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.

Objective To explore the efficacy and safety of blue laser vaporization in the treatment of large-volume (＞80 mL) benign prostatic hyperplasia (BPH). Methods A retrospective analysis was conducted on the clinical data of 149 BPH patients with prostate volume＞80 mL who underwent blue laser vaporization at our hospital during Aug. 2023 and Aug. 2025. The 1-month postoperative maximum urinary flow rate (Qmax) and international prostate symptom score (IPSS), operation time, postoperative hemoglobin drop, bladder irrigation volume, catheter indwelling time, and incidence of postoperative complications were recorded and analyzed. Results All operations were successfully completed, without conversion to other approaches. The operation time was (41.47±11.05) minutes, postoperative hemoglobin drop (2.78±1.19) g/L, bladder irrigation volume (9.97±1.49) bags, and catheter indwelling time (3.30±1.85) days. One month after surgery, the Qmax was significantly higher than the preoperative value [(20.19±3.39) mL/s vs. (2.39±2.17) mL/s], while the IPSS was significantly lower [(4.46±0.87) vs. (27.69±2.06)], with statistically significant differences (P＜0.001). Postoperative complications included 1 case of incontinence (0.67%), 2 cases of urethral stricture/bladder neck contracture (1.34%), and 1 case of secondary bleeding (0.67%), all of which improved with symptomatic treatment. Conclusion Blue laser vaporization is effective for treating large-volume BPH, with advantages such as minimal bleeding risk, short operation time, fast recovery and safety.

ObjectiveTo investigate the efficacy and safety of Shuganning injection in the treatment of liver injury by observing the clinical outcome of patients with liver injury after treatment with Shuganning injection and comparing it with reduced glutathione （GSH）. MethodsThis study was conducted among 175 patients with liver injury who attended 6 hospitals in China （Beijing YouAn Hospital， Capital Medical University； Nanyang First People’s Hospital； The Second Affiliated Hospital of Xi’an Jiaotong University； The Fifth Medical Center of Chinese PLA General Hospital； The Third Hospital of Hebei Medical University； The Affiliated Hospital of Guizhou Medical University） from April 25， 2019 to February 28， 2022. The patients were divided into experimental group （89 patients treated with Shuganning injection） and control group （86 patients treated with GSH）， and the course of treatment was 4 weeks for both groups. Related indicators were recorded before treatment， after treatment， and after drug withdrawal for 8 weeks， including liver function parameters， blood biochemical parameters， blood lipids， coagulation profiles， liver fibrosis markers， traditional Chinese medicine （TCM） syndrome score， and ultrasound findings， as well as adverse events during treatment. The Wilcoxon rank-sum test was used for comparison of continuous data between two groups， and the chi-square test was used for comparison of categorical data between two groups. The Wilcoxon signed-rank test was used for comparison of observation indicators before treatment， at week 4 of treatment， and after drug withdrawal for 8 weeks. When the efficacy evaluation of TCM syndromes was used as the outcome， a pooled analysis was performed for the effective cases and the markedly effective cases， and a Logistic regression model was used to calculate the odds ratio （OR） and its 95%CI. ResultsAfter 4 weeks of treatment with Shuganning injection， the patients showed significant reductions in TCM syndrome score （P<0.001） and the levels of aspartate aminotransferase， alanine aminotransferase， total bilirubin， and direct bilirubin （all P<0.001） and a significant increase in the level of albumin （P=0.002）， and these significant improvements persisted after drug withdrawal for 8 weeks. Furthermore， compared with the control group， the experimental group had a significantly higher proportion of patients assessed as effective or markedly effective cases （48.31% vs 32.56%， P=0.033）. Compared with the control group， the experimental group had a significantly greater change in TCM syndrome score at weeks 1-4 of treatment and after drug withdrawal for 8 weeks （P<0.05）. At week 4 of treatment， the experimental group had a significantly greater reduction in alanine aminotransferase than the control group （P<0.05）， and at week 8 after drug withdrawal， the experimental group had a significantly greater reduction in alanine aminotransferase and aspartate aminotransferase than the control group （all P<0.05）. One patient in the experimental group （1.12%） experienced an adverse event， which was determined to be associated with the progression of viral hepatitis. ConclusionShuganning injection can effectively improve liver injury， with good long-term efficacy and a low incidence rate of adverse reactions.

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 By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

ObjectiveTo study the clinical characteristics and influencing factors of rheumatoid arthritis （RA） in the patients with cold dampness obstruction syndrome. MethodsThe RA patients treated in the Department of Traditional Chinese Medicine and Rheumatology of the China-Japan Friendship Hospital from August 2022 to June 2024 were selected. The demographic information， clinical data， laboratory test results， and traditional Chinese medicine （TCM） symptom information were collected for syndrome differentiation， on the basis of which the characteristics and influencing factors of cold dampness obstruction syndrome were analyzed. ResultsA total of 258 RA patients were selected in this study， including 88 （34.1%） patients with cold dampness obstruction syndrome， 53 （20.5%） patients with dampness and heat obstruction syndrome， 31 （12.0%） patients with wind dampness obstruction syndrome， 29 （11.2%） patients with liver-kidney deficiency syndrome， 19 （7.4%） patients with Qi-blood deficiency syndrome， 14 （5.4%） patients with phlegm-stasis obstruction syndrome， 15 （5.8%） patients with stasis obstructing collateral syndrome and 9 （3.5%） patients with Qi-Yin deficiency syndrome. The patients were assigned into two groups of cold dampness obstruction syndrome and other syndromes. The group of cold dampness obstruction syndrome had lower joint fever， 28-tender joint count （TJC28）， and 28-joint disease activity score （DAS28）-C-reactive protein （CRP） and higher central sensitization， cold feeling of joints， fear of wind and cold， cold limbs， and abdominal distention than the group of other syndromes （P<0.05）. The binary logistic regression analysis showed that central sensitization （OR 5.749， 95%CI 2.116-15.616， P<0.001） and DAS28-CRP （OR 0.600， 95% CI 0.418-0.862， P=0.006） were the independent factors influencing cold dampness obstruction syndrome in RA. ConclusionCold dampness obstruction syndrome is a common syndrome in RA patients. It is associated with central sensitization， cold feeling of joints， abdominal distension and may be a clinical syndrome associated with central sensitization.

Poloxamer， as a non-ionic surfactant， exhibits a unique triblock [polyethylene oxide-poly （propylene oxide）-polyethylene oxide] structure， which endows it with broad application potential in various fields， including solid dispersion technology， nanotechnology， gel technology， biologics， gene engineering and 3D printing. As a carrier， it enhances the solubility and bioavailability of poorly soluble drugs. In the field of nanotechnology， it serves as a stabilizer etc.， enriching preparation methods. In gel technology， its self-assembly behavior and thermosensitive properties facilitate controlled drug release. In biologics， it improves targeting efficiency and reduces side effects. In gene engineering， it enhances delivery efficiency and expression levels. In 3D printing， it provides novel strategies for precise drug release control and the production of high-quality biological products. As a versatile material， poloxamer holds promising prospects in the pharmaceutical field.