Miracle-dz/UniFAR-FTUs huggingface dataset:
Highly compliant biomimetic scaffolds for small diameter tissue-engineered vascular grafts (TEVGs) produced via melt electrowriting (MEW)

Biofabrication approaches toward the development of tissue-engineered vascular grafts (TEVGs) have been widely investigated. However, successful translation has been limited to large diameter applications, with small diameter grafts frequently failing due to poor mechanical performance, in particular mismatched radial compliance. Herein, melt electrowriting (MEW) of poly(ϵ-caprolactone) has enabled the manufacture of highly porous, biocompatible microfibre scaffolds with physiological anisotropic mechanical properties, as substrates for the biofabrication of small diameter TEVGs. Highly reproducible scaffolds with internal diameter of 4.0 mm were designed with 500 and 250 µm pore sizes, demonstrating minimal deviation of less than 4% from the intended architecture, with consistent fibre diameter of 15 ± 2 µm across groups. Scaffolds were designed with straight or sinusoidal circumferential microfibre architecture respectively, to investigate the influence of biomimetic fibre straightening on radial compliance. The results demonstrate that scaffolds with wave-like circumferential microfibre laydown patterns mimicking the architectural arrangement of collagen fibres in arteries, exhibit physiological compliance (12.9 ± 0.6% per 100 mmHg), while equivalent control geometries with straight fibres exhibit significantly reduced compliance (5.5 ± 0.1% per 100 mmHg). Further mechanical characterisation revealed the sinusoidal scaffolds designed with 250 µm pores exhibited physiologically relevant burst pressures of 1078 ± 236 mmHg, compared to 631 ± 105 mmHg for corresponding 500 µm controls. Similar trends were observed for strength and failure, indicating enhanced mechanical performance of scaffolds with reduced pore spacing. Preliminary in vitro culture of human mesenchymal stem cells validated the MEW scaffolds as suitable substrates for cellular growth and proliferation, with high cell viability (>90%) and coverage (>85%), with subsequent seeding of vascular endothelial cells indicating successful attachment and preliminary endothelialisation of tissue-cultured constructs. These findings support further investigation into long-term tissue culture methodologies for enhanced production of vascular extracellular matrix components, toward the development of the next generation of small diameter TEVGs.
A pre-screening technique for bioavailable metals in sediments

ii ACKNOWLEDGEMENTS . iv THESIS CERTIFICATION . v THESIS PUBLICATIONS . vi THESIS PRESENTATIONS . vii TABLE OF CONTENTS . viii LIST OF FIGURES . xii LIST OF TABLES . xvii Chapter 1: Introduction . 18 1.1 Context statement . 19 1.2 Sediments . 19 1.3 Metal bioavailability in sediments . 20 1.3. 1 Metal speciation in sediments . 20 1.3. 2 Effects of sediment particles size on metal bioavailability and benthic communities . 22 1.3. 3 Exposure pathways . 23 1.3. 4 Organism physiology . 25 1.3. 5 Biological process influencing metal chemistry in sediments. 26 1.4 Bioaccumulation . 27 1.5 Bioassay . 28 1.6 Approaches and methods for predicting metal toxicity in sediments . 29 1.7 Sediment quality guidelines. 30 1.8 Monitoring sediment quality . 34 1.9 Diffusive gradients in thin films . 35 1.9. 1 DGT theoretical principles in waters . 37 1.9. 2 Metal speciation . 39 1.9. 3 DGT theoretical principles in sediments and soils . 40 1.9. 4 Homogeneous systems . 40 1.9. 5 Solid phase resupply . 43 1.9. 6 Kinetic of metal exchange and volumetric release . 44 1.9. 7 Estimation of porewater concentration by multiple DGT deployments with varying diffusional thickness . 46
Human Pluripotent Stem Cell-Derived Alveolar Organoids: Cellular Heterogeneity and Maturity

Chronic respiratory diseases such as idiopathic pulmonary fibrosis, chronic obstructive pulmonary disease, and respiratory infections injure the alveoli; the damage evoked is mostly irreversible and occasionally leads to death. Achieving a detailed understanding of the pathogenesis of these fatal respiratory diseases has been hampered by limited access to human alveolar tissue and the differences between mice and humans. Thus, the development of human alveolar organoid (AO) models that mimic in vivo physiology and pathophysiology has gained tremendous attention over the last decade. In recent years, human pluripotent stem cells (hPSCs) have been successfully employed to generate several types of organoids representing different respiratory compartments, including alveolar regions. However, despite continued advances in three-dimensional culture techniques and single-cell genomics, there is still a profound need to improve the cellular heterogeneity and maturity of AOs to recapitulate the key histological and functional features of in vivo alveolar tissue. In particular, the incorporation of immune cells such as macrophages into hPSC-AO systems is crucial for disease modeling and subsequent drug screening. In this review, we summarize current methods for differentiating alveolar epithelial cells from hPSCs followed by AO generation and their applications in disease modeling, drug testing, and toxicity evaluation. In addition, we review how current hPSC-AOs closely resemble in vivo alveoli in terms of phenotype, cellular heterogeneity, and maturity.
Examination of newborn DNA methylation among women with polycystic ovary syndrome/hirsutism

ABSTRACT Research suggests that polycystic ovary syndrome (PCOS) traits (e.g., hyperandrogenism) may create a suboptimal intrauterine environment and induce epigenetic modifications. Therefore, we assessed the associations of PCOS traits with neonatal DNA methylation (DNAm) using two independent cohorts. DNAm was measured in both cohorts using the Infinium MethylationEPIC array. Multivariable robust linear regression was used to determine associations of maternal PCOS exposure or preconception testosterone with methylation β-values at each CpG probe and corrected for multiple testing by false-discovery rate (FDR). In the birth cohort, 12% (102/849) had a PCOS diagnosis (8.1% PCOS without hirsutism; 3.9% PCOS with hirsutism). Infants exposed to maternal PCOS with hirsutism compared to no PCOS had differential DNAm at cg02372539 [β(SE): −0.080 (0.010); FDR p = 0.009], cg08471713 [β(SE):0.077 (0.014); FDR p = 0.016] and cg17897916 [β(SE):0.050 (0.009); FDR p = 0.009] with adjustment for maternal characteristics including pre-pregnancy BMI. PCOS with hirsutism was also associated with 8 differentially methylated regions (DMRs). PCOS without hirsutism was not associated with individual CpGs. In an independent preconception cohort, total testosterone concentrations were associated with 3 DMRs but not with individual CpGs, though the top quartile of testosterone compared to the lowest was marginally associated with increased DNAm at cg21472377 near an uncharacterized locus (FDR p = 0.09). Examination of these probes and DMRs indicate they may be under foetal genetic control. Overall, we found several associations among newborns exposed to PCOS, specifically when hirsutism was reported, and among newborns of women with relatively higher testosterone around conception.
Cpt1a silencing in AgRP neurons improves cognitive and physical capacity and promotes healthy aging in male mice

Abstract Orexigenic neurons expressing agouti‐related protein (AgRP) and neuropeptide Y in the arcuate nucleus (ARC) of the hypothalamus are activated in response to dynamic variations in the metabolic state, including exercise. We previously observed that carnitine palmitoyltransferase 1a (CPT1A), a rate‐limiting enzyme of mitochondrial fatty acid oxidation, is a key factor in AgRP neurons, modulating whole‐body energy balance and fluid homeostasis. However, the effect of CPT1A in AgRP neurons in aged mice and during exercise has not been explored yet. We have evaluated the physical and cognitive capacity of adult and aged mutant male mice lacking Cpt1a in AgRP neurons (Cpt1a KO). Adult Cpt1a KO male mice exhibited enhanced endurance performance, motor coordination, locomotion, and exploration compared with control mice. No changes were observed in anxiety‐related behavior, cognition, and muscle strength. Adult Cpt1a KO mice showed a reduction in gastrocnemius and tibialis anterior muscle mass. The cross‐sectional area (CSA) of these muscles were smaller than those of control mice displaying a myofiber remodeling from type II to type I fibers. In aged mice, changes in myofiber remodeling were maintained in Cpt1a KO mice, avoiding loss of physical capacity during aging progression. Additionally, aged Cpt1a KO mice revealed better cognitive skills, reduced inflammation, and oxidative stress in the hypothalamus and hippocampus. In conclusion, CPT1A in AgRP neurons appears to modulate health and protects against aging. Future studies are required to clarify whether CPT1A is a potential antiaging candidate for treating diseases affecting memory and physical activity.
Design and development of a hepatic lyo-dECM powder as a biomimetic component for 3D-printable hybrid hydrogels

Bioprinting offers new opportunities to obtain reliable 3D in vitro models of the liver for testing new drugs and studying pathophysiological mechanisms, thanks to its main feature in controlling the spatial deposition of cell-laden hydrogels. In this context, decellularized extracellular matrix (dECM)-based hydrogels have caught more and more attention over the last years because of their characteristic to closely mimic the tissue-specific microenvironment from a biological point of view. In this work, we describe a new concept of designing dECM-based hydrogels; in particular, we set up an alternative and more practical protocol to develop a hepatic lyophilized dECM (lyo-dECM) powder as an ‘off-the-shelf’ and free soluble product to be incorporated as a biomimetic component in the design of 3D-printable hybrid hydrogels. To this aim, the powder was first characterized in terms of cytocompatibility on human and porcine mesenchymal stem cells (MSCs), and the optimal powder concentration (i.e. 3.75 mg ml−1) to use in the hydrogel formulation was identified. Moreover, its non-immunogenicity and capacity to reactivate the elastase enzyme potency was proved. Afterward, as a proof-of-concept, the powder was added to a sodium alginate/gelatin blend, and the so-defined multi-component hydrogel was studied from a rheological point of view, demonstrating that adding the lyo-dECM powder at the selected concentration did not alter the viscoelastic properties of the original material. Then, a printing assessment was performed with the support of computational simulations, which were useful to define a priori the hydrogel printing parameters as window of printability and its post-printing mechanical collapse. Finally, the proposed multi-component hydrogel was bioprinted with cells inside, and its post-printing cell viability for up to 7 d was successfully demonstrated.
Hydroxyurea maintains working memory function in pediatric sickle cell disease

Pediatric patients with sickle cell disease (SCD) have decreased oxygen-carrying capacity in the blood and reduced or restricted cerebral blood flow resulting in neurocognitive deficits and cerebral infarcts. The standard treatment for children with SCD is hydroxyurea; however, the treatment-related neurocognitive effects are unclear. A key area of impairment in SCD is working memory, which is implicated in other cognitive and academic skills. N-back tasks are commonly used to investigate neural correlates of working memory. We analyzed functional magnetic resonance imaging (fMRI) of patients with SCD while they performed n-back tasks by assessing the blood-oxygenation level-dependent (BOLD) signals during working memory processing. Twenty hydroxyurea-treated and 11 control pediatric patients with SCD (7-18 years old) performed 0-, 1-, and 2-back tasks at 2 time points, once before hydroxyurea treatment (baseline) and ~1 year after treatment (follow-up). Neurocognitive measures (e.g., verbal comprehension, processing speed, full-scale intelligence quotient, etc.) were assessed at both time points. Although no significant changes in behavior performance of n-back tasks and neurocognitive measures were observed in the treated group, we observed a treatment-by-time interaction in the right cuneus and angular gyrus for the 2- > 0-back contrast. Through searchlight-pattern classifications in the treated and control groups to identify changes in brain activation between time points during the 2-back task, we found more brain areas, especially the posterior region, with changes in the pattern and magnitude of BOLD signals in the control group compared to the treated group. In the control group, increases in 2-back BOLD signals were observed in the right crus I cerebellum, right inferior parietal lobe, right inferior temporal lobe, right angular gyrus, left cuneus and left middle frontal gyrus at 1-year follow-up. Moreover, BOLD signals elevated as the working memory load increased from 0- to 1-back but did not increase further from 1- to 2-back in the right inferior temporal lobe, right angular gyrus, and right superior frontal gyrus. These observations may result from increased cognitive effort during working memory processing with no hydroxyurea treatment. In contrast, we found fewer changes in the pattern and magnitude of BOLD signals across time points in the treated group. Furthermore, BOLD signals in the left crus I cerebellum, right angular gyrus, left cuneus and right superior frontal gyrus of the treated group increased continuously with increasing working memory load from 0- to 2-back, potentially related to a broader dynamic range in response to task difficulty and cognitive effort. Collectively, these findings suggest that hydroxyurea treatment helped maintain working memory function in SCD.
Machine Learning-Based Hyperglycemia Prediction: Enhancing Risk Assessment in a Cohort of Undiagnosed Individuals

Background: Noncommunicable diseases (NCDs) continue to pose a significant health challenge globally, with hyperglycemia serving as a prominent indicator of potential diabetes. This study employed machine learning algorithms to predict hyperglycemia in a cohort of asymptomatic individuals and unraveled crucial predictors contributing to early risk identification. Methods: This dataset included an extensive array of clinical and demographic data obtained from 195 asymptomatic adults residing in a suburban community in Nigeria. The study conducted a thorough comparison of multiple machine learning algorithms to ascertain the most effective model for predicting hyperglycemia. Moreover, we explored feature importance to pinpoint correlates of high blood glucose levels within the cohort. Results: Elevated blood pressure and prehypertension were recorded in 8 (4%) and 18 (9%) individuals respectively. Forty-one (21%) individuals presented with hypertension (HTN), of which 34/41 (82.9%) were females. However, cohort-based gender adjustment showed that 34/118 (28.81%) females and 7/77 (9.02%) males were hypertensive. Age-based analysis revealed an inverse relationship between normotension and age (r = -0.88; P < 0.05). Conversely HTN increased with age (r = 0.53; P < 0.05), peaking between 50-59 years. Isolated systolic hypertension (ISH) and isolated diastolic hypertension (IDH) were recorded in 16/195 (8.21%) and 15/195 (7.69%) individuals respectively, with females recording higher prevalence of ISH 11/16 (68.75%) while males reported a higher prevalence of IDH 11/15 (73.33%). Following class rebalancing, random forest classifier gave the best performance (Accuracy Score = 0.894; receiver operating characteristic-area under the curve (ROC-AUC) score = 0.893; F1 Score = 0.894) of the 27 model classifiers. The feature selection model identified uric acid and age as pivotal variables associated with hyperglycemia. Conclusions: Random Forest classifier identified significant clinical correlates associated with hyperglycemia, offering valuable insights for early detection of diabetes and informing the design and deployment of therapeutic interventions. However, to achieve a more comprehensive understanding of each feature's contribution to blood glucose levels, modeling additional relevant clinical features in larger datasets could be beneficial. Keywords: Hyperglycemia; Diabetes; Machine Learning; Hypertension; Random Forest
Gender inequalities in trajectories of depressive symptoms among young people in London and Tokyo: a longitudinal cross-cohort study.

Background Research suggests gender inequalities in adolescent mental health are context dependent. This implies they may be preventable through social/structural change. However, there is also some evidence that gender mental health gaps are larger in ostensibly more gender equal societies, e.g., 2-3-fold larger in the UK vs. Japan. Using data and methods that overcome important limitations of existing evidence, we tested the hypothesis that gender inequalities in depressive symptom trajectories are larger in London than in Tokyo, and that these differences are not due to incomparable measurement. Methods We used three waves of data from representative adolescent cohorts in Tokyo (TTC; n=2,813) and London (REACH; n=4,287) (n=7,100; age 11-16y). We used multigroup and longitudinal confirmatory factor analysis to examine measurement invariance of the 13-item Short Mood and Feelings Questionnaire (SMFQ) across cohorts, genders, and ages. Latent growth models compared depressive symptom trajectories of boys and girls in London and Tokyo. Outcomes Scalar invariance was well-supported. In London, gender inequalities in depressive symptoms were evident at age 11y (girls: +0.8 [95% CI: 0.3-1.2]); in Tokyo, the difference emerged between 11-14y. In both places, the disparity widened year-on-year, but by age 16y was around twice as large in London. Annual rate of increase in depressive symptoms was around four times steeper among girls in London (1.1 [0.9-1.3]) vs. girls in Tokyo (0.3 [0.2-0.4]). Interpretation Gender inequalities in emotional health are context dependent and may be preventable through social/structural change.
Road Detection From Aerial Images Using Color Features

Urban regions are dynamic environments. Especially their road maps change by the expansion of the urban region. Therefore, automatic detection of roads from very high resolution aerial and satellite images is a very important research field. Unfortunately, the solution is not straightforward by using basic image processing and computer vision algorithms. Therefore, advanced methods are needed for road network detection from aerial and satellite images. In this study, we propose a novel method for automatic detection of road segments from very high resolution color aerial and satellite images. Our method depends on choosing a training set from the input image manually. We use color chroma values of pixels as the discriminative features. Since road pixels have similar color characteristics, the distribution of color chroma feature values of the training region have a peak at a certain point in the feature space which shows the road class. Using this information and one-class classification methodology, we label road segments in a given remotely sensed image. Finally, we fit a road network shape on the detected segment. Experimental results on color aerial and Ikonos satellite images show the importance of color features in road detection applications.
Implications of 3 alternative management policies on groundwater levels in the Texas High Plains

Groundwater supply in the Ogallala Aquifer is diminishing at an unsustainable rate, which is affecting the crop and animal production in the region. The desired future condition adopted by the North Plains Groundwater Conservation District states that at least 40% of the volume of groundwater should remain in the Ogallala Aquifer after 50 years in Dallam, Sherman, Hartley, and Moore counties. The main objective of this study is to evaluate the effects of 3 proposed groundwater management policies on future groundwater levels using a calibrated MODFLOW model. The 3 groundwater management policies considered are permanent conversion of 10% of the total irrigated area to dryland production, temporary conversion of 10% of the total irrigated area to dryland production for the first 15 years, and adoption of advances in biotechnology that allow groundwater use reductions at a rate of 1% per year during the next 50 years. Results indicated that if future average groundwater pumping rates are kept at 2010 withdrawal rates, then 50% of groundwater in the Ogallala Aquifer would remain in 50 years, thus meeting the groundwater district's desired future condition in Dallam, Sherman, Hartley and Moore counties. The most favorable impact on diminishing depletion was obtained with the adoption of advances in biotechnology, which would leave 60% of groundwater remaining in 50 years in the study area. Similar results can be obtained if 1% of irrigated cropland is retired per year. Citation: Hernández JE, Gowda PH, Marek TH, Howell TA, Ha W. 2015. Implications of 3 alternative management policies ongroundwater levels in the Texas High Plains. Texas Water Journal. 6(1):86-102. Available from: https://doi.org/10.21423/twj.v6i1. 7005.
AI-Driven Insights into the complexities of Chinese hamster ovary cells death in order to optimize production processes

Chinese hamster ovary (CHO) cells are a multipurpose and high-performance cell line for recombinant protein production in biopharmaceutical industry. They have proven their ability to produce a wide range of therapeutic proteins with high efficiency and quality. Designing novel and high-performance CHO cell lines has an incredible impact in biopharmaceutical industry that can reduce prices and increase product efficiency. One of the best ways is to prevent CHO cells death during Bioprocessing. Apoptosis is the most common form of CHO cells death during Bioprocessing. Analyzing Apoptosis and cell-cycle complex signaling pathways are necessary for the control of cell growth, efficiency, and the death of CHO cells. Therefore, analyzing and understanding interactions of these pathways and their interactions with other cellular processes can help optimize the performance and quality of CHO cell lines. AI-driven insight solutions and Advanced machine learning algorithms like GAT (Graph Attention Network) used in this project indicate most important Targets in complex signaling pathways. Pathways such as the TNF signaling pathway, and also viruses like: Hepatitis C, HIV1 and Bacteria like: Salmonella have High intersection size and Low P-value with complex signaling pathways. These microorganisms should be used to design high-performance CHO cell lines because they are master in these pathways. This method can be used to find novel and high efficiency targets for curing cancer in humans.
High Frequency Longitudinal RNAseq Reveals Temporally Varying Genes and Recovery Trajectories in Rats

When living organisms are exposed to potentially toxic chemicals, they respond via changes in gene expression. Traditional differentially expressed gene analysis based on before/after blood samples does not reveal the response’s temporal dynamics, and often produces false positives and negatives. Here, we performed longitudinal daily RNA sequencing on rats dosed with tetracycline, isoniazid, carbon tetrachloride, or valproate. We identified 4,302 temporally variable genes (TVGs) with statistically strong change in expression following dosing. Projecting TVG expressions into a 3-dimensional principal component (PC) space reveals consistent trajectories for recovery following dosing, and enables separation of healthy from recovering states with 91% to 99% area under the receiver operator curve. Finally, we observed that Fast Recovery vs. Slow Recovery rats exhibited distinct temporal expression patterns in the TVGs, suggesting that individual variations could be potentially captured via longitudinal RNAseq analysis.