Electromagnetic fields can regulate the fundamental biological processes involved in bone remodeling. As a non-invasive physical therapy, electromagnetic fields with specific parameters have demonstrated therapeutic effects on bone remodeling diseases, such as fractures and osteoporosis. Electromagnetic fields can be generated by the movement of charged particles or induced by varying currents. Based on whether the strength and direction of the electric field change over time, electromagnetic fields can be classified into static and time-varying fields. The treatment of bone remodeling diseases with static magnetic fields primarily focuses on fractures, often using magnetic splints to immobilize the fracture site while studying the effects of static magnetic fields on bone healing. However, there has been relatively little research on the prevention and treatment of osteoporosis using static magnetic fields. Pulsed electromagnetic fields, a type of time-varying field, have been widely used in clinical studies for treating fractures, osteoporosis, and non-union. However, current clinical applications are limited to low-frequency, and research on the relationship between frequency and biological effects remains insufficient. We believe that different types of electromagnetic fields acting on bone can induce various “secondary physical quantities”, such as magnetism, force, electricity, acoustics, and thermal energy, which can stimulate bone cells either individually or simultaneously. Bone cells possess specific electromagnetic properties, and in a static magnetic field, the presence of a magnetic field gradient can exert a certain magnetism on the bone tissue, leading to observable effects. In a time-varying magnetic field, the charged particles within the bone experience varying Lorentz forces, causing vibrations and generating acoustic effects. Additionally, as the frequency of the time-varying field increases, induced currents or potentials can be generated within the bone, leading to electrical effects. When the frequency and power exceed a certain threshold, electromagnetic energy can be converted into thermal energy, producing thermal effects. In summary, external electromagnetic fields with different characteristics can generate multiple physical quantities within biological tissues, such as magnetic, electric, mechanical, acoustic, and thermal effects. These physical quantities may also interact and couple with each other, stimulating the biological tissues in a combined or composite manner, thereby producing biological effects. This understanding is key to elucidating the electromagnetic mechanisms of how electromagnetic fields influence biological tissues. In the study of electromagnetic fields for bone remodeling diseases, attention should be paid to the biological effects of bone remodeling under different electromagnetic wave characteristics. This includes exploring innovative electromagnetic source technologies applicable to bone remodeling, identifying safe and effective electromagnetic field parameters, and combining basic research with technological invention to develop scientifically grounded, advanced key technologies for innovative electromagnetic treatment devices targeting bone remodeling diseases. In conclusion, electromagnetic fields and multiple physical factors have the potential to prevent and treat bone remodeling diseases, and have significant application prospects.

The inheritance, innovation, and development of traditional Chinese medicine(TCM) need to be based on Chinese medicinal materials. The TCM seed industry is the source of TCM production, which is related to the stable supply and quality safety of TCM. This paper summarizes the basic situation of the TCM seed industry and introduces relevant policies and regulations to TCM seeds in the seed industry and the TCM field. At present, the Management Measures of TCM Seeds and Seedlings has not yet promulgated, and TCM seeds are classified as non-major crops in the category of crops for management. This paper also describes the current situation of TCM seed and seedling system construction, which is in the development stage, from six aspects, including the construction of TCM seed industry technical support system; the establishment of TCM seed standard; the construction of germplasm resource preservation system; TCM seed testing, variety registration, and variety protection; production and management of TCM seeds; TCM seed supervision. According to the development status of the TCM seed industry, four problems are put forward, including imperfect systems and standards relevant to TCM seeds, insufficient supervision and law enforcement regarding TCM seeds, insufficient policy measures and capital investment to promote the development of the industry, and the industry's falling into a low-level cycle.Accordingly, four suggestions are provided, including improving laws, regulations, and policies, perfecting standards and norms,strengthening supervision and law enforcement, and promoting support system construction, in order to boost the high-quality development of the TCM seed industry.
Seeds/chemistry* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/standards* ; Plants, Medicinal/chemistry*

OBJECTIVE: To compare clinical effect of arthroscopic double row fixation and single row fixation in treating Ideberg typeⅠA scapular glenoid fracture. METHODS: From June 2018 to December 2022, 26 patients with Ideberg typeⅠA scapular glenoid fracture treated with shoulder arthroscopy were divided into single-row anchor group and double-row anchor group according to the fixation method of fracture block. There were 12 patients in single-row anchor group, including 7 males and 5 females, aged from 25 to 53 years old with an average of (38.42±9.61) years old;the time from injury to operation ranged from 2 to 7 days with an average of (4.75±1.82) days. There were 14 patients in double-row anchor group, including 10 males and 4 females, aged from 21to 53 years old with an average of (37.36±10.19) years old;the time from injury to operation ranged from 1 to 8 days with an average of (4.21±2.01) days. The changes of shoulder joint flexion, abduction, lateral lateral rotation, Constant-Murley shoulder function score and Rowe scores were compared between two groups before operation and 1 year after operation. The percentage of bone mass in pelvis area before operation and the percentage of bone defect in pelvis area at the latest follow-up were compared between two groups. RESULTS: All patients were followed up for 12 to 15 months with an average of (13.08±1.17) months in single-row anchor group and 12 to 15 months with an average of (13.29±1.07) months in double-row anchor group, with no statistical significance between two groups (P>0.05). The results of anterior flexion, abduction and lateral lateral rotation in single-row anchor group were(86.67±6.62) °, (79.50±5.68) °, (38.17±1.70) ° before operation, and (162.50±4.52)°, (169.17±3.35)°, (50.67±10.20)° at 1 year after operation; while in double-row anchor group were (84.14±5.48) °, (81.71±5.20) °, (39.29±3.63) ° before operation and (162.29 ± 5.53) °, (167.14±3.61) °, (56.93±9.56) ° at 1 year after operation;the difference between two groups before operation and 1 year after operation was statistically significant (P<0.05). There were no significant difference between two groups (P>0.05). Constant-Murley scores and Rowe scores in single-row anchor group were (55.42±3.75), (43.75±18.49) before operation and (94.83±2.21), (95.42±4.50) at 1 year after operation, respectively;while in double-row anchor group were (54.50±7.88), (41.79±18.25) before operation and (94.36±4.73), (95.00±4.80) at 1 year after operation;there was no significant difference in Constant-Murley score and Rowe score between two groups before operation and 1 year after operation (P>0.05). There was significant difference in the percentage of bone mass in pelvis area between two groups before operation (P>0.05). There was no significant difference in the percentage of bone defect in the shoulder area between single-row anchor group(4.42±1.51)% and double-row anchor group (2.71±1.44)% at 1 year after operation (P<0.05). CONCLUSION Both single and double row fixation techniques for the treatment of Ideberg typeⅠA scapular glenoid fracture could receive satisfactory functional recovery. However, double-row fixation has more advantages in reducing bone resorption of fracture mass.
Humans ; Female ; Male ; Middle Aged ; Arthroscopy/methods* ; Adult ; Scapula/surgery* ; Case-Control Studies ; Fractures, Bone/physiopathology* ; Fracture Fixation, Internal/methods* ; Shoulder Joint/physiopathology* ; Range of Motion, Articular

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

Wastewater-based epidemiology has emerged as a transformative surveillance tool for estimating substance consumption and monitoring disease prevalence, particularly during the COVID-19 pandemic. It enables the population-level monitoring of illicit drug use, pathogen prevalence, and environmental pollutant exposure. In this perspective, we summarize the key challenges specific to the Chinese context: (1) Sampling inconsistencies, necessitating standardized 24-hour composite protocols with high-frequency autosamplers (≤ 15 min/event) to improve the representativeness of samples; (2) Biomarker validation, requiring rigorous assessment of excretion profiles and in-sewer stability; (3) Analytical method disparities, demanding inter-laboratory proficiency testing and the development of automated pretreatment instruments; (4) Catchment population dynamics, reducing estimation uncertainties through mobile phone data, flow-based models, or hydrochemical parameters; and (5) Ethical and data management concerns, including privacy risks for small communities, mitigated through data de-identification and tiered reporting platforms. To address these challenges, we propose an integrated framework that features adaptive sampling networks, multi-scale wastewater sample banks, biomarker databases with multidimensional metadata, and intelligent data dashboards. In summary, wastewater-based epidemiology offers unparalleled scalability for equitable health surveillance and can improve the health of the entire population by providing timely and objective information to guide the development of targeted policies.
China/epidemiology* ; Humans ; Wastewater/analysis* ; COVID-19/epidemiology* ; Public Health ; Wastewater-Based Epidemiological Monitoring ; SARS-CoV-2

Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective To construct an aptamer-functionalized carboxylated graphene oxide(CGO)fluo-rescent sensor to achieve highly sensitive and specific detection of ketamine(KET)and its metabolite norketamine(NK)using an aptamer capable of simultaneously recognizing KET and NK.Methods A specific aptamer for simultaneous recognition of KET and NK was screened using graphene oxide-sys-tematic evolution of ligand by exponential enrichment(GO-SELEX)and molecular docking tech-niques.The aptamer,labeled with Cy5 fluorescence,was chemically conjugated to CGO to construct an aptamer-functionalized CGO fluorescent sensor.By optimizing detection conditions,including the mass concentration of CGO,aptamer concentration,reaction temperature,and incubation time,quantita-tive analysis of the target analytes was achieved using the ratio of fluorescence intensity changes be-fore and after target addition.The stability of the sensor in biological matrices was evaluated by moni-toring fluorescence intensity changes over incubation time in blank blood and urine,in comparison with the traditional physical adsorption-based CGO fluorescent sensor.Spiked recovery experiments in blank blood and urine were conducted to compare performance with that of HPLC-MS/MS.Results A specific aptamer A5 was selected and chemically conjugated with CGO to construct the aptamer-functionalized CGO fluorescent sensor.Under optimized conditions,the proposed fluorescent sensor ex-hibited a linear detection range of 1.0-5.0 ng/mL for KET,with a limit of detection(LOD)of 0.86 ng/mL;while for NK,the linear detection range was 1.0-5.0 ng/mL,with an LOD of 0.70 ng/mL.Com-pared with the CGO fluorescent sensor constructed via physical adsorption,this sensor demonstrated greater stability in blood and urine.The spiked recovery rates of KET and NK in blank blood and urine ranged from 81.50%to 110.03%,exhibiting detection performance comparable to that of HPLC-MS/MS.Conclusion The aptamer screening method offers a novel approach for selecting aptamers tar-geting drugs and their metabolites.The constructed aptamer-functionalized CGO fluorescent sensor pro-vides an efficient and reliable strategy for the high-performance detection of KET and NK.

Objective To investigate the correlation of serum human epididymis protein 4(HE4)and lung injury Prediction(LIPS)score with sepsis-associated acute respiratory distress syndrome(ARDS)and 28 d mortality.Methods A total of 207 patients with sepsis admitted to the hospital from January 2021 to January 2024 were selected.According to the presence or absence of ARDS,the patients were divided into ARDS group(73 cases)and non-ARDS group(134 cases).According to the 28 d survival,the ARDS group was further di-vided into death group(26 cases)and survival group(47 cases).HE4 level was detected by electrochemilumi-nescence,and LIPS score was calculated.Multivariate Logistic regression model was used to analyze the influ-encing factors of death in ARDS patients.Point biserial correlation was used to analyze the correlation between serum HE4,LIPS score and 28 d death in ARDS patients.The receiver operating characteristic(ROC)curve was used to evaluate the value of serum HE4 and LIPS score in the diagnosis of sepsis-associated ARDS and predicting 28 d mortality.Results Compared with non-ARDS group,the serum HE4 level and LIPS score were significantly increased in ARDS group(P<0.05).The independent risk factors for sepsis-associated ARDS were increased SOFA score,increased blood lactic acid,increased HE4 and increased LIPS score(P<0.05).The 28 d mortality of 73 patients with sepsis-associated ARDS was 35.62%(26/73).Compared with the survival group,the serum HE4 and LIPS scores were increased in the death group(P<0.05).Serum HE4 and LIPS scores were positively correlated with 28 d mortality in patients with sepsis-associated ARDS(r=0.605,0.579,P<0.05).The area under the curve(AUC)of serum HE4 combined with LIPS score in the di-agnosis of sepsis-associated ARDS was 0.909,which was larger than 0.828 and 0.806 of serum HE4 and LIPS score alone(Z=3.360,3.387,all P<0.05).The AUC of serum HE4 combined with LIPS score in predicting 28 d mortality of patients with sepsis-associated ARDS was 0.891,which was larger than 0.808 and 0.779 of by serum HE4 and LIPS score alone(Z=2.028,2.017,all P<0.05).Conclusion The elevated serum HE4 level and LIPS score are independent risk factors for sepsis-associated ARDS,and are closely related to 28 d mortality.The combination of serum HE4 and LIPS score has a high value in the diagnosis of sepsis-associated ARDS and the prediction of 28 d mortality.