Objective To assess the prognostic value of serum lysine hydroxylase 3(PLOD3)and cytokeratin 19 fragment(CYFRA21-1)in predicting the efficacy of three-dimensional brachytherapy in patients with pulmonary metastases.Methods A total of 102 patients with lung metastases who underwent three-dimensional brachytherapy at our hospital were selected as the lung metastasis group from August 2021 to August 2023.During the same period,a control group consisting of 60 healthy individuals who underwent physical examinations was selected.The lung metastasis group was further divided into an effective group(n=66)and an ineffective group(n=36)based on therapeutic outcomes.Enzyme-linked immunosorbent assay was employed to measure the levels of serum PLOD3 and CYFRA21-1.Multiple logistic regression analysis was conducted to identify factors influencing the efficacy of three-dimensional brachytherapy in the lung metastasis group.Receiver operating characteristic(ROC)curves were used to assess the predictive value of serum PLOD3 and CYFRA21-1 for treatment efficacy.Results The levels of serum PLOD3 and CYFRA21-1 in the case group were(34.47±6.17)μg/L,(27.85±5.14)μg/L,respectively,which exhibited significantly higher values compared to those observed in the control group(7.26±2.21)μg/L,(9.31±2.46)μg/L(P<0.05).A positive correlation was found between serum PLOD3 and CYFRA21-1 in the Lung metastasis group(r=0.667,P=0.000).Logistic regression analysis revealed that multiple metastatic lesions along with elevated serum levels of PLOD3 and CYFRA21-1 were identified as risk factors for the efficacy of three-dimensional brachytherapy in patients with lung metastases(P<0.05).Furthermore,when combined with three-dimensional brachytherapy,the area under the curve(AUC)for serum PLOD3 and CYFRA21-1 was calcu-lated as 0.868,demonstrating a superior performance compared to individual measurements of either serum PLOD3 alone(AUC=0.815)or CYFRA21-1 alone(P<0.05).Conclusions The levels of serum PLOD3 and CYFRA21-1 are elevated in patients with lung metastases,exhibiting a significant correlation with the efficacy of three-dimensional brachytherapy.The combined utilization of these two biomarkers demonstrates a robust predictive value for treatment efficacy in patients suffering from lung metastases.

Low rectal cancer accounts for a high proportion of colorectal cancer cases in China, and the choice of treatment strategies critically impacts patient prognosis and quality of life. With the advancement of precision treatment, clinical decision-making requires integrating multi-dimensional factors to move beyond the traditional "one-size-fits-all" approach. The authors focus on the anatomical complexity, high recurrence risk, and functional preservation demands of low rectal cancer, incorporating the latest research advances to explore precision treatment pathways in terms of preoperative high-resolution magnetic resonance imaging assessment, breakthroughs in immunotherapy and precision surgical techniques. Future efforts should further optimize individua-lized strategies through multimodal assessment and multidisciplinary collaboration, refining inte-grated approaches based on evidence-based medicine to enhance clinical efficacy and patient survival outcomes.

Objective:To analyze the epidemiological and clinical characteristics of respiratory pathogens in China.Methods:This study was a cross-sectional study, which encompassed 19 core units of the clinical pathogen network and established a three-tiered clinical pathogen surveillance system. Thirty respiratory samples were collected every two weeks from various units from January to December 2024, and the clinical and pathogen diagnostic information were gathered. A total of 11 864 samples were tested using this system. The tier-1 clinical pathogen surveillance system covered influenza A virus (Flu-A), influenza B virus (Flu-B), respiratory syncytial virus (RSV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The tier-2 clinical pathogen surveillance system focused on 18 key respiratory pathogens. The tier-3 clinical pathogen surveillance system further clarified whether any emerging infectious diseases had occurred.Results:The tier-1 clinical pathogen surveillance system showed Flu-A predominated in December, Flu-B predominated in January, SARS-CoV-2 peaked in March and August, whereas RSV circulated sporadically throughout the year. Geographic trends were broadly consistent across the seven major regions, although Flu-A detection in December was notably higher in Northeast China (48.1%(111/231)) and East China (36.2%(148/409)), and RSV detection was concentrated in the Northwest and South China from January to March. Data from the tier-2 clinical pathogen surveillance system indicated that Streptococcus pneumoniae, Mycoplasma pneumoniae, rhinovirus, and adenovirus were detected year-round, of these, Streptococcus pneumoniae and rhinovirus showed elevated positive detection rates from August to September, while adenovirus peaked in January. Legionella pneumophila was not detected throughout the year, and other pathogens fluctuated throughout the year without a consistent pattern. The predominant etiologic agents of pediatric pneumonia were Mycoplasma pneumoniae (35.0%(105/300)), rhinovirus (25.7%(77/300)), and adenovirus (17.3%(52/300)), whereas adult pneumonia was mainly caused by Streptococcus pneumoniae (10.5%(29/277)), Staphylococcus aureus (6.9%(19/277)), Mycoplasma pneumoniae (6.9%(19/277)), and Flu-A (6.1%(17/277)). The tier-3 clinical pathogen surveillance system did not identify any emerging respiratory pathogens. Conclusion:Respiratory pathogens in China in 2024 exhibit distinct temporal and spatial distribution patterns and vary among different populations.

This article reported two cases of congenital myotonic dystrophy. Case 1 was a premature infant born at 35 weeks of gestation, with severe asphyxia as the initial manifestation. After admission, the infant had limited spontaneous activity, low muscle tone, weak spontaneous respiration, inability to swallow independently, and bilateral talipes equinovarus. The initial diagnosis was neonatal hypoxic-ischemic encephalopathy. However, clinical observation suggested the possibility of other diseases and genetic testing indicated that the number of CTG trinucleotide repeats in the DMPK gene was>150 times, suggesting a high possibility that the child's mother was also affected, but remained undiagnosed due to lack of testing. Case 2 was a full-term infant born at 37 weeks and 1 day of gestation, who presented with asphyxia and dyspnea initially. It also presented with limited spontaneous activity, low muscle tone, weak respiration, and bilateral talipes equinovarus, which was highly similar to the clinical situation of Case 1. The genes of the child and his mother were tested, and the results showed that the number of CTG trinucleotide repeats in the DMPK gene was >150 times for both. Both children died within a few hours after being discharged from the hospital due to the family's decision to abandon treatment.

Tracheal intubation is the most commonly used way to establish artificial airway in intensive care unit patients, and it is the premise of respiratory support and treatment, the success of extubation is an important basis to measure the prognosis of patients. Influenced by many factors, extubation of patients may fail, resulting in prolonged hospitalization, increased medical expenses and increased incidence of complications. This article reviews the literature at home and abroad, and summarizes the main mechanism, risk factors and prevention strategies of extubation failure in intensive care unit patients, aiming at improving the recognition ability of clinical medical staff for extubation failure and providing reference for clinical management and follow-up research.

Objective To investigate the effects of miR-483-3p on hypoxia/reoxygenation(H/R)-induced apoptosis and pyroptosis of H9c2 cardiomyocytes and its possible mechanism.Methods Rat H9c2 cardiomyocytes were cultured in vitro,adeno-associated virus-infected H9c2 and the H/R model were constructed by triple-air incuba-tor,and the cells were randomly divided into blank control(Sham)group,model(H/R)group,AAV-miR-483-3p mimic+H/R(AAV-miR-483-3p)group,AAV-miR-483-3p negative control+H/R(AAV-NC)group.The growth status of cells in each group was observed using an inverted microscope;cell proliferation activity was detected by cell counting kit-8(CCK-8);LDH release by lactate dehydrogenase(LDH)kit;apoptosis rate by flow cytometry;apoptosis by notched end labeling(TUNEL).Western blot(WB)was used to detect the expression levels of IL-1β and GSDMD proteins in each group.Results Compared with the Sham group,the H/R group showed abnormal cell status and increased cell death,decreased cell activity,increased LDH release,increased apoptosis rate and apopto-sis level,and increased expression levels of IL-1β and GSDMD proteins(P<0.05);compared with the H/R group,the AAV-miR-483-3p group showed improved cell status and less cell death,increased cell proliferation activity,increased LDH release,and increased IL-1β and GSDMD protein expression levels(P<0.05).Compared with the H/R group,the AAV-miR-483-3p group showed improved cell status and less cell death,increased cell proliferation activity,decreased LDH release,decreased apoptosis rate and apoptosis level,and decreased expression of IL-1β and GSDMD proteins(P<0.05).Conclusion Over-expression of miR-483-3p can improve H/R-inducedH9c2 cardiomyocyte injury by enhancing cell activity and cell metabolism,and inhibiting apoptosis and cell charring.

Objective:To evaluate the levels and source of cadmium exposure by dietary pathway among middle-aged and elderly people ≥40 in cadmium-contaminated areas of China.Methods:A total of 7 193 people aged 40-89 years from four typical cadmium-contaminated areas in China were selected as the study subjects. Food Frequency Questionnaire (FFQ), Total Diet Study (TDS) and a 3-day-24-hour dietary recall survey were conducted. Dietary cadmium intake and food sources through dietary pathways were assessed based on cadmium content in foods, consumption amounts and intake frequencies.Results:The mean age of the participants was 63.39±12.21 years, with 50.05% being males. The average monthly dietary cadmium intake was 7.39 μg/(kg·BW). Staple foods and vegetables were the primary sources of dietary cadmium intake, accounting for 57.51% and 32.48%, respectively. The monthly dietary cadmium intake in all surveyed regions did not exceed the Provisional Tolerable Monthly Intake (PTMI) recommended by the Joint FAO/WHO Expert Committee on Food Additives (JECFA).Conclusion:The monthly dietary cadmium intake among middle-aged and elderly people in cadmium-contaminated areas of China is relatively low, with the risk remaining at an acceptable level. Staple foods and vegetables are the most significant contributors to dietary cadmium intake.

Objective:To investigate the iodine nutrition status of children and pregnant women in different water iodine areas of Shandong Province.Methods:From February to September 2023, Leling City (iodine deficient), Gaotang County (moderate iodine), and Liangshan County (high iodine) in different water iodine areas of Shandong Province were selected as survey sites. One village was selected from each county (city) in five directions: east, west, south, north, and center. Forty children aged 8 to 10 years (balanced in age, half male and half female) and 20 pregnant women were selected as survey subjects in each village. Random urine samples of children and pregnant women were collected to test for urinary iodine. Meanwhile, thyroid examinations were conducted on children to calculate the goiter rate.Results:A total of 600 urine samples of children were tested, with a median urinary iodine level of 246.0 μg/L. The median urinary iodine levels of children in iodine deficient, moderate iodine and high iodine areas were 219.6, 208.0 and 446.0 μg/L, respectively ( n = 200, 200, 200). The median urinary iodine level of children in high iodine area was significantly higher than that in iodine deficient and moderate iodine areas ( P < 0.05). A total of 600 children underwent thyroid examinations, with a goiter rate of 5.8% (35/600). The goiter rate of children in iodine deficient, moderate iodine, and high iodine areas were 4.0% (8/200), 1.0% (2/200), and 12.5% (25/200), respectively. The goiter rate of children in high iodine area was significantly higher than that in iodine deficient and moderate iodine areas ( P < 0.05). A total of 247 urine samples of pregnant women were tested, with a median urinary iodine level of 158.2 μg/L. The median urinary iodine levels of pregnant women in iodine deficient, moderate iodine, and high iodine areas were 75.3, 175.2 and 321.2 μg/L, respectively ( n = 98, 84, 65). The median urinary iodine level of pregnant women in high iodine area was significantly higher than that in iodine deficient and moderate iodine areas, and the median urinary iodine level of pregnant women in moderate iodine area was significantly higher than that in iodine deficient area ( P < 0.05). Conclusion:The urinary iodine levels of children and pregnant women and the goiter rate of children in high iodine area of Shandong Province are significantly increased, and water iodine may be a key factor affecting the iodine nutrition status of the population.

Low rectal cancer accounts for a high proportion of colorectal cancer cases in China, and the choice of treatment strategies critically impacts patient prognosis and quality of life. With the advancement of precision treatment, clinical decision-making requires integrating multi-dimensional factors to move beyond the traditional "one-size-fits-all" approach. The authors focus on the anatomical complexity, high recurrence risk, and functional preservation demands of low rectal cancer, incorporating the latest research advances to explore precision treatment pathways in terms of preoperative high-resolution magnetic resonance imaging assessment, breakthroughs in immunotherapy and precision surgical techniques. Future efforts should further optimize individua-lized strategies through multimodal assessment and multidisciplinary collaboration, refining inte-grated approaches based on evidence-based medicine to enhance clinical efficacy and patient survival outcomes.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.