Microdroplet-enhanced chip platform for high-throughput immunotherapy marker screening from extracellular vesicle RNAs and membrane proteins.

Extracellular vesicles (EVs) are considered as promising candidates for predicting patients who respond to immunotherapy. Nevertheless, simultaneous detection of multiple EVs markers still presents significant technical challenges. In this work, we developed a high-throughput microdroplet-enhanced chip (MEC) platform, which utilizes thousands of individual microchambers (∼pL) as reactors, accelerating the detection efficiency of the CRISPR/Cas systems and increasing the sensitivity by up to 100-fold (aM level). Ten biomarkers (including 5 RNAs and 5 proteins) from patients' EVs are successfully detected on one chip, and the comprehensive markers show increased accuracy (AUC 0.911) than the individual marker for the efficacy prediction of immunotherapy. This platform provides a high-throughput yet sensitive strategy for screening immunotherapy markers in clinical.

Light/Force-Responsive Room Temperature Phosphorescence in a Zinc-Organic Coordination Polymer.

A zinc-organic hybrid (1) with multifunctional room temperature phosphorescence (RTP) was synthesized. 1 presents light/force-sensitive RTP properties due to the photochromic behavior from gray to light yellow and the transition from crystalline to amorphous state, respectively. Furthermore, inkless printing and information encryption models were successfully constructed to prove their widespread application prospect.

Rapid cycling and emission of volatile sulfur compounds in the eastern Indian Ocean: Impact of runoff inputs and implications for balancing atmospheric carbonyl sulfide budget.

Volatile sulfur compounds, such as dimethyl sulfide (DMS), carbonyl sulfide (OCS), and carbon disulfide (CS2), significantly influence atmospheric chemistry and climate change. Despite the oceans being an important source of these sulfides, the limited understanding of their biogeochemical cycles in seawater introduces considerable uncertainties in quantifying their oceanic emissions and assessing atmospheric OCS budgets. To address this issue, we conducted a comprehensive field survey in the tropical eastern Indian Ocean (EIO) to examine the spatial distributions, source-sink dynamics, and sea-air exchange fluxes of marine DMS, OCS, and CS2. Our study indicates that nutrients, organic matter, and freshwater input from terrestrial runoff significantly affect most of the source-sink processes of these sulfides in the Bay of Bengal and even the tropical EIO. The resulting sulfide accumulation in seawater combined with high wind speeds establishes the tropical EIO as a considerable direct and indirect atmospheric OCS source. These insights underscore the potentially critical role of marine environments influenced by runoff in contributing to the atmospheric OCS budget. However, by integrating these results with previous field surveys, we believe that actual OCS emissions from tropical oceans exceed some bottom-up box-model simulations, yet fall significantly below those predicted by top-down models, still insufficient to bridge the atmospheric OCS source gap. Our detailed examination of source-sink dynamics offers deeper insights into the marine sulfur cycle and has potential implications for refining future box-models, thus mitigating uncertainties in estimating marine sulfur emissions.

Complete genome sequence of the 4-hydroxybenzoate-degrading bacterium Gymnodinialimonas sp. 57CJ19, a potential novel species from intertidal sediments.

A bacterium Gymnodinialimonas sp. 57CJ19, was isolated from the intertidal sediments of Aoshan Bay, and further assays showed that it has the ability to degrade the antibacterial preservative 4-hydroxybenzoate. The complete genome sequence was sequenced, and phylogenomic analyses indicated that strain 57CJ19 represents a potential novel species in the genus Gymnodinialimonas (family Rhodobacteraceae). Its genome contains a 3,861,607-bp circular chromosome with 61.25% G + C content. Gene prediction revealed 3716 protein-encoding genes, 41 tRNA genes, 3 rrn operons, and 3 non-coding RNA genes. Functional annotation revealed a complete metabolic pathway for 4-hydroxybenzoate. The genome sequence of strain 57CJ19 provides new insights into the potential and underlying genomic basis of aromatic compound pollutant degradation by marine bacteria.

Comparison of the Long-term Survival Outcome of Surgery versus Stereotactic Body Radiation Therapy as Initial Local Treatment for Pulmonary Oligometastases from Colorectal Cancer: A Propensity Score Analysis.

PURPOSE: Optimal local treatment for pulmonary oligometastases from colorectal cancer (CRC) remains unclear. We aimed to compare the long-term survival outcomes between surgery and stereotactic body radiation therapy (SBRT) as the initial local treatment for CRC pulmonary oligometastases. MATERIALS AND METHODS: We retrospectively reviewed 335 consecutive patients who initially underwent surgery or SBRT for CRC pulmonary metastases from 2011 to 2022, and 251 patients (173 surgery and 78 SBRT) were ultimately included. Freedom from intrathoracic progression (FFIP), progression-free survival (PFS), and overall survival (OS) were compared using stabilized inverse probability of treatment weighting (sIPTW) analysis. In addition, patterns of intrathoracic progression and subsequent treatment were analyzed. RESULTS: Median follow-up was 61.6 months for surgery and 54.4 months for SBRT. After sIPTW adjustment, significant differences emerged in both FFIP and PFS between surgery and SBRT (FFIP: hazard ratio [HR] = 0.50, 95% confidence interval [CI], 0.31-0.79; PFS: HR = 0.56, 95% CI, 0.36-0.87). The 3- and 5-year FFIP rates were 58.6% and 54.8%, respectively, after surgery, and 34.6% and 31.3%, respectively, after SBRT (P = .006). The 3- and 5-year PFS rates were 49.4% and 45.2%, respectively, after surgery, and 28.8% and 26.1%, respectively, after SBRT (P = .010). However, OS was not significantly affected by treatment approach (HR = 0.93, 95% CI, 0.49-1.76). The 3- and 5-year OS rates were 85.9% and 73.1%, respectively, after surgery, and 78.9% and 68.7%, respectively, after SBRT (P = .849). Recurrence at the treated site was more prevalent after SBRT than after surgery (33.3% vs 16.9%), whereas new intrathoracic tumors occurred more frequently after surgery than after SBRT (71.8% vs 43.1%). Both groups chose radiation therapy as the primary local salvage treatment. CONCLUSIONS: Notwithstanding the significant differences in FFIP and PFS between surgery and SBRT, the long-term survival of patients with CRC pulmonary oligometastases did not depend on the initial choice of the local treatment approach.

Discovery of quaternized pyridine-thiazole-ruthenium complexes as potent anti-Staphylococcus aureus agents.

Quaternization of ruthenium complexes may be a promising strategy for the development of new antibiotics. In response to the increasing bacterial resistance, we integrated the quaternary amine structure into the design of ruthenium complexes and evaluated their antibacterial activity. All the ruthenium complexes showed good antibacterial activity against the tested Staphylococcus aureus (S. aureus). Ru-8 was the most effective antibacterial agent that displayed excellent antibacterial activity against S. aureus (MIC = 0.78-1.56 µg/mL). In vitro experiments showed that all nine ruthenium complexes had low hemolytic toxicity to rabbit erythrocytes. Notably, Ru-8 was found to disrupt bacterial cell membranes, alter their permeability, and induce ROS production in bacteria, all the above leading to the death of bacteria without inducing drug resistance. To further explore the antibacterial activity of Ru-8in vivo, we established a mouse skin wound infection model and a G. mellonella larvae infection model. Ru-8 exhibited significant antibacterial efficacy against S. aureus in vivo and low toxicity to mouse tissues. The Ru-8 showed low toxicity to Raw264.7 cells (mouse monocyte macrophage leukemia cells). This study indicates that the ruthenium complex ruthenium quaternary was a promising strategy for the development of new antibacterial agents.

Mitochondrial DNA Genomes Reveal Relaxed Purifying Selection During Human Population Expansion after the Last Glacial Maximum.

Modern humans have experienced explosive population growth in the past thousand years. We hypothesized that recent human populations have inhabited environments with relaxation of selective constraints, possibly due to the more abundant food supply after the Last Glacial Maximum. The ratio of nonsynonymous to synonymous mutations (N/S ratio) is a useful and common statistic for measuring selective constraints. In this study, we reconstructed a high-resolution phylogenetic tree using a total of 26,419 East Eurasian mitochondrial DNA genomes, which were further classified into expansion and nonexpansion groups on the basis of the frequencies of their founder lineages. We observed a much higher N/S ratio in the expansion group, especially for nonsynonymous mutations with moderately deleterious effects, indicating a weaker effect of purifying selection in the expanded clades. However, this observation on N/S ratio was unlikely in computer simulations where all individuals were under the same selective constraints. Thus, we argue that the expanded populations were subjected to weaker selective constraints than the nonexpanded populations were. The mildly deleterious mutations were retained during population expansion, which could have a profound impact on present-day disease patterns.

Physiological, Metabolome and Gene Expression Analyses Reveal the Accumulation and Biosynthesis Pathways of Soluble Sugars and Amino Acids in Sweet Sorghum under Osmotic Stresses.

Water scarcity is a major environmental constraint on plant growth in arid regions. Soluble sugars and amino acids are essential osmolytes for plants to cope with osmotic stresses. Sweet sorghum is an important bioenergy crop and forage with strong adaptabilities to adverse environments; however, the accumulation pattern and biosynthesis basis of soluble sugars and amino acids in this species under osmotic stresses remain elusive. Here, we investigated the physiological responses of a sweet sorghum cultivar to PEG-induced osmotic stresses, analyzed differentially accumulated soluble sugars and amino acids after 20% PEG treatment using metabolome profiling, and identified key genes involved in the biosynthesis pathways of soluble sugars and amino acids using transcriptome sequencing. The results showed that the growth and photosynthesis of sweet sorghum seedlings were significantly inhibited by more than 20% PEG. After PEG treatments, the leaf osmotic adjustment ability was strengthened, while the contents of major inorganic osmolytes, including K+ and NO3-, remained stable. After 20% PEG treatment, a total of 119 and 188 differentially accumulated metabolites were identified in the stems and leaves, respectively, and the accumulations of soluble sugars such as raffinose, trehalose, glucose, sucrose, and melibiose, as well as amino acids such as proline, leucine, valine, serine, and arginine were significantly increased, suggesting that these metabolites should play key roles in osmotic adjustment of sweet sorghum. The transcriptome sequencing identified 1711 and 4978 DEGs in the stems, as well as 2061 and 6596 DEGs in the leaves after 20% PEG treatment for 6 and 48 h, respectively, among which the expressions of genes involved in biosynthesis pathways of sucrose (such as SUS1, SUS2, etc.), trehalose (including TPS6), raffinose (such as RAFS2 and GOLS2, etc.), proline (such as P5CS2 and P5CR), leucine and valine (including BCAT2), and arginine (such as ASS and ASL) were significantly upregulated. These genes should be responsible for the large accumulation of soluble sugars and amino acids under osmotic stresses. This study deepens our understanding of the important roles of individual soluble sugars and amino acids in the adaptation of sweet sorghum to water scarcity.

Comparative Physiological and Gene Expression Analyses Reveal Mechanisms Involved in Maintaining Photosynthesis Capacity, Alleviating Ion Toxicity and Oxidative Stress of Kentucky Bluegrass under NaCl Treatment.

Kentucky bluegrass (Poa pratensis L.), a widely used cool-season turfgrass, shows a high sensitivity to soil salinity. Clarifying the adaptative mechanisms of Kentucky bluegrass that serve to improve its salt tolerance in saline environments is urgent for the application of this turfgrass in salt-affected regions. In this study, physiological responses of the Kentucky bluegrass cultivars "Explorer" and "Blue Best" to NaCl treatment, as well as gene expressions related to photosynthesis, ion transport, and ROS degradation, were analyzed. The results showed that the growth of "Explorer" was obviously better compared to "Blue Best" under 400 mM NaCl treatment. "Explorer" exhibited a much stronger photosynthetic capacity than "Blue Best" under NaCl treatment, and the expression of key genes involved in chlorophyll biosynthesis, photosystem II, and the Calvin cycle in "Explorer" was greatly induced by salt treatment. Compared with "Blue Best", "Explorer" could effectively maintain Na+/K+ homeostasis in its leaves under NaCl treatment, which can be attributed to upregulated expression of genes, such as HKT1;5, HAK5, and SKOR. The relative membrane permeability and contents of O2- and H2O2 in "Explorer" were significantly lower than those in "Blue Best" under NaCl treatment, and, correspondingly, the activities of SOD and POD in the former were significantly higher than in the latter. Moreover, the expression of genes involved in the biosynthesis of enzymes in the ROS-scavenging system of "Explorer" was immediately upregulated after NaCl treatment. Additionally, free proline and betaine are important organic osmolytes for maintaining hydration status in Kentucky bluegrass under NaCl treatment, as the contents of these metabolites in "Explorer" were significantly higher than in "Blue Best". This work lays a theoretical basis for the improvement of salt tolerance in Kentucky bluegrass.

Compressive Failure Characteristics of 3D Four-Directional Braided Composites with Prefabricated Holes.

The low delamination tendency and high damage tolerance of three-dimensional (3D) braided composites highlight their significant potential in handling defects. To enhance the engineering potential of three-dimensional four-directional (3D4d) braided composites and assess the failure mode of hole defects, this study introduces a series of 3D4d braided composites with prefabricated holes, studying their compressive properties and failure mechanisms through experimental and finite element methods. Digital image correlation (DIC) was used to monitor the compressive strain on the surface of materials. Scanning acoustic microscope (SAM) and scanning electron microscopy (SEM) were used to characterize the longitudinal compression failure mode inside the material. A macroscopic model is established, and the porous materials are predicted by using the general braided composite material prediction theory. While reducing the forecast cost, the error is also controlled within 21%. The analysis of failure mechanisms elucidates the damage extension mode, and the porous damage tolerance ability aligns closely with the bearing mode of braided material structure. Different braiding angles will lead to different bearing modes of materials. Under longitudinal compression, the average strength loss of 15° specimens is 38.21%, and that of 30° specimens is 8.1%. The larger the braided angle, the stronger the porous damage tolerance. Different types of prefabricated holes will also affect their mechanical properties and damage tolerance.

[Spatiotemporal Distributions and Variations in Summertime Ozone Photochemical Production Regimes over Shanxi].

Satellite-based formaldehyde（HCHO）columns and tropospheric nitrogen dioxide columns were observed using the Ozone Monitoring Instrument（OMI），and groundbased observations of ozone（O3）for May-August from 2013 to 2022 were connected to calculate the threshold values of the HCHO to NO2 ratio（FNR）in Shanxi Province. Then，the spatiotemporal distributions and variations in summertime ozone photochemical production regimes were analyzed. The results showed that：① The volatile organic compound（VOC） -sensitive regime area（FNR < 2.3）was obviously reduced，while the VOCs-NOx transitional regime（FNR between 2.3-4.1）area increased in the early years and then decreased， and NO x -sensitive regime area expanded significantly in summer from 2013 to 2022 over Shanxi Province. ② The increased summertime FNR during 2013 to 2019 was associated with the co-effect of increased HCHO columns and decreased tropospheric NO2 columns. The Shanxi Province was generally under an NOx regime since 2016，which reflected the remarkable effect of NO x emission reductions；however，there was a shift from a VOC-sensitive regime to a VOCs-NOx transitional regime，in which O3 pollution aggravation was widespread under the background of decreased NOx emissions. The decrease in O3 concentration during 2020 to 2022 followed the synergistical declines in HCHO columns and tropospheric NO2 columns. ③ The O3 weekend effects were reversed in Linfen and Yuncheng but were persistent in the other nine cities. Satellite-based weekend HCHO and NO2 levels were higher than those on weekdays in some cities of Shanxi Province，indicating that the O3 weekend effect was not only dependent on the changes of precursors emissions but was also closely related to O3 photochemical production sensitivity. The results indicated the necessity of simultaneous controls in NOx emissions and VOCs emissions for ozone abatement plans over Shanxi Province. In addition，Taiyuan，Yangquan，Yuncheng，and Jincheng should continue to promote reduction in NOx emissions.

NCAPD2 augments the tumorigenesis and progression of human liver cancer via the PI3K­Akt­mTOR signaling pathway.

Non­SMC condensin I complex subunit D2 (NCAPD2) is a newly identified oncogene; however, the specific biological function and molecular mechanism of NCAPD2 in liver cancer progression remain unknown. In the present study, the aberrant expression of NCAPD2 in liver cancer was investigated using public tumor databases, including TNMplot, The Cancer Genome Atlas and the International Cancer Genome Consortium based on bioinformatics analyses, and it was validated using a clinical cohort. It was revealed that NCAPD2 was significantly upregulated in liver cancer tissues compared with in control liver tissues, and NCAPD2 served as an independent prognostic factor and predicted poor prognosis in liver cancer. In addition, the expression of NCAPD2 was positively correlated with the percentage of Ki67+ cells. Finally, single­cell sequencing data, gene­set enrichment analyses and in vitro investigations, including cell proliferation assay, Transwell assay, wound healing assay, cell cycle experiments, cell apoptosis assay and western blotting, were carried out in human liver cancer cell lines to assess the biological mechanisms of NCAPD2 in patients with liver cancer. The results revealed that the upregulation of NCAPD2 enhanced tumor cell proliferation, invasion and cell cycle progression at the G2/M­phase transition, and inhibited apoptosis in liver cancer cells. Furthermore, NCAPD2 overexpression was closely associated with the phosphatidylinositol 3­kinase (PI3K)­Akt­mammalian target of rapamycin (mTOR)/c­Myc signaling pathway and epithelial­mesenchymal transition (EMT) progression in HepG2 and Huh7 cells. In addition, upregulated NCAPD2 was shown to have adverse effects on overall survival and disease­specific survival in liver cancer. In conclusion, the overexpression of NCAPD2 was shown to lead to cell cycle progression at the G2/M­phase transition, activation of the PI3K­Akt­mTOR/c­Myc signaling pathway and EMT progression in human liver cancer cells.

[Transport Characteristics and Potential Source Areas of PM2.5 in Yangquan City Under Different Pollution Levels].

Based on the PM2.5 monitoring data, NCEP data, and the meteorological data of the weather situation analysis at the corresponding time in Yangquan City from 2020 to 2022, using the HYSPLIT4 backward trajectory model, multi-station potential source contribution factor analysis （MS-PSCF） and trajectory density analysis （TDA） were introduced to study the differentiation and classification of PM2.5 transport channels and potential sources in Yangquan City. The results showed that： ① The PM2.5 pollution in Yangquan was mainly concentrated in Yangquan and Pingding, whereas the pollution in Yuxian was relatively light. The proportion of days with different pollution levels and the average and maximum values of PM2.5 concentration in Yangquan and Pingding were significantly higher than those in Yuxian, and the distribution characteristics of PM2.5 were closely related to the local special terrain. ② The amount of PM2.5 pollution and the concentration of PM2.5 in different pollution levels were the highest in light wind weather. The influence of east-west regional transport on PM2.5 pollution times and PM2.5 concentration of Yangquan and Pingding was obvious, and the contribution of east wind was significant. The influence of local pollution sources was the main factor in the moderate pollution weather in Yuxian County. ③ There were four main ground conditions for the generation and maintenance of moderate or above pollution weather： warm low pressure type （22%）, high pressure front （bottom） type （54%）, high pressure back type （14%）, and pressure equalization field （10%）. High pressure front （bottom） type was the main ground situation causing the increase in PM2.5 concentration. There were two types of upper air conditions, namely, flat westerly flow type （78%） and northwest flow type （22%）. The upper westerly flow type was the main upper air condition that caused the increase in PM2.5 concentration. ④ The results of transport channels and potential source areas of PM2.5 with different pollution levels obtained by MS-PSCF and TDA were consistent. The main transport channels of PM2.5 were the northeast, southeast, and northwest channels, whereas the northeast and southeast channels were short-distance transport routes, which were the main routes causing the increase in PM2.5 concentration. The northwest channel was consistent with the northwest dust transport channel, belonging to long-distance transmission. The main potential source areas of PM2.5 pollution were located in the central and western parts of Hebei and the southeast part of Hebei, the northeast part of Henan and its junction with the southwest part of Shandong, and the southeast part of Shanxi.

Comprehensive investigation in oncogenic functions and immunological roles of NCBP2 and its validation in prostate cancer.

BACKGROUND: Nuclear cap-binding protein 2 (NCBP2), as the component of the cap-binding complex, participates in a number of biological processes, including pre-mRNA splicing, transcript export, translation regulation and other gene expression steps. However, the role of NCBP2 on the tumor cells and immune microenvironment remains unclear. To systematically analyze and validate functions of NCBP2, we performed a pan-cancer analysis using multiple approaches. METHODS: The data in this study were derived from sequencing, mutation, and methylation data in the TCGA cohort, normal sample sequencing data in the GTEx project, and cell line expression profile data in the CCLE database. RESULTS: Survival analyses including the Cox proportional-hazards model and log-rank test revealed the poor prognostic role of NCBP2 in multiple tumors. We further validated the oncogenic ability of NCBP2 in prostate cancer cell lines, organoids and tumor-bearing mice. A negative correlation was observed between NCBP2 expression and immune score by the ESTIMATE algorithm. Simultaneously, the NCBP2-induced immunosuppressive microenvironment might be related to the decline in CD8+T cells and the increase in regulatory T cells and neutrophils, examined by flow cytometry experiments for NCBP2 overexpressed tumor-bearing mice. CONCLUSION: This research offered strong proof supporting NCBP2 as the prognostic marker and the therapeutic target in the future.

Genome-Scale Multimodal Analysis of Cell-Free DNA Whole-Methylome Sequencing for Noninvasive Esophageal Cancer Detection.

PURPOSE: Simultaneous profiling of cell-free DNA (cfDNA) methylation and fragmentation features to improve the performance of cfDNA-based cancer detection is technically challenging. We developed a method to comprehensively analyze multimodal cfDNA genomic features for more sensitive esophageal squamous cell carcinoma (ESCC) detection. MATERIALS AND METHODS: Enzymatic conversion-mediated whole-methylome sequencing was applied to plasma cfDNA samples extracted from 168 patients with ESCC and 251 noncancer controls. ESCC characteristic cfDNA methylation, fragmentation, and copy number signatures were analyzed both across the genome and at accessible cis-regulatory DNA elements. To distinguish ESCC from noncancer samples, a first-layer classifier was developed for each feature type, the prediction results of which were incorporated to construct the second-layer ensemble model. RESULTS: ESCC plasma genome displayed global hypomethylation, altered fragmentation size, and chromosomal copy number alteration. Methylation and fragmentation changes at cancer tissue-specific accessible cis-regulatory DNA elements were also observed in ESCC plasma. By integrating multimodal genomic features for ESCC detection, the ensemble model showed improved performance over individual modalities. In the training cohort with a specificity of 99.2%, the detection sensitivity was 81.0% for all stages and 70.0% for stage 0-II. Consistent performance was observed in the test cohort with a specificity of 98.4%, an all-stage sensitivity of 79.8%, and a stage 0-II sensitivity of 69.0%. The performance of the classifier was associated with the disease stage, irrespective of clinical covariates. CONCLUSION: This study comprehensively profiles the epigenomic landscape of ESCC plasma and provides a novel noninvasive and sensitive ESCC detection approach with genome-scale multimodal analysis.

Ferroptosis-Related Gene Signatures in Epilepsy: Diagnostic and Immune Insights.

Epilepsy is characterized by a multifaceted aetiology. Ferroptosis has recently been implicated in seizure pathophysiology, although its mechanistic role in epilepsy remains obscure. We examined the roles of ferroptosis-related genes (FRGs) in epilepsy cohorts from the GSE143272 dataset. We investigated the associations between gene expression and the immune response by performing CIBERSORT and MCP-counter analyses. By employing unsupervised consensus clustering and weighted gene coexpression network analysis (WGCNA), we delineated robust gene clusters across cohorts. Single-cell RNA sequencing data from the GSE201048 dataset provided insights into the interactions between pivotal ferroptosis-related genes and immune cells. Additionally, we employed qRT‒PCR technology to measure the levels of these central genes in the tissues of epileptic patients and mice. Our findings revealed seven pivotal genes (TFRC, POR, PTGS2, RELA, PGD, TRIM21, and QSOX1) at the forefront in epilepsy specimens. A diagnostic model harnessing these genes exhibited substantial efficacy (AUC = 0.913). Similarly, the qRT‒PCR analysis of samples from epileptic patients and mouse epileptic brain tissues substantiated these findings. Stratification of 91 patients with epilepsy via WGCNA, based on gene expression, revealed distinct immunological profiles. The scRNA-seq data further indicated increased expression of central genes in macrophages and microglia. Notably, these cells and those with elevated ferroptosis scores were significantly enriched in inflammation-related pathways. These findings support the strong involvement of FRGs in the pathogenesis of epilepsy, particularly neuroinflammation. These central genes hold promise as novel diagnostic biomarkers for epilepsy.

Revealing static and dynamic biomarkers from postprandial metabolomics data through coupled matrix and tensor factorizations.

INTRODUCTION: Longitudinal metabolomics data from a meal challenge test contains both fasting and dynamic signals, that may be related to metabolic health and diseases. Recent work has explored the multiway structure of time-resolved metabolomics data by arranging it as a three-way array with modes: subjects, metabolites, and time. The analysis of such dynamic data (where the fasting data is subtracted from postprandial states) reveals dynamic markers of various phenotypes, and differences between fasting and dynamic states. However, there is still limited success in terms of extracting static and dynamic biomarkers for the same subject stratifications. OBJECTIVES: Through joint analysis of fasting and dynamic metabolomics data, our goal is to capture static and dynamic biomarkers of a phenotype for the same subject stratifications providing a complete picture, that will be more effective for precision health. METHODS: We jointly analyze fasting and dynamic metabolomics data collected during a meal challenge test from the COPSAC 2000 cohort using coupled matrix and tensor factorizations (CMTF), where the dynamic data (subjects by metabolites by time) is coupled with the fasting data (subjects by metabolites) in the subjects mode. RESULTS: The proposed data fusion approach extracts shared subject stratifications in terms of BMI (body mass index) from fasting and dynamic signals as well as the static and dynamic metabolic biomarker patterns corresponding to those stratifications. Specifically, we observe a subject stratification showing the positive association with all fasting VLDLs and higher BMI. For the same subject stratification, a subset of dynamic VLDLs (mainly the smaller sizes) correlates negatively with higher BMI. Higher correlations of the subject quantifications with the phenotype of interest are observed using such a data fusion approach compared to individual analyses of the fasting and postprandial state. CONCLUSION: The CMTF-based approach provides a complete picture of static and dynamic biomarkers for the same subject stratifications-when markers are present in both fasting and dynamic states.

CB2 stimulation of adipose resident ILC2s orchestrates immune balance and ameliorates type 2 diabetes mellitus.

Development of type 2 diabetes mellitus (T2DM) is associated with low-grade chronic type 2 inflammation and disturbance of glucose homeostasis. Group 2 innate lymphoid cells (ILC2s) play a critical role in maintaining adipose homeostasis via the production of type 2 cytokines. Here, we demonstrate that CB2, a G-protein-coupled receptor (GPCR) and member of the endocannabinoid system, is expressed on both visceral adipose tissue (VAT)-derived murine and human ILC2s. Moreover, we utilize a combination of ex vivo and in vivo approaches to explore the functional and therapeutic impacts of CB2 engagement on VAT ILC2s in a T2DM model. Our results show that CB2 stimulation of ILC2s protects against insulin-resistance onset, ameliorates glucose tolerance, and reverses established insulin resistance. Our mechanistic studies reveal that the therapeutic effects of CB2 are mediated through activation of the AKT, ERK1/2, and CREB pathways on ILC2s. The results reveal that the CB2 agonist can serve as a candidate for the prevention and treatment of T2DM.

Deep learning classification of pediatric spinal radiographs for use in large scale imaging registries.

PURPOSE: The purpose of this study is to develop and apply an algorithm that automatically classifies spine radiographs of pediatric scoliosis patients. METHODS: Anterior-posterior (AP) and lateral spine radiographs were extracted from the institutional picture archive for patients with scoliosis. Overall, there were 7777 AP images and 5621 lateral images. Radiographs were manually classified into ten categories: two preoperative and three postoperative categories each for AP and lateral images. The images were split into training, validation, and testing sets (70:15:15 proportional split). A deep learning classifier using the EfficientNet B6 architecture was trained on the spine training set. Hyperparameters and model architecture were tuned against the performance of the models in the validation set. RESULTS: The trained classifiers had an overall accuracy on the test set of 1.00 on 1166 AP images and 1.00 on 843 lateral images. Precision ranged from 0.98 to 1.00 in the AP images, and from 0.91 to 1.00 on the lateral images. Lower performance was observed on classes with fewer than 100 images in the dataset. Final performance metrics were calculated on the assigned test set, including accuracy, precision, recall, and F1 score (the harmonic mean of precision and recall). CONCLUSIONS: A deep learning convolutional neural network classifier was trained to a high degree of accuracy to distinguish between 10 categories pre- and postoperative spine radiographs of patients with scoliosis. Observed performance was higher in more prevalent categories. These models represent an important step in developing an automatic system for data ingestion into large, labeled imaging registries.