Citations

Shock is a life-threatening state of circulatory failure characterized by inadequate tissue oxygen delivery and cellular hypoxia. Lactate has emerged as a central biomarker in the diagnosis, risk stratification, and management of shock, yet its interpretation is complex and context dependent. Although traditionally viewed as a marker of anaerobic metabolism and tissue hypoperfusion, hyperlactatemia in distributive shock, particularly sepsis, frequently reflects multifactorial mechanisms, including increased aerobic glycolysis, adrenergic stimulation, mitochondrial dysfunction, and impaired hepatic clearance. This review examines the pathophysiology and classification of shock, the biochemical basis of lactate production and clearance, and the prognostic significance of both static lactate levels and lactate kinetics. We synthesize evidence supporting lactate as a robust prognostic marker while highlighting limitations of lactate-targeted resuscitation strategies. Emerging data favor multimodal approaches integrating lactate trends with complementary perfusion markers such as capillary refill time and central venous oxygen saturation. Lactate should be interpreted as one component of a comprehensive physiological assessment rather than an isolated therapeutic target.

Importance The Surgery as Needed for Oesophageal Cancer (SANO) trial introduced active surveillance as a noninferior alternative to esophagectomy for patients with esophageal cancer who achieve a clinical complete response (cCR) after neoadjuvant chemoradiation (nCRT). However, concerns remain about recurrence risk, long-term survival, and quality-of-life trade-offs with organ-preserving strategies. Objective To evaluate the long-term comparative effectiveness of active surveillance vs standard esophagectomy in patients with cCR following nCRT for locally advanced esophageal cancer, using updated data from the SANO trial. Design, Setting, and Participants This decision analytical model used Markov modeling and probabilities and utility inputs derived from the SANO trial and existing literature. The base case was a 60-year-old male with good functional status and cT3N1M0 esophageal cancer achieving cCR after nCRT. Exposures Standard routine esophagectomy vs active surveillance after neoadjuvant chemoradiation. Main Outcomes and Measures The primary outcome was quality-adjusted life-years (QALYs); the secondary outcome was life-years. Additional model scenarios explored (1) quality-of-life impacts of esophagectomy modeled as a time-varying covariate and (2) 2-year outcomes to align with the SANO trial time horizon. Sensitivity analyses evaluated recurrence probabilities and surgery-related quality-of-life trade-offs. Results At 5 years, standard surgery yielded greater QALYs (1.74 vs 1.34; incremental gain of 0.40 QALYs or ~4.8 months in perfect health) and life-years (3.11 vs 2.41; incremental gain of 0.70 life-years or ~8.4 months) compared with active surveillance. However, at a 2-year horizon, active surveillance was preferred for QALYs (incremental gain of ~15 days), consistent with the SANO trial. Sensitivity analyses revealed the model favored active surveillance when the recurrence probability was less than 43%, the likelihood of local/resectable recurrence was greater than 94%, or the negative quality-of-life impact of esophagectomy was substantial. Modeling esophagectomy’s quality-of-life impact as time limited further strengthened surgery’s long-term QALY benefit. Conclusions and Relevance This study found that while active surveillance offers short-term quality-of-life benefits and may be appropriate in select patients, particularly those at low recurrence risk or with high surgical risk, esophagectomy remains the preferred strategy for maximizing long-term survival and QALYs. These findings support a nuanced, individualized approach to post-nCRT management, balancing organ preservation with long-term oncologic outcomes.

Background: Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide, accounting for approximately 10% of all cancer cases. Despite the proven effectiveness of conventional screening modalities such as colonoscopy and fecal immunochemical testing (FIT), their invasive nature, high cost, and limited patient compliance hinder widespread adoption. Recent advancements in artificial intelligence (AI) and bowel sound-based signal processing have enabled non-invasive approaches for gastrointestinal diagnostics. Among these, bowel sound analysis—historically considered subjective—has reemerged as a promising biomarker using digital auscultation and machine learning. Objective: This review explores the potential of AI-powered bowel sound analytics for early detection, screening, and characterization of colorectal cancer. It aims to assess current methodologies, summarize reported performance metrics, and highlight translational opportunities and challenges in clinical implementation. Methods: A narrative review was conducted across PubMed, Scopus, Embase, and Cochrane databases using the terms colorectal cancer, bowel sounds, phonoenterography, artificial intelligence, and non-invasive diagnosis. Eligible studies involving human bowel sound-based recordings, AI-based sound analysis, or machine learning applications in gastrointestinal pathology were reviewed for study design, signal acquisition methods, AI model architecture, and diagnostic accuracy. Results: Across studies using convolutional neural networks (CNNs), gradient boosting, and transformer-based models, reported diagnostic accuracies ranged from 88% to 96%. Area under the curve (AUC) values were ≥0.83, with F1 scores between 0.71 and 0.85 for bowel sound classification. In CRC-specific frameworks such as BowelRCNN, AI models successfully differentiate abnormal bowel sound intervals and spectral patterns associated with tumor-related motility disturbances and partial obstruction. Distinct bowel sound-based signatures—such as prolonged sound-to-sound intervals and high-pitched “tinkling” proximal to lesions—demonstrate the physiological basis for CRC detection through bowel sound-based biomarkers. Conclusions: AI-driven bowel sound analysis represents an emerging, exploratory research direction rather than a validated colorectal cancer screening modality. While early studies demonstrate physiological plausibility and technical feasibility, no large-scale, CRC-specific validation studies currently establish sensitivity, specificity, PPV, or NPV for cancer detection. Accordingly, bowel sound analytics should be viewed as hypothesis-generating and potentially complementary to established screening tools, rather than a near-term alternative to validated modalities such as FIT, multitarget stool DNA testing, or colonoscopy.

ABSTRACT Squid sucker ring teeth proteins (suckerins) have recently been shown to exhibit higher molecular‐level adhesion than mussel adhesive proteins–a well‐known class of wet‐resistant adhesive proteins–and can also assemble into nanoparticles in aqueous conditions. Herein, we present recombinant suckerin‐12 colloids and hydrogels as bioadhesives with strong wet adhesion and excellent in vivo biocompatibility. These colloids and hydrogels displayed low cytotoxicity, minimal immunogenicity, and negligible hemolysis, while outperforming fibrin glue in hemostasis, skin cell proliferation and migration, wound closure, and healing. Suckerin hydrogels formulated via riboflavin‐mediated di‐tyrosine crosslinking preserved β‐sheet content and elasticity at an optimal crosslinking density, resulting in enhanced adhesion, hemocompatibility, and in vivo wound closure. Transcriptomic analysis further revealed regulation of genes associated with hemostasis, angiogenesis, proliferation, and re‐epithelialization, with minimal immune activation. Together, these findings establish suckerin‐based adhesives as promising next‐generation biomedical materials that combine scalability, stability under oxidative conditions, and superior performance for external wound repair.

Background: Some studies have reported more severe chondral pathology and less successful hip arthroscopic outcomes in patients with acetabular subchondral cysts. Purpose/Hypothesis: The purpose of this study was to report multicenter arthroscopic outcomes of patients with and without acetabular bone cysts. It was hypothesized that patients with acetabular cysts would demonstrate inferior outcomes at minimum 2-year follow-up compared with patients without acetabular cysts. Study Design: Cohort study; Level of evidence, 3. Methods: A multicenter matched-pair study was performed across 6 medical centers with data from a large prospectively collected database. Inclusion criteria were adult patients who had undergone primary unilateral hip arthroscopy for femoroacetabular impingement syndrome (FAIS). The study group was defined by the presence of a superolateral acetabular subchondral cyst on preoperative imaging. A control group was matched on age; sex; body mass index (BMI); lateral center-edge angle (LCEA); alpha angle; arthroscopic treatments of femoroplasty, acetabuloplasty, and labral treatment (ie, repair, reconstruction, or debridement); Beck chondral grade; and minimum 2-year outcomes using visual analog scale (VAS) for pain, International Hip Outcome Tool-12 (iHOT-12), minimal clinically important difference (MCID), substantial clinical benefit (SCB), and Patient Acceptable Symptom State (PASS). Results: The study included 82 patients, of whom 41 composed the study group and 41 served as matched control patients. The study group had a mean age of 42.16 ± 11.26 years with 48.78% women and a mean BMI of 26.51 ± 4.31 kg/m 2 . Mean LCEA was 33.55°± 6.30°, and mean alpha angle was 70.22°± 9.71°. Mean Beck chondral grade was 2.59 ± 1.27 in the study group and 2.70 ± 0.95 in the matched control group ( P = .72). Two-year mean postoperative iHOT-12 scores for the study and control groups were 69.49 ± 24.51 and 73.24 ± 25.16, respectively ( P = .38), whereas mean postoperative VAS scores for pain were 18.84 ± 18.17 and 20.74 ± 21.39, respectively ( P = .70). The study group reached MCID in 82.93%, SCB in 58.54%, and PASS in 65.85% and were similar to those of the control group. Conclusion: Patients undergoing arthroscopic surgery for FAIS with acetabular cysts had similarly successful outcomes as patients without acetabular cysts. Acetabular subchondral cysts may not be a contraindication to hip arthroscopy in patients with FAIS who would otherwise be indicated for this surgery.

Abstract Chimeric antigen receptor (CAR) T-cell therapy enriched for a memory-like phenotype may persist and function longer than a nonenriched product, thereby improving duration of response (DOR). We conducted a phase I study with bb21217 (NCT03274219), an anti–B-cell maturation antigen CAR T-cell therapy manufactured in the presence of the phosphoinositide 3-kinase inhibitor bb007 to enrich for T cells with a memory-like phenotype, in patients with relapsed/refractory multiple myeloma (N = 72). No new safety concerns were raised with bb21217 therapy (three cases each of grade ≥3 cytokine release syndrome and grade ≥3 neurotoxicity were observed). The objective response rate was 69.4% and the median DOR was 23.8 (95% confidence interval, 16.8–34.8) months. Analysis of the drug product established an association between early memory phenotype and robust expansion and depth of response. Examination of baseline characteristics indicated that tumor burden and prior therapies influenced DOR. The data indicate that generation of CAR T cells early in a disease course when tumor burden is lower and source material exhibits a more naïve phenotype may maximize the clinical benefit potential of the drug product.

INTRODUCTION: Clostridioides difficile infection (CDI) presents a significant challenge in patients with inflammatory bowel disease (IBD), with high recurrence rates and complications. Predicting recurrent CDI (rCDI) in patients with IBD is crucial for implementing targeted interventions to improve patient outcomes. This study aimed to develop and validate a predictive model (RecurCDI-IBD) using supervised machine learning to identify patients with IBD at high risk of developing rCDI. METHODS: Data were collected from adult patients with IBD diagnosed with CDI between 2013 and 2021. Inclusion criteria included adult patients with a confirmed diagnosis of CDI and a history of IBD. The Gradient Boosting Machine learning model (XGBoost) was used to train a binary classification model. Feature engineering included demographic data (age and sex), clinical data (IBD subtype, medication use, and comorbidities), and laboratory data. The primary outcome was the occurrence of rCDI within 60 days of the initial CDI episode. RESULTS: The RecurCDI-IBD model achieved an accuracy of 80.05% and an Area Under the Curve of 0.88 for predicting rCDI. Key predictive features included IBD subtype, sex, specific medications (such as steroids and anti-TNF agents), and comorbidities (such as chronic pulmonary and renal disease). DISCUSSION: The RecurCDI-IBD model demonstrates good discriminatory ability with balanced precision and recall in identifying patients with IBD at higher risk for rCDI. These findings highlight the potential of data-driven approaches to support clinical risk assessment. Further studies incorporating larger and more diverse cohorts and prospective external validation are needed to confirm generalizability and optimize clinical applicability.