Background Gestational weight gain is closely related to maternal and infant health outcomes. Pregnant women are simultaneously exposed to four metals—lithium (Li), vanadium (V), uranium (U), and bismuth (Bi)—through inhalation of fine particulate matter and consumption of contaminated food and water. Existing studies suggest that exposure to these metals may be associated with gestational weight gain. However, no study has yet explored the complex relationships between exposure to mixtures of these four metals and weight gain at different stages of pregnancy. Objective To investigate the associations between mixed exposure to Li, V, U, and Bi in early pregnancy and the average weekly gestational weight gain during both early pregnancy and mid-to-late pregnancy. Methods This prospective study recruited eligible women in early pregnancy from an obstetrics clinic of a tertiary hospital in Jinan, China, between September 2021 and July 2023. Pre-pregnancy weight, current weight (at 11⁺⁰ to 13⁺⁶ weeks of gestation), and spot urine samples (≥5.0 mL) were collected at enrollment. Urinary concentrations of Li, V, Bi, and U were determined using inductively coupled plasma mass spectrometry. Participants were followed up in late pregnancy (≥28 weeks of gestation) to collect information on physical activity via questionnaire; weight measurements at the last antenatal visit (35⁺⁰ to 37⁺⁶ weeks of gestation) were obtained from the hospital information system. After adjusting for covariates, multiple linear regression and generalized additive models were used to assess the associations of individual metals with weekly weight gain in early pregnancy and in mid-to-late pregnancy. Bayesian kernel machine regression (BKMR) and quantile-based g-computation (Qgcomp) were applied to evaluate the joint effects of the metal mixture exposure on weekly weight gain at the two gestational stages. Results A total of 313 pregnant women were included. The geometric means of urinary Li, V, U, and Bi concentrations were 37.07, 0.20, 0.06, and 0.04 μg·L⁻¹, respectively; after creatinine adjustment, the corresponding values were 46.82, 0.25, 0.07, and 0.05 μg·g⁻¹ (Cr). The mean weekly gestational weight gain was (0.19±0.25) kg in early pregnancy and (0.53 ± 0.18) kg in mid-to-late pregnancy. Both multiple linear regression and generalized additive models showed that urinary V concentration was positively associated with average weekly gestational weight gain in early pregnancy, while no significant associations were found for other metals or for gestational weight gain in mid-to-late pregnancy. In the BKMR model with early-pregnancy weight gain as the outcome, V had the strongest association [posterior inclusion probability (PIP)=0.773]. When other metals were fixed at their medians, V showed a positive non-linear association with the outcome. A significant single-metal effect of V and its interaction with Li were observed. Compared with the 50th percentile of the metal mixture, the average weekly weight gain in early pregnancy increased by 0.016 (95%CI: 0.003, 0.029) and 0.018 (95%CI: 0.001, 0.036) at the 60th and 65th percentiles, respectively; conversely, at the 25th percentile, it decreased by 0.026 (95%CI: 0.002, 0.050). Overall, the joint effect of the metal mixture on early- pregnancy weight gain showed an upward trend. In the BKMR model for mid-to-late pregnancy gestational weight gain, all PIPs were<0.5, and no significant single-metal effects, interactions, or joint effects were identified. Qgcomp results confirmed a positive association between the metal mixture and early-pregnancy weight gain (b=0.031, 95%CI: 0.010, 0.051; P<0.01), with V contributing the highest positive weight (0.71). No significant association was found for weight gain in mid-to-late pregnancy (b=0.007, P=0.339). Conclusion Higher levels of co-exposure to the Li, V, Bi, and U metal mixture during early pregnancy may be associated with increased average weekly weight gain in early pregnancy. Among these metals, V exhibits a predominant role and appears to interact with Li. No association is observed between early-pregnancy metal mixture exposure and average weekly gestational weight gain in mid-to-late pregnancy. These findings suggest that monitoring and managing metal exposure during early pregnancy may be crucial for the rational regulation of gestational weight gain.

OBJECTIVE: To investigate the therapeutic effect of Xiangshao Granules (XSG) on post-stroke depression (PSD) and explore the underlying mechanisms. METHODS: Forty-three C57BL/6J mice were divided into 3 groups: sham (n=15), PSD+vehicle (n=14), and PSD+XSG (n=14) groups according to a random number table. The PSD models were constructed using chronic unpredictable mild stress (CUMS) after middle cerebral artery occlusion (MCAO). The sham group only experienced the same surgical operation, but without MACO and CUMS stimulation. The XSG group received XSG (60 mg/kg per day) by gavage for 4 weeks. The mice in the sham and vehicle groups were given the same volume of 0.9% saline at the same time. The body weight and behavior tests including open field test, sucrose preference test, tail suspension test, and elevated plus-maze test, were used to validate the PSD mouse model. Real-time fluorescence quantitative polymerase chain reaction (RT-qPCR), enzyme-linked immunosorbent assay (ELISA), and immunofluorescence staining were used to evaluate the anti-inflammatory effects of XSG. The potential molecular mechanisms were explored and verified through network pharmacology analysis, Nissl staining, Western blot, ELISA, and RT-qPCR, respectively. RESULTS: The body weight and behavior tests showed that MCAO combined with CUMS successfully established the PSD models. XSG alleviated neuronal damage, reduced the expressions of pro-apoptotic proteins Caspase-3 and B-cell lymphoma-2 (BCL-2)-associated X (BAX), and increased the expression of anti-apoptotic protein BCL-2 in PSD mice (P<0.05 or P<0.01). XSG inhibited microglial activation and the expressions of pro-inflammatory cytokines including tumor necrosis factor-α, interleukin (IL)-1 β, and IL-6 via the toll-like receptor 4/nuclear factor kappa-B signaling pathway in PSD mice (P<0.05 or P<0.01). Furthermore, XSG decreased the expression of indoleamine 2,3-dioxygenase1 (IDO1) and increased the concentration of 5-hydroxytryptamine in PSD mice (P<0.05 or P<0.01). CONCLUSION XSG could reverse the anxiety/depressionlike behaviors and reduce the neuronal injury in the hippocampus and prefrontal cortex of PSD mice, which may be a potential therapeutic agent for PSD.
Animals ; Indoleamine-Pyrrole 2,3,-Dioxygenase/metabolism* ; Depression/etiology* ; Drugs, Chinese Herbal/therapeutic use* ; Hippocampus/metabolism* ; Male ; Mice, Inbred C57BL ; Prefrontal Cortex/pathology* ; Microglia/metabolism* ; Stroke/drug therapy* ; Disease Models, Animal ; Mice ; Behavior, Animal/drug effects*

Transarterial radioembolization (TARE) is a widely utilized therapeutic approach for hepatocellular carcinoma (HCC), however, the clinical implementation is constrained by the stringent preparation conditions of radioembolization agents. Herein, we incorporated the superstable homogeneous iodinated formulation technology (SHIFT), simultaneously utilizing an enhanced solvent form in a carbon dioxide supercritical fluid environment, to encapsulate radionuclides (such as ¹³¹I,¹⁷⁷Lu, or ¹⁸F) with lipiodol for the preparation of radiolipiodol. The resulting radiolipiodol exhibited exceptional stability and ultra-high labeling efficiency (≥99%) and displayed notable intratumoral radionuclide retention and in vivo stability more than 2 weeks following locoregional injection in subcutaneous tumors in mice and orthotopic liver tumors in rats and rabbits. Given these encouraging findings, ¹⁸F was authorized as a radiotracer in radiolipiodol for clinical trials in HCC patients, and showed a favorable tumor accumulation, with a tumor-to-liver uptake ratio of ≥50 and minimal radionuclide leakage, confirming the feasibility of SHIFT for TARE applications. In the context of transforming from preclinical to clinical screening, the preparation of radiolipiodol by SHIFT represents an innovative physical strategy for radionuclide encapsulation. Hence, this work offers a reliable and efficient approach for TARE in HCC, showing considerable promise for clinical application (ChiCTR2400087731).

Alzheimer's disease (AD) is characterized by cognitive and functional deterioration, with pathological features such as amyloid-beta (Aβ) aggregates in the extracellular spaces of parenchymal neurons and intracellular neurofibrillary tangles formed by the hyperphosphorylation of tau protein. Despite a thorough investigation, current treatments targeting the reduction of Aβ production, promotion of its clearance, and inhibition of tau protein phosphorylation and aggregation have not met clinical expectations, posing a substantial obstacle in the development of drugs for AD. Recently, artificial intelligence (AI), computational biology (CB), and systems biology (SB) have emerged as promising methodologies in AD research. Their capacity to analyze extensive and varied datasets facilitates the identification of intricate patterns, thereby enriching our comprehension of AD pathology. This paper provides a comprehensive examination of the utilization of AI, CB, and SB in the diagnosis of AD, including the use of imaging omics for early detection, drug discovery methods such as lecanemab, and complementary therapies like phototherapy. This review offers novel perspectives and potential avenues for further research in the realm of translational AD studies.

Direct electrical stimulation of the human cortex can produce subjective visual sensations, yet these sensations are unstable. The underlying mechanisms may stem from differences in electrophysiological activity within the distributed network outside the stimulated site. To address this problem, we recruited 69 patients who experienced visual sensations during invasive electrical stimulation while intracranial electroencephalography (iEEG) data were recorded. We found significantly flattened power spectral slopes in distributed regions involving different brain networks and decreased integrated information during elicited visual sensations compared with the non-sensation condition. Further analysis based on minimum information partitions revealed that the reconfigured network interactions primarily involved the inferior frontal cortex, posterior superior temporal sulcus, and temporoparietal junction. The flattened power spectral slope in the inferior frontal gyrus was also correlated with integrated information. Taken together, this study indicates that the altered electrophysiological signatures provide insights into the neural mechanisms underlying subjective visual sensations.
Humans ; Male ; Female ; Adult ; Visual Perception/physiology* ; Electric Stimulation ; Middle Aged ; Young Adult ; Electrocorticography ; Electroencephalography ; Brain Mapping

OBJECTIVE: To investigate the association of various polycyclic aromatic hydrocarbon (PAH) metabolites with diverse subtypes of cardiovascular disease (CVD) risk. METHODS: A novel predicting risk of cardiovascular disease EVENTs PREVENT equation was used to estimate the 10-year diverse subtypes of CVD risk, and their associations with PAH metabolites were analyzed using multiple logistic regression models, the weighted quantile sum (WQS) model, the quantile g-computation (qgcomp) model, and a stratified analysis of subgroups. RESULTS: For this study, six thousand seven hundred and forty-five participants were selected, and significant positive associations were observed between PAHs, naphthalene (NAP), and fluorene (FLU), and the risks of total CVD, atherosclerotic cardiovascular disease (ASCVD), and heart failure (HF). NAP and FLU were the primary contributors to the effects of PAH mixtures, and their associations with total CVD, ASCVD, and HF risk were significant in younger participants (30 ≤ age < 50 years); however, the associations of phenanthrene (PHEN) with ASCVD, HF, coronary heart disease (CHD), and stroke were dominant in aging participants (age ≥ 50 years). Notably, pyrene (PYR) was negatively associated with the risk of ASCVD, HF, CHD, and stroke. Similarly, negative associations of PYR with the four CVD subtypes were noticeable in aging participants. CONCLUSION Different PAHs metabolites had different impacts on each CVD subtype among different age groups. Notably, the protective effects of PYR on ASCVD, HF, CHD, and stroke were noticeable in aging individuals.
Humans ; Cardiovascular Diseases/chemically induced* ; Middle Aged ; Polycyclic Aromatic Hydrocarbons/metabolism* ; Male ; Female ; Adult ; Aged ; Risk Factors ; China/epidemiology*

Objective : To investigate the distribution of solute carrier organic anion transporter family member 1B1(SLCO1B1) and apolipoprotein E(ApoE) gene polymorphisms in the patients of Han ethnic group with cardiovascular and cerebrovascular diseases from Anhui Province, in order to provide the basis for the individualized therapy of statins in clinical practice. Methods: 924 Han patients with cardiovascular and cerebrovascular diseases were selected. The SLCO1B1 and ApoE genotypes of the patients were detected by polymerase chain reaction-fluorescent probe method, and their distribution was compared among different genders and other regions in China. Results: Seven SLCO1B1 gene subtypes were detected in 924 patients, including *1a/*1b(33.01%),*1b/*1b(41.45%), *1b/*15(12.34%), *1a/*1a(7.03%), *1a/*15(5.52%), *15/*15(0.54%) and *5/*5(0.11%), without detection of the two gene subtypes of *1a/*5 and *5/*15; the normal metabolic genotype I of SLCO1B1(*1a/*1a, *1a/*1b, *1b/*1b) accounted for the highest proportion in this population(81.49%), the intermediate metabolic genotype II and the weak metabolic genotype III of SLCO1B1 accounted for 17.86% and 0.65% respectively; six ApoE gene subtypes were detected, including E3/E3(66.78%), E3/E4(19.37%), E2/E3(9.63%), E4/E4(1.84%), E2/E4(1.73%) and E2/E2(0.65%); the E3 mass genotype(E2/E4, E3/E3) accounted for the highest proportion in this population(68.51%); there was no significant difference in the distribution of SLCO1B1 and ApoE genes between different genders; there was no significant difference in the distribution of SLCO1B1 between the Han population from Anhui and the South China and Central China, but a significant difference was found between the Anhui Han population and the Southwest China(P<0.05); the distribution of ApoE in the Anhui Han population demonstrated no statistically significant variation from those in South China and Southwest China, whereas significant differences were observed in comparison with Central China(P<0.05). Conclusion In the Han population with cardiovascular and cerebrovascular diseases in Anhui, the distributions of SLCO1B1 and ApoE gene polymorphisms show no significant gender differences but exhibit regional variations. These populations are predominantly characterized by class I normal metabolic genotype(SLCO1B1) and E3 mass genotypes(ApoE), indicating a higher tolerance to statin dosages and normal therapeutic efficacy in this cohort.

Objective: To conduct a scoping review on the types, construction methods and predictive performance of health literacy prediction models based on machine learning methods, so as to provide the reference for the improvement and application of such models. Methods: Publications on health literacy prediction models conducted using machine learning methods were retrieved from CNKI, Wanfang Data, VIP, PubMed and Web of Science from inception to May 1, 2024. The quality of literature was assessed using the Prediction Model Risk of Bias ASsessment Tool. Basic characteristics, modeling methods, data sources, missing value handling, predictors and predictive performance were reviewed. Results: A total of 524 publications were retrieved, and 22 publications between 2007 and 2024 were finally enrolled. Totally 48 health literacy prediction models were involved, and 25 had a high risk of bias (52.08%), with major issues focusing on missing value handling, predictor selection and model evaluation methods. Modeling methods included regression models, tree-based machine learning methods, support vector machines and neural network models. Predictors primarily encompassed factors at four aspects: individual, interpersonal, organizational and society/policy aspects, with age, educational level, economic status, health status and internet use appearing frequently. Internal validation was conducted in 14 publications, and external validation was conducted in 4 publications. Forty-two models reported the areas under the receiver operating characteristic curve, which ranged from 0.52 to 0.983, indicating good discrimination. Conclusion Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.

Objective To explore the facilitators and barriers of palliative care volunteering,and to provide references for further advancement of palliative care volunteering.Methods Purposeful sampling was used to select 12 volunteers from a palliative care ward in Hangzhou,Zhejiang Province,between April and September 2024.Semi-structured interviews were conducted,and directed content analysis was applied to organize and analyze the data,followed by theme analysis.Results Facilitators and barriers for volunteers' participation in palliative care volunteering were extracted.The 5 sub-themes of facilitators include motivating factors and perceived benefits,support and collaboration among volunteers,professional training and healthcare recognition,increased social awareness and public acceptance,and government support and institutional safeguards.The 5 sub-themes of barriers include limitations in individual capacity,challenges in collaboration with patients,families and healthcare workers,inadequate management and service mechanisms,uneven development of palliative care and insufficient public attention to psychological problems,and inadequate relevant laws and incentives.Conclusion There are more factors affecting the development of palliative care volunteering,and healthcare professionals should adopt targeted strategies to promote the active participation of volunteers in order to promote the sustainable development of palliative care volunteering.

ObjectiveThe U6 promoter is an essential element for driving sgRNA expression in the clustered regularly interspaced short palindromic repeat sequences/CRISPR-associated protein 9（CRISPR/Cas9）gene editing system in dicotyledonous plants. Endogenous U6 promoters typically exhibit higher transcriptional activity， which can significantly improve gene editing efficiency. This study aims to identify endogenous U6 promoters in Artemisia annua to optimize its CRISPR/Cas9 gene editing system， which holds significant importance for its molecular breeding. MethodsOn the basis of the highly conserved U6 snRNA sequences in Arabidopsis thaliana， endogenous U6 promoters were screened in the A. annua genome. Expression vectors were constructed with candidate AaU6 promoter driving the firefly luciferase （LUC） reporter gene， and then transiently transformed into Nicotiana benthamiana. Transcriptional activities of the promoters were measured and compared by in vivo imaging and the Dual Luciferase Reporter assay. ResultsEight endogenous U6 promoters were successfully cloned from A. annua. Sequences alignment revealed that all these promoters contained the two conserved cis-acting elements， upstream sequence element （USE） and TATA-box， which affected their transcriptional activity. Dual-luciferase activity assays indicated that the transcriptional activities of AaU6-3， AaU6-1， and AaU6-5 were significantly higher than that of the Arabidopsis AtU6-26 promoter， with AaU6-3 exhibiting the highest activity. ConclusionThis study identified three endogenous AaU6 promoters with high transcriptional activity in A. annua， providing key functional elements for establishing an efficient gene editing system in A. annua. These findings will contribute to advancing precision molecular breeding and high-quality germplasm innovation in A. annua.