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Accurate assessment of lymph node (LN) status is critical in cancer management, particularly in gynecological malignancies. However, preoperative identification of pathological LNs remains a significant challenge with current imaging modalities. Full-field optical coherence tomography (FF-OCT) is a non-invasive microscopic technique based on tissue reflectivity and light interference, providing real-time, high-resolution images in < 10 min, with no tissue preparation or alteration required. Our aim was to evaluate the diagnostic accuracy of FF-OCT in identifying LN metastatic foci measuring ≥ 0.2 mm in gynecological cancers, in an intraoperative setting. Comparative analysis of 80 fresh ex vivo LNs with FF-OCT versus gold standard pathology showed high accuracy (97.6%), sensitivity (92.3%), and specificity (98.2%) of FF-OCT. These results support the suitability of FF-OCT integration into clinical practice for real-time assessment of LN status, thereby improving intraoperative decision making while enabling subsequent routine histological analysis.

Introduction There is a demand for intraoperative diagnostic support and image guidance in oncological surgery. Novel techniques can provide images similar to histopathological slides within a few minutes. Optical coherence tomography (OCT) and full-field OCT (FF-OCT) provide images with resolution greater than a hundred micrometers without the need for exogenous contrast agents or specimen staining. The aim of this systematic review was to assess the current clinical applications of OCT and dynamic cell imaging (DCI) in oncologic surgery, examining the translation challenges and proposing perspectives for improving future clinical applications. Materials and Methods The study adhered to the PRISMA guidelines. PubMed, Google Scholar, and ClinicalTrials.gov were searched up to July 2024. Manuscripts reporting data on OCT and (D)-FF-OCT application in oncologic surgery were included in the qualitative analysis. Results Thirty-one studies met the inclusion criteria. Most were from the fields of dermatologic (25.8%) and breast cancer (29%) surgery, followed by prostate and bladder (9.6%), ovarian (9.6%), head and neck (6.4%), gastrointestinal (6.4%), hepato-biliary (3.2%), and general surgery (9.6%). The majority of articles focused on FF-OCT and DCI (80.6%). Compared with the gold standard of final pathology, the OCT sensitivity ranged between 66.7 and 94%, the specificity between 64 and 100%, and the accuracy between 73 and 96%. Conclusions The medical use of OCT has expanded from ophtalmology to other fields including gastroenterology and oncology and, with techniques such as FF-OCT and DCI, can enable rapid intraoperative diagnosis beyond classic histopathology.

Biomarkers that can facilitate disease detection, staging and prediction of outcome are highly desirable to improve survival and to help determine optimized treatment for colorectal cancer patients. microRNAs (miRNAs) are small non-coding RNAs that play a crucial role in gene regulatory networks. The deregulation of miRNA expression has been found in several types of cancer and may represent a novel class of cancer biomarkers. Our aim was to determine the miRNA signature of stage III colorectal cancer (CRC) tumors and to identify potential circulating miRNAs that may represent non-invasive biomarkers in CRC patients. Genome-wide microarray analysis of miRNA expression was performed on 12 paired tumor and non-tumor formalin-fixed paraffin-embedded tissues from stage III CRC patients. A selection of differentially overexpressed miRNAs was validated by quantitative real-time polymerase chain reaction (qRT-PCR) and determined in the serum of a set of 56 individuals (30 stage III CRC patients and 26 healthy individuals). Using 1.5-fold expression difference as a cut-off level, 43 miRNAs were identified as differentially expressed in tumor versus normal tissue. Using reverse transcription and qRT-PCR, 11 miRNAs (miR-135b, miR-141, miR-18a, miR-20a, miR-21, miR-224, miR-29a, miR-31, miR-34a, miR-92a and miR-96) were confirmed as significantly overexpressed in tumor samples when compared with normal samples. We were able to detect 9 of these 11 miRNAs in serum samples from CRC patients and healthy individuals. Serum levels of miR-18a and miR-29a were significantly higher in CRC patients when compared to levels in the controls (p<0.05). In conclusion, this study identified a substantial number of miRNAs which were differentially expressed in stage III colorectal tumors. Moreover, the findings provide relevant information concerning overexpressed tumoral miRNAs as potential circulating biomarkers and highlight serum miR-18a and miR-29a as promising biomarkers for the screening and monitoring of CRC patients.

This research supports the singularity of the Spanish case. The lessons we can learn are a product of the short transition in the mid 1880s from a city-based monetary system (supported by private actors) to a central banking system in the absence of a developed banking system with a nationwide scope, unlike what occurred in the rest of Western Europe. Introducing market arbitrage, we provide novel evidence – using new data – of how price formation in city-based money markets was driven by more than one price. Furthermore, factors such as market conditions, political circumstances and the asymmetrical development of market potential in the Spanish economic geography also played an important role. We also show new empirical support that transaction cost reduction was not associated with improving efficiency during the 1875–85 period when city-based money markets were still operating. The inland payment system was struggling even before its takeover by the Bank of Spain.

Understanding how genetic variants influence disease risk and complex traits (variant-to-function) is one of the major challenges in human genetics. Here we present a model-driven framework to leverage human genome-scale metabolic networks to define how genetic variants affect biochemical reaction fluxes across major human tissues, including skeletal muscle, adipose, liver, brain and heart. As proof of concept, we build personalised organ-specific metabolic flux models for 524,615 individuals of the INTERVAL and UK Biobank cohorts and perform a fluxome-wide association study (FWAS) to identify 4312 associations between personalised flux values and the concentration of metabolites in blood. Furthermore, we apply FWAS to identify 92 metabolic fluxes associated with the risk of developing coronary artery disease, many of which are linked to processes previously described to play in role in the disease. Our work demonstrates that genetically personalised metabolic models can elucidate the downstream effects of genetic variants on biochemical reactions involved in common human diseases. Here, the authors present a method to build genetically personalised metabolic models across tissues to estimate individualised reaction fluxes. A fluxome-wide association study in UK Biobank identifies fluxes associated with metabolites and coronary artery disease.

Techniques such as retroperitoneal graft placement have further enhanced the ability to replicate the physiology of the “native” pancreas. In our center, from January 2000, duodenojejunostomy (DJ) was the standard technique for exocrine drainage (n = 337). Herein, we report a series of 188 pancreas transplantations performed between May 2016 to July 2025, using a fully retrocolic graft position, systemic venous drainage and enteric drainage via duodenoduodenostomy. The primary endpoint was the assessment of intestinal events and their impact on graft and patient survival. A total of 14 patients (7.4%) experienced complications, including paralytic ileus (n = 2), intestinal obstruction (n = 4), duodenal dehiscence following pancreas transplantectomy (n = 1), anastomotic dehiscence (n = 5), and anastomotic bleeding (n = 2). Of these, 11 cases required relaparotomy for adhesiolysis (n = 2), internal hernia repair (n = 1), Hartmann’s procedure (n = 1), transplantectomy (n = 2), primary leak closure (n = 3), and hemostasis with duodenal re-anastomosis (n = 2). After a median follow-up of 42.8 months [IQR 21.8–71.1], graft survival at 1 and 5 years was 87% and 83.4%, respectively (P = 0.688 vs. DJ group), while patient survival was 100% and 98.2% (P = 0.031 vs. DJ group). Duodenoduodenostomy proved to be a feasible and effective technique, offering competitive outcomes in terms of graft and patient survival.

Identifying determinants of medication non-adherence in patients with multimorbidity would provide a step forward in developing patient-centered strategies to optimize their care. Medication appropriateness has been proposed to play a major role in medication non-adherence, reinforcing the importance of interdisciplinary medication review. This study examines factors associated with medication non-adherence among older patients with multimorbidity and polypharmacy. A cross-sectional study of non-institutionalized patients aged ≥65 years with ≥2 chronic conditions and ≥5 long-term medications admitted to an intermediate care center was performed. Ninety-three patients were included (mean age 83.0 ± 6.1 years). The prevalence of non-adherence based on patients’ multiple discretized proportion of days covered was 79.6% (n = 74). According to multivariable analyses, individuals with a suboptimal self-report adherence (by using the Spanish-version Adherence to Refills and Medications Scale) were more likely to be non-adherent to medications (OR = 8.99, 95% CI 2.80–28.84, p < 0.001). Having ≥3 potentially inappropriate prescribing (OR = 3.90, 95% CI 0.95–15.99, p = 0.059) was barely below the level of significance. These two factors seem to capture most of the non-adherence determinants identified in bivariate analyses, including medication burden, medication appropriateness and patients’ experiences related to medication management. Thus, the relationship between patients’ self-reported adherence and medication appropriateness provides a basis to implement targeted strategies to improve effective prescribing in patients with multimorbidity.

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics 1 . Here we examine a large cohort (the INTERVAL study 2 ; n  = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n  = 3,175; Olink, n  = 4,822), plasma metabolomics (Metabolon HD4, n  = 8,153), serum metabolomics (Nightingale, n  = 37,359) and whole-blood Illumina RNA sequencing ( n  = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank 3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK–STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores. A machine learning approach is used to analyse multi-omics (proteomics, metabolomics and transcriptomics) data, producing genetic scores for more than 17,000 biomolecular traits in human blood, and identifying possible associations with disease.

Background The treatment landscape for advanced non-small cell lung cancer (aNSCLC) has evolved rapidly since immuno-oncology (IO) therapies were introduced. This study used recent data to assess real-world treatment patterns and clinical outcomes in aNSCLC in the United Kingdom. Methods Electronic prescribing records of treatment-naive patients starting first-line (1 L) treatment for aNSCLC between June 2016 and March 2018 (follow-up until December 2018) in the United Kingdom were assessed retrospectively. Patient characteristics and treatment patterns were analyzed descriptively. Outcomes assessed included overall survival (OS), time to treatment discontinuation, time to next treatment, and real-world tumor response. Results In all, 1003 patients were evaluated (median age, 68 years [range, 28–93 years]; 53.9% male). Use of 1 L IO monotherapy (0–25.9%) and targeted therapy (11.8–15.9%) increased during the study period, but chemotherapy remained the most common 1 L treatment at all time points (88.2–58.2%). Median OS was 9.5 months (95% CI, 8.8–10.7 months) for all patients, 8.1 months (95% CI, 7.4–8.9 months) with chemotherapy, 14.0 months (95% CI, 10.7–20.6 months) with IO monotherapy, and 20.2 months (95% CI, 16.0–30.5 months) with targeted therapy. In the 28.6% of patients who received second-line treatment, IO monotherapy was the most common drug class (used in 51.6%). Conclusions Although use of 1 L IO monotherapy for aNSCLC increased in the United Kingdom during the study period, most patients received 1 L chemotherapy. An OS benefit for first-line IO monotherapy vs chemotherapy was observed but was numerically smaller than that reported in clinical trials. Targeted therapy was associated with the longest OS, highlighting the need for improved treatment options for tumors lacking targetable mutations.

Aim/hypothesis Here, our aim was to examine whether VLDL and apolipoprotein (apo) CIII induce endoplasmic reticulum (ER) stress, inflammation and insulin resistance in skeletal muscle. Methods Studies were conducted in mouse C2C12 myotubes, isolated skeletal muscle and skeletal muscle from transgenic mice overexpressing apoCIII. Results C2C12 myotubes exposed to VLDL showed increased levels of ER stress and inflammatory markers whereas peroxisome proliferator-activated receptor γ co-activator 1α (PGC-1α) and AMP-activated protein kinase (AMPK) levels were reduced and the insulin signalling pathway was attenuated. The effects of VLDL were also observed in isolated skeletal muscle incubated with VLDL. The changes caused by VLDL were dependent on extracellular signal-regulated kinase (ERK) 1/2 since they were prevented by the ERK1/2 inhibitor U0126 or by knockdown of this kinase by siRNA transfection. ApoCIII mimicked the effects of VLDL and its effects were also blocked by ERK1/2 inhibition, suggesting that this apolipoprotein was responsible for the effects of VLDL. Skeletal muscle from transgenic mice overexpressing apoCIII showed increased levels of some ER stress and inflammatory markers and increased phosphorylated ERK1/2 levels, whereas PGC-1α levels were reduced, confirming apoCIII effects in vivo. Finally, incubation of myotubes with a neutralising antibody against Toll-like receptor 2 abolished the effects of apoCIII on ER stress, inflammation and insulin resistance, indicating that the effects of apoCIII were mediated by this receptor. Conclusions/interpretation These results imply that elevated VLDL in diabetic states can contribute to the exacerbation of insulin resistance by activating ERK1/2 through Toll-like receptor 2.