Background With China's socio-economic development, the dietary structure of Chinese residents has gradually shifted from a traditional Eastern pattern characterized by high carbohydrate intake to a relatively high-fat Western dietary model, alongside a growing burden of chronic diseases. However, dietary changes may vary across different occupational groups. Objective To analyze the long-term trends in dietary energy and three major macronutrient intake among various occupational groups aged 18-59 years in nine provinces of China from 1989 to 2018, providing a scientific basis for developing occupation-specific dietary intervention strategies. Methods Based on 11 waves of data (1989–2018) from the China Health and Nutrition Survey (CHNS), 57458 employed individuals aged 18-59 years were selected as observation subjects after applying inclusion and exclusion criteria. Joinpoint regression was used to analyze temporal trends by calculating the annual percentage change (APC) and average annual percentage change (AAPC) with 95% confidence intervals. The analysis covered the energy supply ratio from the three major macronutrients and the proportion of the participants within the acceptable macronutrient distribution ranges (AMDR) for the total occupational population and specific occupational group. Results From 1989 to 2018, the dietary structure of the occupational population in the nine provinces gradually Westernized. The carbohydrate energy supply ratio showed a decreasing trend (AAPC=−0.77%, 95%CI: −1.00%, −0.55%, P<0.05), while the fat energy supply ratio increased (AAPC=1.42%, 95%CI: 1.07%, 1.77%, P<0.05). The protein energy supply ratio remained largely unchanged (AAPC=−0.19%, 95%CI: −0.08%, 0.46%, P>0.05), and the total energy intake declined (AAPC=−0.62%, 95%CI: −0.94%, −0.30%, P<0.05). Among the occupational groups studied, white-collar workers were the first to show characteristics of dietary Westernization. Using the AMDR as the criterion, their average fat energy supply ratio first exceeded the AMDR upper limit (30%) in 1993, and their average carbohydrate energy supply ratio first fell below the AMDR lower limit (50%) in 2006, both time points being earlier than other occupational groups. Agricultural workers lagged in this transition (their average fat energy supply ratio first reached ≥30% in 2011), but their rate of increase in the fat energy supply ratio was the fastest among all occupational groups (AAPC=1.59%, 95%CI: 0.90%, 2.30%, P<0.05; P for trend comparison between groups<0.05). The other three occupational groups (blue-collar workers, service workers, and others) generally fell between these two extremes. Taking the fat energy supply ratio as an example, their AAPCs of increase were 1.02% (95%CI: 0.73%, 1.32%, P<0.05) for blue-collar workers, 0.85% (95%CI: 0.61%, 1.09%, P<0.05) for service workers, and 0.88% (95%CI: 0.58%, 1.17%, P<0.05) for others. Conclusion From 1989 to 2018, the macronutrient structure of the occupational population aged 18-59 years in nine China provinces is gradually Westernized. The energy supply ratios of carbohydrates and proteins primarily face issues of potential inadequacy, while the fat energy supply ratio is excessively high. Furthermore, the patterns of change vary among different occupational groups. It is recommended to propose personalized dietary advice tailored to specific occupations.

Objective To analyze the prevalence status of cardiometabolic risk factor (CMRF) and its aggregation among workers engaged in new forms of employment. Methods A total of 5 429 new employment workers (including couriers, online food delivery workers, and ride hailing drivers) who underwent health medical examinations at a tertiary hospital in Beijing City were selected as the research subjects using the judgment sampling method. Data on waist circumference, blood pressure, blood glucose, and blood lipid levels were collected to analyze their CMRF [central obesity, elevated blood pressure, elevated blood glucose, elevated triglycerides, and reduced high-density lipoprotein cholesterol (HDL-C)] and their aggregation (with ≥ 2 of the above 5 risk factors) status. Results The detection rates of central obesity, elevated blood pressure, elevated blood glucose, elevated triglycerides, and reduced HDL-C were 61.2%, 38.2%, 29.5%, 40.9% and 22.6%, respectively. The detection rates of CMRF aggregation was 57.8%. The result of multivariable logistic regression analysis showed that male, age ≥45 years, smoking, overweight, and obesity were risk factors for CMRF aggregation (all P<0.05). Conclusion The detection rate of CMRF and its aggregation among workers with new forms of employment in Beijing City is relatively high. Targeted prevention and control efforts should be strengthened for high-risk populations, especially males, workers aged ≥45 years, smokers, and those who are overweight or obese.

Glucocorticoid-induced osteoporosis(GIOP) is a serious metabolic bone disease caused by long-term application of glucocorticoids(GCs). Traditional Chinese medicine(TCM) has unique advantages in improving bone microstructure and antagonizing hormone toxicity. This paper systematically reviews the theoretical research, clinical application, and basic research progress of TCM intervention in GIOP. In terms of theoretical research, the theory of "kidney governing bone and generating marrow" indicates that the kidney is closely related to bone development, revealing that core pathogenesis of GIOP is Yin-Yang disharmony, which can be discussed using the theories of "Yin fire", "ministerial fire", and "Yang pathogen damaging Yin". Thus, regulating Yin and Yang is the basic principle to treat GIOP. In terms of clinical application, effective empirical prescriptions(such as Bushen Zhuanggu Decoction, Bushen Jiangu Decoction, and Zibu Ganshen Formula) and Chinese patent medicines(Gushukang Capsules, Hugu Capsules, Xianling Gubao Capsules, etc.) can effectively increase bone mineral density(BMD) and improve calcium and phosphorus metabolism. The combination of traditional Chinese and western medicine can reduce the risk of fracture and play an anti-GIOP role. In terms of basic research, it has been clarified that active ingredients of TCM(such as fraxetin, ginsenoside Rg_1, and salidroside) reduce bone loss and promote bone formation by inhibiting oxidative stress, ferroptosis, and other pathways, effectively improving bone homeostasis. Additionally, classical prescriptions(Modified Yiguan Decoction, Modified Qing'e Pills, Zuogui Pills, etc.) and Chinese patent medicines(Gushukang Granules, Lurong Jiangu Dropping Pills, Gubao Capsules, etc.) can improve bone marrow microcirculation, promote osteoblast differentiation, and inhibit bone cell apoptosis through multiple pathways, multiple targets, and multiple mechanisms. Through the above three aspects, the TCM research status on GIOP is elucidated in the expectation of providing reference for its diagnosis and treatment using traditional Chinese and western medicine treatment programs.
Osteoporosis/physiopathology* ; Humans ; Glucocorticoids/adverse effects* ; Drugs, Chinese Herbal/administration & dosage* ; Animals ; Medicine, Chinese Traditional ; Bone Density/drug effects*

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Microbial communities such as those residing in the human gut are highly diverse and complex, and many with important implications for health and diseases. The effects and functions of these microbial communities are determined not only by their species compositions and diversities but also by the dynamic intra- and inter-cellular states at the transcriptional level. Powerful and scalable technologies capable of acquiring single-microbe-resolution RNA sequencing information in order to achieve a comprehensive understanding of complex microbial communities together with their hosts are therefore utterly needed. Here we report the development and utilization of a droplet-based smRNA-seq (single-microbe RNA sequencing) method capable of identifying large species varieties in human samples, which we name smRandom-seq2. Together with a triple-module computational pipeline designed for the bacteria and bacteriophage sequencing data by smRandom-seq2 in four human gut samples, we established a single-cell level bacterial transcriptional landscape of human gut microbiome, which included 29,742 single microbes and 329 unique species. Distinct adaptive response states among species in Prevotella and Roseburia genera and intrinsic adaptive strategy heterogeneity in Phascolarctobacterium succinatutens were uncovered. Additionally, we identified hundreds of novel host-phage transcriptional activity associations in the human gut microbiome. Our results indicated that smRandom-seq2 is a high-throughput and high-resolution smRNA-seq technique that is highly adaptable to complex microbial communities in real-world situations and promises new perspectives in the understanding of human microbiomes.
Humans ; Gastrointestinal Microbiome/genetics* ; Bacteriophages/physiology* ; High-Throughput Nucleotide Sequencing ; Sequence Analysis, RNA/methods* ; Bacteria/virology*

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

ObjectiveTo analyze the clinical treatment plan and traditional Chinese medicine （TCM） medication rule of children with primary nephrotic syndrome （PNS） in the First Affiliated Hospital of Henan University of Chinese Medicine. MethodsThe gender and age of children firstly diagnosed with nephrotic syndrome in the pediatric nephrology department of the First Affiliated Hospital of Henan University of Chinese Medicine from November 2019 to December 2022 were collected， and the use of immunosuppressive agents and related frequencies were counted. According to the inclusion and exclusion criteria， an independent TCM prescription database for children with nephrotic syndrome was established. Excel was used to analyze the relevant information of the literature. The frequency counting， association rule analysis， and cluster analysis were carried out on TCM in the prescription， and the high-frequent drugs were analyzed. Results（1） General information： A total of 711 children were included， consisting of 522 males （73.42%） and 189 females （26.58%）. The ratio of male to female was about 2.76∶1. The disease mainly occurred in infants and preschool age， and the average age of onset was （4.74 ± 3.48） years old. （2） Clinical treatment plan and use of immunosuppressive agents： Of the 711 children with PNS， 237 were treated with hormone alone （32.33%）， and 474 （66.67%） received immunosuppressive agents combined with hormones. In the initial treatment， hormone combined with Tacrolimus （TAC） was the preferred treatment （32.91%）. For children with refractory PNS who exhibited poor clinical efficacy， Rituximab （RTX） was mostly used for treatment， with a ratio of up to 23.63%. （3） TCM syndrome and medication rule： In PNS syndrome differentiation， Qi and Yin deficiency was identified as the main syndrome. This involved a total of 477 cases， accounting for 67.09%. Yang deficiency of spleen and kidney was observed in 118 cases， accounting for 16.60%. A total of 711 children were included， of which 706 children were treated with TCM. This involved a total of 706 prescriptions， 226 TCM， and 9 793 frequencies. There were 30 herbs used more than 95 times. The top five TCM were Radix et Rhizoma Glycyrrhizae （81.16%）， Radix Astragali （71.81%）， Poria （68.84%）， Rhizoma Atractylodis Macrocephalae （63.60%）， and Fructus Corni （57.37%）. The drug association rules and network diagram showed that the combination of ''Radix Astragali-Rhizoma Atractylodis Macrocephalae-Poria'' was the closest， and five types of combinations were obtained by cluster analysis. ConclusionIn the diagnosis and treatment of PNS in children， TAC combined with hormones shows good clinical efficacy and high safety. For children with refractory PNS， RTX combined with hormones can be used. TCM medication for PNS should follow the basic principles of strengthening the body and vital Qi and make good use of drugs such as Radix Astragali， Poria， Rhizoma Atractylodis Macrocephalae， and cornus to regulate the Yin and Yang balance and achieve better clinical efficacy.

ObjectiveTo analyze the clinical treatment plan and traditional Chinese medicine （TCM） medication rule of children with primary nephrotic syndrome （PNS） in the First Affiliated Hospital of Henan University of Chinese Medicine. MethodsThe gender and age of children firstly diagnosed with nephrotic syndrome in the pediatric nephrology department of the First Affiliated Hospital of Henan University of Chinese Medicine from November 2019 to December 2022 were collected， and the use of immunosuppressive agents and related frequencies were counted. According to the inclusion and exclusion criteria， an independent TCM prescription database for children with nephrotic syndrome was established. Excel was used to analyze the relevant information of the literature. The frequency counting， association rule analysis， and cluster analysis were carried out on TCM in the prescription， and the high-frequent drugs were analyzed. Results（1） General information： A total of 711 children were included， consisting of 522 males （73.42%） and 189 females （26.58%）. The ratio of male to female was about 2.76∶1. The disease mainly occurred in infants and preschool age， and the average age of onset was （4.74 ± 3.48） years old. （2） Clinical treatment plan and use of immunosuppressive agents： Of the 711 children with PNS， 237 were treated with hormone alone （32.33%）， and 474 （66.67%） received immunosuppressive agents combined with hormones. In the initial treatment， hormone combined with Tacrolimus （TAC） was the preferred treatment （32.91%）. For children with refractory PNS who exhibited poor clinical efficacy， Rituximab （RTX） was mostly used for treatment， with a ratio of up to 23.63%. （3） TCM syndrome and medication rule： In PNS syndrome differentiation， Qi and Yin deficiency was identified as the main syndrome. This involved a total of 477 cases， accounting for 67.09%. Yang deficiency of spleen and kidney was observed in 118 cases， accounting for 16.60%. A total of 711 children were included， of which 706 children were treated with TCM. This involved a total of 706 prescriptions， 226 TCM， and 9 793 frequencies. There were 30 herbs used more than 95 times. The top five TCM were Radix et Rhizoma Glycyrrhizae （81.16%）， Radix Astragali （71.81%）， Poria （68.84%）， Rhizoma Atractylodis Macrocephalae （63.60%）， and Fructus Corni （57.37%）. The drug association rules and network diagram showed that the combination of ''Radix Astragali-Rhizoma Atractylodis Macrocephalae-Poria'' was the closest， and five types of combinations were obtained by cluster analysis. ConclusionIn the diagnosis and treatment of PNS in children， TAC combined with hormones shows good clinical efficacy and high safety. For children with refractory PNS， RTX combined with hormones can be used. TCM medication for PNS should follow the basic principles of strengthening the body and vital Qi and make good use of drugs such as Radix Astragali， Poria， Rhizoma Atractylodis Macrocephalae， and cornus to regulate the Yin and Yang balance and achieve better clinical efficacy.

Objective Based on the radiomics features extracted from the unenhanced CT images of the lower abdomen, a variety of machine learning models were constructed to explore their application value in the assessment of split renal function. Methods A retrospective analysis was conducted on the unenhanced CT images from 240 single kidneys in patients with clinically suspected renal dysfunction. Based on the results of single-photon emission computed tomography renal dynamic imaging, the cases were classified into the normal glomerular filtration rate group (n=118) and the decreased glomerular filtration rate group (n=122). The region of interest was outlined on the unenhanced CT images and the radiomics features were extracted. The features were selected by correlation analysis and least absolute shrinkage and selection operator, and the machine learning models were constructed based on the algorithms of decision tree, support vector machine, random forest, logistic regression, and extreme gradient boosting. Area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were calculated to compare the performance of different models. Results Sixteen radiomics features were selected for constructing the machine learning models. The support vector machine model showed relatively high performance for the assessment of split renal function on the test set, with an area under the receiver operating characteristic curve value of 0.883 (95% confidence interval: 0.804-0.961), an accuracy of 0.778, a sensitivity of 0.811, and a specificity of 0.743. Conclusion The machine learning models constructed based on unenhanced CT radiomics can be used to preliminarily assess split renal function, which provides an innovative, convenient, and safe method for clinical diagnosis and has positive significance for treatment.