Genetic causality and metabolite pathway identifying the relationship of blood metabolites and psoriasis.

BACKGROUND: Psoriasis is a chronic inflammatory disease that causes significant disability. However, little is known about the underlying metabolic mechanisms of psoriasis. Our study aims to investigate the causality of 975 blood metabolites with the risk of psoriasis. MATERIALS AND METHODS: We mainly applied genetic analysis to explore the possible associations between 975 blood metabolites and psoriasis. The inverse variance weighted (IVW) method was used as the primary analysis to assess the possible association of blood metabolites with psoriasis. Moreover, generalized summary-data-based Mendelian randomization (GSMR) was used as a supplementary analysis. In addition, linkage disequilibrium score regression (LDSC) was used to investigate their genetic correction further. Metabolic pathway analysis of the most suggested metabolites was also performed using MetaboAnalyst 5.0. RESULTS: In our primary analysis, 17 metabolites, including unsaturated fatty acids, phospholipids, and triglycerides traits, were selected as potential factors in psoriasis, with odd ratios (OR) ranging from 0.986 to 1.01. The GSMR method confirmed the above results (ß = 0.001, p < 0.05). LDSC analysis mainly suggested the genetic correlation of psoriasis with genetic correlations (rg) from 0.088 to 0.155. Based on the selected metabolites, metabolic pathway analysis suggested seven metabolic pathways including ketone body that may be prominent pathways for metabolites in psoriasis. CONCLUSION: Our study supports the causal role of unsaturated fatty acid properties and lipid traits with psoriasis. These properties may be regulated by the ketone body metabolic pathway.

Efficacy and safety of apatinib plus immune checkpoint inhibitors and transarterial chemoembolization for the treatment of advanced hepatocellular carcinoma.

PURPOSE: The evidence of apatinib plus immune checkpoint inhibitors (ICIs) and transarterial chemoembolization (TACE) for treating advanced hepatocellular carcinoma (HCC) is limited. This study aimed to compare the treatment efficacy and safety of apatinib plus ICIs and TACE with apatinib plus TACE in these patients. METHODS: This study retrospectively enrolled 90 patients with advanced HCC treated with apatinib plus TACE (A-TACE group, n = 52) or apatinib plus ICIs and TACE (IA-TACE group, n = 38). RESULTS: The objective response rate was numerically higher in IA-TACE group compared with A-TACE group without statistical significance (57.9% vs. 36.5%, P = 0.055). Disease control rate was not different between groups (86.8% vs. 76.9%, P = 0.248). Progression-free survival (PFS) was improved in IA-TACE group compared with A-TACE group (P = 0.018). The median PFS (95% confidence interval) was 12.5 (8.7-16.3) months in IA-TACE group and 8.5 (5.6-11.4) months in A-TACE group. Overall survival (OS) was also prolonged in IA-TACE group compared with A-TACE group (P = 0.007). The median OS (95% confidence interval) was 21.1 (15.8-26.4) months in IA-TACE group and 14.3 (11.5-17.1) months in A-TACE group. By multivariate Cox regression model, IA-TACE was independently associated with prolonged PFS (hazard ratio = 0.539, P = 0.038) and OS (hazard ratio = 0.447, P = 0.025). Most adverse events were not different between groups. Only the incidence of reactive cutaneous capillary endothelial proliferation was higher in IA-TACE group compared with A-TACE group (10.5% vs. 0.0%, P = 0.029). CONCLUSION: Apatinib plus ICIs and TACE may be an effective and safe treatment for patients with advanced HCC, but further large-scale studies are needed for verification.

Revealing the polarity decrease of cardiomyocyte in the septic cardiomyopathy by a lipid droplets-targeting fluorescent probe with NIR emission.

Septic cardiomyopathy (SCM) is the main cause of death in critically ill patients with sepsis. However, its definitive pathogenic mechanisms remain to be elucidated. Lipid droplets (LDs) are important sub-organelles that store lipids and participate in intracellular lipid metabolism. Abnormal aggregation and altered polarity of LDs are associated with the development of several cardiac diseases. To date, visualization of abnormal polarity in models of SCM has not been achieved. Herein, we designed and synthesized the probe BDP-551, a polarity-sensitive probe possessing a donor-π-acceptor (D-π-A) structure. BDP-551 exhibits excellent photostability, high LDs targeting, near-infrared (NIR) emission (up to 678 nm) and strong polarity sensitivity. With the help of confocal imaging microscopy, the BDP-551 was able to detect the polarity changes induced in the SCM model cells and visualize the yolk sac region in hypoxic as well as inflamed living zebrafish. In addition, the BDP-551 has been successfully applied to visualize the polarity changes of mice hearts with SCM, proving a decrease of microenvironmental polarity in the development of SCM. Therefore, BDP-551 in this study can be used as a reliable tool to investigate polarity fluctuations and provide new insights into the associated pathogenic and therapeutic mechanisms on SCM.

Phase division and recognition of crystal HRTEM images based on machine learning and deep learning.

The High Resolution Transmission Electron Microscope (HRTEM) images provide valuable insights into the atomic microstructure, dislocation patterns, defects, and phase characteristics of materials. However, the current analysis and research of HRTEM images of crystal materials heavily rely on manual expertise, which is labor-intensive and susceptible to subjective errors. This study proposes a combined machine learning and deep learning approach to automatically partition the same phase regions in crystal HRTEM images. The entire image is traversed by a sliding window to compute the amplitude spectrum of the Fast Fourier Transform (FFT) in each window. The generated data is transformed into a 4-dimensional (4D) format. Principal component analysis (PCA) on this 4D data estimates the number of feature regions. Non-negative matrix factorization (NMF) then decomposes the data into a coefficient matrix representing feature region distribution, and a feature matrix corresponding to the FFT magnitude spectra. Phase recognition based on deep learning enables identifying the phase of each feature region, thereby achieving automatic segmentation and recognition of phase regions in HRTEM images of crystals. Experiments on zirconium and oxide nanoparticle HRTEM images demonstrate the proposed method achieve the consistency of manual analysis. Code and supplementary material are available at https://github.com/rememberBr/HRTEM2.

Strain sensor on a chip for quantifying the magnitudes of tensile stress on cells.

During cardiac development, mechanotransduction from the in vivo microenvironment modulates cardiomyocyte growth in terms of the number, area, and arrangement heterogeneity. However, the response of cells to different degrees of mechanical stimuli is unclear. Organ-on-a-chip, as a platform for investigating mechanical stress stimuli in cellular mimicry of the in vivo microenvironment, is limited by the lack of ability to accurately quantify externally induced stimuli. However, previous technology lacks the integration of external stimuli and feedback sensors in microfluidic platforms to obtain and apply precise amounts of external stimuli. Here, we designed a cell stretching platform with an in-situ sensor. The in-situ liquid metal sensors can accurately measure the mechanical stimulation caused by the deformation of the vacuum cavity exerted on cells. The platform was applied to human cardiomyocytes (AC16) under cyclic strain (5%, 10%, 15%, 20 and 25%), and we found that cyclic strain promoted cell growth induced the arrangement of cells on the membrane to gradually unify, and stabilized the cells at 15% amplitude, which was even more effective after 3 days of culture. The platform's precise control and measurement of mechanical forces can be used to establish more accurate in vitro microenvironmental models for disease modeling and therapeutic research.

Application of Refrigerant Cooling in a Battery Thermal Management System under High Temperature Conditions: A Review.

Battery thermal management (BTM) is crucial for the lifespan and safety of batteries. Refrigerant cooling is a novel cooling technique that is being used gradually. As the core fluid of refrigerant cooling, refrigerants need to possess excellent properties while meeting environmental requirements. This paper elucidates the current state of refrigerants (single refrigerants and mixed refrigerants), synchronously summarizing them from the perspectives of refrigerant properties and refrigerant cooling (immersion and cold plate indirect). It outlines the advantages and disadvantages of single and mixed refrigerants as well as the research and development in the vehicle thermal management system (TMS). The choice of refrigerant directly affects cooling performance, and research on vehicle air conditioning (AC) systems can indirectly guide the BTM. R1234yf and R152a can directly replace R134a, while although R744 has a strong heating capacity, it cannot directly replace R134a. Specific mixed refrigerants reduce the global warming potential (GWP) and flammability issues, thereby improving system efficiency. Additionally, immersion cooling controls the temperature through container pressure. Coordinated control strategies are crucial for indirect cold plate cooling, offering broad prospects for optimizing the cold plate design and intelligent control. The selection of refrigerant and the optimal design of the cooling method greatly improve the thermal performance of the battery. This may promote the good development of BTM.

Analyzing variation of water inflow to inland lakes under climate change: Integrating deep learning and time series data mining.

The alarming depletion of global inland lakes in recent decades makes it essential to predict water inflow from rivers to lakes (WIRL) trend and unveil the dominant influencing driver, particularly in the context of climate change. The raw time series data contains multiple components (i.e., long-term trend, seasonal periodicity, and random noise), which makes it challenging for traditional machine/deep learning techniques to effectively capture long-term trend information. In this study, a novel FactorConvSTLnet (FCS) method is developed through integrating STL decomposition, convolutional neural networks (CNN), and factorial analysis into a general framework. FCS is more robust in long-term WIRL trend prediction through separating trend information as a modeling predictor, as well as unveiling predominant drivers. FCS is applied to typical inland lakes (the Aral Sea and the Lake Balkhash) in Central Asia, and results indicate that FCS (Nash-Sutcliffe efficiency = 0.88, root mean squared error = 67m³/s, mean relative error = 10%) outperforms the traditional CNN. Some main findings are: (i) during 1960-1990, reservoir water storage (WSR) was the dominant driver for the two lakes, respectively contributing to 71% and 49%; during 1991-2014 and 2015-2099, evaporation (EVAP) would be the dominant driver, with the contribution of 30% and 47%; (ii) climate change would shift the dominant driver from human activities to natural factors, where EVAP and surface snow amount (SNW) have an increasing influence on WIRL; (iii) compared to SSP1-2.6, the SNW contribution would decrease by 26% under SSP5-8.5, while the EVAP contribution would increase by 9%. The findings reveal the main drivers of shrinkage of the inland lakes and provide the scientific basis for promoting regional ecological sustainability.

Suffering makes you weaker: Limited evolutionary adaptation in competitively inferior populations.

Interspecific competition can hinder populations from evolutionarily adapting to abiotic environments, particularly by reducing population size and niche space; and feedback may arise between competitive ability and evolutionary adaptation. Here we studied populations of two model bacterial species, Escherichia coli and Pseudomonas fluorescens, that evolved in monocultures and cocultures for approximately 2400 generations at three temperatures. The two species showed a reversal in competitive dominance in cocultures along the temperature gradient. Populations from cocultures where they had been competitively dominant showed the same magnitude of fitness gain as those in monocultures. However, competitively inferior populations in cocultures showed limited abiotic adaptation compared with those in monocultures. The inferior populations in cocultures were also more likely to evolve weaker interspecific competitive ability, or go extinct. The possible competitive ability-adaptation feedback may have crucial consequences for population persistence.

Clinical and Molecular Characterization of AIPL1-Associated Leber Congenital Amaurosis/Early-Onset Severe Retinal Dystrophy.

PURPOSE: This study aimed to characterize the clinical features, genetic findings and genotype-phenotype correlations of patients with Leber congenital amaurosis (LCA) or early-onset severe retinal dystrophy (EOSRD) harboring biallelic AIPL1 pathogenic variants. DESIGN: Retrospective case-series. METHODS: This study consecutively enrolled 51 patients from 47 families with a clinical diagnosis of LCA/EOSRD harboring disease-causing variants in the AIPL1 gene, from October 2021 to September 2023. Molecular genetic findings, medical history, and ophthalmic evaluation including visual acuity (VA), multimodal retinal imaging and electrophysiologic assessment were reviewed. RESULTS: Of the 51 patients (32 with LCA and 19 with EOSRD), 27 (53%) were females, and age at last review ranged from 0.5-58.4 years. We identified 28 disease-causing AIPL1 variants, with 18 being novel. In patients with EOSRD, the mean (range) VA was 1.3 (0.7-2.7) logMAR and 1.3 (0.5-2.3) logMAR for right and left eyes respectively, with an average annual decline of 0.03 logMAR (R2 = 0.7547, P < 0.01). For patients with LCA, the VA ranged from light perception to counting fingers. Optical coherence tomography imaging demonstrated preservation of foveal ellipsoid zone in the 5 youngest EOSRD patients and 9 LCA children. Electroretinography showed severe cone-rod patterns in 78.6% (11/14) of patients with EOSRD, while classical extinguished pattern was documented in all patients with LCA available for the examination. The most common mutation was the nonsense variants of c.421C>T, with am allele frequency of 53.9%. All patients with EOSRD carried at least one missense mutation, of whom 13 identified with c.152A>G and 5 with c.572T>C. Twenty-six patients with LCA harbored two null AIPL1 variants, while 18 were homozygous for c.421C>T, and 6 were heterozygous for c.421C>T with another loss-of-function variant. CONCLUSIONS: This study reveals distinct clinical features and variation spectrum between AIPL1-associated LCA and EOSRD. Patients harboring at least one non-null mutations, especially c.152A>G and c.572T>C, were significantly more likely to have a milder EOSRD phenotype than those with two null mutations. Residual foveal outer retinal structure observed in the youngest proportion of patients suggests an early window for gene augmentation therapy.

Molecular docking and MD simulation studies of 4-thiazol-N-(pyridin-2-yl)pyrimidin-2-amine derivatives as novel inhibitors targeted to CDK2/4/6.

PURPOSE: Nowadays, cyclin-dependent kinase 4/6 (CDK4/6) inhibitors have been approved for treating metastatic breast cancer and have achieved inspiring curative effects. But some discoveries have indicated that CDK 4/6 are not the requisite factors in some cell types because CDK2 partly compensates for the inhibition of CDK4/6. Thus, it is urgent to design CDK2/4/6 inhibitors for significantly enhancing their potency. This study aims to explore the mechanism of the binding of CDK2/4/6 kinases and their inhibitors to design novel CDK2/4/6 inhibitors for significantly enhancing their potency in different kinds of cancers. MATERIALS AND METHODS: A series of 72 disparately functionalized 4-substituted N-phenylpyrimidin-2-amine derivatives exhibiting potent inhibitor activities against CDK2, CDK4 and CDK6 were collected to apply to this research. The total set of these derivatives was divided into a training set (54 compounds) and a test set (18 compounds). The derivatives were constructed through the sketch molecule module in SYBYL 6.9 software. A Powell gradient algorithm and Tripos force field were used to calculate the minimal structural energy and the minimized structure was used as the initial conformation for molecular docking. By the means of 3D-QSAR models, partial least squares (PLS) analysis, molecular dynamics (MD) simulations and binding free energy calculations, we can find the relationship between structure and biological activity. RESULTS: In this study, we used molecular docking, 3D-QSAR and molecular dynamics simulation methods to comprehensively analyze the interaction and structure-activity relationships of 72 new CDK2/4/6 inhibitors. We used detailed statistical data to reasonably verify the constructed 3D-QSAR models for three receptors (q2 of CDK2 = 0.714, R2pred = 0.764, q2 = 0.815; R2pred of CDK4 = 0.681, q2 = 0.757; R2pred of CDK6 = 0.674). MD simulations and decomposition energy analysis validated the reasonability of the docking results and identified polar interactions as crucial factors that influence the different bioactivities of the studied inhibitors of CDK2/4/6 receptors, especially the electrostatic interactions of Lys33/35/43 and Asp145/158/163. The nonpolar interaction with Ile10/12/19 was also critical for the differing potencies of the CDK2/4/6 inhibitors. We concluded that the following probably enhanced the bioactivity against CDK2/4/6 kinases: (1) electronegative groups at the N1-position and electropositive and moderate-sized groups at ring E; (2) electrogroups featured at R2; (3) carbon atoms at the X-position or ring C replaced by a benzene ring; and (4) an electrogroup as R4. CONCLUSION: Previous studies, to our knowledge, only utilized a single approach of 3D-QSAR and did not integrate this method with other sophisticated techniques such as molecular dynamics simulations to discover new potential inhibitors of CDK2, CDK4, or CDK6. So we applied the intergenerational technology, such as 3D-QSAR technology, molecular docking simulation techniques, molecular dynamics simulations and MMPBSA19/MMGBSA20-binding free energy calculations to statistically explore the correlations between the structure with biological activities. The constructed 3D-QSAR models of the three receptors were reasonable and confirmed by the excellent statistical data. We hope the results obtained from this work will provide some useful references for the development of novel CDK2/4/6 inhibitors.

The Association Between Functional Variants in Long Non-coding RNAs and the Risk of Autism Spectrum Disorder Was Not Mediated by Gut Microbiota.

The effect of functional variants in long non-coding RNA (lncRNA) gene regions on autism spectrum disorder (ASD) remains unclear. The present study aimed to investigate the association of functional variants located in lncRNA genes with the risk of ASD and explore whether gut microbiota would mediate the relationship. A total of 87 cases and 71 healthy controls were enrolled in the study. MassARRAY platform and 16S rRNA sequencing were respectively applied to assess the genotype of candidate SNPs and gut microbiota of children. The logistic regression models showed that the association between rs2295412 and the risk of ASD was statistically significant after Bonferroni adjustments. The risk of ASD decreased by 19% for each additional C allele carried by children in multiplicative models (OR = 0.81, 95% CI, 0.69-0.94, P = 0.007). Although we identified significant correlations between rs8113922 polymorphisms, Bifidobacteriales, and ASD, the mediating effect of gut microbiota on the relationship of the polymorphisms with the risk of ASD was not significant. The findings demonstrated that functional variants in lncRNA genes play an important role in ASD and gut microbiota could not mediate the association. Future studies are warranted to verify the results and search for more possible mechanisms of variants located in lncRNA genes implicated in ASD.

Developmental and nuclear proteomic signatures characterize the temporal regulation of fibroin synthesis during the last molting-feeding transition of silkworm.

Silkworm fibroins are natural proteinaceous macromolecules and provide core mechanical properties to silk fibers. The synthesis process of fibroins is posterior silk gland (PSG)-exclusive and appears active at the feeding stage and inactive at the molting stage. However, the molecular mechanisms controlling it remain elusive. Here, the silk gland's physiological and nuclear proteomic features were used to characterize changes in its structure and development from molting to feeding stages. The temporal expression profile and immunofluorescence analyses revealed a synchronous transcriptional on-off mode of fibroin genes. Next, the comparative nuclear proteome of the PSG during the last molting-feeding transition identified 798 differentially abundant proteins (DAPs), including 42 transcription factors and 15 epigenetic factors. Protein-protein interaction network analysis showed a "CTCF-FOX-HOX-SOX" association with activated expressions at the molting stage, suggesting a relatively complex and multifactorial regulation of the PSG at the molting stage. In addition, FAIRE-seq verification indicated "closed" and "open" conformations of fibroin gene promoters at the molting and feeding stages, respectively. Such proteome combined with chromatin accessibility analysis revealed the detailed signature of protein factors involved in the temporal regulation of fibroin synthesis and provided insights into silk gland development as well as silk production in silkworms.

Structure of cryptophyte photosystem II-light-harvesting antennae supercomplex.

Cryptophytes are ancestral photosynthetic organisms evolved from red algae through secondary endosymbiosis. They have developed alloxanthin-chlorophyll a/c2-binding proteins (ACPs) as light-harvesting complexes (LHCs). The distinctive properties of cryptophytes contribute to efficient oxygenic photosynthesis and underscore the evolutionary relationships of red-lineage plastids. Here we present the cryo-electron microscopy structure of the Photosystem II (PSII)-ACPII supercomplex from the cryptophyte Chroomonas placoidea. The structure includes a PSII dimer and twelve ACPII monomers forming four linear trimers. These trimers structurally resemble red algae LHCs and cryptophyte ACPI trimers that associate with Photosystem I (PSI), suggesting their close evolutionary links. We also determine a Chl a-binding subunit, Psb-γ, essential for stabilizing PSII-ACPII association. Furthermore, computational calculation provides insights into the excitation energy transfer pathways. Our study lays a solid structural foundation for understanding the light-energy capture and transfer in cryptophyte PSII-ACPII, evolutionary variations in PSII-LHCII, and the origin of red-lineage LHCIIs.

Complete genome sequence of Rhodococcus sp. strain PD04, a pyridine-degrading bacterium under hypersaline condition.

We report the complete genome sequence of a pyridine-degrading Rhodococcus sp. strain PD04 under 4% salinity environment, isolated from wastewater of coking plant. The genome is 6.07 Mb with 5,767 annotated gene coding sequences.

The anti-tumor activity of tangeretin in esophageal squamous cell carcinoma by inhibiting GLI2-mediated transcription of GPNMB.

Tangeretin (Tan), a citrus flavonoid, possesses a strong anti-tumor efficacy in various human cancers. However, the precise role of Tan in the development of esophageal squamous cell carcinoma (ESCC) remains unclear. RNA sequencing (RNA-seq) analysis was performed to observe the Tan-related genes in Tan-treated TE-1 cells. The direct relationship between GLI family zinc finger 2 (GLI2) and the promoter of glycoprotein non-metastatic melanoma protein B (GPNMB) was predicted by bioinformatics analysis and validated by luciferase reporter and chromatin immunoprecipitation (ChIP) assays. Cell survival after Tan treatment was assessed by CCK8 assay. Gene expression levels were evaluated by a qRT-PCR, western blot, or immunofluorescence method. Cell migration and invasion were detected by wound-healing and transwell assays. The function of Tan in vivo was examined using xenograft studies. Our data indicated anti-migration and anti-invasion functions of Tan in ESCC cells in vitro. Tan also diminished tumor growth in vivo. Mechanistically, Tan diminished the expression and transcriptional activity of GLI2 in ESCC cells. Silencing of GLI2 resulted in decreased expression of GPNMB by inhibiting GPNMB transcription via the binding site at the GPNMB promoter at position +(1539-1550). Moreover, Tan down-regulated GPNMB expression in ESCC cells, and re-expression of GPNMB reversed anti-migration and anti-invasion functions of Tan in ESCC cells. Our findings uncover anti-migration and anti-invasion effects of Tan in ESCC cells by down-regulating GPNMB by suppressing GLI2-mediated GPNMB transcription, providing new evidence that Tan can function as a therapeutic agent against ESCC.

mTORC1 and BMP-Smad1/5 regulation of serum-stimulated myotube hypertrophy: a role for autophagy.

Protein synthesis regulation is critical for skeletal muscle hypertrophy, yet other established cellular processes are necessary for growth-related cellular remodeling. Autophagy has a well-acknowledged role in muscle quality control, but evidence for its role in myofiber hypertrophy remains equivocal. Both mammalian target of rapamycin complex I (mTORC1) and bone morphogenetic protein (BMP)-Smad1/5 (Sma and Mad proteins from Caenorhabditis elegans and Drosophila, respectively) signaling are reported regulators of myofiber hypertrophy; however, gaps remain in our understanding of how this regulation is integrated with growth processes and autophagy regulation. Therefore, we investigated the mTORC1 and Smad1/5 regulation of protein synthesis and autophagy flux during serum-stimulated myotube growth. Chronic serum stimulation experiments were performed on day 5 differentiated C2C12 myotubes incubated in differentiation medium [2% horse serum (HS)] or growth medium [5% fetal bovine serum (FBS)] for 48 h. Rapamycin or LDN193189 was dosed for 48 h to inhibit mTORC1 and BMP-Smad1/5 signaling, respectively. Acute serum stimulation was examined in day 7 differentiated myotubes. Protein synthesis was measured by puromycin incorporation. Bafilomycin A1 and immunoblotting for LC3B were used to assess autophagy flux. Chronic serum stimulation increased myotube diameter 22%, total protein 21%, total RNA 100%, and Smad1/5 phosphorylation 404% and suppressed autophagy flux. Rapamycin, but not LDN193189, blocked serum-induced myotube hypertrophy and the increase in total RNA. Acute serum stimulation increased protein synthesis 111%, Smad1/5 phosphorylation 559%, and rpS6 phosphorylation 117% and suppressed autophagy flux. Rapamycin increased autophagy flux during acute serum stimulation. These results provide evidence for mTORC1, but not BMP-Smad1/5, signaling being required for serum-induced myotube hypertrophy and autophagy flux by measuring LC3BII/I expression. Further investigation is warranted to examine the role of autophagy flux in myotube hypertrophy.NEW & NOTEWORTHY The present study demonstrates that myotube hypertrophy caused by chronic serum stimulation requires mammalian target of rapamycin complex 1 (mTORC1) signaling but not bone morphogenetic protein (BMP)-Smad1/5 signaling. The suppression of autophagy flux was associated with serum-induced myotube hypertrophy and mTORC1 regulation of autophagy flux by measuring LC3BII/I expression. Rapamycin is widely investigated for beneficial effects in aging skeletal muscle and sarcopenia; our results provide evidence that rapamycin can regulate autophagy-related signaling during myotube growth, which could benefit skeletal muscle functional and metabolic health.

Spatiotemporal multi-omics: exploring molecular landscapes in aging and regenerative medicine.

Aging and regeneration represent complex biological phenomena that have long captivated the scientific community. To fully comprehend these processes, it is essential to investigate molecular dynamics through a lens that encompasses both spatial and temporal dimensions. Conventional omics methodologies, such as genomics and transcriptomics, have been instrumental in identifying critical molecular facets of aging and regeneration. However, these methods are somewhat limited, constrained by their spatial resolution and their lack of capacity to dynamically represent tissue alterations. The advent of emerging spatiotemporal multi-omics approaches, encompassing transcriptomics, proteomics, metabolomics, and epigenomics, furnishes comprehensive insights into these intricate molecular dynamics. These sophisticated techniques facilitate accurate delineation of molecular patterns across an array of cells, tissues, and organs, thereby offering an in-depth understanding of the fundamental mechanisms at play. This review meticulously examines the significance of spatiotemporal multi-omics in the realms of aging and regeneration research. It underscores how these methodologies augment our comprehension of molecular dynamics, cellular interactions, and signaling pathways. Initially, the review delineates the foundational principles underpinning these methods, followed by an evaluation of their recent applications within the field. The review ultimately concludes by addressing the prevailing challenges and projecting future advancements in the field. Indubitably, spatiotemporal multi-omics are instrumental in deciphering the complexities inherent in aging and regeneration, thus charting a course toward potential therapeutic innovations.

Tectorigenin improves metabolic dysfunction-associated steatohepatitis by down-regulating tRF-3040b and promoting mitophagy to inhibit pyroptosis pathway.

Tectorigenin (TEC) as a plant extract has the advantage of low side effects on metabolic dysfunction-associated steatohepatitis (MASH) treatment. Our previous study have shown that tRNA-derived RNA fragments (tRFs) associated with autophagy and pyroptosis in MASH, but whether TEC can mitigate MASH through tRFs-mediated mitophagy is not fully understood. This study aims to investigate whether TEC relies on tRFs to adjust the crosstalk of hepatocyte mitophagy with pyroptosis in MASH. Immunofluorescence results of PINK1 and PRKN with MitoTracker Green-labeled mitochondria verified that TEC enhanced mitophagy. Additionally, TEC inhibited pyroptosis, as reflected by the level of GSDME, NLRP3, IL-1ß, and IL-18 decreased after TEC treatment, while the effect of pyroptosis inhibition by TEC was abrogated by Pink1 silencing. We found that the upregulation expression of tRF-3040b caused by MASH was suppressed by TEC. The promotion of mitophagy and the suppression of pyroptosis induced by TEC were abrogated by tRF-3040b mimics. TEC reduced lipid deposition, inflammation, and pyroptosis, and promoted mitophagy in mice, but tRF-3040b agomir inhibited these effects. In summary, our findings provided that TEC significantly reduced the expression of tRF-3040b to enhance mitophagy, thereby inhibiting pyroptosis in MASH. We elucidated a powerful theoretical basis and provided safe and effective potential drugs for MASH with the prevention and treatment.

Cross-ancestry genome-wide association studies of brain imaging phenotypes.

Genome-wide association studies of brain imaging phenotypes are mainly performed in European populations, but other populations are severely under-represented. Here, we conducted Chinese-alone and cross-ancestry genome-wide association studies of 3,414 brain imaging phenotypes in 7,058 Chinese Han and 33,224 white British participants. We identified 38 new associations in Chinese-alone analyses and 486 additional new associations in cross-ancestry meta-analyses at P < 1.46 × 10-11 for discovery and P < 0.05 for replication. We pooled significant autosomal associations identified by single- or cross-ancestry analyses into 6,443 independent associations, which showed uneven distribution in the genome and the phenotype subgroups. We further divided them into 44 associations with different effect sizes and 3,557 associations with similar effect sizes between ancestries. Loci of these associations were shared with 15 brain-related non-imaging traits including cognition and neuropsychiatric disorders. Our results provide a valuable catalog of genetic associations for brain imaging phenotypes in more diverse populations.

Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.

OBJECTIVE: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL). METHODS: The AI system was developed, trained and validated on 5362 images of 551 patients from three hospitals. Automated regions of interest (ROI) segmentation algorithm was utilized to construct image-level features. MIL was used to fusion image level results to patient level features, then the extracted features were modeled by seven machine learning algorithms. Finally, we evaluated the image level and patient level results. Additionally, 50 videos of VFL were prospectively gathered to assess the system's real-time diagnostic capabilities. A human-machine comparison database was also constructed to compare the diagnostic performance of otolaryngologists with and without AI assistance. RESULTS: In internal and external validation sets, the maximum area under the curve (AUC) for image level segmentation models was 0.775 (95 % CI 0.740-0.811) and 0.720 (95 % CI 0.684-0.756), respectively. Utilizing a MIL-based fusion strategy, the AUC at the patient level increased to 0.869 (95 % CI 0.798-0.940) and 0.851 (95 % CI 0.756-0.945). For real-time video diagnosis, the maximum AUC at the patient level reached 0.850 (95 % CI, 0.743-0.957). With AI assistance, the AUC improved from 0.720 (95 % CI 0.682-0.755) to 0.808 (95 % CI 0.775-0.839) for senior otolaryngologists and from 0.647 (95 % CI 0.608-0.686) to 0.807 (95 % CI 0.773-0.837) for junior otolaryngologists. CONCLUSIONS: The MIL based AI-assisted diagnosis system can significantly improve the diagnostic performance of otolaryngologists for VFL and help to make proper clinical decisions.