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.

Patients with Takayasu arteritis combined with aortic valve disease often have a poor prognosis following surgical valve replacement, frequently encountering complications such as perivalvular leakage, valve detachment, and anastomotic aneurysm. This article presents a high-risk case wherein severe aortic valve insufficiency associated with Takayasu arteritis was successfully managed through transcatheter aortic valve implantation via the transapical approach. The patient had satisfactory valve function with no complications observed during the six-month postoperative follow-up. This case provides a minimally invasive and feasible alternative for the clinical management of such high-risk patients.

Objective To systematically review the studies on predictive models for delayed graft function (DGF) after kidney transplantation. Methods Databases including China Biology Medicine Database, China National Knowledge Infrastructure, Wanfang Database, VIP Database, PubMed, Web of Science and CINAHL were searched to collect studies on predictive models for DGF after kidney transplantation published from the establishment of each database to June 29, 2025. Two researchers screened the literatures according to the inclusion and exclusion criteria, evaluated the quality of the literatures using the prediction model risk of bias assessment tool (PROBAST), and conducted a meta-analysis of the common predictors of the models using R software. Results A total of 12 literatures were included, involving 14 predictive models with sample sizes ranging from 103 to 24 653 cases. Donor serum creatinine level, cold ischemia time, donor age and donor body mass index were the top four common predictors. All the predictive models were at high risk of bias and low in applicability. The results of meta-analysis showed that abnormal donor body mass index, advanced donor age, prolonged cold ischemia time and elevated donor serum creatinine level were all associated with an increased risk of DGF after transplantation (all P<0.01), but there was high heterogeneity among the studies. Fixed-effect model and random-effect model were used to re-pool the effect sizes separately. The results indicated that the fixed-effect model and random-effect model had good consistency in terms of donor body mass index, donor age and cold ischemia time, while there was a significant difference in the effect sizes of the two models for donor serum creatinine level. Conclusions The predictive models for DGF risk after kidney transplantation have good predictive performance, but the overall risk of bias is high. In the future, large-sample, multicenter and high-quality prospective clinical studies should be carried out to optimize the predictive models, so as to improve their predictive ability and clinical application value.

Metabolic associated fatty liver disease （MAFLD） is a common chronic liver disease worldwide， and timely and precise intervention can delay disease progression and significantly reduce the risk of serious complications such as liver fibrosis， liver cirrhosis， and liver cancer. Although traditional liver biopsy combined with metabolic markers is the gold standard， it may cause complications such as pain and bleeding as an invasive examination， which has promoted scientific research to shift its focus to the construction of noninvasive assessment systems. In recent years， noninvasive diagnostic technologies based on multi-dimensional detection strategies have been continuously updated， including serological models， imaging techniques， and clinical algorithms. This article systematically reviews the screening methods for MAFLD during the fibrotic stages F1—F3， especially deep learning models based on artificial intelligence， in order to provide ideas for the early screening of MAFLD， as well as a scientific reference for optimizing disease management strategies.

Although video-assisted thoracoscopic surgery (VATS) offers clear advantages, including minimal trauma and rapid recovery, stable intraoperative visualization still depends heavily on the camera assistant. Traditional manual endoscope holding is therefore susceptible to several limitations, including image instability, assistant fatigue, and poor coordination with the primary surgeon. Operating in complex and confined anatomical spaces with a rigid thoracoscope further increases the demands on hand-eye coordination. Thoracoscopic camera-holding technology has progressively evolved from passive support systems to active camera holders and robot-assisted thoracic surgery (RATS) platforms, and is now advancing toward artificial intelligence-driven tracking and intelligent control. Based on this, a series of devices, including multifunctional intelligent assistant arms and active camera-holding arms for thoracic surgery, have been developed and have attracted increasing attention. This article reviews the development of intelligent camera-holding assistant arms and discusses related advances and future directions in the field.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

Owing to its inherent advantages—such as being non-destructive, rapid, highly molecule-specific, and minimally interfered with by moisture—Raman spectroscopy has been widely adopted in the fields of skin barrier function assessment, monitoring the transdermal penetration of active cosmetic ingredients, and the identification and quality control of cosmetic products. Despite these strengths, the practical application of this technique faces a significant bottleneck: the strong fluorescence background generated by endogenous skin components and exogenous cosmetic additives. Endogenous skin substances, such as structural proteins (e.g., collagen and elastin), metabolic coenzymes (e.g., nicotinamide adenine dinucleotide), and pigments (e.g., melanin), together with exogenous cosmetic constituents like organic colorants, chemical sunscreens, and fragrances, often possess strong absorption and emission characteristics. When excited by lasers, these components produce a fluorescence background that can be 10⁶ to 10⁸ times stronger than the Raman scattering signals, effectively masking the inherently weak vibrational fingerprint information. In recent years, driven by the rapid development of optoelectronic hardware and artificial intelligence algorithms, fluorescence suppression strategies have evolved from isolated, single-method approaches into comprehensive, multi-level synergistic systems. These systems are categorized into three distinct tiers: sample preparation, signal acquisition, and data processing. At the sample preparation level, techniques such as photobleaching and surface-enhanced Raman spectroscopy (SERS) are employed to eliminate or bypass the generation of fluorescence at the source. At the signal acquisition level, instrumental improvements—including the use of long-wavelength near-infrared excitation (typically 785 nm or 1 064 nm), confocal spatial filtering, and shifted excitation Raman difference spectroscopy (SERDS)— are utilized to physically isolate Raman signals from the fluorescence background. Furthermore, at the data processing level, numerical baseline correction methods such as polynomial fitting, penalized least squares (e.g., airPLS, arPLS), wavelet transform, and derivative algorithms are increasingly integrated into the analytical pipeline to extract Raman spectral features from mixed signals without increasing hardware costs or acquisition time. This review provides a systematic categorization and critical evaluation of these fluorescence suppression methods, detailing their underlying principles, technical advantages, and inherent limitations in diverse experimental setups. By focusing on critical application scenarios—including skin barrier assessment, percutaneous absorption monitoring, the routine quality control of cosmetics, and the emerging field of portable on-site detection—this paper explores the current state of technique selection and optimization. Finally, the article discusses future development trends, emphasizing the necessity of constructing adaptive, tiered suppression strategies, developing intelligent and automated data processing algorithms, and promoting the integration of portable, multi-modal diagnostic devices. The objective of this review is to provide a comprehensive technical reference to facilitate the transition of Raman spectroscopy from a specialized laboratory tool into a routine, robust analytical platform for advancements in skin science and cosmetic research.

Objective To investigate the epidemiological characteristics of imported malaria cases in Shanghai Municipality from 2020 to 2024, so as to provide insights into dynamic adjustment of imported malaria control strategies. Methods All data pertaining to malaria cases reported in Shanghai Municipality from 2020 to 2024 were collected from Infectious Diseases Reporting Information Management System and Parasitic Diseases Prevention and Control Information Management System of Chinese Center for Disease Control and Prevention, and epidemiological investigation reports of malaria cases. The type of malaria cases, source of acquiring infections, temporal, spatial and population distributions of malaria cases, type of initial diagnosis institutions, accuracy of initial diagnosis, time interval from disease onset to initial diagnosis, and the time interval from initial diagnosis to diagnosis were statistically analyzed. The monthly distribution of malaria cases was analyzed using a circular distribution method. Results A total of 124 malaria cases were reported in Shanghai Municipality from 2020 to 2024, with 14, 52, 22, 8 and 28 cases annually, respectively, and all cases were overseas imported cases. Plasmodium falciparum malaria was the predominant type, accounting for 82.26% (102/124) of all malaria cases, while P. ovale, P. vivax and P. malariae malaria accounted for 8.06% (10/124), 7.26% (9/124) and 2.42% (3/124) of reported cases, respectively. Malaria cases acquired infections from 28 countries in 4 continents, with African countries as a major source of acquiring infections (96.77%, 120/124). Malaria cases were reported across all 16 districts in Shanghai Municipality. There were peaks in numbers of reported malaria cases in May 2021 (9 cases) and November 2021 (9 cases); however, there was no concentration trend in the reporting time of malaria cases from 2020 to 2024 (Z = 2.45, P > 0.05). The reported malaria cases included 116 males and 8 females, with a male-to-female ratio of 14.5∶1.0, and had a median age of 39 (17) years. Worker was the primary occupation of reported malaria cases, accounting for 48.39% (60/124) of all reported cases. City-level medical institutions were the predominant initial diagnosis institutions (75.81%, 94/124). The overall accuracy of initial diagnosis was 74.19% (92/124), and the median time interval from disease onset to initial diagnosis was 0 (2) day (healthcare seeking on the day of disease onset), with 72.58% (90/124) of malaria cases seeking healthcare services within one day. The median time interval from initial diagnosis to diagnosis was 2 (3) days, with 41.94% (52/124) of malaria cases that were definitively diagnosed within one day following initial diagnosis. There were significant differences in the accuracy of initial malaria diagnosis (χ² = 15.01, P < 0.05), the time interval from disease onset to initial diagnosis (H = 29.30, P < 0.001), and the time interval from initial diagnosis to diagnosis (H = 22.92, P < 0.001) among years from 2020 to 2024, and the time interval from disease onset to initial diagnosis (Z = -5.09, P < 0.001) and the time interval from initial diagnosis to diagnosis (Z = -4.14, P < 0.001) were both shorter during the period from 2020 to 2022 than those recorded from 2023 to 2024. In addition, a total of 2 malaria deaths were reported in Shanghai Municipality during the period from 2020 to 2024, both caused by P. falciparum malaria. Conclusions The numbers of malaria cases fluctuated continuously in Shanghai Municipality from 2020 to 2024. It is recommended to continuously strengthen surveillance and response measures, improve malaria diagnosis and treatment capabilities, and conduct targeted health education activities among high-risk populations, such as labors going to overseas malaria hyper-endemic areas, so as to prevent re-establishment of imported malaria.

Objective In this study, the resistance of Blattella germanica to D-cyphenothrin in Guangdong Province was analyzed. Further, the contact activity of eight types of plant essential oils against B. germanica and their synergistic effects with D-cyphenothrin were tested and screened, providing a basis for slowing down insecticide resistance in pests and developing plant synergists. Methods The drip test method was used to measure the resistance levels of B. germanica to D-cyphenothrin in four cities of Guangdong Province:Zhongshan City, Foshan City, Zhuhai City, and Jiangmen City. In addition, the contact killing activities of eight types of plant essential oils against B. germanica, namely, garlic, cinnamon, clove, camphor, eucalyptus leaves, tea tree, Angelica dahurica and peppermint, and their synergistic activities with D-cyphenothrin were evaluated. Results Except for B. germanica in the Xiaolan area of Zhongshan, which was moderately resistant, B. germanica in the other four towns in Guangdong were all highly resistant. Among the eight essential oils tested, garlic essential oil had the strongest toxic activity against B. germanica, with LD50 values of 45.01 μg/individual. A concentration of 2% essential oil plus D-cyphenothrin (LD20)was used to screen for synergistic activity. After 24 h of treatment, Angelica dahurica, garlic, peppermint, camphor, and tea tree essential oils showed synergistic activity. Of these, A. dahurica essential oil had the strongest synergistic activity, with a synergistic coefficient of 125%. Conclusions The essential oil of garlic had the strongest toxic activity against B. germanica, and the essential oils of A. dahurica and garlic together had the strongest synergistic activity with D-cyphenothrin, thereby providing a reference for developing natural plant synergists.

Objective To explore the safety and efficacy of thoracoscopy-guided thoracic paravertebral block (TPVB) in thoracoscopic pulmonary resection, and to provide strategies for enhanced recovery after surgery (ERAS) in thoracoscopic lung resection. Methods Patients who underwent thoracoscopic pulmonary resection (including sublobar resection and lobectomy) in the 987th Hospital of Joint Logistics Support Force of People's Liberation Army, General Hospital of Central Theater Command of the People’s Liberation Army, and the First Affiliated Hospital with Nanjing Medical University between May 2021 and June 2023 were prospectively enrolled. The patients were randomly allocated into three groups in a single-blind manner using a random number table. Group A (incisional nerve block group) received a subcutaneous injection of ropivacaine (0.375%, 2 mg/kg) around the incision during chest closure. Group B (ultrasound-guided TPVB group) received an ultrasound-guided injection of ropivacaine (0.375%, 2 mg/kg) at the paravertebral space after chest closure. Group C (thoracoscopy-guided TPVB group) received a thoracoscopy-guided intrathoracic injection of ropivacaine (0.375%, 2 mg/kg) at the paravertebral space during chest closure. Perioperative adverse drug reactions, pain scores, postoperative analgesic consumption, and postoperative length of hospital stay were compared among the three groups. Results A total of 180 patients were included, comprising 108 females and 72 males, with a mean age of (62.15±7.36) years. There were no statistical differences among the three groups in baseline characteristics, including age, weight, gender, prevalence of comorbidities, operative time, number of surgical incisions, number of chest tubes, or intraoperative dosages of sufentanil and propofol (P>0.05). No adverse anesthesia events occurred during surgery in any of the groups. The pressing frequency of the patient-controlled intravenous analgesia (PCIA) pump, Visual Analogue Scale (VAS) pain scores, the rate of postoperative rescue analgesic use, and the incidences of postoperative cough and dizziness in the group C were significantly lower than those in the other two groups (P<0.05). The postoperative length of hospital stay in the group B and group C was significantly shorter than that in the group A (P<0.05). Conclusion Thoracoscopy-guided TPVB during chest closure can effectively alleviate postoperative pain without increasing postoperative side effects, which facilitates the enhanced recovery after thoracoscopic lung surgery.