Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

The Guidelines for Occupational Hazard Assessment and Control of Active Pharmaceutical Ingredient in the Pharmaceutical Industry (T/WSJD 60—2024) is the first guiding standard in the field of health in China that focuses on occupational health protection for active pharmaceutical ingredient (API). It covers the general principles, work procedures, assessment methods, and control strategies for API occupational hazard assessment, providing practical guidance and recommendations for pharmaceutical enterprises to eliminate or reduce occupational health risks associated with API, improve working environment, and enhance refined management practices. This article interpreted and analyzed the background of standard establishment, formulation process, fundamental basis, and main content, to provide scientific and comprehensive technical support for occupational health managers in the pharmaceutical industry to better apply this standard.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Objective To comparatively analyze the clinical characteristics of primary bilateral macronodular adrenal hyperplasia(PBMAH)and adrenal cortisol-producing Adenoma(CPA),and enhance the understanding of two diseases.Methods The clinical data of 85 PBMAH patients(PBMAH group)and 195 CPA patients(CPA group)diagnosed at Department of Endocrinology,the First Medical Center of Chinese PLA General Hospital,from September 2014 to August 2024 were retrospectively analyzed.The demographic characteristics,comorbidities,biochemical indicators,adrenocorticotropic hormone-cortisol(ACTH-F)levels,and adrenal imaging features and treatment conditions were compared between the two groups.Results(1)General characteristics:Compared with CPA group,PBMAH group had older age at diagnosis and a higher proportion of male patients.(2)Clinical characteristics:Compared with CPA group,PBMAH group had a longer disease duration,a higher proportion of subclinical Cushing's syndrome(CS),and a higher proportion of hypertension,impaired glucose tolerance/diabetes,bone mass reduction or osteoporosis,with higher serum potassium levels,and the differences were statistically significant(P<0.01).(3)Hormone levels:Both PBMAH and CPA groups showed ACTH-F rhythm disorder,significantly increased cortisol levels and suppressed ACTH.Compared with PBMAH group,CPA group had stronger autonomous cortisol secretion ability,manifested by increased midnight serum cortisol(F0:00),16:00 serum cortisol(F16:00),24-hour urinary free cortisol(24 h UFC)levels and lower 8:00 serum ACTH(ACTH8:00)and 16:00 serum ACTH(ACTH16:00)(P<0.01).After low-dose dexamethasone suppression test(LDDST),CPA group showed lower suppression rates of ACTH and cortisol,and higher proportions of paradoxical elevation in serum cortisol and 24 h UFC compared with PBMAH(P<0.01).Conclusions PBMAH has a longer disease course and higher proportions of comorbid metabolic disorders than CPA,mostly manifested as subclinical Cushing's syndrome.CPA has stronger autonomous cortisol secretion ability,with cortisol less likely to be suppressed after LDDST and more obvious paradoxical elevation of cortisol and 24 h UFC.

Objective To characterize multimodal metabolic disorders in subclinical Cushing's syndrome(SCS)patients with different cortisol levels,providing a reference for clinical diagnosis and treatment.Methods A retrospective analysis was conducted on the clinical data of 165 SCS patients diagnosed at the First Medical Center of Chinese PLA General Hospital due to adrenal masses from January 2014 to October 2024.Using the serum cortisol levels after the midnight 1 mg dexamethasone suppression test(1 mg DST)as the cut-off point,SCS patients were divided into high-level group(1 mg DST-F>138 nmol/L,n=96)and low-level group(50 nmol/L<1 mg DST-F≤138 nmol/L,n=69).The differences in age,gender,body mass index(BMI),blood pressure,glucolipid metabolism indices,electrolytes,hormone levels,and imaging features of adrenal adenoma(such as CT values)were compared between the two groups.Multivariate linear regression was used to analyze the correlation between CT values and metabolic indices.Results Compared with low-level group,patients in high-level group were younger(54.0±11.3 vs.57.7±10.3,P=0.034),while there were no statistically significant differences in gender ratio or BMI between the two groups(P>0.05).Both groups exhibited decreased adrenocorticotropic hormone(ACTH)levels and disrupted circadian rhythm.Compared with low-level group,high-level group showed significantly higher F0:00 levels[250.00(170.07,422.53)nmol/L vs.110.00(82.74,133.90)nmol/L]and 24-hour urinary free cortisol(24 h UFC)[568.40(377.80,875.45)nmol/24 h vs.369.40(265.40,494.69)nmol/24 h](P<0.001),with no significant differences in serum F8:00,or 1 mg DST ACTH0:00 levels(P>0.05).Except for the fasting C-peptide level in the high-level group being higher than that in low-level group[(2.88±1.01)ng/ml vs.(2.46±0.78)ng/ml,P=0.024],there were no significant differences in blood pressure,blood lipids,glycated hemoglobin(HbA1c),fasting blood glucose,fasting insulin,serum electrolytes,uric acid,and other indices between the two groups(P>0.05).The CT value of adrenal adenoma during contrast-enhanced scanning was higher in high-level group[80.00(17.80,93.00)Hu vs.52.00(35.50,75.00)Hu,P=0.006]compared with low-level group.Multivariate linear regression analysis revealed that diastolic blood pressure was positively correlated with CT values of adrenal adenomas in both plain scanning(β=0.49,95%CI 0.09-0.90)and contrast-enhanced scanning(β=2.08,95%CI 0.76-3.39),while triglyceride levels were negatively correlated with plain scanning CT values(β=-5.77,95%CI-10.88--0.66).Conclusion Patients with SCS at different cortisol levels differ in age,fasting C-peptide levels,and CT values.CT values may serve as potential imaging markers to assess metabolic risk in SCS patients.

Objective To investigate the clinical characteristics of patients with clinical and subclinical Cushing's syndrome caused by primary bilateral macronodular adrenal hyperplasia(PBMAH).Methods A retrospective analysis was performed on the clinical data of 198 patients with Cushing's syndrome caused by PBMAH diagnosed in the First Medical Center of Chinese PLA General Hospital from January 2004 to October 2024.According to clinical manifestations,the patients were classified into clinical type Cushing's syndrome(n=61)and subclinical type Cushing's syndrome(n=137),and the clinical characteristics of the two types were compared.Results The mean age at diagnosis of patients with PBMAH-induced Cushing's syndrome was(53.5±10.4)years,including 118 males and 80 females,with a male-to-female ratio of 1.475:1.Compared with the subclinical type,the clinical type had a higher proportion of females,higher levels of serum cortisol,24-hour urine free cortisol(24 h UFC),and inhibited serum cortisol after low-dose dexamethasone suppression.Additionally,the clinical type had lower plasma ACTH,larger adrenal nodules and a higher risk of surgery(P<0.05)compared with those in subclinical type.The incidences of hypertension,dyslipidemia,obesity,diabetes mellitus,hypokalemia,vitamin D deficiency,osteoporosis,coronary heart disease,and cerebrovascular disease in patients with Cushing's syndrome caused by PBMAH were 87.9%,50.5%,37.1%,36.9%,27.8%,25.9%,18.7%,18.7%and 12.1%,respectively.Among them,compared with subclinical type patients,clinical type patients had higher incidence of hypokalaemia,vitamin D deficiency and osteoporosis(P<0.05),while there were no statistically significant differences in the incidences of other comorbidities between the two types(P>0.05).The results of postoperative follow-up for PBMAH patients showed that the short-term biochemical remission rate of unilateral total adrenalectomy was 41.5%(22/53)and the long-term biochemical remission rate was 32.0%(8/25).The short-term biochemical remission rate of unilateral partial(or nodular)adrenalectomy was 52.9%(9/17),and the long-term biochemical remission rate was 14.3%(1/7).All patients who underwent unilateral total adrenalectomy plus contralateral partial resection developed adrenal insufficiency(3/3),and 1 patient(1/3)relapsed 3.4 years after surgery.Conclusion Clinical and subclinical types of Cushing's syndrome caused by PBMAH have their distinct clinical characteristics.Surgery is an effective treatment for PBMAH,but a certain proportion of patients fail to achieve biochemical remission after non-bilateral total adrenalectomy.

Objective To establish a stable,reliable,and clinically relevant porcine model of endotoxin-induced acute respiratory distress syndrome(ARDS).Methods Ten 8-month-old male Bama minipigs were deeply sedated,followed by invasive mechanical ventilation and electrocardiographic monitoring.Lipopolysaccharide(LPS)was intravenously pumped at 600 μg/(kg·h)for 3 hours,then maintained at 15 μg/(kg·h)thereafter.Dynamic monitoring was performed at five time points after LPS injection(LPS 0,1,3,5,and 8 h),including arterial blood gas analysis and chest computed tomography(CT)scans.Pathological examination of lung tissues obtained via bronchoscopic biopsy(HE staining and transmission electron microscopy)was conducted.These indicators were comprehensively used to evaluate the success of the animal model.Results At 5 hours after LPS administration,8 minipigs developed symptoms such as skin cyanosis,elevated body temperature,and respiratory distress.The oxygenation index decreased to<300 mmHg.Chest CT scans showed diffuse pulmonary infiltrates.Histopathology revealed alveolar edema and hyaline membrane formation.Transmission electron microscopy demonstrated disruption of pulmonary blood-air barrier,depletion of lamellar bodies in type Ⅱ pneumocytes,inflammatory cell infiltration,and exudation of plasma proteins and fibrin.Compared with LPS 0 h,at LPS 8 h,the oxygenation index and arterial blood pH were significantly decreased(P<0.001),while blood lactic acid and serum potassium were significantly increased(P<0.05);serum calcium and base excess were significantly decreased(P<0.05),and the lung injury score based on HE-stained lung sections was significantly increased(P<0.01).Conclusion The porcine ARDS model established by continuous LPS injection can dynamically simulate the pathophysiological characteristics and typical pathological manifestations of clinical septic ARDS,making it an effective tool to study the pathogenesis,prevention,and treatment strategies of septic ARDS.

Objective:To apply the Timed Up and Go Test(TUGT)to investigate the correlation between motor function, emotional state, cognitive function, and sleep quality among elderly individuals in the Chinese community.Methods:A cross-sectional study was conducted, involving 739 subjects aged 60 to 90 years, who were randomly recruited from December 2021 to August 2023 across Beijing, Tianjin, Zhejiang, Guangdong, and Hainan Provinces in China.Basic demographic information was collected, and the TUGT was utilized to assess motor function.Based on the TUGT time(t), the subjects were divided into three groups: normal motor function group, mild motor abnormality group, and significant motor abnormality group.Cognitive function was evaluated using the Chinese Revised Mini-Mental State Examination(MMSE), while the Patient Health Questionnaire Depression Scale(PHQ-9)was employed to measure the degree of depression.Additionally, the Epworth Sleepiness Scale(ESS)was used to assess excessive daytime sleepiness.The correlation between subjects' motor function and their cognitive abilities, mood, and sleep was subsequently analyzed.Results:Systolic blood pressure, heart rate, PHQ-9, MMSE, and ESS scores were identified as significant factors influencing TUGT time.Specifically, TUGT time was positively correlated with PHQ-9 and ESS scores, while exhibiting negative correlations with systolic blood pressure, heart rate, and MMSE scores.Additionally, TUGT time was negatively correlated with the MMSE subcomponents of orientation, immediate memory, and verbal ability.All observed differences were statistically significant(all P<0.05).Logistic regression analysis indicated that an increase in the PHQ-9 score was associated with an odds ratio( OR)of 1.099(95% CI: 1.045-1.155, P<0.001)(mild motor abnormality group)and 1.150(95% CI: 1.066-1.242, P<0.001)(Significant motor abnormality group).Additionally, a reduction in the MMSE score was observed, with an OR of 0.939(95% CI: 0.886-0.995, P<0.001)(mild motor abnormality group)and 0.793(95% CI: 0.729-0.862, P<0.001)(Significant motor abnormality group).Furthermore, an increase in the ESS score was noted, with ORs of 1.139(95% CI: 1.094-1.186, P<0.001)(mild motor abnormality group)and 1.203(95% CI: 1.132-1.279, P<0.001)(Significant motor abnormality group).These findings suggest that these variables are independently related to decreased motor function. Conclusions:Depression, cognitive impairment, and excessive daytime sleepiness are independent risk factors for motor dysfunction among elderly individuals in community settings.The Timed Up and Go Test TUGT can be utilized for the early screening of motor function decline in this population.