Investigating the relationship of co-exposure to multiple metals with chronic kidney disease: An integrated perspective from epidemiology and adverse outcome pathways.

Systematic studies on the associations between co-exposure to multiple metals and chronic kidney disease (CKD), as well as the underlying mechanisms, remain insufficient. This study aimed to provide a comprehensive perspective on the risk of CKD induced by multiple metal co-exposures through the integration of occupational epidemiology and adverse outcome pathway (AOP). The study participants included 401 male mine workers whose blood metal, ß2-microglobulin (ß2-MG), and cystatin C (Cys-C) levels were measured. Generalized linear models (GLMs), quantile g-computation models (qgcomp), least absolute shrinkage and selection operator (LASSO), and bayesian kernel machine regression (BKMR) were utilized to identify critical nephrotoxic metals. The mean concentrations of lead, cadmium, mercury, arsenic, and manganese were 191.93, 3.92, 4.66, 3.11, 11.35, and 16.33 µg/L, respectively. GLM, LASSO, qgcomp, and BKMR models consistently identified lead, cadmium, mercury, and arsenic as the primary contributors to kidney toxicity. Based on our epidemiological analysis, we used a computational toxicology method to construct a chemical-genetic-phenotype-disease network (CGPDN) from the Comparative Toxicogenomics Database (CTD), DisGeNET, and GeneCard databases, and further linked key events (KEs) related to kidney toxicity from the AOP-Wiki and PubMed databases. Finally, an AOP framework of multiple metals was constructed by integrating the common molecular initiating events (reactive oxygen species) and KEs (MAPK signaling pathway, oxidative stress, mitochondrial dysfunction, DNA damage, inflammation, hypertension, cell death, and kidney toxicity). This is the first AOP network to elucidate the internal association between multiple metal co-exposures and CKD, providing a crucial basis for the risk assessment of multiple metal co-exposures.

Therapeutic effects of natural compounds against diabetic complications via targeted modulation of ferroptosis.

Diabetes mellitus, a chronic metabolic disorder, can result in serious tissue and organ damage due to long-term metabolic dysfunction, leading to various complications. Therefore, exploring the pathogenesis of diabetic complications and developing effective prevention and treatment drugs is crucial. The role of ferroptosis in diabetic complications has emerged as a significant area of research in recent years. Ferroptosis, a recently discovered form of regulated cell death closely linked to iron metabolism imbalance and lipid peroxidation, has garnered increasing attention in studies exploring the potential role of natural products in its regulation. This review provides an overview of the mechanisms underlying ferroptosis, outlines detection methods, and synthesizes information from natural product databases. It also summarizes current research on how natural products may regulate ferroptosis in diabetic complications. Studies have shown that these products can modulate the ferroptosis process by influencing iron ion balance and combating oxidative stress. This highlights the potential of natural products in treating diabetic complications by regulating ferroptosis, offering a new strategy for managing such complications.

Role of post-translational modifications of Sp1 in cancer: state of the art.

Specific protein 1 (Sp1) is central to regulating transcription factor activity and cell signaling pathways. Sp1 is highly associated with the poor prognosis of various cancers; it is considered a non-oncogene addiction gene. The function of Sp1 is complex and contributes to regulating extensive transcriptional activity, apart from maintaining basal transcription. Sp1 activity and stability are affected by post-translational modifications (PTMs), including phosphorylation, ubiquitination, acetylation, glycosylation, and SUMOylation. These modifications help to determine genetic programs that alter the Sp1 structure in different cells and increase or decrease its transcriptional activity and DNA binding stability in response to pathophysiological stimuli. Investigating the PTMs of Sp1 will contribute to a deeper understanding of the mechanism underlying the cell signaling pathway regulating Sp1 stability and the regulatory mechanism by which Sp1 affects cancer progression. Furthermore, it will facilitate the development of new drug targets and biomarkers, thereby elucidating considerable implications in the prevention and treatment of cancer.

Evaluation of disease activity in systemic lupus erythematosus using standard deviation of lymphocyte volume combined with red blood cell count and lymphocyte percentage.

Systemic lupus erythematosus (SLE) commonly damages the blood system and often manifests as blood cell abnormalities. The performance of biomarkers for predicting SLE activity still requires further improvement. This study aimed to analyze blood cell parameters to identify key indicators for a SLE activity prediction model. Clinical data of 138 patients with SLE (high activity, n = 40; moderate activity, n = 44; mild activity, n = 37; low activity, n = 17) and 100 healthy controls (HCs) were retrospectively analyzed. Data from 89 paired admission-discharge patients with SLE were collected. Differences and associations between blood cell parameters and disease indicators, as well as the relationship between the these parameters and organ damage, were examined. Machine-learning methods were employed to develop a prediction model for disease activity evaluation. Most blood cell parameters (22/26, 84.62%) differed significantly between patients with SLE and HCs. Analysis of 89 paired patients with SLE revealed significant changes in most blood cell parameters at discharge. The standard deviation of lymphocyte volume (SD-V-LY), red blood cell (RBC) count, lymphocyte percentage (LY%), hemoglobin(HGB), hematocrit(HCT), and neutrophil percentage(NE%) correlated with disease activity. By employing machine learning, an optimal model was established to predict active SLE using SD-V-LY, RBC count, and LY% (area under the curve [AUC] = 0.908, sensitivity = 0.811). External validation indicated impressive performance (AUC = 0.940, sensitivity = 0.833). Correlation analysis revealed that SD-V-LY was positively correlated with ESR, IgG, IgA, and IgM but was negatively correlated with C3 and C4. The RBC count was linked to renal and hematopoietic system impairments, whereas LY% was associated with joint/muscle involvement. In conclusion, SD-V-LY is associated with SLE disease activity. SD-V-LY combined with RBC count and LY% contributes to a prediction model, which can be utilized as an effective tool for assessing SLE activity.

An ensemble machine learning model assists in the diagnosis of gastric ectopic pancreas and gastric stromal tumors.

OBJECTIVE: To develop an ensemble machine learning (eML) model using multiphase computed tomography (MPCT) for distinguishing between gastric ectopic pancreas (GEP) and gastric stromal tumors (GIST) in lesions < 3 cm. METHODS: In this study, we retrospectively collected MPCT images from 138 patients between April 2017 and June 2023 across two centers. Cohort 1 comprised 94 patients divided into a training cohort and an internal validation cohort, while the 44 patients from Cohort 2 constituted the external validation cohort. Deep learning (DL) models were constructed based on the lesion region, and radiomics features were extracted to develop radiomics models, which were later integrated into the fusion model. Model performance was assessed through the analysis of the area under the receiver operating characteristic curve (AUROC). The diagnostic efficacy of the optimal model was compared with that of a radiologist. Additionally, the radiologist with the assistance of the eML model provides a secondary diagnosis, to assess the potential clinical value of the model. RESULTS: After evaluation using an external validation cohort, the radiomics model demonstrated the highest performance in the venous phase, achieving AUROC of 0.87. The DL model showed optimal performance in the non-contrast phase, with AUROC of 0.81. The eML achieved the best performance across all models, with AUROC of 0.90. The use of eML-assisted analysis resulted in a significant improvement in the junior radiologist's accuracy, rising from 0.77 to 0.93 (p < 0.05). However, the senior radiologist's accuracy, while improving from 0.86 to 0.95, did not exhibit a statistically significant difference. CONCLUSION: eML model based on MPCT can effectively distinguish between GEPs and GISTs < 3 cm. CRITICAL RELEVANCE STATEMENT: The multiphase CT-based fusion model, incorporating radiomics and DL technology, proves effective in distinguishing between GEP and gastric stromal tumors, serving as a valuable tool to enhance diagnoses and offering references for clinical decision-making. KEY POINTS: No studies yet differentiated these tumors via radiomics or DL. Radiomics and DL methodologies unveil potentially distinct phenotypes within lesions. Quantitative analysis on CT for GIST and ectopic pancreas. Ensemble learning aids accurate diagnoses, assisting treatment decisions.

Clinical guidance based on MRI for the management of temporomandibular joint synovial chondromatosis: One institution's experience.

The aim of this retrospective observational study was to introduce a comprehensive MRI evaluation criterion for the clinical management of synovial chondromatosis of the temporomandibular joint (TMJ-SC). Patients received different treatments according to the MRI evaluation system: bone erosion, extent, articular disc condition, location, maturity, and size of loose body. At least a 2-year follow-up was completed to assess tumor recurrence, visual analogue scale score for pain (VAS) and maximum interincisal opening (MIO). Of the 195 patients included for TMJ-SC, 34 received arthroscopy and 161 received open surgery. Among the patients with significant extent of SC, 32 received temporary resection of the condylar neck or zygomatic arch and 2 received treatment combined with ear, nose and throat(ENT). 28 received articular disc reconstruction and 56 received disc repositioning. Patients showed good recovery of joint function with only two cases of tumor recurrence at an average follow-up of 75.1 months after surgery. The MIO had improved from 30.2 mm to 40.0 mm(P < 0.0001) and VAS had decreased from 5.1 to 0.78(P < 0.0001).The preoperative MRI evaluation principles has been effective in selecting appropriate surgical options.

Atypical effective connectivity from the frontal cortex to striatum in alcohol use disorder.

Alcohol use disorder (AUD) is a profound psychiatric condition marked by disrupted connectivity among distributed brain regions, indicating impaired functional integration. Previous connectome studies utilizing functional magnetic resonance imaging (fMRI) have predominantly focused on undirected functional connectivity, while the specific alterations in directed effective connectivity (EC) associated with AUD remain unclear. To address this issue, this study utilized multivariate pattern analysis (MVPA) and spectral dynamic causal modeling (DCM). We recruited 32 abstinent men with AUD and 30 healthy controls (HCs) men, and collected their resting-state fMRI data. A regional homogeneity (ReHo)-based MVPA method was employed to classify AUD and HC groups, as well as predict the severity of addiction in AUD individuals. The most informative brain regions identified by the MVPA were further investigated using spectral DCM. Our results indicated that the ReHo-based support vector classification (SVC) exhibits the highest accuracy in distinguishing individuals with AUD from HCs (classification accuracy: 98.57%). Additionally, our results demonstrated that ReHo-based support vector regression (SVR) could be utilized to predict the addiction severity (alcohol use disorders identification test, AUDIT, R2 = 0.38; Michigan alcoholism screening test, MAST, R2 = 0.29) of patients with AUD. The most informative brain regions for the prediction include left pre-SMA, right dACC, right LOFC, right putamen, and right NACC. These findings were validated in an independent data set (35 patients with AUD and 36 HCs, Classification accuracy: 91.67%; AUDIT, R2 = 0.17; MAST, R2 = 0.20). The results of spectral DCM analysis indicated that individuals with AUD exhibited decreased EC from the left pre-SMA to the right putamen, from the right dACC to the right putamen, and from the right LOFC to the right NACC compared to HCs. Moreover, the EC strength from the right NACC to left pre-SMA and from the right dACC to right putamen mediated the relationship between addiction severity (MAST scores) and behavioral measures (impulsive and compulsive scores). These findings provide crucial evidence for the underlying mechanism of impaired self-control, risk assessment, and impulsive and compulsive alcohol consumption in individuals with AUD, providing novel causal insights into both diagnosis and treatment.

p53 Immunohistochemistry staining patterns and prognosis significance in 212 cases of non-endometrioid endometrial cancer.

OBJECTIVE: To investigate the immunohistochemistry (IHC) staining pattern and prognostic significance of p53 in non-endometrioid endometrial cancer (non-EEC). METHODS: This study retrospectively included 212 non-EEC patients, with histological types including serous carcinoma (SC), clear cell carcinoma (CCC), mixed carcinoma (MC), undifferentiated carcinoma (UC), and carcinosarcoma (CS). p53 IHC was interpreted as normal/wild-type and abnormal/mutant-type, the latter including overexpression, complete absence, and cytoplasmic staining patterns. Moreover, uncommon p53 subclonal/heterogeneous staining patterns were described. Disease-free survival (DFS) and overall survival (OS) were employed as endpoints to evaluate the prognostic significance of p53. RESULTS: In 212 non-EEC cases, 50 (23.6 %) were p53 wild-type, while 162 (76.4 %) displayed abnormal p53 staining. Overexpression was the predominant abnormal p53 staining pattern (122/162), complete absence followed (33/162). All SCs exhibited the mutant p53 staining pattern. The p53 abnormal expression rates in CCC, MC, UC, and CS were 37.5 %, 78.9 %, 35.7 %, and 75.7 %, respectively. Interestingly, of the 12 MC cases with SC components, barring one with p53 subclonal staining, all showed the mutant-type staining. The concordance rate for p53 expression between epithelial and mesenchymal components of CS was 94.3 % (66/70). Kaplan-Meier curves indicated patients with p53 abnormalities had worse DFS compared to those with wild-type p53 (P=0.025). Multivariate Cox regression confirmed that p53 (HR: 2.270, 95 % CI: 1.124-4.586, P=0.022) independently predicted DFS in non-EEC patients, though not for OS. CONCLUSIONS: Non-EEC patients with various histological types exhibit different p53 staining patterns. However, abnormal p53 expression, regardless of histological type, implies a poor DFS in non-EEC patients.

Non-alcoholic fatty liver disease: A new predictor of recurrent ischemic stroke and transient ischemic attack in patients with carotid atherosclerosis.

PURPOSE: Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver disease. This study focused on assessing the predictive significance of NAFLD for recurrent stroke and transient ischemic attack (TIA) risk to determine the value of NAFLD. METHOD: This study included 742 participants (mean age: 64.26 ± 9.42 years, 497 males) with carotid atherosclerosis who underwent carotid CT angiography (CTA) between January 2013 and December 2021 in this retrospective study. NAFLD was diagnosed by non-enhanced abdominal CT. The clinical endpoint was a recurrent ischemic stroke or TIA. Cox proportional hazards and Kaplan-Meier analysis assessed whether NAFLD was associated with the endpoint. We accessed the predictive values of NAFLD, clinical, plaque characteristics, and combined model by the C statistics. The predictive performance of the combined model was assessed by receiver operating characteristic curve (ROC) analysis. RESULTS: A total of 742 participants (mean age: 64.26 ± 9.42 years, 497 males) were included. During 2.9 years of follow-up (interquartile range, 2.1-3.9), 166 patients reached the clinical endpoint. Multivariable cox analyses showed NAFLD was associated with recurrent stroke or TIA in all groups (all P<0.05). Patients with NAFLD had a lower event-free survival (EFS) rate than those without NAFLD (P<0.05). The combined model, including NAFLD, clinical data and plaque features, showed the best performance in predicting the clinical endpoint (AUC=0.79). CONCLUSIONS: NAFLD contributes to the prediction of recurrent ischemic stroke or TIA. NAFLD may be a novel imaging marker that offers a new perspective on preventing cardiovascular disease in the clinic.

"All-in-one" tea polyphenol-modified injectable hyaluronic acid-based hydrogel for diabetic wound healing.

Refractory diabetic wounds are a devastating and rapidly growing clinical problem, which is associated with high incidence rates, mortality, and recurrence rates. Therapeutic angiogenesis in wound tissues is essential to the healing of diabetic wounds. However, the presence of excessive oxidative stress in diabetic wounds hinders angiogenesis, and conventional anti-oxidative approaches are inefficient to compensate for the systematically impaired angiogenesis. Here, a multifunctional supramolecular hyaluronic acid hydrogel dressing for diabetic wounds is successfully designed and constructed (GHPM). The GHPM hydrogel features outstanding properties, including excellent tissue adhesion, antibacterial ability, conductivity, and antioxidant properties. Based on the dynamic crosslinking structure, the GHPM hydrogel also presents adequate injectable and self-healing capabilities, which play a vital role in covering irregular or deep wounds. Additionally, diabetic wounds treated with GHPM hydrogel showed a significant acceleration of wound closure by preventing wound infection, reducing oxidative stress, and accelerating collagen deposition. More interestingly, the combination of electrical stimulation and GHPM hydrogel can effectively promote angiogenesis and neurogenesis, further accelerating diabetic wound healing in an all-around way. This advanced collaborative strategy opens a new avenue in treating diabetic wounds.

Paternal Preconception Hepatitis B Virus Infection and Risk of Congenital Heart Disease in Offspring.

Importance: Previous evidence suggests that maternal hepatitis B virus (HBV) infection during prepregnancy or pregnancy is associated with congenital heart diseases (CHDs) in offspring. However, the association of paternal HBV infection with CHDs is not well examined. Objective: To explore the association of paternal preconception HBV infection with CHDs in offspring. Design, Setting, and Participants: This retrospective cohort study used propensity score matching of data from the Chinese National Free Preconception Checkup Project (NFPCP) from January 1, 2010, to December 31, 2018. Male participants whose wives were aged 20 to 49 years, were uninfected with HBV, and successfully conceived within 1 year after prepregnancy examination were enrolled. Data were analyzed from March 2023 to February 2024. Exposures: The primary exposure was paternal preconception HBV infection status, including uninfected, previous infection (both serum hepatitis B surface antigen and hepatitis B envelope antigen negative), and new infection (serum hepatitis B surface antigen positive). Maternal HBV immune status was further classified as immune or susceptible. Main Outcomes and Measures: The main outcome was CHDs, which were collected from the birth defect registration card of the NFPCP. Logistic regression with robust error variances was used to estimate the association between paternal preconception HBV infection and CHDs in offspring. Results: A total of 6 675 540 couples participated in the NFPCP service. After matching husbands with and without preconception HBV infection in a 1:4 ratio, 3 047 924 couples (median age of husbands, 27 years [IQR, 25-30 years]) were included in this study. Of these couples, 0.025% had offspring with CHDs. Previous paternal HBV infection was independently associated with CHDs in offspring (adjusted relative risk [ARR], 1.40; 95% CI, 1.11-1.76) compared with no infection. Similar results were obtained in subgroup analyses according to maternal HBV immune status. Compared with couples with uninfected husbands and susceptible wives, the risk of CHDs in offspring among couples with previously HBV-infected husbands was similar in couples with wives with susceptible immune status (ARR, 1.49; 95% CI, 1.10-2.03) and in those with wives with immunity (ARR, 1.49; 95%CI, 1.07-2.09). A significantly higher CHD risk in offspring was found among couples with newly infected husbands and immune wives (ARR, 1.38; 95% CI, 1.05-1.82), but there was no difference in risk among those with newly infected husbands and susceptible wives (ARR, 0.99; 95% CI, 0.72-1.36). No interactions were found between maternal immune status and paternal HBV infection. Conclusions and Relevance: In this cohort study using propensity score matching, previous paternal preconception HBV infection was associated with CHD risk in offspring. The findings suggest that personalized reproductive guidance regarding HBV screening and staying free of HBV infection should be provided for both wives and husbands.

Activity Prediction Modeling Based on a Combination of Growth Differentiation Factor 15 and Serum Biomarker Levels in Dermatomyositis and Polymyositis.

AIMS: Growth differentiation factor 15 (GDF15) plays an important role in multiple inflammatory disorders. We aimed to analyze serum GDF15 levels in adult patients with idiopathic inflammatory myopathies (IIMs). METHODS: Serum GDF15 levels were measured in 179 adult patients with IIMs and 76 healthy controls (HCs). The association between GDF15 levels and disease variables was analyzed using Spearman's rank correlation. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the discriminatory ability of GDF15 and the GDF15-to-lymphocyte ratio (GLR). Machine learning methods were applied to build predictive models. RESULTS: GDF15 levels and GLR were significantly elevated in patients with adult IIMs than in HCs. Compared with patients in remission, both GDF15 and GLR were significantly higher in myositis patients in an active phase. GDF15 levels correlated positively with myositis disease activity indices and negatively correlated with lymphocyte and platelet counts. ROC curve analysis revealed that GDF15 levels and GLR outperformed muscle enzymes and distinguished well between patients with active disease and those in remission. Furthermore, even in the normal muscle enzyme group, GDF15 levels and GLR were also well-distinguished between patients with active disease and those in remission. Using machine learning, a logistic regression model of GDF15 combined with creatine kinase and lymphocyte count was constructed and had a reliable predictive value for disease activity. CONCLUSIONS: GDF15, particularly GLR, was significantly correlated with disease activity in adult patients with IIMs. They could serve as useful biochemical markers for evaluating disease activity, monitoring disease progression, and guiding treatment in adult patients with IIMs.

Unveiling the Potential of Sulfur-Containing Gas Signaling Molecules in Acute Lung Injury: A Promising Therapeutic Avenue.

Acute lung injury (ALI) and its most severe form, acute respiratory distress syndrome (ARDS), are pulmonary conditions that cause significant morbidity and mortality. The common etiologies of these conditions include pneumonia, pulmonary contusion, fat embolism, smoke inhalation, sepsis, shock, and acute pancreatitis. Inflammation, oxidative stress, apoptosis, and autophagy are key pathophysiological mechanisms underlying ALI. Hydrogen sulfide (H2S) and sulfur dioxide (SO2) are sulfur-containing gas signaling molecules that can mitigate these pathogenic processes by modulating various signaling pathways, such as toll-like receptor 4 (TLR4)/nod-like receptor protein 3 (NLRP3), extracellular signal-regulating protein kinase 1/2 (ERK1/2), mitogen-activated protein kinase (MAPK), phosphatidyl inositol 3 kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR), and nuclear factor kappa B (NF-κB), thereby conferring protection against ALI. Given the limited clinical effectiveness of prevailing ALI treatments, investigation of the modulation of sulfur-containing gas signaling molecules (H2S and SO2) in ALI is imperative. This article presents an overview of the regulatory pathways of sulfur-containing gas signaling molecules in ALI animal models induced by various stimuli, such as lipopolysaccharide, gas inhalation, oleic acid, and ischemia-reperfusion. Furthermore, this study explored the therapeutic prospects of diverse H2S and SO2 donors for ALI, stemming from diverse etiologies. The aim of the present study was to establish a theoretical framework, in order to promote the new treatment of ALI.

Biomaterial Fg/P(LLA-CL) regulates macrophage polarization and recruitment of mesenchymal stem cells after endometrial injury.

The process of endometrial repair after injury involves the synergistic action of various cells including immune cells and stem cells. In this study, after combing Fibrinogen(Fg) with poly(L-lacticacid)-co-poly(ε-caprolactone)(P(LLA-CL)) by electrospinning, we placed Fg/P(LLA-CL) into the uterine cavity of endometrium-injured rats, and bioinformatic analysis revealed that Fg/P(LLA-CL) may affect inflammatory response and stem cell biological behavior. Therefore, we verified that Fg/P(LLA-CL) could inhibit the lipopolysaccharide (LPS)-stimulated macrophages from switching to the pro-inflammatory M1 phenotype in vitro. Moreover, in the rat model of endometrial injury, Fg/P(LLA-CL) effectively promoted the polarization of macrophages towards the anti-inflammatory M2 phenotype and enhanced the presence of mesenchymal stem cells at the injury site. Overall, Fg/P(LLA-CL) exhibits significant influence on macrophage polarization and stem cell behavior in endometrial injury, justifying further exploration for potential therapeutic applications in endometrial and other tissue injuries.

Therapeutic Potential of Hydrogen Sulfide in Ischemia and Reperfusion Injury.

Ischemia-reperfusion (I/R) injury, a prevalent pathological condition in medical practice, presents significant treatment challenges. Hydrogen sulfide (H2S), acknowledged as the third gas signaling molecule, profoundly impacts various physiological and pathophysiological processes. Extensive research has demonstrated that H2S can mitigate I/R damage across multiple organs and tissues. This review investigates the protective effects of H2S in preventing I/R damage in the heart, brain, liver, kidney, intestines, lungs, stomach, spinal cord, testes, eyes, and other tissues. H2S provides protection against I/R damage by alleviating inflammation and endoplasmic reticulum stress; inhibiting apoptosis, oxidative stress, and mitochondrial autophagy and dysfunction; and regulating microRNAs. Significant advancements in understanding the mechanisms by which H2S reduces I/R damage have led to the development and synthesis of H2S-releasing agents such as diallyl trisulfide-loaded mesoporous silica nanoparticles (DATS-MSN), AP39, zofenopril, and ATB-344, offering a new therapeutic avenue for I/R injury.

Development and validation of peritumoral vascular and intratumoral radiomics to predict pathologic complete responses to neoadjuvant chemotherapy in patients with triple-negative breast cancer.

BACKGROUND: To develop and validate a peritumoral vascular and intratumoral radiomics model to improve pretreatment predictions for pathologic complete responses (pCRs) to neoadjuvant chemoradiotherapy (NAC) in patients with triple-negative breast cancer (TNBC). METHODS: A total of 282 TNBC patients (93 in the primary cohort, 113 in the validation cohort, and 76 in The Cancer Imaging Archive [TCIA] cohort) were retrospectively included. The peritumoral vasculature on the maximum intensity projection (MIP) from pretreatment DCE-MRI was segmented by a Hessian matrix-based filter and then edited by a radiologist. Radiomics features were extracted from the tumor and peritumoral vasculature of the MIP images. The LASSO method was used for feature selection, and the k-nearest neighbor (k-NN) classifier was trained and validated to build a predictive model. The diagnostic performance was assessed using the ROC analysis. RESULTS: One hundred of the 282 patient (35.5%) with TNBC achieved pCRs after NAC. In predicting pCRs, the combined peritumoral vascular and intratumoral model (fusion model) yields a maximum AUC of 0.82 (95% confidence interval [CI]: 0.75, 0.88) in the primary cohort, a maximum AUC of 0.67 (95% CI: 0.57, 0.76) in the internal validation cohort, and a maximum AUC of 0.65 (95% CI: 0.52, 0.78) in TCIA cohort. The fusion model showed improved performance over the intratumoral model and the peritumoral vascular model, but not significantly (p > 0.05). CONCLUSION: This study suggested that combined peritumoral vascular and intratumoral radiomics model could provide a non-invasive tool to enable prediction of pCR in TNBC patients treated with NAC.

Polyoxometalate functionalized magnetic metal-organic framework with multi-affinity sites for efficient enrichment of phosphopeptides.

The reasonable design of metal-organic framework (MOF)-derived nanomaterial has important meaning in increasing the enrichment efficiency in the study of protein phosphorylation. In this work, a polyoxometalate (POM) functionalized magnetic MOF nanomaterial (Fe3O4@MIL-125-POM) was designed and fabricated. The nanomaterial with multi-affinity sites (unsaturated metal sites and metal oxide clusters) was used for the enrichment of phosphopeptides. Fe3O4@MIL-125-POM had high-efficient enrichment performance towards phosphopeptides (selectivity, a mass ratio of bovine serum albumin/α-casein/ß-casein at 5000:1:1; sensitivity, 0.1 fmol; satisfactory repeatability, ten times). Furthermore, Fe3O4@MIL-125-POM was employed to enrich phosphopeptides from non-fat milk digests, saliva, serum, and A549 cell lysate. The enrichment results illustrated the great potential of Fe3O4@MIL-125-POM for efficient identification of low-abundance phosphopeptides.

Chronic Lead Exposure in Adult Mice: Associations with miR-671/CDR1as Regulation, NF-κB Signaling, and Alzheimer's Disease-like Pathology.

Long-term exposure to lead (Pb) can result in chronic damage to the body through accumulation in the central nervous system (CNS) leading to neurodegenerative diseases, such as Alzheimer's disease (AD). This study delves into the intricate role of miR-671/CDR1as regulation in the etiology of AD-like lesions triggered by chronic Pb exposure in adult mice. To emulate the chronic effects of Pb, we established a rodent model spanning 10 months of controlled Pb administration, dividing 52 C57BL/6J mice into groups receiving varying concentrations of Pb (1, 2, or 4 g/L) alongside an unexposed control. Blood Pb levels were monitored using serum samples to ensure accurate dosing and to correlate with observed toxicological outcomes. Utilizing the Morris water maze, a robust behavioral assay for assessing cognitive functions, we documented a dose-dependent decline in learning and memory capabilities among the Pb-exposed mice. Histopathological examination of the hippocampal tissue revealed tell-tale signs of AD-like neurodegeneration, characterized by the accumulation of amyloid plaques and neurofibrillary tangles. At the molecular level, a significant upregulation of AD-associated genes, namely amyloid precursor protein (APP), ß-secretase 1 (BACE1), and tau, was observed in the hippocampal tissue of Pb-exposed mice. This was accompanied by a corresponding surge in the protein levels of APP, BACE1, amyloid-ß (Aß), and phosphorylated tau (p-tau), further implicating Pb in the dysregulation of these key AD markers. The expression of CDR1as, a long non-coding RNA implicated in AD pathogenesis, was found to be suppressed in Pb-exposed mice. This observation suggests a potential mechanistic link between Pb-induced neurotoxicity and the dysregulation of the CDR1as/miR-671 axis, which warrants further investigation. Moreover, our study identified a dose-dependent alteration in the intracellular and extracellular levels of the transcription factor nuclear factor-kappa B (NF-κB). This finding implicates Pb in the modulation of NF-κB signaling, a pathway that plays a pivotal role in neuroinflammation and neurodegeneration. In conclusion, our findings underscored the deleterious effects of Pb exposure on the CNS, leading to the development of AD-like pathology. The observed modulation of NF-κB signaling and miR-671/CDR1as regulation provides a plausible mechanistic framework for understanding the neurotoxic effects of Pb and its potential contribution to AD pathogenesis.

Law compliance decision making for autonomous vehicles on highways.

As autonomous driving advances, autonomous vehicles will share the road with human drivers. This requires autonomous vehicles to adhere to human traffic laws under safe conditions. Simultaneously, when confronted with dangerous situations, autonomous driving should also possess the capability to deviate from traffic laws to ensure safety. However, current autonomous vehicles primarily prioritize safety and collision avoidance in their decision-making and planning. This may lead to misunderstandings and distrust from human drivers in mixed traffic flow, and even accidents. To address this, this paper proposes a decoupled hierarchical framework for compliance safety decision-making. The framework primarily consists of two layers: the decision-making layer and the motion planning layer. In the decision-making layer, a candidate behavior set is constructed based on the scenario, and a dual layer admission assessment is utilized to filter out unsafe and non-compliant behaviors from the candidate sets. Subsequently, the optimal behavior is selected as the decision behavior according to the designed evaluation metrics. The decision-making layer ensures that the vehicle can meet lane safety requirements and comply with static traffic laws. In the motion planning layer, the surrounding vehicles and the road are modeled as safety potential fields and traffic laws potential fields. Combining the optimal decision behavior, they are incorporated into the cost function of the model predictive control to achieve compliant and safe trajectory planning. The planning layer ensures that the vehicle meets trajectory safety requirements and complies with dynamic traffic laws under safe conditions. Finally, four typical scenarios are used to evaluate the effectiveness of the proposed method. The results indicate that the proposed method can ensure compliance in safe conditions while also temporarily deviating from traffic laws in emergency situations to ensure safety.

Cobalt Phthalocyanine-Modified Magnetic Metal-Organic Frameworks for Specific Enrichment of Phosphopeptides.

For mass spectrometry (MS)-based phosphoproteomics studies, sample pretreatment is an essential step for efficient identification of low-abundance phosphopeptides. Herein, a cobalt phthalocyanine-modified magnetic metal-organic framework (MOF) (Fe3O4@MIL-101-CoPc) was prepared and applied to enrich phosphopeptides before MS analysis. Fe3O4@MIL-101-CoPc exhibited an excellent magnetic response (74.98 emu g-1) and good hydrophilicity (7.75°), which were favorable for the enrichment. Fe3O4@MIL-101-CoPc showed good enrichment performance with high selectivity (1:1:5000), sensitivity (0.1 fmol), reusability (10 circles), and recovery (91.3%). Additionally, the Fe3O4@MIL-101-CoPc-based MS method was able to successfully detect 827 phosphopeptides from the A549 cell lysate, demonstrating a high enrichment efficiency (89.3%). This study promotes the application of postfunctionalized MOFs for phosphoproteomics analysis.