Application evaluation of cardiopulmonary exercise test to guide comprehensive pulmonary rehabilitation in patients with pneumoconiosis / 环境与职业医学

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 (Wmax). 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 Wmax 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 Wmax [(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.

Identification of novel bioactive proteins and their produced oligopeptides from Torreya grandis nuts using proteomic based prediction.

Torreya grandis nut is a chief functional food in China consumed for centuries. Besides its rich protein composition, increasing studies are now focusing on T. grandis functional proteins that have not yet identified. In this study, liquid chromatography coupled with mass spectrometry detection of smaller and major proteins, revealed that the major peptide was 36935.00 Da. Proteome sequencing annotated 142 proteins in total. Bioactive proteins such as defensin 4 was annotated and its anti-microbial function was verified. Finally, functional oligopeptides were predicted by searching sequences of digested peptides in databases. Ten group of oligopeptides were suggested to exhibit antioxidant, Angiotensin-converting enzyme inhibition, anti-inflammatory. The predicted antioxidant activity was experimentally validated. It is interesting that a peptide GYCVSDNN digested from defensin 4 showed antioxidant activity. This study reports novel functional peptides from T. grandis nuts that have not been isolated and/or included as functional ingredients in nutraceuticals and in food industry.

Application of deep eutectic solvents in protein extraction and purification.

Deep eutectic solvents (DESs) are a mixture of hydrogen bond donor (HBD) and hydrogen bond acceptor (HBA) molecules that can consist, respectively, of natural plant metabolites such as sugars, carboxylic acids, amino acids, and ionic molecules, which are for the vast majority ammonium salts. Media such as DESs are modular tools of sustainability that can be pointed toward the extraction of bioactive molecules due to their excellent physicochemical properties, their relatively low price, and accessibility. The present review focuses on the application of DESs for protein extraction and purification. The in-depth effects and principles that apply to DES-mediated extraction using various renewable biomasses will be discussed as well. One of the most important observations being made is that DESs have a clear ability to maintain the biological and/or functional activity of the extracted proteins, as well as increase their stability compared to traditional solvents. They demonstrate true potential for a reproducible but more importantly, scalable protein extraction and purification compared to traditional methods while enabling waste valorization in some particular cases.

Preparation of N,S-codoped magnetic bagasse biochar and adsorption characteristics for tetracycline.

Agricultural waste disposal and purification of polluted water are always the key issues of environmental restoration. In this work, thiourea-functionalized magnetic bagasse biochar (MFeBC) was prepared for tetracycline (TC) removal from aqueous solutions. Firstly, MFeBC was prepared by a combined impregnation and chemical coprecipitation method. Furthermore, MFeBC was characterized by Brunauer-Emmett-Teller surface area analysis, Fourier transform infrared spectrometry, X-ray diffraction analysis, scanning electron microscopy, X-ray photoelectron spectroscopy and the magnetic hysteresis curves. For the TC adsorption, the effects of different solution pH level, adsorbent dosage, initial TC concentration and temperature on the adsorption performance were studied respectively. Moreover, the results indicated that the Freundlich isotherm models appropriately described the adsorption process. The kinetic data were better fitted by the pseudo-second-order kinetic model. The maximum TC adsorption capacity of MFeBC reached 69.26 mg g-1. Hydrogen bonding and Π-Π interactions played a dominant role in the adsorption process. Therefore, MFeBC can be used as an effective adsorbent for tetracycline removal from aqueous solution.

Comparison on efficiency of three artificial intelligence-based models to read pneumoconiosis chest radiographs / 环境与职业医学

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.

Diurnal Variation in Hydration of the Cervical Intervertebral Disc Assessed Using T2 Mapping of Magnetic Resonance Imaging

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.