ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

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.

ObjectiveTo investigate the mechanisms by which the combination of berberine （BBR） and baicalin （BAI） ameliorates type 2 diabetes mellitus （T2DM） due to internal accumulation of dampness-heat from the perspectives of gut microbiota and metabolomics. MethodsAntibiotics were used to induce pseudo-sterile mice. Thirty pseudo-sterile mice were randomized into a normal fecal microbiota transplantation group （n=10） and a T2DM （syndrome of internal accumulation of dampness-heat） fecal microbiota transplantation group （n=20）. The mice were then administrated with suspensions of fecal microbiota from healthy volunteers and a patient with T2DM due to internal accumulation of dampness-heat by gavage， respectively. Each mouse received 200 µL suspension every other day for a total of 15 times to reshape the gut microbiota. The T2DM model mice were then assigned into a model group （n=8） and a BBR-BAI group （n=11）. BBR was administrated at a dose of 200 mg·kg^-1， and BAI was administrated in a ratio of BBR-BAI 10∶1 based on preliminary research findings. The administration lasted for 8 consecutive weeks. Fasting blood glucose （FBG）， glycated hemoglobin （HbA1c）， insulin （INS）， triglycerides （TG）， total cholesterol （CHOL）， low-density lipoprotein cholesterol （LDL-C）， high-density lipoprotein cholesterol （HDL-C）， aspartate aminotransferase （AST）， and alanine aminotransferase （ALT） levels were measured to evaluate the effects of the BBR-BAI combination on glucose and lipid metabolism and liver function in T2DM mice. Hematoxylin-eosin staining was employed to observe pathological changes in the colon tissue. The expression of claudin-1， zonula occludens-1 （ZO-1）， and occludin in the colon tissue was determined by Western blot. Real-time quantitative polymerase chain reaction（Real-time PCR） was employed to assess the levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， and interleukin-6 （IL-6） in the colon tissue. The fecal microbiota composition and differential metabolites were analyzed by 16S rRNA sequencing and ultra-high performance liquid chromatography-quadrupole-time of flight tandem mass spectrometry （UPLC-Q-TOF-MS）， respectively. ResultsThe BBR-BAI combination lowered the FBG， HbA1c， and INS levels （P<0.05， P<0.01） and alleviated insulin resistance （P<0.01） in T2DM mice. Additionally， BBR-BAI elevated the levels of ZO-1， occludin， and claudin-1 （P<0.05， P<0.01） and down-regulated the expression levels of TNF-α， IL-1β， and IL-6 in the colon （P<0.05， P<0.01）. The results of 16S rRNA sequencing showed that BBR-BAI increased the relative abundance of Ligilactobacillus， Phascolarctobacterium， and Akkermansia （P<0.05）， while significantly decreasing the relative abundance of Alistipes， Odoribacter， and Colidextribacter （P<0.05）. UPLC-Q-TOF-MS identified 28 differential metabolites， which were primarily involved in arachidonic acid metabolism and α-linolenic acid metabolism. ConclusionBBR-BAI can ameliorate T2DM due to internal accumulation of dampness-heat by modulating the relative abundance of various bacterial genera in the gut microbiota and the expression of fecal metabolites.

Methods: Seventy-five patients with atlas fracture were included from January 2015 to December 2020. Based on the anatomy of the fracture line, atlas fractures were divided into three types. Each type was divided into two subtypes according to the fracture displacement. Unweighted Cohen kappa coefficients were applied to evaluate the reliability and reproducibility. Results: According to the new classification, 17 cases of type A1, 12 of type A2, seven of type B1, 13 of type B2, 12 of type C1, and 14 of type C2 were identified. The K-values of the interobserver and intraobserver reliability were 0.846 and 0.912, respectively, for the new classification. The K-values of interobserver reliability for types A, B, and C were 0.843, 0.799, and 0.898, respectively. The K-values of intraobserver reliability for types A, B, and C were 0.888, 0.910, and 0.935, respectively. The mean K-values of the interobserver and intraobserver reliability for subtypes were 0.687 and 0.829, respectively. Conclusions The new classification of atlas fractures can cover nearly all atlas fractures. This system is the first to evaluate the severity of fractures based on the C1 articular facet and fracture displacement and strengthen the anatomy ring of the atlas. It is concise, easy to remember, reliable, and reproducible.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， network pharmacology， molecular docking and cell experiments， the active ingredients， possible targets and molecular mechanisms of Baoxin granules（BXG） regulating ferroptosis in the treatment of heart failure（HF） were explored. MethodsBXG intestinal absorption fluid was prepared by everted gut sac and the chemical composition contained therein were identified by UPLC-Q-TOF-MS. According to the obtained components， the potential targets of BXG were predicted， and the HF-related targets and related genes of ferroptosis were retrieved at the same time， and the intersecting targets were obtained by Venn diagram. In addition， the protein-protein interaction（PPI） network and the component-target network were constructed， and the core components and core targets were obtained by topological analysis. Then Gene Ontology（GO） function and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis were performed on the core targets， and molecular docking validation of the key targets and main components was carried out by AutoDockTools 1.5.7. H9c2 cells were used to establish a oxygen-glucose deprivation model， and the protective effect of BXG on cells was investigated by detecting cell viability， cell survival rate and reactive oxygen species（ROS） level. The protein expression levels of signal transducer and activator of transcription 3（STAT3）， phosphorylation（p）-STAT3 and glutathione peroxidase 4（GPX4） were detected by Western blot to clarify the regulatory effect of BXG on ferroptosis. ResultsA total of 61 chemical components in BXG intestinal absorption fluid were identified， and network pharmacology obtained 27 potential targets of BXG for the treatment of HF， as well as 139 signaling pathways. BXG may act on core targets such as STAT3， tumor protein p53（TP53）， epidermal growth factor receptor（EGFR）， JUN and prostaglandin-endoperoxide synthase 2（PTGS2） through core components such as glabrolide and limonin， which in turn intervene in lipid and atherosclerosis， phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）， endocrine resistance and other signaling pathways to exert therapeutic effects on HF. Molecular docking showed that the docking results of multiple groups of targets and compounds were good. In vitro cell experiments showed that compared with the blank group， the cell viability and survival rate of the model group were significantly decreased， the level of ROS was significantly increased（P<0.01）， the expression levels of STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 proteins were significantly decreased（P<0.05， P<0.01）. Compared with the model group， the cell viability and survival rate of the BXG group were significantly increased， the ROS level was significantly decreased（P<0.01）， the STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 protein levels were significantly increased（P<0.05， P<0.01）. ConclusionBXG may inhibit the occurrence of ferroptosis by up-regulating the expression of STAT3 and GPX4， thus exerting a therapeutic effect on HF， and flavonoids may be the key components of this role.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective:To investigate whether neoadjuvant therapy can improve the prognosis of patients with pancreatic cancer.Methods:A retrospective case-control study analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database on 12, 103 patients who underwent surgical treatment between January 1, 2010, and December 31, 2021. Patients were divided into the neoadjuvant therapy group ( n=3 276) and the upfront surgery group ( n=8 827) based on whether they received neoadjuvant treatment. The neoadjuvant therapy group included 2 342 patients receiving neoadjuvant chemotherapy and 934 patients receiving neoadjuvant chemoradiotherapy. The upfront surgery group consisted of 4 335 patients receiving adjuvant chemotherapy, 1 987 patients receiving adjuvant chemoradiotherapy, 63 patients receiving adjuvant radiotherapy, and 2 442 patients undergoing surgery alone. Propensity score matching was used to eliminate group differences and create a cohort with no statistical differences in other clinicopathological features except for the grouping variable. Variables such as age, gender, tumor location, race, population of residence, tumor diameter, household income, TNM stage, and information on radiotherapy and chemotherapy were used for 1∶1 case matching. T stage, N stage, and the use of radiotherapy or chemotherapy were matched exactly. After matching, 1 182 patients were included in each group: the neoadjuvant therapy group contained 1 155 patients receiving neoadjuvant chemoradiotherapy and 27 receiving neoadjuvant chemotherapy, while the upfront surgery group comprised 848 patients receiving adjuvant chemotherapy and 334 receiving adjuvant chemoradiotherapy. TNM staging was reported according to the 7th edition of the AJCC guidelines. The primary outcome was overall survival. Measurement data with skewed distributions were expressed as M( Q1, Q3), and intergroup comparisons were conducted using the Wilcoxon rank-sum test. Categorical data were compared using the chi-square test or the Fisher′s exact test. The Log-rank test and subgroup analyses to assess interactions between neoadjuvant therapy and subgroup in COX regression models were used to compare survival benefits across variables. Landmark analysis was performed to create segmented survival curves, studying the impact of neoadjuvant therapy on prognosis during different follow-up periods. Results:The neoadjuvant therapy group had a higher proportion of T 4 tumor involving celiac axis, superior mesenteric artery, and/or common hepatic artery compared to the upfront surgery group (14.7% vs 2.8%, P<0.001). Additionally, significant differences were observed between groups in terms of race, location, population of residence, age, tumor diameter, tumor stage, and adjuvant therapy regimen ( P<0.05). The median overall survival time in the neoadjuvant therapy group was 30 months, compared to 22 months in the upfront surgery group ( P<0.001). In the neoadjuvant therapy group, the median survival was 30 months for both neoadjuvant chemotherapy and chemoradiotherapy patients; in the upfront surgery group, it was 26 months for both adjuvant chemotherapy and chemoradiotherapy patients, 17 months for adjuvant radiotherapy patients, and 12 months for surgery-only patients. After propensity score matching, there were no differences in the distribution of clinical characteristics between groups ( P>0.05), and all patients in the matched cohort had received chemotherapy. The matched neoadjuvant therapy group had a longer median overall survival compared to the upfront surgery group (30 months vs 27 months, P<0.001). Subgroup interaction analysis revealed that T stage had a significant interaction with neoadjuvant therapy, both before (T 4 stage: HR=0.382, 95% CI: 0.319-0.458; T 2-T 3 stages: HR=0.696, 95% CI: 0.656-0.738; T 1 stage: HR=1.199, 95% CI: 0.867-1.657; interaction P<0.001) and after matching (T 4 stage: HR=0.581, 95% CI: 0.414-0.814; T 2-T 3 stages: HR=0.827, 95% CI: 0.734-0.931; T 1 stage: HR=1.320, 95% CI: 0.716-2.433; interaction P=0.043). Subgroup interaction analysis indicated that T 1 patients did not benefit from neoadjuvant therapy; survival curves plotted for matched T 1 patients showed no difference in survival between the neoadjuvant therapy group and the upfront surgery group ( P=0.323). Conversely, non-T 1 (T 2-T 4) stage patients showed significant survival benefits in both unmatched and matched cohorts ( P<0.001). Landmark analysis showing that the survival benefits occurred mainly in the early postoperative period of up to 3 years ( P<0.001), but there was no difference in overall survival between the neoadjuvant therapy group and the upfront surgery group of >3 years ( P>0.05). Patients with Arterial invasion (T 4 stage compared to T 1-T 3 stages) showed a similarly significant interaction with the benefit of neoadjuvant therapy in both the pre-matching cohort (interaction P<0.001) and the post-matching cohort (interaction P=0.037). Patients with T 4 stage disease in the neoadjuvant therapy group had longer overall survival compared to the upfront surgery group (median overall survival in pre-matching cohort: 30 months vs 13 months, P<0.001; median overall survival in post-matching cohort: 28 months vs 18 months, P=0.001). Among T 4 stage patients in the post-matching cohort, neoadjuvant therapy provided significant survival benefits during the early postoperative period of up to 3 years ( P=0.001). However, there was no difference in overall survival between the neoadjuvant therapy group and the direct surgery group beyond 3 years( P=0.729). Conclusions:The prognosis in the neoadjuvant therapy group was better than in the upfront surgery group. Propensity score matching and subgroup interaction analysis showed that non-T 1 and T 4 stage patients benefited more from neoadjuvant therapy, with benefits mainly seen in the early postoperative period (≤3 years).