OBJECTIVES: To evaluate the impact of HBV infection on pre- and postpartum health-related quality of life (HRQoL) in pregnant women. METHODS: A prospective matched cohort consisting of 70 HBV-infected and 70 healthy pregnant women was recruited from the Fifth Affiliated Hospital of Guangzhou Medical University between April 17 and September 25, 2023. HRQoL of the participants was assessed at 16-24 weeks of gestation, between 32 weeks and delivery, and 5-13 weeks postpartum. Mixed linear models were used for evaluating temporal trends of HRQoL changes, and univariate ANOVA with multiple linear regression was used to identify the predictors of HRQoL. RESULTS: Compared with healthy pregnant women, HBV-infected pregnant women had consistently lower total HRQoL scores across all the 3 intervals, with the lowest scores observed between 32 weeks of gestation and delivery, during which these women had significantly reduced mental component scores (74.27±13.43 vs 80.21±12.9, P=0.009) and postpartum mental (76.52±16.19 vs 85.02±6.51, P<0.001) and physical component scale scores (77.17±14.71 vs 83.09±10.1, P=0.009). HBV infection was identified as an independent risk factor affecting HRQoL during late pregnancy and postpartum periods. Additional independent risk factors for postpartum HRQoL reduction included self-pay medical expenses, spouse's neutral attitude toward the current pregnancy, and preexisting comorbidities (all P<0.05). CONCLUSIONS HRQoL of pregnant women deteriorates progressively in late pregnancy, and HBV infection exacerbates reductions of physical function and role emotion in late pregnancy and after delivery, suggesting the importance of targeted interventions for financial burdens, partner support and comorbid conditions to improve HRQoL of pregnant women with HBV infection.
Humans ; Female ; Pregnancy ; Quality of Life ; Prospective Studies ; Postpartum Period ; Hepatitis B, Chronic/psychology* ; Adult ; Pregnancy Trimester, Third ; Pregnancy Trimester, Second ; Pregnancy Complications, Infectious

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Objective:To apply the Timed Up and Go Test(TUGT)to investigate the correlation between motor function, emotional state, cognitive function, and sleep quality among elderly individuals in the Chinese community.Methods:A cross-sectional study was conducted, involving 739 subjects aged 60 to 90 years, who were randomly recruited from December 2021 to August 2023 across Beijing, Tianjin, Zhejiang, Guangdong, and Hainan Provinces in China.Basic demographic information was collected, and the TUGT was utilized to assess motor function.Based on the TUGT time(t), the subjects were divided into three groups: normal motor function group, mild motor abnormality group, and significant motor abnormality group.Cognitive function was evaluated using the Chinese Revised Mini-Mental State Examination(MMSE), while the Patient Health Questionnaire Depression Scale(PHQ-9)was employed to measure the degree of depression.Additionally, the Epworth Sleepiness Scale(ESS)was used to assess excessive daytime sleepiness.The correlation between subjects' motor function and their cognitive abilities, mood, and sleep was subsequently analyzed.Results:Systolic blood pressure, heart rate, PHQ-9, MMSE, and ESS scores were identified as significant factors influencing TUGT time.Specifically, TUGT time was positively correlated with PHQ-9 and ESS scores, while exhibiting negative correlations with systolic blood pressure, heart rate, and MMSE scores.Additionally, TUGT time was negatively correlated with the MMSE subcomponents of orientation, immediate memory, and verbal ability.All observed differences were statistically significant(all P<0.05).Logistic regression analysis indicated that an increase in the PHQ-9 score was associated with an odds ratio( OR)of 1.099(95% CI: 1.045-1.155, P<0.001)(mild motor abnormality group)and 1.150(95% CI: 1.066-1.242, P<0.001)(Significant motor abnormality group).Additionally, a reduction in the MMSE score was observed, with an OR of 0.939(95% CI: 0.886-0.995, P<0.001)(mild motor abnormality group)and 0.793(95% CI: 0.729-0.862, P<0.001)(Significant motor abnormality group).Furthermore, an increase in the ESS score was noted, with ORs of 1.139(95% CI: 1.094-1.186, P<0.001)(mild motor abnormality group)and 1.203(95% CI: 1.132-1.279, P<0.001)(Significant motor abnormality group).These findings suggest that these variables are independently related to decreased motor function. Conclusions:Depression, cognitive impairment, and excessive daytime sleepiness are independent risk factors for motor dysfunction among elderly individuals in community settings.The Timed Up and Go Test TUGT can be utilized for the early screening of motor function decline in this population.

Objective:To analyze the factors influencing postoperative complications and survival in patients undergoing hepatectomy for primary liver cancer (PLC).Methods:Two hundred and eighty-eight patients with PLC who underwent hepatectomy at Tianjin Medical University Cancer Hospital from April 2018 to December 2020 were prospectively enrolled, including 235 males and 53 females, aged (58.5±9.5) years. Nutritional evaluations included the nutritional risk screening 2002 (NRS-2002), patient-generated subjective global assessment (PG-SGA), and physical metrics such as body mass index, handgrip strength, arm circumference, mid-arm muscle circumference (MAMC), and triceps skinfold thickness (TSF). Based on the occurrence of postoperative complications during hospitalization including abdominal infection, bleeding, bile leakage, intra-abdominal fluid accumulation, pulmonary infection, intestinal fistula, and wound dehiscence, patients were divided into two groups: the complication group ( n=205) and the non-complication group ( n=83). Multivariate logistic regression analysis was performed to identify the factors related to postoperative complications, while Cox proportional hazards regression was used to evaluate the impact of various variables on postoperative survival. Survival analysis was conducted using the Kaplan-Meier method, and differences in survival rates were compared using the log-rank test. Results:Compared with the non-complication group, patients in the complication group had a significantly longer postoperative hospital stay [13(8, 16) d vs. 7(5, 9) d], higher proportions of low MAMC [34.1% (24/83) vs. 20.0% (41/205)], lower grip strength [28.9% (24/83) vs. 17.6% (36/205)], higher incidence of intraoperative blood loss ≥200 ml [44.6% (37/83) vs. 22.0% (45/205)], and greater proportion of resection involving ≥3 liver segments [45.8% (38/83) vs. 26.3% (54/205)] (all P<0.05). Multivariate logistic regression analysis identified the low MAMC ( OR=2.01, 95% CI: 1.09-3.71, P=0.025), intraoperative blood loss ≥200 ml ( OR=2.75, 95% CI: 1.55-4.90, P=0.001), and resection involving ≥3 liver segments ( OR=2.02, 95% CI: 1.15-3.55, P=0.015) as independent risk factors for postoperative complications in patients undergoing hepatectomy for PLC. Multivariate Cox regression analysis revealed that low TSF ( HR=1.94, 95% CI: 1.01-3.72, P=0.047), low handgrip strength ( HR=2.23, 95% CI: 1.29-3.88, P=0.004), and resection involving ≥3 liver segments ( HR=1.96, 95% CI: 1.15-3.36, P=0.014) were risk factors associated with poor survival after surgery. Conclusions:Low MAMC, intraoperative blood loss ≥200 ml, and resection involving ≥3 liver segments are risk factors for postoperative complications in patients undergoing hepatectomy for PLC, while low TSF, reduced handgrip strength, and resection involving ≥3 liver segments are predictors of poor postoperative survival.

Dysfunction of the diaphragm is a common problem in mechanically ventilated patients and is closely related to various adverse outcomes.This review summarizes the evaluation methods of diaphragm function,the association between diaphragm dysfunction and adverse clinical outcomes in critically ill mechanically ventilated patients,and the protective effect of diaphragm function on adverse outcomes related to mechanical ventilation.The aim is to provide references for medical staff to optimize evaluation techniques,develop personalized nursing plans,and improve patients' quality of life and health outcomes.

The Integration of Sports and Health forms an essential part of China's distinctive public health service system, and the prevention and treatment of chronic diseases and active health of the elderly group are important practice directions of physical and health integration.Research highlights that this approach effectively supports cardiovascular health, addresses musculoskeletal disorders, alleviates neurodegenerative conditions, and enhances mental well-being, thereby contributing positively to chronic disease prevention and management in the elderly population.Currently, community organizations and professional institutions are the primary providers of these services in China.Looking ahead, the development of elderly-oriented sports and health integration services in China should focus on ensuring institutional and policy support, promoting health-conscious ideologies, delivering high-quality services, and cultivating a skilled professional workforce, as well as establishing a standardized evaluation system.

Objective:To explore the gait and eye movement parameters in early Parkinson's disease(PD)with sleep disorders, and analyze their association with underlying pathophysiological mechanisms.Methods:This study was a cross-sectional single-center design that included 82 early PD patients with Hoehn-Yahr(H-Y)staging ≤2.5 who visited Beijing Hospital from October 2023 to May 2025.Patients were divided into two groups according to the PDSS-2 score(total score ≤15 for the no sleep disorder group and total score >15 for the sleep disorder group). Gait and eye movement parameters were collected respectively through the ReadyGo system and the EyeKnow eye movement system, and analyzed in combination with clinical scales.Multivariate logistic regression was employed to identify independent characteristic parameters associated with sleep disorders.Results:In terms of gait, the sleep disorder group had significantly lower step speed, left-right stride speed, and left-right swing speed(all P<0.05), and significantly higher variability of left-right stride time( P=0.017, 0.026). Regarding eye movements, the sleep disorder group had significantly more vertical smooth pursuit offsets[(56.24±2.87)times vs.(45.98±18.18)times, P=0.040], significantly higher maximum real-time variability of the right eye in response to light stimuli(90.75 vs.67.95%, P=0.006), and a longer latency to error responses in the counter-scanning task(337.06 vs.286.63 ms, P=0.005). To precisely control for confounding factors, key covariates such as mood and disease severity were included in the multivariate logistic regression model.After comprehensive adjustment, higher anxiety levels(Hamilton Anxiety Rating Scale, HAMA)( OR=1.32, P<0.001)and an increased number of vertical smooth pursuit offsets( OR=1.06, P=0.010)were independent factors associated with sleep disorders in early PD patients. Conclusions:In early PD patients, sleep disorders are closely associated with specific abnormalities in gait and eye movement parameters.In particular, vertical smooth pursuit offsets may serve as an objective biomarker independent of emotional status, reflecting the dysfunction of shared neural circuits.However, further mechanism studies are needed to verify whether they reflect the dysfunction of shared neural circuits.

Objective:To evaluate gait characteristics in early-stage Parkinson′s disease (PD) patients using an artificial intelligence-based quantitative motor function assessment system (Readygo) and validate whether PD patients with clinically normal gait actually exhibit objective gait impairments, and to explore the features and progression patterns of gait dysfunction in early PD.Methods:This cross-sectional, single-center study enrolled early-stage PD patients (Hoehn-Yahr stage≤2.5) from outpatient or inpatient departments of Beijing Hospital between October 2023 and October 2024, along with accompanying caregivers as healthy controls (HCs). Demographic data (sex, age, education level) were collected, and cognitive, psychological, and sleep-related scales assessments were administered. Based on the gait score (Item 3.10) from the Movement Disorder Society-Unified Parkinson′s Disease Rating Scale-Ⅲ (MDS-UPDRS-Ⅲ), PD patients were stratified into 3 subgroups: PD-normal gait (score=0), PD-mild gait impairment (score=1), and PD-moderate gait impairment (score=2). The Readygo system quantified gait parameters, including step width, stride length, step height, gait speed, stride velocity, swing velocity, and turn duration. Binary Logistic regression was uesd to identify biomarkers differentiating PD-normal gait group from HCs.Results:A total of 66 early-stage PD patients and 34 HCs were enrolled. Across the HCs, PD-normal gait, PD-mild gait impairment and PD-moderate gait impairment groups, there was a progressive decline in gait speed [1.07 (0.97, 1.15) m/s vs 0.97 (0.90, 1.06) m/s vs 0.90 (0.82, 1.00) m/s vs 0.77 (0.72, 0.86) m/s, H=29.949, P<0.001], bilateral stride velocity [left: 1.14 (1.07, 1.21) m/s vs 1.06 (0.94, 1.14) m/s vs 0.95 (0.88, 1.04) m/s vs 0.86 (0.76, 0.93) m/s, H=30.778, P<0.001; right: 1.12 (1.04, 1.22) m/s vs 1.04 (0.95, 1.13) m/s vs 0.96 (0.90, 1.04) m/s vs 0.89 (0.77, 0.90) m/s, H=29.561, P<0.001], and bilateral swing velocity [left: (2.56±0.28) m/s vs (2.38±0.32) m/s vs (2.19±0.33) m/s vs (1.96±0.32) m/s, F=14.132, P<0.001; right: 2.46 (2.35, 2.62) m/s vs 2.35 (2.13, 2.62) m/s vs 2.22 (2.05, 2.36) m/s vs 2.03 (1.71, 2.13) m/s, H=25.771, P<0.001], along with a progressive shortening of bilateral step length [left: 1.19 (1.14, 1.27) m vs 1.15 (1.04, 1.22) m vs 1.05 (0.93, 1.18) m vs 0.95 (0.80, 1.06) m, H=32.613, P<0.001; right: 1.20 (1.14, 1.30) m vs 1.13 (1.03, 1.22) m vs 1.07 (0.90, 1.17) m vs 0.97 (0.80, 1.03) m, H=30.528, P<0.001]. Conversely, turning time progressively lengthened [1.20 (1.09, 1.49) s vs 1.21 (1.10, 1.46) s vs 1.30 (1.19, 1.51) s vs 1.98 (1.53, 2.12) s, H=23.195, P<0.001]. Logistic regression identified that the right stride length was a discriminative factor between HCs and PD-normal gait group ( OR=0.023, 95% CI 0-0.291, P=0.012). Conclusions:As gait dysfunction worsens, PD patients demonstrate gradual reductions in speed-related parameters and stride length, with increasing turn duration.Early PD patients with clinically normal gait may already exhibit subtle impairments. Right stride length may serve as a potential biomarker to distinguish PD patients from HCs.

Objective:To construct an ultrasound-responsive nano-oxygen carrier，and to enhance cell survival within myocardial patches and promote myocardial infarction（MI）repair.Methods:Ultrasound-responsive phase-change nanobubbles（ND）were first prepared and integrated into GelMA hydrogel to construct myocardial patches. Low-intensity pulsed ultrasound（LIPUS）irradiation was applied to explore whether the nanobubbles could optimize the hydrogel properties. Hemoglobin（Hb）was further encapsulated into the nanobubbles to construct an oxygen carrier（ND-Hb）. In vitro and in vivo experiments were conducted to evaluate whether the optimized myocardial patches could improve cell survival and facilitate MI repair. In vitro，cell-loaded patches were divided into 6 groups（control，ND，Hb，LIPUS，LIPUS+ND，and LIPUS+oxygen carrier groups）to assess the cell viability and protein expression. In vivo，an acute MI model was established in SD rats，which were randomly assigned to 4 groups（control，Hb，LIPUS+ND，and LIPUS+oxygen carrier groups）.Myocardial patches were implanted，and cardiac function（echocardiography），cell survival（BLI imaging），angiogenesis（CD31 and α-SMA immunofluorescence）and connexin protein expression（Cx43）were evaluated. Results:Following the incorporation of ND and LIPUS irradiation，scanning electron microscopy revealed numerous micropores（about 2 μm）within the hydrogel were observed by scanning electron microscopy. The nano-oxygen carrier was successfully constructed，with a particle size of（301.2 ± 92.4）nm，and released oxygen under LIPUS stimulation. In vitro，at days 3，7，and 14，the cell survival rates in the LIPUS+oxygen carrier group［（89.6 ± 2.1）%，（79.3 ± 1.8）%，（70.9 ± Conclusions:This study successfully employs LIPUS combined with ND-Hb to enhance hydrogel properties，facilitating nutrient exchange within myocardial patches. Additionally，ultrasound-mediated oxygen release improves seed cell survival and promotes myocardial infarction repair.

Transformer models have emerged as pivotal tools within the realm of drug discovery,distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes.Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data,these models showcase remarkable efficacy across various tasks,including new drug design and drug target identification.The adaptability of pre-trained trans-former-based models renders them indispensable assets for driving data-centric advancements in drug discovery,chemistry,and biology,furnishing a robust framework that expedites innovation and dis-covery within these domains.Beyond their technical prowess,the success of transformer-based models in drug discovery,chemistry,and biology extends to their interdisciplinary potential,seamlessly combining biological,physical,chemical,and pharmacological insights to bridge gaps across diverse disciplines.This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields.In our review,we elucidate the myriad applications of transformers in drug discovery,as well as chemistry and biology,spanning from protein design and protein engineering,to molecular dynamics(MD),drug target iden-tification,transformer-enabled drug virtual screening(VS),drug lead optimization,drug addiction,small data set challenges,chemical and biological image analysis,chemical language understanding,and single cell data.Finally,we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.