With the rapid advancement of hemodynamic indices and monitoring technologies, their classification methods and application processes have become increasingly complex. Currently, no unified standard hasbeen established, making it difficult to fully meet the clinical requirements for hemodynamic management. To assist in hemodynamic monitoring assessment and therapeutic decision-making in critically ill patients, the Critical Hemodynamic Therapy Collaborative Group, in conjunction with the Critical Ultrasound Study Group, has jointly developed the Standard for the Application of Hemodynamic Monitoring Techniques in Critical Care. The first part of this standard systematically categorizes hemodynamic indicators into flow indicators, pressure and its derivative indicators, and tissue perfusion indicators, while elaborating on the clinical application of each. The second part establishes a standardized clinical implementation pathway for hemodynamic monitoring. It proposes a tiered monitoring strategy-comprising basic, advanced, indication-specific, and special scenario monitoring-tailored to different clinical settings. It emphasizes the central role of critical care ultrasound across all levels of monitoring and establishes hemodynamic assessment standards for organs such as the brain, kidneys, and gastrointestinal tract. This standard aims to provide a unified framework for clinical practice, teaching, training, and research in critical care medicine, thereby promoting standardized development within the discipline.

ObjectiveTo investigate the possible mechanism by which Zhiqiao Gancao Decoction （枳壳甘草汤， ZGD） delays intervertebral disc degeneration （IDD） based on the Hippo-yes-associated protein （YAP）/transcriptional co-activator with PDZ-binding motif （TAZ） signaling pathway. MethodsA total of 50 SD rats were randomly divided into sham surgery group， model group， low-dose ZGD group， high-dose ZGD group， and high-dose ZGD + inhibitor group， with 10 rats in each group. In the sham surgery group， the rats were pierced in the skin and muscle at the Co6/7/8 segments of the tail with a 21G needle （depth approximately 2 mm） without damaging the intervertebral disc. In the other groups， rats were injected with a 21G needle at the Co6/7/8 segments of the tail to establish an IDD model by piercing the tail intervertebral disc 5 mm. One week after modeling， rats in the low-dose and high-dose ZGD groups were given 6.24 and 12.24 g/（kg·d） of the decoction via gastric gavage， respectively. The high-dose ZGD + inhibitor group was given 12.24 g/（kg·d） of the decoction and an intraperitoneal injection of YAP/TAZ inhibitor Verteporfin 10 mg/kg. The sham surgery and model groups were given 5 ml/（kg·d） of normal saline via gavage. The gavage was given once a day， and the intraperitoneal injection was given every other day. After 4 weeks of continuous intervention， the pathological changes of the tail intervertebral discs were observed using HE staining， Oil Red O-Green staining， and Toluidine Blue staining. Immunohistochemistry was used to detect the expression of aggrecan and MMP3 in the nucleus pulposus. TUNEL fluorescence staining was performed to detect apoptosis in the nucleus pulposus， and the apoptosis rate was calculated. Western blot was used to detect the Hippo-YAP/TAZ signaling pathway， including YAP， phosphorylated YAP （p-YAP）， phosphorylated MST1/2 （p-MST1/2）， phosphorylated TAZ （p-TAZ） and apoptosis-related proteins， such as Cleaved Caspase 3， P53， Bcl-2 and Bax. ResultsCompared with sham surgery group， the rats in the model group showed significant degenerative changes in the intervertebral disc. The levels of aggrecan， Bcl-2， and YAP proteins in the nucleus pulposus decreased， while the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and the apoptosis rate increased （P < 0.01）. Compared with the model group， the drug intervention groups showed partial recovery in intervertebral disc degeneration. The levels of aggrecan， Bcl-2， and YAP proteins increased， while the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and the apoptosis rate decreased （P＜0.05 or P＜0.01）. The high-dose ZGD group showed more significant recovery in intervertebral disc degeneration compared to the low-dose ZGD group， with a decrease in the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and apoptosis rate， and an increase in the levels of aggrecan， Bcl-2， and YAP proteins （P＜0.05 or P＜0.01）. Compared with the high-dose ZGD group， the high-dose ZGD + inhibitor group showed a reduced recovery in intervertebral disc degeneration， with an increase in the levels of p-MST1/2， p-YAP， p-TAZ， P53， Bax， Cleaved Caspase 3， MMP3 proteins， and apoptosis rate， and a decrease in the levels of aggrecan， Bcl-2， and YAP proteins （P＜0.05 or P＜0.01）. ConclusionZGD may delay intervertebral disc degeneration by inhibiting the phosphorylation of YAP in the nucleus pulposus， maintaining the function of the Hippo-YAP/TAZ signaling pathway， and reducing apoptosis of nucleus pulposus cells.

OBJECTIVE To explore the effect and mechanism of Zhiqiao gancao decoction （ZQGCD） on pathological angiogenesis of degenerative intervertebral disc. METHODS The rats were randomly divided into sham operation group （normal saline）， model group （normal saline）， hypoxia inducible factor-1α （HIF-1α） inhibitor （YC-1） group [2 mg/（kg·d）， tail vein injection]， and ZQGCD low-dose， medium-dose and high-dose groups [3.06， 6.12， 12.24 g/（kg·d）]， with 8 rats in each group. Except for sham operation group， lumbar disc degeneration model of rat was constructed in all other groups. After modeling， they were given relevant medicine once a day， for consecutive 3 weeks. After the last medication， pathological changes and angiogenesis of the intervertebral disc tissue in rats were observed； the levels of inflammatory factors [interleukin-1β （IL-1β）， IL-6， tumor necrosis factor-α （TNF-α）] and the expressions of angiogenesis-related proteins [HIF-1α， vascular endothelial growth factor （VEGF）， VEGF receptor 2 （VEGFR2）， angiotensin 1（Ang 1）， Ang 2] in the com intervertebral disc tissue in rats were all determined. In cell experiment， the primary nucleus pulposus cells were isolated and cultured from rats， and cellular degeneration was induced using 50 ng/mL TNF-α. The cells were divided into blank control group （10% blank control serum）， TNF-α group （10% blank control serum）， YC-1 group （10% blank control serum+0.2 mmol/L YC-1）， and 5%， 10%， 15% drug-containing serum group （5%， 10%， 15% drug-containing serum）. After 24 hours of intervention， the nucleus pulposus cells were co-cultured with HUVEC. The expressions of Collagen Ⅱ， matrix metalloproteinase-3 （MMP-3） in nucleus pulposus cells were detected. HUVEC proliferation， migration and tube forming ability were detected， and the expression levels of the HIF-1α/VEGF/Ang signal axis and angiogenesis- related proteins （add MMP-2， MMP-9） in HUVEC were detected. RESULTS Animal experiments had shown that compared with model group， the positive expression of CD31 in the intervertebral disc tissues of rats in each drug group was down-regulated （P＜ 0.05）， the levels of inflammatory factors and angiogenesis-related proteins were decreased significantly （P＜0.05）， and the pathological changes in the intervertebral disc were alleviated. Cell experiments had shown that compared with TNF-α group， the expression of Collagen Ⅱ in nucleus pulposus cells of all drug groups was significantly up-regulated （P＜0.05）， and the expression of MMP-3 was significantly down-regulated （P＜0.05）； the proliferation， migration and tubulogenesis of HUVEC were significantly weakened （P＜0.05）. The mRNA and protein expressions of HIF-1α， VEGF， Ang 2 as well as the expression of angiogenesis-related proteins （except for the expression of Ang 2 mRNA and HIF-1α， VEGFR2， Ang 2 protein in 5% drug- containing serum group） were significantly down-regulated （P＜0.05）. CONCLUSIONS ZQGCD may inhibit the HIF-1α/VEGF/ Ang signal axis to weaken the angiogenic ability of vascular endothelial cells， improve pathological angiogenesis in the intervertebral disc， and delay the degeneration of the intervertebral disc.

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.

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.

Learning-associated functional plasticity at hippocampal synapses remains largely unexplored. Here, in a single session of reward-based trace conditioning, we examine learning-induced synaptic plasticity in the dorsal CA1 hippocampus (dCA1). Local field-potential recording combined with selective optogenetic inhibition first revealed an increase of dCA1 synaptic responses to the conditioned stimulus (CS) induced during conditioning at both Schaffer collaterals to the stratum radiatum (Rad) and temporoammonic input to the lacunosum moleculare (LMol). At these dCA1 inputs, synaptic potentiation of CS-responding excitatory synapses was further demonstrated by locally blocking NMDA receptors during conditioning and whole-cell recording sensory-evoked synaptic responses in dCA1 neurons from naive animals. An overall similar time course of the induction of synaptic potentiation was found in the Rad and LMol by multiple-site recording; this emerged later and saturated earlier than conditioned behavioral responses. Our experiments demonstrate a cued memory-associated dCA1 synaptic plasticity induced at both Schaffer collaterals and temporoammonic pathways.
Animals ; CA1 Region, Hippocampal/physiology* ; Male ; Association Learning/physiology* ; Neuronal Plasticity/physiology* ; Cues ; Memory/physiology* ; Synapses/physiology* ; Conditioning, Classical/physiology* ; Excitatory Postsynaptic Potentials/physiology* ; Receptors, N-Methyl-D-Aspartate/antagonists & inhibitors* ; Rats ; Optogenetics

OBJECTIVE: This study reports the first imported case of Lassa fever (LF) in China. Laboratory detection and molecular epidemiological analysis of the Lassa virus (LASV) from this case offer valuable insights for the prevention and control of LF. METHODS: Samples of cerebrospinal fluid (CSF), blood, urine, saliva, and environmental materials were collected from the patient and their close contacts for LASV nucleotide detection. Whole-genome sequencing was performed on positive samples to analyze the genetic characteristics of the virus. RESULTS: LASV was detected in the patient's CSF, blood, and urine, while all samples from close contacts and the environment tested negative. The virus belongs to the lineage IV strain and shares the highest homology with strains from Sierra Leone. The variability in the glycoprotein complex (GPC) among different strains ranged from 3.9% to 15.1%, higher than previously reported for the seven known lineages. Amino acid mutation analysis revealed multiple mutations within the GPC immunogenic epitopes, increasing strain diversity and potentially impacting immune response. CONCLUSION The case was confirmed through nucleotide detection, with no evidence of secondary transmission or viral spread. The LASV strain identified belongs to lineage IV, with broader GPC variability than previously reported. Mutations in the immune-related sites of GPC may affect immune responses, necessitating heightened vigilance regarding the virus.
Humans ; China/epidemiology* ; Genome, Viral ; Lassa Fever/virology* ; Lassa virus/classification* ; Molecular Epidemiology ; Phylogeny

Objective To investigate the current status of sleep quality,depression,anxiety and stress of special service convalescents and their correlation.Methods A questionnaire survey was conducted on 311 special service convalescents by the Pittsburgh sleep quality index(PSQI)and the depression-anxiety-stress self-rating scale-21(DASS-21)from May to July 2022.Results The mean total PSQI score of 311 special service convalescents was 4.93±3.14,and 63 of them(20.26%)had sleep quality problems(total score of PSQI>7).The proportions of respondents with the scores≥2 in sleep time,daytime dysfunction,subjective sleep quality,and fall-asleep time were 30.87%,26.05%,21.22%,and 20.26%,respectively.The proportions of respondents with mild depression,anxiety and stress were 6.11%,4.50%and 2.57%,respectively,which were higher than the other three grades(moderate,severe and very serious).The incidence of sleep quality problems,depression,anxiety,and stress in respondents aged 40 years and above was higher than those in the other age groups,and there was a tendency to increase with age.The total score of PSQI and all factors(except hypnotic drugs)were positively correlated with depression,anxiety,and stress in special service convalescents(all P<0.01).Regression analysis showed that depression and stress were the direct influencing factors of sleep quality.Conclusion The special service convalescents have varying degrees of sleep quality problems and negative emotions such as depression,anxiety,and stress,especially those aged 40 years and above.Sleep quality is closely related to depression,anxiety,and stress.