Regulation of T helper cell differentiation by the interplay between histone modification and chromatin interaction.

The development and function of the immune system are controlled by temporospatial gene expression programs, which are regulated by cis-regulatory elements, chromatin structure, and trans-acting factors. In this study, we cataloged the dynamic histone modifications and chromatin interactions at regulatory regions during T helper (Th) cell differentiation. Our data revealed that the H3K4me1 landscape established by MLL4 in naive CD4+ T cells is critical for restructuring the regulatory interaction network and orchestrating gene expression during the early phase of Th differentiation. GATA3 plays a crucial role in further configuring H3K4me1 modification and the chromatin interaction network during Th2 differentiation. Furthermore, we demonstrated that HSS3-anchored chromatin loops function to restrict the activity of the Th2 locus control region (LCR), thus coordinating the expression of Th2 cytokines. Our results provide insights into the mechanisms of how the interplay between histone modifications, chromatin looping, and trans-acting factors contributes to the differentiation of Th cells.

Acetylation coordinates the crosstalk between carbon metabolism and ammonium assimilation in Salmonella enterica.

Enteric bacteria use up to 15% of their cellular energy for ammonium assimilation via glutamine synthetase (GS)/glutamate synthase (GOGAT) and glutamate dehydrogenase (GDH) in response to varying ammonium availability. However, the sensory mechanisms for effective and appropriate coordination between carbon metabolism and ammonium assimilation have not been fully elucidated. Here, we report that in Salmonella enterica, carbon metabolism coordinates the activities of GS/GDH via functionally reversible protein lysine acetylation. Glucose promotes Pat acetyltransferase-mediated acetylation and activation of adenylylated GS. Simultaneously, glucose induces GDH acetylation to inactivate the enzyme by impeding its catalytic centre, which is reversed upon GDH deacetylation by deacetylase CobB. Molecular dynamics (MD) simulations indicate that adenylylation is required for acetylation-dependent activation of GS. We show that acetylation and deacetylation occur within minutes of "glucose shock" to promptly adapt to ammonium/carbon variation and finely balance glutamine/glutamate synthesis. Finally, in a mouse infection model, reduced S. enterica growth caused by the expression of adenylylation-mimetic GS is rescued by acetylation-mimicking mutations. Thus, glucose-driven acetylation integrates signals from ammonium assimilation and carbon metabolism to fine-tune bacterial growth control.

The transcription factor TCF-1 initiates the differentiation of T(FH) cells during acute viral infection.

Induction of the transcriptional repressor Bcl-6 in CD4(+) T cells is critical for the differentiation of follicular helper T cells (T(FH) cells), which are essential for B cell-mediated immunity. In contrast, the transcription factor Blimp1 (encoded by Prdm1) inhibits T(FH) differentiation by antagonizing Bcl-6. Here we found that the transcription factor TCF-1 was essential for both the initiation of T(FH) differentiation and the effector function of differentiated T(FH) cells during acute viral infection. Mechanistically, TCF-1 bound directly to the Bcl6 promoter and Prdm1 5' regulatory regions, which promoted Bcl-6 expression but repressed Blimp1 expression. TCF-1-null T(FH) cells upregulated genes associated with non-T(FH) cell lineages. Thus, TCF-1 functions as an important hub upstream of the Bcl-6-Blimp1 axis to initiate and secure the differentiation of T(FH) cells during acute viral infection.

The Kinase mTORC1 Promotes the Generation and Suppressive Function of Follicular Regulatory T Cells.

Follicular regulatory T (Tfr) cells differentiate from conventional regulatory T (Treg) cells and suppress excessive germinal center (GC) responses by acting on both GC B cells and T follicular helper (Tfh) cells. Here, we examined the impact of mTOR, a serine/threonine protein kinase that senses and integrates diverse environmental cues, on the differentiation and functional competency of Tfr cells in response to protein immunization or viral infection. By genetically deleting Rptor or Rictor, essential components for mTOR complex 1 (mTORC1) and mTOR complex 2 (mTORC2), respectively, we found that mTORC1 but not mTORC2 is essential for Tfr differentiation. Mechanistically, mTORC1-mediated phosphorylation of the transcription factor STAT3 induced the expression of the transcription factor TCF-1 by promoting STAT3 binding to the Tcf7 5'-regulatory region. Subsequently, TCF-1 bound to the Bcl6 promoter to induce Bcl6 expression, which launched the Tfr cell differentiation program. Thus, mTORC1 initiates Tfr cell differentiation by activating the TCF-1-Bcl-6 axis during immunization or infection.

Identification of significant gene expression changes in multiple perturbation experiments using knockoffs.

Large-scale multiple perturbation experiments have the potential to reveal a more detailed understanding of the molecular pathways that respond to genetic and environmental changes. A key question in these studies is which gene expression changes are important for the response to the perturbation. This problem is challenging because (i) the functional form of the nonlinear relationship between gene expression and the perturbation is unknown and (ii) identification of the most important genes is a high-dimensional variable selection problem. To deal with these challenges, we present here a method based on the model-X knockoffs framework and Deep Neural Networks to identify significant gene expression changes in multiple perturbation experiments. This approach makes no assumptions on the functional form of the dependence between the responses and the perturbations and it enjoys finite sample false discovery rate control for the selected set of important gene expression responses. We apply this approach to the Library of Integrated Network-Based Cellular Signature data sets which is a National Institutes of Health Common Fund program that catalogs how human cells globally respond to chemical, genetic and disease perturbations. We identified important genes whose expression is directly modulated in response to perturbation with anthracycline, vorinostat, trichostatin-a, geldanamycin and sirolimus. We compare the set of important genes that respond to these small molecules to identify co-responsive pathways. Identification of which genes respond to specific perturbation stressors can provide better understanding of the underlying mechanisms of disease and advance the identification of new drug targets.

ReProMSig: an integrative platform for development and application of reproducible multivariable models for cancer prognosis supporting guideline-based transparent reporting.

Adequate reporting is essential for evaluating the performance and clinical utility of a prognostic prediction model. Previous studies indicated a prevalence of incomplete or suboptimal reporting in translational and clinical studies involving development of multivariable prediction models for prognosis, which limited the potential applications of these models. While reporting templates introduced by the established guidelines provide an invaluable framework for reporting prognostic studies uniformly, there is a widespread lack of qualified adherence, which may be due to miscellaneous challenges in manual reporting of extensive model details, especially in the era of precision medicine. Here, we present ReProMSig (Reproducible Prognosis Molecular Signature), a web-based integrative platform providing the analysis framework for development, validation and application of a multivariable prediction model for cancer prognosis, using clinicopathological features and/or molecular profiles. ReProMSig platform supports transparent reporting by presenting both methodology details and analysis results in a strictly structured reporting file, following the guideline checklist with minimal manual input needed. The generated reporting file can be published together with a developed prediction model, to allow thorough interrogation and external validation, as well as online application for prospective cases. We demonstrated the utilities of ReProMSig by development of prognostic molecular signatures for stage II and III colorectal cancer respectively, in comparison with a published signature reproduced by ReProMSig. Together, ReProMSig provides an integrated framework for development, evaluation and application of prognostic/predictive biomarkers for cancer in a more transparent and reproducible way, which would be a useful resource for health care professionals and biomedical researchers.

SPHK1/S1P/S1PR pathway promotes the progression of peritoneal fibrosis by mesothelial-mesenchymal transition.

Long-term exposure to non-physiologically compatible dialysate inevitably leads to peritoneal fibrosis (PF) in patients undergoing peritoneal dialysis (PD), and there is no effective prevention or treatment for PF. Sphingosine-1-phosphate (S1P) is a bioactive sphingolipid produced after catalysis by sphingosine kinase (SPHK) 1/2 and activates signals through the S1P receptor (S1PR) via autocrine or paracrine. However, the role of SPHK1/S1P/S1PR signaling has never been elucidated in PF. In our research, we investigated S1P levels in peritoneal effluents and demonstrated the role of SPHK1/S1P/S1PR pathway in peritoneal fibrosis. It was found that S1P levels in peritoneal effluents were positively correlated with D/P Cr (r = 0.724, p < .001) and negatively correlated with 4 h ultrafiltration volume (r = -0.457, p < .001). S1PR1 and S1PR3 on peritoneal cells were increased after high glucose exposure in vivo and in vitro. Fingolimod was applied to suppress S1P/S1PR pathway. Fingolimod restored mouse peritoneal function by reducing interstitial hyperplasia, maintaining ultrafiltration volume, reducing peritoneal transport solute rate, and mitigating the protein expression changes of fibronectin, vimentin, α-SMA, and E-cadherin induced by PD and S1P. Fingolimod preserved the morphology of the human peritoneal mesothelial cells, MeT-5A, and moderated the mesothelial-mesenchymal transition (MMT) process. We further delineated that SPHK1 was elevated in peritoneal cells after high glucose exposure and suppression of SPHK1 in MeT-5A cells reduced S1P release. Overexpression of SPHK1 in MeT-5A cells increased S1P levels in the supernatant and fostered the MMT process. PF-543 treatment, targeting SPHK1, alleviated deterioration of mouse peritoneal function. In conclusion, S1P levels in peritoneal effluent were correlated with the deterioration of peritoneal function. SPHK1/S1P/S1PR pathway played an important role in PF.

Memory deficit in patients with cerebral small vessel disease: evidence from eye tracking technology.

Cerebral small vessel disease is the one of the most prevalent causes of vascular cognitive impairment. We aimed to find objective and process-based indicators related to memory function to assist in the detection of memory impairment in patients with cerebral small vessel disease. Thirty-nine cerebral small vessel disease patients and 22 healthy controls were invited to complete neurological examinations, neuropsychological assessments, and eye tracking tasks. Eye tracking indicators were recorded and analyzed in combination with imaging features. The cerebral small vessel disease patients scored lower on traditional memory task and performed worse on eye tracking memory task performance compared to the healthy controls. The cerebral small vessel disease patients exhibited longer visit duration and more visit count within areas of interest and targets and decreased percentage value of total visit duration on target images to total visit duration on areas of interest during decoding stage among all levels. Our results demonstrated the cerebral small vessel disease patients performed worse in memory scale and eye tracking memory task, potentially due to their heightened attentional allocation to nontarget images during the retrieval stage. The eye tracking memory task could provide process-based indicators to be a beneficial complement to memory assessment and new insights into mechanism of memory impairment in cerebral small vessel disease patients.

TMEM120B strengthens breast cancer cell stemness and accelerates chemotherapy resistance via ß1-integrin/FAK-TAZ-mTOR signaling axis by binding to MYH9.

BACKGROUND: Breast cancer stem cell (CSC) expansion results in tumor progression and chemoresistance; however, the modulation of CSC pluripotency remains unexplored. Transmembrane protein 120B (TMEM120B) is a newly discovered protein expressed in human tissues, especially in malignant tissues; however, its role in CSC expansion has not been studied. This study aimed to determine the role of TMEM120B in transcriptional coactivator with PDZ-binding motif (TAZ)-mediated CSC expansion and chemotherapy resistance. METHODS: Both bioinformatics analysis and immunohistochemistry assays were performed to examine expression patterns of TMEM120B in lung, breast, gastric, colon, and ovarian cancers. Clinicopathological factors and overall survival were also evaluated. Next, colony formation assay, MTT assay, EdU assay, transwell assay, wound healing assay, flow cytometric analysis, sphere formation assay, western blotting analysis, mouse xenograft model analysis, RNA-sequencing assay, immunofluorescence assay, and reverse transcriptase-polymerase chain reaction were performed to investigate the effect of TMEM120B interaction on proliferation, invasion, stemness, chemotherapy sensitivity, and integrin/FAK/TAZ/mTOR activation. Further, liquid chromatography-tandem mass spectrometry analysis, GST pull-down assay, and immunoprecipitation assays were performed to evaluate the interactions between TMEM120B, myosin heavy chain 9 (MYH9), and CUL9. RESULTS: TMEM120B expression was elevated in lung, breast, gastric, colon, and ovarian cancers. TMEM120B expression positively correlated with advanced TNM stage, lymph node metastasis, and poor prognosis. Overexpression of TMEM120B promoted breast cancer cell proliferation, invasion, and stemness by activating TAZ-mTOR signaling. TMEM120B directly bound to the coil-coil domain of MYH9, which accelerated the assembly of focal adhesions (FAs) and facilitated the translocation of TAZ. Furthermore, TMEM120B stabilized MYH9 by preventing its degradation by CUL9 in a ubiquitin-dependent manner. Overexpression of TMEM120B enhanced resistance to docetaxel and doxorubicin. Conversely, overexpression of TMEM120B-∆CCD delayed the formation of FAs, suppressed TAZ-mTOR signaling, and abrogated chemotherapy resistance. TMEM120B expression was elevated in breast cancer patients with poor treatment outcomes (Miller/Payne grades 1-2) than in those with better outcomes (Miller/Payne grades 3-5). CONCLUSIONS: Our study reveals that TMEM120B bound to and stabilized MYH9 by preventing its degradation. This interaction activated the ß1-integrin/FAK-TAZ-mTOR signaling axis, maintaining stemness and accelerating chemotherapy resistance.

Causal effects of endometriosis on cancer risk: A Mendelian randomization study.

Endometriosis has been reported in epidemiological studies to be associated with certain types of cancer. However, the presence of reverse causality and residual confounding due to common risk factors introduces uncertainty regarding the extent to which endometriosis itself contributes to the development of cancer. We performed the Mendelian randomization (MR) to investigate the causal associations between endometriosis and 34 different types of cancers. The results of the inverse-variance-weighted (IVW) model suggested that genetic predisposition to endometriosis was causally associated with an increased risk for ovarian cancer (OR = 3.2913; p-value = .0320). The genetic liabilities to endometriosis had causal associations with the decreased risk for skin cancer (OR = 0.9973; p-value = .0219), hematological cancer (OR = 0.9953; p-value = .0175) and ER- breast cancer (OR = 0.6960; p-value = .0381). The causal association of the above combinations were robust by test of heterogeneity and pleiotropy. Together, our study suggests that endometriosis had causal effect on cancer risk.

Biomarker-Driven DNA-Functionalized Colloidal Programmed Simultaneous Assembly and Disassembly in Cells.

Complex structures and devices, both natural and artificial, can often undergo assembly and disassembly. Assembly and disassembly allow multiple stimuli to initiate, for example, the assembly and disassembly of primary cilia under the control of E3 ubiquitin ligases and deubiquitinases. Although biology relies on such schemes, they are rarely available in materials science. Here, we demonstrate a DNA-functionalized colloidal Au response to endogenous biomarkers to trigger simultaneous assembly and disassembly techniques. Colloidal Au is initially inert because the starting DNA strands are paired and prehybridized. TK1 mRNA competes to bind one of the paired strands and release its complement. The released complement binds to the next colloidal Au to initiate assembly, and APE1 can shear the colloidal Au assembly binding site to initiate disassembly. Our strategy provides temporal and spatial logic control during colloidal Au assembly and disassembly, and this simultaneous assembly and disassembly process can be used for sequential detection and cellular imaging of two biomarkers, effectively reducing signal false-positive results and shortening detection time. This work highlights biomarker-controlled colloidal Au simultaneous assembly and disassembly in ways that are simple and versatile, with the potential to enrich the application scope of DNA nanotechnology and provide an idea for the application of precision medicine testing.

ChloroDBPFinder: Machine Learning-Guided Recognition of Chlorinated Disinfection Byproducts from Nontargeted LC-HRMS Analysis.

High-resolution mass spectrometry (HRMS) is a prominent analytical tool that characterizes chlorinated disinfection byproducts (Cl-DBPs) in an unbiased manner. Due to the diversity of chemicals, complex background signals, and the inherent analytical fluctuations of HRMS, conventional isotopic pattern (37Cl/35Cl), mass defect, and direct molecular formula (MF) prediction are insufficient for accurate recognition of the diverse Cl-DBPs in real environmental samples. This work proposes a novel strategy to recognize Cl-containing chemicals based on machine learning. Our hierarchical machine learning framework has two random forest-based models: the first layer is a binary classifier to recognize Cl-containing chemicals, and the second layer is a multiclass classifier to annotate the number of Cl present. This model was trained using ∼1.4 million distinctive MFs from PubChem. Evaluated on over 14,000 unique MFs from NIST20, this machine learning model achieved 93.3% accuracy in recognizing Cl-containing MFs (Cl-MFs) and 92.9% accuracy in annotating the number of Cl for Cl-MFs. Furthermore, the trained model was integrated into ChloroDBPFinder, a standalone R package for the streamlined processing of LC-HRMS data and annotating both known and unknown Cl-containing compounds. Tested on existing Cl-DBP data sets related to aspartame chlorination in tap water, our ChloroDBPFinder efficiently extracted 159 Cl-containing DBP features and tentatively annotated the structures of 10 Cl-DBPs via molecular networking. In another application of a chlorinated humic substance, ChloroDBPFinder extracted 79 high-quality Cl-DBPs and tentatively annotated six compounds. In summary, our proposed machine learning strategy and the developed ChloroDBPFinder provide an advanced solution to identifying Cl-containing compounds in nontargeted analysis of water samples. It is freely available on GitHub (https://github.com/HuanLab/ChloroDBPFinder).

Plasmonic Gold Nanostar-Based Probes with Distance-Dependent Plasmon-Enhanced Fluorescence for Ultrasensitive DNA Methyltransferase Assay.

The ultrasensitive DNA methyltransferase (Dam MTase) assay is of high significance for biomedical research and clinical diagnosis because of its profound effect on gene regulation. However, detection sensitivity is still limited by shortcomings, including photobleaching and weak signal intensities of conventional fluorophores at low concentrations. Plasmonic nanostructures with ultrastrong electromagnetic fields and fluorescence enhancement capability that can overcome these intrinsic defects hold great potential for ultrasensitive bioanalysis. Herein, a silica-coated gold nanostars (Au NSTs@SiO2)-based plasmon-enhanced fluorescence (PEF) probe with 20 "hot spots" was developed for ultrasensitive detection of Dam MTase. Here, the Dam Mtase assay was achieved by detecting the byproduct PPi of the rolling circle amplification reaction. It is worth noting that, benefiting from the excellent fluorescence enhancement capability of Au NSTs originating from their 20 "hot spots", the detection limit of Dam Mtase was reduced by nearly 105 times. Moreover, the proposed Au NST-based PEF probe enabled versatile evaluation of Dam MTase inhibitors as well as endogenous Dam MTase detection in GW5100 and JM110 Escherichia coli cell lysates, demonstrating its potential in biomedical analysis.

Pain/Stress, Mitochondrial Dysfunction and Neurodevelopment in Preterm Infants.

Introduction Preterm infants experience tremendous early life pain/stress during their neonatal intensive care unit (NICU) hospitalization, which impacts their neurodevelopmental outcomes. Mitochondrial function/dysfunction may interface between perinatal stress events and neurodevelopment. Nevertheless, the specific proteins or pathways linking mitochondrial functions to pain-induced neurodevelopmental outcomes in infants are remain unidentified. Our study aims to investigate the associations among pain/stress, proteins associated with mitochondrial function/dysfunction, and neurobehavioral responses in preterm infants. Methods We conducted a prospective cohort study, enrolling 33 preterm infants between September 2017 and July 2022 at two affiliated NICUs located in Hartford and Farmington, CT. NICU Network Neurobehavioral Scale (NNNS) datasets were evaluated to explore potential association with neurobehavioral outcomes. The daily pain/stress experienced by infant's during their NICU stay was documented. At 36-38 weeks post-menstrual age (PMA), neurobehavioral outcomes were evaluated using the NNNS and buccal swabs were collected for further analysis. Mass spectrometry-based proteomics was conducted on epithelial cells obtained from buccal swabs to evaluate protein expression level. Lasso statistical methods were conducted to study the association between protein abundance and infants' NNNS summary scores. Multiple linear regression and Gene Ontology (GO) enrichment analyses were performed to examine how clinical characteristics and neurodevelopmental outcomes may be associated with protein levels and underlying molecular pathways. Results During NICU hospitalization, preterm premature rupture of membrane (PPROM) were negatively associated with neurobehavioral outcomes. The protein functions including leptin receptor binding activity, glutathione disulfide oxidoreductase activity and response to oxidative stress, lipid metabolism, phosphate and proton transmembrane transporter activity were negatively associated with neurobehavioral outcomes, in the contrast, cytoskeletal regulation, epithelial barrier and protection function were found to be associated with the optimal neurodevelopmental outcomes. In addition, mitochondrial function associated proteins including SPRR2A, PAIP1, S100A3, MT-CO2, PiC, GLRX, PHB2, and BNIPL-2 demonstrated positive association with favorable neurodevelopmental outcomes, while proteins of ABLIM1, UNC45A, Keratins, MUC1, and CYB5B showed positive association with adverse neurodevelopmental outcomes. Conclusion Mitochondrial function-related proteins were observed to be associated with early life pain/stress and neurodevelopmental outcomes in infants. Large-scale studies with longitudinal datasets are warranted. Buccal proteins could be used to predict potential neurobehavioral outcomes.

Potato calcium sensor modules StCBL3-StCIPK7 and StCBL3-StCIPK24 negatively regulate plant immunity.

BACKGROUND: Potato late blight, caused by Phytophthora infestans, is the most devastating disease on potato. Dissecting critical immune components in potato will be supportive for engineering P. infestans resistance. Upon pathogens attack, plant Ca2+ signature is generated and decoded by an array of Ca2+ sensors, among which calcineurin B-like proteins (CBLs) coupled with plant specific CBL-interacting protein kinases (CIPKs) are much less explored in plant immunity. RESULTS: In this study, we identified that two differential potato CBL-CIPK modules regulate plant defense responses against Phytophthora and ROS production, respectively. By deploying virus-induced gene silencing (VIGS) system-based pathogen inoculation assays, StCBL3 was shown to negatively regulate Phytophthora resistance. Consistently, StCBL3 was further found to negatively regulate PTI and ETI responses in Nicotiana benthamiana. Furthermore, StCIPK7 was identified to act together with StCBL3 to negatively regulate Phytophthora resistance. StCIPK7 physically interacts with StCBL3 and phosphorylates StCBL3 in a Ca2+-dependent manner. StCBL3 promotes StCIPK7 kinase activity. On the other hand, another StCBL3-interacting kinase StCIPK24 negatively modulating flg22-triggered accumulation of reactive oxygen species (ROS) by interacting with StRBOHB. CONCLUSIONS: Together, these findings demonstrate that the StCBL3-StCIPK7 complex negatively modulates Phytophthora resistance and StCBL3-StCIPK24 complex negatively regulate ROS production. Our results offer new insights into the roles of potato CBL-CIPK in plant immunity and provide valuable gene resources to engineer the disease resistance potato in the future.

diseaseGPS: auxiliary diagnostic system for genetic disorders based on genotype and phenotype.

SUMMARY: The next-generation sequencing brought opportunities for the diagnosis of genetic disorders due to its high-throughput capabilities. However, the majority of existing methods were limited to only sequencing candidate variants, and the process of linking these variants to a diagnosis of genetic disorders still required medical professionals to consult databases. Therefore, we introduce diseaseGPS, an integrated platform for the diagnosis of genetic disorders that combines both phenotype and genotype data for analysis. It offers not only a user-friendly GUI web application for those without a programming background but also scripts that can be executed in batch mode for bioinformatics professionals. The genetic and phenotypic data are integrated using the ACMG-Bayes method and a novel phenotypic similarity method, to prioritize the results of genetic disorders. diseaseGPS was evaluated on 6085 cases from Deciphering Developmental Disorders project and 187 cases from Shanghai Children's hospital. The results demonstrated that diseaseGPS performed better than other commonly used methods. AVAILABILITY AND IMPLEMENTATION: diseaseGPS is available to freely accessed at https://diseasegps.sjtu.edu.cn with source code at https://github.com/BioHuangDY/diseaseGPS.

Optimization of Mach-Zehnder interferometer of high-spectral-resolution lidar for large-scale wind measurement.

The optimization design of a quadri-channel Mach-Zehnder interferometer (QMZI) of the high-spectral-resolution lidar is presented for the large-scale wind measurement. The optimized QMZI can discriminate the Doppler frequency shift generated by atmospheric wind from aerosol Mie scattering echo signals and molecular Rayleigh scattering echo signals, and then the wind information can be retrieved. The optimal optical path differences (OPDs) of QMZI are determined by theoretical and simulation analysis. The wind measurement simulation experiments prove that the designed QMZI can measure the large-scale wind with an accuracy of meter level.

Modified Gexia-Zhuyu Tang inhibits gastric cancer progression by restoring gut microbiota and regulating pyroptosis.

BACKGROUND: Gexia-Zhuyu Tang (GZT), a traditional Chinese medicine formula, is used to treat a variety of diseases. However, its roles in gastric cancer (GC) remain unclear. OBJECTIVE: The aim of this study was to explore the roles and underlying molecular mechanisms of modified GZT in GC. METHODS: The effects of modified GZT on GC were investigated by constructing mouse xenograft models with MFC cell line. The fecal samples from low-dose, high-dose, and without modified GZT treatment groups were collected for the 16S rRNA gene sequencing and fecal microbiota transplantation (FMT). Histopathological alterations of mice were evaluated using the hematoxylin-eosin (HE). Immunohistochemical (IHC) analysis with Ki67 and GSDMD was performed to measure tissue cell proliferation and pyroptosis, respectively. Proteins associated with pyroptosis, invasion, and metastasis were detected by Western blotting. Enzyme-linked immunosorbent assay (ELISA) was used to assess inflammation-related factors levels. RESULTS: Modified GZT inhibited GC tumor growth and reduced metastasis and invasion-related proteins expression levels, including CD147, VEGF, and MMP-9. Furthermore, it notably promoted caspase-1-dependent pyroptosis, as evidenced by a dose-dependent increase in TNF-α, IL-1ß, IL-18, and LDH levels, along with elevated protein expression of NLRP3, ASC, and caspase-1. Additionally, modified GZT increased species abundance and diversity of the intestinal flora. FMT assay identified that modified GZT inhibited GC tumor progression through regulation of intestinal flora. CONCLUSIONS: Modified GZT treatment may promote pyroptosis by modulating gut microbiota in GC. This study identifies a new potential approach for the GC clinical treatment.

Exosomal circBBS2 inhibits ferroptosis by targeting miR-494 to activate SLC7A11 signaling in ischemic stroke.

Umbilical cord-mesenchymal stem cells (UC-MSCs)-derived exosomes have been considered as an effective treatment for ischemic stroke. CircRNA BBS2 (circBBS2) was demonstrated to be down-regulated in patients with ischemic stroke. However, the role of UC-MSCs-derived exosomal circBBS2 in ischemic stroke and potential mechanisms remain unclear. Hypoxia/reperfusion (H/R)-exposed SH-SY5Y cells and middle cerebral artery occlusion (MCAO)-treated rats were served as in vitro and in vivo models of ischemic stroke. Target gene expression was detected by qRT-PCR. Cell viability was assessed by MTT assay. Ferroptosis was determined by iron, MDA, GSH, and lipid ROS levels. Protein levels were measured by Western blotting. The target relationships among circBBS2, miR-494, and SLC7A11 were validated by RNA-pull down, RIP, and dual-luciferase reporter assays. TTC and HE staining were performed to evaluate cerebral infarction volume and neuropathological changes. circBBS2 was lowly expressed and ferroptosis was triggered in MCAO rats and H/R-stimulated SH-SY5Y cells. UC-MSCs-derived exosomes enhanced cell viability and restrained ferroptosis via increasing circBBS2 expression in SH-SY5Y cells. Mechanistically, circBBS2 sponged miR-494 to enhance the SLC7A11 level. Knockdown of miR-494 or SLC7A11 reversed the effects of silencing circBBS2 or miR-494 on ferroptosis of SH-SY5Y cells, respectively. Furthermore, UC-MSCs-derived exosomes attenuated ischemic stroke in rats via delivering circBBS2 to inhibit ferroptosis. UC-MSCs-derived exosomal circBBS2 enhanced SLC7A11 expression via sponging miR-494, therefore repressing ferroptosis and relieving ischemic stroke. Our findings shed light on a novel mechanism for UC-MSCs-derived exosomes in the treatment of ischemic stroke.

Advances in performance degradation mechanism and safety assessment of LiFePO4for energy storage.

In the context of 'energy shortage', developing a novel energy-based power system is essential for advancing the current power system towards low-carbon solutions. As the usage duration of lithium-ion batteries for energy storage increases, the nonlinear changes in their aging process pose challenges to accurately assess their performance. This paper focuses on the study LiFeO4(LFP), used for energy storage, and explores their performance degradation mechanisms. Furthermore, it introduces common battery models and data structures and algorithms, which used for predicting the correlation between electrode materials and physical parameters, applying to state of health assessment and thermal warning. This paper also discusses the establishment of digital management system. Compared to conventional battery networks, dynamically reconfigurable battery networks can realize real-time monitoring of lithium-ion batteries, and reduce the probability of fault occurrence to an acceptably low level.