Abstract To promote adolescents active participation in physical activity and improve sleep quality, the article analyzes the relationship of adolescent physical activity with subjective sleep satisfaction, sleep latency, sleep continuity, sleep efficiency, and sleep duration. It explores potential mechanisms underlying the link between physical activity and sleep quality, including physiological mechanisms (circadian rhythms, body temperature, neuroendocrine systems, and immune function), and psychological mechanisms (stress relief, improvement of negative emotions, and promotion of mental relaxation). Based on existing research, it is recommended that adolescents engage in moderate to vigorous physical activity daily to promote improved sleep quality.

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Septic shock is the primary cause of mortality in sepsis, with its core pathophysiological mechanism being severe ischemia and hypoxia in critical units—composed of microcirculation and the mitochondria of functional cells—resulting from disruptions in blood flow and oxygen flow following a dysregulated host response. Due to the systemically convergent yet clinically heterogeneous nature of the host response, current understanding and management strategies for hemodynamics remain inconsistent, often leading to inadequate resuscitation or overtreatment. To improve the quality of care, based on a systematic review of the "blood flow-oxygen flow" theory, an expert panel emphasizes reevaluating septic shock from an integrated perspective of blood flow and oxygen flow, and has formulated the Expert Consensus on Blood Flow and Oxygen Delivery Phenotyping and Clinical Management of Septic Shock (2025). The consensus proposes that clinical typing of blood flow-oxygen flow should comprehensively consider cardiac function, vascular tone, oxygen flow utilization status in critical units, and disease trajectory, while optimizing subtype identification by integrating host response phenotypes and artificial intelligence technologies. It advocates establishing a continuous assessment system through multi-site oxygen flow monitoring for organ perfusion, peripheral perfusion monitoring, and critical care ultrasound. Under the framework of the "critical care triangle", the consensus promotes the implementation of individualized, bundled management strategies, providing guidance for multiple management points to restore blood flow-oxygen flow matching, reduce the risk of organ failure, and decrease patient mortality.

Neurocritical care involves complex pathophysiological mechanisms, and its incidence is higher, injuries are more severe, and treatment is more challenging in high-altitude environments. This consensus, based on the latest domestic and international evidence-based medical data, establishes a standardized, goal-oriented framework for neurocritical care management applicable in high-altitude regions and nationwide. The consensus was developed following international standards for evidence quality assessment and underwent two rounds of Delphi expert consultation, resulting in 32 recommendation statements covering three parts: management systems, monitoring and assessment, and core strategies. Key updates include: advocating for the establishment of independent neurocritical care units and implementing precise tiered diagnosis and treatment based on the "Five Differences in Critical Care" concept; constructing a "trinity" multimodal brain monitoring system centered on cerebral blood flow, cerebral oxygenation, and brain function, emphasizing routine bedside transcranial Doppler ultrasound, cerebral oximetry, and continuous electroencephalography monitoring; shifting management strategies from mild hypothermia therapy to targeted temperature management, and defining the "446" target management pathway for the supercritical stage; emphasizing the assessment of static and dynamic cerebrovascular autoregulation functions through multimodal methods to achieve individualized optimal mean arterial pressure management; elevating cerebrospinal fluid management goals to the level of "glymphatic system" function maintenance; implementing a multidisciplinary collaborative, whole-process management model focusing on patients' long-term neurological functional outcomes; de-escalation criteria include multidimensional indicators such as recovery of brain structure, restoration of cerebrovascular autoregulation, improvement in cerebrospinal fluid dynamics, and reduction in biomarker levels; and integrating cutting-edge technologies like artificial intelligence into post-critical care management and rehabilitation planning. This consensus systematically integrates the entire process of neurocritical care management, reflecting the modern connotation of goal-oriented, dynamic, and multimodal integration in neurocritical care medicine. It aims to adapt to new trends such as deepening understanding of pathophysiological mechanisms, the integration of medicine and engineering, and the empowerment of artificial intelligence, thereby further advancing the discipline of critical care medicine.

ObjectiveTo analyze the long-term trend of incidence and mortality of type 2 diabetic kidney disease （DKD） in China from 1990 to 2021. MethodsThe Joinpoint regression model was used to analyze the average annual percentage change （AAPC） of standardized incidence rate and standardized mortality rate， and the age-period-cohort （APC） model was constructed to analyze the longitudinal age change， period and cohort effect risk ratio （RR）. ResultsFrom 1990 to 2021， the standardized incidence rate of type 2 DKD in males and females showed an overall upward trend， with AAPC of 0.08% and 0.36%， respectively. The age-standardized mortality rate of the total population and female showed a downward trend， with AAPC of -0.61% and -1.03%， respectively. However， there was no significant difference in males. APC model showed that the age effect existed： the peak age was 75-79 years old， the mortality rate of females increased， and the mortality rate of males decreased after 80-84 years old. For the effect of time period， the risk of type 2 DKD incidence in females in 2017—2021 was 1.05 times that in 2002—2006， and the risk of death in males and females in 2017—2021 was 0.84 and 0.71 times that in 2002—2006， respectively. For cohort effects， the highest risk of disease was seen in men and women born in 1967—1971， and the highest risk of death was seen in men born in 1952—1956 and women born in 1912—1916. ConclusionFrom 1990 to 2021， the standardized incidence rate of type 2 DKD in China shows an upward trend， and the standardized mortality rate shows a downward trend. It is necessary to strengthen the health behavior publicity and education of type 2 DKD， and actively carry out early screening to reduce the disease burden.

Alzheimer’s disease (AD) is a chronic neurodegenerative disorder that severely affects the health of the elderly, marked by its incurability, high prevalence, and extended latency period. The current approach to AD prevention and treatment emphasizes early detection and intervention, particularly during the pre-AD stage of mild cognitive impairment (MCI), which provides an optimal “window of opportunity” for intervention. Clinical detection methods for MCI, such as cerebrospinal fluid monitoring, genetic testing, and imaging diagnostics, are invasive and costly, limiting their broad clinical application. Speech, as a vital cognitive output, offers a new perspective and tool for computer-assisted analysis and screening of cognitive decline. This is because elderly individuals with cognitive decline exhibit distinct characteristics in semantic and audio information, such as reduced lexical richness, decreased speech coherence and conciseness, and declines in speech rate, voice rhythm, and hesitation rates. The objective presence of these semantic and audio characteristics lays the groundwork for computer-based screening of cognitive decline. Speech information is primarily sourced from databases or collected through tasks involving spontaneous speech, semantic fluency, and reading, followed by analysis using computer models. Spontaneous language tasks include dialogues/interviews, event descriptions, narrative recall, and picture descriptions. Semantic fluency tasks assess controlled retrieval of vocabulary items, requiring participants to extract information at the word level during lexical search. Reading tasks involve participants reading a passage aloud. Summarizing past research, the speech characteristics of the elderly can be divided into two major categories: semantic information and audio information. Semantic information focuses on the meaning of speech across different tasks, highlighting differences in vocabulary and text content in cognitive impairment. Overall, discourse pragmatic disorders in AD can be studied along three dimensions: cohesion, coherence, and conciseness. Cohesion mainly examines the use of vocabulary by participants, with a reduction in the use of nouns, pronouns, verbs, and adjectives in AD patients. Coherence assesses the ability of participants to maintain topics, with a decrease in the number of subordinate clauses in AD patients. Conciseness evaluates the information density of participants, with AD patients producing shorter texts with less information compared to normal elderly individuals. Audio information focuses on acoustic features that are difficult for the human ear to detect. There is a significant degradation in temporal parameters in the later stages of cognitive impairment; AD patients require more time to read the same paragraph, have longer vocalization times, and produce more pauses or silent parts in their spontaneous speech signals compared to normal individuals. Researchers have extracted audio and speech features, developing independent systems for each set of features, achieving an accuracy rate of 82% for both, which increases to 86% when both types of features are combined, demonstrating the advantage of integrating audio and speech information. Currently, deep learning and machine learning are the main methods used for information analysis. The overall diagnostic accuracy rate for AD exceeds 80%, and the diagnostic accuracy rate for MCI also exceeds 80%, indicating significant potential. Deep learning techniques require substantial data support, necessitating future expansion of database scale and continuous algorithm upgrades to transition from laboratory research to practical product implementation.

Objective: To assess the effect of transarterial embolization (TAE) for adhesive capsulitis (AC) by evaluating clinical outcomes and changes in inflammation using magnetic resonance imaging (MRI). Materials and Methods: Patients who had undergone TAE between August 2020 and August 2023 for AC refractory to conservative treatments without any invasive procedures for more than 3 months, and had undergone baseline and 3-month post-AC follow-up contrast-enhanced MRI evaluations, were included. A suspension mixture of 500 mg imipenem/cilastatin in 10 mL of iodinated contrast agent was used for TAE. MRI results were analyzed to assess periarticular capsule/ligament inflammation. Clinical assessments included pain scores using the numeric rating scale (NRS) and functional scores using the quick disabilities of the arm, shoulder, and hand (Quick DASH) questionnaire. Results: Twenty-five patients (female:male, 14:11; age, 54.9 ± 7.1 years) were included. Significant reductions in average NRS pain scores as well as improvements in Quick DASH scores and range of motion, including anterior flexion and abduction, were observed at 1, 3, and 6 months after TAE (all P < 0.001). MRI analyses revealed that TAE significantly decreased the grades of axillary recess capsule enhancement, rotator interval (RI) capsule T2 signal intensity, and RI capsule enhancement (all P ≤ 0.004). Conclusion TAE may be an effective and safe therapeutic approach for AC refractory to conservative treatments, alleviating pain and supporting functional recovery. The observed MRI findings suggest that the effectiveness of TAE for AC may be attributed to the reduction of inflammation and the elimination of angiogenesis.

Diabetic nephropathy (DN) remains a leading cause of end-stage renal disease (ESRD), driven by chronic inflammation, oxidative stress, and apoptosis. Current therapies targeting glycemic and blood pressure control fail to address the underlying molecular mechanisms of DN. This study investigates the therapeutic potential of andrographolide (AD), a diterpenoid lactone from Andrographis paniculata, in mitigating DN by modulating key molecular pathways. Through integrative network pharmacology, molecular docking, and in vivo/in vitro experiments, 107 overlapping DN-related targets were identified, with STAT3, PI3K, and AKT1 emerging as core nodes. Molecular docking revealed high binding affinities between AD and these targets, supporting its modulatory potential. In vivo, AD significantly improved renal function in streptozotocin-induced DN rats, reducing proteinuria, glomerular hypertrophy, and renal fibrosis. AD also attenuated oxidative stress, decreased pro-inflammatory cytokine levels, and enhanced antioxidant enzyme activities, demonstrating systemic anti-inflammatory and antioxidative effects. In vitro studies further confirmed that AD alleviates podocyte oxidative stress and apoptosis under high glucose conditions by suppressing the RAGE-NF-κB and STAT3/PI3K/Akt pathways. Histological analyses revealed substantial improvements in renal architecture, including reductions in fibrosis and mesangial expansion. These results underscore AD’s multi-target mechanism, directly addressing DN’s core pathological drivers, including inflammation, oxidative stress, and apoptosis. As a natural compound with notable safety and efficacy, AD holds promise as an adjunct or standalone therapeutic agent for DN. This study establishes a robust preclinical foundation for AD, warranting further exploration in clinical trials and its potential application in other diabetic complications.

Diabetic nephropathy (DN) remains a leading cause of end-stage renal disease (ESRD), driven by chronic inflammation, oxidative stress, and apoptosis. Current therapies targeting glycemic and blood pressure control fail to address the underlying molecular mechanisms of DN. This study investigates the therapeutic potential of andrographolide (AD), a diterpenoid lactone from Andrographis paniculata, in mitigating DN by modulating key molecular pathways. Through integrative network pharmacology, molecular docking, and in vivo/in vitro experiments, 107 overlapping DN-related targets were identified, with STAT3, PI3K, and AKT1 emerging as core nodes. Molecular docking revealed high binding affinities between AD and these targets, supporting its modulatory potential. In vivo, AD significantly improved renal function in streptozotocin-induced DN rats, reducing proteinuria, glomerular hypertrophy, and renal fibrosis. AD also attenuated oxidative stress, decreased pro-inflammatory cytokine levels, and enhanced antioxidant enzyme activities, demonstrating systemic anti-inflammatory and antioxidative effects. In vitro studies further confirmed that AD alleviates podocyte oxidative stress and apoptosis under high glucose conditions by suppressing the RAGE-NF-κB and STAT3/PI3K/Akt pathways. Histological analyses revealed substantial improvements in renal architecture, including reductions in fibrosis and mesangial expansion. These results underscore AD’s multi-target mechanism, directly addressing DN’s core pathological drivers, including inflammation, oxidative stress, and apoptosis. As a natural compound with notable safety and efficacy, AD holds promise as an adjunct or standalone therapeutic agent for DN. This study establishes a robust preclinical foundation for AD, warranting further exploration in clinical trials and its potential application in other diabetic complications.

Neuroscience is a significant frontier discipline within the natural sciences and has become an important interdisciplinary frontier scientific field. Brain is one of the most complex organs in the human body, and its structural and functional analysis is considered the “ultimate frontier” of human self-awareness and exploration of nature. Driven by the strategic layout of “China Brain Project”, Chinese scientists have conducted systematic research focusing on “understanding the brain, simulating the brain, and protecting the brain”. They have made breakthrough progress in areas such as the principles of brain cognition, mechanisms and interventions for brain diseases, brain-like computation, and applications of brain-machine intelligence technology, aiming to enhance brain health through biomedical technology and improve the quality of human life. Due to limited understanding and comprehension of neuroscience, there are still many important unresolved issues in the field of neuroscience, resulting in a lack of effective measures to prevent and protect brain health. Therefore, in addition to actively developing new generation drugs, exploring non pharmacological treatment strategies with better health benefits and higher safety is particularly important. Epidemiological data shows that, exercise is not only an indispensable part of daily life but also an important non-pharmacological approach for protecting brain health and preventing neurodegenerative diseases, forming an emerging research field known as motor neuroscience. Basic research in motor neuroscience primarily focuses on analyzing the dynamic coding mechanisms of neural circuits involved in motor control, breakthroughs in motor neuroscience research depend on the construction of dynamic monitoring systems across temporal and spatial scales. Therefore, high spatiotemporal resolution detection of movement processes and movement-induced changes in brain structure and neural activity signals is an important technical foundation for conducting motor neuroscience research and has developed a set of tools based on traditional neuroscience methods combined with novel motor behavior decoding technologies, providing an innovative technical platform for motor neuroscience research. The protective effect of exercise in neurodegenerative diseases provides broad application prospects for its clinical translation. Applied research in motor neuroscience centers on deciphering the regulatory networks of neuroprotective molecules mediated by exercise. From the perspectives of exercise promoting neurogenesis and regeneration, enhancing synaptic plasticity, modulating neuronal functional activity, and remodeling the molecular homeostasis of the neuronal microenvironment, it aims to improve cognitive function and reduce the incidence of Parkinson’s disease and Alzheimer’s disease. This has also advanced research into the molecular regulatory networks mediating exercise-induced neuroprotection and facilitated the clinical application and promotion of exercise rehabilitation strategies. Multidimensional analysis of exercise-regulated neural plasticity is the theoretical basis for elucidating the brain-protective mechanisms mediated by exercise and developing intervention strategies for neurological diseases. Thus,real-time analysis of different neural signals during active exercise is needed to study the health effects of exercise throughout the entire life cycle and enhance lifelong sports awareness. Therefore, this article will systematically summarize the innovative technological developments in motor neuroscience research, review the mechanisms of neural plasticity that exercise utilizes to protect the brain, and explore the role of exercise in the prevention and treatment of major neurodegenerative diseases. This aims to provide new ideas for future theoretical innovations and clinical applications in the field of exercise-induced brain protection.

This paper aimed to systematically evaluate the effects of hypoxic training at different fraction of inspired oxygen (FiO₂) on body composition, glucose metabolism, and lipid metabolism in obese individuals, and to determine the optimal oxygen concentration range to provide scientific evidence for personalized and precise hypoxic exercise prescriptions. A systematic search was conducted in the Cochrane Library, PubMed, Web of Science, Embase, and CNKI databases for randomized controlled trials and pre-post intervention studies published up to March 31, 2025, involving hypoxic training interventions in obese populations. Meta-analysis was performed using RevMan 5.4 software to assess the effects of different fraction of inspired oxygen (FiO₂≤14% vs. FiO₂>14%) on BMI, body fat percentage, waist circumference, fasting blood glucose, insulin, HOMA-IR, triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), with subgroup analyses based on oxygen concentration. A total of 22 studies involving 292 participants were included. Meta-analysis showed that hypoxic training significantly reduced BMI (mean difference (MD)=-2.29,95%CI: -3.42 to -1.17, P<0.000 1), body fat percentage (MD=-2.32, 95%CI: -3.16 to -1.47, P<0.001), waist circumference (MD=-3.79, 95%CI: -6.73 to -0.85, P=0.01), fasting blood glucose (MD=-3.58, 95%CI: -6.23 to -0.93, P=0.008), insulin (MD=-1.60, 95%CI: -2.98 to -0.22, P=0.02), TG (MD=-0.18, 95%CI: -0.25 to -0.12, P<0.001), and LDL-C (MD=-0.25, 95%CI: -0.39 to -0.11, P=0.000 3). Greater improvements were observed under moderate hypoxic conditions with FiO₂>14%. Changes in HOMA-IR (MD=-0.74, 95%CI: -1.52 to 0.04,P=0.06) and HDL-C (MD=-0.09, 95%CI: -0.21 to 0.02, P=0.11) were not statistically significant. Hypoxic training can significantly improve body composition, glucose metabolism, and lipid metabolism indicators in obese individuals, with greater benefits observed under moderate hypoxia (FiO>14%). As a key parameter in hypoxic exercise interventions, the precise setting of oxygen concentration is crucial for optimizing intervention outcomes.