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.

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 retrospectively analyze the epidemic characteristics and spatial distribution of vomiting and diarrhea outbreaks in schools and kindergartens in Shanghai from 2015 to 2019, so as to provide the scientific evidence for optimizing prevention and control of vomiting and diarrhea outbreaks in schools and kindergartens. Methods: Data collection and analysis were carried out on the vomiting and diarrhea outbreaks reported to Shanghai Municipal Center for Disease Control and Prevention from 2015 to 2019. Epidemiological characteristics were analyzed and compared. The proportion and incidence of outbreaks in schools and kindergartens were calculated, and the influencing factors of outbreaks were analyzed by multivariate Logistic regression. The index of Moran s I was used for the global and local spatial auto correlation analysis. Results: Among the 344 vomiting and diarrhea outbreaks, 98.26% occurred in kindergartens, primary schools, middle schools and other educational institutions. The median number of cases per outbreak was 15. The number of suspected outbreaks and the percentage of cases involved peaked in 2015 ( 60.00% , 84.35%) and then decreased year by year to 16.00% and 38.80% in 2019. About 86.98% of the outbreaks were transmitted by human to human contact. Among the 329 outbreaks with samples collected from cases and/or environments, the main pathogen detected was norovirus ( n =280), and sapovirus was detected in outbreak for the first time in 2016. The outbreaks showed obvious seasonality, with two peaks (November, March) and one trough (July), and the majority of outbreaks occurred in primary schools (44.38%) and kindergartens (32.84%). Compared with kindergartens, the probabilities of suspected epidemic outbreaks in primary schools, combined schools, middle schools and other educational institutions were higher (adjusted OR =6.40, 9.16, 12.64 , 5.58, P <0.01). The proportion and incidence of outbreaks in educational institutions in different districts showed no high-high aggregation areas. Conclusions Primary schools and kindergartens are key places for the prevention and control of vomiting and diarrhea outbreaks. Targeted prevention and control measures should be strengthened at the beginning of each semester and before the peak of the epidemic each year. Timely reporting of symptoms, suspension of school admissions after symptoms appear and standardized disposal of vomit are effective measures to reduce interpersonal transmission and control the scale of an outbreak.

Xiaoke formula (XKF) is a classic formula for the treatment of insulin resistance (IR), but there is still unclear on bioactive equivalent combinatorial components (BECC) of XKF. In this study, based on the previous research of our team, three components, berberine, astragaloside IV and chlorogenic acid, were selected as the BECC of XKF, and their efficacy and mechanism were investigated. A high-fat diet-induced IR mouse model was used to detect blood glucose, insulin sensitivity, lipid metabolism, immune & inflammatory factors, etc., and staining of pathology sections was used to detect histopathological changes. Network pharmacology was used to predict the potential targets and signaling pathways of XKF and its BECC, and the results of the network were verified by Western blot. The animal welfare and experimental procedures followed the regulations of the Laboratory Animal Ethics Committee of Beijing MDKN Biotech Company (MDKN-2023-019). The results showed that BECC, which was composed of berberine, astragaloside IV and chlorogenic acid in the ratio of the original formula of XKF, was comparable to XKF in improving the glycemia, insulin sensitivity, histopathological damage, dyslipidemia, and immuno-inflammation in IR mice. The results of network pharmacology and Western blot suggested that the BECC of XKF and XKF might alleviate IR by promoting the activation of hepatic phosphatidylinositol 3-kinase (PI3K), phosphorylation of protein kinase B (AKT), and inhibiting the expression of glucose-6-phosphate phosphatase (G6PC) and phosphoenolpyruvate carboxykinase 1 (PCK1), the key limiting enzymes of hepatic gluconeogenesis. The above results suggest that berberine, astragaloside IV and chlorogenic acid can be used as the potential BECC of XKF to improve IR, and can regulate lipid metabolism, immuno-inflammation, and promote hepatic PI3K/AKT signaling to inhibit hepatic gluconeogenesis, regulate glucose homeostasis, and improve IR in mice.

With the rapid society development and broad recognition of "Healthy China", the demands for good life and health are increasing. Accordingly, the concept of "food and medicine homologous" have been attractive. The concept of "food and medicine homologous" has a long history in China, and is an essence of various ideas in traditional Chinese medicine, such as diet therapy, medicated diet, regimen and preventive treatment of disease, representing an important field in health science. Many studies have found that the active ingredients of "food and medicine homologous" substances are multiple types, multiple mechanisms and multiple targets, exerting their biological effects after oral administration and chemical or metabolic transformation. In this review, the chemical basis and biological principles of various "food and medicine homologous" substances were summarized as compounds, biological macromolecules and intestinal flora. By focusing on the intestinal flora, we discussed the detailed biological principles of several classic "food and medicine homologous" substances. The scientific significance of "food and medicine homologous" concept were also discussed. This review explores the concept of "food and medicine homologous" from the perspective of modern medicine, in order to provide insights for future drug development and human health.

ObjectiveGlutathione (γ-glutamyl-L-cysteinylglycine, GSH) is the most abundant non-protein compound containing sulfhydryl (―SH) groups in cells. It serves as a source of reducing equivalents, effectively neutralizing harmful reactive substances, and playing a crucial role in maintaining cellular redox balance. Therefore, sensitive detection and accurate measurement of GSH levels in tissues are of great importance. In this work, we presents a novel method for GSH detection utilizing electron paramagnetic resonance (EPR) spectroscopy. MethodsInitially, ABTS (2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate acid)) solution was mixed with K₂S₂O₈ solution and reacted in the dark for 12 to 16 h to prepare ABTS·⁺ solution, which was then quantified using UV-Vis spectroscopy. Subsequently, the concentration of glutathione (GSH) was determined based on the changes in the EPR signal of ABTS·⁺. On this basis, the optimal reaction time and temperature were explored to establish a standard equation correlating the EPR signal intensity of ABTS·⁺ with GSH concentration. Finally, the derived standard curve was employed to quantitatively analyze the GSH concentration in whole blood from C57BL/6J mice, and the results were compared with those reported in the literature to verify the accuracy of the method. ResultsThe experimental results demonstrate that this method has a linear detection range from50 nmol/L to 15 μmol/L for GSH, spanning two orders of magnitude, with a limit of detection (LOD) at0.50 nmol/L. The measured GSH content in mouse whole blood is (10 660±706) nmol/g Hb, which agrees with the value of (11 200±237) nmol/g Hb as previously reported. Furthermore, a similar method was developed for detection of glutathione disulfide (GSSG) at higher reaction temperature. ConclusionThis article presents a novel assay for the rapid detection of GSH using the intensity of EPR signal from ABTS·⁺ as indicator. This method demonstrates enhanced detection sensitivity and a broader linear range compared to conventional colorimetric methods. Furthermore, we have extended the application of this method to detect GSH content in blood samples efficiently and accurately, offering valuable information for assessing tissue redox balance, thus holding significant potentials.

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.

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.