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 make clear exercise combined with Shenghui Tang interferes in acetylcholine receptor （M1AChR） to improve mitochondrial autophagy and enhance cognition of Alzheimer's disease （AD） model rats through the adenylate activated protein kinase （AMPK）/mammalian target of rapamycin （mTOR） signaling pathway. MethodsForty-eight male SD rats of SPF grade were randomly divided into a blank group， a model group， a Shenghui Tang group （9.3 g·kg^-1）， an exercise group， an exercise + Shenghui Tang group （9.3 g·kg^-1）， and a rapamycin group （1.5 mg·kg^-1）. Except for the blank group， the rat model of AD was constructed by injecting amyloid beta （Aβ_1-42） into hippocampus stereotaxically. The exercise group received treadmill exercise for 4 weeks， while the Shenghui Tang group received intragastric administration for 4 weeks， and the exercise + Shenghui Tang group received treadmill exercise and intragastric administration of Shenghui Tang for 4 weeks simultaneously. After the intervention， the Morris water maze test was used to detect the learning and memory ability. Spontaneous behavior was observed in the open field test. The pathological structure of hippocampal neurons was observed by NISSl staining. The expression level of M1AChR in hippocampus was detected by immunohistochemistry （IHC）. The autophagy ultrastructure of hippocampal neurons was observed by transmission electron microscopy. The apoptosis rate was evaluated by terminal deoxynucleotidyl transferase dUTP nick end labeling （TUNEL）. The expression of Beclin1 and microtubule-associated protein light chain 3β （LC3β） was detected by immunofluorescence （IF）. The protein expression of M1AChR， AMPK， p-AMPK， mTOR， Beclin1， LC3β， and chelate 1 （SQSTM1/p62） in hippocampus was detected by Western blot. ResultsCompared with the blank group， the model group exhibited significantly increased platform escape latency on the fifth day （P<0.01） and significantly decreased activity distance in the target quadrant and times of crossing the platform （P<0.01）. The total movement distance in the open field， the time of movement in the central area， and the average speed obviously decreased （P<0.05）. The arrangement of nerve cells in hippocampus CA1 region was dispersed， and the numbers of Nissl bodies and M1AChR positive cells significantly decreased （P<0.01）. The expression of TUNEL positive cells was significantly increased （P<0.01）. The typical autophagic lysosomal structure decreased. The protein expression of M1AChR， p-AMPK/AMPK， p-mTOR/mTOR， Beclin1， LC3Ⅱ/Ⅰ in hippocampus was significantly decreased （P<0.01）， and the protein expression of p62 was significantly increased （P<0.01）. Compared with the model group， the exercise + Shenghui Tang group exhibited obviously improved space exploration and positioning navigation ability （P<0.05， P<0.01）. The total movement distance in the open field， the time of movement in the central area， and the average speed of movement significantly increased （P<0.01）. The number of Nissl bodies significantly increased （P<0.01）. The number of M1AChR positive cells in hippocampus was significantly increased （P<0.01）. The expression of TUNEL positive cells was significantly decreased （P<0.01）. The protein expression of M1AChR， p-AMPK/AMPK， p-mTOR/mTOR， Beclin1， LC3Ⅱ/Ⅰ in hippocampus was significantly increased （P<0.01）， while the protein expression of p62 was significantly decreased （P<0.01）. Compared with the exercise + Shenghui Tang group， the Shenghui Tang group and the exercise group showed significantly increased platform escape latency on the fifth day （P<0.01） and obviously decreased activity distance in the target quadrant and times of crossing the platform （P<0.05， P<0.01）. The total movement distance in the open field， the time of movement in the central area， and the average speed of movement significantly decreased （P<0.01）. The number of Nissl bodies and the number of M1AChR positive cells significantly decreased （P<0.01）. The expression of TUNEL positive cells was obviously increased （P<0.05）. Ultrastructure of the hippocampal region showed decreased autophagy level. The protein expression of M1AChR， p-AMPK/AMPK， p-mTOR/mTOR， LC3Ⅱ/Ⅰ in the hippocampus was obviously decreased in the Shenghui Tang group （P<0.05， P<0.01）， while the protein expression of p62 was significantly increased （P<0.01）. In the exercise group， the protein expression of M1AChR， p-AMPK/AMPK， Beclin1， and LC3Ⅱ/Ⅰ was obviously decreased （P<0.05， P<0.01）， while the protein expression of p-mTOR/mTOR and p62 was significantly increased （P<0.01）. ConclusionExercise combined with traditional Chinese medicine can enhance the expression of M1AChR in the hippocampus of AD model rats， induce autophagy through the AMPK/mTOR signaling pathway， and improve the learning and memory ability of AD rats.

Objective: To investigate the association between sleep duration and depressive symptoms in children and adolescents, so as to provide scientific evidence for promoting mental health and preventing depression among relevant populations. Methods: A total of 2 192 children and adolescents aged 10-17 years with complete data from the 2018 China Family Panel Studies Database were included. Eight item Center for Epidemiologic Studies Depressive Scale(CES-D8) was used to assess participants depressive levels, and sleep duration was assessed via questionnaire. Multivariate Logistic regression model was used to analyze the association between different sleep duration categories and depressive symptom occurrence among children and adolescents. A restricted cubic spline(RCS) model analyzed the dose response relationship between sleep duration and the risk of depressive symptoms occurrence and segmented Logistic regression models to identify dose response effects. Results: Among the surveyed children and adolescents, 524(23.91%) exhibited depressive symptoms. Compared to those with sufficient sleep, children aged 10-12 years had a higher risk of depressive symptoms on average per day( OR =1.66, 95% CI =1.19-2.33) and during weekdays( OR =1.76, 95% CI =1.26-2.46), as well as in adolescents aged 13-17 years on a daily basis( OR =1.40，95% CI =1.06-1.85) and during weekdays( OR = 1.48，95% CI =1.12-1.95), and excessive sleep in adolescents on rest days was also significantly associated with higher risk of depressive symptoms( OR =1.65，95% CI =1.11-2.43)(all P <0.05). RCS analysis results indicate that children s sleep duration exhibits a linear negative correlation with the risk of depressive symptoms(all P nonlinear >0.05), while adolescents sleep duration showed a U shaped association with depressive symptoms(all P nonlinear <0.05) on a daily basis, during weekdays and weekends, with potential threshold effects at 10.00, 9.88, and 9.60 hours, respectively. Conclusions Sleep duration among children and adolescents is associated with depressive symptoms, with notable age related differeneces. It is recommended to develop targeted age specific interventions to reduce the risk of depressive symptoms in children and adolescents.

Objective: To investigate the association of the joint effect of body fat levels and dyslipidemia with cardiovascular structural abnormalities in children, so as to provide a scientific reference for the early prevention of cardiovascular damage. Methods: Based on the data from the second follow up (October 2021 to January 2022) of the Huantai Children Cardiovascular Health Follow up Cohort, 1 308 children with complete data were included. The fat mass percentage (FMP), fat mass index (FMI), subcutaneous fat mass (SFM) and visceral fat mass (VFM), left ventricular mass index (LVMI), relative wall thickness (RWT), thickening of carotid intima-media thickening (cIMT) , left ventricular hypertrophy (LVH) and left ventricular geometric remodeling (LVG), triglyceride (TG), total cholesterol (TC) ,high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) were obtained. Multivariable Logistic regression model was used to analyze the associations of FMP, FMI, SFM and VFM with thickening of cIMT, LVH and LVG. The joint effects of these body fat indicators and dyslipidemia on the aforementioned cardiovascular outcomes were further explored. Restricted cubic spline model was used to examine the dose response relationships between body fat levels and cardiovascular structural abnormalities. Results: Elevated body fat levels were significantly associated with an increased risk of cardiovascular structural abnormalities, exhibiting J shaped dose response relationships (all P <0.05). Compared with the group with normal body fat and normolipidemia, the risks of thickening of cIMT, LVH, and LVG in the group with elevated FMP combined with dyslipidemia were higher[ OR (95% CI )=11.70 (6.49-21.27), 5.53 (2.97-10.17), 2.33 (1.30-4.05)]; in the group with elevated FMI combined with dyslipidemia, the corresponding risks were higher[ OR (95% CI )= 11.68 (6.43-21.38), 6.98 (3.73-12.92), 2.65 (1.50-4.61)]; in the group with elevated SFM combined with dyslipidemia, the corresponding risks were higher[ OR (95% CI )=10.55 (5.83-19.24), 5.11 (2.71-9.45), 1.99 (1.11- 3.46 )]; and in the group with elevated VFM combined with dyslipidemia, the corresponding risks were higher[ OR (95% CI )=12.44 (6.76-23.14), 6.17 ( 3.31 -11.38), 2.30 (1.30-3.99)] (all P <0.05). Sex stratified analyses showed that the risk of thickening of cIMT in the combined exposure group of all four body fat indicators and dyslipidemia was significantly higher in girls than in boys (all P <0.01). Conclusions Elevated body fat levels and dyslipidemia have a combined effect in children, collectively increasing the risk of cardiovascular structural abnormalities. Prevention of cardiovascular damage in children should focus on both adiposity management and blood lipid regulation.

The advancement of microbiome technologies has facilitated a growing interest in the interactions between urinary microbiota and urinary stone formation. This article systematically reviews the technological evolution, and the reciprocal mechanism of microbiota involvement in lithogenesis and its clinical significance. It specifically highlights the changes within the urinary microbiota of calcium oxalate stone patients, notably a depletion of Lactobacillus populations and an enrichment of pathogenic taxa such as Enterobacteriaceae. Furthermore, it delineates the mechanisms whereby microbes participate in stone formation through metabolic regulation, physical adhesion, and inflammatory processes. The article also explores the influence exerted by distinct stone types on the structural composition and functional dynamics of the urinary microbiota. Integrated multi-omics analyses offer novel perspectives for unraveling the intricate microbiome-host interaction network. This approach is anticipated to facilitate significant advances in developing precision-focused prophylactic and therapeutic strategies for urinary stones from a microecological standpoint.

ObjectiveTranscranial focused ultrasound (tFUS) has emerged as a promising noninvasive neuromodulation technique capable of modulating neural activity with high spatial specificity. However, whether tFUS stimulation of the primary somatosensory cortex (S1) can reliably evoke conscious tactile perception without external peripheral sensory input remains unclear. Therefore, this study examined the feasibility of inducing hand-related tactile perception through targeted S1 stimulation and further investigated how sonication duration (SD), a key temporal parameter, influences the consistency of this perceptual response. The findings may provide empirical evidence for optimizing tFUS parameters in human somatosensory modulation. MethodsForty-eight healthy adults participated in the study and were assigned to two experiments. Experiment 1 included 24 participants and was designed to preliminarily examine whether S1-targeted tFUS could evoke hand-related tactile sensations. This experiment comprised two sub-experiments, Experiment 1a and Experiment 1b, with 12 participants in each. Specifically, Experiment 1a used a randomized active stimulation protocol targeting the bilateral S1 to assess the initial feasibility of inducing contralateral tactile perception, whereas Experiment 1b employed an alternating hemispheric design incorporating both active and sham stimulation to verify the specificity of the tFUS-induced sensations. Experiment 2 enrolled another 24 participants and used a real-sham dual-probe design to control for spatial tactile cues that might arise from probe-scalp contact. Five SD levels, including 200, 400, 600, 800, and 1 000 ms, were systematically tested to evaluate how stimulation duration influenced the behavioral response. The primary behavioral outcome was the perceptual consistency rate, quantified according to the accuracy of contralateral tactile localization. ResultsIn Experiment 1, 91.7% of participants reported reliable hand-related tactile sensations during active tFUS stimulation, including numbness, tingling, or similar sensory experiences. Contralateral localization accuracy under active stimulation was significantly higher than the0.50 chance level (P<0.05). In contrast, localization performance under sham stimulation did not differ from chance, suggesting that the observed tactile responses were mainly induced by active S1-targeted tFUS stimulation rather than nonspecific stimulation cues. In Experiment 2, perceptual consistency rates significantly exceeded the chance level under the 400 and 1 000 ms SD conditions(P<0.05), whereas no significant effect was observed at 200, 600, or 800 ms. Pairwise comparisons further showed that the 400 and 1 000 ms conditions produced significantly higher perceptual consistency rates than the 200 ms condition (P<0.05). ConclusiontFUS stimulation of S1 can elicit distinct hand-related tactile sensations without peripheral sensory input, demonstrating the feasibility of using targeted cortical ultrasound stimulation to induce conscious somatosensory perception. The reliability of this perceptual effect was modulated by sonication duration, indicating that temporal stimulation parameters play an important role in shaping both the occurrence and consistency of behavioral responses. Among the tested conditions, 400 ms appeared to provide a favorable temporal window for generating stable tactile perception, whereas excessively short stimulation may be insufficient to produce consistent responses. These findings highlight the sensitivity of somatosensory networks to ultrasonic modulation and provide useful parameter guidance for the application of tFUS in noninvasive sensory enhancement and cortical functional mapping.

Objective: To evaluate the accuracy of body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR) in screening true obesity among children, so as to provide a scientific basis for precise screening and early prevention and control of childhood obesity. Methods: A total of 1 322 children aged 10-15 years old were surveyed by the Huantai Children Cardiovascular Health Cohort in 2021. Fat mass percentage (FMP) and fat mass index (FMI) were measured by bioelectrical impedance analysis, with FMP or FMI values at or above the age and sex-specific 70th percentiles as the criteria for defining true obesity. BMI, WC and WHtR were used to define general obesity and central obesity. The accuracy of these measures in screening for true obesity was evaluated by calculating the missed diagnosis rate, misdiagnosis rate, area under the curve(AUC) for receiver operating characteristic and Kappa coefficient. Results: Boys had higher BMI [(21.79±4.56) kg/m 2], WC [(76.41±12.53) cm] and WHtR (0.47±0.07) than girls [(20.83±4.13) kg/m 2, (70.69±10.06) cm, (0.45±0.06)] ( t =4.02, 9.19, 6.63), while boys had lower FMP [(18.29±8.35)%] and FMI [(4.35±2.79) kg/m 2] than girls [(24.87±6.51)%, (5.44±2.53) kg/m 2] ( t =-16.10,-7.42) ( P <0.01). Using FMP as a reference standard, the diagnosis error rates of screening for true obesity based on BMI, WC and WHtR were 12.24%, 2.11% and 2.11%, respectively; the diagnosis error rates were 10.88%, 27.28% and 24.33%; the AUC values were 0.88, 0.85 and 0.87; the Kappa coefficients were 0.67, 0.48 and 0.52. Using FMI as a reference standard, rates of BMI, WC and WHtR screening for true obesity were 14.20%, 1.23% and 2.78%; the diagnosis error rates were 4.81%, 20.84% and 18.14 %; the AUC values were 0.90, 0.89 and 0.90; the Kappa coefficients were 0.81, 0.64 and 0.67. Conclusions BMI has a higher diagnosis error rate in screening for true obesity in children, while WC and WHtR have higher diagnosis error rates. It is recommended to promote body fat assessment in clinical practice, so as to achieve more accurate prevention and control of chronic diseases.

Reproductive system diseases are among the primary contributors to the decline in social fertility rates and the intensification of aging, posing significant threats to both physical and mental health, as well as quality of life. Recent research has revealed the substantial potential of the gut microbiota in improving reproductive system diseases. Under healthy conditions, the gut microbiota maintains a dynamic balance, whereas dysfunction can trigger immune-inflammatory responses, metabolic disorders, and other issues, subsequently leading to reproductive system diseases through the gut-gonadal axis. Reproductive diseases, in turn, can exacerbate gut microbiota imbalance. This article reviews the impact of the gut microbiota and its metabolites on both male and female reproductive systems, analyzing changes in typical gut microorganisms and their metabolites related to reproductive function. The composition, diversity, and metabolites of gut bacteria, such as Bacteroides, Prevotella, and Firmicutes, including short-chain fatty acids, 5-hydroxytryptamine, γ-aminobutyric acid, and bile acids, are closely linked to reproductive function. As reproductive diseases develop, intestinal immune function typically undergoes changes, and the expression levels of immune-related factors, such as Toll-like receptors and inflammatory cytokines (including IL-6, TNF-α, and TGF-β), also vary. The gut microbiota and its metabolites influence reproductive hormones such as estrogen, luteinizing hormone, and testosterone, thereby affecting folliculogenesis and spermatogenesis. Additionally, the metabolism and absorption of vitamins can also impact spermatogenesis through the gut-testis axis. As the relationship between the gut microbiota and reproductive diseases becomes clearer, targeted regulation of the gut microbiota can be employed to address reproductive system issues in both humans and animals. This article discusses the regulation of the gut microbiota and intestinal immune function through microecological preparations, fecal microbiota transplantation, and drug therapy to treat reproductive diseases. Microbial preparations and drug therapy can help maintain the intestinal barrier and reduce chronic inflammation. Fecal microbiota transplantation involves transferring feces from healthy individuals into the recipient’s intestine, enhancing mucosal integrity and increasing microbial diversity. This article also delves into the underlying mechanisms by which the gut microbiota influences reproductive capacity through the gut-gonadal axis and explores the latest research in diagnosing and treating reproductive diseases using gut microbiota. The goal is to restore reproductive capacity by targeting the regulation of the gut microbiota. While the gut microbiota holds promise as a therapeutic target for reproductive diseases, several challenges remain. First, research on the association between gut microbiota and reproductive diseases is insufficient to establish a clear causal relationship, which is essential for proposing effective therapeutic methods targeting the gut microbiota. Second, although gut microbiota metabolites can influence lipid, glucose, and hormone synthesis and metabolism via various signaling pathways—thereby indirectly affecting ovarian and testicular function—more in-depth research is required to understand the direct effects of these metabolites on germ cells or granulosa cells. Lastly, the specific efficacy of gut microbiota in treating reproductive diseases is influenced by multiple factors, necessitating further mechanistic research and clinical studies to validate and optimize treatment regimens.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.