The relatively recent adoption of Endoscopic Sleeve Gastroplasty (ESG) amongst obese patients has gained approval within the surgical community due to its notable benefits, including significant weight loss, safety, feasibility, repeatability, and potential reversibility. However, despite its promising clinical outcomes and reduced invasiveness, there is still a lack of standardised procedures for performing ESG. Multiple suture patterns and stitching methods have been proposed over time, yet rational tools to quantify and compare their effects on gastric tissues are absent. To address this gap, this study proposed a computational approach. The research involved a case study analyzing three distinct suture patterns (C-shaped, U-shaped and Z-shaped) using a patient-specific computational stomach model generated from magnetic resonance imaging. Simulations mimicked food intake by placing wire features in the intragastric cavity to replicate sutures, followed by applying a linearly increasing internal pressure up to 15 mmHg. The outcomes facilitated comparisons between suture configurations based on pressure-volume behaviours and the distribution of maximum stress on biological tissues, revealing the U-shaped as the more effective in terms of volume reduction, even if with reduced elongation strains and increased tissues stresses, whereas the Z-shaped is responsible of the greatest stomach shortness after ESG. In summary, computational biomechanics methods serve as potent tools in clinical and surgical settings, offering insights into aspects that are challenging to explore in vivo, such as tissue elongation and stress. These methods allow for mechanical comparisons between different configurations, although they might not encompass crucial clinical outcomes.

OBJECTIVE: Personalised medicine is seen as an exciting opportunity to improve the health outcomes of people with obesity. As research on phenotyping and personalised treatment for obesity rapidly advances, this study sought to understand patient preferences and perspectives on personalised medicine for obesity.
METHODS: A participatory world café methodology was used to garner the perspectives of people living with obesity on the potential opportunities and limitations associated with a personalised approach to obesity risk identification and treatment. Data were recorded by participants on tablemats and analysed thematically using thematic analysis.
RESULTS: Patients expressed the hope that personalised medicine for obesity would reduce stigma, support understanding of obesity as a disease, and improve treatment outcomes and acceptance. They also expressed concern about the accuracy of personalised medicine for obesity, its implications for insurance and that further advances in individual, personalised medicine, would detract attention from social, environmental, economic and psychological drivers of obesity.
CONCLUSIONS: This study highlights how patients are generally very optimistic about the potential for personalised obesity medicine but also raise a number of legitimate concerns that will be of interest to clinicians, industry, and policy makers.

We aimed to identify an expression profile of lncRNAs potentially related to treatment response in Psoriatic arthritis (PsA) patients, to be used as potential genomic biomarkers predictors of drug treatment effectiveness. In addition, we evaluated a possible association between lncRNAs genetic variants and the response to therapy using the clinical parameter of Disease Activity Index. For the expression study, we collected 48 treated PsA patients, monitoring the treatment response for 12 months. We initially used PCR Array and, then, we validated the results with qRT-PCR. We also retrospectively genotyped 163 treated PsA patients. Firstly, we observed a significant difference in the expression level between Responder and non-Responder patients, of 4 lncRNAs in the group of PsA patients treated with TNFi and of 3 lncRNAs in the group of patients treated with IL17i. Then, we confirmed a significant decrease of MEG3 expression in non-Responder patients compared to Responders, also considering separately the single groups of patients treated with TNFi and IL17i. In addition, our results seem to highlight a potential dose-dependent effect of rs941576 (MEG3) variant allele on Disease Activity Index. Our study suggests a possible role of the lncRNA MEG3 in the treatment response to biological drugs.

Cefotaxime administration is recommended in doses of 3-12 g/day in adults with a Glomerular Filtration Rate (GFR) > 5 mL/min. This study aimed to assess the impact of renal function and obesity on cefotaxime concentrations in intensive care unit (ICU) patients. A retrospective cohort study was conducted on consecutive ICU patients receiving continuous cefotaxime infusion between 2020 and 2022 [IRBN992021/CHUSTE]. Doses were not constant; consequently, a concentration-to-dose ratio (C/D) was considered. Statistical analysis was performed to assess the relationship between cefotaxime concentrations, renal function, and obesity. A total of 70 patients, median age 61 years, were included, with no significant difference in cefotaxime concentrations between obese and non-obese patients. However, concentrations varied significantly by GFR, with underdosing prevalent in patients with normal to increased renal function and overdosing in those with severely impaired renal function. Adjustment of cefotaxime dosing according to GFR was associated with improved target attainment. Cefotaxime dosing in critically ill patients should consider renal function, with higher initial doses required in patients with normal to increased GFR and lower doses in those with severely impaired renal function. Therapeutic drug monitoring may aid in optimising dosing regimens. Prospective studies are warranted to validate these findings and inform clinical practice.

Prescribing drugs for psychosis (antipsychotics) is challenging due to high rates of poor treatment outcomes, which are in part explained by an individual\'s genetics. Pharmacogenomic (PGx) testing can help clinicians tailor the choice or dose of psychosis drugs to an individual\'s genetics, particularly psychosis drugs with known variable response due to CYP2D6 gene variants (\'CYP2D6-PGx antipsychotics\').
This study aims to investigate differences between demographic groups prescribed \'CYP2D6-PGx antipsychotics\' and estimate the proportion of patients eligible for PGx testing based on current pharmacogenomics guidance.
A cross-sectional study took place extracting data from 243 patients\' medical records to explore psychosis drug prescribing, including drug transitions. Demographic data such as age, sex, ethnicity, and clinical sub-team were collected and summarised. Descriptive statistics explored the proportion of \'CYP2D6-PGx antipsychotic\' prescribing and the nature of transitions. We used logistic regression analysis to investigate associations between demographic variables and prescription of \'CYP2D6-PGx antipsychotic\' versus \'non-CYP2D6-PGx antipsychotic\'.
Two-thirds (164) of patients had been prescribed a \'CYP2D6-PGx antipsychotic\' (aripiprazole, risperidone, haloperidol or zuclopenthixol). Over a fifth (23%) of patients would have met the suggested criteria for PGx testing, following two psychosis drug trials. There were no statistically significant differences between age, sex, or ethnicity in the likelihood of being prescribed a \'CYP2D6-PGx antipsychotic\'.
This study demonstrated high rates of prescribing \'CYP2D6-PGx-antipsychotics\' in an EIP cohort, providing a rationale for further exploration of how PGx testing can be implemented in EIP services to personalise the prescribing of drugs for psychosis.

Stress is an important predictor of long-term conditions. We examine whether hair cortisol (a biomarker of stress) is associated with incidence and accumulation of multiple long-term conditions (MLTC).
We included data from 4295 individuals aged ≥50 years within the English Longitudinal Study of Ageing dataset with data on hair cortisol, sociodemographic and health behaviour variables. Cox proportional hazards models were used to quantify the association between hair cortisol at baseline and accumulation of MLTC between 2012/2013 and 2018/2019, both for individuals with and without MLTC at baseline.
Our cohort included 1458 (34.0%) individuals who accumulated MLTC between 2012/2013 and 2018/2019. The proportion of individuals with zero, 1, and ≥ 2 conditions at baseline who accumulated MLTC were 12.0% (n = 127), 40.4% (n = 520), and 41.7% (n = 811), respectively. Higher cortisol levels were associated with higher risk of accumulation of MLTC in both unadjusted [HR:1.15(1.05-1.25)] and models adjusted for sociodemographic and health behaviours [HR:1.12(1.02-1.22)]. For individuals without MLTC at baseline, higher cortisol levels were significantly associated with higher risk of developing MLTC in unadjusted [HR: 1.20(1.05-1.36)] and adjusted models [HR: 1.16(1.02-1.32)].
The study provides the first evidence of the role of stress in the development and accumulation of MLTC. This modifiable risk factor could be targeted to reduce the risk of MLTC. However, further work is needed to better understand the mechanisms and pathways that link stress and accumulation of MLTC.

Awareness related to the risk/benefit profile of therapies used in paediatric and elderly patients is limited. We carried out a study, called the MEAP 3.0 study, to collect and analyse evidence of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) that occurred in frail populations under polypharmacy in a real-world setting. Data were retrieved from reports of ADRs and pharmacological counselling from patients treated in hospitals and territorial health services. We collected 2977 ADRs reports and identified \'anti-infectives for systemic use\' and \'cardiovascular system\' as the most frequently implicated pharmacological classes in under-18 and over-65 patients, respectively. We detected 2179 DDIs, of which 10.7% were related to at least one ADR: 22 were classified as \'contraindicated\' (7 in the paediatric group and 15 in the elderly one), and 61 as \'major\' (6 in the paediatric patients and 55 in the geriatric ones), while 151 DDIs were classified as \'moderate\' (10 referred to paediatric population, and 109 to elderly patient) and as \'minor\' (1 in paediatric patients, and 31 in the elderly ones). The MEAP 3.0 project demonstrates that pharmacovigilance surveillance and therapeutic reconciliation are valid strategies to avoid potential DDIs and the occurrence of ADRs, allowing for personalised medicine.

UNASSIGNED: Personalised therapy has emerged as a possibly more efficient approach taking disease heterogeneity into account. The aim of this study was to determine whether recently described subgroups of childhood diabetes have prognostic association with diabetes-specific complications and, therefore, might be a basis for personalised therapies.
UNASSIGNED: We applied a previously developed subgroup classification to pediatric patients (diabetes onset <18 years) from the prospective Diabetes Patient Follow-up (DPV) registry with documented data between January 1, 2000 and March 31, 2022, from diabetes centers in Germany, Austria, Switzerland, and Luxembourg. The classification required information on islet autoantibody status, age, haemoglobin A1c (HbA1c), and body-mass index (BMI-SDS) at disease manifestation, as well as follow up data after 2 and after 4 years, which was available in 22,719 patients. Patients without documented data on these parameters were excluded from the analysis. The cumulative risk of severe hypoglycemia, diabetic ketoacidosis (DKA), retinopathy, and nephropathy were analysed by Kaplan-Meier analyses over a median follow-up of 6.8 years (IQR 4.8-9.6).
UNASSIGNED: Patients were classified into 10 subgroups (P1-P7 islet autoantibody-positive, n = 19,811; N1-N3 islet autoantibody-negative, n = 2908). The groups varied markedly with respect to specific acute and chronic complications. Severe hypoglycemia was a characteristic feature in young islet autoantibody-positive subgroups P1, P3, P4 (10-year risk 46, 46 and 47%) and the islet autoantibody-negative groups N1, N2 (43 and 46%). Nephropathy was identified in patient groups P2 and P5 (10-year risk 16%), which had features of moderate disease such as preserved C-peptide, low HbA1c, and very low frequency of DKA at diabetes onset. Group P7, which was defined by a high BMI, was associated with poor metabolic control, DKA, and retinopathy. In contrast, islet autoantibody-negative patients with high BMI (N3) had a low risk for all four complications.
UNASSIGNED: Subgrouping of childhood diabetes at diabetes onset provided prognostic value for the development of acute and chronic diabetes-specific complications.
UNASSIGNED: The DPV initiative is supported by The German Ministry of Education and Research (BMBF) within the German Center for Diabetes Research, the diabetes surveillance of the Robert Koch Institute, the German Diabetes Association (DDG) and INNODIA.

[This corrects the article DOI: 10.3389/fphar.2023.1178421.].

OBJECTIVE: Adrenocortical carcinoma (ACC) is a rare aggressive malignancy with heterogeneous clinical outcomes. Recent studies proposed a combination of clinical/histopathological parameters (S-GRAS score) or molecular biomarkers (BMs) to improve prognostication. We performed a comparative analysis of DNA-based BMs by evaluating their added prognostic value to the S-GRAS score.
METHODS: A total of 194 formalin-fixed, paraffin-embedded (FFPE) ACC samples were analysed, including a retrospective training cohort (n = 107) and a prospective validation cohort (n = 87). Targeted DNA sequencing and pyrosequencing were used to detect somatic single-nucleotide variations in ACC-specific genes and methylation in the promoter region of paired box 5 (PAX5). The European Network for the Study of Adrenocortical Tumors (ENSAT) tumour stage, age, symptoms at presentation, resection status, and Ki-67 were combined to calculate S-GRAS. Endpoints were overall (OS), progression-free (PFS), and disease-free survival (DFS). Prognostic role was evaluated by multivariable survival analysis and their performance compared by Harrell\'s concordance index (C index).
RESULTS: In training cohort, an independent prognostic role was confirmed at multivariate analysis for two DNA-based BMs: alterations in Wnt/β-catenin and Rb/p53 pathways and hypermethylated PAX5 (both P< .05 for PFS and DFS, hazard ratio [HR] 1.47-2.33). These were combined to S-GRAS to obtain a combined (COMBI) score. At comparative analysis, the best discriminative prognostic model was COMBI score in both cohorts for all endpoints, followed by S-GRAS score (C index for OS 0.724 and 0.765, PFS 0.717 and 0.670, and DFS 0.699 and 0.644, respectively).
CONCLUSIONS: Targeted DNA-based BM evaluated on routinely available FFPE samples improves prognostication of ACC beyond routinely available clinical and histopathological parameters. This approach may help to better individualise patient\'s management.