Alpha-Lipoic Acid Induces Adipose Tissue Browning through AMP-Activated Protein Kinase Signaling in Vivo and in Vitro.

Background: AMP-activated protein kinase (AMPK) is a key enzyme for cellular energy homeostasis and improves metabolic disorders. Brown and beige adipose tissues exert thermogenesis capacities to dissipate energy in the form of heat. Here, we investigated the beneficial effects of the antioxidant alpha-lipoic acid (ALA) in menopausal obesity and the underlying mechanisms. Methods: Female Wistar rats (8 weeks old) were subjected to bilateral ovariectomy (Ovx) and divided into four groups: Sham (n=8), Ovx (n=11), Ovx+ALA2 (n=10), and Ovx+ALA3 (n=6) (ALA 200 and 300 mg/kg/day, respectively; gavage) for 8 weeks. 3T3-L1 cells were used for in vitro study. Results: Rats receiving ALA2 and ALA3 treatment showed significantly lower levels of body weight and white adipose tissue (WAT) mass than those of the Ovx group. ALA improved plasma lipid profiles including triglycerides, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol. Hematoxylin & eosin staining of inguinal WAT showed that ALA treatment reduced Ovx-induced adipocyte size and enhanced uncoupling protein 1 (UCP1) expression. Moreover, plasma levels of irisin were markedly increased in ALA-treated Ovx rats. Protein expression of brown fat-specific markers including UCP1, PRDM16, and CIDEA was downregulated by Ovx but markedly increased by ALA. Phosphorylation of AMPK, its downstream acetyl-CoA carboxylase, and its upstream LKB1 were all significantly increased by ALA treatment. In 3T3-L1 cells, administration of ALA (100 and 250 µM) reduced lipid accumulation and enhanced oxygen consumption and UCP1 protein expression, while inhibition of AMPK by dorsomorphin (5 µM) significantly reversed these effects. Conclusion: ALA improves estrogen deficiency-induced obesity via browning of WAT through AMPK signaling.

Hepatic danger signaling triggers TREM2+ macrophage induction and drives steatohepatitis via MS4A7-dependent inflammasome activation.

Metabolic dysfunction-associated steatohepatitis (MASH), formerly known as nonalcoholic steatohepatitis (NASH), is an advanced stage of metabolic fatty liver disease. The pathogenic mechanisms of MASH center on hepatocyte injury and the ensuing immune response within the liver microenvironment. Recent work has implicated TREM2+ macrophages in various disease conditions, and substantial induction of TREM2+ NASH-associated macrophages (NAMs) serves as a hallmark of metabolic liver disease. Despite this, the mechanisms through which NAMs contribute to MASH pathogenesis remain poorly understood. Here, we identify membrane-spanning 4-domains a7 (MS4A7) as a NAM-specific pathogenic factor that exacerbates MASH progression in mice. Hepatic MS4A7 expression was strongly induced in mouse and human MASH and associated with the severity of liver injury. Whole-body and myeloid-specific ablation of Ms4a7 alleviated diet-induced MASH pathologies in male mice. We demonstrate that exposure to lipid droplets (LDs), released upon injury of steatotic hepatocytes, triggered NAM induction and exacerbated MASH-associated liver injury in an MS4A7-dependent manner. Mechanistically, MS4A7 drove NLRP3 inflammasome activation via direct physical interaction and shaped disease-associated cell states within the liver microenvironment. This work reveals the LD-MS4A7-NLRP3 inflammasome axis as a pathogenic driver of MASH progression and provides insights into the role of TREM2+ macrophages in disease pathogenesis.

The kainate receptor GluK2 mediates cold sensing in mice.

Thermosensors expressed in peripheral somatosensory neurons sense a wide range of environmental temperatures. While thermosensors detecting cool, warm and hot temperatures have all been extensively characterized, little is known about those sensing cold temperatures. Though several candidate cold sensors have been proposed, none has been demonstrated to mediate cold sensing in somatosensory neurons in vivo, leaving a knowledge gap in thermosensation. Here we characterized mice lacking the kainate-type glutamate receptor GluK2, a mammalian homolog of the Caenorhabditis elegans cold sensor GLR-3. While GluK2 knockout mice respond normally to heat and mechanical stimuli, they exhibit a specific deficit in sensing cold but not cool temperatures. Further analysis supports a key role for GluK2 in sensing cold temperatures in somatosensory DRG neurons in the periphery. Our results reveal that GluK2-a glutamate-sensing chemoreceptor mediating synaptic transmission in the central nervous system-is co-opted as a cold-sensing thermoreceptor in the periphery.

Quantitative analysis of the relationship between the myocardial bridge and the FAI of pericoronal fat on computed tomography.

We performed this cohort study to investigate whether the myocardial bridge (MB) affects the fat attenuation index (FAI) and to determine the optimal cardiac phase to measure the volume and the FAI of pericoronary adipose tissue (PCAT). The data of 300 patients who were diagnosed with MB of the left anterior descending (LAD) coronary artery were retrospectively analyzed. All of patients were divided into the MB group and the MB with atherosclerosis group. In addition, 104 patients with negative CCTA results were enrolled as the control group. There was no significant difference between FAI values measured in systole and diastole (P > 0.05). There was no significant difference in FAI among the MB group, the MB with atherosclerosis group, and the control group (P > 0.05). In MB with atherosclerosis group, LAD stenosis degree (< 50%) (OR = 0.186, 95% CI 0.036-0.960; P = 0.045) and MB located in the distal part of LAD opening (OR = 0.880, 95% CI 0.789-0.980; P = 0.020) were protective factors of FAI value. A distance (from the LAD opening to the proximal point of the MB) of 29.85 mm had the highest predictive value for abnormal FAI [area under the curve (AUC), 0.798], with a sensitivity of 81.1% and a specificity of 74.6%.

Quantitative computed tomography angiography evaluation of the coronary fractional flow reserve in patients with left anterior descending artery myocardial bridging.

PURPOSE: To quantitatively investigate the effect of myocardial bridge (MB) in the left anterior descending artery (LAD) on the fractional flow reserve (FFR). MATERIALS AND METHODS: Three-hundred patients with LAD MB who had undergone coronary artery CT angiography (CCTA) were retrospectively enroled, and 104 normal patients were enroled as the control. The CCTA-derived fractional flow reserve (FFRCT) was measured at the LAD 10 mm proximal (FFR1) and 20-40 mm distal (FFR3) to the MB and at the MB location (FFR2). RESULTS: FFR2 and FFR3 of the MB (with BM only) and MBLA (with both MB and atherosclerosis) groups were significantly (p < 0.01) lower than those of the control. The FFR3 distal to the MB was significantly lower (p < 0.01) than that of the control. The FFRCT of the whole LAD in the MBLA group was significantly (p < 0.05) lower than that of the MB and control group (p < 0.05). MB length (OR 1.061) and MB muscle index (odds ratio or OR 1.007) were two risk factors for abnormal FFRCT, and MB length was a significant independent risk factor for abnormal FFRCT (OR = 1.077). LAD stenosis degree was a risk factor for abnormal FFRCT values (OR 3.301, 95% confidence interval [CI] 1.441-7.562, p = 0.005) and was also a significant independent risk factor (OR = 3.369, 95% CI: 1.392-8.152; p = 0.007) for abnormal FFRCT. CONCLUSION: MB significantly affects the FFRCT of distal coronary artery. For patients with MB without atherosclerosis, the MB length is a risk factor significantly affecting FFRCT, and for patients with MB accompanied by atherosclerosis, LAD stenotic severity is an independent risk factor for FFRCT.

The therapeutic potential of dietary intervention: based on the mechanism of a tryptophan derivative-indole propionic acid on metabolic disorders.

Tryptophan (TRP) contributes to individual immune homeostasis and good condition via three complex metabolism pathways (5-hydroxytryptamine (5-HT), kynurenine (KP), and gut microbiota pathway). Indole propionic acid (IPA), one of the TRP derivatives of the microbiota pathway, has raised more attention because of its impact on metabolic disorders. Here, we retrospect increasing evidence that TRP metabolites/IPA derived from its proteolysis impact host health and disease. IPA can activate the immune system through aryl hydrocarbon receptor (AHR) and/or Pregnane X receptor (PXR) as a vital mediator among diet-caused host and microbe cross-talk. Different levels of IPA in systemic circulation can predict the risk of NAFLD, T2DM, and CVD. IPA is suggested to alleviate cognitive impairment from oxidative damage, reduce gut inflammation, inhibit lipid accumulation and attenuate the symptoms of NAFLD, putatively enhance the intestinal epithelial barrier, and maintain intestinal homeostasis. Now, we provide a general description of the relationships between IPA and various physiological and pathological processes, which support an opportunity for diet intervention for metabolic diseases.

Inhibitory effects of naringenin on estrogen deficiency-induced obesity via regulation of mitochondrial dynamics and AMPK activation associated with white adipose tissue browning.

AIMS: Post-ovariectomy (OVX) changes in hormones induce obesity and white adipose tissue (WAT) inflammation. Increased energy expenditure via WAT browning is a novel therapeutic strategy for treating obesity. Naringenin (NAR) reduces inflammation and lipogenesis in obesity and attenuates estrogen deficiency-associated metabolic disorders; however, its role in WAT browning remains unclear. MATERIALS AND METHODS: We investigated NAR ability to inhibit estrogen deficiency-associated obesity in vivo using a rat model and in vitro using 3T3-L1 adipocytes. KEY FINDINGS: NAR significantly decreased the body weight and WAT mass of rats. O2 consumption, CO2 production, and energy expenditure were significantly lower in the OVX group than in the sham group, but NAR treatment reversed these effects of OVX. NAR treatment markedly improved glucose intolerance and lipid profiles as well as leptin, adiponectin, and irisin levels. NAR upregulated markers of browning and mitochondrial biogenesis in inguinal WAT. Moreover, it enhanced markers of mitochondrial fusion and inhibited fission via activating the AMP-activated protein kinase pathway. Similar results were observed in 3T3-L1 adipocytes. Moreover, NAR-induced mitochondrial biogenesis and fusion were suppressed by dorsomorphin (an AMP-activated protein kinase inhibitor). SIGNIFICANCE: NAR alleviates obesity and metabolic dysfunction through the induction of WAT browning achieved via the modulation of AMP-activated protein kinase-regulated mitochondrial dynamics in WATs. NAR supplementation may therefore represent a potential intervention for preventing postmenopausal adipose tissue dysregulation.

Five similar anthocyanidin molecules display distinct disruptive effects and mechanisms of action on Aß1-42 protofibril: A molecular dynamic simulation study.

Alzheimer's disease (AD) is associated with the deposition of amyloid-ß (Aß) fibrillary aggregates. Disaggregation of Aß fibrils is considered as one of the promising AD treatments. Recent experimental studies showed that anthocyanidins, one type of flavonoids abundant in fruits/vegetables, can disaggregate Aß fibrillary aggregates. However, their relative disruptive capacities and underlying mechanisms are largely unknown. Herein, we investigated the detailed interactions between five most common anthocyanidins (cyanidin, aurantinidin, peonidin, delphinidin, and pelargonidin) and Aß protofibril (an intermediate of Aß fibrillization) by performing microsecond molecular dynamic simulations. We found that all five anthocyanidins can destroy F4-L34-V36 hydrophobic core and K28-A42 salt bridge, leading to Aß protofibril destabilization. Aurantinidin exhibits the strongest damage to Aß protofibril (with the most severe disruption on K28-A42 salt bridges), followed by cyanidin (with the most destructive effect on F4-L34-V36 core). Detailed analyses reveal that the protofibril-destruction capacities of anthocyanidins are subtly modulated by the interplay of anthocyanidin-protofibril hydrogen bonding, hydrophobic, aromatic stacking interactions, which are dictated by the number or location of hydroxyl/methyl groups of anthocyanidins. These findings provide important mechanistic insights into Aß protofibril disaggregation by anthocyanidins, and suggest that aurantinidin/cyanidin may serve as promising starting-points for the development of new drug candidates against AD.

Prognostic value of CT-derived fractional flow reserve and fat attenuation index in patients with suspected coronary artery disease: a sex-disaggregated analyses.

BACKGROUND: There are sex differences in many risk factors associated with coronary artery disease (CAD). CT-derived fractional flow reserve (CT-FFR) and fat attenuation index (FAI) have been shown to independently predict cardiovascular events. We aimed to examine the impact of sex on the prognostic value of CT-FFR and FAI in suspected CAD patients, and to examine the incremental prognostic value of FAI over CT-FFR in both sex. METHODS: A total of 1334 consecutive suspected CAD subjects who underwent coronary computed tomographic angiography (CCTA) were retrospectively collected. We divided the patients into males and females and calculated CT-FFR and FAI data from CCTA images. Kaplan-Meier analysis was used to assess the risk of major adverse cardiovascular events (MACE) stratified by CT-FFR and FAI in both sex. Cox regression models were used to assess the incremental prognostic value of FAI by adding the variable to a model that included CT-FFR and clinical variables. RESULTS: During a median follow-up of 2.08 years, 212 patients had MACE. CT-FFR ≤ 0.80 was significantly associated with MACE in both sex. FAI value of left anterior descending artery (FAI[LAD]) and FAI value of left circumflex (FAI[LCX]) ≥ 70.1 were significantly associated with MACE in females. FAI[LCX] added incremental prognostic value over clinical and CT-FFR variables in females, with hazard ratio (HR) 3.230 (1.982-5.265, P = 0.000), Harrel's C 0.669 (P < 0.001), net reclassification improvement (NRI) 0.161 (0.073-0.260, P < 0.001), and integrated discrimination index (IDI) 0.036 (0.008-0.090, P = 0.010). FAI[LAD] did not enhance risk prediction in females (Harrel's C 0.643, P = 0.054; NRI 0.041, P = 0.189; IDI 0.005, P = 0.259). The decision curve analysis demonstrated that the model including FAI[LCX] resulted in the highest net benefit. CONCLUSIONS: In suspected CAD patients, the prognostic value of CT-FFR is not significantly biased by sex. The prognostic value of FAI[LAD] and FAI[LCX] were significantly associated with MACE in females, but not males. FAI[LCX], not FAI[LAD], added incremental prognostic value over CT-FFR and might enhance CT-FFR risk stratification in females.

SMG: self-supervised masked graph learning for cancer gene identification.

Cancer genomics is dedicated to elucidating the genes and pathways that contribute to cancer progression and development. Identifying cancer genes (CGs) associated with the initiation and progression of cancer is critical for characterization of molecular-level mechanism in cancer research. In recent years, the growing availability of high-throughput molecular data and advancements in deep learning technologies has enabled the modelling of complex interactions and topological information within genomic data. Nevertheless, because of the limited labelled data, pinpointing CGs from a multitude of potential mutations remains an exceptionally challenging task. To address this, we propose a novel deep learning framework, termed self-supervised masked graph learning (SMG), which comprises SMG reconstruction (pretext task) and task-specific fine-tuning (downstream task). In the pretext task, the nodes of multi-omic featured protein-protein interaction (PPI) networks are randomly substituted with a defined mask token. The PPI networks are then reconstructed using the graph neural network (GNN)-based autoencoder, which explores the node correlations in a self-prediction manner. In the downstream tasks, the pre-trained GNN encoder embeds the input networks into feature graphs, whereas a task-specific layer proceeds with the final prediction. To assess the performance of the proposed SMG method, benchmarking experiments are performed on three node-level tasks (identification of CGs, essential genes and healthy driver genes) and one graph-level task (identification of disease subnetwork) across eight PPI networks. Benchmarking experiments and performance comparison with existing state-of-the-art methods demonstrate the superiority of SMG on multi-omic feature engineering.

Integrated network analysis and metabolomics reveal the molecular mechanism of Yinchen Sini decoction in CCl4-induced acute liver injury.

Objective: Yinchen Sini decoction (YCSND), a traditional Chinese medicine (TCM) formula, plays a crucial role in the treatment of liver disease. However, the bioactive constituents and pharmacological mechanisms of action remain unclear. The present study aimed to reveal the molecular mechanism of YCSND in the treatment of acute liver injury (ALI) using integrated network analysis and metabolomics. Methods: Ultra-high-performance liquid chromatography coupled with Q-Exactive focus mass spectrum (UHPLC-QE-MS) was utilized to identify metabolites in YCSND, and high-performance liquid chromatography (HPLC) was applied to evaluate the quality of four botanical drugs in YCSND. Cell damage and ALI models in mice were established using CCl4. 1H-NMR metabolomics approach, along with histopathological observation using hematoxylin and eosin (H&E), biochemical measurements, and reverse transcription quantitative real-time PCR (RT-qPCR), was applied to evaluate the effect of YCSND on CCl4- induced ALI. Network analysis was conducted to predict the potential targets of YCSND in ALI. Result: Our results showed that 89 metabolites in YCSND were identified using UHPLC-QE-MS. YCSND protected against ALI by reducing the levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), and malondialdehyde (MDA) contents and increasing those of superoxide dismutase (SOD), and glutathione (GSH) both in vivo and in vitro. The 1H-NMRmetabolic pattern revealed that YCSND reversed CCl4-induced metabolic abnormalities in the liver. Additionally, the Kyoto Encyclopedia of Genes and Genome (KEGG) pathway enrichment analysis identified five pathways related to liver injury, including the PI3K-AKT, MAPK, HIF-1, apoptosis, and TNF signaling pathways. Moreover, RT-qPCR showed YCSND regulated the inflammatory response (Tlr4, Il6, Tnfα, Nfκb1, Ptgs2, and Mmp9) and apoptosis (Bcl2, Caspase3, Bax, and Mapk3), and inhibited PI3K-AKT signaling pathway (Pi3k and Akt1). Combined network analysis and metabolomics showed a link between the key targets (Tlr4, Ptgs2, and Mmp9) and vital metabolites (choline, xanthine, lactate, and 3-hydroxybutyric acid) of YCSND in ALI. Conclusion: Overall, the results contribute to the understanding of the therapeutic effects of YCSND on ALI, and indicate that the integrated network analysis and metabolomics could be a powerful strategy to reveal the pharmacological effects of TCM.

Association of quantitative computed tomography-based right atrial appendage and right atrium parameters with postradiofrequency ablation recurrence of atrial fibrillation.

Background: The significance of the right atrial appendage (RAA) and right atrium (RA) in the recurrence of atrial fibrillation (AF) after radiofrequency ablation (RFA) remains uncertain. This retrospective case-control study aimed to quantitatively evaluate the role of morphological parameters of the RAA and RA in the recurrence of AF after RFA based on 256-slice spiral computed tomography (CT). Methods: A total of 297 patients with AF who underwent RFA for the first time between January 1 and October 31, 2020, were enrolled in the study, and they were divided into a nonrecurrence group (n=214) and a recurrence group (n=83). The volume of the RA, RAA and left atrium (LA); height of the RAA; long and short diameter, perimeter, and area of the RAA base; right atrial anteroposterior diameter; tricuspid annulus diameter; crista terminalis thickness; and cavotricuspid isthmus (CVTI) were measured, and the clinical data of patients were collected. Results: (I) Multivariable logistic regression analysis followed by univariable logistic regression analysis showed that the height of the RAA [odds ratio (OR) =1.124; 95% confidence interval (CI): 1.024-1.233; P=0.014], short diameter of the RAA base (OR =1.247; 95% CI: 1.118-1.391; P=0.001), crista terminalis thickness (OR =1.594; 95% CI: 1.052-2.415; P=0.028) and duration of AF (OR =1.009; 95% CI: 1.003-1.016; P=0.006) were independent predictors of postradiofrequency ablation AF recurrence. (II) Receiver operating characteristic (ROC) curve analysis showed that the prediction model constructed according to the multivariate logistic regression analysis presented good accuracy [area under the curve (AUC) =0.840; P=0.001]. A short diameter of the RAA base >26.95 mm had the highest predictive value for AF recurrence, with a sensitivity of 0.614 and a specificity of 0.822 (AUC =0.786, P=0.001). Pearson correlation analysis showed that there was a significant correlation between right atrial volume and left atrial volume (r=0.720, P<0.001). Conclusions: A significant increase in diameter and volume of the RAA and RA and tricuspid annulus diameter may correlate with postradiofrequency ablation AF recurrence. The height of the RAA, short diameter of the RAA base, crista terminalis thickness, and AF duration were independent predictors of recurrence. Among them, the short diameter of the RAA base had the highest predictive value for recurrence.

Modified stochastic medium prediction model for the deformation response of concealed underground stations under existing pipelines.

The underground pipeline network in the city is so intertwined that the concealed excavation of a metro station inevitably leads to a series of underground pipelines, causing settlement deformation and further risk of leakage. The existing theoretical methods for analysing settlement deformation are mostly for circular chambers, whereas metro stations have a nearly square cross-sectional form and different construction methods are very different, which have a greater impact on the deformation of the overlying pipelines. In this paper, based on the random medium theory and Peck's formula, the improved random medium model for predicting ground deformation is modified, the correction coefficients λ and η for the influence of different construction methods are proposed, the prediction model of underground pipeline deformation under different construction methods is obtained, and the numerical models of four work methods commonly used in urban tunnel construction: pillar hole method, side hole method, middle hole method and Pile-Beam-Arch (PBA) method are constructed through simulation, and the mathematical analysis software was used to fit the results to the model and obtain the range of correction coefficients λ and η for each of the four methods, and the accuracy and applicability of the theoretical model was verified by combining with actual engineering cases. The influence on the overlying pipes is in descending order: side hole method, pillar hole method, middle hole method and PBA method. The theoretical model provided in this paper for predicting the deformation of pipes in any overlying strata of the tunnel is well suited to the actual project and has a high degree of correlation with the measured results.

Sulfur-Mediated Formal Allylic C-H Cyclopropanation of α-Methylstyrenes.

Allylic C-H cyclopropanation of α-methylstyrene and its derivatives was realized through a one-pot two-step sequence, formally converting two aliphatic C-H bonds to C-C bonds with a good yield and high diastereoselectivity, thus providing a quick entry to the synthetically useful vinyl cyclopropane structures.

Three-Tesla magnetic resonance imaging of left ventricular volume and function in comparison with computed tomography and echocardiography.

This study investigated the correlation between 3-Tesla magnetic resonance imaging (MRI) and 256 multiple-slice computed tomography (MSCT) or 2-dimensional echocardiography (ECHO) in evaluating left ventricle. Forty patients were retrospectively enrolled to undergo cardiac MSCT, 3-Tesla MRI and 2-dimensional ECHO within 1 week. The end-diastolic (EDV) and end-systolic volume (ESV), stroke volume (SV) and ejection fraction (EF) were analyzed and compared. MSCT was highly significantly correlated with MRI. Compared with MRI, MSCT slightly overestimated ESV for about 8.7 mL, but slightly underestimated EF and SV for about 6.8% and 5.8 mL, respectively. A high consistency existed between MSCT and MRI, with the 95% limit of agreement (-19.6, 25.4) mL for EDV, (-2.6,20.1) mL for ESV, (-28.3,16.6) mL for SV, and (-18.8%,5.1) % for EF. ECHO was also significantly correlated with MRI. The ECHO slightly underestimated the left ventricular function compared with MRI, with an underestimation of 9.4 mL for EDV, 3.5 mL for ESV, 5.8 mL for SV and 1.0% for EF. A wider agreement limit existed between MRI and ECHO. MSCT has a better correlation and agreement relationship with MRI parameters than 2-dimensional ECHO in assessing the left ventricle and may serve as a possible alternative to MRI.

Indole metabolites and colorectal cancer: Gut microbial tryptophan metabolism, host gut microbiome biomarkers, and potential intervention mechanisms.

Tryptophan (Trp) functions in host-disease interactions. Its metabolism is a multi-pathway process. Indole and its derivatives are Trp metabolites unique to the human gut microbiota. Changes in Trp metabolism have also been detected in colorectal cancer (CRC). Here, combined with the existing CRC biomarkers, we ascribed it to the altered bacteria having the indole-producing ability by making a genomic prediction. We also reviewed the anti-inflammatory and possible anti-cancer mechanisms of indoles, including their effects on tumor cells, the ability to repair the gut barrier, regulation of the host immune system, and provide resistance against oxidative stress. Indole and its derivatives, along with related bacteria, could be targeted as auxiliary strategies to restrain cancer development in the future.

Targeting tumor heterogeneity: multiplex-detection-based multiple instance learning for whole slide image classification.

MOTIVATION: Multiple instance learning (MIL) is a powerful technique to classify whole slide images (WSIs) for diagnostic pathology. The key challenge of MIL on WSI classification is to discover the critical instances that trigger the bag label. However, tumor heterogeneity significantly hinders the algorithm's performance. RESULTS: Here, we propose a novel multiplex-detection-based multiple instance learning (MDMIL) which targets tumor heterogeneity by multiplex detection strategy and feature constraints among samples. Specifically, the internal query generated after the probability distribution analysis and the variational query optimized throughout the training process are utilized to detect potential instances in the form of internal and external assistance, respectively. The multiplex detection strategy significantly improves the instance-mining capacity of the deep neural network. Meanwhile, a memory-based contrastive loss is proposed to reach consistency on various phenotypes in the feature space. The novel network and loss function jointly achieve high robustness towards tumor heterogeneity. We conduct experiments on three computational pathology datasets, e.g. CAMELYON16, TCGA-NSCLC, and TCGA-RCC. Benchmarking experiments on the three datasets illustrate that our proposed MDMIL approach achieves superior performance over several existing state-of-the-art methods. AVAILABILITY AND IMPLEMENTATION: MDMIL is available for academic purposes at https://github.com/ZacharyWang-007/MDMIL.

Uncovering the specificity and predictability of tryptophan metabolism in lactic acid bacteria with genomics and metabolomics.

Tryptophan is metabolized by microorganisms into various indole derivatives that have been proven to alleviate diseases and promote human health. Lactic acid bacteria (LAB) are a broad microbial concept, some of which have been developed as probiotics. However, the capacity of most LAB to metabolize tryptophan is unknown. In this study, the aim is to reveal the rule of tryptophan metabolism in LAB by multi-omics. The findings showed that LAB were rich in genes for tryptophan catabolism and that multiple genes were shared among LAB species. Although the number of their homologous sequences was different, they could still form the same metabolic enzyme system. The metabolomic analysis revealed that LAB were capable of producing a variety of metabolites. Strains belonging to the same species can produce the same metabolites and have similar yields. A few strains showed strain-specificity in the production of indole-3-lactic acid (ILA), indole-3-acetic acid, and 3-indolealdehyde (IAld). In the genotype-phenotype association analysis, the metabolites of LAB were found to be highly consistent with the outcomes of gene prediction, particularly ILA, indole-3-propionic acid, and indole-3-pyruvic acid. The overall prediction accuracy was more than 87% on average, which indicated the predictability of tryptophan metabolites of LAB. Additionally, genes influenced the concentration of metabolites. The levels of ILA and IAld were significantly correlated with the numbers of aromatic amino acid aminotransferase and amidase, respectively. The unique indolelactate dehydrogenase in Ligilactobacillus salivarius was the primary factor contributing to its large production of ILA. In summary, we demonstrated the gene distribution and production level of tryptophan metabolism in LAB and explored the correlation between genes and phenotypes. The predictability and specificity of the tryptophan metabolites in LAB were proven. These results provide a novel genomic method for the discovery of LAB with tryptophan metabolism potential and offer experimental data for probiotics that produce specific tryptophan metabolites.

PFresGO: an attention mechanism-based deep-learning approach for protein annotation by integrating gene ontology inter-relationships.

MOTIVATION: The rapid accumulation of high-throughput sequence data demands the development of effective and efficient data-driven computational methods to functionally annotate proteins. However, most current approaches used for functional annotation simply focus on the use of protein-level information but ignore inter-relationships among annotations. RESULTS: Here, we established PFresGO, an attention-based deep-learning approach that incorporates hierarchical structures in Gene Ontology (GO) graphs and advances in natural language processing algorithms for the functional annotation of proteins. PFresGO employs a self-attention operation to capture the inter-relationships of GO terms, updates its embedding accordingly and uses a cross-attention operation to project protein representations and GO embedding into a common latent space to identify global protein sequence patterns and local functional residues. We demonstrate that PFresGO consistently achieves superior performance across GO categories when compared with 'state-of-the-art' methods. Importantly, we show that PFresGO can identify functionally important residues in protein sequences by assessing the distribution of attention weightings. PFresGO should serve as an effective tool for the accurate functional annotation of proteins and functional domains within proteins. AVAILABILITY AND IMPLEMENTATION: PFresGO is available for academic purposes at https://github.com/BioColLab/PFresGO. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Molecular characterization and expression analysis of a novel cold-inducible RNA-binding protein (CIRBP) gene in lamprey (Lethenteron reissneri).

Cold-inducible RNA-binding protein (CIRBP) responds to a wide array of cellular stresses such as cold shock, hypoxia, and inflammatory responses. However, functional studies of CIRBP in jawless vertebrates are limited. In this study, a CIRBP homolog from the jawless vertebrate lamprey (Lethenteron reissneri) was cloned and characterized (named Lr-CIRBP). The cDNA fragment of Lr-CIRBP has a 516 bp open reading frame (ORF) that encodes 171 amino acids, comprising a glycine-rich region at the C-terminal, similar to higher vertebrates but slightly shorter, and an RNA recognition motif (RRM) domain at the N-terminus. The predicted Lr-CIRBP sequence had 51.4 ~ 70.6% similarity with CIRBPs from other vertebrates. Further phylogenetic analysis revealed that Lr-CIRBP is located in the outgroup of vertebrates and is the ancestor of vertebrates. Based on real-time quantitative PCR experimental analysis, Lr-CIRBP expression was highest in leukocytes and increased significantly after multi-stimulation, peaking at 12 h. RNA interference showed that Lr-CIRBP knockdown can down-regulate the expression of inflammatory factors in Lethenteron reissneri. In conclusion, our study successfully clarifies the ancestral features and functions of CIRBP, while revealing valuable insight into how the protein is involved in the immune responses of a jawless vertebrate.