addition, although not statistically significant, the effect directions of systolic BP through ACEi variants (0.72; 0.39-1.33; p = 0.296) or thiazides variants (0.74; 0.53-1.03; p = 0.072) on pre-frailty were also protective. Similar results were obtained in analyses for diastolic BP. SMR of expression in artery showed that decreased expression level of KCNH2, a target gene of BBs, was associated with lower frailty index (beta -0.02, p = 2.87 × 10-4). This MR analysis found evidence that the use of BBs and CCBs was potentially associated with reduced frailty risk in the general population, and identified KCNH2 as a promising target for further clinical trials to prevent manifestations of frailty.

Dissection of the spatial dynamics of biosynthesis, transport, and turnover of major amino acids in tea plants (Camellia sinensis).

High levels of free amino acids (AAs) in tea leaves are crucial for tea flavor and health function; however, the dynamic AA biosynthesis, transport, and turnover in tea plants remain elusive. Here we dissected whole tea plants for these dynamics by assessing AA profiles and transcriptomes of metabolic pathway genes in tea roots, stems, and leaves and revealing their distinctive features with regard to AA synthesis, transport, and degradation/recycling. Nitrogen assimilation dominated in the roots wherein glutamine (Gln), theanine, and arginine (Arg) were actively synthesized. Arg was transported into trunk roots and stems, together with Glu, Gln, and theanine as the major AAs in the xylem sap for long-distance root-to-leaf transport. Transcriptome analysis revealed that genes involved in Arg synthesis were highly expressed in roots, but those for Arg transport and degradation were highly expressed in stems and young leaves, respectively. CsGSIa transcripts were found in root meristem cells, root, stem and leaf vascular tissues, and leaf mesophyll where it appeared to participate in AA synthesis, transport, and recycling. Overexpression of CsGSIa in tea transgenic hairy roots and knockdown of CsGSIa in transgenic hairy roots and tea leaves produced higher and lower Gln and theanine than wild-type roots and leaves, respectively. This study provides comprehensive and new insights into AA metabolism and transport in the whole tea plant.

Mycobacterium tuberculosis suppresses host antimicrobial peptides by dehydrogenating L-alanine.

Antimicrobial peptides (AMPs), ancient scavengers of bacteria, are very poorly induced in macrophages infected by Mycobacterium tuberculosis (M. tuberculosis), but the underlying mechanism remains unknown. Here, we report that L-alanine interacts with PRSS1 and unfreezes the inhibitory effect of PRSS1 on the activation of NF-κB pathway to induce the expression of AMPs, but mycobacterial alanine dehydrogenase (Ald) Rv2780 hydrolyzes L-alanine and reduces the level of L-alanine in macrophages, thereby suppressing the expression of AMPs to facilitate survival of mycobacteria. Mechanistically, PRSS1 associates with TAK1 and disruptes the formation of TAK1/TAB1 complex to inhibit TAK1-mediated activation of NF-κB pathway, but interaction of L-alanine with PRSS1, disables PRSS1-mediated impairment on TAK1/TAB1 complex formation, thereby triggering the activation of NF-κB pathway to induce expression of AMPs. Moreover, deletion of antimicrobial peptide gene ß-defensin 4 (Defb4) impairs the virulence by Rv2780 during infection in mice. Both L-alanine and the Rv2780 inhibitor, GWP-042, exhibits excellent inhibitory activity against M. tuberculosis infection in vivo. Our findings identify a previously unrecognized mechanism that M. tuberculosis uses its own alanine dehydrogenase to suppress host immunity, and provide insights relevant to the development of effective immunomodulators that target M. tuberculosis.

"Age" of tea: The impact of long-term storage on the aroma of Tuo tea and age prediction.

This study investigates the dynamic changes in the aroma profile of Tuo tea during long-term storage, a process not well understood yet critical to the formation of aged tea's unique characteristics. Aroma profiling of Tuo tea samples stored for 2 to 25 years was conducted using sensory evaluation and the HS-SPME/GC × GC-QTOFMS technique, revealing a progressive transition from fresh, fruity, and floral scents to more stale, woody, and herbal notes. Among 275 identified volatiles, 55 were correlated with storage duration (|r| > 0.8, p < 0.05), and 49 differential compounds (VIP > 1, FC > 1.2, FC < 0.833, p < 0.05) were identified across three storage stages (2-4, 5-10, and 13-25 years). Furthermore, theaspirane, eucalyptol, o-xylene, and 1-ethylidene-1H-indene were selected as potential markers of Tuo tea aging, incorporating the implementation of a Random Forest (RF) model. Additionally, our model exhibited high accuracy in predicting the age of Tuo tea within a prediction error range of -2.51 to 2.84 years. This research contributes to a comprehensive understanding of the impact of storage time on tea aroma and aids in the precise identification of tea age.

Mycobacterium tuberculosis produces D-serine under hypoxia to limit CD8+ T cell-dependent immunity in mice.

Adaptation to hypoxia is a major challenge for the survival of Mycobacterium tuberculosis (Mtb) in vivo. Interferon (IFN)-γ-producing CD8+ T cells contribute to control of Mtb infection, in part by promoting antimicrobial activities of macrophages. Whether Mtb counters these responses, particularly during hypoxic conditions, remains unknown. Using metabolomic, proteomic and genetic approaches, here we show that Mtb induced Rv0884c (SerC), an Mtb phosphoserine aminotransferase, to produce D-serine. This activity increased Mtb pathogenesis in mice but did not directly affect intramacrophage Mtb survival. Instead, D-serine inhibited IFN-γ production by CD8+ T cells, which indirectly reduced the ability of macrophages to restrict Mtb upon co-culture. Mechanistically, D-serine interacted with WDR24 and inhibited mTORC1 activation in CD8+ T cells. This decreased T-bet expression and reduced IFN-γ production by CD8+ T cells. Our findings suggest an Mtb evasion mechanism where pathogen metabolic adaptation to hypoxia leads to amino acid-dependent suppression of adaptive anti-TB immunity.

Effects of isolated scenting on the taste quality of broken green tea based on metabolomics.

Liquid chromatography-mass spectrometry (LC-MS) combined with multivariate analysis were used to characterize the nonvolatile compounds of broken green tea and explore the effect of isolated scenting on metabolic profile and taste quality of broken green tea in this research. A total of 236 nonvolatile compounds were identified and 13 compounds were believed to be the key characteristic taste compounds of scented broken green tea. Meanwhile, the optimal isolated scenting time of broken green tea was determined to be 10 h based on the sensory evaluation and PLS results. The contents and types of flavonoids, organic acids and catechins lead to the difference of taste quality at different scenting times. Overall, these findings provided a theoretical basis for scenting to improve the taste of broken green tea, and provide a new idea for improving the taste of broken green tea.

ARIP: A Tool for Precise Interatomic Contact Area and Volume Calculation in Proteins.

The interplay patterns of amino acid residues are pivotal in determining the tertiary structure and flexibility of proteins, which in turn are intricately linked to their functionality and interactions with other molecules. Here, we introduce ARIP, a novel tool designed to identify contact residues within proteins. ARIP employs a modified version of the dr_sasa algorithm and an atomic overlap weighted algorithm to directly calculate the contact area and volume between atoms based on their van der Waals radius. It also allows for the selection of solvent radii, recognizing that not every atom in proteins can interact with water molecules. The solvent parameters were derived from the analysis of approximately 5000 protein and nucleic acid structures with water molecules determined using X-ray crystallography. One advantage of the modified algorithm is its capability to analyze multiple models within a single PDB file, making it suitable for molecular dynamic capture. The contact volume is symmetrically distributed between the interacting atoms, providing more informative results than contact area for the analysis of intra- and intermolecular interactions and the development of scoring functions. Furthermore, ARIP has been applied to four distinct cases: capturing key residue-residue contacts in NMR structures of P4HB, protein-drug binding of CYP17A1, protein-DNA binding of SPI1, and molecular dynamic simulations of BRD4.

Osmosensor-mediated control of Ca2+ spiking in pollen germination.

Higher plants survive terrestrial water deficiency and fluctuation by arresting cellular activities (dehydration) and resuscitating processes (rehydration). However, how plants monitor water availability during rehydration is unknown. Although increases in hypo-osmolarity-induced cytosolic Ca2+ concentration (HOSCA) have long been postulated to be the mechanism for sensing hypo-osmolarity in rehydration1,2, the molecular basis remains unknown. Because osmolarity triggers membrane tension and the osmosensing specificity of osmosensing channels can only be determined in vivo3-5, these channels have been classified as a subtype of mechanosensors. Here we identify bona fide cell surface hypo-osmosensors in Arabidopsis and find that pollen Ca2+ spiking is controlled directly by water through these hypo-osmosensors-that is, Ca2+ spiking is the second messenger for water status. We developed a functional expression screen in Escherichia coli for hypo-osmosensitive channels and identified OSCA2.1, a member of the hyperosmolarity-gated calcium-permeable channel (OSCA) family of proteins6. We screened single and high-order OSCA mutants, and observed that the osca2.1/osca2.2 double-knockout mutant was impaired in pollen germination and HOSCA. OSCA2.1 and OSCA2.2 function as hypo-osmosensitive Ca2+-permeable channels in planta and in HEK293 cells. Decreasing osmolarity of the medium enhanced pollen Ca2+ oscillations, which were mediated by OSCA2.1 and OSCA2.2 and required for germination. OSCA2.1 and OSCA2.2 convert extracellular water status into Ca2+ spiking in pollen and may serve as essential hypo-osmosensors for tracking rehydration in plants.

Integrated Network Pharmacology and Experimental Validation Approach to Investigate the Mechanisms of Radix Rehmanniae Praeparata - Angelica Sinensis - Radix Achyranthis Bidentatae in Treating Knee Osteoarthritis.

Background: Knee osteoarthritis (KOA) is a persistent degenerative condition characterized by the deterioration of cartilage. The Chinese herbal formula Radix Rehmanniae Praeparata- Angelica Sinensis-Radix Achyranthis Bidentatae (RAR) has often been used in effective prescriptions for KOA as the main functional drug, but its underlying mechanism remains unclear. Therefore, network pharmacology and verification experiments were employed to investigate the impact and mode of action of RAR in the treatment of KOA. Methods: The destabilization of the medial meniscus model (DMM) was utilized to assess the anti-KOA effect of RAR by using gait analysis, micro-computed tomography (Micro-CT), and histology. Primary chondrocytes were extracted from the rib cartilage of a newborn mouse. The protective effects of RAR on OA cells were evaluated using a CCK-8 assay. The antioxidative effect of RAR was determined by measuring reactive oxygen species (ROS), superoxide dismutase (SOD), and glutathione (GSH) production. Furthermore, network pharmacology and molecular docking were utilized to propose possible RAR targets for KOA, which were further verified through experiments. Results: In vivo, RAR significantly ameliorated DMM-induced KOA characteristics, such as subchondral bone sclerosis, cartilage deterioration, gait abnormalities, and the degree of knee swelling. In vitro, RAR stimulated chondrocyte proliferation and the expression of Col2a1, Comp, and Acan. Moreover, RAR treatment significantly reduced ROS accumulation in an OA cell model induced by IL-1ß and increased the activity of antioxidant enzymes (SOD and GSH). Network pharmacology analysis combined with molecular docking showed that Mapk1 might be a key therapeutic target. Subsequent research showed that RAR could downregulate Mapk1 mRNA levels in IL-1ß-induced chondrocytes and DMM-induced rats. Conclusion: RAR inhibited extracellular matrix (ECM) degradation and oxidative stress response via the MAPK signaling pathway in KOA, and Mapk1 may be a core target.

Characterization of key odorants in 'Baimaocha' black teas from different regions.

'Baimmaocha' is a distinctive resource for production of high-quality black tea, and its processed black tea has unique aroma characteristics. 190 volatile compounds were identified by comprehensive two-dimensional gas chromatography-olfactometry-quadrupole-time-of-flight mass spectrometry(GC × GC-O-Q-TOMS), and among them 23 compounds were recognized as key odorants contributing to forming different aroma characteristics in 'Baimaocha' black teas of Rucheng, Renhua, and Lingyun (RCBT, RHBT, LYBT). The odor activity value coupled with GC-O showed that methyl salicylate (RCBT), geraniol (RHBT), trans-ß-ionone and benzeneacetaldehyde (LYBT) might be the most definitive aroma compounds identified from their respective regions. Furthermore, PLS analysis revealed three odorants as significant contributors to floral characteristic, four odorants related to fruity attribute, four odorants linked to fresh attribute, and three odorants associated with roasted attribute. These results provide novel insights into sensory evaluation and chemical substances of 'Baimaocha' black tea and provide a theoretical basis for controlling and enhancement tea aroma quality.

Tea Polyphenol Epigallocatechin Gallate Protects Against Nonalcoholic Fatty Liver Disease and Associated Endotoxemia in Rats via Modulating Gut Microbiota Dysbiosis and Alleviating Intestinal Barrier Dysfunction and Related Inflammation.

Nonalcoholic fatty liver disease (NAFLD) is characterized by fat accumulation and inflammation. Epigallocatechin gallate (EGCG) has been proven to be effective against NAFLD, but its hepatoprotective mechanisms based on the "gut microbiota-barrier-liver axis" are still not fully understood. Herein, the results demonstrated that EGCG effectively ameliorated NAFLD phenotypes and metabolic disorders in rats fed a high-fat diet (HFD), and inhibited intestinal barrier dysfunction and inflammation, which is also supported in the experiment of Caco-2 cells. Moreover, EGCG could restore gut microbiota diversity and composition, particularly promoting beneficial microbes, including short-chain fatty acids (SCFAs) producers, such as Lactobacillus, and suppressing Gram-negative bacteria, such as Desulfovibrio. The microbial modulation raised SCFA levels, decreased lipopolysaccharide levels, inhibited the TLR4/NF-κB pathway, and strengthened intestinal barrier function via Nrf2 pathway activation, thereby alleviating liver steatosis and inflammation. Spearman's correlation analysis showed that 24 key OTUs, negatively or positively associated with NAFLD and metabolic disorders, were also reshaped by EGCG. Our results suggested that a combinative improvement of EGCG on gut microbiota dysbiosis, intestinal barrier dysfunction, and inflammation might be a potential therapeutic target for NAFLD.

The Protective Effects of L-Theanine against Epigallocatechin Gallate-Induced Acute Liver Injury in Mice.

Epigallocatechin-3-gallate (EGCG) is a main bioactive constituent in green tea. Being a redox-active polyphenol, high-dose EGCG exhibits pro-oxidative activity and could cause liver injury. L-theanine is a unique non-protein amino acid in green tea and could provide liver-protective effects. The purpose of this study was to investigate the hepatoprotective effects of L-theanine on EGCG-induced liver injury and the underlying mechanisms. A total of 300 mg/kg L-theanine was administrated to ICR mice for 7 days. Then, the acute liver injury model was established through intragastric administration of 1000 mg/kg EGCG. Pretreatment with L-theanine significantly alleviated the oxidative stress and inflammatory response caused by high-dose EGCG through modulation of Nrf2 signaling and glutathione homeostasis. Furthermore, metabolomic results revealed that L-theanine protects mice from EGCG-induced liver injury mainly through the regulation of amino acid metabolism, especially tryptophan metabolism. These findings could provide valuable insights into the potential therapeutic applications of L-theanine and highlight the importance of the interactions between dietary components.

Genetic susceptibility to chronic diseases leads to heart failure among Europeans: the influence of leukocyte telomere length.

BACKGROUND: Genetic susceptibility to various chronic diseases has been shown to influence heart failure (HF) risk. However, the underlying biological pathways, particularly the role of leukocyte telomere length (LTL), are largely unknown. We investigated the impact of genetic susceptibility to chronic diseases and various traits on HF risk, and whether LTL mediates or modifies the pathways. METHODS: We conducted prospective cohort analyses on 404 883 European participants from the UK Biobank, including 9989 incident HF cases. Multivariable Cox regression was used to estimate associations between HF risk and 24 polygenic risk scores (PRSs) for various diseases or traits previously generated using a Bayesian approach. We assessed multiplicative interactions between the PRSs and LTL previously measured in the UK Biobank using quantitative PCR. Causal mediation analyses were conducted to estimate the proportion of the total effect of PRSs acting indirectly through LTL, an integrative marker of biological aging. RESULTS: We identified 9 PRSs associated with HF risk, including those for various cardiovascular diseases or traits, rheumatoid arthritis (P = 1.3E-04), and asthma (P = 1.8E-08). Additionally, longer LTL was strongly associated with decreased HF risk (P-trend = 1.7E-08). Notably, LTL strengthened the asthma-HF relationship significantly (P-interaction = 2.8E-03). However, LTL mediated only 1.13% (P < 0.001) of the total effect of the asthma PRS on HF risk. CONCLUSIONS: Our findings shed light onto the shared genetic susceptibility between HF risk, asthma, rheumatoid arthritis, and other traits. Longer LTL strengthened the genetic effect of asthma in the pathway to HF. These results support consideration of LTL and PRSs in HF risk prediction.

Trans-eQTL mapping in gene sets identifies network effects of genetic variants.

Nearly all trait-associated variants identified in genome-wide association studies (GWASs) are noncoding. The cis regulatory effects of these variants have been extensively characterized, but how they affect gene regulation in trans has been the subject of fewer studies because of the difficulty in detecting trans-expression quantitative loci (eQTLs). We developed trans-PCO for detecting trans effects of genetic variants on gene networks. Our simulations demonstrate that trans-PCO substantially outperforms existing trans-eQTL mapping methods. We applied trans-PCO to two gene expression datasets from whole blood, DGN (N = 913) and eQTLGen (N = 31,684), and identified 14,985 high-quality trans-eSNP-module pairs associated with 197 co-expression gene modules and biological processes. We performed colocalization analyses between GWAS loci of 46 complex traits and the trans-eQTLs. We demonstrated that the identified trans effects can help us understand how trait-associated variants affect gene regulatory networks and biological pathways.

Sulfatase-Induced In Situ Formulation of Antineoplastic Supra-PROTACs.

Proteolysis targeting chimera (PROTAC) technology is an innovative strategy for cancer therapy, which, however, suffers from poor targeting delivery and limited capability for protein of interest (POI) degradation. Here, we report a strategy for the in situ formulation of antineoplastic Supra-PROTACs via intracellular sulfatase-responsive assembly of peptides. Coassembling a sulfated peptide with two ligands binding to ubiquitin VHL and Bcl-xL leads to the formation of a pro-Supra-PROTAC, in which the ratio of the two ligands is rationally optimized based on their protein binding affinity. The resulting pro-Supra-PROTAC precisely undergoes enzyme-responsive assembly into nanofibrous Supra-PROTACs in cancer cells overexpressing sulfatase. Mechanistic studies reveal that the pro-Supra-PROTACs selectively cause apparent cytotoxicity to cancer cells through the degradation of Bcl-xL and the activation of caspase-dependent apoptosis, during which the rationally optimized ligand ratio improves the bioactivity for POI degradation and cell death. In vivo studies show that in situ formulation enhanced the tumor accumulation and retention of the pro-Supra-PROTACs, as well as the capability for inhibiting tumor growth with excellent biosafety when coadministrating with chemodrugs. Our findings provide a new approach for enzyme-regulated assembly of peptides in living cells and the development of PROTACs with high targeting delivering and POI degradation efficiency.

Using genetics and proteomics data to identify proteins causally related to COVID-19, healthspan and lifespan: a Mendelian randomization study.

BACKGROUND: COVID-19 pandemic poses a heavy burden on public health and accounts for substantial mortality and morbidity. Proteins are building blocks of life, but specific proteins causally related to COVID-19, healthspan and lifespan have not been systematically examined. METHODS: We conducted a Mendelian randomization study to assess the effects of 1,361 plasma proteins on COVID-19, healthspan and lifespan, using large GWAS of severe COVID-19 (up to 13,769 cases and 1,072,442 controls), COVID-19 hospitalization (32,519 cases and 2,062,805 controls) and SARS-COV2 infection (122,616 cases and 2,475,240 controls), healthspan (n = 300,477) and parental lifespan (~0.8 million of European ancestry). RESULTS: We identified 35, 43, and 63 proteins for severe COVID, COVID-19 hospitalization, and SARS-COV2 infection, and 4, 32, and 19 proteins for healthspan, father's attained age, and mother's attained age. In addition to some proteins reported previously, such as SFTPD related to severe COVID-19, we identified novel proteins involved in inflammation and immunity (such as ICAM-2 and ICAM-5 which affect COVID-19 risk, CXCL9, HLA-DRA and LILRB4 for healthspan and lifespan), apoptosis (such as FGFR2 and ERBB4 which affect COVID-19 risk and FOXO3 which affect lifespan) and metabolism (such as PCSK9 which lowers lifespan). We found 2, 2 and 3 proteins shared between COVID-19 and healthspan/lifespan, such as CXADR and LEFTY2, shared between severe COVID-19 and healthspan/lifespan. Three proteins affecting COVID-19 and seven proteins affecting healthspan/lifespan are targeted by existing drugs. CONCLUSIONS: Our study provided novel insights into protein targets affecting COVID-19, healthspan and lifespan, with implications for developing new treatment and drug repurposing.

Alternative splicing of CARM1 regulated by LincGET-guided paraspeckles biases the first cell fate in mammalian early embryos.

The heterogeneity of CARM1 controls first cell fate bias during early mouse development. However, how this heterogeneity is established is unknown. Here, we show that Carm1 mRNA is of a variety of specific exon-skipping splicing (ESS) isoforms in mouse two-cell to four-cell embryos that contribute to CARM1 heterogeneity. Disruption of paraspeckles promotes the ESS of Carm1 precursor mRNAs (pre-mRNAs). LincGET, but not Neat1, is required for paraspeckle assembly and inhibits the ESS of Carm1 pre-mRNAs in mouse two-cell to four-cell embryos. We further find that LincGET recruits paraspeckles to the Carm1 gene locus through HNRNPU. Interestingly, PCBP1 binds the Carm1 pre-mRNAs and promotes its ESS in the absence of LincGET. Finally, we find that the ESS seen in mouse two-cell to four-cell embryos decreases CARM1 protein levels and leads to trophectoderm fate bias. Our findings demonstrate that alternative splicing of CARM1 has an important role in first cell fate determination.

Potential anti-hyperglycemic activity of black tea theaflavins through inhibiting α-amylase.

Hyperglycemia can cause early damage to human bady and develop into diabates that will severely threaten human healthy. The effectively clinical treatment of hyperglycemiais is by inhibiting the activity of α-amylase. Black tea has been reported to show inhibitory effect on α-amylase and can be used for hyperglycemia treatment. However, the mechanism underlying is unclear. In this study, in vivo experiment showed that black tea theaflavins extract (BTE) effectively alleviated hyperglycemia. In vitro experiment showed that the effects may be caused by the interation between theaflavins and α-amylase. While TF1 and TF3 were mixed type inhibitors of α-amylase, TF2A and TF2B were competitive inhibitors of α-amylase. Molecular docking analysis showed that theaflavins monomers interacted with the hydrophobic region of α-amylase. Further study verified that monomer-α-amylase complex was spontaneously formed depending on hydrophobic interactions. Taken together, theaflavins showed potential anti-hyperglycemia effect via inhibiting α-amylase activity. Our results suggested that theaflavins might be utilized as a new type of α-amylase inhibitor to prevent and cure hyperglycemia.

Benchmarking Supervised and Self-Supervised Learning Methods in A Large Ultrasound Muti-task Images Dataset.

Deep learning in ultrasound(US) imaging aims to construct foundational models that accurately reflect the modality's unique characteristics. Nevertheless, the limited datasets and narrow task types have restricted this field in recent years. To address these challenges, we introduce US-MTD120K, a multi-task ultrasound dataset with 120,354 real-world two-dimensional images. This dataset covers three standard plane recognition and two diagnostic tasks in ultrasound imaging, providing a rich basis for model training and evaluation. We detail the data collection, distribution, and labelling processes, ensuring a thorough understanding of the dataset's structure. Furthermore, we conduct extensive benchmark tests on 27 state-of-the-art methods from both supervised and self-supervised learning(SSL) perspectives. In the realm of supervised learning, we analyze the sensitivity of two main feature computation methods to ultrasound images at the representational level, highlighting that models which judiciously constrain global feature computation could potentially serve as a viable analytical approach for US image analysis. In the context of self-supervised learning, we delved into the modelling process of self-supervised learning models for medical images and proposed an improvement strategy, named MoCo-US, a solution that addresses the excessive reliance on pretext task design from the input side. It achieves competitive performance with minimal pretext task design and enhances other SSL methods simply. The dataset and the code will be available at https://github.com/JsongZhang/CDOA-for-UMTD.