Pancreatic ductal adenocarcinoma (PDAC) exhibits the highest incidence of perineural invasion among all solid tumors. The intricate interplay between tumors and the nervous system plays an important role in PDAC tumorigenesis, progression, recurrence, and metastasis. Various clinical symptoms of PDAC, including anorexia and cancer pain, have been linked to aberrant neural activity, while the presence of perineural invasion is a significant prognostic indicator. The use of conventional neuroactive drugs and neurosurgical interventions for PDAC patients is on the rise. An in-depth exploration of tumor–nervous system crosstalk has revealed novel therapeutic strategies for mitigating PDAC progression and effectively relieving symptoms. In this comprehensive review, we elucidate the regulatory functions of tumor–nervous system crosstalk, provide a succinct overview of the relationship between tumor–nervous system dialogue and clinical symptomatology, and deliberate the current research progress and forthcoming avenues of neural therapy for PDAC. 

Tumor microenvironment crosstalk between tumors and the nervous system in pancreatic cancer: Molecular mechanisms and clinical perspectives.

Objectives Our aim was to investigate the interactive causal effects between gut microbiota and host urate metabolism and explore the underlying mechanism using genetic methods. Methods We extracted summary statistics from the abundance of 211 microbiota taxa from the MiBioGen (N =18,340), 205 microbiota metabolism pathways from the Dutch Microbiome Project (N =7738), gout from the Global Biobank Meta-analysis Initiative (N =1,448,128), urate from CKDGen (N =288,649), and replication datasets from the Global Urate Genetics Consortium (N gout =69,374; N urate =110,347). We used linkage disequilibrium score regression and bidirectional Mendelian randomization (MR) to detect genetic causality between microbiota and gout/urate. Mediation MR and colocalization were performed to investigate potential mediators in the association between microbiota and urate metabolism. Results Two taxa had a common causal effect on both gout and urate, whereas the Victivallaceae family was replicable. Six taxa were commonly affected by both gout and urate, whereas the Ruminococcus gnavus group genus was replicable. Genetic correlation supported significant results in MR. Two microbiota metabolic pathways were commonly affected by gout and urate. Mediation analysis indicated that the Bifidobacteriales order and Bifidobacteriaceae family had protective effects on urate mediated by increasing docosahexaenoic acid. These two bacteria shared a common causal variant rs182549 with both docosahexaenoic acid and urate, which was located within MCM6/LCT locus. Conclusions Gut microbiota and host urate metabolism had a bidirectional causal association, implicating the critical role of host-microbiota crosstalk in hyperuricemic patients. Changes in gut microbiota can not only ameliorate host urate metabolism but also become a foreboding indicator of urate metabolic diseases.

/pdf/dissecting-the-causal-effect-between-gut-microbiota-dha-and-inq28loz.pdf

Dissecting the causal effect between gut microbiota, DHA, and urate metabolism: A large-scale bidirectional Mendelian randomization

BACKGROUND
Metformin has the potential for treating numerous diseases, but there are still many unrecognized and unreported adverse events (AEs).


METHODS
We selected data from the United States FDA Adverse Event Reporting System (FAERS) database from the first quarter (Q1) of 2004 to the fourth quarter (Q4) of 2022 for disproportionality analysis to assess the association between metformin and related adverse events.


RESULTS
In this study 10,500,295 case reports were collected from the FAERS database, of which 56,674 adverse events related to metformin were reported. A total of 643 preferred terms (PTs) and 27 system organ classes (SOCs) that were significant disproportionality conforming to the four algorithms simultaneously were included. The SOCs included metabolic and nutritional disorders (p = 0.00E + 00), gastrointestinal disorders (p = 0.00E + 00) and others. PT levels were screened for adverse drug reaction (ADR) signals such as acute pancreatitis (p = 0.00E + 00), melas syndrome, pemphigoid (p = 0.00E + 00), skin eruption (p = 0.00E + 00) and drug exposure during pregnancy (p = 0.00E + 00).


CONCLUSION
Most of our results were consistent with the specification, but some new signals of adverse reactions such as acute pancreatitis were not included. Therefore, further studies are needed to validate unlabeled adverse reactions and provide important support for clinical monitoring and risk identification of metformin.

Metformin adverse event profile: a pharmacovigilance study based on the FDA Adverse Event Reporting System (FAERS) from 2004 to 2022.

The prevalence of obesity, diabetes mellitus (DM), and pancreatic cancer (PC) has been consistently increasing in the last two decades worldwide. Sharing various influential risk factors in genetics and environmental inducers in pathogenesis, the close correlations of these three diseases have been demonstrated in plenty of clinical studies using multiple parameters among different populations. On the contrary, most measures aimed to manage and treat obesity and DM effectively reduce the risk and prevent PC occurrence, yet certain drugs can inversely promote pancreatic carcinogenesis instead. Most importantly, an elevation of blood glucose with or without a reduction in body weight, along with other potential tools, may provide valuable clues for detecting PC at an early stage in patients with obesity and DM, favoring a timely intervention and prolonging survival. Herein, the epidemiological and etiological correlations among these three diseases and the supporting clinical evidence of their connections are first summarized to favor a better and more thorough understanding of obesity- and DM-related pancreatic carcinogenesis. After comparing the distinct impacts of different weight-lowering and anti-diabetic treatments on the risk of PC, the possible diagnostic implications of hyperglycemia and weight loss in PC screening are also addressed in detail. 

Obesity, diabetes mellitus, and pancreatic carcinogenesis: Correlations, prevention, and diagnostic implications.

The need for a common education and training track in surgical oncology across Europe has been emphasized. ESSO provides several hands-on courses for skills training and face-to-face discussions. The core curriculum provides a framework for the overall theoretical requirements in surgical oncology. The UEMS/EBSQ fellowship exam is designed to test core competencies in the candidate's core knowledge in their prespecified area of expertise. A core set of points for each cancer type is lacking. Hence, a condensed outline of themed expected to be covered in the curriculum and relevant to an optimal practice in surgical oncology is provided. This article outlines pancreatic cancer. 

Pancreatic cancer.

1Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Fudan University, Shanghai, China 2Research Units of Embryo Original Diseases, Chinese Academy of Medical Sciences, Shanghai, China 3Key Laboratory of Reproductive Genetics (Ministry of Education), Zhejiang University School of Medicine, Hangzhou, China 4Shanghai Key Laboratory of Embryo Original Diseases, Shanghai, China

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/ctm2.969

Diabetes predisposition inherited through maternal germline

Background Elevated serum uric acid (SUA) correlates with inflammation, but the pan-immune inflammation value (PIV)—a novel integrated inflammatory marker—has not been explored in relation to SUA. We investigated cross-sectional and longitudinal PIV-SUA associations. Methods We analyzed 5,766 participants aged ≥60 years from a 2018 cardiovascular examination cohort with 2022 follow-up. The PIV was calculated as neutrophil number × platelet number × monocyte number/lymphocyte number, with cell counts expressed as ×1000 cells/μL. Hyperuricemia was defined as SUA concentrations ≥ 420 μmol/L (7 mg/dL) in males and ≥ 360 μmol/L (6 mg/dL) in females. Cross-sectional associations were assessed via multivariate linear/logistic regression; longitudinal associations via Cox regression. Results At baseline, hyperuricemia prevalence was 22.4% among 5,766 participants (mean age 68.5 years). Restricted cubic spline showed a nonlinear PIV-SUA relationship. In fully adjusted models, each 1-SD PIV increase associated with higher SUA (β ± SE: 3.7 ± 1.1; P<0.0001). PIV quartiles (vs. lowest) showed β values: Q2 = 7.5, Q3 = 6.7, Q4 = 12.5 (P trend<0.001). Logistical regression revealed each 1-SD PIV increase linked to higher hyperuricemia risk (OR = 1.12, 95%CI 1.05-1.29; P = 0.0003). PIV quartiles (vs. lowest) had ORs: Q2 = 1.27, Q3 = 1.23, Q4 = 1.54 (P trend<0.001). Over 4-year follow-up, Cox regression indicated a J-curve relationship between PIV and SUA/hyperuricemia, with the lowest risk at PIV quartile 2. Conclusions PIV showed a nonlinear relationship with serum uric acid and hyperuricemia in cross-sectional analyses, while exhibiting a J-curve relationship in longitudinal studies. These suggest dynamic interactions between inflammatory markers and uric acid metabolism, dependent on inflammation duration.

Cross-sectional and longitudinal associations between pan-immune-inflammation value and serum uric acid

Time in target range of systolic blood pressure and eGFR slope in patients with type 2 diabetes.

Diastolic and Systolic Blood Pressure Time in Target Range as a Cardiovascular Risk Marker in Patients with Type 2 Diabetes A Post Hoc Analysis of ACCORD BP Trial.

Current guidelines for dyslipidemia management recommend that the LDL-C goal be lower than 70 mg/dL. The present study investigated the prognostic significance of visit-to-visit variability in LDL-C, and minimum and maximum LDL-C during follow-up in diabetes mellitus.The risk of outcomes in relation to visit-to-visit LDL-C variability was investigated in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Lipid trial. LDL-C variability indices were coefficient of variation (CV), variability independent of the mean (VIM), and average real variability (ARV). Multivariable Cox proportional hazards models were employed to estimate the adjusted hazard ratio (HR) and 95% confidence interval (CI).Compared with the placebo group (n=2667), the fenofibrate therapy group (n=2673) had a significantly (P<0.01) lower mean plasma triglyceride (152.5 vs. 178.6 mg/dL), and total cholesterol (158.3 vs.162.9 mg/dL) but a similar mean LDL-C during follow-up (88.2 vs. 88.6 mg/dL, P>0.05). All three variability indices were associated with primary outcome, total mortality and cardiovascular mortality both in the total population and in the fenofibrate therapy group but only with primary outcome in the placebo group. The minimum LDL-C but not the maximum during follow-up was significantly associated with various outcomes in the total population, fenofibrate therapy and placebo group. The minimum LDL-C during follow-up ≥70 mg/dL was associated with an increased risk for various outcomes.Visit-to-visit variability in LDL-C was a strong predictor of outcomes, independent of mean LDL-C. Patients with LDL-C controlled to less than 70 mg/dL during follow-up might have a benign prognosis. ClinicalTrials.gov number: NCT00000620. 

/pdf/prognostic-significance-of-visit-to-visit-variability-and-35nsl9se.pdf

Prognostic significance of visit-to-visit variability, and maximum and minimum LDL cholesterol in diabetes mellitus

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