Background It is a research hotspot to study the changes of metabolites and metabolic pathways in the process of coal worker's pneumoconiosis (CWP) by metabonomics and to explore its pathogenesis. Objective To study the change of metabolites in bronchoalveolar lavage fluid (BALF) of patients with CWP and explore the metabolic regulation mechanism of the disease. Methods Patients with CWP who met the national diagnostic criteria according to Diagnosis of occupational pneumoconiosis (GBZ 70-2015) and underwent massive whole lung lavage were selected as the case group, and patients with tracheostenosis who underwent bronchoscopy were selected as the control group. BALF samples were collected from the cases and the controls. After filtering out large particles and mucus, the supernatant was stored in a −80 ℃ refrigerator. The samples were detected and analyzed by liquid chromatography-mass spectrometry after adding extraction solution, cold bath ultrasonication, and high-speed centrifugation, and the metabolic profiles and related data of CWP patients were obtained. The differential metabolites related to the occurrence and development of CWP were screened by multiple statistical analysis; furthermore, we searched the Kyoto Encyclopedia of Genes and Genomes (KEGG) database for potential metabolic pathways involved in the progression. Results There was no significant difference in the general conditions of the subjects, such as weight, height, age, and length of service among the stage I group, the stage II group, the stage III group, and the control group (P˃0.05). When comparing the CWP stage I group with the control group, 48 differential metabolites were screened out, among which 14 were up-regulated and 34 were down-regulated. A total of 66 differential metabolites were screened out between the patients with CWP stage II and the controls, 14 up-regulated and 52 down-regulated differential metabolites. Compared with the control group, 63 differential metabolites were screened out in the patients with CWP stage III, including 11 up-regulated and 52 down-regulated differential metabolites. There were 36 differential metabolites that may be related to the occurrence of CWP, among which 11 differential metabolites were up-regulated, and 25 were down-regulated. Four significant differential metabolic pathways were identified through KEGG database query: linoleic acid metabolic pathway, alanine metabolic pathway, sphingolipid metabolic pathway, and glycerophospholipid metabolic pathway. Conclusion The metabolomic study of BALF show that there are 36 different metabolites in the occurrence and development of CWP, mainly associating with linoleic acid metabolism, alanine metabolism, sphingolipid metabolism, and glycerophospholipid metabolism pathways.

Background Pneumoconiosis is a widespread occupational disease in China at present. As a type of lung diseases, its pathological damage is mainly irreversible fibrotic changes in the lungs. Several studies have shown that the occurrence and development of lung diseases such as coal workers' pneumoconiosis are closely related to intestinal flora. Objective To observe intestinal flora of coal workers' pneumoconiosis patients based on the results of 16SrDNA high-throughput sequencing and evaluate the changes of intestinal flora after treatment with tetrandrine tablets. Methods A total of 80 patients with coal workers' pneumoconiosis attending the outpatient clinic of the Department of Occupational Diseases of the Emergency General Hospital from April to July 2022 were enrolled. All patients were treated with tetrandrine tablets for 4 weeks, with group A before the treatment of tetrandrine tablets and group B after the treatment. In the same period, 24 healthy controls (group C) were set up. Stool samples were collected before and after the treatment. Using 16SrDNA high-throughput sequencing, gene V3-V4 sequencing technology, and bioinformatic analysis platform, we evaluated the intestinal flora after treatment by groups. Results The dominant flora at the phylum level and genus level were the same across three groups. The relative abundances of phylum Bacteroidetes, Bifidobacterium, Bacteroides, and Facealibacterium in groups B and C were higher than those in group A, and the relative abundances of phy-lum Actinobacteria, genus Blautia, and genus Romboutsia in groups B and C were lower than those in group A (P＜0.05). The relative abundances of genus Clostridium, genus Megamonas, and genus Lactobacillus in group C was lower than that in groups A and B (P＜0.05). The alpha diversity analysis showed that the Chao1 index was higher in group A than in group C (P＜0.01). Compared with group A, the Shannon index was higher in group B, and the increases of Simpson index were all statistically significant in stage I patients (P＜0.05), but the differences in Chao1 index were not statistically significant (P＞0.05). The differences in the values of Chao1 index, Shannon index, and Simpson index in stage Ⅱ and stage III patients were not statistically significant (P＞0.05). The beta diversity analysis showed that the difference in flora structure between group A and group C was statistically significant (P＜0.05); the differences in flora structure before and after treatment in the same stage patients were statistically significant (P＜0.05). The partial least squares discriminant analysis (PLS-DA) showed that there were significant differences between group A and group C, and between group A and group B. The LEfSe analysis showed that the significant markers contributing to the differences were basically the same in stage I, stage Ⅱ, and stage Ⅲ after treatment, which were mainly phylum Bacteroidetes and its subordinate groups, class Negativicutes, or-der Selenomonas, and genus Facealibacterium. Conclusion There are differences in the distribution of flora between coal workers' pneumoconiosis patients and healthy individuals, and the structure and relative abundance of intestinal flora are changed and the number of beneficial flora is increased after treatment with tetrandrine tablets.

Background Multi-slice spiral computerized tomography (MSCT) can be used as an auxiliary diagnosis of chest radiography in diagnosis of pneumoconiosis, but there are few studies on the correlations between interstitial images and stage classification of coal workers' pneumoconiosis in the existing literature. Objective To present MSCT imaging manifestations and distribution characteristics of coal workers' pneumoconiosis and complications, evaluate correlations between coal workers' pneumoconiosis stages and pulmonary interstitial lesions, and provide a reliable imaging diagnosis basis for pneumoconiosis interstitial lesions. Methods From June 2022 to June 2023, a total of 1002 patients with coal workers' pneumoconiosis confirmed by the pneumoconiosis diagnostic and identification group in the Department of Occupational Diseases of the Emergency General Hospital were enrolled. MSCT was used to observe the abnormal imaging manifestations of the lungs of coal workers' pneumoconiosis patients and the diseases of pulmonary fibrosis related to their own diseases (thickening of the interlobular septum, bronchial perivascular interstitial mass thickening, parenchymal banding, subpleural line, intralobular interstitial thickening, honeycomb, and subpleural interstitial thickening), the occurrence of coal workers' pneumoconiosis and complications (old tuberculosis, active tuberculosis, pneumonia, atelectasis, lung cancer, bronchiectasis), and the density, size, and location of pneumoconiosis nodules. Imaging data were analyzed and statistically processed. Results All 1002 patients were male, with an average age of (60.71±6.87) years and an average dust exposure time of (23.01±7.80) years. Among them, there were 470 patients with stage I, 422 patients with stage II, and 110 patients with stage III. There were significant differences in the distribution of thickening of the interlobular septum, bronchial perivascular interstitial mass thickening, parenchymal banding, intralobular interstitial thickening, subpleural interstitial thickening, and honeycomb across different stages (P<0.05). Statistically significant differences in p, q, and r subsets of round nodules were found in patients with pneumoconiosis at different stages (P<0.05). Observed nodule types included solid nodules, pure ground-glass shadow nodules, and partial solid nodules. There were statistically significant differences in pulmonary tuberculosis and bronchiectasis among different stages of coal workers' pneumoconiosis (P<0.05). There were statistically significant differences in interstitial shadows and patches combined with interstitial shadows among different stages of pneumoconiosis complicated with pneumonia (P<0.05). Conclusion MSCT provides images of the progression of coal workers' pneumoconiosis and have a certain relationship with the stages of coal workers' pneumoconiosis, which is conducive to the formulation of reasonable treatment plans in the early clinical stage. Therefore, in the diagnosis and treatment of pneumoconiosis, a great attention should be paid to the imaging technology of chest computerized tomography, especially the use of MSCT examination.

Background At present, the practice of pulmonary rehabilitation for pneumoconiosis in China is in a primary stage. The basis for formulating an individualized comprehensive pulmonary rehabilitation plan is still insufficient, which is one of the factors limiting the development of community-level rehabilitation work. Objective To formulate an exercise prescription based on maximum heart rate measured by cardiopulmonary exercise test (CPET), conduct an individualized comprehensive pulmonary rehabilitation program with the exercise prescription for patients with stable pneumoconiosis, and evaluate its role in improving exercise endurance and quality of life, thus provide a basis for the application and promotion of pulmonary rehabilitation. Methods A total of 68 patients were recruited from the Occupational Disease Prevention Hospital of Jinneng Holding Coal Industry Group Co., Ltd. from April to August 2022 , and were divided into an intervention group and a control group by random number table method, with 34 cases in each group. All the pneumoconiosis patients participated in a baseline test. The control group was given routine drug treatment, while the intervention group received multidisciplinary comprehensive pulmonary rehabilitation treatment on the basis of routine drug treatment, including health education, breathing training, exercise training, nutrition guidance, psychological intervention, and sleep management, whose exercise intensity was determined according to the maximum heart rate provided by CPET. The rehabilitation training lasted for 24 weeks. Patients were evaluated at registration and the end of study respectively. CPET was used to measure peak oxygen uptake per kilogram (pVO₂/kg), anaerobic threshold (AT), carbon dioxide equivalent of ventilation (EqCO₂), maximum metabolic equivalent (METs), and maximum work (W_max). The modified British Medical Research Council Dyspnea Questionnaire (mMRC), Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), Pittsburgh Sleep Quality Index (PSQI), Chronic Obstructive Pulmonary Disease Assessment Test (CAT), and Short Form of Health Survey (SF-36) were used to evaluate the potential effect of the comprehensive pulmonary rehabilitation program. Results Among the included 68 patients, 63 patients were having complete data, then 31 cases were assigned in the control group and 32 cases in the interventional group. Before the intervention, there was no significant difference in pVO₂/kg, AT, EqCO₂, METs, or W_max between the two groups (P>0.05). At the end of the trail, the indicators like pVO₂/kg [(19.81±2.38) mL·(min·kg)⁻¹], AT [(14.48±2.33) mL·(min·kg)⁻¹], METs (5.64±0.69), and W_max [(85.25±14) W] of patients in the intervention group were all higher than those [(13.90±2.37) mL·(min·kg)⁻¹, (11.70±1.94) mL·(min kg)⁻¹, (3.97±0.70), and (61.77±14.72) W, respectively] in the control group (P<0.001); there was no significant difference in EqCO₂ between the two groups (P=0.083). Before the trial, there was no significant difference in mMRC, SAS, SDS, PSQI, or CAT scores between the two groups (P>0.05). At the end of the trail, the mMRC score (1.16±0.57), SAS score (27.93±2.12), SDS score (26.48±1.44), PSQI score (1.08±0.88), and CAT score (4.34±3.28) of patients in the intervention group were lower than those [(2.03±0.83), (35.87±6.91), (34.23±6.65), (5.37±3.03), and (13.87±7.53), respectively] in the control group (P<0.001). The SF-36 scores of bodily pain (94.13±10.72), general health (87.50±5.68), vitality (95.31±5.53), mental health (99.88±0.71), and health changes (74.22±4.42) in the intervention group were higher than those [(71.87±32.72), (65.81±15.55), (74.52±16.45), (86.97±16.56), and (29.84±13.50), respectively] in the control group (P<0.001), and no significant difference was found in social functioning and role emotional scores (P>0.05). Conclusion Comprehensive pulmonary rehabilitation can increase the oxygen intake and exercise endurance of pneumoconiosis patients, ameliorate dyspnea symptoms, elevate psychological state and sleep quality, and improve the quality of life.

The Republic of China period （1912—1949） was an important stage of transition from traditional herbalism to clinical Chinese materia medica. The clinical application of Chinese materia medica became the focus of academic attention. During the Republic of China period， the research objectives， methods， and content of clinical Chinese materia medica were clarified， and the basic framework of Chinese materia medica was established through efficacy classification and item description. Based on the historical background at that time， striving for survival in adversity were the internal factors driving the construction of clinical Chinese materia medica， and the rise of academic education and the popularity of traditional Chinese medicine journals provided favorable conditions for the development of clinical Chinese materia medica. The clinical Chinese materia medica during the Republic of China period gradually formed a theoretical structure and core content that was distinctly different from that of traditional herbal medicine， which was integrated with the scientific research of Chinese materia medica and promoted the continuous development of Chinese materia medica together with other subdisciplines， presenting distinctive characteristics of the times and important academic significance.

Objective To observe the value of dual-source CT(DECT)virtual monoenergetic imaging(VMI)for differentiating prostate cancer(PC)and benign prostatic hyperplasia(BPH).Methods Thirty-three patients with PC(PC group)and 44 patients with BPH(BPH group)were retrospectively enrolled,and 40-100 keV(with 10 keV interval)VMI were reconstructed based on arterial phase DECT images,respectively.Clinical data,focal CT value and contrast-to-noise ratio(CNR)of VMI with different energy levels and conventional linear fusion images of arterial phase were compared between groups.Binary logistic regression models were constructed based on clinical data being significantly different between groups,focal CT value of VMI with energy level with the highest CNR,also focal CT value of conventional linear fusion images of arterial phase,respectively.The area under the receiver operating characteristic curve(AUC)was calculated to evaluate the efficacy of each model for differentiating PC and BPH.Results Free prostate-specific antigen(f-PSA),total prostate-specific antigen(t-PSA),focal CT value of 40-100 keV VMI and conventional linear fusion images of arterial phase in PC group were all higher,while short diameter in PC group was smaller than those in BPH group(all P＜0.05).Logistic regression models were constructed based on f-PSA,t-PSA,short diameter,CT value at 40 keV VMI and CT value at conventional linear fusion images of arterial phase,respectively,with AUC for differentiating PC and BPH of 0.879,0.902,0.701,0.911 and 0.857,respectively.Conclusion DECT VMI could be used as a supplementary examination for prostate diseases,and 40 keV VMI had the best efficacy for differentiating PC and BPH.

Objective:To evaluate the image quality of prostate T 2WI reconstructed based on deep learning (deep learning T 2WI) and the diagnostic performance for prostate cancer (PCa) in the transition zone. Methods:Totally 79 patients who underwent prostate MRI for elevated prostate specific antigen from December 2020 to September 2022 were prospectively consecutively collected from Beijing Hospital. Scan sequences included axial standard T 2WI, deep learning T 2WI, and diffusion-weighted imaging. The scan time was recorded. The image quality was scored subjectively including image quality, diagnostic confidence, noise level, artifacts, clarity and lesion detectability. For objective evaluation of image quality, signal-to-noise ratio (SNR) and contrast signal-to-noise ratio (CNR) were calculated. Two-parameter MRI prostate imaging reporting and data system version 2.1 (PI-RADS v2.1) scoring was performed for transition zone lesions using deep learning T 2WI and standard T 2WI, respectively. The subjective and objective image quality evaluation metrics for deep learning T 2WI and standard T 2WI were compared using the Wilcoxon signed-rank test. For transition zone lesions, the diagnostic performance of PI-RADS scores with deep learning T 2WI and standard T 2WI for PCa was evaluated by the receiver operating characteristic curve based on the lesion (all lesions in the transition zone) and the patient (the most malignant lesions in the transition zone), respectively, using the pathologic results as the gold standard. The area under the curve (AUC) was compared using the DeLong test. Results:Deep learning T 2WI significantly reduced the examination time by 64.6.%, from 4 min 37 s to 1 min 38 s. The scores of subjective image quality of deep learning T 2WI and standard T 2WI all were 5 (4, 5). The differences in image quality and lesion detectability were statistically significant ( Z=-2.32, -2.36, P=0.020, 0.018), and the differences of all other image quality evaluation metrics were not statistically significant ( P>0.05). The SNR of deep learning T 2WI and standard T 2WI were 17.11 (14.09, 21.92) and 9.15 (7.16, 11.17), with a statistically significant difference ( Z=-7.72, P<0.001). The CNR of deep learning T 2WI and standard T 2WI were 20.78 (13.42, 31.42) and 11.05 (7.82, 16.25), with a statistically significant difference ( Z=-7.54, P<0.001). Based on the lesion (40 PCa and 48 benign lesions), the AUC of the two-parameter PI-RADS score with deep learning T 2WI and standard T 2WI for diagnosing PCa in the transition zone were 0.915 (95%CI 0.856-0.975) and 0.916 (95%CI 0.857-0.976), without statistically significant difference ( Z=0.03, P=0.973). Based on the patient (33 PCa and 46 benign patients), the AUC of the two-parameter PI-RADS score with deep learning T 2WI and standard T 2WI were 0.921 (95%CI 0.857-0.984) and 0.939 (95%CI 0.886-0.992), without statistically significant difference ( Z=0.59, P=0.558). Conclusions:Compared with standard T 2WI, deep learning T 2WI of the prostate reduces scanning time while maintaining image quality and has comparable diagnostic performance for PCa in the transition zone.

Objective:To explore and analyze the online Q&A texts for hyperglycemia in pregnancy (HIP) users in online health communities, and to provide references for health information services for HIP patients.Methods:A total of 108 590 Q&A texts were collected from "Diabetes Forum" and "Mom Forum". Social network analysis was used to construct the co-occurrence network of feature words in text content and carry out visual analysis and display. On the basis of identifying content themes, the relationship between themes and the nodes within themes were further analyzed, and the attributes of content themes were differentiated with Wilson's information behavior model.Results:In this study, a question and answer text feature word network for pregnant hyperglycemia users with 321 nodes was constructed, among which the largest sub-net included 177 nodes. A total of 12 content themes were identified to seek motivation around two major categories of information, including blood sugar control and coping with disease stress. Among them, the themes with physiological, cognitive, and emotional attributes were 4, 7 and 6, respectively. The number of feature words contained in drug treatment, diet and nutrition was the most prominent, and there were feature words with high degree of centrality in each theme.Conclusions:The content that hyperglycemia in pregnancy (HIP) users pay attention to has multiple attributes and dimensions. Clinical and community healthcare workers and other health information providers can continuously improve the information service content for HIP patients to meet their health information needs.

Objective: The study aimed to investigate the diurnal variation in cervical disc hydration and its relationship with cervical degeneration. Materials and Methods: C3–C7 discs of 86 prospectively enrolled participants (37 males, 49 females; mean age ± standard deviation, 23.5 ± 2.5 years) were assessed using T2 mapping in the morning and evening. All discs were stratified by Miyazaki grade or C2–C7 Cobb angle and T2 values (T2). The degree of diurnal T2 variation (T2-DDV), defined as (morning T2 – evening T2)/morning T2 x 100%, was measured for the entire disc, annulus fibrosus (AF), nucleus pulposus (NP), and endplate zones. Results: T2 of the entire disc decreased significantly after the daytime load (p < 0.001), with a T2-DDV of 13.3% for all discs and 16.0%, 12.2%, and 13.0% for healthy (grade I), mild degenerative (grade II), and advanced degenerative (grade III/IV) discs, respectively. T2 of regional NPs and AFs decreased significantly from morning to evening (p ≤ 0.049) except in the healthy anterior inner AF (p = 0.092). Compared with healthy discs, mild degenerative discs displayed lower T2 and T2-DDV in regional NPs (p < 0.001). Advanced degenerative discs showed higher T2-DDV in the anterior inner AF compared with healthy discs (p = 0.050). Significant diurnal T2 changes in the endplate zones were observed only in healthy discs (p = 0.013). Cervical discs in the low Cobb angle group showed higher T2-DDV in the anterior AFs and anterior NP and lower T2-DDV in the posterior AF than those in the high Cobb angle group (p ≤ 0.041). Conclusion This study characterized the diurnal variation in hydration of the cervical discs as assessed using T2 mapping and revealed early chemo-mechanical coupling dysfunction in degenerating discs. Cervical sagittal alignment on MRI can affect the diurnal stress patterns of the cervical discs. T2 mapping is sensitive to disc biomechanical dysfunction and offers translational potential from biomechanical research to clinical application.

Background Diagnosis of pneumoconiosis by radiologist reading chest X-ray images is affected by many factors and is prone to misdiagnosis/missed diagnosis. With the rapid development of artificial intelligence in the field of medical imaging, whether artificial intelligence can be used to read images of pneumoconiosis deserves consideration. Objective Three deep learning models for identifying presence of pneumoconiosis were constructed based on deep convolutional neural network. An optimal model was selected by comparing diagnostic efficiency of the three models. Methods Digital radiography (DR) chest images were collected between June 2017 and December 2020 from 7 hospitals and standard radiograph quality control protocol was also followed. The DR chest images with positive results were classified into the positive group, while those without pneumoconiosis were classified into the negative group. The collected chest radiographs were labeled by experts who had passed the assessment of reading radiographs,and the experts were constantly assessed for consistency in the labeling process based on an expectation-maximization algorithm. The labeled data were cleaned, archived, and preprocessed, and then were grouped into a training set and a verification set. Three deep convolutional neural network models TMNet, ResNet-50, and ResNeXt-50 were constructed and trained by ten-fold cross-validation method to obtain an optimal model. Five hundred cases of DR chest radiographs that were not included in the training set and the validation set were collected, and identified by five senior experts as the gold standard, named the test set. The accuracy rate, sensitivity, specificity, area under curve (AUC), and other indexes of the three models were derived after testing, and the efficiency of the three models was evaluated and compared. Results A total of 24867 DR chest radiographs of the training set and the validation set were collected in this study, including 6978 images in the positive group and 17889 images in the negative group. There were 312 cases of pulmonary abnormalities such as pneumothorax and pulmonary tuberculosis. A total of nine experts labeled the chest radiographs, the labeling consistency rate of pneumoconiosis (non-staging) was above 88%, and the labeling consistency rate of pneumoconiosis staging ranged from 84.68% to 93.66%. The diagnostic accuracy, sensitivity, specificity, and AUC of TMNet were 95.20%, 99.66%, 88.61%, and 0.987, respectively. The indicators of ResNeXt were 87.00%, 89.93%, 82.67%, and 0.911, respectively. Those of ResNet were 84.00%, 85.91%, 81.19%, and 0.912, respectively. All these indexes of TMNet were higher than those of ResNeXt-50 and ResNet-50 models. The AUC differences between TMNet and the other two models were both statistically significant (P<0.001). Conclusion All the three convolutional neural network models can effectively diagnose the presence of pneumoconiosis, among which TMNet provides the best efficiency.