ObjectiveTo study the chemical constituents of Painong powder and the constituents absorbed into blood after oral administration to rats by ultra performance liquid chromatography-quadrupole-electrostatic field orbitrap high-resolution mass spectrometry （UPLC-Q-Orbitrap-MS）. MethodsUPLC-Q-Orbitrap-MS was employed for mass spectrometry data acquisition. The chemical constituents of Painong Powder and the constituents absorbed into blood were characterized and identified via Xcalibur 4.2 and Compound Discoverer v3.3.1 （CD） based on retention time， accurate molecular weights， secondary fragmentation ions， and comparison with reference standards and literature reports. ResultsA total of 176 chemical compounds， including 56 flavonoids， 42 triterpenoid saponins， 23 monoterpenes， 7 coumarins， 5 tannins， and other 43 compounds were identified from Painong powder. 49 components were identified in the rat plasma after oral administration of Painong powder， including 33 prototype constituents and 16 metabolites. The major metabolic pathways included hydrolysis in phase Ⅰ metabolic reactions， as well as methylation， sulfation， and glucuronidation in phase Ⅱ metabolic reaction. ConclusionThe method comprehensively identified the chemical constituents of Painong powder both in vitro and in vivo， and may provide a reference for the study of quality control and clinical applications.

ObjectiveTo investigate the mechanism of salt processing of Psoraleae Fructus （PF） through modern analytical techniques and biotechnology， focusing on its effects related to hepatotoxicity and anti-osteoporosis activity. MethodsThe zebrafish model was utilized to evaluate the impact of PF and salt-processed Psoraleae Fructus （SPF） on the hepatotoxicity （using 134.17 ， 178.89， 268.34 mg·L^-1 as low， medium， and high dose groups of PF， 135.04， 180.06， 270.08 mg·L^-1 as low， medium， and high dose groups of SPF， respectively） and anti-osteoporotic activity （using 33.54 ， 67.08 and 134.17 mg·L^-1 as low， medium， and high dose groups of PF， 33.76， 67.52， 135.04 mg·L^-1 as low， medium， and high dose groups of SPF， respectively）， which was using alizarin red skull staining of zebrafish as an indicator of different batches of PF. The specific dosage of a batch of PF was taken as an example. Then ultra-performance liquid chromatography-quadrupole-time of flight-mass spectrometry（UPLC-Q-TOF-MS） analysis was employed to identify the chemical composition of PF before and after salt processing， and PCA， OPLS-DA， and independent sample t-test were used to elucidating the compositional changes associated with the effects of salt processing on hepatotoxicity and anti-osteoporosis activity. ResultsUnder specific conditions， PF induced notable hepatotoxicity in zebrafish while simultaneously demonstrating protective effect against prednisolone-induced osteoporosis. In comparison to PF， SPF showed alleviated hepatotoxicity while retaining significant anti-osteoporosis activity. UPLC-Q-TOF-MS analysis revealed that after salt processing， the overall chemical composition of PF showed a downward trend， with 69 components showing a decrease in content， represented by psoralen， and 13 components showing an increase， represented by 4′-O-methyl psoralen B. Further multivariate statistical analysis revealed 11 key differential components before and after salt processing of PF， including psoralen and bakuchiol. ConclusionSalt processing effectively diminishes hepatotoxicity without impairing therapeutic efficacy against osteoporosis of PF， which may be related to the compositional changes before and after salt processing of PF and provides key evidence to reveal the scientific significance of salt processing of PF.

Objective To explore the wearing status and actual noise reduction effect of hearing protectors among noise workers in a typical automobile manufacturing enterprise. Methods In April 2024, an occupational hazard factor testing was carried out in an automobile manufacturing industry, and at the same time, the hearing protection fit test was conducted for noise workers. Intervention and guidance were provided to those who did not pass the minimum standard of baseline PAR. The difference in PAR between baseline and post-intervention was compared, and the effectiveness of hearing protector wearing method training was evaluated. Results The exceeding rate of the company's noise operation post was 50.77% (66/130). The baseline PAR of the subjects with working experience of less than 15 years and wearing hearing protectors throughout noisy work was higher, and the differences were statistically significant (P<0.05). Compared with those with 80dB≤L_{EX, 8h}<85dB, more research subjects with L_{EX, 8h}≥85dB failed baseline PAR (39.13%). After intervention, the PAR of the subjects who did not pass the minimum standard of baseline PRA increased from 2.0 (0.0, 5.3) to 17.0 (14.8, 20.0), and the protection level was significantly improved, and the difference was statistically significant (P<0.01). Conclusion The individual fit test of hearing protector is an important means to evaluate the actual noise reduction level of hearing protector and guide the selection of hearing protection models. Corporate training can help improve the PAR of hearing protectors.

ObjectiveThe malaria parasites remodel the host erythrocyte structure by exporting parasite proteins that interact with the membrane skeleton proteins of red blood cells (RBCs), facilitating their intracellular survival and pathogenicity. Skeleton-binding protein 1 (SBP1) is a conserved exported protein across Plasmodium species. In Plasmodium falciparum, SBP1 has been reported to interact with erythrocyte membrane skeleton proteins 4.1R and spectrin, while its contribution to erythrocyte remodeling and parasite virulence in Plasmodium berghei (Pb) remains unclear. This study aims to determine whether PbSBP1 associates with the host cytoskeletal protein 4.1R and to investigate its role in the remodeling of host RBCs and the pathogenicity of Plasmodium berghei. MethodsIn Plasmodium berghei, the relationship between PbSBP1 and the erythrocyte cytoskeletal protein 4.1R was examined using co-immunoprecipitation. A Pbsbp1 gene knockout mutant of Plasmodium berghei (Pbsbp1∆) was generated based on the principle of double crossover homologous recombination. The deformability of erythrocytes infected with Pbsbp1∆ parasites was assessed using microfluidic methods. Microchannels with an array of cylindrical pillars were used to detect modifications in infected RBC deformability. The infected RBCs were squashed between the rows and recovered between the columns and the transit velocity (μm/s) of infected RBCs travelling through the microchannel was recorded. The component of the erythrocyte membrane skeleton junctional complex, tropomodulin (TMOD), was fluorescently labeled, and the cytoskeletal network of infected erythrocytes was imaged using super-resolution stochastic optical reconstruction microscopy (STORM) to analyze ultrastructural changes in the cytoskeleton of wild-type (WT) and Pbsbp1∆-infected erythrocytes. Actin-based junctional complexes were displayed as individual clusters by the labeled TMOD in the STORM images, and the cluster densities and distances between adjacent clusters of infected RBCs were calculated. Additionally, rodent malaria models (BALB/c mice) and experimental cerebral malaria models (C57BL/6 mice) were employed to monitor the growth of Pbsbp1∆ and WT parasites during the intraerythrocytic stage and their capacity to induce cerebral malaria in mice. ResultsPbSBP1 may participate in the remodeling of infected erythrocytes through direct or indirect interaction with the erythrocyte cytoskeletal protein 4.1R. Microfluidic assays revealed that the deformability of erythrocytes infected with Pbsbp1∆ parasites was significantly enhanced compared to those infected with WT parasites. STORM imaging further demonstrated that the ultrastructure of the erythrocyte cytoskeleton in Pbsbp1∆-infected cells was altered relative to that in WT-infected erythrocytes. The distances between nearest neighbors of clusters had a tendency to increase while the cluster densities were decreased in Pbsbp1∆-infected RBCs compared to WT-infected RBCs. Subsequent phenotypic analysis indicated that the growth rate of Pbsbp1∆ parasites during the intraerythrocytic stage was significantly slower than that of WT parasites, and their ability to induce cerebral malaria in mice was also attenuated. These findings suggest that PbSBP1 is involved in the remodeling of the erythrocyte membrane skeleton, likely through its direct or indirect interaction with protein 4.1R, thereby regulating the deformability of infected erythrocytes and influencing the pathogenicity of the blood-stage parasites. ConclusionThis study establishes a role for PbSBP1 in host erythrocyte remodeling and parasite virulence, providing new research strategies for the prevention and treatment of malaria.

Objective To establish an "human serum - porcine aortic endothelial cells (PAEC) - human platelets" in vitro model and explore the mechanism of xenotransplantation-related coagulation dysfunction mediated by immune complexes - platelet FcγRⅡa (CD32a) receptor. Methods Healthy human serum was co-incubated with PAEC to prepare the supernatant containing immune complexes, which was then used to stimulate healthy human platelets, or directly treated with the serum of xenogeneic liver transplant recipients. Flow cytometry was used to detect platelet activation markers CD62P and surface IgG binding levels, and the platelet adhesion function was evaluated by platelet-PAEC adhesion experiments. CD32a blocking antibody IV.3 and SYK blocker SKYIN 4 were used to clarify the signaling pathways. Results The supernatant from the co-incubation of healthy human serum and PAEC could significantly induce platelet activation and endothelial adhesion. The use of the serum from xenogeneic liver transplant recipients could also significantly induce platelet activation. Antibody IV.3 and SYK blocker SKYIN 4 could significantly inhibit these effects. Conclusions In xenotransplantation, the immune complexes formed by human serum antibodies and porcine endothelial antigens may induce abnormal platelet activation through the platelet CD32a receptor, which is an important mechanism of non-complement-dependent post-transplant coagulation dysfunction, providing a new target for the intervention of coagulation complications in xenotransplantation.

Objective To explore the clinical efficacy of robot-assisted coronary artery bypass grafting through a small incision in the left intercostal space in the treatment of multivessel coronary disease. Methods A retrospective analysis was conducted on the clinical data of patients who underwent coronary artery bypass grafting through a small incision in the left intercostal space at Central China Fuwai Hospital of Zhengzhou University from January 1, 2023 to October 15, 2024. Patients were divided into a robotic group and a minimally invasive group based on whether the surgery was assisted by the Da Vinci robot. Results A total of 81 patients were included, with 57 in the minimally invasive group, including 41 males and 16 females, with a median age of 65.0 (57.5, 69.5) years; and 24 in the robotic group, including 17 males and 7 females, with a median age of 61.0 (56.0, 69.0) years. There was no statistically significant difference in baseline data between the two groups (P>0.05). The robotic group had less intraoperative bleeding [300 (200, 438) mL vs. 500 (375, 600) mL, P=0.006], shorter postoperative mechanical ventilation time [15.0 (13.3, 23.5) h vs. 22.0 (15.5, 39.5) h, P=0.037], and lower incidence of postoperative pain [8 (33.3%) vs. 33 (57.9%), P=0.043]. The hospitalization cost in the robotic group was higher than that in the minimally invasive group [130491 (123298, 135691) yuan vs. 123892 (115543, 133449) yuan, P=0.023]. There was no statistical difference in postoperative laboratory indicators between the two groups (P>0.05). There was also no statistical difference in the duration of surgery, postoperative 24 h drainage volume, ICU stay time, postoperative hospital stay or incidences of perioperative compications including pleural effusion, transfusion, new-onset atrial fibrillation, acute kidney injury, non-union of incision, major cardiovascular and cerebrovascular adverse events, and reoperation between the two groups (P>0.05). Conclusion Compared with the minimally invasive group, the robotic group shows satisfactory efficacy and can effectively reduce postoperative pain and intraoperative bleeding, and shorten postoperative mechanical ventilation time.

Sleep is an instinctive behavior alternating awakening state, sleep entails many active processes occurring at the cellular, circuit and organismal levels. The function of sleep is to restore cellular energy, enhance immunity, promote growth and development, consolidate learning and memory to ensure normal life activities. However, with the increasing of social pressure involved in work and life, the incidence of sleep disorders (SD) is increasing year by year. In the short term, sleep disorders lead to impaired memory and attention; in the longer term, it produces neurological dysfunction or even death. There are many ways to directly or indirectly contribute to sleep disorder and keep the hormones, including pharmacological alternative treatments, light therapy and stimulus control therapy. Exercise is also an effective and healthy therapeutic strategy for improving sleep. The intensities, time periods, and different types of exercise have different health benefits for sleep, which can be found through indicators such as sleep quality, sleep efficiency and total sleep time. So it is more and more important to analyze the mechanism and find effective regulation targets during sleep disorder through exercise. Dopamine (DA) is an important neurotransmitter in the nervous system, which not only participates in action initiation, movement regulation and emotion regulation, but also plays a key role in the steady-state remodeling of sleep-awakening state transition. Appreciable evidence shows that sleep disorder on humans and rodents evokes anomalies in the dopaminergic signaling, which are also implicated in the development of psychiatric illnesses such as schizophrenia or substance abuse. Experiments have shown that DA in different neural pathways plays different regulatory roles in sleep behavior, we found that increasing evidence from rodent studies revealed a role for ventral tegmental area DA neurons in regulating sleep-wake patterns. DA signal transduction and neurotransmitter release patterns have complex interactions with behavioral regulation. In addition, experiments have shown that exercise causes changes in DA homeostasis in the brain, which may regulate sleep through different mechanisms, including cAMP response element binding protein signal transduction, changes in the circadian rhythm of biological clock genes, and interactions with endogenous substances such as adenosine, which affect neuronal structure and play a neuroprotective role. This review aims to introduce the regulatory effects of exercise on sleep disorder, especially the regulatory mechanism of DA in this process. The analysis of intracerebral DA signals also requires support from neurophysiological and chemical techniques. Our laboratory has established and developed an in vivo brain neurochemical analysis platform, which provides support for future research on the regulation of sleep-wake cycles by movement. We hope it can provide theoretical reference for the formulation of exercise prescription for clinical sleep disorder and give some advice to the combined intervention of drugs and exercise.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.