To identify independent risk factors for recurrent pregnancy loss (RPL) among antiphospholipid antibody (aPL)-positive individuals who were either in early pregnancy (≤12 weeks' gestation) or not pregnant, and to develop and validate a risk prediction model to support early clinical risk stratification and intervention. We retrospectively analyzed 197 aPL-positive patients with a history of adverse pregnancy outcomes. Of the 197 aPL-positive patients, 31 met the diagnostic criteria for APS, and 166 had isolated aPL positivity. The patients were divided into an RPL group (n = 76) or a non-RPL group (n = 121) based on the occurrence of RPL, and were then randomly assigned (7:3) into a training set (n = 138) and a validation set (n = 59). Candidate predictors were screened using univariate logistic regression and entered into multivariate logistic regression to identify independent risk factors. Model discrimination and clinical utility were assessed using the area under the curve (AUC), calibration curves, and decision curve analysis (DCA), and a nomogram was subsequently constructed to facilitate individualized risk estimation. The results showed that coagulation factor V, coagulation factor VIII, TAT, ANA, and D-dimer were independent risk factors for RPL in aPL-positive individuals (either within the first 12 weeks of pregnancy or non-pregnant). The prediction model developed based on these factors demonstrated good discrimination, with AUC values of 0.787 and 0.711 in the training and validation sets, respectively. DCA confirmed that the model provided net clinical benefit across a wide range of threshold probabilities. In conclusion, the nomogram allows for rapid individualized risk assessment and shows promising potential for clinical translation.

Since the Mars Science Laboratory landed in 2012, the ChemCam instrument aboard the rover has collected in-situ laser-induced breakdown spectroscopy (LIBS) data and context images along more than 35 km of the Gale Crater traverse, providing valuable observations including diagenetic features such as light-toned veins. These veins are of particular scientific interest because they are interpreted as indicators of past fluid circulation on Mars and provide insights into the evolution of habitability on Mars. Their identification, however, currently relies on manual visual inspection of Remote Micro Imager (RMI) images, a process that is time-consuming and sensitive to differences in human interpretation. To address this issue, in this paper we introduce a novel pixel-level labeled, multimodal dataset of ChemCam observations specifically tailored for vein detection, along with customized U-Net models to integrate both textural (RMI) and chemical (LIBS) modalities. To further ensure trustworthy scientific use, we incorporate the Learn-Then-Test (LTT) framework to provide statistical control of the false discovery rate without requiring model retraining. The experimental results demonstrate that the proposed customized U-Net models trained on the developed dataset, combined with risk-controlled prediction, increases the efficiency of pixel-level vein identification through automation and produces statistically reliable predictions for multimodal ChemCam data.

Objective: To evaluate histopathological markers of inflammation and tissue repair in esophageal specimens obtained during substitution surgery and determine their association with postoperative anastomotic stenosis.Design: Retrospective cross-sectional study.Setting: Tertiary care referral center (Clínica de Tracto Digestivo Superior, Hospital General de México "Dr. Eduardo Liceaga").Participants: Sixteen adults undergoing esophageal substitution for benign disease between January 2012 and January 2022. Inclusion required complete clinical records and native esophageal histology; cases with malignancy or missing histology were excluded.Methods: Archived slides from the proximal esophageal margin were reviewed with hematoxylin and eosin and Masson's trichrome. A semi-quantitative score assessed neutrophilic infiltration, lymphocytic infiltration, collagen deposition, and granulation tissue across mucosa, submucosa, and muscularis (range 0-18), classifying profiles as low risk (≤15) or high risk (≥16). Patients were grouped by presence (CEA) or absence (SEA) of postoperative stenosis. Statistical comparisons used Fisher's exact test and Mann-Whitney U, with medians (IQR) and exact p-values.Results: Median total histological scores were higher in CEA than SEA (18 [17-18] vs 12 [9-15]; P=0.014). All stenosis cases were high-risk, whereas 92.3% of non-stenosis cases were low-risk (P=0.007). Individual inflammatory markers were not statistically different between groups; however, collagen deposition and granulation tissue appeared more severe among CEA patients. No meaningful differences in demographic or operative variables were observed.Conclusion: In this exploratory study, a composite histopathological score identified patients at increased risk of postoperative anastomotic stenosis. The approach may support risk stratification and surveillance in gastrointestinal reconstructive surgery and warrants external validation.

The strong propensity for lymphatic and distant metastases in gastrointestinal neuroendocrine tumours (GEP-NETS) often precludes cure for many patients. Platelet derived growth factor receptor alpha (PDGFRA) is commonly overexpressed in metastatic GEP-NETs and has been targeted in clinical trials, but there have been no direct mechanistic studies of PDGFRA cell signalling in neuroendocrine tumours. To address this gap, we examined the role of this tyrosine kinase receptor in the neuroendocrine cell lines BON-1 and QGP-1. We reveal increased colony formation and migratory potential without substantially altering proliferative capacity. This phenotype, similar to that seen in other PDGFRA cell line studies, appears to be mediated through Akt and MAP kinase pathways. Interestingly, in both xenograft models we also saw how PDGFRA expression induced striking similarities to the vascular nature of NET tumours, quantified through the vascular marker CD31 and vessel density. In terms of tumour growth, the presence of PDGFRA more than doubled the size of QGP-1 xenograft tumours but did not significantly alter BON-1 growth. The divergent in vivo phenotypes observed between BON-1 and QGP-1 xenografts likely reflect intrinsic differences in MAPK pathway activation. The creation of these new cell lines will aid in further studies to understand the potential role of targeting PDGFRA as a theranostic modality for patients with neuroendocrine tumours.

The coconut water market continues to expand, but industrial supply is constrained by the high perishability of fresh coconut water and the need for stabilization routes that preserve quality. This study optimized crossflow microfiltration of coconut water using a silicon carbide (SiC) ceramic membrane, high permeability, chemical/thermal robustness, and cleanability, and assessed the techno-economic feasibility of a green coconut biorefinery producing microfiltered coconut water and coconut pulp. Pressure and temperature were modeled and optimized using a face-centered design (FCD) and artificial neural networks coupled with a genetic algorithm (ANN-GA), considering permeate flux and fouling index (p < 0.05). Both approaches converged to the same operating point, and experimental validation at 75 kPa and 30 °C achieved 605.32 ± 15.34 L h-1 m-2 and 82.79 ± 1.35% at VRR = 1. Sample-level fit statistics favored ANN (higher R2 and lower sample-level errors), whereas condition-wise grouped cross-validation (leave-one-condition-out) indicated higher predictivity and lower RMSECV for the quadratic FCD/RSM models across experimental conditions, highlighting response-dependent generalization within the investigated domain. Fouling analysis indicated concentration polarization as the main resistance contribution and a flux-decline behavior best described by the intermediate blocking mechanism. A SuperPro Designer® simulation over a 20-year project life indicated economic feasibility under baseline assumptions (Internal rate of return-IRR = 23.80%, Net present value-NPV = US$733,761, payback = 2.96 years), with profitability remaining attractive under ±10% selling-price variation. Overall, the process optimization and modeling outcomes align with the economic case, reinforcing the potential of this biorefinery concept for industrial deployment.

Proteins of halophilic microorganisms thrive in high-salt environments. Compared to mesophilic proteins, they are enriched in acidic residues and small polar/apolar amino acids while being depleted in large hydrophobic residues, features that strongly influence their structure and stability. Here we critically examine experimental and computational studies investigating the mechanistic connection between the halophilic proteome and thermodynamic stability of halophilic proteins as a function of salt concentration. A defining feature of halophilic proteins is their highly negative surface charge, arising from abundant acidic residues. Some studies suggest this property is essential to ensure proteins remain folded at high salt concentrations, while others argue that a net negative protein charge might always be destabilizing. Alternative views propose that reducing solvent-exposed hydrophobic surface area is more critical than charge for stability at high salt concentrations. Advancing our understanding on this topic will require addressing multiple knowledge gaps. The unfolded states of both protein classes remain poorly characterized, leaving differences in local and non-local entropy contributions between the folded and the unfolded states to salt-dependent protein stability largely unexplored. Packing, cation-carbonyl and hydrophobic SASA differences between both protein classes are also insufficiently quantified. Atomistic molecular dynamics simulations with explicit solvent can advantageously be used to investigate these issues. Simultaneously, theoretical frameworks to understand how small perturbations in protein composition impact its stability as a function of salt concentration need to be expanded to include these contributions, which to date have been neglected, to fully understand how a halophilic proteome impacts salt-dependent stability.