Objective To establish and internally validate a predictive model for poorly differentiated adenocarcinoma based on CT imaging and tumor marker results. Methods Patients with solid and partially solid lung nodules who underwent lung nodule surgery at the Department of Thoracic Surgery, the Affiliated Brain Hospital of Nanjing Medical University in 2023 were selected and randomly divided into a training set and a validation set at a ratio of 7:3. Patients' CT features, including average density value, maximum diameter, pleural indentation sign, and bronchial inflation sign, as well as patient tumor marker results, were collected. Based on postoperative pathological results, patients were divided into a poorly differentiated adenocarcinoma group and a non-poorly differentiated adenocarcinoma group. Univariate analysis and logistic regression analysis were performed on the training set to establish the predictive model. The receiver operating characteristic (ROC) curve was used to evaluate the model's discriminability, the calibration curve to assess the model's consistency, and the decision curve to evaluate the clinical value of the model, which was then validated in the validation set. Results A total of 299 patients were included, with 103 males and 196 females, with a median age of 57.00 (51.00, 67.25) years. There were 211 patients in the training set and 88 patients in the validation set. Multivariate analysis showed that carcinoembryonic antigen (CEA) value [OR=1.476, 95%CI (1.184, 1.983), P=0.002], cytokeratin 19 fragment antigen (CYFRA21-1) value [OR=1.388, 95%CI (1.084, 1.993), P=0.035], maximum tumor diameter [OR=6.233, 95%CI (1.069, 15.415), P=0.017], and average density [OR=1.083, 95%CI (1.020, 1.194), P=0.040] were independent risk factors for solid and partially solid lung nodules as poorly differentiated adenocarcinoma. Based on this, a predictive model was constructed with an area under the ROC curve of 0.896 [95%CI (0.810, 0.982)], a maximum Youden index corresponding cut-off value of 0.103, sensitivity of 0.750, and specificity of 0.936. Using the Bootstrap method for 1000 samplings, the calibration curve predicted probability was consistent with actual risk. Decision curve analysis indicated positive benefits across all prediction probabilities, demonstrating good clinical value. Conclusion For patients with solid and partially solid lung nodules, preoperative use of CT to measure tumor average density value and maximum diameter, combined with tumor markers CEA and CYFRA21-1 values, can effectively predict whether it is poorly differentiated adenocarcinoma, allowing for early intervention.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Exercise fatigue is a complex physiological and psychological phenomenon that includes peripheral fatigue in the muscles and central fatigue in the brain. Peripheral fatigue refers to the loss of force caused at the distal end of the neuromuscular junction, whereas central fatigue involves decreased motor output from the primary motor cortex, which is associated with modulations at anatomical sites proximal to nerves that innervate skeletal muscle. The central regulatory failure reflects a progressive decline in the central nervous system’s capacity to recruit motor units during sustained physical activity. Emerging evidence highlights the critical involvement of central neurochemical regulation in fatigue development, particularly through neurotransmitter-mediated modulation. Alterations in neurotransmitter release and receptor activity could influence excitatory and inhibitory signal pathways, thus modulating the perception of fatigue and exercise performance. Increased serotonin (5-HT) could increase perception of effort and lethargy, reduce motor drive to continue exercising, and contribute to exercise fatigue. Decreased dopamine (DA) and noradrenaline (NE) neurotransmission can negatively impact arousal, mood, motivation, and reward mechanisms and impair exercise performance. Furthermore, the serotonergic and dopaminergic systems interact with each other; a low 5-HT/DA ratio enhances motor motivation and improves performance, and a high 5-HT/DA ratio heightens fatigue perception and leads to decreased performance. The expression and activity of neurotransmitter receptors would be changed during prolonged exercise to fatigue, affecting the transmission of nerve signals. Prolonged high-intensity exercise causes excess 5-HT to overflow from the synaptic cleft to the axonal initial segment and activates the 5-HT1A receptor, thereby inhibiting the action potential of motor neurons and affecting the recruitment of motor units. During exercise to fatigue, the DA secretion is decreased, which blocks the binding of DA to D1 receptor in the caudate putamen and inhibits the activation of the direct pathway of the basal ganglia to suppress movement, meanwhile the binding of DA to D2 receptor is restrained in the caudate putamen, which activates the indirect pathway of the basal ganglia to influence motivation. Furthermore, other neurotransmitters and their receptors, such as adenosine (ADO), glutamic acid (Glu), and γ‑aminobutyric acid (GABA) also play important roles in regulating neurotransmitter balance and fatigue. The occurrence of central fatigue is not the result of the action of a single neurotransmitter system, but a comprehensive manifestation of the interaction between multiple neurotransmitters. This review explores the important role of neurotransmitters and their receptors in central motor fatigue, reveals the dynamic changes of different neurotransmitters such as 5-HT, DA, NE, and ADO during exercise, and summarizes the mechanisms by which these neurotransmitters and their receptors regulate fatigue perception and exercise performance through complex interactions. Besides, this study presents pharmacological evidence that drugs such as agonists, antagonists, and reuptake inhibitors could affect exercise performance by regulating the metabolic changes of neurotransmitters. Recently, emerging interventions such as dietary bioactive components intake and transcranial electrical stimulation may provide new ideas and strategies for the prevention and alleviation of exercise fatigue by regulating neurotransmitter levels and receptor activity. Overall, this work offers new theoretical insights into the understanding of exercise central fatigue, and future research should further investigate the relationship between neurotransmitters and their receptors and exercise fatigue.

ObjectiveTo evaluate the clinical efficacy and safety of Huaban Jiedu Formulation （化斑解毒方， HJF） in treating psoriasis vulgaris with blood-heat syndrome. MethodsA randomized， double-blind， placebo-controlled study was conducted with 60 patients diagnosed with psoriasis vulgaris of blood-heat syndrome. Patients were randomly assigned to either a treatment group or a control group， with 30 cases in each. The treatment group received HJF granules orally， one dose a day， combined with topical Qingshi Zhiyang Ointment （青石止痒软膏）， while the control group received placebo granules， one dose a day， combined with the same topical ointment. Both groups were topically treated twice daily of 28 days treatment cours. Psoriasis area and severity index （PASI）， visual analogue scale for pruritus （VAS）， traditional Chinese medicine （TCM） syndrome scores， dermatology life quality index （DLQI）， and psoriasis life stress inventory （PLSI） were assessed before treatment and on day 14 and day 28. Response rates for PASI 50 （≥50% reduction） and PASI 75 （≥75% reduction）， as well as overall clinical efficacy， were compared between groups. Serum levels of interleukin-6 （IL-6） and interleukin-17 （IL-17） were measured before and after 28 days of treatment. Adverse reactions during treatment were recorded. ResultsAfter 28 days of treatment， both groups showed significant reductions in PASI total score， lesion area score， erythema， scaling， and infiltration scores， pruritus VAS score， TCM syndrome score， DLQI， PLSI， and serum IL-6 and IL-17 levels （P＜0.05）. Compared to the control group， the treatment group had significantly greater improvements in PASI total score and erythema score， TCM syndrome score， serum IL-6 and IL-17 levels， and PASI 50 response rate after 28 days （P＜0.05）. Between-group comparisons of score differences before and after 28-day treatment revealed that the treatment group showed significantly better improvements in PASI total， lesion area score， erythema score， TCM syndrome score， DLQI， PLSI， and inflammatory markers （P＜0.05 or P＜0.01）. The total effective rate on day 14 and day 28 was 40.00% （12/30） and 83.33% （25/30） in the treatment group， versus 6.90% （2/29） and 41.38% （12/29） in the control group， respectively. The clinical efficacy in the treatment group was significantly superior to that in the control group （P＜0.05）. Mild gastric discomfort occurred in 3 patients in the treatment group and 1 in the control group. ConclusionHJF can effectively improve skin lesions and TCM symptoms relieve pruritus， enhance quality of life， and reduce inflammatory markers IL-6 and IL-17， in patients with blood-heat syndrome of psoriasis vulgaris， with a good safety profile.

Aural vertigo frequently encountered in the otolaryngology department of traditional Chinese medicine （TCM） mainly involves peripheral vestibular diseases of Western medicine， such as Meniere's disease， benign paroxysmal positional vertigo， vestibular neuritis， and vestibular migraine， being a hot research topic in both TCM and Western medicine. Western medical therapies alone have unsatisfactory effects on recurrent aural vertigo， aural vertigo affecting the quality of life， aural vertigo not relieved after surgery， aural vertigo with complex causes， and children's aural vertigo. The literature records and clinical practice have proven that TCM demonstrates unique advantages in the treatment of aural vertigo. The China Association of Chinese medicine sponsored the "17th youth salon on the diseases responding specifically to TCM： Aural vertigo" and invited vertigo experts of TCM and Western medicine to discuss the difficulties and advantages of TCM diagnosis and treatment of aural vertigo. The experts deeply discussed the achievements and contributions of TCM and Western medicine in the diagnosis and treatment of aural vertigo， the control and mitigation of the symptoms， and the solutions to disease recurrence. The discussion clarified the positioning and advantages of TCM treatment and provided guidance for clinical and basic research on aural vertigo.

Six compounds were isolated from the roots of Ephedra sinica Stapf using various chromatographic techniques such as silica gel column chromatography, thin layer chromatography and semi-preparative HPLC. Their chemical structures were identified by analysis of physicochemical properties and spectral data, and determined as (Z)-docosanylferulate (1), (E)-docosanylferulate (2), bis (2-ethylheptyl) phythalate (3), 2,2′-oxybis (1,4-di-tert-butylbenzene) (4), diisobutyl phthalate (5), bis (2-ethylhexyl) phthalate (6). Among them, compound 1 is a new compound, compounds 2-4 were first isolated from Ephedra. A corticosterone-induced PC-12 cell injury model was used for compound activity screening. The results showed that compounds 1 and 5 significantly improved corticosterone-induced PC-12 cell injury and significantly increased 5-HT₇ receptor protein expression in the cells, indicating potential antidepressant activity.

Objective To investigate the relationship between insomnia,gastrointestinal symptoms,and glycosylated hemoglobin(HbA1c)levels in individuals diagnosed with type 2 diabetes mellitus(T2DM),as well as the related influencing factors.Methods A total of 910 T2DM patients treated in our multicenter from January 2022 to December 2022 were enrolled in this study.General information(gender,age,smoking and drinking history,exercise,course of disease,treatment and complications),HbA1c,Athens Insomnia Scale(AIS)scores and Gastrointestinal Symptoms Rating Scale(GSRS)scores of patients were collected.The differences of sleep and gastrointestinal symptoms between groups were analyzed,and the correlation between the differences and HbA1c was analyzed.Furthermore,the risk factors for non-standard HbA1c were analyzed.Results The AIS score and GSRS score in the HbA1c control group were less than those in the non-standard group(P＜0.01).Insomnia was reported by 37.0％of T2DM patients,and the HbA1c level in the insomnia group was significantly higher than that in the non-insomnia group(10.00％±2.38％vs.8.26％±1.73％,P＜0.01).Gastrointestinal symptoms were present in 57.5％of T2DM patients,and the HbA1c levels in the group with gastrointestinal symptoms were significantly higher than those in the group without gastrointestinal symptoms(9.26％±2.23％vs.8.43％±1.98％,P＜0.01).Furthermore,26.3％of T2DM patients experienced both insomnia and gastrointestinal symptoms.Remarkably,the HbA1c levels in the group with both insomnia and gastrointestinal symptoms were significantly higher than those in the group without either condition(10.18％±2.44％vs.8.45％±1.86％,P＜0.01).Correlation analysis demonstrated a significant association between sleep quality,gastrointestinal function,and HbA1c levels(P＜0.01).The logistic regression analysis result revealed that age,GSRS score,AIS score,and the presence of insomnia combined with gastrointestinal symptoms were independent risk factors for predicting HbA1c≥6.5％(P＜0.01).Having both insomnia and gastrointestinal symptoms concurrently was the strongest risk factor for substandard HbA1c control,and the risk of blood sugar control may increase about 5 times when both appear together.Conclusion Insomnia and gastrointestinal symptoms are common comorbidities in T2DM patients,showing a cross-interfering relationship,and they appear together with poor blood sugar control,interact causally,and amplify each other.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.

Objective To investigate the effects of liver-specific knockout of adenosine 5'-monophosphate-activated protein kinase α(AMPKα)on pancreatic function and glucose metabolism-related genes in mice.Methods AMPKα1/α2flox/flox mice were divided into blank group(common feed)and model group(60％high fat choline deficiency feet)with eight mice in each group,and another 8 AMPKα1/α2flox/flox/Alb-Cre+mice were divided into the knockout group(60％high fat choline deficiency feet).The kit detected the levels of blood lipids and liver function indexes.The differential genes in the mouse pancreas were detected by transcriptome sequencing.The expression of differential genes in mice was detected by real-time fluorescence quantitative polymerase chain reaction and Western blotting.Results The levels of triglyceride in the blank group,model group and knockout group were(0.94±0.11),(0.71±0.14)and(1.05±0.17)mmol·L-1;the levels of triglyceride and high-density lipoprotein were(1.62±0.07),(0.44±0.08)and(0.90±0.06)mmol·L-1;the levels of glutamic oxaloacetic transaminase were(7.02±5.87),(15.60±3.15)and(22.70±2.14)U·L-1;the levels of glutamic pyruvic transaminase were(14.56±11.55),(48.64±15.84)and(75.40±11.96)U·L-1;the expression levels of phosphoenolpyruvate carboxykinase 1(PCK1)mRNA were 1.00±0,1.37±0.25 and 0.31±0.18;the relative expression levels of PCK1 protein were 0.77±0.27,1.23±0.43 and 0.51±0.40,respectively.Significant differences existed in the above indexes between the knockout group and the model group(all P＜0.05).Conclusion PCK1 gene may be an essential gene mediating the effect of liver AMPKα on islet function.

Objective To investigate the relationship and potential pathways between metal(loid)exposure and the risk of polycystic ovary syndrome(PCOS)in women of childbearing age. Methods This case-control study included 200 patients with PCOS(cases)and 896 non-PCOS controls with the age of 25-37 years.The concentrations of 29 metal(loid)s in the follicular fluid(FF)and clinical indicators in the serum were measured in all participants.Logistic regression analysis and mediation analysis were conducted to evaluate the associations between metal(loid)exposure and PCOS risk and investigate the possible roles of clinical indicators,respectively. Results Logistic regression analysis revealed an association between high copper levels in FF and increased PCOS risk(highest vs.lowest quartile:adjusted odds ratio=2.94,95%confidence interval:1.83-4.72).A high luteinizing hormone/follicle-stimulating hormone ratio and elevated levels of testosterone and anti-Müllerian hormone(AMH)were strongly associated with increased PCOS risk induced by high copper exposure.The mediation analysis indicated a mediating effect of AMH in the association between copper exposure and PCOS risk. Conclusion Copper may affect PCOS risk through the hypothalamic-pituitary-ovarian axis,mediated by AMH.Copper exposure and internal AMH levels are important indicators for early warning of PCOS development.