Developing a Help Desk Service for Enhanced Coordination in Health Informatics Projects: A Sharepoint and Power Automate Approach.

Healthcare projects necessitate effective collaboration between clinical and technical partners, particularly during pivotal phases like lab testing and piloting. However, challenges in coordination often impede seamless collaboration, leading to inefficiencies and delays. This paper presents a comprehensive approach to developing a help desk service tailored for CAREPATH projects, leveraging SharePoint services and Power Automate. The solution aims to bridge communication gaps, foster collaboration, and enhance coordination among clinical and technical partners. Through iterative development and testing, we refined the system based on stakeholder feedback, resulting in streamlined workflows and improved document management. During the lab testing phase, the help desk system demonstrated significant improvements in resolution duration, communication efficiency, and success solution rates. Stakeholder feedback highlighted enhanced collaboration and improved access to project documentation. With successful testing, the help desk is poised for implementation in subsequent phases, promising further enhancements in patient engagement, technology integration, and scalability. These findings underscore the critical role of help desks in healthcare ICT projects, offering a transformative approach to project management and stakeholder collaboration. Future directions include enhancing patient engagement, leveraging advanced technologies, and conducting longitudinal studies to evaluate long-term impact. Embracing these directions will drive positive change, delivering better outcomes for patients and caregivers in healthcare ICT projects.

Advancing Healthcare Through Interoperability: Implementing Scalable Solutions for Patient Data Integration.

Healthcare faces significant challenges in exchanging and utilizing health information across diverse providers, necessitating innovative solutions for improved interoperability. This study presents a comprehensive exploration of scalable technical and semantic solutions for patient care integration, emphasizing the implementation of these solutions within the framework of the Fast Healthcare Interoperability Resources (FHIR) standard. Our approach revolves around the development and deployment of Technical Interoperability Suite (TIS) and Semantic Interoperability Suite (SIS) technology solutions to disparate health information systems, predominantly Electronic Health Records (EHRs) into a unified Patient Care Platform, fostering comprehensive data exchange and utilization. The integration process involves importing data from various EHR systems and transforming imported patient data into FHIR-standardized formats. The provided solution supports various functionalities, including automatic and manual importation of patient data, through standard computer-readable templates. The integration of TIS and SIS solutions is underpinned by a robust technological framework, incorporating technologies such as Typescript, Deno, and document-oriented databases such as MongoDB. The effectiveness of our interoperability solutions was validated through deployment in multinational EU projects: ADLIFE and CAREPATH. The scalability and generalizability of our approach underscore its potential for diverse healthcare settings.

Safety and DIVA Capability of Novel Live Attenuated Classical Swine Fever Marker Vaccine Candidates in Pregnant Sows.

Classical Swine Fever (CSF), a highly contagious viral disease affecting pigs and wild boar, results in significant economic losses in the swine industry. In endemic regions, prophylactic vaccination and stamping-out strategies are used to control CSF outbreaks. However, sporadic outbreaks and persistent infections continue to be reported. Although the conventional attenuated CSF vaccines protect pigs against the disease, they do not allow for the differentiation of infected from vaccinated animals (DIVA), limiting their use as an eradication tool. In this study, three targeted attenuation strategies were employed to generate vaccine candidates based on the current prevalent CSFV group 2 strains GD18 and QZ07: a single deletion of H79 in Erns (QZ07-sdErnsH-KARD), double deletion of H79 and C171 in Erns (GD18-ddErnsHC-KARD and QZ07-ddErnsHC-KARD), and deletion of H79 in Erns combined with a 5-168 amino acids deletion of Npro (GD18-ddNpro-ErnsH-KARD). Additionally, a negative serological marker with four substitutions in a highly conserved epitope in E2 recognized by the monoclonal antibody 6B8 was introduced in each candidate for DIVA purposes. The safety of these four resulting vaccine candidates was evaluated in pregnant sows. Two candidates, GD18-ddErnsHC-KARD and QZ07-sdErnsH-KARD were found to be safe for pregnant sows and unlikely to cause vertical transmission. Both candidates also demonstrated potential to be used as DIVA vaccines, as was shown using a proprietary blocking ELISA based on the 6B8 monoclonal antibody. These results, together with our previous work, constitute a proof-of-concept for the rational design of CSF antigenically marked modified live virus vaccine candidates.

Artemisia argyi polyphenols Attenuates DSS-induced colitis in mice by regulating the structural composition of gut microbiota.

BACKGROUND: Intestinal health is affected by heredity, lifestyle, and structure of gut microbiota. The imbalance of symbiotic and harmful bacteria in gut microbiota may increase the occurrence of colonic inflammation. Supplementary A. muciniphila can improve the survival rate of colitis mice, reduce colon tissue injury, and the expression of anti-inflammatory factors was upregulated. Artemisia argyi has been reported to have anti-inflammatory, antioxidant, bactericidal, and immunomodulatory effects. However, its anti-inflammatory effect and mechanism, and its influence on gut microbiota and metabolites are still unclear yet. PURPOSE: To explore whether Artemisia argyi Polyphenols(AAPs) can alleviate ulcerative colitis (UC) by changing gut microbiota. METHODS: The therapeutic effect of AAPs on colitis was investigated by inducing ulcerative colitis in mice using dextran sodium sulfate (DSS) and administering different doses of AAPs orally to mice. Exploring the levels of inflammatory proteins, oxidative stress proteins, and barrier proteins using western blotting and immunofluorescence, and explored the structural changes of gut microbiota and its metabolites. Meanwhile, in order to explore whether the role of AAPs in alleviating colitis is based on the regulation of gut microbiota structure, we conducted fecal microbiota transplantation (FMT). RESULTS: It showed that AAPs and FMT trial alleviated DSS-induced colonic injury, including clinical parameters and pathological injury of colon tissue, reduction in the expression of inflammatory proteins: IL-6, TNF-α, p-p65, p-IκBα, and increase in the expression of antioxidant proteins: Nrf2, NQO-1 and HO-1 and barrier proteins: Claudin-1, Occludin, ZO-1 and MUC2. AAPs and FMT promoted the content of beneficial bacteria, such as Butyricimonas and Lactobacillus, and the content of beneficial metabolites for instance acetic acid, butyric acid, and valeric acid has also increased. CONCLUSION: These results suggested that AAPs might improve DSS-induced colonic injury by changing the structural of gut microbiota while promoting the synthesis of fatty acids in the intestine, thereby providing a theoretical basis for using AAPs to treat ulcerative colitis.

Mechanistic study of pre-eclampsia and macrophage-associated molecular networks: bioinformatics insights from multiple datasets.

Background: Pre-eclampsia is a pregnancy-related disorder characterized by hypertension and proteinuria, severely affecting the health and quality of life of patients. However, the molecular mechanism of macrophages in pre-eclampsia is not well understood. Methods: In this study, the key biomarkers during the development of pre-eclampsia were identified using bioinformatics analysis. The GSE75010 and GSE74341 datasets from the GEO database were obtained and merged for differential analysis. A weighted gene co-expression network analysis (WGCNA) was constructed based on macrophage content, and machine learning methods were employed to identify key genes. Immunoinfiltration analysis completed by the CIBERSORT method, R package "ClusterProfiler" to explore functional enrichment of these intersection genes, and potential drug predictions were conducted using the CMap database. Lastly, independent analysis of protein levels, localization, and quantitative analysis was performed on placental tissues collected from both preeclampsia patients and healthy control groups. Results: We identified 70 differentially expressed NETs genes and found 367 macrophage-related genes through WGCNA analysis. Machine learning identified three key genes: FNBP1L, NMUR1, and PP14571. These three key genes were significantly associated with immune cell content and enriched in multiple signaling pathways. Specifically, these genes were upregulated in PE patients. These findings establish the expression patterns of three key genes associated with M2 macrophage infiltration, providing potential targets for understanding the pathogenesis and treatment of PE. Additionally, CMap results suggested four potential drugs, including Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin, which may have the potential to reverse pre-eclampsia. Conclusion: Studying the expression levels of three key genes in pre-eclampsia provides valuable insights into the prevention and treatment of this condition. We propose that these genes play a crucial role in regulating the maternal-fetal immune microenvironment in PE patients, and the pathways associated with these genes offer potential avenues for exploring the molecular mechanisms underlying preeclampsia and identifying therapeutic targets. Additionally, by utilizing the Connectivity Map database, we identified drug targets like Ttnpb, Doxorubicin, Tyrphostin AG 825, and Tanespimycin as potential clinical treatments for preeclampsia.

TRABD modulates mitochondrial homeostasis and tissue integrity.

High TRABD expression is associated with tau pathology in patients with Alzheimer's disease; however, the function of TRABD is unknown. Human TRABD encodes a mitochondrial outer-membrane protein. The loss of TRABD resulted in mitochondrial fragmentation, and TRABD overexpression led to mitochondrial clustering and fusion. The C-terminal tail of the TRABD anchored to the mitochondrial outer membrane and the TraB domain could form homocomplexes. Additionally, TRABD forms complexes with MFN2, MIGA2, and PLD6 to facilitate mitochondrial fusion. Flies lacking dTRABD are viable and have normal lifespans. However, aging flies exhibit reduced climbing ability and abnormal mitochondrial morphology in their muscles. The expression of dTRABD is increased in aged flies. dTRABD overexpression leads to neurodegeneration and enhances tau toxicity in fly eyes. The overexpression of dTRABD also increased reactive oxygen species (ROS), ATP production, and protein turnover in the mitochondria. This study suggested that TRABD-induced mitochondrial malfunctions contribute to age-related neurodegeneration.

Histological Subtype Classification of Non-Small Cell Lung Cancer with Radiomics and 3D Convolutional Neural Networks.

Non-small cell lung carcinoma (NSCLC) is the most common type of pulmonary cancer, one of the deadliest malignant tumors worldwide. Given the increased emphasis on the precise management of lung cancer, identifying various subtypes of NSCLC has become pivotal for enhancing diagnostic standards and patient prognosis. In response to the challenges presented by traditional clinical diagnostic methods for NSCLC pathology subtypes, which are invasive, rely on physician experience, and consume medical resources, we explore the potential of radiomics and deep learning to automatically and non-invasively identify NSCLC subtypes from computed tomography (CT) images. An integrated model is proposed that investigates both radiomic features and deep learning features and makes comprehensive decisions based on the combination of these two features. To extract deep features, a three-dimensional convolutional neural network (3D CNN) is proposed to fully utilize the 3D nature of CT images while radiomic features are extracted by radiomics. These two types of features are combined and classified with multi-head attention (MHA) in our proposed model. To our knowledge, this is the first work that integrates different learning methods and features from varied sources in histological subtype classification of lung cancer. Experiments are organized on a mixed dataset comprising NSCLC Radiomics and Radiogenomics. The results show that our proposed model achieves 0.88 in accuracy and 0.89 in the area under the receiver operating characteristic curve (AUC) when distinguishing lung adenocarcinoma (ADC) and lung squamous cell carcinoma (SqCC), indicating the potential of being a non-invasive way for predicting histological subtypes of lung cancer.

Glucose uptake in trophoblasts of GDM mice is regulated by the AMPK-CLUT3 signaling pathway.

GDM, as a metabolic disease during pregnancy, regulates GLUT3 translocation by AMPK, thereby affecting glucose uptake in trophoblasts. It provides a new research idea and therapeutic target for alleviating intrauterine hyperglycemia in GDM. STZ was used to construct GDM mice, inject AICAR into pregnant mice, and observe fetal and placental weight; flow cytometry was employed for the detection of glucose uptake by primary trophoblast cells; immunofluorescence was applied to detect the localization of GLUT3 and AMPK in placental tissue; Cocofal microscope was used to detect the localization of GLUT3 in trophoblast cells;qRT-PCR and Western blot experiments were carried out to detect the expression levels of GLUT3 and AMPK in placental tissue; CO-IP was utilized to detect the interaction of GLUT3 and AMPK. Compared with the normal pregnancy group, the weight of the fetus and placenta of GDM mice increased (P < 0.001), and the ability of trophoblasts to take up glucose decreased (P < 0.001). In addition, AMPK activity in trophoblasts and membrane localization of GLUT3 in GDM mice were down-regulated compared with normal pregnant mice (P < 0.05). There is an interaction between GLUT3 and AMPK. Activating AMPK in trophoblasts can up-regulate the expression of GLUT3 membrane protein in trophoblasts of mice (P < 0.05) and increase the glucose uptake of trophoblasts (P < 0.05). We speculate that inhibition of AMPK activity in GDM mice results in aberrant localization of GLUT3, which in turn attenuates glucose uptake by placental trophoblast cells. AICAR activates AMPK to increase the membrane localization of GLUT3 and improve the glucose uptake capacity of trophoblasts.

Forsythiaside A attenuates lipopolysaccharide-induced mouse mastitis by activating autophagy and regulating gut microbiota and metabolism.

Mastitis is an inflammatory disease of the mammary gland with a high incidence in lactating animals, significantly impacting their health and breastfeeding. Moreover, mastitis adversely affects milk quality and yield, resulting in substantial economic losses for the dairy farming industry. Forsythiaside A (FTA), a phenylethanol glycoside analog extracted from Forsythia, exhibits notable anti-inflammatory and antioxidant properties. However, its protective effects and specific mechanisms against mastitis remain unclear. In this study, a lipopolysaccharide (LPS)-induced mouse mastitis model was used to investigate the protective effect of FTA on LPS-induced mastitis and its potential mechanism using histological assays, Western blot, qRT-PCR, FITC-albumin permeability test, 16s rRNA gene sequencing analysis and non-targeted metabolomics assays to investigate the protective effect of FTA on LPS-induced mastitis model and its potential mechanism. The results demonstrated that FTA significantly mitigated LPS-induced mouse mastitis by reducing inflammation and apoptosis levels, modulating the PI3K/AKT/mTOR signaling pathways, inducing autophagy, and enhancing antioxidant capacity and the expression of tight junction proteins. Furthermore, FTA increased the abundance of beneficial microbiota while decreasing the levels of harmful microbiota in mice, thus counteracting the gut microbiota disruption induced by LPS stimulation. Intestinal metabolomics analysis revealed that FTA primarily regulated LPS-induced metabolite alterations through key metabolic pathways, such as tryptophan metabolism. This study confirms the anti-inflammatory and antioxidant effects of FTA on mouse mastitis, which are associated with key metabolic pathways, including the restoration of gut microbiota balance and the regulation of tryptophan metabolism. These findings provide a novel foundation for the treatment and prevention of mammalian mastitis using FTA.

Alien emergent aquatic plants develop better ciprofloxacin tolerance and metabolic capacity than one native submerged species.

Antibiotic pollution and biological invasion pose significant risks to freshwater biodiversity and ecosystem health. However, few studies have compared the ecological adaptability and ciprofloxacin (CIPR) degradation potential between alien and native macrophytes. We examined growth, physiological response, and CIPR accumulation, translocation and metabolic abilities of two alien plants (Eichhornia crassipes and Myriophyllum aquaticum) and one native submerged species (Vallisneria natans) exposed to CIPR at 0, 1 and 10 mg/L. We found that E. crassipes and M. aquaticum's growth were unaffected by CIPR while V. natans was significantly hindered under the 10 mg/L treatment. CIPR significantly decreased the maximal quantum yield of PSII, actual quantum yield of PSII and relative electron transfer rate in E. crassipes and V. natans but didn't impact these photosynthetic characteristics in M. aquaticum. All the plants can accumulate, translocate and metabolize CIPR. M. aquaticum and E. crassipes in the 10 mg/L treatment group showed greater CIPR accumulation potential than V. natans indicated by higher CIPR contents in their roots. The oxidative cleavage of the piperazine ring acts as a key pathway for these aquatic plants to metabolize CIPR and the metabolites mainly distributed in plant roots. M. aquaticum and E. crassipes showed a higher production of CIPR metabolites compared to V. natans, with M. aquaticum exhibiting the strongest CIPR metabolic ability, as indicated by the most extensive structural breakdown of CIPR and the largest number of potential metabolic pathways. Taken together, alien species outperformed the native species in ecological adaptability, CIPR accumulation and metabolic capacity. These findings may shed light on the successful invasion mechanisms of alien aquatic species under antibiotic pressure and highlight the potential ecological impacts of alien species, particularly M. aquaticum. Additionally, the interaction of antibiotic contamination and invasion might further challenge the native submerged macrophytes and pose greater risks to freshwater ecosystems.

Endothelial progenitor cells control remodeling of uterine spiral arteries for the establishment of utero-placental circulation.

Placental ischemia, resulting from inadequate remodeling of uterine spiral arteries, is a factor in the development of preeclampsia. However, the effect of endothelial progenitor cells that play a role in the vascular injury-repair program is largely unexplored during remodeling. Here, we observe that preeclampsia-afflicted uterine spiral arteries transition to a synthetic phenotype in vascular smooth muscle cells and characterize the regulatory axis in endothelial progenitor cells during remodeling in human decidua basalis. Excessive sEng, secreted by AMP-activated protein kinase (AMPK)-deficient endothelial progenitor cells through the inhibition of HO-1, damages residual endothelium and leads to the accumulation of extracellular matrix produced by vascular smooth muscle cells during remodeling, which is further confirmed by animal models. Collectively, our findings suggest that the impaired functionality of endothelial progenitor cells contributes to the narrowing of remodeled uterine spiral arteries, leading to reduced utero-placental perfusion. This mechanism holds promise in elucidating the pathogenesis of preeclampsia.

Enteric coronavirus nsp2 is a virulence determinant that recruits NBR1 for autophagic targeting of TBK1 to diminish the innate immune response.

Non-structural protein 2 (nsp2) exists in all coronaviruses (CoVs), while its primary function in viral pathogenicity, is largely unclear. One such enteric CoV, porcine epidemic diarrhea virus (PEDV), causes high mortality in neonatal piglets worldwide. To determine the biological role of nsp2, we generated a PEDV mutant containing a complete nsp2 deletion (rPEDV-Δnsp2) from a highly pathogenic strain by reverse genetics, showing that nsp2 was dispensable for PEDV infection, while its deficiency reduced viral replication in vitro. Intriguingly, rPEDV-Δnsp2 was entirely avirulent in vivo, with significantly increased productions of IFNB (interferon beta) and IFN-stimulated genes (ISGs) in various intestinal tissues of challenged newborn piglets. Notably, nsp2 targets and degrades TBK1 (TANK binding kinase 1), the critical kinase in the innate immune response. Mechanistically, nsp2 induced the macroautophagy/autophagy process and recruited a selective autophagic receptor, NBR1 (NBR1 autophagy cargo receptor). NBR1 subsequently facilitated the K48-linked ubiquitination of TBK1 and delivered it for autophagosome-mediated degradation. Accordingly, the replication of rPEDV-Δnsp2 CoV was restrained by reduced autophagy and excess productions of type I IFNs and ISGs. Our data collectively define enteric CoV nsp2 as a novel virulence determinant, propose a crucial role of nsp2 in diminishing innate antiviral immunity by targeting TBK1 for NBR1-mediated selective autophagy, and pave the way to develop a new type of nsp2-based attenuated PEDV vaccine. The study also provides new insights into the prevention and treatment of other pathogenic CoVs.Abbreviations: 3-MA: 3-methyladenine; Baf A1: bafilomycin A1; CoV: coronavirus; CQ: chloroquine; dpi: days post-inoculation; DMVs: double-membrane vesicles; GABARAP: GABA type A receptor-associated protein; GFP: green fluorescent protein; GIGYF2: GRB10 interacting GYF protein 2; hpi: hours post-infection; IFA: immunofluorescence assay; IFIH1: interferon induced with helicase C domain 1; IFIT2: interferon induced protein with tetratricopeptide repeats 2; IFITM1: interferon induced transmembrane protein 1; IFNB: interferon beta; IRF3: interferon regulatory factor 3; ISGs: interferon-stimulated genes; mAb: monoclonal antibody; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MAVS: mitochondrial antiviral signaling protein; NBR1: NBR1 autophagy cargo receptor; nsp2: non-structural protein 2; OAS1: 2'-5'-oligoadenylate synthetase 1; PEDV: porcine epidemic diarrhea virus; PRRs: pattern recognition receptors; RIGI: RNA sensor RIG-I; RT-qPCR: reverse transcription quantitative polymerase chain reaction; SQSTM1: sequestosome 1; TBK1: TANK binding kinase 1; TCID50: 50% tissue culture infectious doses; VSV: vesicular stomatitis virus.

Machine-learning-based models to predict cardiovascular risk using oculomics and clinic variables in KNHANES.

BACKGROUND: Recent researches have found a strong correlation between the triglyceride-glucose (TyG) index or the atherogenic index of plasma (AIP) and cardiovascular disease (CVD) risk. However, there is a lack of research on non-invasive and rapid prediction of cardiovascular risk. We aimed to develop and validate a machine-learning model for predicting cardiovascular risk based on variables encompassing clinical questionnaires and oculomics. METHODS: We collected data from the Korean National Health and Nutrition Examination Survey (KNHANES). The training dataset (80% from the year 2008 to 2011 KNHANES) was used for machine learning model development, with internal validation using the remaining 20%. An external validation dataset from the year 2012 assessed the model's predictive capacity for TyG-index or AIP in new cases. We included 32122 participants in the final dataset. Machine learning models used 25 algorithms were trained on oculomics measurements and clinical questionnaires to predict the range of TyG-index and AIP. The area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score were used to evaluate the performance of our machine learning models. RESULTS: Based on large-scale cohort studies, we determined TyG-index cut-off points at 8.0, 8.75 (upper one-third values), 8.93 (upper one-fourth values), and AIP cut-offs at 0.318, 0.34. Values surpassing these thresholds indicated elevated cardiovascular risk. The best-performing algorithm revealed TyG-index cut-offs at 8.0, 8.75, and 8.93 with internal validation AUCs of 0.812, 0.873, and 0.911, respectively. External validation AUCs were 0.809, 0.863, and 0.901. For AIP at 0.34, internal and external validation achieved similar AUCs of 0.849 and 0.842. Slightly lower performance was seen for the 0.318 cut-off, with AUCs of 0.844 and 0.836. Significant gender-based variations were noted for TyG-index at 8 (male AUC=0.832, female AUC=0.790) and 8.75 (male AUC=0.874, female AUC=0.862) and AIP at 0.318 (male AUC=0.853, female AUC=0.825) and 0.34 (male AUC=0.858, female AUC=0.831). Gender similarity in AUC (male AUC=0.907 versus female AUC=0.906) was observed only when the TyG-index cut-off point equals 8.93. CONCLUSION: We have established a simple and effective non-invasive machine learning model that has good clinical value for predicting cardiovascular risk in the general population.

Clinical and economic comparison of laparoscopic versus open hepatectomy for primary hepatolithiasis: a propensity score-matched cohort study.

BACKGROUND: It is unclear whether laparoscopic hepatectomy (LH) for hepatolithiasis confers better clinical benefit and lower hospital costs than open hepatectomy (OH). This study aim to evaluate the clinical and economic value of LH versus OH. METHODS: Patients undergoing OH or LH for primary hepatolithiasis at Yijishan Hospital of Wannan Medical College between 2015 and 2022 were divided into OH group and LH group. Propensity score matching (PSM) was used to balance the baseline data. Deviation-based cost modelling and weighted average median cost (WAMC) were used to assess and compare the economic value. RESULTS: A total of 853 patients were identified. After exclusions, 403 patients with primary hepatolithiasis underwent anatomical hepatectomy (OH n=143; LH n=260). PSM resulted in 2 groups of 100 patients each. Although LH required a longer median operation duration compared with OH (285.0 versus 240.0 min, respectively, P<0.001), LH patients had fewer wound infections, fewer pre-discharge overall complications (26 versus 43%, respectively, P=0.009), and shorter median postoperative hospital stays (8.0 versus 12.0 days, respectively, P<0.001). No differences were found in blood loss, major complications, stone clearance, and mortality between the two matched groups. However, the median overall hospital cost of LH was significantly higher than that of OH (CNY¥52,196.1 versus 45,349.5, respectively, P=0.007). Although LH patients had shorter median postoperative hospital stays and fewer complications than OH patients, the WAMC was still higher for the LH group than for the OH group with an increase of CNY¥9,755.2 per patient undergoing LH. CONCLUSION: The overall clinical benefit of LH for hepatolithiasis is comparable or even superior to that of OH, but with an economic disadvantage. There is a need to effectively reduce the hospital costs of LH and the gap between costs and diagnosis-related group reimbursement to promote its adoption.

Macrophage-Capturing Self-Assembly Photosensitizer Nanoparticles Induces Immune Microenvironment Re-Programming and Golgi-Responsive Immunogenic Cell Death in Head and Neck Carcinoma.

Head and neck carcinoma treatment is shifted toward the combination of therapy causing immune checkpoint blockade (ICB) and immunogenic cell death. In this study, a CSFRi-chimeric TAMCSFR+-targeting extracellular vesicle (EV@CSFRi) platform is developed and designed an intracellular protoporphyrin conjugated with RVRR peptide sequence for furin-cleavage to perform Golgi-targeting and generating ROS (GT-RG). The graphical abstract illustrates the self-assembly of GT-RG nanoparticles into nanofiber through the hydrophily of RVRR and hydrophobicity of RG, and the red line indicates the site of furin cleavage. As is shown in the Graphical abstract, the Golgi-targeting Protoporphyrin-RVRR platform is composed with CSFRi-chimeric extracellular vesicles and forms the tumor-responsive TAM-reprogramming bilayers (GT-RGEV@CSFRi). The GT-RGEV@CSFRi acted as a multifunctional theranostic platform, which can induce immunogenic cell death and further help modulate TAM, thus suppressing the HNC xenograft model by combination therapy with anti-PD-1.

Establishment of a machine learning predictive model for non-alcoholic fatty liver disease: A longitudinal cohort study.

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease, which lacks effective drug treatments. This study aimed to construct an eXtreme Gradient Boosting (XGBoost) prediction model to identify or evaluate potential NAFLD patients. METHODS AND RESULTS: We conducted a longitudinal study of 22,140 individuals from the Beijing Health Management Cohort. Variable filtering was performed using the least absolute shrinkage and selection operator. Random Over Sampling Examples was used to address imbalanced data. Next, the XGBoost model and the other three machine learning (ML) models were built using balanced data. Finally, the variable importance of the XGBoost model was ranked. Among four ML algorithms, we got that the XGBoost model outperformed the other models with the following results: accuracy of 0.835, sensitivity of 0.835, specificity of 0.834, Youden index of 0.669, precision of 0.831, recall of 0.835, F-1 score of 0.833, and an area under the curve of 0.914. The top five variables with the greatest impact on the onset of NAFLD were aspartate aminotransferase, cardiometabolic index, body mass index, alanine aminotransferase, and triglyceride-glucose index. CONCLUSION: The predictive model based on the XGBoost algorithm enables early prediction of the onset of NAFLD. Additionally, assessing variable importance provides valuable insights into the prevention and treatment of NAFLD.

Association of sex-specific body mass index and waist circumference trajectories with non-alcoholic fatty liver disease incidence based on growth mixture modeling.

BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease. The relationship between the trajectories of obesity indicators and incident NAFLD is unknown. Therefore, this study aims to explore the sex-specific association between the trajectories of obesity indicators and the incidence of NAFLD. METHODS AND RESULTS: In total, 9067 participants were recruited for this longitudinal study. Obesity indicators use body mass index (BMI) and waist circumference (WC). The trajectory of obesity indicators was analyzed using the growth mixture modeling. The multivariate logistic regression model was used to analyze the association between obesity indicators' trajectories and incident NAFLD. Over a median follow-up of 1.82 years, 1013 (11.74%) participants developed NAFLD. We identified BMI and WC change trajectories as the stable group, increasing group, and decreasing group. After adjusting for baseline level and other confounders, multivariate logistic regression analysis showed that compared with stable group of BMI, the increasing group, and decreasing group odds ratio and 95% confidence interval of NAFLD were 2.10 (1.06-4.15), and 0.25 (0.09-0.67) in men, and 1.82 (1.08-3.04) and 0.32 (0.16-0.64) in women. Compared with stable group of WC, the increasing group was 2.57 (1.39-4.74) in men, the increasing group, and decreasing group were 2.29 (1.70-3.10) and 0.28 (0.12-0.64) in women. Sensitivity analysis showed that the results were stable. CONCLUSION: The BMI and WC changing trajectories are significantly associated with the incidence of NAFLD in men and women. Populations of real-world health examinations can be categorized based on obesity indicator changes to prevent NAFLD.

A multi-tissue metabolome atlas of primate pregnancy.

Pregnancy induces dramatic metabolic changes in females; yet, the intricacies of this metabolic reprogramming remain poorly understood, especially in primates. Using cynomolgus monkeys, we constructed a comprehensive multi-tissue metabolome atlas, analyzing 273 samples from 23 maternal tissues during pregnancy. We discovered a decline in metabolic coupling between tissues as pregnancy progressed. Core metabolic pathways that were rewired during primate pregnancy included steroidogenesis, fatty acid metabolism, and arachidonic acid metabolism. Our atlas revealed 91 pregnancy-adaptive metabolites changing consistently across 23 tissues, whose roles we verified in human cell models and patient samples. Corticosterone and palmitoyl-carnitine regulated placental maturation and maternal tissue progenitors, respectively, with implications for maternal preeclampsia, diabetes, cardiac hypertrophy, and muscle and liver regeneration. Moreover, we found that corticosterone deficiency induced preeclampsia-like inflammation, indicating the atlas's potential clinical value. Overall, our multi-tissue metabolome atlas serves as a framework for elucidating the role of metabolic regulation in female health during pregnancy.

Antifatigue effects and antioxidant activity in polysaccharide fractions from Chinese yam bulbils.

Polysaccharides are the principal component in Chinese yam (Dioscorea opposita Thunb.) bulbils. The properties and antifatigue of polysaccharides from yam bulbils (PYB) were identified and compared. Their molecular weights (PYB-1 and PYB-2) were approximately 145 and 11 kDa, respectively, with active ß-configurations. Meanwhile, the antifatigue activities of PYBs were tested in mice via exhaustive swimming tests (EST). The EST results indicated that PYB-1 and PYB-2 significantly prolonged swimming time in mice (p < .05). Associated with this increase was a rise in hepatic glycogen content and antioxidant enzyme (superoxide dismutase (SOD), glutathione peroxidase (GSH-Px)) activity, along with a decline in blood urea nitrogen, lactic acid, and malondialdehyde levels. The results showed that molecular weight might contribute to the antifatigue effects of PYBs. Additionally, antioxidant tests showed that PYB-1 had stronger free-radical scavenging activity than PYB-2. Taken together, the findings indicated that PYBs exhibited effective antifatigue and antioxidant activities providing additional evidence supporting the use of PYBs as functional food ingredients for relieving fatigue.