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Survival scenarios of patients with localized and metastatic pancreatic adenocarcinoma:A population-based study
No full textPancreatic adenocarcinoma (PAC) is notorious for its poor survival. The provision of survival scenarios-that is, best-case, typical and worst-case scenarios-could prove valuable to patients and clinicians. This study investigated survival scenarios and how these have changed over a period of 16 years for patients with PAC. Data from the Netherlands Cancer Registry were used to identify patients with localized and metastatic PAC (2005-2021). Survival scenarios, including best-case, upper-typical, typical (median), lower-typical, and worst-case, were estimated based on survival curve percentiles (p10, p25, p50, p75, and p90). Annual differences were assessed for significance using weighted linear regression analyses. Factors associated with these scenarios were identified through univariable tests. Overall, 14,622 patients with localized and 20,199 with metastatic PAC were included. For patients with localized PAC, the best, upper-typical and typical survival scenarios improved statistically significant with average annual improvement of 1.54 (95%CI: 1.2-1.88), 0.67 (0.56-0.78), and 0.24 (0.19-0.29) months, respectively. For patients with metastatic PAC the best and upper-typical survival scenarios increased statically significantly with annual improvement of 0.28 (0.21-0.34) and 0.06 (0.02-0.09) months, respectively. The best-case and upper-typical scenarios were associated with younger patients, more aggressive disease-focused treatments, fewer comorbidities, and better overall performance status. Over the past 16 years, survival improvements in patients with PAC have been most notable in these scenarios. Although the absolute gains were modest, these results offer encouraging potential for advancements in life-prolonging care for this type of cancer
Obesity and metabolic syndrome in adults with a 22q11.2 microdeletion
No full textObjective: Copy number variations (CNVs) may contribute to medical conditions. However, research on the impact of individual CNVs on endocrine disease is limited. This study aimed to provide new data on obesity and metabolic syndrome (MetS) in adults with microdeletion 22q11.2, the pathogenic CNV associated with 22q11.2 deletion syndrome. Methods: We examined prevalence rates of obesity and MetS in 103 adults with a typical 22q11.2 deletion (45.2% male, at median age 30.0 (range 17–71) years) and compared these rates with population-based data. Generalized obesity was defined by a body mass index (BMI) ≥ 30 kg/m 2, abdominal obesity by a waist circumference (WC) of ≥102 cm in males and ≥88 cm in females, and MetS by standard Joint Interim Statement criteria. General linear models were used to examine the independent associations of age, sex, congenital heart defect, smoking, and antipsychotic use with BMI, WC, and the presence of MetS. Results: Prevalence rates of generalized obesity (32.0%), abdominal obesity (51.5%), and MetS (33.0%) were significantly higher compared to a population-based cohort (15.7% (P < 0.0001), 36.1% (P = 0.002), and 15.2% (P < 0.0001), respectively). In antipsychotic naïve subjects, significant correlations were observed between age and BMI (r = 0.54, P < 0.001), and age and WC (r = 0.60, P < 0.001). These correlations were not present in individuals taking antipsychotic medication. The models predicting BMI (F(5, 97) = 3.083, R 2 = 0.137, P = 0.01) and WC (F(5, 92) = 5.985, R 2 = 0.245, P < 0.001) were significant. Only age was individually predictive of outcomes (P < 0.05 and P < 0.001). The model predicting MetS was also significant (P < 0.001), with higher age being the only factor associated with MetS (OR = 1.07, 95% CI = 1.03–1.12, P < 0.001). Conclusions: Generalized and abdominal obesity, as well as MetS, appear to be common in adults with 22q11.2 deletion syndrome, emphasizing the importance of careful monitoring from a young age. These findings contribute to the limited knowledge about the association between pathogenic CNVs, obesity, and MetS.</p
Versatile immobilization of mimicking peptides on additively manufactured functionalized α-amino acid based poly(ester amide)s
No full textα-Amino acid based polyester amides (AA-PEAs) exhibit remarkable properties, including biocompatibility, biodegradability, flexibility, thermal stability, and mechanical integrity. The incorporation of α-amino acids enhances cytocompatibility, hydrogen bonding, and favorable cell-polymer interactions, making AA-PEAs appealing for biomedical applications, notably tissue engineering. However, addressing complex tissue regeneration requires additional enhancements. Introducing biologically instructive factors, like growth factors and peptides, becomes essential to facilitate cell growth, proliferation, and differentiation. This study explores α-amino acid based functionalized polyester amides (AA-FPEAs) for their potential in tissue engineering, focusing on their underexplored role as thermoplastic resources for fused deposition modeling (FDM). Novel AA-FPEAs with alkyne moieties were synthesized and additively manufactured via FDM, highlighting their structure–property correlation. Employing a facile copper-free click chemistry strategy, we successfully attached a CGRGDS mimicking peptide to AA-FPEAs using UV light and a photoinitiator with water as a solvent. UV–Vis analysis confirmed the feasibility of the click reaction, and TOF-SIMS analysis verified CGRGDS attachment on AA-FPEA films and AM scaffolds. In vitro evaluation further demonstrated that AA-FPEAs support cell growth and proliferation, highlighting their biocompatibility. These findings underscore the potential of AA-FPEAs as versatile functionalized biomaterials for tissue engineering applications.</p
Fluid status assessment in heart failure patients:pilot validation of the Maastricht Decompensation Questionnaire
No full textBackground: eHealth products have the potential to enhance heart failure (HF) care by identifying at-risk patients. However, existing risk models perform modestly and require extensive data, limiting their practical application in clinical settings. This study aims to address this gap by validating a more suitable risk model for eHealth integration. Methods: We developed the Maastricht Decompensation Questionnaire (MDQ) based on expert opinion to assess HF patients’ fluid status using common signs and symptoms. Subsequently, the MDQ was administered to a cohort of HF outpatients at Maastricht University Medical Centre. Patients with ≥ 10 MDQ points were categorised as ‘decompensated’, patients with < 10 MDQ points as ‘not decompensated’. HF nurses, blinded to MDQ scores, served as the gold standard for fluid status assessment. Patients were classified as ‘correctly’ if MDQ and nurse assessments aligned; otherwise, they were classified as ‘incorrectly’. Results: A total of 103 elderly HF patients were included. The MDQ classified 50 patients as ‘decompensated’, with 17 of them being correctly classified (34%). Additionally, 53 patients were categorised as ‘not decompensated’, with 48 of them being correctly classified (90%). The calculated area under the curve was 0.69 (95% confidence interval: 0.57–0.81; p < 0.05). Cronbach’s alpha reliability coefficient for the MDQ was 0.85. Conclusions: The MDQ helps identify decompensated HF patients through clinical signs and symptoms. Further trials with larger samples are needed to confirm its validity, reliability and applicability. Tailoring the MDQ to individual patient profiles may improve its accuracy.</p
Daily blood flow restriction does not affect muscle fiber capillarization and satellite cell content during 2 wk of bed rest in healthy young men
No full textThe present study assessed whether single-leg daily blood flow restriction (BFR) treatment attenuates the decline in muscle fiber size, capillarization, and satellite cell (SC) content during 2 wk of bed rest in healthy, young men. Twelve healthy, young men (age: 24 ± 3 yr; BMI: 23.7 ± 3.1 kg/m 2) were subjected to 2 wk of bed rest, during which one leg was exposed to three times daily 5 min of BFR, whereas the contralateral leg received sham treatment [control (CON)]. Muscle biopsies were obtained from the m. vastus lateralis from both the BFR and CON legs before and immediately after 2 wk of bed rest. Types I and II muscle fiber size, myonuclear content, capillarization, and SC content were assessed by immunohistochemistry. No significant decline in either type I or type II muscle fiber size was observed following bed rest, with no differences between the CON and BFR legs (P > 0.05). Type I muscle fiber capillary density increased in response to bed rest in both legs (P < 0.05), whereas other muscle fiber capillarization measures remained unaltered. SC content decreased in both type I (from 7.4 ± 3.2 to 5.9 ± 2.7 per 100 fibers) and type II (from 7.2 ± 3.4 to 6.5 ± 3.2 per 100 fibers) muscle fibers (main effect of time P ¼ 0.018), with no significant differences between the BFR and CON legs (P > 0.05). In conclusion, 2 wk of bed rest has no effect on muscle capillarization and decreases the SC content, and daily BFR treatment does not affect skeletal muscle fiber size and SC content in healthy, young men.</p
Heterogeneity and Penumbra of White Matter Hyperintensities in Small Vessel Diseases Determined by Quantitative MRI
No full textBACKGROUND: White matter hyperintensities (WMHs) are established structural imaging markers of cerebral small vessel disease. The pathophysiologic condition of brain tissue varies over the core, the vicinity, and the subtypes of WMH and cannot be interpreted from conventional magnetic resonance imaging. We aim to improve our pathophysiologic understanding of WMHs and the adjacently injured normal-appearing white matter in terms of microstructural and microvascular alterations using quantitative magnetic resonance imaging in patients with sporadic and genetic cerebral small vessel disease. METHODS: Structural T2-weighted imaging, multishell diffusion imaging, and dynamic contrast-enhanced magnetic resonance imaging were performed at 3T in 44 participants with sporadic cerebral small vessel disease and 32 participants with monogenic cerebral small vessel disease (cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy; 59±12 years, 41 males) between June 2017 and May 2020 as part of the prospective, multicenter (Edinburgh, the United Kingdom; Maastricht, the Netherlands; and Munich, Germany), observational INVESTIGATE-SVDs study (Imaging Neurovascular, Endothelial and Structural Integrity in Preparation to Treat Small Vessel Diseases). The mean diffusivity, free water content, and perfusion (all derived from multishell diffusion imaging), as well as the blood-brain barrier leakage and plasma volume fraction (derived from dynamic contrast-enhanced magnetic resonance imaging), were compared between deep and periventricular WMH types using paired t tests. Additional spatial analyses were performed inside and outside the WMH types to determine the internal heterogeneity and the extent of the penumbras, that is, adjacent white matter at risk for conversion to WMH. RESULTS: Periventricular WMH had higher mean diffusivity, higher free water content, and more plasma volume compared with deep WMH (P<0.001, P=0.01, and P<0.001, respectively). No differences were observed in perfusion (P=0.94) and blood-brain barrier leakage (P=0.65) between periventricular and deep WMHs. The spatial analyses inside WMH and the adjacent white matter revealed a gradual gradient in white matter microstructure, free water content, perfusion, and plasma volume but not in blood-brain barrier leakage. CONCLUSIONS: We showed different pathophysiological heterogeneity of the 2 WMH types. Periventricular WMHs display more severe damage and fluid accumulation compared with deep WMH, whereas deep WMHs reflect stronger hypoperfusion in the lesion's core. REGISTRATION: URL: https://www.isrctn.com; Unique identifier: ISRCTN10514229.</p
A Comprehensive Guide to Volatolomics Data Analysis
No full textVolatolomics (or volatilomics), the study of volatile organic compounds, has emerged as a significant branch of metabolomics due to its potential for non-invasive diagnostics and disease monitoring. However, the analysis of high-resolution data from mass spectrometry and gas sensor array-based instruments remains challenging. The careful consideration of experimental design, data collection, and processing strategies is essential to enhance the quality of results obtained from subsequent analyses. This comprehensive guide provides an in-depth exploration of volatolomics data analysis, highlighting the essential steps, such as data cleaning, pretreatment, and the application of statistical and machine learning techniques, including dimensionality reduction, clustering, classification, and variable selection. The choice of these methodologies, along with data handling practices, such as missing data imputation, outlier detection, model validation, and data integration, is crucial for identifying meaningful metabolites and drawing accurate diagnostic conclusions. By offering researchers the tools and knowledge to navigate the complexities of volatolomics data analysis, this guide emphasizes the importance of understanding the strengths and limitations of each method.</p
Belief Identification by Proxy
No full textIt is well-known that individual beliefs cannot be identified using traditional choice data, unless we exogenously assume state-independent utilities. In this paper, I propose a novel methodology that solves this long-standing identification problem in a simple way. This method relies on extending the state space by introducing a proxy, for which the agent has no stakes conditional on the original state space. The latter allows us to identify the agent's conditional beliefs about the proxy given each state realization, which in turn suffices for indirectly identifying her beliefs about the original state space. This approach is analogous to the one of instrumental variables in econometrics. Similarly to instrumental variables, the appeal of this method comes from the flexibility in selecting a proxy
Effects of four-weeks porcine-collagen hydrolysate consumption on glucose concentrations, glycemic variability, and fasting/postprandial cardiometabolic risk markers in men and women with overweight or obesity:A randomized, controlled trial
No full textBackground: Different collagen hydrolysate sources have reduced fasting glucose concentrations. Although porcine-derived collagen hydrolysate predicts in vitro the highest potency for improving glucose metabolism, these effects have not been studied in humans. Aim: To evaluate the effects of porcine-derived collagen hydrolysate on continuously monitored glucose concentrations in real-life conditions in individuals with overweight/obesity. Additionally, postprandial responses following a mixed meal test were examined. Methods: Fifty-six men and women participated in this randomized placebo-controlled parallel trial. After a two-week run-in period, participants consumed daily for four weeks 10 g porcine-derived collagen hydrolysate or placebo (erythritol). The primary outcome parameter was the interstitial glucose area under the curve (AUC) during daytime (07:00 to 22:00) measured during three consecutive days. In addition, glycemic variability (GV) was quantified. For this, a continuous glucose monitor (Freestyle Libre ProiQ, Wiesbaden, Germany) was used at the end of the run-in and intervention periods. Postprandial glucose, insulin, and triacylglycerol concentrations were also evaluated after a mixed meal tolerance test. Furthermore, fasting glucose, insulin, hemoglobin A1c (HbA1c), homeostatic model assessment for insulin resistance (HOMA-IR), HOMA of ß-cell function (HOMA-ß), and triacylglycerol changes were analyzed. Physical activity profiles and dietary intakes were monitored to exclude confounding by these lifestyle factors. Results: Collagen hydrolysate consumption did not significantly affect daytime interstitial glucose AUC concentrations (95%CI for the effect size: -5.1, 30.0 mmol/(L*h); p-value = 0.159), but increased several GV metrics: standard deviation (95%CI: 0.0, 0.2 mmol/L; p-value = 0.011), continuous overall net glycemic action (CONGA-4) (95%CI: 0.1, 0.4 mmol/L; p-value = 0.015), coefficient of variation (95%CI: 0.1, 3.0 %; p-value = 0.036), M-value (95%CI: 0.2, 1.8; p-value = 0.036), and mean amplitude of glycemic excursions (MAGE) (95%CI: 0.2, 1.8 mmol/L; p-value = 0.036). Furthermore, the postprandial glucose AUC after the mixed meal test significantly increased (95%CI: 0, 103 mmol/L*4-h; p-value = 0.049), as well as fasting insulin concentrations (p-value = 0.005), HOMA-IR (p-value = 0.008), and HOMA-ß (p-value = 0.009). Other parameters, anthropometrics, physical activity, and energy/nutrient intakes were not significantly changed. Conclusion: Four-week collagen hydrolysate intake did not change free-living glucose concentrations, but increased GV, postprandial glucose AUC, fasting insulin, HOMA-IR, and HOMA-ß. However, these changes were small with limited clinical relevance. Therefore, it can be concluded that this porcine-derived collagen hydrolysate does not improve glucose metabolism or other cardiometabolic risk markers. Clinical trial registration: This clinical trial was registered in November 2021 as NCT05282641
New rectum dose surface mapping methodology to identify rectal subregions associated with toxicities following prostate cancer radiotherapy
No full textBackground and purpose: Growing evidence suggests that spatial dose variations across the rectal surface influence toxicity risk after radiotherapy. Existing methodologies employ a fixed, arbitrary physical extent for rectal dose mapping, limiting their analysis. We developed a method to standardise rectum contours, unfold them into 2D cylindrical surface maps, and identify subregions where higher doses increase rectal toxicities. Materials and methods: Data of 1,048 patients with prostate cancer from the REQUITE study were used. Deep learning based automatic segmentations were generated to ensure consistency. Rectum length was standardised using linear transformations superior and inferior to the prostate. The automatic contours were validated against the manual contours through contour variation assessment with cylindrical mapping. Voxel-based analysis of the dose surface maps for the manual and automatic contours against individual rectal toxicities was performed using Student's t permutation test and Cox Proportional Hazards Model (CPHM). Significance was defined by permutation testing. Results: Our method enabled the analysis of 1,048 patients using automatic segmentation. Student's t-test showed significance (p < 0.05) in the lower posterior for clinical-reported proctitis and patient-reported bowel urgency. Univariable CPHM identified a 3 % increased risk per Gy for clinician-reported proctitis and a 2 % increased risk per Gy for patient-reported bowel urgency in the lower posterior. No other endpoints were significant. Conclusion: We developed a methodology that unfolds the rectum to a 2D surface map. The lower posterior was significant for clinician-reported proctitis and patient-reported bowel urgency, suggesting that reducing the dose in the region could decrease toxicity risk