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Abstract Cancer cells with BRCA1/2 deficiencies are sensitive to poly (ADP-ribose) polymerase (PARP) inhibitors. We evaluated the efficacy of talazoparib in DNA-Damage Repair (DDR)-altered patients. In this phase II trial, patients were enrolled onto one of four cohorts based on molecular alterations: (1) somatic BRCA1/2, (2) other homologous recombination repair pathway, (3) PTEN and (4) germline BRCA1/2. The primary endpoint was a clinical benefit rate (CBR): complete response, partial response or stable disease ≥24 weeks. 79 patients with a median of 4 lines of therapy were enrolled. CBR for cohorts 1–4 were: 32.5%, 19.7%, 9.4% and 30.6%, respectively. PTEN mutations correlated with reduced survival and a trend towards shorter time to progression.Talazoparib demonstrated clinical benefit in selected DDR-altered patients. PTEN mutations/loss patients derived limited clinical benefit. Further study is needed to determine whether PTEN is prognostic or predictive of response to PARP inhibitors.

Summary: The goal of therapeutic cancer vaccines and immune checkpoint therapy (ICT) is to promote T cells with anti-tumor capabilities. Here, we compared mutant neoantigen (neoAg) peptide-based vaccines with ICT in preclinical models. NeoAg vaccines induce the most robust expansion of proliferating and stem-like PD-1+TCF-1+ neoAg-specific CD8 T cells in tumors. Anti-CTLA-4 and/or anti-PD-1 ICT promotes intratumoral TCF-1− neoAg-specific CD8 T cells, although their phenotype depends in part on the specific ICT used. Anti-CTLA-4 also prompts substantial changes to CD4 T cells, including induction of ICOS+Bhlhe40+ T helper 1 (Th1)-like cells. Although neoAg vaccines or ICTs expand iNOS+ macrophages, neoAg vaccines maintain CX3CR1+CD206+ macrophages expressing the TREM2 receptor, unlike ICT, which suppresses them. TREM2 blockade enhances neoAg vaccine efficacy and is associated with fewer CX3CR1+CD206+ macrophages and induction of neoAg-specific CD8 T cells. Our findings highlight different mechanisms underlying neoAg vaccines and different forms of ICT and identify combinatorial therapies to enhance neoAg vaccine efficacy.

Abstract Acute kidney injury (AKI) is the sudden decrease in renal function that can be attributed to dysregulated reactive oxygen species (ROS) production and impaired mitochondrial function. Irisin, a type I membrane protein secreted by skeletal muscles in response to physical activity, has been reported to alleviate kidney damage through regulation of mitochondrial biogenesis and oxidative metabolism. In this study, a macrophage membrane‐coated metal‐organic framework (MCM@MOF) is developed as a nanocarrier for encapsulating irisin to overcome the inherent characteristics of irisin, including a short circulation time, limited kidney‐targeting ability, and low membrane permeability. The engineered irisin‐mediated biomimetic nanotherapeutics have extended circulation time and enhanced targeting capability toward injured kidneys due to the preservation of macrophage membrane proteins. The irisin‐encapsulated biomimetic nanotherapeutics effectively mitigate acute ischemia‐reperfusion injury by protecting mitochondrial function and modulating SOD2 levels in renal tubular epithelial cells. The present study provides novel insights to advance the development of irisin as a potential therapeutic approach for AKI.

Abstract Background Diabetic cardiomyopathy (DCM) is a serious complication in patients with type 1 diabetes mellitus (T1DM), which still lacks adequate therapy. Irisin, a cleavage peptide off fibronectin type III domain-containing 5, has been shown to preserve cardiac function in cardiac ischemia–reperfusion injury. Whether or not irisin plays a cardioprotective role in DCM is not known. Methods and results T1DM was induced by multiple low-dose intraperitoneal injections of streptozotocin (STZ). Our current study showed that irisin expression/level was lower in the heart and serum of mice with STZ-induced TIDM. Irisin supplementation by intraperitoneal injection improved the impaired cardiac function in mice with DCM, which was ascribed to the inhibition of ferroptosis, because the increased ferroptosis, associated with increased cardiac malondialdehyde (MDA), decreased reduced glutathione (GSH) and protein expressions of solute carrier family 7 member 11 (SLC7A11) and glutathione peroxidase 4 (GPX4), was ameliorated by irisin. In the presence of erastin, a ferroptosis inducer, the irisin-mediated protective effects were blocked. Mechanistically, irisin treatment increased Sirtuin 1 (SIRT1) and decreased p53 K382 acetylation, which decreased p53 protein expression by increasing its degradation, consequently upregulated SLC7A11 and GPX4 expressions. Thus, irisin-mediated reduction in p53 decreases ferroptosis and protects cardiomyocytes against injury due to high glucose. Conclusion This study demonstrated that irisin could improve cardiac function by suppressing ferroptosis in T1DM via the SIRT1-p53-SLC7A11/GPX4 pathway. Irisin may be a therapeutic approach in the management of T1DM-induced cardiomyopathy.

Abstract Clustering and visualization are essential parts of single-cell gene expression data analysis. The Euclidean distance used in most distance-based methods is not optimal. The batch effect, i.e., the variability among samples gathered from different times, tissues, and patients, introduces large between-group distance and obscures the true identities of cells. To solve this problem, we introduce Label-Aware Distance (Lad), a metric using temporal/spatial locality of the batch effect to control for such factors. We validate Lad on simulated data as well as apply it to a mouse retina development dataset and a lung dataset. We also found the utility of our approach in understanding the progression of the Coronavirus Disease 2019 (COVID-19). Lad provides better cell embedding than state-of-the-art batch correction methods on longitudinal datasets. It can be used in distance-based clustering and visualization methods to combine the power of multiple samples to help make biological findings.

Summary: Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy (ACT), have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA sequencing (RNA-seq) datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.

Abstract The development of functional textiles combining conventional apparel with advanced technologies for personal health management (PHM) has garnered widespread attention. However, the current PHM textiles often achieve multifunctionality by stacking functional modules, leading to poor durability and scalability. Herein, a scalable and robust PHM textile is designed by integrating electrical, radiative, and solar heating, electromagnetic interference (EMI) shielding, and piezoresistive sensing performance onto cotton fabric. This is achieved through an uncomplicated screen‐printing process using silver paste. The conductivity of the PHM textile is ≈1.6 × 104 S m−1, ensuring an electric heating temperature of ≈134 °C with a low voltage of 1.7 V, as well as an EMI shielding effectiveness of ≈56 dB, and human motion monitoring performance. Surprisingly, the radiative/solar heating capability of the PHM textile surpasses that of traditional warm leather. Even after undergoing rigorous physical and chemical treatments, the PHM textile maintains terrific durability. Additionally, the PHM textile possesses maneuverable scalability and comfortable wearability. This innovative work opens up new avenues for the strategic design of PHM textiles and provides an advantageous guarantee of mass production.

Abstract Host anti-viral factors are essential for controlling SARS-CoV-2 infection but remain largely unknown due to the biases of previous large-scale studies toward pro-viral host factors. To fill in this knowledge gap, we perform a genome-wide CRISPR dropout screen and integrate analyses of the multi-omics data of the CRISPR screen, genome-wide association studies, single-cell RNA-Seq, and host-virus proteins or protein/RNA interactome. This study uncovers many host factors that are currently underappreciated, including the components of V-ATPases, ESCRT, and N-glycosylation pathways that modulate viral entry and/or replication. The cohesin complex is also identified as an anti-viral pathway, suggesting an important role of three-dimensional chromatin organization in mediating host-viral interaction. Furthermore, we discover another anti-viral regulator KLF5, a transcriptional factor involved in sphingolipid metabolism, which is up-regulated, and harbors genetic variations linked to COVID-19 patients with severe symptoms. Anti-viral effects of three identified candidates (DAZAP2/VTA1/KLF5) are confirmed individually. Molecular characterization of DAZAP2/VTA1/KLF5-knockout cells highlights the involvement of genes related to the coagulation system in determining the severity of COVID-19. Together, our results provide further resources for understanding the host anti-viral network during SARS-CoV-2 infection and may help develop new countermeasure strategies.

Abstract Traffic time series anomaly detection has been intensively studied for years because of its potential applications in intelligent transportation. However, classical traffic anomaly detection methods often overlook the evolving dynamic associations between road network nodes, which leads to challenges in capturing the long-term temporal correlations, spatial characteristics, and abnormal node behaviors in datasets with high periodicity and trends, such as morning peak travel periods. In this paper, we propose a mirror temporal graph autoencoder (MTGAE) framework to explore anomalies and capture unseen nodes and the spatiotemporal correlation between nodes in the traffic network. Specifically, we propose the mirror temporal convolutional module to enhance feature extraction capabilities and capture hidden node-to-node features in the traffic network. Morever, we propose the graph convolutional gate recurrent unit cell (GCGRU CELL) module. This module uses Gaussian kernel functions to map data into a high-dimensional space, and enables the identification of anomalous information and potential anomalies within the complex interdependencies of the traffic network, based on prior knowledge and input data. We compared our work with several other advanced deep-learning anomaly detection models. Experimental results on the NYC dataset illustrate that our model works best compared to other models for traffic anomaly detection.

In this study, the pure Al and binary Al–Ni alloys with Ni addition of 1, 3, 6, and 10 wt % were coated via micro arc oxidation (MAO) in a tetraborate and phosphate based electrolyte for 60 min. With increased Ni content, the color of MAO coating became darker due to increased Ni-containing compounds on the surface. The Ni played a negative effect on the coating growth, decreasing both the coating thickness and surface roughness. The coatings on the Al–Ni alloys were mainly composed of γ-Al2O3 and α-Al2O3, and the Ni facilitated the formation of α-Al2O3 in the coating. Nanoparticles of NiO were generated around the edge of discharge channels for Al–6Ni and Al–10Ni alloys after a certain oxidation time. All coatings exhibited a uniform and dense surface structure, with the outer layer being more compact than the inner layer. Many tiny pores were found in the inner layer. Despite the corrosion resistance was decreased, the anti-wear performance of MAO treated samples was improved with the increased Ni content in the matrix. While, the corrosion resistance of the coated samples decreased with the adding of Ni content in the matrix.

Abstract Advances in single-cell technology have enabled molecular dissection of heterogeneous biospecimens at unprecedented scales and resolutions. Cluster-centric approaches are widely applied in analyzing single-cell data, however they have limited power in dissecting and interpreting highly heterogenous, dynamically evolving data. Here, we present GSDensity, a graph-modeling approach that allows users to obtain pathway-centric interpretation and dissection of single-cell and spatial transcriptomics (ST) data without performing clustering. Using pathway gene sets, we show that GSDensity can accurately detect biologically distinct cells and reveal novel cell-pathway associations ignored by existing methods. Moreover, GSDensity, combined with trajectory analysis can identify curated pathways that are active at various stages of mouse brain development. Finally, GSDensity can identify spatially relevant pathways in mouse brains and human tumors including those following high-order organizational patterns in the ST data. Particularly, we create a pan-cancer ST map revealing spatially relevant and recurrently active pathways across six different tumor types.

Recognizing sleep posture is crucial for the monitoring of people with sleeping disorders. Existing contact-based systems might interfere with sleeping, while camera-based systems may raise privacy concerns. In contrast, radar-based sensors offer a promising solution with high penetration ability and the capability to detect vital bio-signals. This study propose a deep learning method for human sleep pose recognition from signals acquired from single-antenna Frequency-Modulated Continuous Wave (FMCW) radar device. To capture both frequency features and sequential features, we introduce ResTCN, an effective architecture combining Residual blocks and Temporal Convolution Network (TCN) to recognize different sleeping postures, from augmented statistical motion features of the radar time series. We rigorously evaluated our method with an experimentally acquired data set which contains sleeping radar sequences from 16 volunteers. We report a classification accuracy of 82.74% on average, which outperforms the state-of-the-art methods.

IntroductionThe starter used in solid-state fermentation (SSF) vinegar, known as seed Pei is a microbial inoculant from the previous batch that is utilized during the acetic acid fermentation stage. The seed Pei, which has a notable impact on vinegar fermentation and flavor, is under-researched with comparative studies on microorganisms.MethodsHerein metagenomics was employed to reveal the microbes and their potential metabolic functions of four seed Pei from three regions in China.ResultsThe predominant microbial taxa in all four starters were bacteria, followed by viruses, eukaryotes, and archaea, with Lactobacillus sp. or Acetobacter sp. as main functional taxa. The seed Pei used in Shanxi aged vinegar (SAV) and Sichuan bran vinegar (SBV) exhibited a higher similarity in microbial composition and distribution of functional genes, while those used in two Zhenjiang aromatic vinegar (ZAV) differed significantly. Redundancy analysis (RDA) of physicochemical factors and microbial communities indicated that moisture content, pH, and reducing sugar content are significant factors influencing microbial distribution. Moreover, seven metagenome-assembled genomes (MAGs) that could potentially represent novel species were identified.ConclusionsThere are distinctions in the microbiome and functional genes among different seed Pei. The vinegar starters were rich in genes related to carbohydrate metabolism. This research provides a new perspective on formulating vinegar fermentation starters and developing commercial fermentation agents for vinegar production.

Abstract Background There are few studies comparing robotic-assisted surgery (RAS) and laparoscopic-assisted surgery (LAS) in Hirschsprung’s disease (HSCR). This study aimed to compare intraoperative and postoperative outcomes between RAS and LAS performed during the same period. Methods All consecutive 75 patients with pathologically diagnosed as HSCR who underwent Swenson pull-through surgery from April 2020 to Nov 2022, were included. Patients were divided into RAS group and LAS group and a retrospective analysis was performed based on clinical indexes and prognosis. Results A total of 75 patients were included, among which, 31 patients received RAS and 44 received LAS. The RAS and LAS groups had similar ages, sex, weight, postoperative hospital stays, and fasting times. Compared with LAS, blood loss (p = 0.002) and the incidence of Hirschsprung-associated enterocolitis (p = 0.046) were significantly lower in the RAS group. The first onset of Hirschsprung-associated enterocolitis in patients younger than 3 months occurred significantly earlier (p = 0.043). Two patients experienced anastomotic leakage in the LAS group and one patient experienced incisional hernia in the RAS group. The cost of RAS was significantly higher than that of LAS (p 3 months) may improve outcomes.

Abstract This study investigates the hypothesis of holistic processing of Chinese formulaic sequences within sentence contexts, examining the performance of both native and non-native speakers. A self-paced masking experiment was conducted to collect response times and gather quantitative sentence context data for subsequent statistical analysis. The findings reveal that both native and non-native participants exhibited shorter response times for formulaic sequences compared to non-formulaic sequences. However, contextual effects were found to only impact the processing of formulaic sequences among non-native learners. The study concludes by emphasizing the importance of contextual effects in L2 teaching and highlighting the theoretical and pedagogical implications of the research on formulaic sequences in L2 usage.

Abstract Flap necrosis, the most prevalent postoperative complication of reconstructive surgery, is significantly associated with ischaemia–reperfusion injury. Recent research indicates that exosomes derived from bone marrow mesenchymal stem cells (BMSCs) hold potential therapeutic applications in several diseases. Traditionally, BMSCs are cultured under normoxic conditions, a setting that diverges from their physiological hypoxic environment in vivo. Consequently, we propose a method involving the hypoxic preconditioning of BMSCs, aimed at exploring the function and the specific mechanisms of their exosomes in ischaemia–reperfusion skin flaps. This study constructed a 3 × 6 cm2 caudal superficial epigastric skin flap model and subjected it to ischaemic conditions for 6 h. Our findings reveal that exosomes from hypoxia-pretreated BMSCs significantly promoted flap survival, decrease MCP-1, IL-1β, and IL-6 levels in ischaemia–reperfusion injured flap, and reduce oxidative stress injury and apoptosis. Moreover, results indicated that Hypo-Exo provides protection to vascular endothelial cells from ischaemia–reperfusion injury both in vivo and in vitro. Through high-throughput sequencing and bioinformatics analysis, we further compared the differential miRNA expression profiles between Hypo-Exo and normoxic exosomes. Results display the enrichment of several pathways, including autophagy and mTOR. We have also elucidated a mechanism wherein Hypo-Exo promotes the survival of ischaemia–reperfusion injured flaps. This mechanism involves carrying large amounts of miR-421-3p, which target and regulate mTOR, thereby upregulating the expression of phosphorylated ULK1 and FUNDC1, and subsequently further activating autophagy. In summary, hypoxic preconditioning constitutes an effective and promising method for optimizing the therapeutic effects of BMSC-derived exosomes in the treatment of flap ischaemia–reperfusion injury.

Abstract Cells often alter metabolic strategies under nutrient-deprived conditions to support their survival and growth. Characterizing metabolic reprogramming in the tumor microenvironment (TME) is of emerging importance in cancer research and patient care. However, recent technologies only measure a subset of metabolites and cannot provide in situ measurements. Computational methods such as flux balance analysis (FBA) have been developed to estimate metabolic flux from bulk RNA-seq data and can potentially be extended to single-cell RNA-seq (scRNA-seq) data. However, it is unclear how reliable current methods are, particularly in TME characterization. Here, we present a computational framework METAFlux (METAbolic Flux balance analysis) to infer metabolic fluxes from bulk or single-cell transcriptomic data. Large-scale experiments using cell-lines, the cancer genome atlas (TCGA), and scRNA-seq data obtained from diverse cancer and immunotherapeutic contexts, including CAR-NK cell therapy, have validated METAFlux’s capability to characterize metabolic heterogeneity and metabolic interaction amongst cell types.

Abstract Acute myeloid leukemia (AML) is a heterogeneous disease characterized by high rate of therapy resistance. Since the cell of origin can impact response to therapy, it is crucial to understand the lineage composition of AML cells at time of therapy resistance. Here we leverage single-cell chromatin accessibility profiling of 22 AML bone marrow aspirates from eight patients at time of therapy resistance and following subsequent therapy to characterize their lineage landscape. Our findings reveal a complex lineage architecture of therapy-resistant AML cells that are primed for stem and progenitor lineages and spanning quiescent, activated and late stem cell/progenitor states. Remarkably, therapy-resistant AML cells are also composed of cells primed for differentiated myeloid, erythroid and even lymphoid lineages. The heterogeneous lineage composition persists following subsequent therapy, with early progenitor-driven features marking unfavorable prognosis in The Cancer Genome Atlas AML cohort. Pseudotime analysis further confirms the vast degree of heterogeneity driven by the dynamic changes in chromatin accessibility. Our findings suggest that therapy-resistant AML cells are characterized not only by stem and progenitor states, but also by a continuum of differentiated cellular lineages. The heterogeneity in lineages likely contributes to their therapy resistance by harboring different degrees of lineage-specific susceptibilities to therapy.

Abstract Genomically-informed therapy requires consideration of the functional impact of genomic alterations on protein expression and/or function. However, a substantial number of variants are of unknown significance (VUS). The MD Anderson Precision Oncology Decision Support (PODS) team developed an actionability classification scheme that categorizes VUS as either “Unknown” or “Potentially” actionable based on their location within functional domains and/or proximity to known oncogenic variants. We then compared PODS VUS actionability classification with results from a functional genomics platform consisting of mutant generation and cell viability assays. 106 (24%) of 438 VUS in 20 actionable genes were classified as oncogenic in functional assays. Variants categorized by PODS as Potentially actionable (N = 204) were more likely to be oncogenic than those categorized as Unknown (N = 230) (37% vs 13%, p = 4.08e-09). Our results demonstrate that rule-based actionability classification of VUS can identify patients more likely to have actionable variants for consideration with genomically-matched therapy.

To improve the cooling heat transfer performance of torpedo combustion chambers, a numerical simulation of the thermal-fluid-solid cooling heat transfer process in a torpedo combustion chamber was performed based on the thermal-fluid-solid coupling numerical calculation method. The flow field distribution was obtained under two types of cooling water channel structures in the combustion chamber, and the cooling heat transfer performance under these different water channel structures was analyzed. The results indicated that, with an increase in the number of the water channels at the bottom of cooling area, the turbulent intensity decreased, and size of the local overheating area reduced. With an increase in the number of outlet water channels at the bottom of the cooling area, the turbulence, vortex, and local overheating area at the outlet gradually disappeared, and the block flow at the bottom of the cooling area caused by water impact also disappeared. Furthermore, the heat transfer efficiency was improved by increasing the number of water channels, with a larger number of water channels at the bottom yielding better improvement in the heat transfer efficiency. Increasing the number of water channels in the combustion chamber raised the cooling heat transfer power about 8.5%, and the maximum temperature of the shell decreased by 11 K. The results of this study can provide a reference for the design and improvement of the cooling structure of torpedo combustion chambers.

Objective To investigate whether GRK4 regulates the phosphorylation and function of renal CCKBR. Methods GRK4 A142V transgenic mice were used as an animal model of enhanced GRK4 activity, and siRNA was used to silence the GRK4 gene to investigate the regulatory effect of GRK4 on CCKBR phosphorylation and function. Finally, the co-localization and co-connection of GRK4 and CCKBR in RPT cells were observed by laser confocal microscopy and immunoprecipitation to explore the mechanism of GRK4 regulating CCKBR. Results Gastrin infusion significantly increased urinary flow and sodium excretion rates in GRK4 WT mice (P

BackgroundThe emergence of the robotic surgery system has assisted the further development of minimally invasive surgery by facilitating more delicate and precise complex procedures. The purpose of this study was to present a study of robot-assisted resection of the choledochal cyst and to discuss the technical points.MethodsIn total, 133 patients who were diagnosed with a choledochal cyst and underwent surgery from April 2020 to February 2022 in the Children's Hospital, Zhejiang University School of Medicine, were retrospectively analyzed. The data were collected including the clinical information of the patients, operative details, and postoperative outcomes.ResultsAmong these 133 patients, 99 underwent robot-assisted surgery and 34 underwent laparoscopic assisted surgery. The median operation time was 180 min, with an interquartile range (IQR) of 170–210 min for the robot-assisted group and 180 min with an IQR of 157.5–220 min in the laparoscopic assisted group (P = 0.290). The detection rate of 82.5% for the distal opening of the cystic type of choledochal cyst was higher in the robot-assisted group than that in the laparoscopic assisted group at 34.8% (P = 0.000). The postoperative hospital stay was shorter (P = 0.009) and the hospitalization expense was higher (P = 0.000) in the robot-assisted group than that of the laparoscopic assisted group. There was no significant difference between the two groups in terms of complications, postoperative indwelling days of the abdominal drainage tube, intraoperative blood loss, and postoperative fasting time (P > 0.05).ConclusionsRobot-assisted resection of choledochal cyst is safe and feasible, it is ideal for the patient requiring a meticulous operation, and its postoperative recovery was shorter than for traditional laparoscopy.

The properties of super-Eddington accretion disks exhibit substantial distinctions from the sub-Eddington ones. In this paper, we investigate the accretion process of a magnetized neutron star (NS) surrounded by a super-Eddington disk. By constructing self-similar solutions for the disk structure, we study in detail an interaction between the NS magnetosphere and the inner region of the disk, revealing that this interaction takes place within a thin boundary layer. The magnetosphere truncation radius is found to be approximately proportional to the Alfvén radius, with a coefficient ranging between 0.34–0.71, influenced by the advection and twisting of a magnetic field, NS rotation, and radiation emitted from an NS accretion column. Under super-Eddington accretion, the NS can readily spin up to become a rapid rotator. The proposed model can be employed to explore the accretion and evolution of NSs in diverse astrophysical contexts, such as ultraluminous X-ray binaries or active galactic nucleus disks.

The disk of an active galactic nucleus (AGN) is widely regarded as a prominent formation channel of binary black hole (BBH) mergers that can be detected through gravitational waves (GWs). Besides, the presence of dense environmental gas offers the potential for an embedded BBH merger to produce electromagnetic (EM) counterparts. In this paper, we investigate EM emission powered by the kicked remnant of a BBH merger occurring within the AGN disk. The remnant BH will launch a jet via the accretion of a magnetized medium as it traverses the disk. The resulting jet will decelerate and dissipate energy into a lateral cocoon as it propagates. We explore three radiation mechanisms of the jet–cocoon system—jet breakout emission, disk cocoon cooling emission, and jet cocoon cooling emission—and find that the jet cocoon cooling emission is likely to be detected in its own frequency bands. We predict a soft X-ray transient, lasting for O (10 ^3 ) s, to serve as an EM counterpart, of which the time delay O (10) days after the GW trigger contributes to follow-up observations. Consequently, BBH mergers in the AGN disk represent a novel multimessenger source. In the future, enhanced precision in measuring and localizing GWs, coupled with diligent searches for such associated EM signals, will effectively validate or restrict the origin of BBH mergers in the AGN disk.

Radar signal has been shown as a promising source for human identification. In daily home sleep-monitoring scenarios, large-scale motion features may not always be practical, and the heart motion or respiration data may not be as ideal as they are in a controlled laboratory setting. Human identification from radar sequences is still a challenging task. Furthermore, there is a need to address the open-set recognition problem for radar sequences, which has not been sufficiently studied. In this paper, we propose a deep learning-based approach for human identification using radar sequences captured during sleep in a daily home-monitoring setup. To enhance robustness, we preprocess the sequences to mitigate environmental interference before employing a deep convolution neural network for human identification. We introduce a Principal Component Space feature representation to detect unknown sequences. Our method is rigorously evaluated using both a public data set and a set of experimentally acquired radar sequences. We report a labeling accuracy of 98.2% and 96.8% on average for the two data sets, respectively, which outperforms the state-of-the-art techniques. Our method excels at accurately distinguishing unknown sequences from labeled ones, with nearly 100% detection of unknown samples and minimal misclassification of labeled samples as unknown.

It is unclear if the molecular profiles of pancreatic ductal adenocarcinoma (PDAC) preclinical models remain stable during propagation. Here, the authors characterise clonal evolution throughout propagation in PDAC cell lines and a patient-derived organoid using single-cell genomics, transcriptomics and epigenomics.

Summary: Extracellular vesicles (EVs) regulate the tumor microenvironment by facilitating transport of biomolecules. Despite extensive investigation, heterogeneity in EV secretion among cancer cells and the mechanisms that support EV secretion are not well characterized. We developed an integrated method to identify individual cells with differences in EV secretion and performed linked single-cell RNA-sequencing on cloned single cells from the metastatic breast cancer cells. Differential gene expression analyses identified a four-gene signature of breast cancer EV secretion: HSP90AA1, HSPH1, EIF5, and DIAPH3. We functionally validated this gene signature by testing it across cell lines with different metastatic potential in vitro. Analysis of the TCGA and METABRIC datasets showed that this signature is associated with poor survival, invasive breast cancer types, and poor CD8+ T cell infiltration in human tumors. We anticipate that our method for directly identifying the molecular determinants of EV secretion will have broad applications across cell types and diseases.

Abstract Integration of single-cell multiomics profiles generated by different single-cell technologies from the same biological sample is still challenging. Previous approaches based on shared features have only provided approximate solutions. Here, we present a novel mathematical solution named bi-order canonical correlation analysis (bi-CCA), which extends the widely used CCA approach to iteratively align the rows and the columns between data matrices. Bi-CCA is generally applicable to combinations of any two single-cell modalities. Validations using co-assayed ground truth data and application to a CAR-NK study and a fetal muscle atlas demonstrate its capability in generating accurate multimodal co-embeddings and discovering cellular identity.

Abstract Diffuse large B-cell lymphoma (DLBCL) is the most common subtype of lymphoma in dogs with a multicentric form. This study aimed to assemble 41 variants of the previously reported genes and to investigate these variants in canine DLBCL using the Agena MassARRAY platform. These variants were chosen based on the high prevalence observed in canine B- and T-cell lymphomas, their significance for target therapy, and compatibility for multiplex PCR amplification. Lymph node biopsy was performed from 60 dogs with B-cell lymphoma comprising 47 purebred and 13 crossbred dogs. All dogs presented single nucleotide polymorphisms (SNPs) at HYAL4 and SATB1 genes. The lesser mutual SNPs were observed at SEL1L, excluding a cocker spaniel, and c-Kit, with the exception of a pug and a French bulldog. Even though no statistical association was noted between each SNP and dog breed, purebreds were 3.88 times more likely to have a SNP at FLT3 rs852342480 (95%CI 0.50–45.03, p = 0.26), 3.64 times at TRAF3 F306X (95%CI 0.58–42.50, p = 0.43) and 2.66 times at TRAF3 E303EX (95%CI 0.56–13.12, p = 0.31). Also, DLBCL dogs (CHOP-based treatment) with c-Kit T425= had a poorer prognosis with shorter median overall survival times (OST) than dogs with the wild type. Dogs treated with COP chemotherapy and contained 3–5 variants at SEL1L were associated with decreased median OST. Therefore, this SNP’s lymphoma panel provides valuable information that we can use to outline a prognosis and develop a treatment plan for the targeted therapy of each dog.

Abstract Cellular heterogeneity underlies cancer evolution and metastasis. Advances in single-cell technologies such as single-cell RNA sequencing and mass cytometry have enabled interrogation of cell type-specific expression profiles and abundance across heterogeneous cancer samples obtained from clinical trials and preclinical studies. However, challenges remain in determining sample sizes needed for ascertaining changes in cell type abundances in a controlled study. To address this statistical challenge, we have developed a new approach, named Sensei, to determine the number of samples and the number of cells that are required to ascertain such changes between two groups of samples in single-cell studies. Sensei expands the t-test and models the cell abundances using a beta-binomial distribution. We evaluate the mathematical accuracy of Sensei and provide practical guidelines on over 20 cell types in over 30 cancer types based on knowledge acquired from the cancer cell atlas (TCGA) and prior single-cell studies. We provide a web application to enable user-friendly study design via https://kchen-lab.github.io/sensei/table_beta.html .

Background B cells play a pivotal role in regulating the immune response. The induction of B cell-mediated immunosuppressive function requires B cell activating signals. However, the mechanisms by which activated B cells mediate T-cell suppression are not fully understood.Methods We investigated the potential contribution of metabolic activity of activated B cells to T-cell suppression by performing in vitro experiments and by analyzing clinical samples using mass cytometry and single-cell RNA sequencing.Results Here we show that following activation, B cells acquire an immunoregulatory phenotype and promote T-cell suppression by metabolic competition. Activated B cells induced hypoxia in T cells in a cell–cell contact dependent manner by consuming more oxygen via an increase in their oxidative phosphorylation (OXPHOS). Moreover, activated B cells deprived T cells of glucose and produced lactic acid through their high glycolytic activity. Activated B cells thus inhibited the mammalian target of rapamycin pathway in T cells, resulting in suppression of T-cell cytokine production and proliferation. Finally, we confirmed the presence of tumor-associated B cells with high glycolytic and OXPHOS activities in patients with melanoma, associated with poor response to immune checkpoint blockade therapy.Conclusions We have revealed for the first time the immunomodulatory effects of the metabolic activity of activated B cells and their possible role in suppressing antitumor T-cell responses. These findings add novel insights into immunometabolism and have important implications for cancer immunotherapy.

BackgroundInsulin resistance is associated with atrial remodeling as well as atrial fibrillation (AF). However, there was limited evidence on the relationship of triglyceride-glucose index (TyG) index, a simple, valuable marker of insulin resistance, with AF. Thus, we aimed to investigate the association between TyG index and AF among hospitalized patients.MethodsA retrospective observational study was conducted in Daping Hospital, which included 356 hospitalized patients from the Department of Cardiology. Clinical and biochemical parameters were collected from electronic medical records and AF was diagnosed from electrocardiogram (ECG) findings.ResultsWe found that the TyG index was significantly higher in the AF group than in the group without AF. Multivariate logistic regression revealed that hypertension (OR = 1.756, 95%CI 1.135-2.717, P = 0.011) and TyG index (OR = 2.092, 95%CI 1.412-3.100, P

To solve the problem that existing methods are difficult to achieve efficient deployment and service protection in deterministic network (DetNet), a DetNet service protection architecture based on SRv6 was proposed.By leveraging this architecture, a service-oriented DetNet protection scheme was designed and the share protection policy was formulated.With the aid of backup bandwidth share, the proposed heuristic based on shortest path optimized network resource utilization and delay.The simulation results show that the share protection algorithm achieves better performance than non-share algorithm.

BackgroundObservational studies have shown inconsistent results of the associations between type 2 diabetes mellitus (T2DM) and blood lipid profiles, while there is also a lack of evidence from randomized controlled trials (RCTs) for the causal effects of T2DM on blood lipid profiles and lipoprotein subclasses.ObjectivesOur study aimed at investigating the causal effects of T2DM on blood lipid profiles and concentration of particle-size-determined lipoprotein subclasses by using the two-sample Mendelian randomization (MR) method.MethodsWe obtained genetic variants for T2DM and blood lipid profiles including high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglycerides (TG), and total cholesterol (TC) from international genome-wide association studies (GWASs). Two-sample MR method was applied to explore the potential causal effects of genetically predicted T2DM on blood lipid profiles based on different databases, respectively, and results from each MR analysis were further meta-analyzed to obtain the summary results. The causal effects of genetically predicted T2DM on the concentration of different subclasses of lipoproteins that are determined by particle size were also involved in MR analysis.ResultsGenetically predicted 1-unit higher log odds of T2DM had a significant causal effect on a higher level of TG (estimated β coefficient: 0.03, 95% confidence interval [CI]: 0.00 to 0.06) and lower level of HDL-C (estimated β coefficient: −0.09, 95% CI: −0.11 to −0.06). The causality of T2DM on the level of TC or LDL-C was not found (estimated β coefficient: −0.01, 95% CI: −0.02 to 0.01 for TC and estimated β coefficient: 0.01, 95% CI: −0.01 to 0.02 for LDL-C). For different sizes of lipoprotein particles, 1-unit higher log odds of T2DM was causally associated with higher level of small LDL particles, and lower level of medium HDL particles, large HDL particles, and very large HDL particles.ConclusionEvidence from our present study showed causal effects of T2DM on the level of TG, HDL-C, and concentration of different particle sizes of lipoprotein subclasses comprehensively, which might be particularly helpful in illustrating dyslipidemia experienced by patients with T2DM, and further indicate new treatment targets for these patients to prevent subsequent excessive cardiovascular events from a genetic point of view.

Understanding and predicting nuclear fuel behavior is the cornerstone for fuel design and optimization, and the safe and economic operation of nuclear reactors. Due to the excellent neutronic economy and safe operational characteristics of lead/lead-bismuth-based liquid metal coolant, lead-cooled fast reactor (LFR) has received much attention and has been regarded as one of the top candidate reactors for Generation IV nuclear power plants. Mixed oxide (MOX) fuel is beneficial to improve fuel cycle utilization and consume weapons-grade plutonium, among which hollow MOX fuel has excellent heat transfer advantages, which can further improve fuel economy and safety, and has good development prospects. In this work, an annular uranium-plutonium mixed oxide (MOX) fuel operating in a liquid lead/lead-bismuth cooled fast reactor is modeled and simulated to predict its behavior under transient and steady-state operation. This model has several modules working in a fully coupled approach based on COMSOL Multiphysics, such as heat transfer, fuel burnup, oxygen redistribution, plutonium redistribution, porosity evolution, fission gas release, JOG growth, and grain size evolution. The modeling results were benchmarked with the existing codes and experimental data, and the results were in satisfactory agreement. The parameters analysis was carried out in this work. Consistent with the solid MOX fuel, the O/M ratio (or deviation from the stoichiometry of oxygen) significantly affects temperature evolution, fission gas migration and release behavior, and plutonium redistribution. Linear power also has a significant influence on fuel performance.

Abstract Sample barcoding is essential in mass cytometry analysis, since it can eliminate potential procedural variations, enhance throughput, and allow simultaneous sample processing and acquisition. Sample pooling after prior surface staining termed live-cell barcoding is more desirable than intracellular barcoding, where samples are pooled after fixation and permeabilization, since it does not depend on fixation-sensitive antigenic epitopes. In live-cell barcoding, the general approach uses two tags per sample out of a pool of antibodies paired with five palladium (Pd) isotopes in order to preserve appreciable signal-to-noise ratios and achieve higher yields after sample deconvolution. The number of samples that can be pooled in an experiment using live-cell barcoding is limited, due to weak signal intensities associated with Pd isotopes and the relatively low number of available tags. Here, we describe a novel barcoding technique utilizing 10 different tags, seven cadmium (Cd) tags and three Pd tags, with superior signal intensities that do not impinge on lanthanide detection, which enables enhanced pooling of samples with multiple experimental conditions and markedly enhances sample throughput.

BackgroundCholedochal cyst perforation is extremely rare, and early diagnosis or prediction is important for the immediate therapeutic intervention of perforations. This study aimed to define the predictor(s) of an impending or complete spontaneous perforation of choledochal cyst and establish the optimal operative timing.MethodsAll 429 consecutive choledochal cyst patients from January 2015 to December 2021, were included. A retrospective study was performed based on Kaplan-Meier analysis, and Cox univariate and multivariate analyses.ResultsA total of 429 patients were included, among which, 21 had choledochal cyst perforations (group A), and 408 did not (group B). Compared to group B, the serum alanine aminotransferase, aspartate aminotransferase, direct bilirubin, gamma-glutamyl transpeptidase, indirect bilirubin, total bilirubin, and alkaline phosphatase were significantly higher in group A (p = 0.025, 0.006, < 0.0001, 0.0001, 0.001, < 0.0001, and 0.033). High serum gamma-glutamyl transpeptidase was negatively associated with perforation-free preoperative survival, and multivariate Cox regression revealed that serum gamma-glutamyl transpeptidase was an independent predictive factor for an impending or complete perforation (p = 0.042).ConclusionsA gamma-glutamyl transpeptidase level ≥ 346.5 U/L accompanied with significantly elevated liver enzymes and bilirubin levels was indicative of the possibility of an impending or complete choledochal cyst perforation, and a proactive surgical approach should be considered.

Background The use of gastric acid suppressants (GASs) has an influence on the exposure of some epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) and therefore may affect the effectiveness and safety of EGFR-TKIs. The impact of GASs, including proton pump inhibitors (PPIs) and histamine type 2 receptor antagonists (H2RAs), on the effectiveness and safety of EGFR-TKIs remains unclear. We conducted a meta-analysis to explore the impact of GASs on the effectiveness and safety of EGFR-TKIs in non–small cell lung cancer (NSCLC) patients.Method We searched the PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, and Wanfang databases thoroughly from inception to 2nd February 2021, including the studies for NSCLC patients who used GASs, offering the adjusted hazard ratio (HR) of effectiveness outcomes such as overall survival (OS) and progression-free survival (PFS) or adjusted odds ratio (OR) of the adverse drug reaction (ADRs), and the results were calculated with a random effect. Two researchers independently screened the literature, extracted data, and evaluated the quality. Stata 15.0 was used for meta-analysis.Result Twelve studies were finally included. Nine of them were cohort studies, and three of them were case–control studies. For effectiveness outcomes, the use of GASs was associated with shorter PFS (HR 1.66 [1.40, 1.98]) and OS (HR 1.50 [1.31, 1.72]), and the use of PPIs was associated with shorter OS (HR 1.56 [1.21, 2.02]), regardless of the overlap time and type of EGFR-TKIs. For safety outcomes, the use of GASs (OR 1.98 [1.19, 3.31]) or PPIs (OR 1.91 [1.17, 3.12]) were both associated with an increased risk of hepatotoxicity.Conclusion The concomitant use of GASs is associated with shorter PFS and OS for NSCLC patients taking EGFR-TKIs and is also associated with a higher risk of hepatotoxicity. The co-administration of GASs should be avoided; if they cannot be avoided, H2RAs is a better choice.Systematic Review Registration: (https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021235018), identifier (PROSPERO 2021 CRD42021235018)

Dysregulated phosphorylation is well-known in cancers, but it has largely been studied in isolation from mutations. Here the authors introduce HotPho, a tool that can discover spatial interactions between phosphosites and mutations, which are associated with activating mutation and genetic dependencies in cancer.

To improve the computational efficiency and classification accuracy in the context of big data, an optimized parallel random forest algorithm is proposed based on the Spark computing framework. First, a new Gini coefficient is defined to reduce the impact of feature redundancy for higher classification accuracy. Next, to reduce the number of candidate split points and Gini coefficient calculations for continuous features, an approximate equal-frequency binning method is proposed to determine the optimal split points efficiently. Finally, based on Apache Spark computing framework, the forest sampling index (FSI) table is defined to speed up the parallel training process of decision trees and reduce data communication overhead. Experimental results show that the proposed algorithm improves the efficiency of constructing random forests while ensuring classification accuracy, and is superior to Spark-MLRF in terms of performance and scalability.

Abstract We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution. The source code of our study is available at https://github.com/KChen-lab/MEDALT .

In the past few years, sparse subspace clustering (SSC) has gained many studies and found wide applications. However, SSC suffers from the limitation in scalability. Furthermore, current SSC methods could hardly tackle stream data where the structure of subspaces may change along time. In this paper, we propose a novel method to extend SSC to stream data (StreamSSC). Our method is based on maintaining a small subset of representatives to characterize the structure of the underlying subspaces during stream data. StreamSSC is efficient in both computation and memory. Experimental results on both synthetic and real-world streams demonstrate the effectiveness of StreamSSC. For efficiency, StreamSSC is faster than existing online subspace clustering methods by roughly a magnitude.

[Abstract]: As disease models are continually advancing, we could realize the “integration of knowledge and action” in pharmacy to prevent and treat diseases more effectively. This can only be done by advocating multi-domain integration. Holistic integrative pharmacy is guided by a holistic view and a new type of theory and practice system that broadens the field of pharmacy research through multidisciplinary approach. Comprehensively understanding the profound connotation of holistic integrative pharmacy and applying it to disease prevention and treatment will help to promote the development of modern pharmacy, reform pharmacy education, and improve people's health.

[Abstract]: Holistic integrative pharmacy is an inevitable trend in the development of in modern pharmacy. This paper attempts to expound the concept of holistic integrative pharmacy and its application in teaching practice. Holistic integrative pharmacy will be used to train interdisciplinary and innovative holistic integrative pharmaceutical professionals to meet the requirements of modern society in terms of creation of new drugs and rational use of drugs, and it will contribute to the Healthy China policy.

Pulmonary ischemia/reperfusion (IR) injury is the leading cause of acute lung injury, which is mainly attributed to reactive oxygen species (ROS) induced cell injuries and apoptosis. Since rosmarinic acid (RA) has been identified as an antioxidant natural ester, this natural compound might protect against pulmonary IR injury. In this study, the mice were given RA daily (50, 75, or 100 mg/kg) by gavage for 7 days before the pulmonary IR injury. We found that hypoxemia, pulmonary edema, and serum inflammation cytokines were aggravated in pulmonary IR injury. RA pretreatment (75 and 100 mg/kg) effectively reversed these parameters, while 50 mg/kg RA pretreatment was less pronounced. Our data also indicated RA pretreatment mitigated the upregulation of pro-oxidant NADPH oxidases (NOX2 and NOX4) and the downregulation of anti-oxidant superoxide dismutases (SOD1 and SOD2) upon IR injury. In vitro studies showed RA preserved the viability of anoxia/reoxygenation (AR)-treated A549 cells (a human lung epithelial cell line), and the results showed the protective effect of RA started at 5 μM concentration, reached its maximum at 15 μM, and gradually decreased at 20–25 μM. Besides, RA pretreatment (15 μM) greatly reduced the lactate dehydrogenase release levels subjected to AR treatment. Moreover, the results of our research revealed that RA eliminated ROS production and reduced alveolar epithelial cell apoptosis through activating the phosphatidylinositol 3 kinase (PI3K)/protein kinase B (Akt) signaling pathway, which was supported by using wortmannin, because in the presence of wortmannin, the RA-mediated protection was blocked. Meanwhile, wortmannin also reversed the protective effects of RA in mice. Together, our results demonstrate the beneficial role of RA in pulmonary IR injury via PI3K/Akt-mediated anti-oxidation and anti-apoptosis, which could be a promising therapeutic intervention for pulmonary IR injury.

Background: In the past 5 years, China has quickly followed US’s steps to approve the new drug application of biologics for dermatological diseases. There is an increasing interest in the current biologic landscape and further potentials in China. Our study aims to analyze features of clinical trials on non-cancer dermatological biologics and synthesize recent achievements and impediments, in order to forecast the development trends in China.Methods: Three registers (the Chinese Clinical Trial Registry, Center for Drug Evaluation, and ClinicalTrials.gov) were searched for clinical trials of non-cancer dermatological biologics initiated between 2016 and 2020 in mainland China. Trial information (the first posted year, sponsor type, study phase and site, recruitment status, disease, drug target, and drug registration type) and certain study design (selection of the control group, primary efficacy outcome, and inclusion of patient-reported outcome for non–phase I or II trials only) information were extracted and analyzed.Results: A total of 60 trials were identified. The number of registered dermatological biologic trials significantly increased with an annual increase of 59% from 2016 to 2020, primarily driven by psoriasis (47/60, 78.3%) and atopic dermatitis (6/60, 10.0%) trials. The tumor necrosis factor (TNF)-α and interleukin (IL)-17 remained the hottest drug targets (17/60, 28.3% for TNF-α and 18/60, 30.0% for IL-17). In addition to TNF-α and IL-17, many new psoriasis drug targets came into place since 2018 (IL-12/23) and 2019 (IL-36 and glucagon-like peptide-1 (GLP-1)). Thirty percent (18/60) of the trials were conducted for biosimilar products, all of which were sponsored by local pharmaceutical companies and 88.9% of which were targeting on TNF-α. Targets of IL-36, IL-5, and IgE were only available in trials sponsored by global companies.Conclusion: There was great progress on the innovation of dermatological biologics in the past 5 years in China in terms of surged number of clinical trials, increased biosimilars and “me-too” drugs which greatly improved patient access to novel treatments, execution of parallel clinical trials, and improved hospital GCP office and regulatory environment. Further efforts for local pharmaceutical companies should include relocating resources to exploring novel drug targets and dermatological diseases other than psoriasis or atopic dermatitis.Systematic Review Registration: [website], identifier [registration number].

SARS-CoV-2 vaccines pose as the most effective approach for mitigating the COVID-19 pandemic. High-degree efficacy of SARS-CoV-2 vaccines in clinical trials indicates that vaccination invariably induces an adaptive immune response. However, the emergence of breakthrough infections in vaccinated individuals suggests that the breadth and magnitude of vaccine-induced adaptive immune response may vary. We assessed vaccine-induced SARS-CoV-2 T cell response in 21 vaccinated individuals and found that SARS-CoV-2–specific T cells, which were mainly CD4+ T cells, were invariably detected in all individuals but the response was varied. We then investigated differentiation states and cytokine profiles to identify immune features associated with superior recall function and longevity. We identified SARS-CoV-2–specific CD4+ T cells were polyfunctional and produced high levels of IL-2, which could be associated with superior longevity. Based on the breadth and magnitude of vaccine-induced SARS-CoV-2 response, we identified 2 distinct response groups: individuals with high abundance versus low abundance of SARS-CoV-2–specific T cells. The fractions of TNF-α– and IL-2–producing SARS-CoV-2 T cells were the main determinants distinguishing high versus low responders. Last, we identified that the majority of vaccine-induced SARS-CoV-2 T cells were reactive against non-mutated regions of mutant S-protein, suggesting that vaccine-induced SARS-CoV-2 T cells could provide continued protection against emerging variants of concern.

BackgroundObservational studies have shown an association between early age at menarche (AAM) and myocardial infarction (MI) with recorded cases. In this Mendelian randomization (MR) study, we used large amounts of summary data from genome-wide association studies (GWASs) to further estimate the association of genetically predicted AAM with genetically predicated risk of MI and investigate to what extent this association is mediated by genetically determined lifestyles, cardiometabolic factors, and estrogen exposure.MethodsA two-step, two-sample MR study was performed by mediation analysis. Genetic variants identified by GWAS meta-analysis of reproductive genetics consortium (n = 182,416) were selected for genetically predicted AAM. Genetic variants identified by the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis plus The Coronary Artery Disease Genetics Consortium (n = 184,305) were selected for genetically predicted risk of MI. Genetic variants from other international GWAS summary data were selected for genetically determined mediators.ResultsThis MR study showed that increase in genetically predicted AAM was associated with lower risk of genetically predicted MI (odds ratio 0.91, 95% confidence interval 0.84–0.98). Inverse variance weighted (IVW) MR analysis also showed that decrease in genetically predicted AAM was associated with higher genetically predicted alcohol intake frequency, current smoking behavior, higher waist-to-hip ratio, and higher levels of systolic blood pressure (SBP), fasting blood glucose, hemoglobin A1c (HbA1c), and triglycerides (TGs). Furthermore, increase in genetically predicted AAM was associated with genetically predicted longer sleep duration, higher levels of high-density lipoproteins, and older age at which hormone replacement therapy was started. The most essential mediators identified were genetically predicted current smoking behavior and levels of HbA1c, SBP, and TGs, which were estimated to genetically mediate 13.9, 12.2, 10.5, and 9.2%, respectively, with a combined mediation proportion of 37.5% in the association of genetically predicted AAM with genetically predicted increased risk of MI in an MR framework.ConclusionOur MR analysis showed that increase in genetically predicted AAM was associated with lower genetically predicted risk of MI, which was substantially mediated by genetically determined current smoking behavior and levels of HbA1c, SBP, and TGs. Intervening on the above mediators may reduce the risk of MI.