The technology of xenogeneic organ transplantation, as one of the core strategies to address the current contradiction between the supply and demand of transplant organs, has achieved significant breakthroughs from basic research to clinical application driven by factors such as the innovation of gene modification technology, the injection of research capital and the expansion of clinical trials, especially with the first actual clinical application of a pig heart-to-human transplant. China is also at the forefront of this field. This article intends to summarize the international research trends of xenogeneic organ transplantation (including financial support, the evolution of research stages and global clinical trial cases), and analyze the evolution and optimization of xenogeneic transplantation immunosuppression schemes, as well as the breakthroughs and unresolved scientific issues in current key clinical application technologies. The aim is to comprehensively present the progress of this field from basic research to clinical transformation, and provide references for promoting the rapid development of China's xenogeneic transplantation technology and subsequent clinical transformation and research directions.

Objective: To investigate the serological identification and blood group gene sequencing analysis of two rare cases of K phenotype producing high-frequency antigen antibodies (anti-Ku), and to study the serological interrelationship between K cells and the high-frequency antigen antibody anti-KL. Methods: Serological methods were used to identify the antigen phenotypes of the ABO, Rh, and Kell blood group systems and to screen for and identify unexpected antibodies in the two patients. The characteristics of the unexpected antibodies were verified by the indirect antiglobulin test (IAT) using papain or dithiothreitol (DTT) -treated screening cells. The titer of anti-Ku was determined via the tube method using DTT-treated plasma. The Kell blood group genotype was determined by gene sequencing. The distinctive antigenicity of K cells was validated through their reactivity with anti-KL in IAT, and absorption-elution techniques were employed to corroborate the type of anti-KL. Results: Serological findings: Case 1 was blood group O, CCDee; Case 2 was blood group A, CCDee. Both cases exhibited the Kell phenotype: K-k-, Kp (a-b-). High-frequency antigen antibodies were detected in the plasma of both patients. The reactivity of these antibodies was slightly enhanced with papain-treated screening cells but became negative with DTT-treated cells. The anti-Ku (IgG) titer for Case 1 was 64. For Case 2, the anti-Ku (IgM) titer was<1, and the anti-Ku (IgG) titer was 32. Gene sequencing revealed that both cases harbored a homozygous c.715G>T mutation in the KEL gene, corresponding to the genotype KEL02N.24, consistent with the rare K phenotype. The unique high expression of the Kx antigen on K cells was confirmed through the antibody characteristics of anti-KL. Absorption-elution techniques demonstrated that K cells could separate anti-Km and anti-Kx, thereby supporting the classification of anti-KL. Conclusion: Serological and molecular biological assays identified both patients as having the rare Kell-null (K ) phenotype. If such rare blood types go undetected in transfusion medicine, the administration of standard blood products can readily induce the production of high-frequency antigen antibodies such as anti-Ku, potentially leading to a transfusion crisis due to the subsequent difficulty in finding compatible blood. The serological relationship between K cells and anti-KL clarified the characteristic high expression of the Kx antigen on K phenotype erythrocytes and concurrently supported the typological features of the rare high-frequency antibody anti-KL. This represents the first such verified report in China.

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.

Methods: Six finite element models of T12 burst fractures were developed to simulate short-segment stabilization under normal or osteoporotic bone conditions, with/without augmentation screws at the fractured vertebra. Spinal stiffness, implant stresses, and axial displacement/micromotion of the bony defect were measured and compared under mechanical loading. Results: Osteoporotic models exhibited a greater range of motion (ROM) than normal bone. All six-screw constructs reduced ROM across all motions compared with traditional four-screw models. Osteoporotic fracture models gained greater benefit from intermediate screw augmentation at the fracture vertebra, which also lowered axial displacement/micromotion. In six-screw models, rod stress increased while pedicle screw stress decreased. Intermediate screws at fractured vertebrae produced similar changes in stress distribution across all fixation models, regardless of bone quality. Conclusions Our findings may facilitate implant selection for osteoporotic burst fractures, supporting the use of more rigid fixation sixscrew constructs to reduce the risk of mechanical failure and postoperative re-collapse.

Methods: A total of 45 patients diagnosed with de novo thoracic or lumbar SEA who underwent posterior-only surgical decompression between 2005 and 2014, with a minimum postoperative follow-up of 2 years, were included. Patients were stratified based on the presence or absence of postoperative residual ND, and neurological function was assessed immediately after surgery and at the final followup using the Frankel grading system. SITE scores, along with clinical and radiological data associated with residual ND, were collected. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to identify significant predictors. Results: Patients with residual ND had significantly lower SITE scores than those without residual ND (4.3±1.3 vs. 7±1.8, p<0.0001). Multivariate analysis identified the SITE score as an independent predictor (odds ratio, 2.70; p=0.012). ROC analysis showed that a SITE score ≤6 predicted residual ND with 73.3% sensitivity and 100% specificity, with an area under the curve of 0.877 (p<0.001). Other significant predictors included cauda equina syndrome and a shorter symptom-to-surgery interval, both of which were associated with a higher risk of residual ND. Conclusions The SITE score is a reliable and independent predictor of residual ND after surgery for SEA. SITE scores <6 indicate a significantly higher risk of postoperative ND.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

In March 2024, three male and two female specimens of the genus Lispe were intercepted on cargo ships inbound for Wan Zai Port under Gongbei Customs. Based on morphological characteristics and molecular analysis, the specimens were identified as Lispe pumila. In this study, we describe the morphological features, diagnostic characteristics, and geographical distribution of L. pumila, with the aim of providing a reference for the identification of this species when intercepted at ports.

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.

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.