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.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

ObjectiveTo present the exploration and application of a prospective follow-up research method for acute infectious disease surveillance based on natural community populations， using COVID-19 infection as an example， and to provide a reference for improving the infectious disease surveillance and early warning system. MethodsA multi-stage probability proportional sampling method was employed to sample residents from all communities of 16 administrative districts in Shanghai， with households as the units. A cohort for acute infectious diseases based on natural community populations was established. The baseline survey was conducted for all cohort subjects， and COVID-19 antigen test kits were distributed. From December 21， 2022 to September 30， 2023， prospective follow-up monitoring of COVID-19 antigen and nucleic acid was carried out on the study subjects on a weekly basis. The baseline characteristics and follow-up information of the cohort subjects were described. ResultsThe cohort for acute infectious diseases included a total of 12 881 subjects， comprising 6 098 males （47.3%） and 6 783 females （52.7%）. The baseline survey revealed that 35.2% （4 540/12 881） of the subjects had a history of COVID-19 infection. During the follow-up period from December 21， 2022 to September 30， 2023， the average incidence density in the cohort was 0.61/person-year， with a higher incidence density in females （0.63/person-year） compared to males （0.59/person-year）. Individuals aged 60 and above （0.64/person-year） and those with underlying health conditions （0.67/person-year） had a higher incidence density. Healthcare workers showed a notably higher incidence density （0.84/person-year） than that in other occupational groups. As of September 30， 2023， a total of 340 subjects in the cohort experienced secondary infections， with a median interval of 170 days between the first and second infections. ConclusionThis study applies cohort study method to acute infectious disease surveillance， providing crucial data support for estimating infection rates and forecasting alerts for acute infectious diseases in the community. This method can be promoted and applied as a new approach for acute infectious disease surveillance.

Objective To comprehensively excavate and analyze the research status,research hotspots and future trends of the literature related to the field of acupoint catgut embedding therapy for pain treatment in the CNKI database.Methods We searched the CNKI database from its establishment to June 2022,and scientifically analyzed the authors,keywords,and institutions of the included literature of acupoint catgut embedding therapy for pain treatment through specific algorithms of Citespace to generate a visual knowledge map.Results A total of 319 documents were included for statistical analysis,the number of publications in the field of acupoint catgut embedding therapy for the treatment of pain was generally on the rise,the number of publications by various authors was on the low side,and there was a lack of co-operation between the research teams,with the main institutions being the Guang'anmen Hospital,Chinese Academy of Chinese Medical Sciences,Affiliated Hospital of Youjiang Medical Universities of Nationalities and the Guangzhou University of Chinese Medicine,forming a 10-keyword clustering,and the hotspots of diseases under study were mainly mixed haemorrhoids,postoperative pain,low back and leg pain and dysmenorrhoea,etc..The main interventions were pure acupoint catgut embedding therapy and the combination of acupoint catgut embedding therapy and other acupuncture therapies,and the main research method was clinical research.Conclusion Acupoint catgut embedding therapy for the treatment of pain has a good development prospect,the future needs to deepen the clinical research,strengthen the mechanism research,pay attention to the joint use of acupoint catgut embedding therapy and other traditional Chinese medicine methods,and pay attention to the research of different thread materials.

BACKGROUND:Kidney deficiency is the main pathogenesis of osteoporosis.To study the relationship between the two major syndrome types of kidney deficiency,Kidney-Yang deficiency and Kidney-Yin deficiency,is beneficial for the development of clinical diagnosis and treatments based on the combination of disease and syndrome. OBJECTIVE:To evaluate the biomechanical differences of the rat femurs with Kidney-Yang deficiency and Kidney-Yin deficiency caused by Yougui pills,and to demonstrate the scientific efficacy of medication based on the combination of disease and syndrome in osteoporosis from a biomechanical perspective. METHODS:The bilateral ovaries of 60 female Sprague-Dawley rats were surgically removed to establish an ovariectomized osteoporosis model.At 10 weeks after modeling,all the rats were randomly divided into a Kidney-Yang deficiency group(n=30)and a Kidney-Yin deficiency group(n=30).Rats with Kidney-Yang deficiency were given gluteal intramuscular injection of hydrocortisone,while rats with Kidney-Yin deficiency were orally administered with thyroid tablet suspension,once a day,for 14 consecutive days.After successful modeling,20 rats in each group were given a suspension of Yougui pills by gavage once a day for 12 consecutive weeks and the remaining 10 rats were used as the control group without intervention.After gavage,the microstructural parameters of the bone were measured using Micro-CT scanning.Three-point bending,finite element simulation,femoral head compression,and surface indentation distribution experiments of the femurs were performed on a mechanical testing machine. RESULTS AND CONCLUSION:Micro-CT revealed that the femoral bone density,bone volume fraction,bone surface density,trabecular number,and trabecular separation were improved in the Kidney-Yin deficiency+Yougui pills group compared with the Kidney-Yin deficiency group(P＜0.05);the femoral bone volume fraction,bone surface density,trabecular number,and trabecular thickness were improved in the Kidney-Yang deficiency+Yougui pills group compared with the Kidney-Yang deficiency group(P＜0.05).The three-point bending experiment showed that the femur elastic modulus,maximum bending strength and bending fracture strength were decreased(P＜0.05)and toughness was increased(P＜0.05)in the Kidney-Yang deficiency+Yougui pills group compared with the Kidney-Yang deficiency group.Finite element simulation showed that Yougui pills could significantly improve the bending resistance of the femurs in the Kidney-Yang deficiency group,but had no significant effect on the Kidney-Yin deficiency group.The femoral head compression experiments showed that Yougui pills could enhance the ability of the femoral head to resist deformation in the Kidney-Yang deficiency group,but there was no significant difference in the effect of Yougui pills on the surface properties of the femoral head in the Kidney-Yin deficiency group and the Kidney-Yang deficiency group.To conclude,Yougui pills can significantly enhance the biomechanical properties of the osteoporotic bones with Kidney-Yang deficiency,but have no significant effect on the osteoporotic bone with Kidney-Yin deficiency.

ObjectiveTo observe the clinical effectiveness and safety of Xuandi Ziyin Mixture （玄地滋阴合剂） for central precocious puberty （CPP） in girls with syndrome of yin deficiency and fire exuberance， and to analyse the effect of body mass index （BMI） on the effectiveness. MethodsA total of 236 girls with CPP of yin deficiency and fire exuberance syndrome were included， and all of them were given Xuandi Ziyin Mixture， 30 ml each time， twice a day， for a total treatment period of 6 months. Before and after treatment， children's weight， height and bone age were measured， BMI and BMI Z-score （BMI Z） and the difference between bone age and actual age were calculated； ultrasound was used to detect uterine and ovarian sizes， and to calculate uterine volume （V_uterus）， bilateral ovarian volume （V_{left ovary}， V_{right ovary}）， and bilateral maximal follicle diameters （r_{left follicle} and r_{right follicle}）； and serum sex hormones were measured， including follicle-stimulating hormone （FSH）， luteinising hormone （LH）， prolactin （PRL）， estradiol （E₂）， and testosterone （T）， and were scored for traditional Chinese medicine （TCM） syndrome. Multiple linear regression was used to analyse the influence factors of the difference between bone age and actual age， and changes in uterine volume. The children were divided into the normal weight group and the overweight/obesity group according to baseline BMI， and the bone age， the difference between bone age and actual age， V_uterus and BMI Z scores before and after treatment were compared between the two groups. ResultsFinally， 199 children entered the statistical analysis. Compared with pre-treatment， the bone age， BMI and BMI Z scores of the children increased after treatment， and the difference between bone age and actual age， TCM syndrome scores， V_uterus， V_{left ovary}， V_{right ovary}， r_{left follicle} and r_{right follicle} decreased； and the levels of serum FSH， LH， E₂， and T significantly decreased （P＜0.05 or P＜0.01）. The difference between bone age and actual age was negatively correlated with LH and V_uterus （P＜0.05）， and changes in uterine volume were positively correlated with LH （P＜0.01）. Comparing between the groups before and after treatment， the bone age， difference between bone age and actual age， and BMI Z scores of children in the normal weight group （100 cases） were significantly smaller than those in the overweight/obesity group （99 cases） （P＜0.01）. Compared with pre-treatment， the bone age of the children in both groups increased， but the difference between bone age and actual age and V_uterus were significantly smaller （P＜0.01）. Further comparison of Δ bone age and actual age difference and ΔV_uterus （Δ = post-treatment value - pre-treatment value） between the two groups showed no statistically significant difference （P＞0.05）. ConclusionsXuandi Ziyin Mixture can reduce bone age， sex hormone level， ovary and uterus size， and improve clinical symptoms in girls with yin deficiency and fire exuberance syndrome of CPP. It is also effective in overweight/obese children， and the inhibitory effect on bone age in girls with CPP is not affected by BMI， with good safety.

Objective To analyze the pathogenic characteristics and drug sensitivity of candidaemia,and construct a short-term mortality risk prediction scoring model.Methods The clinical data of patients with candidaemia admitted to the 909 Hospital of Joint Logistics Support Force from January 2011 to December 2020 were retrospectively analyzed,and the composition of pathogen composition,drug sensitivity test results and incidence of hospitalized patients were analyzed.324 cases of candidaemia were randomly divided into modeling group(190 cases)and validation group(134 cases),and the risk factors were screened by binary logistic regression.According to the odds ratio(OR)score,the 30 day mortality risk prediction scoring model was constructed,and the predictive performance of the model was verified both in modeling and validation groups.Results 356 strains of Candida including 126 strains of C.albicans(35.39%),79 strains of C.tropicalis(22.19%),74 strains of C.parapsilosis(20.79%),48 strains of C.glabrata(13.48%),14 strains of C.guilliermondii(3.93%),8 strains of C.krusei(2.25%),and 7 strains of other Candida(1.97%)were detected in 336 patients with candidemia.The incidence of candidaemia among hospitalized patients increased from 0.20 ‰ in 2011 to 0.48 ‰ in 2020.The resistance rate of candida to amphotericin B was significantly lower than that of fluconazole,voriconazole and itraconazole(P＜0.05).Among the 324 cases included in the model,95 patients died in 30 days after diagnosis,and the mortality rate was 29.32%.The proportion of males,fever,and parenteral nutrition in modeling group was significantly higher than that in validation group(P＜0.05),while the proportion of chronic lung disease and surgical history within one month were lower than those in validation group(P＜0.05).Logistic regression analysis showed that chronic renal failure,mechanical ventilation,severe neutropenia,failure to receive anti-fungal treatment within 72 hours,and APACHE Ⅱ≥20 were risk factors for short-term death of candidaemia,the OR values were 3.179,1.970,2.979,2.080,and 2.399,and the risk scores were 6,4,6,4,and 5,respectively.The area under the curve(AUC)of the risk scoring model for modeling group was 0.792(95%CI 0.721-0.862),and the result of Hosmer-Lemeshow(H-L)test was P=0.305;The AUC of validation group was 0.796(95%CI 0.735-0.898),and the H-L test result was P=0.329.A risk score≤8 indicated a low risk group for short-term mortality,a score of 9-15 indicated a medium risk group,and a score≥16 indicated a high risk group.Conclusions The incidence of candidemia in hospitalized patients is increasing and the mortality is high.The risk prediction score model can effectively predict the short-term prognosis and facilitate the early identification of the prognosis.

ObjectiveThis study aimed to develop a novel method for encapsulating oocytes in sodium alginate hydrogel using microfluidics, then to vitrify these encapsulated oocytes in a single-step process with low concentrations of cryoprotectants. MethodsWe utilized a flow-focusing microfluidic chip to generate sodium alginate hydrogel microspheres. The influence of various parameters, including throat structure, cross-linking method, sodium alginate concentrations, and flow rate ratios on the stability diameter, and coefficient of variation of microspheres were examined. To further investigate the cold-resistance of these microspheres, we used cryomicroscopy to observe changes in volume and morphology of microspheres during cooling and warming processes. We used microfluidic chip to encapsulate oocytes in sodium alginate hydrogel microspheres, the empty rate of microspheres and loss rate of oocytes were determined. After releasing from microspheres and parthenogenetic activation with cytochalasin B and strontium chloride, the survival, cleavage and blastocyst rates were evaluated during in vitro maturation. Finally, oocytes encapsulated in sodium alginate microspheres were vitrified with low concentrations of cryoprotectants. We compared the survival and development capability of the oocytes with the Cryotop method. ResultsWhen the throat of the microfluidic chip measures 300 μm in length and 120 μm in width, microspheres can be uniformly formed at the throat of the chip. Sodium alginate generates microspheres with a wide size distribution when cross-linking outside the chip, while internal cross-linking within the chip results in more uniform microspheres. The stability of microsphere formation is significantly improved with the use of a three-channel internal cross-linking chip. At a flow rate of 2 μl/min and with 1% sodium alginate, the microfluidic chip can consistently and uniformly produce microspheres. Under flow rate ratios of 10, 15, and 20, the average microsphere diameters are 262.71 μm, 193.63 μm, and 156.63 μm, respectively. The sodium alginate hydrogel microspheres maintained their volume and structural integrity during the cooling and warming processes. Using a three-channel internal cross-linking microfluidic chip to encapsulate oocytes, at a flow rate ratio of 10, the empty rate is 32.28%, and the cell loss rate is 11.09%. After encapsulation and subsequent release, the oocyte survival rate (96.99%), cleavage rate (88.71%), and blastocyst formation rate (26.29%) showed no significant differences compared to the fresh group. After the microspheres were vitrified using a low concentration of cryoprotectant (10% DMSO+10% ehylene glycol (EG)+0.5 mol/L trehalose), the survival rate, cleavage rate, and blastocyst rate were 92.48%, 70.80%, and 20.42%, respectively. No significant difference was observed when compared to the Cryotop method using a higher concentration of cryoprotectant solution (15% DMSO+15% EG+0.5 mol/L trehalose). ConclusionWe designed and fabricated a microfluidic system with three-channel internal cross-linking chips used for oocyte vitrification preservation. The microfluidic system can generate oocytes-loaded sodium alginate hydrogel microspheres with uniform size, low empty rate, and good cold-resistance. The method successfully reduced the concentration of cryoprotectants in a single-step vitrification process, the developmental capability of oocytes during in vitro maturation were comparable with Cryotop method. Unlike the Cryotop method, the oocytes encapsulated in hydrogel does not come into contact with liquid nitrogen, eliminating the risk of cross-contamination. This study provides a novel approach to oocyte vitrification.

Objective To observe the efficacy and safety of Morinda officinalis oligosaccharides in the continuation treatment of mild and moderate depression.Methods An open,single-arm,multi-center design was adopted in our study.Adult patients with mild and moderate depression who had received acute treatment of Morinda officinalis oligosaccharides were enrolled and continue to receive Morinda officinalis oligosaccharides capsules for 24 weeks,the dose remained unchanged during continuation treatment.The remission rate,recurrence rate,recurrence time,and the change from baseline to endpoint of Hamilton Depression Scale(HAMD),Hamilton Anxiety Scale(HAMA),Clinical Global Impression-Severity(CGI-S)and Arizona Sexual Experience Scale(ASEX)were evaluated.The incidence of treatment-related adverse events was reported.Results The scores of HAMD-17 at baseline and after treatment were 6.60±1.87 and 5.85±4.18,scores of HAMA were 6.36±3.02 and 4.93±3.09,scores of CGI-S were 1.49±0.56 and 1.29±0.81,scores of ASEX were 15.92±4.72 and 15.57±5.26,with significant difference(P＜0.05).After continuation treatment,the remission rate was 54.59％(202 cases/370 cases),and the recurrence rate was 6.49％(24 cases/370 cases),the recurrence time was(64.67±42.47)days.The incidence of treatment-related adverse events was 15.35％(64 cases/417 cases).Conclusion Morinda officinalis oligosaccharides capsules can be effectively used for the continuation treatment of mild and moderate depression,and are well tolerated and safe.

Objective:To understand the epidemiological characteristics of diarrheagenic Escherichia ( E. ) coli infection in infectious diarrhea outpatients aged 15 years and older in Shanghai and provide evidence for the development of disease control strategies .Methods:Based on multistage systematic sampling, diarrhea surveillance was conducted in 22 sentinel hospitals in Shanghai, the information about cases' demographic, clinical, and epidemiological characteristics were collected. Stool samples were collected for the detection and typing of diarrheagenic E. coli by local centers for disease control and prevention. The positive rate of diarrheagenic E. coli in different populations and seasons from 2014 to 2021 were analyzed. Statistical analysis was conducted by using χ2 test. Results:In 15 185 diarrhea cases, 8.05% (1 222/15 185) were positive for diarrheagenic E. coli. The positive rate was higher in men (8.74%, 684/7 824) than in women (7.31%, 538/7 361). The positive rate was highest in age group 15-29 years (9.14%, 335/3 665) and the annual positive rate was highest in 2021 (10.21%, 83/813), the differences were all significant ( P<0.05). In the 1 264 strains of diarrheagenic E. coli analyzed through PCR, enterotoxingenic E. coli was the most frequently identified pathogen (50.24%, 635/1 264), followed by enteroadhesive E. coli (27.93%, 353/1 264), and enteropathogenic E. coli (21.36%, 270/1 264). The positive rate of diarrheagenic E. coli showed obvious seasonality with peak in summer (13.92%, 774/5 562) ( χ2=495.73, P<0.001). Conclusions:Diarrheagenic E. coli has become a prominent pathogen in infectious diarrhea cases in Shanghai, the disease can occur all the year round with incidence peak during summer and autumn. Predominant subtypes included enterotoxingenic E. coli, enteroadhesive E. coli and enteropathogenic E. coli. Targeted prevention and control strategies are needed for diarrheagenic E. coli-induced infectious diarrhea in different age groups, seasons and for different types of infections.