Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

Background Platelet parameters are important indicators of cardiovascular risk, and environmental pollutants such as polychlorinated biphenyls (PCBs) may impair platelet function through oxidative stress. Objective To investigate the differential effects of single and mixed exposure to PCBs on platelet parameters among individuals with normal glucose tolerance (NGT), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM), and to evaluate the potential modifying role of a healthy lifestyle. Methods This study included 2249 participants (including 707 with NGT, 759 with IFG, and 783 with T2DM). Plasma PCB concentrations were measured using triple quadrupole gaschromatography-tandem mass spectrometry. Generalized linear regression was used to assess the associations between individual PCB congeners and platelet parameters. Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) models were used to evaluate the overall effects of PCBs mixture exposure on platelet parameters across different glycemic states, as well as its interaction with healthy lifestyle score (HLS). Results Generalized linear regression analyses showed significant differences in the effects of PCBs on platelet parameters across different glycemic states (P<0.05). After adjusting for confounders, PCBs mixture exposure was significantly associated with lower platelet counts (PLT) in individuals with NGT (b=−10.60, 95%CI: −16.48, −4.71) and IFG (b=−12.91, 95%CI: −18.90, −6.92), whereas no significant association was observed in individuals with T2DM (P=0.051). Mean platelet volume (MPV) and platelet-large cell ratio (P-LCR) increased significantly with higher PCBs exposure levels across all three groups (P<0.05). BKMR analysis showed a positive association between PCBs mixture exposure and P-LCR, with the strongest association observed in the NGT group. Furthermore, a significant interaction was observed between HLS and PCBs mixture exposure, and a higher HLS attenuated the effects of PCBs on P-LCR. Conclusion Glycemic glycemic states may modify the effects of PCBs on platelets. Individuals with NGT appear more sensitive to PCBs exposure, whereas the T2DM state may attenuate this effect. Moreover, healthy lifestyles, including not smoking, moderate alcohol consumption, maintaining moderate-to-high physical activity, a healthy diet, and an appropriate body mass index (BMI), may mitigate the adverse effects of most PCBs on platelet parameters.

Background Platelet parameters are important indicators of cardiovascular risk, and environmental pollutants such as polychlorinated biphenyls (PCBs) may impair platelet function through oxidative stress. Objective To investigate the differential effects of single and mixed exposure to PCBs on platelet parameters among individuals with normal glucose tolerance (NGT), impaired fasting glucose (IFG), and type 2 diabetes mellitus (T2DM), and to evaluate the potential modifying role of a healthy lifestyle. Methods This study included 2249 participants (including 707 with NGT, 759 with IFG, and 783 with T2DM). Plasma PCB concentrations were measured using triple quadrupole gaschromatography-tandem mass spectrometry. Generalized linear regression was used to assess the associations between individual PCB congeners and platelet parameters. Quantile g-computation (QGC) and Bayesian kernel machine regression (BKMR) models were used to evaluate the overall effects of PCBs mixture exposure on platelet parameters across different glycemic states, as well as its interaction with healthy lifestyle score (HLS). Results Generalized linear regression analyses showed significant differences in the effects of PCBs on platelet parameters across different glycemic states (P<0.05). After adjusting for confounders, PCBs mixture exposure was significantly associated with lower platelet counts (PLT) in individuals with NGT (b=−10.60, 95%CI: −16.48, −4.71) and IFG (b=−12.91, 95%CI: −18.90, −6.92), whereas no significant association was observed in individuals with T2DM (P=0.051). Mean platelet volume (MPV) and platelet-large cell ratio (P-LCR) increased significantly with higher PCBs exposure levels across all three groups (P<0.05). BKMR analysis showed a positive association between PCBs mixture exposure and P-LCR, with the strongest association observed in the NGT group. Furthermore, a significant interaction was observed between HLS and PCBs mixture exposure, and a higher HLS attenuated the effects of PCBs on P-LCR. Conclusion Glycemic glycemic states may modify the effects of PCBs on platelets. Individuals with NGT appear more sensitive to PCBs exposure, whereas the T2DM state may attenuate this effect. Moreover, healthy lifestyles, including not smoking, moderate alcohol consumption, maintaining moderate-to-high physical activity, a healthy diet, and an appropriate body mass index (BMI), may mitigate the adverse effects of most PCBs on platelet parameters.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Colorectal cancer (CRC) often spreads to the liver, necessitating surgical treatment for CRC liver metastasis (CRLM). Iron-deficiency anemia is common in CRC patients and is associated with fatigue and weakness. This study investigated the effects of iron-deficiency anemia on the outcomes of surgical resection of CRLM. Methods: This population-based, retrospective study evaluated data from adults ≥20 years old with CRLM who underwent hepatic resection. All patient data were extracted from the 2005–2018 US National (Nationwide) Inpatient Sample (NIS) database. The outcome measures were in-hospital outcomes including 30-day mortality, unfavorable discharge, and prolonged length of hospital stay (LOS), and short-term complications such as bleeding and infection. Associations between iron-deficiency anemia and outcomes were determined using logistic regression analysis. Results: Data from 7,749 patients (representing 37,923 persons in the United States after weighting) were analyzed. Multivariable analysis revealed that iron-deficiency anemia was significantly associated with an increased risk of prolonged LOS (adjusted odds ratio [aOR], 2.76; 95% confidence interval [CI], 2.30–3.30), unfavorable discharge (aOR, 2.42; 95% CI, 1.83–3.19), bleeding (aOR, 5.05; 95% CI, 2.92–8.74), sepsis (aOR, 1.60; 95% CI, 1.04–2.46), pneumonia (aOR, 2.54; 95% CI, 1.72–3.74), and acute kidney injury (aOR, 1.71; 95% CI, 1.24–2.35). Subgroup analyses revealed consistent associations between iron-deficiency anemia and prolonged LOS across age, sex, and obesity status categories. Conclusion In patients undergoing hepatic resection for CRLM, iron-deficiency anemia is an independent risk factor for prolonged LOS, unfavorable discharge, and several critical postoperative complications. These findings underscore the need for proactive anemia management to optimize surgical outcomes.

Background/Aims: Treatment indications for patients with chronic hepatitis B (CHB) remain contentious, particularly for patients with mild alanine aminotransferase (ALT) elevation. We aimed to evaluate treatment effects in this patient population. Methods: This rollover study extended a placebo-controlled trial that enrolled non-cirrhotic patients with CHB and ALT levels below two times the upper limit of normal. Following 3 years of randomized intervention with either tenofovir disoproxil fumarate (TDF) or placebo, participants were rolled over to open-label TDF for 3 years. Liver biopsies were performed before and after the treatment to evaluate histopathological changes. Virological, biochemical, and serological outcomes were also assessed (NCT02463019). Results: Of 146 enrolled patients (median age 47 years, 80.8% male), 123 completed the study with paired biopsies. Overall, the Ishak fibrosis score decreased in 74 (60.2%), remained unchanged in 32 (26.0%), and increased in 17 (13.8%) patients (p<0.0001). The Knodell necroinflammation score decreased in 58 (47.2%), remained unchanged in 29 (23.6%), and increased in 36 (29.3%) patients (p=0.0038). The proportion of patients with an Ishak score ≥ 3 significantly decreased from 26.8% (n=33) to 9.8% (n=12) (p=0.0002). Histological improvements were more pronounced in patients switching from placebo. Virological and biochemical outcomes also improved in placebo switchers and remained stable in patients who continued TDF. However, serum HBsAg levels did not change and no patient cleared HBsAg. Conclusions In CHB patients with minimally raised ALT, favorable histopathological, biochemical, and virological outcomes were observed following 3-year TDF treatment, for both treatment-naïve patients and those already on therapy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Gastric cancer with peritoneal metastasis (GCPM) is a common and lethal manifestation of advanced gastric cancer, with a median survival of only 5-11 months. This consensus was developed by 30 experts from Asia (China, Japan, Korea, and Singapore) using the Delphi method and the GRADE evidence grading system. A total of 29 statements were formulated, covering the diagnosis and assessment of GCPM, indications for laparoscopic exploration and NIPS (normothermic intraperitoneal and systemic treatment), treatment regimens, prevention and management of complications, criteria for conversion surgery, and postoperative intraperitoneal therapy. The consensus aims to standardize clinical practice and improve the prognosis of patients with GCPM.

Purpose: Colorectal cancer (CRC) often spreads to the liver, necessitating surgical treatment for CRC liver metastasis (CRLM). Iron-deficiency anemia is common in CRC patients and is associated with fatigue and weakness. This study investigated the effects of iron-deficiency anemia on the outcomes of surgical resection of CRLM. Methods: This population-based, retrospective study evaluated data from adults ≥20 years old with CRLM who underwent hepatic resection. All patient data were extracted from the 2005–2018 US National (Nationwide) Inpatient Sample (NIS) database. The outcome measures were in-hospital outcomes including 30-day mortality, unfavorable discharge, and prolonged length of hospital stay (LOS), and short-term complications such as bleeding and infection. Associations between iron-deficiency anemia and outcomes were determined using logistic regression analysis. Results: Data from 7,749 patients (representing 37,923 persons in the United States after weighting) were analyzed. Multivariable analysis revealed that iron-deficiency anemia was significantly associated with an increased risk of prolonged LOS (adjusted odds ratio [aOR], 2.76; 95% confidence interval [CI], 2.30–3.30), unfavorable discharge (aOR, 2.42; 95% CI, 1.83–3.19), bleeding (aOR, 5.05; 95% CI, 2.92–8.74), sepsis (aOR, 1.60; 95% CI, 1.04–2.46), pneumonia (aOR, 2.54; 95% CI, 1.72–3.74), and acute kidney injury (aOR, 1.71; 95% CI, 1.24–2.35). Subgroup analyses revealed consistent associations between iron-deficiency anemia and prolonged LOS across age, sex, and obesity status categories. Conclusion In patients undergoing hepatic resection for CRLM, iron-deficiency anemia is an independent risk factor for prolonged LOS, unfavorable discharge, and several critical postoperative complications. These findings underscore the need for proactive anemia management to optimize surgical outcomes.