Biotransformation characteristics of urate-lowering probiotic fermented apple juice and potential regulatory mechanisms for ameliorating hyperuricemia via mediating gut microbiota and metabolic pathways.

Hyperuricemia has evolved into a global public health concern, and applying probiotics fermented apple juice holds promise for alleviating this condition. This study aimed to investigate the biotransformation and metabolic features of urate-lowering probiotics sequentially fermented dealcoholized apple juice (PSFA), and assess its ameliorative effects and potential mechanisms on hyperuricemia mice. Results showed that CICC 6074 and 20,292 possessed excellent purine, nucleotide and nucleoside degradation and acid and bile salt resistance; sequential fermentation decreased the fructose in apple juice, and viable counts reached 3.76 × 108 CFU/mL. Histopathological analysis showed that PSFA ameliorated kidney damage in hyperuricemia mice. Furthermore, PSFA significantly reduced Urea, Creatinine and Uric acid levels in hyperuricemia mice; and inhibited xanthine oxidase activity and the expression of pro-inflammatory factors. Importantly, PSFA reversed gut microbiota dysbiosis and raised the abundance of beneficial bacteria (Lactobacillush, Faecalibaculum and Lachnospiraceae_NK4A136_group). KEGG and COG functional prediction results revealed that the potential mechanism of PSFA to ameliorate hyperuricemia may be lipid metabolism and glycolysis pathways.

GSTO1 aggravates EGFR-TKIs resistance and tumor metastasis via deglutathionylation of NPM1 in lung adenocarcinoma.

Despite significantly improved clinical outcomes in EGFR-mutant lung adenocarcinoma, all patients develop acquired resistance and malignancy on the treatment of EGFR tyrosine kinase inhibitors (EGFR-TKIs). Understanding the resistance mechanisms is crucial to uncover novel therapeutic targets to improve the efficacy of EGFR-TKI treatment. Here, integrated analysis using RNA-Seq and shRNAs metabolic screening reveals glutathione S-transferase omega 1 (GSTO1) as one of the key metabolic enzymes that is required for EGFR-TKIs resistance in lung adenocarcinoma cells. Aberrant upregulation of GSTO1 confers EGFR-TKIs resistance and tumor metastasis in vitro and in vivo dependent on its active-site cysteine 32 (C32). Pharmacological inhibition or knockdown of GSTO1 restores sensitivity to EGFR-TKIs and synergistically enhances tumoricidal effects. Importantly, nucleophosmin 1 (NPM1) cysteine 104 is deglutathionylated by GSTO1 through its active C32 site, which leads to activation of the AKT/NF-κB signaling pathway. In addition, clinical data illustrates that GSTO1 level is positively correlated with NPM1 level, NF-κB-mediated transcriptions and progression of human lung adenocarcinoma. Overall, our study highlights a novel mechanism of GSTO1 mediating EGFR-TKIs resistance and malignant progression via protein deglutathionylation, and GSTO1/NPM1/AKT/NF-κB axis as a potential therapeutic vulnerability in lung adenocarcinoma.

The causal role between circulating immune cells and diabetic nephropathy: a bidirectional Mendelian randomization with mediating insights.

Diabetic nephropathy (DN) is a critical inflammatory condition linked to diabetes, affecting millions worldwide. This study employs Mendelian randomization (MR) to explore the causal relationship between immune cell signatures and DN, analyzing over 731 immune signatures and incorporating data from 1400 metabolites to investigate potential mediators. Despite no statistically significant influence of DN on immunophenotypes after FDR correction, some phenotypes with unadjusted low P-values warranted mention, including CD34 on Hematopoietic Stem Cell (Myeloid cell Panel), CD45 on CD33- HLA DR- (Myeloid cell Panel). Furthermore, three immunophenotypes were identified to have a significant impact on DN risk: CD16-CD56 on HLA DR+ NK (TBNK Panel), CD45 on HLA DR+ T cell (TBNK Panel), and CD33dim HLA DR+ CD11b+ AC (Myeloid cell Panel). Our findings underscore the critical role of immune cells in DN, highlighting potential mediators and offering new insights into its underlying mechanisms.

Analysis of risk factors for weaning failure from mechanical ventilation in critically ill older patients with coronavirus disease 2019.

Objective: This study aimed to investigate the factors influencing weaning failure from invasive mechanical ventilation (IMV) in critically ill older patients with coronavirus disease 2019 (COVID-19). Methods: We enrolled critically ill older patients with COVID-19 who were admitted to the medical intensive care unit (ICU) and received IMV between December 2022 and June 2023. Results: We included 68 critically ill older patients with COVID-19 (52 male [76.5 %] and 16 female individuals [23.5 %]). The patients' median age (interquartile range) was 75.5 (70.3-82.8) years. The median length of ICU stay was 11.5 (7.0-17.8) days; 34 cases (50.0 %) were successfully weaned from IMV. The successfully weaned group had a higher proportion of underlying chronic obstructive pulmonary disease [6 (17.6 %) vs. 0, P = 0.033] and fewer cases of diabetes [7 (20.6 %) vs. 16 (47.1 %), P = 0.021] compared with the weaning failure group. Serum lactate levels [1.5 (1.2-2.3) vs. 2.6 (1.9-3.1) mmol/L, P < 0.001], blood urea nitrogen [8.2 (6.3-14.4) vs. 11.4 (8.0-21.3) mmol/L, P = 0.033], Acute Physiology and Chronic Health Evaluation (APACHE) II score [19.0 (12.0-23.3) vs. 22.5 (16.0-29.3), P = 0.014], and hospitalization days before endotracheal intubation [1.0 (0.0-5.0) vs. 3.0 (0.0-11.0), P = 0.023] were significantly decreased in the successfully weaned group, whereas PaO2/FiO2 [148.3 (94.6-200.3) vs. 101.1 (67.0-165.1), P = 0.038] and blood lymphocyte levels [0.6 (0.4-1.0) vs. 0.5 (0.2-0.6) 109/L, P = 0.048] were significantly increased, compared with the weaning failure group. Multivariate logistic regression analysis showed that diabetes (OR= 3.413, 95 %CI 1.029-11.326), P = 0.045), APACHE II Score (OR = 1.089, 95 % CI 1.008-1.175), P = 0.030), and hospitalization days before endotracheal intubation (OR = 1.137, 95 % CI 1.023-1.264), P = 0.017) were independent risk factors for weaning failure. Conclusion: In critically ill older patients with COVID-19 with diabetes, higher APACHE II Score, and longer hospitalization days before endotracheal intubation, weaning from IMV was more challenging. The study could help develop strategies for improving COVID-19 treatment.

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.

MTHFR as a Novel Candidate Marker for Litter Size in Rabbits.

Litter size is a significant economic trait during animal reproduction. This current study attempted to decipher whether MTHFR promotes the apoptosis of granulosa cells (GCs) and inhibits their proliferation by investigating the effects of the MTHFR gene using flow cytometry and a Cell Counting Kit-8 (CCK-8) assay. MTHFR is linked with ovarian follicle development in the reproductive performance of 104 female New Zealand rabbits. We observed that MTHFR could regulate the mRNA of follicular development-related genes (TIMP1, CITED1, FSHR, GHR, HSD17B1, and STAR) with a qRT-PCR, and we observed the protein expression of CITED1 and GHR using a western blot (WB) analysis. The dual luciferase activity assays helped identify the core promoter region of the MTHFR gene, and the polymorphism of the MTHFR promoter region was studied using Sanger sequencing. The results indicated four single nucleotide polymorphisms (SNPs) within the core promoter region, among which the g.-680C>A locus was significantly associated with both the total and alive litter sizes. Additionally, the CC genotype was associated with the largest total and alive litter sizes, compared to the CA and AA genotypes (p < 0.05). In conclusion, this study investigated the effects of MTHFR on ovarian granulosa cells and its association with selected reproductive parameters in rabbits. The results provide a theoretical foundation for the use of MTHFR as a molecular marker in rabbits.

Mitochondrial metabolic reprogramming in diabetic kidney disease.

Diabetic kidney disease, known as a glomerular disease, arises from a metabolic disorder impairing renal cell function. Mitochondria, crucial organelles, play a key role in substance metabolism via oxidative phosphorylation to generate ATP. Cells undergo metabolic reprogramming as a compensatory mechanism to fulfill energy needs for survival and growth, attracting scholarly attention in recent years. Studies indicate that mitochondrial metabolic reprogramming significantly influences the pathophysiological progression of DKD. Alterations in kidney metabolism lead to abnormal expression of signaling molecules and activation of pathways, inducing oxidative stress-related cellular damage, inflammatory responses, apoptosis, and autophagy irregularities, culminating in renal fibrosis and insufficiency. This review delves into the impact of mitochondrial metabolic reprogramming on DKD pathogenesis, emphasizing the regulation of metabolic regulators and downstream signaling pathways. Therapeutic interventions targeting renal metabolic reprogramming can potentially delay DKD progression. The findings underscore the importance of focusing on metabolic reprogramming to develop safer and more effective therapeutic approaches.

Maintaining calcium homeostasis as a strategy to alleviate nephrotoxicity caused by evodiamine.

Evodiamine (EVO), the main active alkaloid in Evodia rutaecarpa, was shown to exert various pharmacological activities, especially anti-tumor. Currently, it is considered a potential anti-cancer drug due to its excellent anti-tumor activity, which unfortunately has adverse reactions, such as the risk of liver and kidney injury, when Evodia rutaecarpa containing EVO is used clinically. In the present study, we aim to clarify the potential toxic target organs and toxicity mechanism of EVO, an active monomer in Evodia rutaecarpa, and to develop mitigation strategies for its toxicity mechanism. Transcriptome analysis and related experiments showed that the PI3K/Akt pathway induced by calcium overload was an important step in EVO-induced apoptosis of renal cells. Specifically, intracellular calcium ions were increased, and mitochondrial calcium ions were decreased. In addition, EVO-induced calcium overload was associated with TRPV1 receptor activation. In vivo TRPV1 antagonist and calcium chelator effects were observed to significantly reduce body weight loss and renal damage in mice due to EVO toxicity. The potential nephrotoxicity of EVO was further confirmed by an in vivo test. In conclusion, TRPV1-mediated calcium overload-induced apoptosis is one of the mechanisms contributing to the nephrotoxicity of EVO due to its toxicity, whereas maintaining body calcium homeostasis is an effective measure to reduce toxicity. These studies suggest that the clinical use of EVO-containing herbal medicines should pay due attention to the changes in renal function of patients as well as the off-target effects of the drugs.

Layer-by-layer coated probiotics with chitosan and liposomes exhibit enhanced therapeutic effects for DSS-induced colitis in mice.

Probiotic therapy has emerged as a promising approach for the treatment of gastrointestinal diseases, offering advantages in terms of safety and convenience. However, oral probiotics encounter significant challenges, including exposure to a hostile gastric environment with low pH, bile salts, elevated levels of reactive oxygen species (ROS), and damage to the protective mucus layer. These factors reduce probiotic survival rates and limit their physiological activity. To address these challenges, we developed a layer-by-layer coated probiotics with curcumin-loaded liposome and polymer. Through DSS-induced colitis mice experiments, we demonstrated that the coated probiotics exhibited an improved survival rate in the gastrointestinal tract and enhanced adhesion to the intestinal mucosa. Furthermore, multi-layered coated probiotics exhibited remarkable efficacy in alleviating colitis by efficiently repairing the gut barrier, modulating gut microbial homeostasis, and reducing bacterial motility at sites of colonic inflammation. Our innovative approach holds promise for effectively treating gastrointestinal diseases.

A pupillary contrast response in mice and humans: Neural mechanisms and visual functions.

In the pupillary light response (PLR), increases in ambient light constrict the pupil to dampen increases in retinal illuminance. Here, we report that the pupillary reflex arc implements a second input-output transformation; it senses temporal contrast to enhance spatial contrast in the retinal image and increase visual acuity. The pupillary contrast response (PCoR) is driven by rod photoreceptors via type 6 bipolar cells and M1 ganglion cells. Temporal contrast is transformed into sustained pupil constriction by the M1's conversion of excitatory input into spike output. Computational modeling explains how the PCoR shapes retinal images. Pupil constriction improves acuity in gaze stabilization and predation in mice. Humans exhibit a PCoR with similar tuning properties to mice, which interacts with eye movements to optimize the statistics of the visual input for retinal encoding. Thus, we uncover a conserved component of active vision, its cell-type-specific pathway, computational mechanisms, and optical and behavioral significance.

Identifying autism spectrum disorder from multi-modal data with privacy-preserving.

The application of deep learning models to precision medical diagnosis often requires the aggregation of large amounts of medical data to effectively train high-quality models. However, data privacy protection mechanisms make it difficult to perform medical data collection from different medical institutions. In autism spectrum disorder (ASD) diagnosis, automatic diagnosis using multimodal information from heterogeneous data has not yet achieved satisfactory performance. To address the privacy preservation issue as well as to improve ASD diagnosis, we propose a deep learning framework using multimodal feature fusion and hypergraph neural networks for disease prediction in federated learning (FedHNN). By introducing the federated learning strategy, each local model is trained and computed independently in a distributed manner without data sharing, allowing rapid scaling of medical datasets to achieve robust and scalable deep learning predictive models. To further improve the performance with privacy preservation, we improve the hypergraph model for multimodal fusion to make it suitable for autism spectrum disorder (ASD) diagnosis tasks by capturing the complementarity and correlation between modalities through a hypergraph fusion strategy. The results demonstrate that our proposed federated learning-based prediction model is superior to all local models and outperforms other deep learning models. Overall, our proposed FedHNN has good results in the work of using multi-site data to improve the performance of ASD identification.

PSEENet: A pseudo-siamese neural network incorporating electroencephalography and electrooculography characteristics for heterogeneous sleep staging.

Sleep staging plays a critical role in evaluating the quality of sleep. Currently, most studies are either suffering from dramatic performance drops when coping with varying input modalities or unable to handle heterogeneous signals. To handle heterogeneous signals and guarantee favorable sleep staging performance when a single modality is available, a pseudo-siamese neural network (PSN) to incorporate electroencephalography (EEG), electrooculography (EOG) characteristics is proposed (PSEENet). PSEENet consists of two parts, spatial mapping modules (SMMs) and a weight-shared classifier. SMMs are used to extract high-dimensional features. Meanwhile, joint linkages among multi-modalities are provided by quantifying the similarity of features. Finally, with the cooperation of heterogeneous characteristics, associations within various sleep stages can be established by the classifier. The evaluation of the model is validated on two public datasets, namely, Montreal Archive of Sleep Studies (MASS) and SleepEDFX, and one clinical dataset from Huashan Hospital of Fudan University (HSFU). Experimental results show that the model can handle heterogeneous signals, provide superior results under multimodal signals and show good performance with single modality. PSEENet obtains accuracy of 79.1%, 82.1% with EEG, EEG and EOG on Sleep-EDFX, and significantly improves the accuracy with EOG from 73.7% to 76% by introducing similarity information.

Distributed feature representations of natural stimuli across parallel retinal pathways.

How sensory systems extract salient features from natural environments and organize them across neural pathways is unclear. Combining single-cell and population two-photon calcium imaging in mice, we discover that retinal ON bipolar cells (second-order neurons of the visual system) are divided into two blocks of four types. The two blocks distribute temporal and spatial information encoding, respectively. ON bipolar cell axons co-stratify within each block, but separate laminarly between them (upper block: diverse temporal, uniform spatial tuning; lower block: diverse spatial, uniform temporal tuning). ON bipolar cells extract temporal and spatial features similarly from artificial and naturalistic stimuli. In addition, they differ in sensitivity to coherent motion in naturalistic movies. Motion information is distributed across ON bipolar cells in the upper and the lower blocks, multiplexed with temporal and spatial contrast, independent features of natural scenes. Comparing the responses of different boutons within the same arbor, we find that axons of all ON bipolar cell types function as computational units. Thus, our results provide insights into the visual feature extraction from naturalistic stimuli and reveal how structural and functional organization cooperate to generate parallel ON pathways for temporal and spatial information in the mammalian retina.

Predation without direction selectivity.

Across the animal kingdom, visual predation relies on motion-sensing neurons in the superior colliculus (SC) and its orthologs. These neurons exhibit complex stimulus preferences, including direction selectivity, which is thought to be critical for tracking the unpredictable escape routes of prey. The source of direction selectivity in the SC is contested, and its contributions to predation have not been tested experimentally. Here, we use type-specific cell removal to show that narrow-field (NF) neurons in the mouse SC guide predation. In vivo recordings demonstrate that direction-selective responses of NF cells are independent of recently reported stimulus-edge effects. Monosynaptic retrograde tracing reveals that NF cells receive synaptic input from direction-selective ganglion cells. When we eliminate direction selectivity in the retina of adult mice, direction-selective responses in the SC, including in NF cells, are lost. However, eliminating retinal direction selectivity does not affect the hunting success or strategies of mice, even when direction selectivity is removed after mice have learned to hunt, and despite abolishing the gaze-stabilizing optokinetic reflex. Thus, our results identify the retinal source of direction selectivity in the SC. They show that NF cells in the SC guide predation, an essential spatial orienting task, independent of their direction selectivity, revealing behavioral multiplexing of complex neural feature preferences and highlighting the importance of feature-selective manipulations for neuroethology.

Association of urinary chlorpyrifos, paraquat, and cyproconazole levels with the severity of fatty liver based on MRI.

BACKGROUND: The objective of this study was to detect the urinary levels of chlorpyrifos, paraquat, and cyproconazole in residents living in Fuyang City and to analyze the correlation between these urinary pesticides levels and the severity of fatty liver disease (FLD). METHODS: All participants' fat fraction (FF) values were recorded by MRI (Magnetic resonance imaging). First-morning urine samples were collected from 53 participants from Fuyang Peoples'Hospital. The levels of three urinary pesticides were measured using ß-glucuronidase hydrolysis followed by a. The results were analyzed by using Pearson correlation analysis and binary logistic regression analysis to reveal the correlation between three urinary pesticides and the severity of fatty liver. RESULTS: 53 individuals were divided into 3 groups based on the results from MRI, with 20 cases in the normal control group, 16 cases in the mild fatty liver group, and 17 cases in the moderate and severe fatty liver group. Urinary chlorpyrifos level was increased along with the increase of the severity of fatty liver. Urinary paraquat level was significantly higher both in the low-grade fatty liver group and moderate & serve grade fatty liver group compared with the control group. No significant differences in urinary cyproconazole levels were observed among the three groups. Furthermore, urinary chlorpyrifos and paraquat levels were positively correlated with FF value. And chlorpyrifos was the risk factor that may be involved in the development of FLD and Receiver Operating Characteristic curve (ROC curve) analysis showed that chlorpyrifos and paraquat may serve as potential predictors of FLD. CONCLUSION: The present findings indicate urinary chlorpyrifos and paraquat were positively correlated with the severity of fatty liver. Moreover, urinary chlorpyrifos and paraquat have the potential to be considered as the predictors for development of FLD. Thus, this study may provide a new perspective from the environmental factors for the diagnosis, prevention, and treatment of FLD.

Using fs/QCA to explore the influencing factors of urban green infrastructure development and its combinational drivers: the case of the Yangtze River Delta region of China.

High levels of urban green infrastructure (UGI) development can help mitigate the climate, biodiversity, and habitat crises faced by cities and support the achievement of sustainable urban development. Based on the relevant data of 41 cities in the Yangtze River Delta region obtained from 2011 to 2020, this study measured the development level of natural and geographic conditions, economic development, urban construction, social and cultural development, and eco-environment quality and urban green infrastructure (UGI); evaluated the development trend of UGI in the region during the 12th Five-Year Plan and 13th Five-Year Plan by using entropy TOPSIS; and used fs/QCA to explain the high-level development path of each city toward the achievement of a green infrastructure. The results showed that (1) the development level of UGI in the Yangtze River Delta region decreases from southeast to northwest, and gradually decreases from Shanghai, Hangzhou, and other central cities. (2) There were several different configurations of high levels and non-high levels of UGI development drivers across regions, confirming the existence of multiple causality and asymmetry indices in the drivers of UGI. (3) During the "12th Five-Year Plan" and the "13th Five-Year Plan" period, the conditions needed to achieve a high level of UGI gradually became stricter, expanding from nature-social culture and urban construction-eco-environmental drivers to nature-urban construction, nature-social culture-eco-environmental, urban construction-economy-social culture-eco-environmental drivers. Research findings can provide greater guidance and implications for future sustainable urban development.

Anchored-fusion enables targeted fusion search in bulk and single-cell RNA sequencing data.

Here, we present Anchored-fusion, a highly sensitive fusion gene detection tool. It anchors a gene of interest, which often involves driver fusion events, and recovers non-unique matches of short-read sequences that are typically filtered out by conventional algorithms. In addition, Anchored-fusion contains a module based on a deep learning hierarchical structure that incorporates self-distillation learning (hierarchical view learning and distillation [HVLD]), which effectively filters out false positive chimeric fragments generated during sequencing while maintaining true fusion genes. Anchored-fusion enables highly sensitive detection of fusion genes, thus allowing for application in cases with low sequencing depths. We benchmark Anchored-fusion under various conditions and found it outperformed other tools in detecting fusion events in simulated data, bulk RNA sequencing (bRNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Our results demonstrate that Anchored-fusion can be a useful tool for fusion detection tasks in clinically relevant RNA-seq data and can be applied to investigate intratumor heterogeneity in scRNA-seq data.