IL-8 promotes lens capsular residual cells migration by down-regulates expression of E-cadherin and ZO-1 via the CXCR1/2-NF-κB-RhoA signal pathway.

BACKGROUND: Posterior capsular opacification is a major complication following cataract surgery, marked by proliferation, migration, epithelial-mesenchymal transition, and fibrosis of residual epithelial cells. Various inflammatory cytokines are upregulated and contribute to the development of posterior capsular opacification. The effect of interleukin-8 on residual epithelial cells has not been fully determined. METHODS: Aqueous humor and anterior capsules samples were collected from cataract surgery. Capsular bags from rats and pigs were cultured in DMEM media. Protein and mRNA expressions were measured using immunoblot and qPCR. Cell migration was assessed using the transwell assay. RESULTS: Interleukin-8 is an early inflammatory factor secreted by residual lens epithelial cells. Migration of lens epithelial cells in aqueous humor positively correlates with interleukin-8 levels, and this effect is inhibited by the receptors of interleukin-8 CXCR1/2 blocker Reparaxin. The expression of tight-junction protein ZO-1 and cell-adhesion protein E-cadherin were down-regulated by administrating interleukin-8, and cell migration of both SRA01/04 cell line in vitro and capsular residual epithelial cells ex vivo were up-regulated via activating RhoA expression and RhoA/GTPase activity. The loss-of- function studies demonstrate that interleukin-8 binding to its receptor CXCR1/2 activates NF-κB/p65, which then turns on the RhoA's expression and RhoA/GTPase activity, and RhoA-modulated the downexpression of E-cadherin and ZO-1 and the increase of cell migration. CONCLUSIONS: The upregulation in interleukin-8 occurs early in posterior capsular opacification and contributes to down-regulating tight-junctions among epithelial cells and elevates cell migration via the CXCR1/2-NF-κB-RhoA signaling pathway. These demonstrated that interleukin-8 could be a potential target for preventing posterior capsular opacification.

Sulforaphane improves post-resuscitation myocardial dysfunction by inhibiting cardiomyocytes ferroptosis via the Nrf2/IRF1/GPX4 pathway.

BACKGROUND: Ferroptosis is an important type of cell death contributing to myocardial dysfunction induced by whole body ischemia reperfusion following cardiac arrest (CA) and resuscitation. Sulforaphane (SFN), known as the activator of the nuclear factor E2-related factor 2 (Nrf2), has been proven to effectively alleviate regional myocardial ischemia reperfusion injury. The present study was designed to investigate whether SFN could improve post-resuscitation myocardial dysfunction by inhibiting cardiomyocytes ferroptosis and its potential regulatory mechanism. METHODS AND RESULTS: An in vivo pig model of CA and resuscitation was established. Hypoxia/reoxygenation (H/R)-stimulated AC16 cardiomyocytes was constructed as an in vitro model to simulate the process of CA and resuscitation. In vitro experiment, SFN reduced ferroptosis-related ferrous iron, lipid reactive oxygen species, and malondialdehyde, increased glutathione, and further promoted cell survival after H/R stimulation in AC16 cardiomyocytes. Mechanistically, the activation of Nrf2 with the SFN decreased interferon regulatory factor 1 (IRF1) expression, then reduced its binding to the promoter of glutathione peroxidase 4 (GPX4), and finally recovered the latter's transcription after H/R stimulation in AC16 cardiomyocytes. In vivo experiment, SFN reversed abnormal expression of IRF1 and GPX4, inhibited cardiac ferroptosis, and improved myocardial dysfunction after CA and resuscitation in pigs. CONCLUSIONS: SFN could effectively improve myocardial dysfunction after CA and resuscitation, in which the mechanism was potentially related to the inhibition of cardiomyocytes ferroptosis through the regulation of Nrf2/IRF1/GPX4 pathway.

Periaqueductal gray subregions connectivity and its association with micturition desire-awakening function.

Existing literature strongly supports the idea that children with primary nocturnal enuresis (PNE) have brainstem abnormalities. However, the connection between pre-micturition arousal responses and brain functional connectivities is still not clearly defined. Our study investigated the correlation between the gradations of micturition desire-awakening (MDA) functionality and the functional connectivity of the midbrain periaqueductal gray (PAG), a pivotal brainstem hub implicated in the neural regulation of micturition in humans. Neuroimaging and behavioral data from 133 patients with PNE and 40 healthy children were acquired from functional magnetic resonance imaging (fMRI) and precise clinical observations, respectively. The whole-brain correlation analyses were undertaken to elucidate the complex connectivity patterns between the subregions of PAG and the cerebral cortex, with a focus on their correlation to the spectrum of MDA functionality. A positive correlation was identified between MDA dysfunction and the resting-state functional connectivity (RSFC) between the left ventrolateral periaqueductal gray (vlPAG) and the right temporal pole of the superior temporal gyrus. Conversely, a negative correlation was observed between MDA dysfunction and the RSFC of the right vlPAG with the right superior parietal lobule. Additionally, MDA dysfunction exhibited a negative association with the RSFC between the dorsomedial PAG (dmPAG) and the right inferior parietal lobule. These findings may indicate that the specific signal from a distended bladder is blocked in the PAG and its functional connectivity with the executive function, attention, and default mode networks, ultimately leading to impaired arousal and bladder control. This revelation underscores potential neural targets for future therapeutic interventions.

Evaluation of the Alveolar Crest and Cemento-Enamel Junction in Periodontitis Using Object Detection on Periapical Radiographs.

The severity of periodontitis can be analyzed by calculating the loss of alveolar crest (ALC) level and the level of bone loss between the tooth's bone and the cemento-enamel junction (CEJ). However, dentists need to manually mark symptoms on periapical radiographs (PAs) to assess bone loss, a process that is both time-consuming and prone to errors. This study proposes the following new method that contributes to the evaluation of disease and reduces errors. Firstly, innovative periodontitis image enhancement methods are employed to improve PA image quality. Subsequently, single teeth can be accurately extracted from PA images by object detection with a maximum accuracy of 97.01%. An instance segmentation developed in this study accurately extracts regions of interest, enabling the generation of masks for tooth bone and tooth crown with accuracies of 93.48% and 96.95%. Finally, a novel detection algorithm is proposed to automatically mark the CEJ and ALC of symptomatic teeth, facilitating faster accurate assessment of bone loss severity by dentists. The PA image database used in this study, with the IRB number 02002030B0 provided by Chang Gung Medical Center, Taiwan, significantly reduces the time required for dental diagnosis and enhances healthcare quality through the techniques developed in this research.

Microbial signatures predictive of short-term prognosis in severe pneumonia.

Objective: This retrospective cohort study aimed to investigate the composition and diversity of lung microbiota in patients with severe pneumonia and explore its association with short-term prognosis. Methods: A total of 301 patients diagnosed with severe pneumonia underwent bronchoalveolar lavage fluid metagenomic next-generation sequencing (mNGS) testing from February 2022 to January 2024. After applying exclusion criteria, 236 patients were included in the study. Baseline demographic and clinical characteristics were compared between survival and non-survival groups. Microbial composition and diversity were analyzed using alpha and beta diversity metrics. Additionally, LEfSe analysis and machine learning methods were employed to identify key pathogenic microorganism associated with short-term mortality. Microbial interaction modes were assessed through network co-occurrence analysis. Results: The overall 28-day mortality rate was 37.7% in severe pneumonia. Non-survival patients had a higher prevalence of hypertension and exhibited higher APACHE II and SOFA scores, higher procalcitonin (PCT), and shorter hospitalization duration. Microbial α and ß diversity analysis showed no significant differences between the two groups. However, distinct species diversity patterns were observed, with the non-survival group showing a higher abundance of Acinetobacter baumannii, Klebsiella pneumoniae, and Enterococcus faecium, while the survival group had a higher prevalence of Corynebacterium striatum and Enterobacter. LEfSe analysis identified 29 distinct terms, with 10 potential markers in the non-survival group, including Pseudomonas sp. and Enterococcus durans. Machine learning models selected 16 key pathogenic bacteria, such as Klebsiella pneumoniae, significantly contributing to predicting short-term mortality. Network co-occurrence analysis revealed greater complexity in the non-survival group compared to the survival group, with differences in central genera. Conclusion: Our study highlights the potential significance of lung microbiota composition in predicting short-term prognosis in severe pneumonia patients. Differences in microbial diversity and composition, along with distinct microbial interaction modes, may contribute to variations in short-term outcomes. Further research is warranted to elucidate the clinical implications and underlying mechanisms of these findings.

Prediction of clear cell renal cell carcinoma ≤ 4cm: visual assessment of ultrasound characteristics versus ultrasonographic radiomics analysis.

Objective: To investigate the diagnostic efficacy of the clinical ultrasound imaging model, ultrasonographic radiomics model, and comprehensive model based on ultrasonographic radiomics for the differentiation of small clear cell Renal Cell Carcinoma (ccRCC) and Renal Angiomyolipoma (RAML). Methods: The clinical, ultrasound, and contrast-enhanced CT(CECT) imaging data of 302 small renal tumors (maximum diameter ≤ 4cm) patients in Tianjin Medical University Cancer Institute and Hospital from June 2018 to June 2022 were retrospectively analyzed, with 182 patients of ccRCC and 120 patients of RAML. The ultrasound images of the largest diameter of renal tumors were manually segmented by ITK-SNAP software, and Pyradiomics (v3.0.1) module in Python 3.8.7 was applied to extract ultrasonographic radiomics features from ROI segmented images. The patients were randomly divided into training and internal validation cohorts in the ratio of 7:3. The Random Forest algorithm of the Sklearn module was applied to construct the clinical ultrasound imaging model, ultrasonographic radiomics model, and comprehensive model. The efficacy of the prediction models was verified in an independent external validation cohort consisting of 69 patients, from 230 small renal tumor patients in two different institutions. The Delong test compared the predictive ability of three models and CECT. Calibration Curve and clinical Decision Curve Analysis were applied to evaluate the model and determine the net benefit to patients. Results: 491 ultrasonographic radiomics features were extracted from 302 small renal tumor patients, and 9 ultrasonographic radiomics features were finally retained for modeling after regression and dimensionality reduction. In the internal validation cohort, the area under the curve (AUC), sensitivity, specificity, and accuracy of the clinical ultrasound imaging model, ultrasonographic radiomics model, comprehensive model, and CECT were 0.75, 76.7%, 60.0%, 70.0%; 0.80, 85.6%, 61.7%, 76.0%; 0.88, 90.6%, 76.7%, 85.0% and 0.90, 92.6%, 88.9%, 91.1%, respectively. In the external validation cohort, AUC, sensitivity, specificity, and accuracy of the three models and CECT were 0.73, 67.5%, 69.1%, 68.3%; 0.89, 86.7%, 80.0%, 83.5%; 0.90, 85.0%, 85.5%, 85.2% and 0.91, 94.6%, 88.3%, 91.3%, respectively. The DeLong test showed no significant difference between the clinical ultrasound imaging model and the ultrasonographic radiomics model (Z=-1.287, P=0.198). The comprehensive model showed superior diagnostic performance than the ultrasonographic radiomics model (Z=4. 394, P<0.001) and the clinical ultrasound imaging model (Z=4. 732, P<0.001). Moreover, there was no significant difference in AUC between the comprehensive model and CECT (Z=-0.252, P=0.801). Both in the internal and external validation cohort, the Calibration Curve and Decision Curve Analysis showed a better performance of the comprehensive model. Conclusion: It is feasible to construct an ultrasonographic radiomics model for distinguishing small ccRCC and RAML based on ultrasound images, and the diagnostic performance of the comprehensive model is superior to the clinical ultrasound imaging model and ultrasonographic radiomics model, similar to that of CECT.

The interplay between metal ions and immune cells in glioma: pathways to immune escape.

This review explores the intricate roles of metal ions-iron, copper, zinc, and selenium-in glioma pathogenesis and immune evasion. Dysregulated metal ion metabolism significantly contributes to glioma progression by inducing oxidative stress, promoting angiogenesis, and modulating immune cell functions. Iron accumulation enhances oxidative DNA damage, copper activates hypoxia-inducible factors to stimulate angiogenesis, zinc influences cell proliferation and apoptosis, and selenium modulates the tumor microenvironment through its antioxidant properties. These metal ions also facilitate immune escape by upregulating immune checkpoints and secreting immunosuppressive cytokines. Targeting metal ion pathways with therapeutic strategies such as chelating agents and metalloproteinase inhibitors, particularly in combination with conventional treatments like chemotherapy and immunotherapy, shows promise in improving treatment efficacy and overcoming resistance. Future research should leverage advanced bioinformatics and integrative methodologies to deepen the understanding of metal ion-immune interactions, ultimately identifying novel biomarkers and therapeutic targets to enhance glioma management and patient outcomes.

An endothelium membrane mimetic antithrombotic coating enables safer and longer extracorporeal membrane oxygenation application.

Thrombosis and plasma leakage are two of the most frequent dysfunctions of polypropylene (PP) hollow fiber membrane (PPM) used in extracorporeal membrane oxygenation (ECMO) therapy. In this study, a superhydrophilic endothelial membrane mimetic coating (SEMMC) was constructed on polydopamine-polyethyleneimine pre-coated surfaces of the PPM oxygenator and its ECMO circuit to explore safer and more sustainable ECMO strategy. The SEMMC is fabricated by multi-point anchoring of a phosphorylcholine and carboxyl side chained copolymer (PMPCC) and grafting of heparin (Hep) to form PMPCC-Hep interface, which endows the membrane superior hemocompatibility and anticoagulation performances. Furthermore, the modified PPM reduces protein adsorption amount to less than 30 ng/cm2. More significantly, the PMPCC-Hep coated ECMO system extends the anti-leakage and non-clotting oxygenation period to more than 15 h in anticoagulant-free animal extracorporeal circulation, much better than the bare and conventional Hep coated ECMO systems with severe clots and plasma leakage in 4 h and 8 h, respectively. This SEMMC strategy of grafting bioactive heparin onto bioinert zwitterionic copolymer interface has great potential in developing safer and longer anticoagulant-free ECMO systems. STATEMENT OF SIGNIFICANCE: A superhydrophilic endothelial membrane mimetic coating was constructed on surfaces of polypropylene hollow fiber membrane (PPM) oxygenator and its ECMO circuit by multi-point anchoring of a phosphorylcholine and carboxyl side chain copolymer (PMPCC) and grafting of heparin (Hep). The strong antifouling nature of the PMPCC-Hep coating resists the adsorption of plasma bio-molecules, resulting in enhanced hemocompatibility and anti-leakage ability. The grafted heparin on the zwitterionic PMPCC interface exhibits superior anticoagulation property. More significantly, the PMPCC-Hep coating achieves an extracorporeal circulation in a pig model for at least 15 h without any systemic anticoagulant. This endothelial membrane mimetic anticoagulation strategy shows great potential for the development of safer and longer anticoagulant-free ECMO systems.

Construction and validation of a predictive model of mortality of tuberculosis-destroyed lung patients requiring mechanical ventilation: A single-center retrospective cohort study.

The mortality rate for intensive care unit tuberculosis-destroyed lung (TDL) patients requiring mechanical ventilation (MV) remains high. We conducted a retrospective analysis of adult TDL patients requiring MV who were admitted to the intensive care unit of a tertiary infectious disease hospital in Chengdu, Sichuan Province, China from January 2019 to March 2023. Univariate and multivariate COX regression analyses were conducted to determine independent patient prognostic risk factors that were used to construct a predictive model of patient mortality. A total of 331 patients were included, the median age was 63.0 (50.0-71.0) years, 262 (79.2%) were males and the mortality rate was 48.64% (161/331). Training and validation data sets were obtained from 245 and 86 patients, respectively. Analysis of the training data set revealed that body mass index <18.5 kg/m2, blood urea nitrogen ≥7.14 mmol/L and septic shock were independent risk factors for increased mortality of TDL patients requiring MV. These variables were then used to construct a risk-based model for predicting patient mortality. Area under curve, sensitivity, and specificity values obtained using the model for the training data set were 0.808, 79.17%, and 68.80%, respectively, and corresponding values obtained using the validation data set were 0.876, 95.12%, and 62.22%, respectively. Concurrent correction curve and decision curve analyses confirmed the high predictive ability of the model, indicating its potential to facilitate early identification and classification-based clinical management of high-risk TDL patients requiring MV.

The association between blood urea nitrogen to albumin ratio and the 28 day mortality in tuberculosis patients complicated by sepsis.

The relationship between blood urea nitrogen to albumin ratio (BAR) and the prognosis of patients with tuberculosis (TB) complicated by sepsis remains unclear. This study aimed to explore the association between BAR and overall patient prognosis. This was a retrospective cohort study of patients with TB complicated by sepsis who were admitted to the intensive care unit (ICU) of the Public Health Clinical Center of Chengdu between January 2019 and February 2023. The relationship between BAR values and prognosis in these patients was investigated using multivariate Cox regression, stratified analysis with interaction, restricted cubic spline (RCS), and threshold effect analysis. Sensitivity analyses were conducted to assess the robustness of the results. Our study included 537 TB patients complicated by sepsis admitted in the ICU, with a median age of 63.0 (48.0, 72.0) years; 76.7% of whom were men. The multivariate-restricted cubic spline analysis showed a non-linear association between BAR and patient prognosis. In the threshold analysis, we found that TB patients complicated by sepsis and a BAR < 7.916 mg/g had an adjusted hazard ratio (HR) for prognosis of 1.163 (95% CI 1.038-1.303; P = 0.009). However, when the BAR was ≥ 7.916 mg/g, there was no significant increase in the risk of death. The results of the sensitivity analysis were stable.

The SPI1/SMAD5 cascade in the promoting effect of icariin on osteogenic differentiation of MC3T3-E1 cells: a mechanism study.

BACKGROUND: Dysregulation of osteogenic differentiation is a crucial event during osteoporosis. The bioactive phytochemical icariin has become an anti-osteoporosis candidate. Here, we elucidated the mechanisms underlying the promoting function of icariin in osteogenic differentiation. METHODS: Murine pre-osteoblast MC3T3-E1 cells were stimulated with dexamethasone (DEX) to induce osteogenic differentiation, which was evaluated by an Alizarin Red staining assay and ALP activity measurement. The mRNA amounts of SPI1 and SMAD5 were detected by real-time quantitative PCR. Expression analysis of proteins, including osteogenic markers (OPN, OCN and RUNX2) and autophagy-associated proteins (LC3, Beclin-1, and ATG5), was performed by immunoblotting. The binding of SPI1 and the SMAD5 promoter was predicted by the Jaspar2024 algorithm and confirmed by chromatin immunoprecipitation (ChIP) experiments. The regulation of SPI1 in SMAD5 was examined by luciferase assays. RESULTS: During osteogenic differentiation of MC3T3-E1 cells, SPI1 and SMAD5 were upregulated. Functionally, SPI1 overexpression enhanced autophagy and osteogenic differentiation of MC3T3-E1 cells, while SMAD5 downregulation exhibited opposite effects. Mechanistically, SPI1 could enhance SMAD5 transcription and expression. Downregulation of SMAD5 also reversed SPI1 overexpression-induced autophagy and osteogenic differentiation in MC3T3-E1 cells. In MC3T3-E1 cells under DEX stimulation, icariin increased SMAD5 expression by upregulating SPI1. Furthermore, icariin could attenuate SPI1 depletion-imposed inhibition of autophagy and osteogenic differentiation of MC3T3-E1 cells. CONCLUSION: Our findings demonstrate that the SPI1/SMAD5 cascade, with the ability to enhance osteogenic differentiation, underlies the promoting effect of icariin on osteogenic differentiation of MC3T3-E1 cells.

Development and Validation of a Risk Mortality Prediction Model for Patients with Pulmonary Tuberculosis Complicated by Severe Community-Acquired Pneumonia in the Intensive Care Unit.

Purpose: The mortality rate from pulmonary tuberculosis (PTB) complicated by severe community-acquired pneumonia (SCAP) in the intensive care unit (ICU) remains high. We aimed to develop a rapid and simple model for the early assessment and stratification of prognosis in these patients. Patients and Methods: All adult patients with PTB complicated by SCAP admitted to the ICU of a tertiary hospital in Chengdu, Sichuan, China between 2019 and 2021 (development cohort) and 2022 (validation cohort) were retrospectively included. Data on demographics, comorbidities, laboratory values, and interventions were collected. The outcome was the 28-day mortality. Stepwise backward multivariate Cox analysis was used to develop a mortality risk prediction score model. Receiver operating characteristic (ROC) and calibration curves were used to evaluate the model's predictive efficiency. Decision curve analysis (DCA) was used to validate the model's clinical value and impact on decision making. Results: Overall, 357 and 168 patients were included in the development and validation cohorts, respectively. The Pulmonary Tuberculosis Severity Index (PTSI) score included long-term use of glucocorticoid, body mass index (BMI) <18.5 kg/m2, diabetes, blood urea nitrogen (BUN) ≥7.14 mmol/L, PO2/FiO2 <150 mmHg, and vasopressor use. The area under the ROC curve (AUC) values were 0.817 (95% CI: 0.772-0.863) and 0.814 for the development and validation cohorts, respectively. The PTSI score had a higher AUC than the APACHE II, SOFA, and CURB-65 score. The calibration curves indicated good calibration in both cohorts. The DCA of the PTSI score indicated the high clinical application of the model compared with the APACHE II and SOFA scores. Conclusion: This prognostic tool was designed to rapidly evaluate the 28-day mortality risk in individuals with PTB complicated by SCAP. It can stratify this patient group into relevant risk categories, guide targeted interventions, and enhance clinical decision making, thereby optimizing patient care and improving outcomes.

Effects of exposure to multiple metallic elements in the first trimester of pregnancy on the risk of preterm birth.

Exposure to certain heavy metals has been demonstrated to be associated with a higher risk of preterm birth (PTB). However, studies focused on the effects of other metal mixtures were limited. A nested case‒control study enrolling 94 PTB cases and 282 controls was conducted. Metallic elements were detected in maternal plasma collected in the first trimester using inductively coupled plasma‒mass spectrometry. The effect of maternal exposure on the risk of PTB was investigated using logistic regression, least absolute shrinkage and selection operator, restricted cubic spline (RCS), quantile g computation (QGC) and Bayesian kernel machine regression (BKMR). Vanadium (V) and arsenic (As) were positively associated with PTB risk in the logistic model, and V remains positively associated in the multi-exposure logistic model. QGC analysis determined V (69.42%) and nickel (Ni) (70.30%) as the maximum positive and negative contributors to the PTB risk, respectively. BKMR models further demonstrated a positive relationship between the exposure levels of the mixtures and PTB risk, and V was identified as the most important independent variable among the elements. RCS analysis showed an inverted U-shape effect of V and gestational age, and plasma V more than 2.18 µg/L was considered a risk factor for shortened gestation length. Exposure to metallic elements mixtures consisting of V, As, cobalt, Ni, chromium and manganese in the first trimester was associated with an increased risk of PTB, and V was considered the most important factor in the mixtures in promoting the incidence of PTB.

Deletion of endothelial IGFBP5 protects against ischaemic hindlimb injury by promoting angiogenesis.

BACKGROUND: Angiogenesis is critical for forming new blood vessels from antedating vascular vessels. The endothelium is essential for angiogenesis, vascular remodelling and minimisation of functional deficits following ischaemia. The insulin-like growth factor (IGF) family is crucial for angiogenesis. Insulin-like growth factor-binding protein 5 (IGFBP5), a binding protein of the IGF family, may have places in angiogenesis, but the mechanisms are not yet completely understood. We sought to probe whether IGFBP5 is involved in pathological angiogenesis and uncover the molecular mechanisms behind it. METHODS AND RESULTS: IGFBP5 expression was elevated in the vascular endothelium of gastrocnemius muscle from critical limb ischaemia patients and hindlimb ischaemic (HLI) mice and hypoxic human umbilical vein endothelial cells (HUVECs). In vivo, loss of endothelial IGFBP5 (IGFBP5EKO) facilitated the recovery of blood vessel function and limb necrosis in HLI mice. Moreover, skin damage healing and aortic ring sprouting were faster in IGFBP5EKO mice than in control mice. In vitro, the genetic inhibition of IGFBP5 in HUVECs significantly promoted tube formation, cell proliferation and migration by mediating the phosphorylation of IGF1R, Erk1/2 and Akt. Intriguingly, pharmacological treatment of HUVECs with recombinant human IGFBP5 ensued a contrasting effect on angiogenesis by inhibiting the IGF1 or IGF2 function. Genetic inhibition of IGFBP5 promoted cellular oxygen consumption and extracellular acidification rates via IGF1R-mediated glycolytic adenosine triphosphate (ATP) metabolism. Mechanistically, IGFBP5 exerted its role via E3 ubiquitin ligase Von Hippel-Lindau (VHL)-regulated HIF1α stability. Furthermore, the knockdown of the endothelial IGF1R partially abolished the reformative effect of IGFBP5EKO mice post-HLI. CONCLUSION: Our findings demonstrate that IGFBP5 ablation enhances angiogenesis by promoting ATP metabolism and stabilising HIF1α, implying IGFBP5 is a novel therapeutic target for treating abnormal angiogenesis-related conditions.

A global survey on the use of the international classification of diseases codes for metabolic dysfunction-associated fatty liver disease.

BACKGROUND: With the implementation of the 11th edition of the International Classification of Diseases (ICD-11) and the publication of the metabolic dysfunction-associated fatty liver disease (MAFLD) nomenclature in 2020, it is important to establish consensus for the coding of MAFLD in ICD-11. This will inform subsequent revisions of ICD-11. METHODS: Using the Qualtrics XM and WJX platforms, questionnaires were sent online to MAFLD-ICD-11 coding collaborators, authors of papers, and relevant association members. RESULTS: A total of 890 international experts in various fields from 61 countries responded to the survey. We also achieved full coverage of provincial-level administrative regions in China. 77.1% of respondents agreed that MAFLD should be represented in ICD-11 by updating NAFLD, with no significant regional differences (77.3% in Asia and 76.6% in non-Asia, p = 0.819). Over 80% of respondents agreed or somewhat agreed with the need to assign specific codes for progressive stages of MAFLD (i.e. steatohepatitis) (92.2%), MAFLD combined with comorbidities (84.1%), or MAFLD subtypes (i.e., lean, overweight/obese, and diabetic) (86.1%). CONCLUSIONS: This global survey by a collaborative panel of clinical, coding, health management and policy experts, indicates agreement that MAFLD should be coded in ICD-11. The data serves as a foundation for corresponding adjustments in the ICD-11 revision.

Multi-feature Fusion Network on Gray Scale Ultrasonography: Effective Differentiation of Adenolymphoma and Pleomorphic Adenoma.

RATIONALE AND OBJECTIVES: to develop a deep learning radiomics graph network (DLRN) that integrates deep learning features extracted from gray scale ultrasonography, radiomics features and clinical features, for distinguishing parotid pleomorphic adenoma (PA) from adenolymphoma (AL) MATERIALS AND METHODS: A total of 287 patients (162 in training cohort, 70 in internal validation cohort and 55 in external validation cohort) from two centers with histologically confirmed PA or AL were enrolled. Deep transfer learning features and radiomics features extracted from gray scale ultrasound images were input to machine learning classifiers including logistic regression (LR), support vector machines (SVM), KNN, RandomForest (RF), ExtraTrees, XGBoost, LightGBM, and MLP to construct deep transfer learning radiomics (DTL) models and Rad models respectively. Deep learning radiomics (DLR) models were constructed by integrating the two features and DLR signatures were generated. Clinical features were further combined with the signatures to develop a DLRN model. The performance of these models was evaluated using receiver operating characteristic (ROC) curve analysis, calibration, decision curve analysis (DCA), and the Hosmer-Lemeshow test. RESULTS: In the internal validation cohort and external validation cohort, comparing to Clinic (AUC=0.767 and 0.777), Rad (AUC=0.841 and 0.748), DTL (AUC=0.740 and 0.825) and DLR (AUC=0.863 and 0.859), the DLRN model showed greatest discriminatory ability (AUC=0.908 and 0.908) showed optimal discriminatory ability. CONCLUSION: The DLRN model built based on gray scale ultrasonography significantly improved the diagnostic performance for benign salivary gland tumors. It can provide clinicians with a non-invasive and accurate diagnostic approach, which holds important clinical significance and value. Ensemble of multiple models helped alleviate overfitting on the small dataset compared to using Resnet50 alone.

Association Between Age and the 28-Day All-Cause Mortality in Tuberculosis Complicated by Sepsis in ICU Patients: A Retrospective Cohort Study.

Purpose: Age is considered a vital factor in intensive care units (ICUs) because of its association with physiological frailty, comorbidities, and immune system function. Previous studies have examined the association between age and prognosis in patients with tuberculosis (TB) or sepsis; however, the association between age and prognosis in ICU patients with TB complicated by sepsis is rare. This study aimed to assess the association between age and the prognosis of patients in the ICU with TB complicated by sepsis. Patients and Methods: Data from the ICU of the Public Health Clinical Center of Chengdu were analyzed using the multivariable Cox regression model, stratified analysis with interaction, restricted cubic spline (RCS), and threshold effect analysis to investigate the association between age and 28-day all-cause mortality in patients with TB complicated by sepsis. Results: In total, 520 patients diagnosed with TB and sepsis were enrolled (120 women [23.1%]; median age, 64 years). The association between age and risk of death exhibited a J-shaped curve on the RCS (P for nonlinearity = 0.001). In the threshold analysis, the hazard ratio for the risk of death was 1.104 (95% confidence interval, 1.05-1.16) in participants aged ≥66.2 years. The risk of death increased by 10.4% with every 1-year increase in age in patients with TB complicated by sepsis. No significant association was found between age and 28-day all-cause mortality in patients aged <66.2 years. Conclusion: A nonlinear relationship was observed between age and short-term all-cause mortality in patients in the ICU with TB complicated by sepsis. Patients with a higher age at admission may have a higher risk of death and require focused attention, close monitoring, and early treatment to reduce mortality.

SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions.

BACKGROUND: Detecting epistatic interactions (EIs) involves the exploration of associations among single nucleotide polymorphisms (SNPs) and complex diseases, which is an important task in genome-wide association studies. The EI detection problem is dependent on epistasis models and corresponding optimization methods. Although various models and methods have been proposed to detect EIs, identifying EIs efficiently and accurately is still a challenge. RESULTS: Here, we propose a linear mixed statistical epistasis model (LMSE) and a spherical evolution approach with a feedback mechanism (named SEEI). The LMSE model expands the existing single epistasis models such as LR-Score, K2-Score, Mutual information, and Gini index. The SEEI includes an adaptive spherical search strategy and population updating strategy, which ensures that the algorithm is not easily trapped in local optima. We analyzed the performances of 8 random disease models, 12 disease models with marginal effects, 30 disease models without marginal effects, and 10 high-order disease models. The 60 simulated disease models and a real breast cancer dataset were used to evaluate eight algorithms (SEEI, EACO, EpiACO, FDHEIW, MP-HS-DHSI, NHSA-DHSC, SNPHarvester, CSE). Three evaluation criteria (pow1, pow2, pow3), a T-test, and a Friedman test were used to compare the performances of these algorithms. The results show that the SEEI algorithm (order 1, averages ranks = 13.125) outperformed the other algorithms in detecting EIs. CONCLUSIONS: Here, we propose an LMSE model and an evolutionary computing method (SEEI) to solve the optimization problem of the LMSE model. The proposed method performed better than the other seven algorithms tested in its ability to identify EIs in genome-wide association datasets. We identified new SNP-SNP combinations in the real breast cancer dataset and verified the results. Our findings provide new insights for the diagnosis and treatment of breast cancer. AVAILABILITY AND IMPLEMENTATION: https://github.com/scutdy/SSO/blob/master/SEEI.zip .

Machine learning provides insights for spatially explicit pest management strategies by integrating information on population connectivity and habitat use in a key agricultural pest.

BACKGROUND: Insect pests have garnered increasing interest because of anthropogenic global change, and their sustainable management requires knowledge of population habitat use and spread patterns. To enhance this knowledge for the prevalent tea pest Empoasca onukii, we utilized a random forest algorithm and a bivariate map to develop and integrate models of its habitat suitability and genetic connectivity across China. RESULTS: Our modeling revealed heterogeneous spatial patterns in suitability and connectivity despite the common key environmental predictor of isothermality. Analyses indicated that tea cultivation in areas surrounding the Tibetan Plateau and the southern tip of China may be at low risk of population outbreaks because of their predicted low suitability and connectivity. However, regions along the middle and lower reaches of the Yangtze River should consider the high abundance and high recolonization potential of E. onukii, and thus the importance of control measures. Our results also emphasized the need to prevent dispersal from outside regions in the areas north of the Yangtze River and highlighted the effectiveness of internal management efforts in southwestern China and along the southeastern coast. Further projections under future conditions suggested the potential for increased abundance and spread in regions north of the Yangtze River and the southern tip of China, and indicated the importance of long-term monitoring efforts in these areas. CONCLUSION: These findings highlighted the significance of combining information on habitat use and spread patterns for spatially explicit pest management planning. In addition, the approaches we used have potential applications in the management of other pest systems and the conservation of endangered biological resources. © 2024 Society of Chemical Industry.