Improving Prediction of Survival and Progression in Metastatic Non-Small Cell Lung Cancer After Immunotherapy Through Machine Learning of Circulating Tumor DNA.

PURPOSE: To use modern machine learning approaches to enhance and automate the feature extraction from the longitudinal circulating tumor DNA (ctDNA) data and to improve the prediction of survival and disease progression, risk stratification, and treatment strategies for patients with 1L non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: Using IMpower150 trial data on patients with untreated metastatic NSCLC treated with atezolizumab and chemotherapies, we developed a machine learning algorithm to extract predictive features from ctDNA kinetics, improving survival and progression prediction. We analyzed kinetic data from 17 ctDNA summary markers, including cell-free DNA concentration, allele frequency, tumor molecules in plasma, and mutation counts. RESULTS: Three hundred and ninety-eight patients with ctDNA data (206 in training and 192 in validation) were analyzed. Our models outperformed existing workflow using conventional temporal ctDNA features, raising overall survival (OS) concordance index to 0.72 and 0.71 from 0.67 and 0.63 for C3D1 and C4D1, respectively, and substantially improving progression-free survival (PFS) to approximately 0.65 from the previous 0.54-0.58, a 12%-20% increase. Additionally, they enhanced risk stratification for patients with NSCLC, achieving clear OS and PFS separation. Distinct patterns of ctDNA kinetic characteristics (eg, baseline ctDNA markers, depth of ctDNA responses, and timing of ctDNA clearance, etc) were revealed across the risk groups. Rapid and complete ctDNA clearance appears essential for long-term clinical benefit. CONCLUSION: Our machine learning approach offers a novel tool for analyzing ctDNA kinetics, extracting critical features from longitudinal data, improving our understanding of the link between ctDNA kinetics and progression/mortality risks, and optimizing personalized immunotherapies for 1L NSCLC.

Study on the affinity sites of cadmium's binding to ligands by thermodynamics and nuclear magnetic resonance spectroscopy.

The affinity sites of cadmium (Cd(II)) when binding to cysteine (Cys) and glutathione (GSH) were studied via thermodynamics and nuclear magnetic resonance (NMR) spectroscopy methods. The results showed that the Cd(II) binding sites of Cys and GSH were -SH (exothermic), -NH2 (endothermic) and -COOH (endothermic). The thermodynamic behaviour of Cd(II) binding to Cys/GSH in boric acid and HEPES buffers differed, with the former being mainly endothermic and the latter mainly exothermic. It could be inferred that, in the boric acid system, the main binding site of Cd(II) with Cys and GSH is changed from -SH in HEPES to -COOH and -NH2 in boric acid. This was confirmed by the results of NMR experiments of Cd(II) with Cys/GSH. 1D 1H-NMR experiments showed that, after the combination of Cd(II) and Cys, the changes in the chemical shifts and peak strengths of protons near the -SH group for the reaction in HEPES were greater than when boric acid buffer was used. Changes in the chemical shift and peak strength of the -NH2 protons due to the binding of Cd(II) to GSH were evident in the boric acid buffer but not in HEPES. The screening of functional monomers is very important in the process of preparation of cadmium ion-imprinted materials. This research provides important theoretical and experimental guidance for the screening of functional monomers.

Exploring the chemical diversity of sesquiterpenes from the rarely studied south China sea soft coral Sinularia tumulosa assisted by molecular networking strategy.

Molecular networking strategy-based prioritization of the isolation of the rarely studied soft coral Sinularia tumulosa yielded 14 sesquiterpenes. These isolated constituents consisted of nine different types of carbon frameworks, namely asteriscane, humulane, capillosane, seco-asteriscane, guaiane, dumortane, cadinane, farnesane, and benzofarnesane. Among them, situmulosaols A-C (1, 3 and 4) were previously undescribed ones, whose structures with absolute configurations were established by the combination of extensive spectral data analyses, quantum mechanical-nuclear magnetic resonance and time-dependent density functional theory electronic circular dichroism calculations, the Snatzke's method, and the modified Mosher's method. Notably, situmulosaol C (4) was the second member of capillosane-type sesquiterpenes. The plausible biogenetic relationships of these skeletally different sesquiterpenes were proposed. All sesquiterpenoids were evaluated for their antibacterial, cytotoxic and anti-inflammatory effects. The bioassay results showed compound 14 exhibited significant antibacterial activities against a variety of fish and human pathogenic bacteria with MIC90 values ranging from 3.6 to 33.8 µg/mL. Moreover, moderate cytotoxic effects against HEL cells for components 13 and 14 and moderate inhibitory effect on lipopolysaccharide-induced inflammatory responses in RAW264.7 cells for substance 13 were also observed.

Relationship between chemokine/chemokine receptor and glioma prognosis and outcomes: Systematic review and meta-analysis.

BACKGROUND: Glioma is a primary tumor originating from the central nervous system, and despite ongoing efforts to improve treatment, its overall survival rate remains low. There are a limited number of reports regarding the clinical grading, prognostic impact, and utility of chemokines. Therefore, conducting a meta-analysis is necessary to obtain convincing and conclusive results. METHODS: A comprehensive literature search was conducted using various databases, including PubMed, Web of Science, The Cochrane Library, Embase, Ovid Medline, CNKI, Wanfang Database, VIP, and CBM. The search encompassed articles published from the inception of the databases until March 2024. The estimated odds ratio (ORs), standard mean difference (SMDs), and hazard ratio (HR) with their corresponding 95% confidence intervals (95% CI) were calculated to assess the predictive value of chemokine and receptor levels in glioma risk. Additionally, heterogeneity tests and bias tests were performed to evaluate the reliability of the findings. RESULTS: This meta-analysis included a total of 36 studies, involving 2,480 patients diagnosed with glioma. The results revealed a significant association between the expression levels of CXCR4 (n = 8; OR = 22.28; 95 % CI = 11.47-43.30; p = 0.000), CXCL12 (n = 4; OR = 10.69; 95 % CI = 7.03-16.24; p = 0.000), CCL2 (n = 6; SMD = -0.83; 95 % CI = -0.98--0.67; p = 0.000), CXCL8 (n = 3; SMD = 0.75; 95 % CI = 0.47-1.04; p = 0.000), CXCR7 (n = 3; OR = 20.66; 95 % CI = 10.20-41.82; p = 0.000), CXCL10 (n = 2; SMD = 3.27; 95 % CI = 2.91-3.62; p = 0.000) and the risk of glioma. Additionally, a significant correlation was observed between CXCR4 (n = 8; OR = 4.39; 95 % CI = 3.04-6.32; p = 0.000), (n = 6; SMD = 1.37; 95 % CI = 1.09-1.65; p = 0.000), CXCL12 (n = 6; OR = 6.30; 95 % CI = 3.87-10.25; p = 0.000), (n = 5; ES = 2.25; 95 % CI = 1.15-3.34; p = 0.041), CCL2 (n = 3; OR = 9.65; 95 % CI = 4.55-20.45; p = 0.000), (n = 4; SMD = -1.47; 95 % CI = -1.68--1.26; p = 0.000), and CCL18 (n = 3; SMD = 1.62; 95 % CI = 1.30-1.93; p = 0.000) expression levels and high-grade glioma (grades 3-4). Furthermore, CXCR4 (HR = 2.38, 95 % CI = 1.66-3.40; p = 0.000) exhibited a strong correlation with poor overall survival (OS) rates in glioma patients. CONCLUSION: The findings of this study showed a robust association between elevated levels of CXCR4, CXCL12, CCL2, CXCL8, CXCL10 and CXCR7 with a higher risk of glioma. Furthermore, the WHO grading system was validated by the strong correlation shown between higher expression of CXCR4, CXCL12, CCL2, and CCL18 and WHO high-grade gliomas (grades 3-4). Furthermore, the results of the meta-analysis suggested that CXCR4 might be a helpful biomarker for predicting the worse prognosis of glioma patients.

Berberine alleviates neuroinflammation by downregulating NFκB/LCN2 pathway in sepsis-associated encephalopathy: network pharmacology, bioinformatics, and experimental validation.

BACKGROUND: Sepsis refers to a systemic inflammatory response caused by infection, involving multiple organs. Sepsis-associated encephalopathy (SAE), as one of the most common complications in patients with severe sepsis, refers to the diffuse brain dysfunction caused by sepsis without central nervous system infection. However, there is no clear diagnostic criteria and lack of specific diagnostic markers. METHODS: The main active ingredients of coptidis rhizoma(CR) were identified from TCMSP and SwissADME databases. SwissTargetPrediction and PharmMapper databases were used to obtain targets of CR. OMIM, DisGeNET and Genecards databases were used to explore targets of SAE. Limma differential analysis was used to identify the differential expressed genes(DEGs) in GSE167610 and GSE198861 datasets. WGCNA was used to identify feature module. GO and KEGG enrichment analysis were performed using Metascape, DAVID and STRING databases. The PPI network was constructed by STRING database and analyzed by Cytoscape software. AutoDock and PyMOL software were used for molecular docking and visualization. Cecal ligation and puncture(CLP) was used to construct a mouse model of SAE, and the core targets were verified in vivo experiments. RESULTS: 277 common targets were identified by taking the intersection of 4730 targets related to SAE and 509 targets of 9 main active ingredients of CR. 52 common DEGs were mined from GSE167610 and GSE198861 datasets. Among the 25,864 DEGs in GSE198861, LCN2 showed the most significant difference (logFC = 6.9). GO and KEGG enrichment analysis showed that these 52 DEGs were closely related to "inflammatory response" and "innate immunity". A network containing 38 genes was obtained by PPI analysis, among which LCN2 ranked the first in Degree value. Molecular docking results showed that berberine had a well binding affinity with LCN2. Animal experiments results showed that berberine could inhibit the high expression of LCN2,S100A9 and TGM2 induced by CLP in the hippocampus of mice, as well as the high expression of inflammatory factors (TNFα, IL-6 and IL-1ß). In addition, berberine might reduce inflammation and neuronal cell death by partially inhibiting NFκB/LCN2 pathway in the hippocampus of CLP models, thereby alleviating SAE. CONCLUSION: Overall, Berberine may exert anti-inflammatory effects through multi-ingredients, multi-targets and multi-pathways to partially rescue neuronal death and alleviate SAE.

A review of phyto- and microbial-remediation of indoor volatile organic compounds.

Volatile organic compounds (VOCs) are crucial air pollutants in indoor environments, emitted from building materials, furniture, consumer products, cleaning products, smoking, fuel combustion, cooking, and other sources. VOCs are also emitted from human beings via breath and whole-body skin. Some VOCs cause dermal/ocular irritation as well as gastrointestinal, neurological, cardiovascular, and/or carcinogenic damage to human health. Because people spend most of their time indoors, active control of indoor VOCs has garnered attention. Phytoremediation and microbial remediation, based on plant and microorganism activities, are deemed sustainable, cost-effective, and public-friendly technologies for mitigating indoor VOCs. This study presents the major sources of VOCs in indoor environments and their compositions. Various herbaceous and woody plants used to mitigate indoor VOCs are summarized and their VOCs removal performance is compared. Moreover, this paper reviews the current state of active phytoremediation and microbial remediation for the control of indoor VOCs, and discusses future directions.

Intragraft memory-like CD127hiCD4+Foxp3+ Tregs maintain transplant tolerance.

CD4+Foxp3+ regulatory T cells (Tregs) play an essential role in suppressing transplant rejection, but their role within the graft and heterogeneity in tolerance are poorly understood. Here, we compared phenotypic and transcriptomic characteristics of Treg populations within lymphoid organs and grafts in an islet xenotransplant model of tolerance. We showed Tregs were essential for tolerance induction and maintenance. Tregs demonstrated heterogeneity within the graft and lymphoid organs of tolerant mice. A subpopulation of CD127hi Tregs with memory features were found in lymphoid organs, presented in high proportions within long-surviving islet grafts, and had a transcriptomic and phenotypic profile similar to tissue Tregs. Importantly, these memory-like CD127hi Tregs were better able to prevent rejection by effector T cells, after adoptive transfer into secondary Rag-/- hosts, than naive Tregs or unselected Tregs from tolerant mice. Administration of IL-7 to the CD127hi Treg subset was associated with a strong activation of phosphorylation of STAT5. We proposed that memory-like CD127hi Tregs developed within the draining lymph node and underwent further genetic reprogramming within the graft toward a phenotype that had shared characteristics with other tissue or tumor Tregs. These findings suggested that engineering Tregs with these characteristics either in vivo or for adoptive transfer could enhance transplant tolerance.

TGF-ß2-induced alterations of m6A methylation in hTERT RPE-1 cells.

N6-methyladenosine (m6A) is a major type of RNA modification implicated in various pathophysiological processes. Transforming growth factor ß2 (TGF-ß2) induces epithelial-mesenchymal transition (EMT) in retinal pigmental epithelial (RPE) cells and promotes the progression of proliferative vitreoretinopathy (PVR). However, the role of m6A methylation in the EMT of human telomerase reverse transcriptase (hTERT) retinal pigmental epithelium (RPE)-1 cells has not been clarified. Here, we extracted RNA from RPE cells subjected to 0 or 20 ng/mL TGF-ß2 for 72 h and identified differentially methylated genes (DMGs) by m6A-Seq and differentially expressed genes (DEGs) by RNA-Seq. We selected the genes related to EMT by conjoint m6A-Seq/RNA-Seq analysis and verified them by qRT-PCR. We then confirmed the function of m6A methylation in the EMT of RPE cells by knocking down the methyltransferase METTL3 and the m6A reading protein YTHDF1. Sequencing yielded 5814 DMGs and 1607 DEGs. Conjoint analysis selected 467 genes altered at the m6A and RNA levels that are closely associated with the EMT-related TGF-ß, AGE-RAGE, PI3K-Akt, P53, and Wnt signaling pathways. We also identified ten core EMT genes ACTG2, BMP6, CDH2, LOXL2, SNAIL1, SPARC, BMP4, EMP3, FOXM1, and MYC. Their RNA levels were evaluated by qRT-PCR and were consistent with the sequencing results. We observed that METTL3 knockdown enhanced RPE cell migration and significantly upregulated the EMT markers N-cadherin (encoded by CDH2), fibronectin (FN), Snail family transcription repressor (SLUG), and vimentin. However, YTHDF1 knockdown had the opposite effects and decreased both cell migration and the N-cadherin, FN, and SLUG expression levels. The present study clarified TGF-ß2-induced m6A- and RNA-level differences in RPE cells, indicated that m6A methylation might regulate EMT marker expression, and showed that m6A could regulate TGF-ß2-induced EMT.

A Mobile Applet for Assessing Medication Adherence and Managing Adverse Drug Reactions Among Patients With Cancer: Usability and Utility Study.

BACKGROUND: Medication adherence and the management of adverse drug reactions (ADRs) are crucial to the efficacy of antitumor drugs. A WeChat applet, also known as a "Mini Program," is similar to the app but has marked advantages. The development and use of a WeChat applet makes follow-up convenient for patients with cancer. OBJECTIVE: This study aimed to assess the usability and utility of a newly developed WeChat applet, "DolphinCare," among patients with cancer in Shanghai. METHODS: A qualitative methodology was used to obtain an in-depth understanding of the experiences of patients with cancer when using DolphinCare from the usability and utility aspects. The development phase consisted of 2 parts: alpha and beta testing. Alpha testing combined the theory of the Fogg Behavior Model and the usability model. Alpha testing also involved testing the design of DolphinCare using a conceptual framework, which included factors that could affect medication adherence and ADRs. Beta testing was conducted using in-depth interviews. In-depth interviews allowed us to assist the patients in using DolphinCare and understand whether they liked or disliked DolphinCare and found it useful. RESULTS: We included participants who had an eHealth Literacy Scale (eHEALS) score of ≥50%, and a total of 20 participants were interviewed consecutively. The key positive motivators described by interviewers were to be reminded to take their medications and to alleviate their ADRs. The majority of the patients were able to activate and use DolphinCare by themselves. Most patients indicated that their trigger to follow-up DolphinCare was the recommendation of their known and trusted health care professionals. All participants found that labels containing the generic names of their medication and the medication reminders were useful, including timed pop-up push notifications and text alerts. The applet presented the corresponding information collection forms of ADRs to the patient to fill out. The web-based consultation system enables patients to consult pharmacists or physicians in time when they have doubts about medications or have ADRs. The applet had usabilities and utilities that could improve medication adherence and the management of ADRs among patients with cancer. CONCLUSIONS: This study provides preliminary evidence regarding the usability and utility of this type of WeChat applet among patients with cancer, which is expected to be promoted for managing follow-up among other patients with other chronic disease.

Abnormal metabolism in hepatic stellate cells: Pandora's box of MAFLD related hepatocellular carcinoma.

Metabolic associated fatty liver disease (MAFLD) is a significant risk factor for the development of hepatocellular carcinoma (HCC). Hepatic stellate cells (HSCs), as key mediators in liver injury response, are believed to play a crucial role in the repair process of liver injury. However, in MAFLD patients, the normal metabolic and immunoregulatory mechanisms of HSCs become disrupted, leading to disturbances in the local microenvironment. Abnormally activated HSCs are heavily involved in the initiation and progression of HCC. The metabolic disorders and abnormal activation of HSCs not only initiate liver fibrosis but also contribute to carcinogenesis. In this review, we provide an overview of recent research progress on the relationship between the abnormal metabolism of HSCs and the local immune system in the liver, elucidating the mechanisms of immune imbalance caused by abnormally activated HSCs in MAFLD patients. Based on this understanding, we discuss the potential and challenges of metabolic-based and immunology-based mechanisms in the treatment of MAFLD-related HCC, with a specific focus on the role of HSCs in HCC progression and their potential as targets for anti-cancer therapy. This review aims to enhance researchers' understanding of the importance of HSCs in maintaining normal liver function and highlights the significance of HSCs in the progression of MAFLD-related HCC.

MESBC: A novel mutually exclusive spectral biclustering method for cancer subtyping.

Many soft biclustering algorithms have been developed and applied to various biological and biomedical data analyses. However, few mutually exclusive (hard) biclustering algorithms have been proposed, which could better identify disease or molecular subtypes with survival significance based on genomic or transcriptomic data. In this study, we developed a novel mutually exclusive spectral biclustering (MESBC) algorithm based on spectral method to detect mutually exclusive biclusters. MESBC simultaneously detects relevant features (genes) and corresponding conditions (patients) subgroups and, therefore, automatically uses the signature features for each subtype to perform the clustering. Extensive simulations revealed that MESBC provided superior accuracy in detecting pre-specified biclusters compared with the non-negative matrix factorization (NMF) and Dhillon's algorithm, particularly in very noisy data. Further analysis of the algorithm on real datasets obtained from the TCGA database showed that MESBC provided more accurate (i.e., smaller p-value) overall survival prediction in patients with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) cancers when compared to the existing, gold-standard subtypes for lung cancers (integrative clustering). Furthermore, MESBC detected several genes with significant prognostic value in both LUAD and LUSC patients. External validation on an independent, unseen GEO dataset of LUAD showed that MESBC-derived clusters based on TCGA data still exhibited clear biclustering patterns and consistent, outstanding prognostic predictability, demonstrating robust generalizability of MESBC. Therefore, MESBC could potentially be used as a risk stratification tool to optimize the treatment for the patient, improve the selection of patients for clinical trials, and contribute to the development of novel therapeutic agents.

Image-Based Subtype Classification for Glioblastoma Using Deep Learning: Prognostic Significance and Biologic Relevance.

PURPOSE: To apply deep learning algorithms to histopathology images, construct image-based subtypes independent of known clinical and molecular classifications for glioblastoma, and produce novel insights into molecular and immune characteristics of the glioblastoma tumor microenvironment. MATERIALS AND METHODS: Using whole-slide hematoxylin and eosin images from 214 patients with glioblastoma in The Cancer Genome Atlas (TCGA), a fine-tuned convolutional neural network model extracted deep learning features. Biclustering was used to identify subtypes and image feature modules. Prognostic value of image subtypes was assessed via Cox regression on survival outcomes and validated with 189 samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data set. Morphological, molecular, and immune characteristics of glioblastoma image subtypes were analyzed. RESULTS: Four distinct subtypes and modules (imClust1-4) were identified for the TCGA patients with glioblastoma on the basis of the image feature data. The glioblastoma image subtypes were significantly associated with overall survival (OS; P = .028) and progression-free survival (P = .003). Apparent association was also observed for disease-specific survival (P = .096). imClust2 had the best prognosis for all three survival end points (eg, after 25 months, imClust2 had >7% surviving patients than the other subtypes). Examination of OS in the external validation using the unseen CPTAC data set showed consistent patterns. Multivariable Cox analyses confirmed that the image subtypes carry unique prognostic information independent of known clinical and molecular predictors. Molecular and immune profiling revealed distinct immune compositions of the tumor microenvironment in different image subtypes and may provide biologic explanations for the patterns in patients' outcomes. CONCLUSION: Our image-based subtype classification on the basis of deep learning models is a novel tool to refine risk stratification in cancers. The image subtypes detected for glioblastoma represent a promising prognostic biomarker with distinct molecular and immune characteristics and may facilitate developing novel, individualized immunotherapies for glioblastoma.

[miR-185-5p alleviates the inflammatory response of acute gouty arthritis by inhibiting of IL-1ß].

Objective To investigate the relationship between interleukin-1ß (IL-1ß) and miR-185-5p in the process of joint injury in acute gouty arthritis (AGA). Methods The serum miR-185-5p levels of 89 AGA patients and 91 healthy volunteers were detected by real-time quantitative PCR. The correlation between miR-185-5p expression level and VAS score or IL-1ß expression level was evaluated by Pearson correlation coefficient method. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic value of miR-185-5p in AGA. THP-1 cells were induced by sodium urate (MSU) to construct an in vitro acute gouty inflammatory cell model. After the expression level of miR-185-5p in THP-1 cells was upregulated or downregulated by transfection of miR-185-5p mimics or inhibitors in vitro, inflammatory cytokines of THP-1 cells, such as IL-1ß, IL-8 and tumor necrosis factor α (TNF-α), were detected by ELISA. The luciferase reporter gene assay was used to determine the interaction between miR-185-5p and the 3'-UTR of IL-1ß. Results Compared with the healthy control group, the expression level of serum miR-185-5p in AGA patients was significantly reduced. The level of serum miR-185-5p was negatively correlated with VAS score and IL-1ß expression level. The area under the curve (AUC) was 0.905, the sensitivity was 80.17% and the specificity was 83.52%. Down-regulation of miR-185-5p significantly promoted the expression of IL-1ß, IL-8 and tumor necrosis factor (TNF-α), while overexpression of miR-185-5p showed the opposite results. Luciferase reporter gene assay showed that IL-1ß was the target gene of miR-185-5p, and miR-185-5p negatively regulated the expression of IL-1ß. Conclusion miR-185-5p alleviates the inflammatory response in AGA by inhibiting IL-1ß.

Malonate differentially affects cell survival and confers chemoresistance in cancer cells via the induction of p53-dependent autophagy.

Metabolic network intertwines with cancerous signaling and drug responses. Malonate is a prevailing metabolite in cancer and a competitive inhibitor of succinate dehydrogenase (SDH). Recent studies showed that malonate induced reactive oxygen species (ROS)-dependent apoptosis in neuroblastoma cells, but protected cells from ischemia-reperfusion injury. We here revealed that malonate differentially regulated cell death and survival in cancer cells. While high-dose malonate triggered ROS-dependent apoptosis, the low-dose malonate induced autophagy and conferred resistance to multiple chemotherapeutic agents. Mechanistically, our results showed that malonate increased p53 stability and transcriptionally up-regulated autophagy modulator DRAM (damage-regulated autophagy modulator), thus promoting autophagy. We further proved that autophagy is required for malonate-associated chemoresistance. Collectively, our findings suggest that malonate plays a double-edge function in cancer response to stressors, and highlights a pro-cancer impact of p53-induced autophagy in response to malonate.

Evaluating Prognostic Value of Dynamics of Circulating Lactate Dehydrogenase in Colorectal Cancer Using Modeling and Machine Learning.

Pretreatment serum lactate dehydrogenase (LDH) levels have been associated with poor prognosis in several types of cancer, including metastatic colorectal cancer (mCRC). However, very few models link survival to longitudinal LDH measured repeatedly over time during treatment. We investigated the prognostic value of on-treatment LDH dynamics in mCRC. Using data from two large phase III studies (2L and 3L+ mCRC settings, n = 824 and 210, respectively), we found that integrating longitudinal LDH data with baseline risk factors significantly improved survival prediction. Current LDH values performed best, enhancing discrimination ability (area under the receiver operating characteristic curve) by 4.5~15.4% and prediction accuracy (Brier score) by 3.9~15.0% compared with baseline variables. Combining all longitudinal LDH markers further improved predictive performance. After controlling for baseline covariates and other longitudinal LDH indicators, current LDH levels remained a significant risk factor in mCRC, increasing mortality risk by over 90% (P < 0.001) in 2L patients and 60-70% (P < 0.01) in 3L+ patients per unit increment in current log (LDH). Machine-learning techniques, like functional principal component analysis (FPCA), extracted informative features from longitudinal LDH data, capturing over 99% of variability and allowing prediction of survival. Unsupervised clustering based on the extracted FPCA features stratified patients into three groups with distinct LDH dynamics and survival outcomes. Hence, our approaches offer a valuable and cost-effective way for risk stratification and improves survival prediction in mCRC using LDH trajectories.

Deciphering the pivotal role of people with high-frequency occupational animal exposure in antibiotic resistance transmission between humans and animals.

BACKGROUND: The spread of antibiotic-resistant bacteria (ARB) and antibiotic resistance genes (ARGs) among humans and food-producing animals has been widely reported. However, the transmission routes and associated risk factors remain incompletely understood. METHODS: Here, we used commensal Escherichia coli bacteria strains from faeces of pigs and local citizens [HEG: high exposure group (pig breeders, butchers or restaurant chefs) and LEG: low exposure group (other occupations)] to explore the dynamics of ARB and ARG transmission between animals and humans. RESULTS: Most ARGs (96%) present in pigs were shared with humans. Carriage rates of the shared ARGs suggest two transmission patterns among pigs, the HEG and LEG: one pattern was highest in pigs, gradually decreasing in the HEG and LEG (e.g. floR and cmlA1); the other pattern was increasing from pigs to the HEG but then decreasing in the LEG (e.g. mcr-1.1). Carriage rates of the HEG were higher than in the LEG in both patterns, implicating the HEG as a crucial medium in transmitting ARB and ARGs between food-producing animals and humans. Moreover, frequent inter/intragroup transmission via strains, plasmids and/or mobile elements was evident. Carriage of mcr-1.1 on human-gut-prevalent plasmids possibly promoted its enrichment in the HEG. CONCLUSIONS: The HEG is a crucial factor in transmitting ARB and ARGs between food-producing animals and humans. Rational measures to contain the risks of occupational exposure are urgently needed to keep dissemination of antibiotic resistance in check and safeguard public health.

Bi-steric mTORC1 inhibitors induce apoptotic cell death in tumor models with hyperactivated mTORC1.

The PI3K/AKT/mTOR pathway is commonly dysregulated in cancer. Rapalogs exhibit modest clinical benefit, likely owing to their lack of effects on 4EBP1. We hypothesized that bi-steric mTORC1-selective inhibitors would have greater potential for clinical benefit than rapalogs in tumors with mTORC1 dysfunction. We assessed this hypothesis in tumor models with high mTORC1 activity both in vitro and in vivo. Bi-steric inhibitors had strong growth inhibition, eliminated phosphorylated 4EBP1, and induced more apoptosis than rapamycin or MLN0128. Multiomics analysis showed extensive effects of the bi-steric inhibitors in comparison with rapamycin. De novo purine synthesis was selectively inhibited by bi-sterics through reduction in JUN and its downstream target PRPS1 and appeared to be the cause of apoptosis. Hence, bi-steric mTORC1-selective inhibitors are a therapeutic strategy to treat tumors driven by mTORC1 hyperactivation.

GGNpTCR: A Generative Graph Structure Neural Network for Predicting Immunogenic Peptides for T-cell Immune Response.

Identifying the interactions between T-cell receptor (TCRs) and human antigens is a crucial step in developing new vaccines, diagnostics, and immunotherapy. Current methods primarily focus on learning binding patterns from known TCR binding repertoires by using sequence information alone without considering the binding specificity of new antigens or exogenous peptides that have not appeared in the training set. Furthermore, the spatial structure of antigens plays a critical role in immune studies and immunotherapy, which should be addressed properly in the identification of interacting TCR-antigen pairs. In this study, we introduced a novel deep learning framework based on generative graph structures, GGNpTCR, for predicting interactions between TCR and peptides from sequence information. Results of real data analysis indicate that our model achieved excellent prediction for new antigens unseen in the training data set, making significant improvements compared to existing methods. We also applied the model to a large COVID-19 data set with no antigens in the training data set, and the improvement was also significant. Furthermore, through incorporation of additional supervised mechanisms, GGNpTCR demonstrated the ability to precisely forecast the locations of peptide-TCR interactions within 3D configurations. This enhancement substantially improved the model's interpretability. In summary, based on the performance on multiple data sets, GGNpTCR has made significant progress in terms of performance, universality, and interpretability.

Surgical Inflammation Alters Immune Response to Intraoperative Photodynamic Therapy.

Surgical cytoreduction for patients with malignant pleural mesothelioma (MPM) is used for selected patients as a part of multi-modality management strategy. Our group has previously described the clinical use of photodynamic therapy (PDT), a form of non-ionizing radiation, as an intraoperative therapy option for MPM. Although necessary for the removal of bulk disease, the effects of surgery on residual MPM burden are not understood. In this bedside-to-bench study, Photofrin-based PDT introduced the possibility of achieving a long-term response in murine models of MPM tumors that were surgically debulked by 60% to 90%. Thus, the addition of PDT provided curative potential after an incomplete resection. Despite this success, we postulated that surgical induction of inflammation may mitigate the comprehensive response of residual disease to further therapy. Utilizing a previously validated tumor incision (TI) model, we demonstrated that the introduction of surgical incisions had no effect on acute cytotoxicity by PDT. However, we found that surgically induced inflammation limited the generation of antitumor immunity by PDT. Compared with PDT alone, when TI preceded PDT of mouse tumors, splenocytes and/or CD8+ T cells from the treated mice transferred less antitumor immunity to recipient animals. These results demonstrate that addition of PDT to surgical cytoreduction significantly improves long-term response compared with cytoreduction alone, but at the same time, the inflammation induced by surgery may limit the antitumor immunity generated by PDT. These data inform future potential approaches aimed at blocking surgically induced immunosuppression that might improve the outcomes of intraoperative combined modality treatment. Significance: Although mesothelioma is difficult to treat, we have shown that combining surgery with a form of radiation, photodynamic therapy, may help people with mesothelioma live longer. In this study, we demonstrate in mice that this regimen could be further improved by addressing the inflammation induced as a by-product of surgery.

TIPE2 ameliorates neuroinflammation and cognitive impairment in sepsis-associated encephalopathy through regulating RhoA/ROCK2-NF-κB signaling pathway.

Sepsis-associated encephalopathy (SAE) is an acute brain dysfunction induced by systemic inflammation caused by sepsis and is one of the most common types of encephalopathy in intensive care units. Deteriorative neuroinflammation is closely related to the development of brain injury, which often transforms into common pathological manifestations in patients with severe sepsis. Therefore, taking necessary preventive and protective measures for potential brain injury and promptly reducing neuroinflammatory injury is necessary to improve the long-term prognoses of patients. Tumor necrosis factor-α-induced protein 8-like 2 (TIPE2) can play a significant protective role in septic lung injury, but studies on its expression and role in neurological diseases are rare. In the present study, we found that TIPE2 can expressed in microglia and ameliorate brain injury caused by SAE by suppressing neuroinflammation. The RhoA/ROCK2 pathway is the central coordinator of tissue injury response, and the activation of RhoA participates in the lipopolysaccharide-induced activation of the nuclear factor kappa B (NF-κB) signaling pathway. The activation of RhoA and phosphorylation of NF-κB was enhanced after TIPE2 deficiency. Importantly, TIPE2 negatively regulates inflammatory responses in vivo and in vitro and plays a protective role in SAE by inhibiting the activation of RhoA/ROCK2-NF-κB signaling pathways. The ultimate aim of our proposed project is to provide a theoretical basis for the development of a novel strategy for the early prevention and therapy of SAE.