Clinical features combined with ultrasound characteristics to predict TERT promoter mutations in papillary thyroid carcinoma: a single-center study over the past 5 years.

Purpose: Telomerase reverse transcriptase (TERT) has been reported in papillary thyroid carcinoma (PTC). This study aimed to investigate the correlation of TERT promoter mutations with clinical and ultrasound (US) features in PTC and to develop a model to predict TERT promoter mutations. Methods: Preoperative US images, postoperative pathological features, and TERT promoter mutation information were evaluated in 365 PTC patients confirmed by surgery. Univariate and multivariate factor analyses were performed to identify risk factors for TERT promoter mutations. A predictive model was established to assess the clinical predictive value. Results: Of the 365 patients with PTC (498 nodules), the number of those with TERT promoter mutations was 67 cases (75 nodules), and the number of those without mutations was 298 cases (423 nodules). The median age was 40 years in the wild-type group and 60 years in the mutant group. Male patients made up 35.82% of the mutant group and 22.82% of the wild-type group. Multivariate analysis revealed that the independent risk factors associated with the occurrence of TERT promoter mutation in PTC were as follows: older age (odds ratio (OR) = 1.07; p = 0.002), maximum diameter of ≥ 10 mm (OR = 3.94; p < 0.0001), unilateral (OR = 4.15; p < 0.0001), multifocal (OR = 7.69; p < 0.0001), adjacent to the thyroid capsule (OR = 1.94; p = 0.044), and accompanied by other benign nodules (OR = 1.94, p = 0.039). A predictive model was established, and the area under the curve (AUC) of the receiver operating characteristic was 0.839. TERT promoter mutations were associated with high-risk US and clinical features compared with the wild-type group. Conclusion: TERT promoter mutations were associated with older ages. They were also found to be multifocal, with a maximum diameter of ≥ 10 mm, unilateral, adjacent to the thyroid capsule, and accompanied by other benign nodules. The predictive model was of high diagnostic value.

STING agonist, SMA-2, inhibits clear cell renal cell carcinoma through improving tumor microenvironment.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent and lethal subtype of kidney cancer, patients with ccRCC usually have very poor prognosis and short survival. Therefore, it is urgent to develop more effective therapeutics or medications to suppress ccRCC progression. Here, we demonstrated that STING agonist, MSA-2 significantly inhibits tumor progress and prolongs the survival of ccRCC mice by promoting cytokines secretion. Moreover, MSA-2 triggered the trafficking and infiltration of CD8+ T cells, supported by the generation of a chemokine milieu that promoted recruitment and modulation of the immunosuppressive TME in ccRCC. These findings suggest that MSA-2 potentially serves an effective and preferable adjuvant immunotherapy of ccRCC.

Epidemiological and Clinical Characteristics of Neonatal Ureaplasma urealyticum Infection.

Purpose: To understand the epidemiology and clinical features of Ureaplasma urealyticum (UU) infection in hospitalized neonates due to vertical transmission from mother to child. Methods: Respiratory secretions were collected from neonates hospitalized in the neonatology department of the Maternal and Child Health Hospital of Hubei Province from July 2020 to June 2022, and PCR was used to detect UU-DNA in respiratory secretions. The neonates were divided into UU-positive and UU-negative groups, the epidemiological and clinical characteristics of two groups, were statistically analyzed. Results: A total of 7257 hospitalized neonates were included in this study, of whom 561 were UU positive and 6696 were UU negative, with a UU detection rate of 7.73%. The detection rate among female neonates was higher than male neonates, and the highest detection rate was found in the period from 1-7 days after birth; the detection rate was highest in spring and fall, and the lowest in winter, but the overall difference was not statistically significant (P>0.05). Compared with the UU-negative group, neonates in the UU-positive group were more likely to be preterm, have a lower birth weight, be delivered vaginally, and have maternal preterm rupture of membranes. In addition, neonates in the UU-positive group were more likely to be co-infected with pathogens and to have complications related to UU infections, which were all statistically significant (P<0.05). Conclusion: Neonatal UU infections are detected more frequently in female infants, with the highest detection rate occurring in 1-7 days after birth, and the most prevalent periods for infection being spring and fall. Vaginal delivery and premature rupture of membranes may lead to an increased risk of vertical UU transmission from mother to child, and UU infection is strongly associated with preterm labor, low birth weight, pathogen co-infection, and related complications.

Induction of therapeutic immunity and cancer eradication through biofunctionalized liposome-like nanovesicles derived from irradiated-cancer cells.

Immunotherapy has revolutionized the treatment of cancer. However, its efficacy remains to be optimized. There are at least two major challenges in effectively eradicating cancer cells by immunotherapy. Firstly, cancer cells evade immune cell killing by down-regulating cell surface immune sensors. Secondly, immune cell dysfunction impairs their ability to execute anti-cancer functions. Radiotherapy, one of the cornerstones of cancer treatment, has the potential to enhance the immunogenicity of cancer cells and trigger an anti-tumor immune response. Inspired by this, we fabricate biofunctionalized liposome-like nanovesicles (BLNs) by exposing irradiated-cancer cells to ethanol, of which ethanol serves as a surfactant, inducing cancer cells pyroptosis-like cell death and facilitating nanovesicles shedding from cancer cell membrane. These BLNs are meticulously designed to disrupt both of the aforementioned mechanisms. On one hand, BLNs up-regulate the expression of calreticulin, an "eat me" signal on the surface of cancer cells, thus promoting macrophage phagocytosis of cancer cells. Additionally, BLNs are able to reprogram M2-like macrophages into an anti-cancer M1-like phenotype. Using a mouse model of malignant pleural effusion (MPE), an advanced-stage and immunotherapy-resistant cancer model, we demonstrate that BLNs significantly increase T cell infiltration and exhibit an ablative effect against MPE. When combined with PD-1 inhibitor (α-PD-1), we achieve a remarkable 63.6% cure rate (7 out of 11) among mice with MPE, while also inducing immunological memory effects. This work therefore introduces a unique strategy for overcoming immunotherapy resistance.

Prediction of lymph node metastasis in patients with papillary thyroid cancer based on radiomics analysis and intraoperative frozen section analysis: A retrospective study.

INTRODUCTION: To evaluate the diagnostic efficiency among the clinical model, the radiomics model and the nomogram that combined radiomics features, frozen section (FS) analysis and clinical characteristics for the prediction of lymph node (LN) metastasis in patients with papillary thyroid cancer (PTC). METHODS: A total of 208 patients were randomly divided into two groups randomly with a proportion of 7:3 for the training groups (n = 146) and the validation groups (n = 62). The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for the selection of radiomics features extracted from ultrasound (US) images. Univariate and multivariate logistic analyses were used to select predictors associated with the status of LN. The clinical model, radiomics model and nomogram were subsequently established by logistic regression machine learning. The area under the curve (AUC), sensitivity and specificity were used to evaluate the diagnostic performance of the different models. The Delong test was used to compare the AUC of the three models. RESULTS: Multivariate analysis indicated that age, size group, Adler grade, ACR score and the psammoma body group were independent predictors of lymph node metastasis (LNM). The results showed that in both the training and validation groups, the nomogram showed better performance than the clinical model, albeit not statistically significant (p > .05), and significantly outperformed the radiomics model (p < .05). However, the nomogram exhibits a slight improvement in sensitivity that could reduce the incidence of false negatives. CONCLUSION: We propose that the nomogram holds substantial promise as an effective tool for predicting LNM in patients with PTC.

[Banxia Xiexin Decoction inhibiting colitis-associated colorectal cancer infected with Fusobacterium nucleatum by regulating Wnt/ß-catenin pathway].

This paper investigates the intervention effect and mechanism of Banxia Xiexin Decoction(BXD) on colitis-associated colorectal cancer(CAC) infected with Fusobacterium nucleatum(Fn). C57BL/6 mice were randomly divided into a control group, Fn group, CAC group [azoxymethane(AOM)/dextran sulfate sodium salt(DSS)](AOM/DSS), model group, and BXD group. Except for the control and AOM/DSS groups, the mice in the other groups were orally administered with Fn suspension twice a week. The AOM/DSS group, model group, and BXD group were also injected with a single dose of 10 mg·kg~(-1) AOM combined with three cycles of 2.5% DSS taken intragastrically. The BXD group received oral administration of BXD starting from the second cycle until the end of the experiment. The general condition and weight changes of the mice were monitored during the experiment, and the disease activity index(DAI) was calculated. At the end of the experiment, the colon length and weight of the mice in each group were compared. Hematoxylin-eosin(HE) staining was used to observe the pathological changes in the colon tissue. Enzyme-linked immunosorbent assay(ELISA) was used to detect the levels of interleukin(IL)-2, IL-4, and IL-6 inflammatory factors in the serum. Immunohistochemistry(IHC) was used to detect the expression of Ki67, E-cadherin, and ß-catenin in the colon tissue. Western blot was used to detect the protein content of Wnt3a, ß-catenin, E-cadherin, annexin A1, cyclin D1, and glycogen synthase kinase-3ß(GSK-3ß) in the colon tissue. The results showed that compared with the control group, the Fn group had no significant lesions. The mice in the AOM/DSS group and model group had decreased body weight, increased DAI scores, significantly increased colon weight, and significantly shortened colon length, with more significant lesions in the model group. At the same time, the colon histology of the model group showed more severe adenomas, inflammatory infiltration, and cellular dysplasia. The levels of IL-4 and IL-6 in the serum were significantly increased, while the IL-2 content was significantly decreased. The IHC results showed low expression of E-cadherin and high expression of Ki67 and ß-catenin in the model group, with a decreased protein content of E-cadherin and GSK-3ß and an increased protein content of Wnt3a, ß-catenin, annexin A1, and cyclin D1. After intervention with BXD, the body weight of the mice increased; the DAI score decreased; the colon length increased, and the tumor decreased. The histopathology showed reduced tumor proliferation and reduced inflammatory infiltration. The levels of IL-6 and IL-4 in the serum were significantly decreased, while the IL-2 content was increased. Meanwhile, the expression of E-cadherin was upregulated, and that of Ki67 and ß-catenin was downregulated. The protein content of E-cadherin and GSK-3ß increased, while that of Wnt3a, ß-catenin, annexin A1, and cyclin D1 decreased. In conclusion, BXD can inhibit CAC infected with Fn, and its potential mechanism may be related to the inhibition of Fn binding to E-cadherin, the decrease in annexin A1 protein level, and the regulation of the Wnt/ß-catenin pathway.

Dose‒Response Effects of Patient Engagement on Anxiety and Depression in a Cognitive-Behavioral Intervention: Secondary Analysis of a Pilot Randomized Controlled Trial and a Clinical Controlled Trial.

Understanding the dose‒response relationship between patient engagement in cognitive behavioral therapy (CBT) and health outcomes is critical for developing and implementing effective CBT programs. In studies of CBT interventions, patient engagement is measured only at a single time point, and outcomes are typically assessed before and after the intervention. Examination of the dose‒response relationship between patient engagement in CBT and outcomes is limited. It is unclear whether a dose‒response relationship exists between patient engagement in on-site CBT intervention and anxiety and depression in people living with HIV (PLWH). If present, does this dose‒response relationship occur early or later in the intervention? This study aimed to address this gap by examining the dose‒response relationships between patient engagement and anxiety and depression in CBT interventions among PLWH. Utilizing data from a pilot randomized trial (10 participants) and a clinical controlled trial (70 participants), our secondary analysis spans baseline, 3-month, and 6-month assessments. Both trials implemented the nurse-led CBT intervention. Cluster analysis identified two groups based on on-site attendance and WeChat activity. Patients with good adherence (6-10 times) of on-site attendance exhibited significantly lower anxiety and depression scores at 3 months (ß = 1.220, P = 0.047; ß = 1.270, P = 0.019), with no significant differences observed at 6 months. WeChat activity did not significantly influence anxiety or depression scores. The findings highlight a significant short-term dose‒response relationship, endorsing nurse-led CBT interventions for mental health in PLWH. Organizational strategies should focus on incentivizing and facilitating patient engagement, particularly through enhancing WeChat features.

Smart osteoclasts targeted nanomedicine based on amorphous CaCO3 for effective osteoporosis reversal.

BACKGROUND: Osteoporosis is characterized by an imbalance in bone homeostasis, resulting in the excessive dissolution of bone minerals due to the acidified microenvironment mediated by overactive osteoclasts. Oroxylin A (ORO), a natural flavonoid, has shown potential in reversing osteoporosis by inhibiting osteoclast-mediated bone resorption. The limited water solubility and lack of targeting specificity hinder the effective accumulation of Oroxylin A within the pathological environment of osteoporosis. RESULTS: Osteoclasts' microenvironment-responsive nanoparticles are prepared by incorporating Oroxylin A with amorphous calcium carbonate (ACC) and coated with glutamic acid hexapeptide-modified phospholipids, aiming at reinforcing the drug delivery efficiency as well as therapeutic effect. The obtained smart nanoparticles, coined as OAPLG, could instantly neutralize acid and release Oroxylin A in the extracellular microenvironment of osteoclasts. The combination of Oroxylin A and ACC synergistically inhibits osteoclast formation and activity, leading to a significant reversal of systemic bone loss in the ovariectomized mice model. CONCLUSION: The work highlights an intelligent nanoplatform based on ACC for spatiotemporally controlled release of lipophilic drugs, and illustrates prominent therapeutic promise against osteoporosis.

Exploring Stigma Experience and Coping Strategies Among Women Living with HIV/AIDS in China: A Phenomenological Study.

Purpose: As of the end of 2022, over 20 million women worldwide, aged 15 and above, are living with HIV. Stigma remains a formidable barrier for women living with HIV/AIDS, hindering their access to healthcare and exacerbating health disparities. Indeed, some women living with HIV/AIDS can successfully confront and overcome stigma. There remains a paucity of qualitative research exploring the stigma coping strategies of women living with HIV/AIDS in China. This study was aimed to gain the deeper understanding of stigma experienced by women living with HIV/AIDS and coping strategies. Patients and Methods: We recruited diverse participants using snowball sampling and purposive sampling. Semi-structured personal in-depth interviews were conducted with 30 women living with HIV/AIDS from December 2022 to June 2023. The samples were from four HIV/AIDS designated hospitals. The data were analyzed using the Colaizzi seven-step model. Results: The experiences of stigma among women living with HIV/AIDS included family role (wife/mother/grandmother) collapse and disgusted by family, resignation in being shunned by others, helplessness due to social exclusion, grief at being devaluated, and resentment for experiencing injustice. The coping strategies used to deal with stigma included concealing their conditions, avoiding socialization, and attempting to retaliate against society. Conclusion: Healthcare professionals are recommended to offer women living with HIV/AIDS effective emotional support and guidance to cope with stigma. The study highlights the stigma they face, providing valuable evidence for policymakers. Recommendations emphasize the importance of developing services addressing both physical and psychological needs of women living with HIV/AIDS.

Prediction of High-Risk Gastrointestinal Stromal Tumor Recurrence Based on Delta-CT Radiomics Modeling: A 3-Year Follow-up Study After Surgery.

Background: Medium- to high-risk classification-gastrointestinal stromal tumors (MH-GIST) have a high recurrence rate and are difficult to treat. This study aims to predict the recurrence of MH-GIST within 3 years after surgery based on clinical data and preoperative Delta-CT Radiomics modeling. Methods: A retrospective analysis was conducted on clinical imaging data of 242 cases confirmed to have MH-GIST after surgery, including 92 cases of recurrence and 150 cases of normal. The training set and test set were established using a 7:3 ratio and time cutoff point. In the training set, multiple prediction models were established based on clinical data of MH-GIST and the changes in radiomics texture of enhanced computed tomography (CT) at different time periods (Delta-CT radiomics). The area under curve (AUC) values of each model were compared using the Delong test, and the clinical net benefit of the model was tested using decision curve analysis (DCA). Then, the model was externally validated in the test set, and a novel nomogram predicting the recurrence of MH-GIST was finally created. Results: Univariate analysis confirmed that tumor volume, tumor location, neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), diabetes, spicy hot pot, CT enhancement mode, and Radscore 1/2 were predictive factors for MH-GIST recurrence (P < .05). The combined model based on these above factors had significantly higher predictive performance (AUC = 0.895, 95% confidence interval [CI] = [0.839-0.937]) than the clinical data model (AUC = 0.735, 95% CI = [0.6 62-0.800]) and radiomics model (AUC = 0.842, 95% CI = [0.779-0.894]). Decision curve analysis also confirmed the higher clinical net benefit of the combined model, and the same results were validated in the test set. The novel nomogram developed based on the combined model helps predict the recurrence of MH-GIST. Conclusions: The nomogram of clinical and Delta-CT radiomics has important clinical value in predicting the recurrence of MH-GIST, providing reliable data reference for its diagnosis, treatment, and clinical decision-making.

Suppressing label noise in medical image classification using mixup attention and self-supervised learning.

Deep neural networks (DNNs) have been widely applied in medical image classification and achieve remarkable classification performance. These achievements heavily depend on large-scale accurately annotated training data. However, label noise is inevitably introduced in the medical image annotation, as the labeling process heavily relies on the expertise and experience of annotators. Meanwhile, DNNs suffer from overfitting noisy labels, degrading the performance of models. Therefore, in this work, we innovatively devise noise-robust training approach to mitigate the adverse effects of noisy labels in medical image classification. Specifically, we incorporate contrastive learning and intra-group attention mixup strategies into the vanilla supervised learning. The contrastive learning for feature extractor helps to enhance visual representation of DNNs. The intra-group attention mixup module constructs groups and assigns self-attention weights for group-wise samples, and subsequently interpolates massive noisy-suppressed samples through weighted mixup operation. We conduct comparative experiments on both synthetic and real-world noisy medical datasets under various noise levels. Rigorous experiments validate that our noise-robust method with contrastive learning and attention mixup can effectively handle with label noise, and is superior to state-of-the-art methods. An ablation study also shows that both components contribute to boost model performance. The proposed method demonstrates its capability of curb label noise and has certain potential toward real-world clinic applications.

Microglia and macrophage metabolism: a regulator of cerebral gliomas.

Reciprocal interactions between the tumor microenvironment (TME) and cancer cells play important roles in tumorigenesis and progression of glioma. Glioma-associated macrophages (GAMs), either of peripheral origin or representing brain-intrinsic microglia, are the majority population of infiltrating immune cells in glioma. GAMs, usually classified into M1 and M2 phenotypes, have remarkable plasticity and regulate tumor progression through different metabolic pathways. Recently, research efforts have increasingly focused on GAMs metabolism as potential targets for glioma therapy. This review aims to delineate the metabolic characteristics of GAMs within the TME and provide a summary of current therapeutic strategies targeting GAMs metabolism in glioma. The goal is to provide novel insights and therapeutic pathways for glioma by highlighting the significance of GAMs metabolism.

Colon microbiota and metabolite potential impact on tail fat deposition of Altay sheep.

Tail fat deposition of Altay sheep not only increased the cost of feeding but also reduced the economic value of meat. Currently, because artificial tail removal and gene modification methods cannot solve this problem, it is maybe to consider reducing tail fat deposition from the path of intestinal microbiota and metabolite. We measured body weight and tail fat weight, collected the serum for hormone detection by enzyme-linked immunosorbent assay, and collected colon contents to 16S rRNA sequence and liquid chromotography with mass spectrometry detection to obtain colon microbiota and metabolite information, from 12 3-month-old and 6-month-old Altay sheep. Subsequently, we analyzed the correlation between colon microbiota and tail fat weight, hormones, and metabolites, respectively. We identified that the tail fat deposition of Altay sheep increased significantly with the increase of age and body weight, and the main microbiota that changed were Verrucomicrobia, Cyanobacteria, Akkermansia, Bacteroides, Phocaeicola, Escherichia-Shigella, and Clostridium_sensu_stricto_1. The results indicated that the diversities of metabolites in the colon contents of 3-months old and 6-months old were mainly reflected in phosphocholine (PC) and phosphatidylethanolamine (PE) in the lipid metabolism pathway. The correlations analyzed showed that Verrucomicrobia, Chlamydiae, Akkermansia, Ruminococcaceae_UCG-005, Bacteroides, and Phocaeicola were negatively correlated with tail fat deposition. Verrucomicrobia, Akkermansia, and Bacteroides were negatively correlated with growth hormone (GH). Verrucomicrobia was positively correlated with L-a-lysophosphatidylserine and PE(18:1(9Z)/0:0). Our results showed that tail fat deposition of Altay sheep was probably correlated with the abundance of Verrucomicrobia, Akkermansia, Bacteroides of colon microbiota, PC, PE of metabolites, and GH of serum. IMPORTANCE: Excessive tail fat deposition of Altay sheep caused great economic losses, and the current research results could not solve this problem well. Now, our research speculates that the tail fat deposition of Aletay sheep may be related to the abundance of Verrucomicrobia, Akkermansia, Bacteroides, metabolites phosphocholine, phosphatidylethanolamine, and growth hormone of serum. Further investigation of the interaction mechanism between these microbiota or metabolites and tail fat deposition is helpful in reducing tail fat deposition of Altay sheep and increasing the economic benefits of breeding farms.

Using Pupil Diameter for Psychological Resilience Assessment in Medical Students Based on SVM and SHAP Model.

Effectively assessing psychological resilience for medical students is vital for identifying at-risk individuals and developing tailored interventions. At present, few studies have combined physiological indexes of the human body and machine learning for psychological resilience assessment. This study presents a novel approach that employs pupil diameter features and machine learning to predict psychological resilience risk objectively. Firstly, we designed a stimulus paradigm (via auditory and visual stimuli) and collected pupil diameter data from participants using eye-tracking technology. Secondly, the pupil data was preprocessed, including linear interpolation, blink detection, and subtractive baseline correction. Thirdly, statistical metrics were extracted and optimal feature subsets were obtained by Recursive Feature Elimination with Cross-Validation (RFECV). Subsequently, the classification models, including Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost), were trained. The experimental results show that the SVM model has the best performance, and its balance accuracy, recall, and AUC reach 0.906, 0.89, and 0.932, respectively. Finally, we leveraged the Shapley additive explanation (SHAP) model for interpretability analysis. It revealed auditory stimuli have a more significant effect than visual stimuli in psychological resilience assessment. These findings suggested that pupil diameter could be a vital metric for assessing psychological resilience.

Effects of Lactobacillus paracasei N1115 on gut microbial imbalance and liver function in patients with hepatitis B-related cirrhosis.

BACKGROUND: Hepatitis B cirrhosis (HBC) is a chronic disease characterized by irreversible diffuse liver damage and aggravated by intestinal microbial imbalance and metabolic dysfunction. Although the relationship between certain single probiotics and HBC has been explored, the impact of the complex ready-to-eat Lactobacillus paracasei N1115 (LP N1115) supplement on patients with HBC has not been determined. AIM: To compare the changes in the microbiota, inflammatory factor levels, and liver function before and after probiotic treatment in HBC patients. METHODS: This study included 160 HBC patients diagnosed at the General Hospital of Ningxia Medical University between October 2018 and December 2020. Patients were randomly divided into an intervention group that received LP N1115 supplementation and routine treatment and a control group that received routine treatment only. Fecal samples were collected at the onset and conclusion of the 12-wk intervention period. The structure of the intestinal microbiota and the levels of serological indicators, such as liver function and inflammatory factors, were assessed. RESULTS: Following LP N1115 intervention, the intestinal microbial diversity significantly increased in the intervention group (P < 0.05), and the structure of the intestinal microbiota was characterized by an increase in the proportions of probiotic microbes and a reduction in harmful bacteria. Additionally, the intervention group demonstrated notable improvements in liver function indices and significantly lower levels of inflammatory factors (P < 0.05). CONCLUSION: LP N1115 is a promising treatment for ameliorating intestinal microbial imbalance in HBC patients by modulating the structure of the intestinal microbiota, improving liver function, and reducing inflammatory factor levels.

Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging.

Identifying the progression stages of Alzheimer's disease (AD) can be considered as an imbalanced multi-class classification problem in machine learning. It is challenging due to the class imbalance issue and the heterogeneity of the disease. Recently, graph convolutional networks (GCNs) have been successfully applied in AD classification. However, these works did not handle the class imbalance issue in classification. Besides, they ignore the heterogeneity of the disease. To this end, we propose a novel cost-sensitive weighted contrastive learning method based on graph convolutional networks (CSWCL-GCNs) for imbalanced AD staging using resting-state functional magnetic resonance imaging (rs-fMRI). The proposed method is developed on a multi-view graph constructed using the functional connectivity (FC) and high-order functional connectivity (HOFC) features of the subjects. A novel cost-sensitive weighted contrastive learning procedure is proposed to capture discriminative information from the minority classes, encouraging the samples in the minority class to provide adequate supervision. Considering the heterogeneity of the disease, the weights of the negative pairs are introduced into contrastive learning and they are computed based on the distance to class prototypes, which are automatically learned from the training data. Meanwhile, the cost-sensitive mechanism is further introduced into contrastive learning to handle the class imbalance issue. The proposed CSWCL-GCN is evaluated on 720 subjects (including 184 NCs, 40 SMC patients, 208 EMCI patients, 172 LMCI patients and 116 AD patients) from the ADNI (Alzheimer's Disease Neuroimaging Initiative). Experimental results show that the proposed CSWCL-GCN outperforms state-of-the-art methods on the ADNI database.

Risk factors for methotrexate resistance in low-risk gestational trophoblastic neoplasia patients (FIGO score 0-4).

The challenge of methotrexate (MTX) resistance among low-risk gestational trophoblastic neoplasia (GTN) patients has always been prominent. Despite the International Federation of Gynaecology and Obstetrics (FIGO) score of 0-4 patients comprising the majority of low-risk GTN patients, a comprehensive exploration of the prevalence and risk factors associated with MTX resistance has been limited. Therefore, we aimed to identify associated risk factors in GTN patients with a FIGO score of 0-4. Between January 2005 and December 2020, 310 low-risk GTN patients received primary MTX chemotherapy in two hospitals, with 265 having a FIGO score of 0-4. In the FIGO 0-4 subgroup, 94 (35.5%) were resistant to MTX chemotherapy, and 34 (12.8%) needed multi-agent chemotherapy. Clinicopathologic diagnosis of postmolar choriocarcinoma (OR = 17.18, 95% CI: 4.64-63.70, P < 0.001) and higher pretreatment human chorionic gonadotropin concentration on a logarithmic scale (log-hCG concentration) (OR = 18.11, 95% CI: 3.72-88.15, P < 0.001) were identified as independent risk factors associated with MTX resistance according to multivariable logistic regression. The decision tree model and regression model were developed to predict the risk of MTX resistance in GTN patients with a FIGO score of 0-4. Evaluation of model discrimination, calibration and net benefit revealed the superiority of the decision tree model, which comprised clinicopathologic diagnosis and pretreatment hCG concentration. The patients in the high- and medium-risk groups of the decision tree model had a higher probability of MTX resistance. This study represents the investigation into MTX resistance in GTN patients with a FIGO score of 0-4 and disclosed a remission rate of approximately 65% with MTX chemotherapy. Higher pretreatment hCG concentration and clinicopathologic diagnosis of postmolar choriocarcinoma were independent risk factors associated with resistance to MTX chemotherapy. The decision tree model demonstrated enhanced predictive capabilities regarding the risk of MTX resistance and can serve as a valuable tool to guide the clinical treatment decisions for GTN patients with a FIGO score of 0-4.

Mechanically Robust Hemostatic Hydrogel Membranes with Programmable Strain-Adaptive Microdomain Entanglement for Wound Treatment in Dynamic Tissues.

Supramolecular hydrogels emerge as a promising paradigm for sutureless wound management. However, their translation is still challenged by the insufficient mechanical robustness in the context of complex wounds in dynamic tissues. Herein, we report a tissue-adhesive supramolecular hydrogel membrane based on biocompatible precursors for dressing wounds in highly dynamic tissues, featuring robust mechanical resilience through programmable strain-adaptive entanglement among microdomains. Specifically, the hydrogels are synthesized by incorporating a long-chain polyurethane segment into a Schiff base-ligated short-chain oxidized cellulose/quaternized chitosan network via acylhydrazone bonding, which readily establishes interpenetrating entangled microdomains in dynamic cross-linked hydrogel matrices to enhance their tear and fatigue resistance against extreme mechanical stresses. After being placed onto dynamic tissues, the hydrogel dressing could efficiently absorb blood to achieve rapid hemostasis. Moreover, metal ions released from ruptured erythrocytes could be scavenged by the Schiff base linkers to form additional ionic bonds, which would trigger the cross-linking of the short-chain components and establish abundant crystalline microdomains, eventually leading to the in situ stiffening of the hydrogels to endure heavy mechanical loads. Benefiting from its hemostatic capacity and strain adaptable mechanical performance, this hydrogel wound dressing shows promise for the clinical management of various traumatic wounds.

Expert consensus on Prospective Precision Diagnosis and Treatment Strategies for Osteoporotic Fractures.

Osteoporotic fractures are the most severe complications of osteoporosis, characterized by poor bone quality, difficult realignment and fixation, slow fracture healing, and a high risk of recurrence. Clinically managing these fractures is relatively challenging, and in the context of rapid aging, they pose significant social hazards. The rapid advancement of disciplines such as biophysics and biochemistry brings new opportunities for future medical diagnosis and treatment. However, there has been limited attention to precision diagnosis and treatment strategies for osteoporotic fractures both domestically and internationally. In response to this, the Chinese Medical Association Orthopaedic Branch Youth Osteoporosis Group, Chinese Geriatrics Society Geriatric Orthopaedics Committee, Chinese Medical Doctor Association Orthopaedic Physicians Branch Youth Committee Osteoporosis Group, and Shanghai Association of Integrated Traditional Chinese and Western Medicine Osteoporosis Professional Committee have collaborated to develop this consensus. It aims to elucidate emerging technologies that may play a pivotal role in both diagnosis and treatment, advocating for clinicians to embrace interdisciplinary approaches and incorporate these new technologies into their practice. Ultimately, the goal is to improve the prognosis and quality of life for elderly patients with osteoporotic fractures.