CMTM6: A Critical Prognostic Indicator in Non-Small Cell Lung Cancer.

While CKLF-like MARVEL transmembrane domain containing 6 (CMTM6)'s role in stabilizing PD-L1 and immune evasion within tumors is established, its expression in lung cancer tissue and adjacent macrophages remains uncertain. The study aimed to elucidate this ambiguity by investigating CMTM6's role in non-small cell lung cancer (NSCLC) prognosis. Employing immunohistochemical staining on 141 NSCLC and 110 adjacent normal lung tissue samples, CMTM6 expression was evaluated using the HSCORE system. Interestingly, NSCLC exhibited significantly higher CMTM6 levels (161.04±86.60) compared to normal tissues (71.20±45.10) (p < 0.001), detected not only in cancer cells but also in macrophages, lymphocytes, and nearby bronchial epithelial cells. Stratifying patients by CMTM6 levels unveiled a correlation between heightened expression and poorer overall survival (p = 0.003), alongside a link to tumor-infiltrating lymphocytes (TIL) (p = 0.037), especially in cases with increased TIL. Multivariate analysis identified CMTM6 as an independent predictor of overall survival (p = 0.009), implying that elevated CMTM6 expression in NSCLC might signify an adverse prognostic marker for patient outcomes.

Enhancing the fairness of AI prediction models by Quasi-Pareto improvement among heterogeneous thyroid nodule population.

Artificial Intelligence (AI) models for medical diagnosis often face challenges of generalizability and fairness. We highlighted the algorithmic unfairness in a large thyroid ultrasound dataset with significant diagnostic performance disparities across subgroups linked causally to sample size imbalances. To address this, we introduced the Quasi-Pareto Improvement (QPI) approach and a deep learning implementation (QP-Net) combining multi-task learning and domain adaptation to improve model performance among disadvantaged subgroups without compromising overall population performance. On the thyroid ultrasound dataset, our method significantly mitigated the area under curve (AUC) disparity for three less-prevalent subgroups by 0.213, 0.112, and 0.173 while maintaining the AUC for dominant subgroups; we also further confirmed the generalizability of our approach on two public datasets: the ISIC2019 skin disease dataset and the CheXpert chest radiograph dataset. Here we show the QPI approach to be widely applicable in promoting AI for equitable healthcare outcomes.

Tumor immunity: A brief overview of tumor­infiltrating immune cells and research advances into tumor­infiltrating lymphocytes in gynecological malignancies (Review).

Tumor immunity is a promising topic in the area of cancer therapy. The 'soil' function of the tumor microenvironment (TME) for tumor growth has attracted wide attention from scientists. Tumor-infiltrating immune cells in the TME, especially the tumor-infiltrating lymphocytes (TILs), serve a key role in cancer. Firstly, relevant literature was searched in the PubMed and Web of Science databases with the following key words: 'Tumor microenvironment'; 'TME'; 'tumor-infiltrating immunity cells'; 'gynecologic malignancies'; 'the adoptive cell therapy (ACT) of TILs'; and 'TIL-ACT' (https://pubmed.ncbi.nlm.nih.gov/). According to the title and abstract of the articles, relevant items were screened out in the preliminary screening. The most relevant selected items were of two types: All kinds of tumor-infiltrating immune cells; and advanced research on TILs in gynecological malignancies. The results showed that the subsets of TILs were various and complex, while each subpopulation influenced each other and their effects on tumor prognosis were diverse. Moreover, the related research and clinical trials on TILs were mostly concentrated in melanoma and breast cancer, but relatively few focused on gynecological tumors. In conclusion, the present review summarized the biological classification of TILs and the mechanisms of their involvement in the regulation of the immune microenvironment, and subsequently analyzed the development of tumor immunotherapy for TILs. Collectively, the present review provides ideas for the current treatment dilemma of gynecological tumor immune checkpoints, such as adverse reactions, safety, personal specificity and efficacy.

Effect and Safety of Herbal Medicine Foot Baths in Patients with Diabetic Peripheral Neuropathy: A Multicenter Double-Blind Randomized Controlled Trial.

OBJECTIVE: To evaluate the effect and safety of foot baths with Tangbi Waixi Decoction (TW) in treating patients with diabetic peripheral neuropathy (DPN). METHODS: It is a multicenter double-blinded randomized controlled trial. Participants with DPN were recruited between November 18, 2016 and May 30, 2018 from 8 hospitals in China. All patients received basic treatments for glycemic management. Patients received foot baths with TW herbal granules either 66.9 g (intervention group) or 6.69 g (control group) for 30 min once a day for 2 weeks and followed by a 2-week rest, as a therapeutic course. If the Toronto Clinical Scoring System total score (TCSS-TS) ⩾6 points, the patients received a total of 3 therapeutic courses (for 12 weeks) and were followed up for 12 weeks. The primary outcome was change in TCSS-TS score at 12 and 24 weeks. Secondary outcomes included changes in bilateral motor nerve conduction velocity (MNCV) and sensory nerve conduction velocity (SNCV) of the median and common peroneal nerve. Safety was also assessed. RESULTS: Totally 632 patients were enrolled, and 317 and 315 were randomized to the intervention and control groups, respectively. After the 12-week intervention, patients in both groups showed significant declines in TCSSTS scores, and significant increases in MNCV and SNCV of the median and common peroneal nerves compared with pre-treatment (P<0.05). The reduction of TCSS-TS score at 12 weeks and the increase of SNCV of median nerve at 24 weeks in the control group were greater than those in the intervention group (P<0.05). The number of adverse events did not differ significantly between groups (P>0.05), and no serious adverse event was related with treatment. CONCLUSION: Treatment of TW foot baths was safe and significantly benefitted patients with DPN. A low dose of TW appeared to be more effective than a high dose. (Registry No. ChiCTR-IOR-16009331).

Convolutional neural networks combined with classification algorithms for the diagnosis of periodontitis.

OBJECTIVES: We aim to develop a deep learning model based on a convolutional neural network (CNN) combined with a classification algorithm (CA) to assist dentists in quickly and accurately diagnosing the stage of periodontitis. MATERIALS AND METHODS: Periapical radiographs (PERs) and clinical data were collected. The CNNs including Alexnet, VGG16, and ResNet18 were trained on PER to establish the PER-CNN models for no periodontal bone loss (PBL) and PBL. The CAs including random forest (RF), support vector machine (SVM), naive Bayes (NB), logistic regression (LR), and k-nearest neighbor (KNN) were added to the PER-CNN model for control, stage I, stage II and stage III/IV periodontitis. Heat map was produced using a gradient-weighted class activation mapping method to visualize the regions of interest of the PER-Alexnet model. Clustering analysis was performed based on the ten PER-CNN scores and the clinical characteristics. RESULTS: The accuracy of the PER-Alexnet and PER-VGG16 models with the higher performance was 0.872 and 0.853, respectively. The accuracy of the PER-Alexnet + RF model with the highest performance for control, stage I, stage II and stage III/IV was 0.968, 0.960, 0.835 and 0.842, respectively. Heat map showed that the regions of interest predicted by the model were periodontitis bone lesions. We found that age and smoking were significantly related to periodontitis based on the PER-Alexnet scores. CONCLUSION: The PER-Alexnet + RF model has reached high performance for whole-case periodontal diagnosis. The CNN models combined with CA can assist dentists in quickly and accurately diagnosing the stage of periodontitis.

Liver indicators affecting the relationship between BMI and hypertension in type 2 diabetes: a mediation analysis.

BACKGROUND: Body mass index (BMI) is an important risk factor for hypertension in diabetic patients. However, the underlying mechanisms remain poorly understood. Although liver-derived biological intermediates may play irreplaceable roles in the pathophysiology of diabetes, few studies have explored them in the association between BMI and hypertension in diabetes. OBJECTIVE: To investigate the role of liver enzymes in mediating the relationship between BIM exposure and hypertension in type 2 diabetes mellitus (T2DM). METHODS: We included a total of 1765 participants from the China National Diabetic Chronic Complications Study Cohort. Associations between liver enzymes and hypertension were estimated using multivariable regression models. The function of liver indicators in the relationship between BMI and hypertension was assessed using mediation analysis. Mediation analysis was conducted, taking into account age, diabetes duration, current smoking, fasting plasma glucose level, glycated hemoglobin, anti-diabetic therapy, and family history of diseases, including diabetes, hypertension, obesity, and hyperlipidemia. RESULTS: For men, the association of BMI with hypertension was partially mediated by alanine aminotransferase (ALT), with a proportion of mediation was 68.67%, by aspartate aminotransferase (AST) was 27.02%, and by γ-glutamyltransferase (GGT) was 38.58%, by AST/ALT was 63.35%; for women, the proportion mediated by ALT was 36.93%, and by AST was 37.47%, and GGT was 44.60%, and AST/ALT was 43.73% for BMI (all P < 0.05). CONCLUSION: The effect of BMI on hypertension is partly mediated by liver indicators (ALT, AST, GGT, and AST/ALT) in diabetic patients. Our results may provide opportunities to identify new targets for hypertension interventions.

Associations between dietary patterns and renal impairment in individuals with diabetes: a cross-sectional study.

BACKGROUND: A variety of chronic diseases are affected by diet. To our knowledge, few studies have investigated the relationship between dietary patterns and renal impairment in individuals with diabetes within an Asian population. This study aimed to assess the relationship between renal impairment and dietary patterns in individuals with diabetes within a Chinese population. METHODS: In this cross-sectional survey, we analysed data on 1522 participants with diabetes aged 18 years or older who took part in the China National Diabetic Chronic Complications Study. We utilised the Chinese Diabetes Complications Questionnaire, including the semiquantitative food frequency questionnaire (SQFFQ). We identified three dietary patterns using factor analysis: Chinese traditional, healthy and plant-based dietary patterns, and these dietary patterns were used to classify participants into four groups based on the quartiles of their scores. A decrease in the estimated glomerular filtration rate (eGFR; <60 mL/min/1.73 m2 ) and an increase in the albumin-to-creatinine ratio (ACR; ≥3 mg/mmol) were used as indicators of renal impairment. Binary logistic regression models were used to estimate the odds ratio (OR) of the highest quartile (Q4: high intake levels of each dietary pattern) for renal impairment compared to the lowest quartile (Q1: low intake levels of each dietary pattern). RESULTS: Among the 1522 participants, there was a 5.5% prevalence of low eGFR, with prevalence rates of 5.2% in men and 5.9% in women, yet the prevalence of albuminuria was as high as 47.9%. After adjusting for confounders, participants in Q4 of the plant-based dietary pattern had a smaller OR for renal impairment than those in Q1. CONCLUSIONS: Our findings demonstrated that a plant-based dietary pattern is associated with a reduced risk of renal impairment in a population with diabetes.

Study on the effect of excavation sequence of three-hole shield tunnel on surface settlement and segment deformation.

In order to study the influence of excavation sequence of three-hole parallel shield tunnel on surface settlement and segment convergence, an improved "three-stage analysis method" was proposed to calculate the surface settlement of three-hole parallel shield tunnel. Based on Peck's existing theory, this method deduced the ground settlement formula under the three-hole parallel condition, and can calculate the ground settlement more accurately. Based on the engineering background of a shield tunnel section in Jiangsu Province, a three-dimensional model of a three-hole parallel shield tunnel was established by using Flac3d software, and the three-hole parallel shield tunnel was simulated under four working conditions: right-center-left, right-left-center, right-left-right and right-center (reverse)-left. This paper analyzed the influence of tunnel excavation sequence on surface settlement, soil displacement and deformation of tunnel segments. The construction sequence was optimized based on the above influencing factors. It was found that Case 4, S-type sequential excavation, produced the least ground settlement. The surface settlement value caused by S-type excavation sequence was only 11.41 mm, and the convergence value of the segments generated by S-type excavation sequence was relatively small. Considering the economic factors such as construction efficiency and benefit, the S-shaped excavation sequence was better. The new calculation method of tunnel surface settlement and the optimal sequence of tunnel construction proposed in this paper can provide reference for actual construction.

Low-dose nalmefene pretreatment reduces etomidate-induced myoclonus: A randomized, double-blind controlled trial.

BACKGROUND: This study compared the effectiveness of nalmefene and fentanyl in reducing the incidence and severity of etomidate-induced myoclonus. METHODS: One hundred fifty patients were randomized to receive 0.25ug/kg of nalmefene, 1ug/kg of fentanyl, or the same volume of normal saline 3 minutes prior to etomidate-induced anesthesia. The primary observational indexes were the severity level and incidence of etomidate-induced myoclonus, and the secondary observational index included blood pressure, heart rate, and the incidence of adverse effects from anesthesia induction to resuscitation, such as cough, chest wall rigidity, dizziness, nausea, pain after awakening, and intraoperative awareness. RESULTS: The incidence of myoclonus was significantly lower in the nalmefene group (8.0%) than in the fentanyl group (32.0%) (P = .003) and in the normal saline group (72.0%) (P = .000). The severity level of myoclonus in the nalmefene group was significantly lower than the fentanyl group (P = .001) and normal saline group (P = .000). Meanwhile, the incidences of cough and chest wall rigidity during anesthesia induction were significantly lower in the nalmefene group compared with the fentanyl group (P = .003, P = .027). There were no statistically significant differences in heart rate and mean arterial pressure among the 3 gruops (P > .05). There was no difference in the incidence of adverse effects among the 3 groups during recovery from anesthesia (P > .05). CONCLUSION: Intravenous injection of 0.25ug/kg of nalmefene 3 minutes prior to etomidate is more effective in preventing etomidate-induced myoclonus during general anesthesia than 1ug/kg of fentanyl.

Association of sleep behaviors, insulin resistance surrogates, and the risk of hypertension in Chinese adults with type 2 diabetes mellitus.

Objective: Our aim was to evaluate the association between midday napping, combined sleep quality, and insulin resistance surrogates and the risk of hypertension in patients with type 2 diabetes mellitus (T2DM). Methods: Data were collected using a standardized questionnaire. Binary logistic regression was performed to estimate the odds ratio (OR) and 95% confidence interval (CI) for the risk of hypertension. Systolic and diastolic blood pressure were grouped as categorical variables and unpaired two-sided Student's t-test and Spearman correlation analysis were performed to estimate the association between different blood pressure levels and insulin resistance surrogates. Results: The overall prevalence rate of hypertension was 50%. Age (OR = 1.056, 95% CI:1.044-1.068), poor sleep quality (OR = 1.959, 95% CI:1.393-2.755), hyperlipidemia (OR = 1.821, 95% CI:1.462-2.369), family history of hypertension (OR = 2.811, 95% CI:2.261-3.495), and obesity (OR = 5.515, 95% CI:1.384-21.971) were significantly associated with an increased risk of hypertension. Midday napping for 1-30 min was negatively correlated with the risk of hypertension (OR = 0.534, 95% CI:0.305-0.936, P <0.05). Conclusion: Poor sleep quality and obesity are independent risk factors for hypertension. Midday napping (1-30 min) is associated with a decreased risk of hypertension in patients with T2DM.

An injectable MB/BG@LG sustained release lipid gel with antibacterial and osteogenic properties for efficient treatment of chronic periodontitis in rats.

Periodontitis is a chronic inflammatory disease characterized by the colonization of pathogenic microorganisms and the loss of periodontal supporting tissue. However, the existing local drug delivery system for periodontitis has some problems including subpar antibacterial impact, easy loss, and unsatisfactory periodontal regeneration. In this study, a multi-functional and sustained release drug delivery system (MB/BG@LG) was developed by encapsulating methylene blue (MB) and bioactive glass (BG) into the lipid gel (LG) precursor by Macrosol technology. The properties of MB/BG@LG were characterized using a scanning electron microscope, a dynamic shear rotation rheometer, and a release curve. The results showed that MB/BG@LG could not only sustained release for 16 days, but also quickly fill the irregular bone defect caused by periodontitis through in situ hydration. Under 660 â€‹nm light irradiation, methylene blue-produced reactive oxygen species (ROS) can reduce local inflammatory response by inhibiting bacterial growth. In addition, in vitro and vivo experiments have shown that MB/BG@LG can effectively promote periodontal tissue regeneration by reducing inflammatory response, promoting cell proliferation and osteogenic differentiation. In summary, MB/BG@LG exhibited excellent adhesion properties, self-assembly properties, and superior drug release control capabilities, which improved the clinical feasibility of its application in complex oral environments.

A novel combined intelligent algorithm prediction model for the tunnel surface settlement.

To ensure the safety and stability of the shield tunnel construction process, the ground settlement induced by the shield construction needs to be effectively predicted. In this paper, a prediction method combining empirical mode decomposition (EMD), chaotic adaptive sparrow search algorithm (CASSA), and extreme learning machine (ELM) is proposed. First, the EMD is used to decompose the settlement sequence into trend vectors and fluctuation vectors to fully extract the effective information of the sequence; Second, the sparrow search algorithm is improved by introducing Cubic chaotic mapping to initialize the population and adaptive factor to optimize the searcher's position formula, and the chaotic adaptive sparrow search algorithm is proposed; Finally, the CASSA-ELM prediction model is constructed by using CASSA to find the optimal values of weights and thresholds in the extreme learning machine. The fluctuation components and trend components decomposed by EMD are predicted one by one, and the prediction results are superimposed and reconstructed to obtain the predicted final settlement. Taking a shield interval in Jiangsu, China as an example, the meta-heuristic algorithm-optimized ELM model improves the prediction accuracy by 10.70% compared with the traditional ELM model. The combined EMD-CASSA-ELM prediction model can greatly improve the accuracy and speed of surface settlement prediction, and provide a new means for safety monitoring in shield tunnel construction. Intelligent prediction methods can predict surface subsidence more automatically and quickly, becoming a new development trend.

Improved Environmental Stimulus and Biological Competition Tactics Interactive Artificial Ecological Optimization Algorithm for Clustering.

An interactive artificial ecological optimization algorithm (SIAEO) based on environmental stimulus and a competition mechanism was devised to find the solution to a complex calculation, which can often become bogged down in local optimum because of the sequential execution of consumption and decomposition stages in the artificial ecological optimization algorithm. Firstly, the environmental stimulus defined by population diversity makes the population interactively execute the consumption operator and decomposition operator to abate the inhomogeneity of the algorithm. Secondly, the three different types of predation modes in the consumption stage were regarded as three different tasks, and the task execution mode was determined by the maximum cumulative success rate of each individual task execution. Furthermore, the biological competition operator is recommended to modify the regeneration strategy so that the SIAEO algorithm can provide consideration to the exploitation in the exploration stage, break the equal probability execution mode of the AEO, and promote the competition among operators. Finally, the stochastic mean suppression alternation exploitation problem is introduced in the later exploitation process of the algorithm, which can tremendously heighten the SIAEO algorithm to run away the local optimum. A comparison between SIAEO and other improved algorithms is performed on the CEC2017 and CEC2019 test set.

The impact of early pregnancy metabolic disorders on pregnancy outcome and the specific mechanism.

Miscarriage is the most common complication of pregnancy. The most common causes of early miscarriage are chromosomal abnormalities of the embryo, maternal endocrine abnormalities, organ malformations, and abnormal immune factors. Late miscarriages are mostly caused by factors such as cervical insufficiency. However, the causes of 50% of miscarriages remain unknown. Recently, increasing attention has been given to the role of metabolic abnormalities in miscarriage. In this review, we mainly discuss the roles of four major metabolic pathways (glucose, lipid, and amino acid metabolism, and oxidation‒reduction balance) in miscarriage and the metabolism-related genes that lead to metabolic disorders in miscarriage. Depending on aetiology, the current treatments for miscarriage include hormonal and immunological drugs, as well as surgery, while there are few therapies for metabolism. Therefore, we also summarize the drugs for metabolism-related targets. The study of altered metabolism underlying miscarriage not only helps us to understand the mechanisms involved in miscarriage but also provides an important basis for clinical research on new therapies.

Human understandable thyroid ultrasound imaging AI report system - A bridge between AI and clinicians.

Artificial intelligence (AI) enables accurate diagnosis of thyroid cancer; however, the lack of explanation limits its application. In this study, we collected 10,021 ultrasound images from 8,079 patients across four independent institutions to develop and validate a human understandable AI report system named TiNet for thyroid cancer prediction. TiNet can extract thyroid nodule features such as texture, margin, echogenicity, shape, and location using a deep learning method conforming to the clinical diagnosis standard. Moreover, it offers excellent prediction performance (AUC 0.88) and provides quantitative explanations for the predictions. We conducted a reverse cognitive test in which clinicians matched the correct ultrasound images according to TiNet and clinical reports. The results indicated that TiNet reports (87.1% accuracy) were significantly easier to understand than clinical reports (81.6% accuracy; p < 0.001). TiNet can serve as a bridge between AI-based diagnosis and clinicians, enhancing human-AI cooperative medical decision-making.

Age at diagnosis, diabetes duration and the risk of cardiovascular disease in patients with diabetes mellitus: a cross-sectional study.

Background: The purpose of the study was to evaluate characteristics and risk of cardiovascular disease (CVD) according to age at diagnosis and disease duration among adults with diabetes mellitus (DM). Methods: The association between age at diagnosis, diabetes duration and CVD were examined in 1,765 patients with DM. High risk of estimated ten-year atherosclerotic cardiovascular disease (ASCVD) was performed by the Prediction for ASCVD Risk in China (China-PAR) project. Data were compared with analysis of variance and χ2 test, respectively. Multiple logistic regression was used to determine the risk factors of CVD. Results: The mean age at diagnosis (± standard deviation) was 52.91 ± 10.25 years and diabetes duration was 8.06 ± 5.66 years. Subjects were divided into early-onset DM group (≤43 years), late-onset DM group (44 to 59 years), elderly-onset DM group (≥60 years) according to age at diagnosis. Diabetes duration was classified by 5 years. Both early-onset and longest diabetes duration (>15 years) had prominent hyperglycaemia. Diabetes duration was associated with the risk of ischemic stroke (odds ratio (OR), 1.091) and coronary artery disease (OR, 1.080). Early-onset group (OR, 2.323), and late-onset group (OR, 5.199), and hypertension (OR, 2.729) were associated with the risk of ischemic stroke. Late-onset group (OR, 5.001), disease duration (OR, 1.080), and hypertension (OR, 2.015) and hyperlipidemia (OR, 1.527) might increase the risk of coronary artery disease. Aged over 65 (OR, 10.192), central obesity (OR, 1.992), hypertension (OR, 18.816), cardiovascular drugs (OR, 5.184), antihypertensive drugs (OR, 2.780), and participants with disease duration >15 years (OR, 1.976) were associated with the high risk of estimated ten-year ASCVD in participants with DM. Conclusion: Age at diagnosis, diabetes duration, hypertension and hyperlipidemia were independent risks of CVD. Longest (>15 years) diabetes duration increased the high risk of ten-year ASCVD prediction among Chinese patients with DM. It's urgent to emphasize the importance of age at diagnosis and diabetes duration to improve primary complication of diabetes.

Hydrophilic surface-modified 3D printed flexible scaffolds with high ceramic particle concentrations for immunopolarization-regulation and bone regeneration.

Bioceramic scaffolds used in bone tissue engineering suffer from a low concentration of ceramic particles (<50 wt%), because the high concentration of ceramic particles increases the brittleness of the composite. 3D printed flexible PCL/HA scaffolds with high ceramic particle concentrations (84 wt%) were successfully fabricated in this study. However, the hydrophobicity of PCL weakens the composite scaffold hydrophilicity, which may limit the osteogenic ability to some extent. Thus, as a less time-consuming, less labour intensive, and more cost-effective treatment method, alkali treatment (AT) was employed to modify the surface hydrophilicity of the PCL/HA scaffold, and its regulation of immune responses and bone regeneration were investigated in vivo and in vitro. Initially, several concentrations of NaOH (0.5, 1, 1.5, 2, 2.5, and 5 mol L-1) were employed in tests to determine the appropriate concentration for AT. Based on the comprehensive consideration of the results of mechanical experiments and hydrophilicity, 2 mol L-1 and 2.5 mol L-1 of NaOH were selected for further investigation in this study. The PCL/HA-AT-2 scaffold dramatically reduced foreign body reactions as compared to the PCL/HA and PCL/HA-AT-2.5 scaffolds, promoted macrophage polarization towards the M2 phenotype and enhanced new bone formation. The Wnt/ß-catenin pathway might participate in the signal transduction underlying hydrophilic surface-modified 3D printed scaffold-regulated osteogenesis, according to the results of immunohistochemical staining. In conclusion, hydrophilic surface-modified 3D printed flexible scaffolds with high ceramic particle concentrations can regulate the immune reactions and macrophage polarization to promote bone regeneration, and the PCL/HA-AT-2 scaffold is a potential candidate for bone tissue repair.