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Physiology-Based Diagnosis and Management of Bronchopulmonary Dysplasia Associated Pulmonary Hypertension (BPD-PH)
Full text linkDifferential Effects of Ischemia and Inflammation on Plasma-Derived Extracellular Vesicle Characteristics and Function in a Mouse Model
Full text linkExtracellular vesicles (EVs) have long been understood to be important mediators of cell-to-cell communication and may lead to the molecular aftermath and exacerbation of brain injuries such as stroke. This study explored how the source of the EVs influenced their characteristics and the effect these differences had on naïve brain tissue. EVs were isolated from mice post-stroke in the acute or chronic stages of recovery in animals with and without reperfusion (transient and permanent middle cerebral artery occlusion) and from a model of systemic inflammation (i.p. lipopolysaccharide). The data show that neither stroke nor inflammation significantly increases EV numbers compared to sham or naïve animals. Post-stroke EVs exhibited a panel of different platelet and inflammatory markers when compared to EVs derived from a model of inflammation, reflecting differences between stroke and systemic immune activation. When injected into the brain, both stroke-derived and inflammation-derived EVs induced pro-inflammatory cytokine gene expression (IL-1β and CXCL1), suggesting a potential role in neuroinflammation. However, no clear group-level differences in microglial or astrocytic reactivity were detected at the level of regional histological assessment, despite consistent increases in ICAM-1 reactivity. The findings here underscore the complexity of EVs’ roles in pathophysiology and highlight the need for improved EV isolation methods. With further longitudinal studies, we may be able to more accurately determine how the context of the injury (reperfusion vs. no reperfusion vs. inflammation) might contribute to the EV populations and their function. Understanding more about EVs in different contexts will improve our ability to use EVs as biomarkers but also our capacity to interfere with EV biology as a novel therapeutic approach
Machine Learning-Based Dry Gas Reservoirs Z-Factor Prediction for Sustainable Energy Transitions to Net Zero
Full text linkDry gas reservoirs play a pivotal transitional role in meeting the net-zero target worldwide. Accurate modelling and simulation of this energy source require fast and reliable prediction of the gas compressibility factor (Z-factor). The experimental measurements of Z-factor are the most reliable source; however, they are expensive and time-consuming. This makes developing accurate predictive models essential. Traditional methods, such as empirical correlations and Equations of States (EoSs), often lack accuracy and computational efficiency. This study aims to address these limitations by leveraging the predictive power of machine learning (ML) techniques. Hence in this study three ML models of Artificial Neural Network (ANN), Group Method of Data Handling (GMDH), and Genetic Programming (GP) were developed. These models were trained on a comprehensive dataset comprising 1079 samples where pseudo-reduced pressure (Ppr) and pseudo-reduced temperature (Tpr) served as input and experimentally measured Z-factors as output. The performance of the developed ML models was benchmarked against two cubic EoSs of Peng–Robinson (PR) and van der Waals (vdW), and two semi-empirical correlations of Dranchuk-Abou-Kassem (DAK) and Hall and Yarborough (HY), and recent developed ML based models, using statistical metrics of Mean Squared Error (MSE), coefficient of determination (R2), and Average Absolute Relative Deviation Percentage (AARD%). The proposed ANN model reduces average prediction error by approximately 70% relative to the PR equation of state and by over 35% compared with the DAK correlation, while maintaining robust performance across the full Ppr and Tpr of dry gas systems. Additionally paired t-tests and Wilcoxon signed-rank tests performed on the ML results confirmed that the ANN model achieved statistically significant improvements over the other models. Moreover, two physical equations using the white-box models of GMDH and GP were proposed as a function of Ppr and Tpr for prediction of the dry gas Z-factor. The sensitivity analysis of the data shows that the Ppr has the highest positive effect of 88% on Z-factor while Tpr has a moderate effect of 12%. This study presents the first unified, statistically validated comparison of ANN, GMDH, and GP models for accurate and interpretable Z-factor prediction. The developed models can be used as an alternative tool to bridge the limitation of cubic EoSs and limited accuracy and applicability of empirical models
Diagnostic accuracy of ascending cystourethrogram for localising recto-urinary fistulas in non-colostomized male neonates with high anorectal malformations: Cairo University paediatric surgery experience
Full text linkBackground: Accurate preoperative identification of recto-urinary fistulas in male neonates with high anorectal malformations (ARMs) is essential for surgical planning, especially when considering single-stage repair. The ascending cystourethrogram (ACU) provides a simple, minimally invasive approach that eliminates the need for a preliminary colostomy. This study explored the feasibility and early clinical value of ACU in defining recto-urinary fistula anatomy in selected neonates. Methods: This prospective study included 35 male neonates with high ARM who underwent ACU before definitive repair. The presence and level of recto-urinary fistulas were recorded and compared with intraoperative findings. When imaging did not demonstrate the fistula, distal colostography was performed to confirm the diagnosis. Results: ACU identified recto-urinary fistulas in 30 of 35 neonates (85.7%; 95% CI: 70.6–94.1%). Detected fistulas included recto-bladder neck (14.3%), recto-prostatic (42.9%), and recto-bulbar (28.6%) types. In five cases (14.3%), a fistula was not visualised on ACU; however, distal colostogram confirmed the diagnosis in four. Relative to intraoperative findings, ACU demonstrated a sensitivity of 85.7% and a positive predictive value of 100%. Conclusion: ACU is a reliable, minimally invasive, and readily available technique for early localisation of recto-urinary fistulas in male neonates with high ARM, demonstrating close correlation with intraoperative findings. It can be safely performed within the first 24 h of life, enabling prompt anatomical assessment and supporting the appropriate selection of candidates for single-stage repair. These findings reinforce ACU’s role as a practical first-line diagnostic tool in the management of high anorectal malformations
Better Material Properties and Faster Catalyzed Chemical Recycling for Poly( L ‐Lactide) Using a Simple Commercial Glycerol Ethoxylate Additive
Full text linkPoly(L‐lactide) (PLLA) is the largest volume commercial bio‐derived plastic, but its brittleness and end‐of‐life recycling remain challenges. Here, glycerol ethoxylate (GEO), a branched ethylene glycol derivative, both toughens commercial PLLA and accelerates its catalyzed chemical recycling to L‐lactide. A series of GEO–PLLA blends, containing 2–20 wt.% GEO, show significantly improved ductility and toughening compared to pure PLLA. The lead 10 wt.% GEO–PLLA sample achieves 9x higher elongation at break (191% ± 4%) and 6x higher tensile toughness (57.9 ± 1.9 MJ m−3), while retaining desirable tensile strength (36.3 ± 1.5 MPa), thermal properties (Tg = 39°C and Tm = 149°C) and crystallinity (25%). The GEO–PLLA samples are efficiently chemically recycled to L‐lactide, showing both high recycling activity (TOF = 2240 ± 73 h−1) and quantitative selectivity for L‐lactide (> 99%). The recycling is performed neat, at 180°C, using low loadings of commercial Sn(II)Oct2 catalyst. The 10 wt.% GEO–PLLA sample shows significantly faster chemical recycling than PLLA, with kobs = 22.9 ± 0.8 h−1 versus kobs = 1.8 ± 0.2 h−1 for PLLA. This recycling process is successful even with contamination from other commercial plastics, demonstrating its applicability to future postconsumer waste streams
A synthetic ERFVII-dependent circuit in yeast sheds light on the regulation of early hypoxic responses of plants
Full text linkPlants face hypoxic conditions either chronically, as particular tissues are characterized by fluctuating or stable low oxygen levels, or acutely, when flooded. In vascular plants, transcriptional adaptive responses to hypoxia are rapidly mounted by Ethylene Response Factors VII (ERFVIIs), regulated by Plant Cysteine Oxidases (PCOs) through the cysteine branch of the N-degron pathway (Cys-NDP) for oxygen sensing. However, this relatively simple regulatory circuit, consisting of both constitutively expressed as well as hypoxia-inducible ERFVIIs and PCOs, interacts with diverse signaling cues and pathways invoked by hypoxia. To understand the share of the PCO-mediated oxygen sensing mechanism in the production of hypoxia responses, we insulated the PCO/ERFVII circuit from Arabidopsis thaliana and adapted it to Saccharomyces cerevisiae. Using a reporter gene to monitor the output of the circuit allowed us to compare the speed and amplitude of response to hypoxia in the engineered yeast and the source organism. Hypoxia triggered ERFVII stabilization both in Arabidopsis and yeast, leading to a similarly fast transcriptional response that was however larger in plants. A simple hypoxia-inducible feedback loop improved the amplitude of response in yeast, demonstrating the importance of this regulation in the endogenous PCO/ERFVII circuit. Finally, computational modeling of the yeast circuit enabled us to identify promoter competition and presence of hypoxia-inducible PCOs as key parameters that shape early hypoxia responses in plant cells
Impact of Chinese students' perceived parental expectations on academic achievement: The mediating role of academic self-concept
Full text linkAchieving high academic achievement is crucial in high school education, influencing students' future opportunities and development. Parental expectations are recognized as a significant factor in academic success, with some researchers highlighting the mediating role of academic self-concept. However, limited research has specifically tested this mediating effect, especially in mainland China. This study, based on the Expectancy-Value Theory, examined the relationship between parental expectations and academic achievement, focusing on the mediating role of academic self-concept among Chinese high school students preparing for the Gaokao. A cross-sectional survey collected data on students' perceived parental expectations, academic self-concept, and standardized test scores from 143 senior high school students in Guangdong Province. Bivariate correlation, hierarchical multiple linear regression, and PROCESS macro mediation analysis revealed that higher parental expectations significantly predicted higher academic self-concept and academic achievement, with academic self-concept partially mediating this relationship. These findings inform Chinese parents of high school students in Guangdong Province to set high but realistic expectations and work to enhance their children's perceptions of academic abilities. While the study offers valuable insights into educational practices in China, its cross-sectional design might limit the understanding of causal relationships, and focusing on a single high school tends to restrict generalizability. Future research could employ longitudinal methods and include diverse samples to further explore these relationships and the mediating role of academic self-concept in the context of China
Optimizing drug-resistant tuberculosis diagnosis: cost-effectiveness of rapid molecular and phenotypic assays in South Africa
Full text linkBackground: Timely detection of drug-resistant tuberculosis (DR-TB) is essential for effective treatment and preventing poor outcomes. Rapid molecular diagnostics are promising alternatives to conventional phenotypic drug susceptibility testing (pDST), offering faster and more accessible detection of resistance. This study evaluated the cost-effectiveness of rapid molecular assays, alone or combined with pDST, for detecting resistance to isoniazid, rifampicin, and fluoroquinolones from a South African healthcare provider perspective. Methods: A decision-analytic model was developed to simulate TB-related outcomes for a hypothetical cohort of microbiologically confirmed TB patients. Nine diagnostic strategies were evaluated: pDST alone; four rapid molecular tests (line probe assays [LPAs], Xpert MTB/RIF [Xpert] followed by Xpert MTB/XDR [Xpert XDR], Xpert MTB/RIF Ultra [Xpert Ultra] followed by Xpert XDR, and targeted next-generation sequencing [tNGS]); and combinations pairing each molecular test with pDST. Outcomes included early treatment rates, mortality, direct medical costs, disability-adjusted life-years (DALYs), and incremental cost-effectiveness ratios (ICERs). Base-case, sensitivity, and scenario analyses were performed. Results: In the base-case analysis, ‘Xpert followed by Xpert XDR + pDST’ was the preferred cost-effective strategy, with an ICER of USD 6,554/DALY averted—below South Africa's GDP per capita threshold. While ‘tNGS + pDST’ yielded the greatest health benefits—lowest DALYs (1.9877), highest early treatment rate (995.54/1,000 tested), and lowest mortality (90.22/1000 tested)—its ICER (USD 25,918/DALY averted) exceeded three times the GDP per capita, rendering it not cost-effective. Sensitivity analyses highlighted the impact of diagnostic accuracy and treatment timing on cost-effectiveness outcomes. Probabilistic sensitivity analysis showed ‘tNGS + pDST’ had the highest probability of being cost-effective when the willingness-to-pay threshold exceeded USD 10,500/DALY averted. Diagnostic replacement scenario analysis revealed that tNGS alone could be a cost-effective alternative (ICER = USD 1712 per DALY averted) when pDST was unavailable. An extended two-year time horizon analysis confirmed base-case robustness. Conclusions: Combining rapid molecular diagnostics with pDST offers a cost-effective and clinically beneficial approach for DR-TB detection in high-burden settings. The Xpert-based strategy provides an optimal balance of diagnostic yield, early treatment, and economic efficiency in South Africa. tNGS represents a feasible alternative in settings where pDST is inaccessible, warranting further evaluation for broader implementation
CORE-VNS: Dosing and titration of VNS therapy in contemporary clinical practice
Full text linkIn this analysis of dosing and titration in the CORE-VNS study, we aimed to replicate previously published findings related to dosing and titration of VNS Therapy and describe the impact of Scheduled Programming (SP).Participants who received their first VNS Therapy device during the CORE-VNS study and who attended at least one of either the 6- or 12-month follow-ups were selected for this analysis. Various statistical models (generalized linear mixed models, weighted Cox regression, Kaplan-Meier, and Poisson regression) were used to assess the relationship between VNS titration and clinical response. Participants who were predominantly manually titrated were compared to those who were predominantly titrated using SP. 526 participants met the inclusion criteria for this analysis. The majority were titrated manually (n = 364), compared with the SP feature (n = 162). We found a strong relationship between speed of titration and onset of clinical response but did not find SP use to significantly impact time-to-dose. The mean time-to-response in the SP group was 7.8 months, compared to a mean time-to-response of 10.7 months for manually titrated patients but this effect was not significant in the Cox regression. Patients who were titrated using SP were able to complete their titration phase with fewer required in-office visits than manually titrated patients (p < 0.0001). We replicate prior findings that titration speed of VNS impacts the time to response. Scheduled Programming does not appear to strongly impact titration speed but aids the clinical workflow and reduces patient burden by reducing the frequency of required in-office titration visits
Partition function of the Kitaev quantum double model
No full textWe compute the degeneracy of energy levels in the Kitaev quantum double model for any discrete group on any planar graph forming the skeleton of a closed orientable surface of arbitrary genus. The derivation is based on the fusion rules of the properly identified vertex and plaquette excitations, which are selected among the anyons, i.e., the simple objects of the Drinfeld center . These degeneracies are given in terms of the quantum dimensions of the anyons and allow one to obtain the exact finite-temperature partition function of the model, valid for any finite-size system