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.

Obstructive sleep apnea (OSA) is an increasingly widespread sleep-breathing disordered disease, and is an independent risk factor for many high-risk chronic diseases such as hypertension, coronary heart disease, stroke, arrhythmias and diabetes, which is potentially fatal. The key to the prevention and treatment of OSA is early diagnosis and treatment, so the assessment and diagnostic technologies of OSA have become a research hotspot. This paper reviews the research progresses of severity assessment parameters and diagnostic technologies of OSA, and discusses their future development trends. In terms of severity assessment parameters of OSA, apnea hypopnea index (AHI), as the gold standard, together with the percentage of duration of apnea hypopnea (AH%), lowest oxygen saturation (LSpO₂), heart rate variability (HRV), oxygen desaturation index (ODI) and the emerging biomarkers, constitute a multi-dimensional evaluation system. Specifically, the AHI, which measures the frequency of sleep respiratory events per hour, does not fully reflect the patients’ overall sleep quality or the extent of their daytime functional impairments. To address this limitation, the AH%, which measures the proportion of the entire sleep cycle affected by apneas and hypopneas, deepens our understanding of the impact on sleep quality. The LSpO₂ plays a critical role in highlighting the potential severe hypoxic episodes during sleep, while the HRV offers a different perspective by analyzing the fluctuations in heart rate thereby revealing the activity of the autonomic nervous system. The ODI provides a direct and objective measure of patients’ nocturnal oxygenation stability by calculating the number of desaturation events per hour, and the biomarkers offers novel insights into the diagnosis and management of OSA, and fosters the development of more precise and tailored OSA therapeutic strategies. In terms of diagnostic techniques of OSA, the standardized questionnaire and Epworth sleepiness scale (ESS) is a simple and effective method for preliminary screening of OSA, and the polysomnography (PSG) which is based on recording multiple physiological signals stands for gold standard, but it has limitations of complex operations, high costs and inconvenience. As a convenient alternative, the home sleep apnea testing (HSAT) allows patients to monitor their sleep with simplified equipment in the comfort of their own homes, and the cardiopulmonary coupling (CPC) offers a minimal version that simply analyzes the electrocardiogram (ECG) signals. As an emerging diagnostic technology of OSA, machine learning (ML) and artificial intelligence (AI) adeptly pinpoint respiratory incidents and expose delicate physiological changes, thus casting new light on the diagnostic approach to OSA. In addition, imaging examination utilizes detailed visual representations of the airway’s structure and assists in recognizing structural abnormalities that may result in obstructed airways, while sound monitoring technology records and analyzes snoring and breathing sounds to detect the condition subtly, and thus further expands our medical diagnostic toolkit. As for the future development directions, it can be predicted that interdisciplinary integrated researches, the construction of personalized diagnosis and treatment models, and the popularization of high-tech in clinical applications will become the development trends in the field of OSA evaluation and diagnosis.

ObjectiveTo explore the effect of different drying conditions on the appearance and intrinsic quality indicators of Pinelliae Rhizoma for screening suitable drying conditions， so as to provide reference for its standardized production and quality evaluation. MethodsDifferent dried samples of Pinelliae Rhizoma were prepared by lime-assisted sweating method and intermittent drying method. Visual analysis was employed to measure the color brightness values（L^*） of the surface， cross-section and powder of the samples， texture analyzer was used to determine the hardness of the samples under different drying conditions. The total starch content was calculated by measuring the contents of amylose and amylopectin in the samples with ultraviolet-visible spectroscopy. High performance liquid chromatography（HPLC） was used to determine the contents of seven nucleoside components（uracil， hypoxanthine， uridine， inosine， guanosine， β-thymidine and adenosine） in the samples. Pearson correlation analysis was conducted to explore the correlation between the external characteristics and intrinsic indicators of the different dried samples. Principal component analysis（PCA） was used to comprehensively rank the data of various indicators， and partial least squares-discriminant analysis（PLS-DA） was used to screen differential components with variable importance in the projection（VIP） value>1. Furthermore， the difference between the optimal drying condition for Pinelliae Rhizoma and the traditional sun-drying method was explored by independent samples t-test. ResultsWith the increase of temperature， the color of the intermittently dried samples gradually deepened， while their hardness gradually decreased. Concurrently， the contents of extract， total starch， uridine and adenosine exhibited an upward trend， whereas the contents of uracil， hypoxanthine and inosine displayed a downward trajectory. Compared with the intermittent drying group， the content of extract in the samples subjected to lime-assisted sweating increased. With the increase of lime dose， the hardness and the total content of nucleoside components in the samples showed a downward trend， while the total starch content showed an upward trend. Correlation analysis showed that the comprehensive score of L^* was negatively correlated with the contents of uracil， hypoxanthine and inosine， and positively correlated with the contents of uridine， guanosine and adenosine. Hardness was negatively correlated with adenosine content， and positively correlated with the contents of inosine， uracil and hypoxanthine. Through comprehensive consideration and comprehensive score of principal components， the method of 5% lime-mixed sweating for 6 days emerged as the top-ranking approach. Except for the extract， the results of independent samples t-test showed that there was no significant difference between the 5% lime-mixed sweating for 6 days and the traditional sun-drying in terms of other content indicators. ConclusionThe whiteness and firmness of Pinelliae Rhizoma exhibit significant correlations with its chemical composition， while uridine， uracil， guanosine， adenosine and inosine are the key constituents responsible for the quality difference of Pinelliae Rhizoma under different drying conditions. The lime-assisted sweating method optimized in this study can be proposed as a viable alternative to the traditional sun-drying method. This method not only ensures the quality of the medicinal material but also effectively reduces the drying time and prevents mold contamination， which provides a valuable reference for the standardization of drying conditions and the establishment of quality evaluation criteria for Pinelliae Rhizoma.

Objective: To understand the incidence risk and risk factors of tuberculosis (TB) among middle school students in Chongqing, so as to provide a basis for formulating TB prevention and control strategies. Methods: From September to December 2022, 32 181 middle school students were selected as the study cohort from 15 administrative districts in Chongqing by using the stratified cluster random sampling method. All cohort members were screened with the tuberculin skin test (TST), and relevant information was collected from January 1, 2023 to December 31, 2024. On the basis of active screening, the follow up data of the participants were compared with the National Tuberculosis Management Information System to obtain the incidence status of the study subjects. The Log rank test was used to compare the TB incidence rates among students with different characteristics, and a Cox proportional hazards model was established to analyze the incidence risk and risk factors of TB. Results: The TST screening rate of the cohort members was 93.0%. During the 2 year follow up period, a total of 36 TB cases occurred, with a cumulative incidence rate of 111.87/100 000 and an incidence density of 55.95/100 000. Among them, the cumulative incidence rate of students from public schools (170.44/ 100 000 ) was higher than that of students from private schools (41.16/100 000), the cumulative incidence rate of students in schools located in high epidemic areas (153.95/100 000) was higher than that in medium epidemic areas (69.00/100 000), and the difference was statistically significant ( χ 2=11.49, 4.73, both P <0.05). The Log-rank test for different TST results showed that the difference in TB comulative incidence rate between students with strongly positive TST results (216.55/ 100 000 ) and those with negative TST results (81.40/100 000) was statistically significant ( χ 2=5.85, P <0.05). Univariate analysis using the Cox proportional hazards model revealed that the risk of TB was lower in students from private schools ( HR=0.25, 95% CI = 0.10-0.59) and students in medium epidemic areas ( HR=0.46, 95%CI =0.23-0.94); whereas the risk of TB was increased in students with strongly positive TST results ( HR=1.39, 95%CI =1.05-1.84) (all P <0.05). Multivariate Cox regression analysis showed that the risk of TB in students from private schools was lower than that of students from public schools ( HR=0.23, 95%CI=0.08-0.62, P <0.05). Conclusions The annual average incidence rate of TB among middle school students in Chongqing is at a relatively high level. It is necessary to strengthen the management and intervention for student groups, including those in public schools, those in schools located in high epidemic areas, and those with strongly positive TST results, so as to reduce the incidence rate of TB.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Humans ; Vascular Stiffness ; Coal Mining ; Occupational Diseases/epidemiology* ; Risk Factors ; Coal ; Miners

Pyroptosis is the programmed death of cells accompanied by an inflammatory response and is widely involved in the development of a variety of diseases, such as infectious diseases, cardiovascular diseases, and neurodegeneration. It has been shown that cellular scorching is involved in the pathogenesis of pulmonary arterial hypertension ( PAH) in cardiovascular diseases. Patients with PAH have perivascular inflammatory infiltrates in lungs, pulmonary vasculopathy exists in an extremely inflam-matory microenvironment, and pro-inflammatory factors in cellular scorching drive pulmonary vascular remodelling in PAH patients. This article reviews the role of cellular scorch in the pathogenesis of PAH and the related research on drugs for the treatment of PAH, with the aim of providing new ideas for clinical treatment of PAH.

Objective:To explore the application and key points of microchannel approaches in resec-tion of cervical intraspinal tumors.Methods:A retrospective analysis was performed on 51 cases of cervi-cal spinal canal tumors from February 2017 to March 2020.Among them,5 cases were located epidural space,6 cases were located epidural and subdural space,and 40 cases were located under the subdural extramedullary space(6 cases were located on the ventral side of the spinal cord).The maximum diameter ranged from 0.5 to 3.0 cm.The clinical manifestations included neck,shoulder or upper limb pain 43 cases,sensory disturbance(numbness)in 22 cases,and limb weakness in 8 cases.The micro-channel keyhole technique was used to expose the tumor,and the tumor was resected microscopically.Results:In this study,35 patients underwent hemilaminectomy,12 patients underwent interlaminar fenestration,2 patients underwent medial 1/4 facetectomy on the basis of hemilaminectomy or interlaminar fenestration.Two tumors were resected through anatomy space(no bone was resected).The degree of tumor resection included total resection in 50 cases and subtotal resection in 1 case.The type of the tumor included 36 schwannomas,12 meningiomas,2 enterogenic cysts and 1 dermoid cyst.There was no infec-tion and cerebrospinal fluid leakage postoperatively.Limb numbness occurred in 7 patients.The average follow-up time was 15 months(3 to 36 months).No deformity such as cervical instability or kyphosis was found.The tumor had no recurrence.Conclusion:The cervical spinal canal is relatively wide,cervical tumors with no more than three segments can be fully exposed by means of microchannel technology.Besides intramedullary or malignant tumors,they can be microsurgically removed.Preservation of the skeletal muscle structure of cervical spine is beneficial to recover the anatomy and function of cervical spine.The electrophysiological monitoring helps to avoid spinal cord or nerve root injury.

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.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive dysfunction and behavioral impairment, and there is a lack of effective drugs to treat AD clinically. Existing medications for the treatment of AD, such as Tacrine, Donepezil, Rivastigmine, and Aducanumab, only serve to delay symptoms and but not cure disease. To add insult to injury, these medications are associated with very serious adverse effects. Therefore, it is urgent to explore effective therapeutic drugs for AD. Recently, studies have shown that a variety of enzyme inhibitors, such as cholinesterase inhibitors, monoamine oxidase (MAO)inhibitors, secretase inhibitors, can ameliorate cholinergic system dysfunction, Aβ production and deposition, Tau protein hyperphosphorylation, oxidative stress damage, and the decline of synaptic plasticity, thereby improving AD symptoms and cognitive function. Some plant extracts from natural sources, such as Umbelliferone, Aaptamine, Medha Plus, have the ability to inhibit cholinesterase activity and act to improve learning and cognition. Isochromanone derivatives incorporating the donepezil pharmacophore bind to the catalytic active site (CAS) and peripheral anionic site (PAS) sites of acetylcholinesterase (AChE), which can inhibit AChE activity and ameliorate cholinergic system disorders. A compound called Rosmarinic acid which is found in the Lamiaceae can inhibit monoamine oxidase, increase monoamine levels in the brain, and reduce Aβ deposition. Compounds obtained by hybridization of coumarin derivatives and hydroxypyridinones can inhibit MAO-B activity and attenuate oxidative stress damage. Quinoline derivatives which inhibit the activation of AChE and MAO-B can reduce Aβ burden and promote learning and memory of mice. The compound derived from the combination of propargyl and tacrine retains the inhibitory capacity of tacrine towards cholinesterase, and also inhibits the activity of MAO by binding to the FAD cofactor of monoamine oxidase. A series of hybrids, obtained by an amide linker of chromone in combine with the benzylpiperidine moieties of donepezil, have a favorable safety profile of both cholinesterase and monoamine oxidase inhibitory activity. Single domain antibodies (such as AAV-VHH) targeted the inhibition of BACE1 can reduce Aβ production and deposition as well as the levels of inflammatory cells, which ultimately improve synaptic plasticity. 3-O-trans-p-coumaroyl maslinic acid from the extract of Ligustrum lucidum can specifically inhibit the activity of γ-secretase, thereby rescuing the long-term potentiation and enhancing synaptic plasticity in APP/PS1 mice. Inhibiting γ-secretase activity which leads to the decline of inflammatory factors (such as IFN-γ, IL-8) not only directly improves the pathology of AD, but also reduces Aβ production. Melatonin reduces the transcriptional expression of GSK-3β mRNA, thereby decreasing the levels of GSK-3β and reducing the phosphorylation induced by GSK-3β. Hydrogen sulfide can inhibitGSK-3β activity via sulfhydration of the Cys218 site of GSK-3β, resulting in the suppression of Tau protein hyperphosphorylation, which ameliorate the motor deficits and cognitive impairment in mice with AD. This article reviews enzyme inhibitors and conformational optimization of enzyme inhibitors targeting the regulation of cholinesterase, monoamine oxidase, secretase, and GSK-3β. We are hoping to provide a comprehensive overview of drug development in the enzyme inhibitors, which may be useful in treating AD.