Abstract: Introduction: In preeclampsia (PE), impaired trophoblast proliferation and differentiation are thought to cause abnormal placentation and subsequent clinical manifestations of the disease—i.e., hypertension, proteinuria, and end-organ damage. Insulin-like growth factor 1 (IGF-1) influences trophoblast cell function, however the mechanisms of IGF-1’s action on trophoblasts is not well understood. Inhibitor of DNA binding protein 2 (ID2) is involved in trophoblast differentiation and implicated in many processes disrupted in PE including placental development, vascular differentiation, and angiogenesis. We hypothesized that IGF-1 regulates trophoblast proliferation and differentiation via ID2. Methods: Immortalized human first trimester trophoblast cells (HTR-8/SVneo) were treated with IGF-1 for 24 hours after serum starvation. ID2 mRNA and protein were measured, as well as trophoblast cell viability, proliferation, tube formation and migration. Results: IGF-1 decreased ID2 expression in a dose-dependent manner. IGF-1 decreased trophoblast proliferation but increased cell viability, differentiation, and migration. ID2 overexpression mitigated the effects of IGF-1 on trophoblast cells. Discussion: These data suggest IGF-1 could regulate trophoblast proliferation and differentiation through ID2. Dysregulation of ID2-mediated IGF-1 signaling in trophoblast cells could be involved in the pathogenesis of pregnancy disorders like uterine growth restriction and PE.

Abstract: The epidemiology of Chagas disease in humans has markedly changed within the past several decades in the United States of America. This report discusses autochthonous cases of Chagas disease and disease in immigrants from Latin American countries. Directions for epidemiology research and medical care are discussed given the evolving epidemiology of the disease in the United States of America.

Abstract: Background/Objectives: Climate change adversely affects some of the fundamental determinants of health, and children are the population group most vulnerable to exposure to environmental risk factors. The main objective of this study was to validate in the Portuguese context three scales to assess attitudes, knowledge and skills on children's environmental health. Methods: A cross-sectional observational study was developed to translate, adapt, and validate the questionnaire consisting of the following three scales: Attitude Scale (SANS_2), knowledge scale (ChEHK-Q), and skills scale (ChEHS-Q). This was carried out in two phases: The translation and adaptation process and the validation process using the classical measure theory and item response theory with undergraduate nursing students. Results: We obtained a valid and reliable questionnaire to measure children's environmental health competence consisting of an attitude scale (α = 0.84), a knowledge scale (Infit = 0.98, Outfit = 0.97, item reliability = 0.98 and people reliability = 0.75) and a skills scale (Infit = 1.00, Outfit = 0.99, item reliability = 0.82 and people reliability = 0.88). The mean score on the attitude scale was 28.15 (5-35) ± 4.61; 14.92 (0-26) ± 4.51 on the knowledge scale, and 42.51 (24-60) ± 6.41 on the skills scale. Conclusions: We found that most Portuguese nursing students have very good pro-environmental attitudes and good knowledge and skills in dealing with children's environmental health. The questionnaire obtained in this study will be useful for comparative studies with other countries and for evaluating the effectiveness of educational interventions.

Abstract: We show a simple bijection $P$ between permutations $S_n$ of length $n$ and underdiagonal paths of size $n$, the last being lattice paths made of up $U=(1,1)$, down $D=(1,-1)$, west $W=(-1,1)$ steps, running from $(0,0)$ to $(2n,0)$, and such that: (1) the path is weakly bounded by the lines $y=0$ and $x=y$; (2) a $D$ (resp. $W$) step cannot be followed by a $W$ (resp. $D$) step. The aim of this paper is to study and enumerate families of underdiagonal paths which are defined by restricting the bijection $P$ to subclasses of $S_n$ avoiding some vincular patterns. For a given pattern $\tau$, let $S(\tau)$ be the family of permutations avoiding $\tau$, and $P(\tau)$ the family of underdiagonal paths corresponding to permutations in $S(\tau)$, precisely $P(\tau)=\{ P(\pi): \pi \in S(\tau) \}.$ We will consider patterns $\tau$ of length $3$ and $4$, and, when it is possible, we will provide a characterization of the underdiagonal paths of $P(\tau)$ in terms of geometrical constrains, or equivalently, the avoidance of some factors. Finally, we will provide a recursive growth of these families by means of generating trees and then their enumerative sequence.

Abstract: Kidney cancer has become a major global health issue over time, showing how early detection can play a very important role in mediating the disease. Traditional histological image analysis is recognized as the clinical gold standard for diagnosis although it is highly manual and labor-intensive. Due to this issue, many are interested in comput-er-aided diagnostics technologies to assist pathologists in their diagnostic. Specifically, deep learning (DL) has become a viable remedy in this field. Nonetheless, the capacity of existing DL models to extract comprehensive visual features for accurate classification is limited. Towards the end, this study proposes using ensemble models that combine the strengths of multiple transformers and deep learning model architectures. By leveraging the collective knowledge of these models, the ensemble enhances classification perfor-mance and enables more precise and effective kidney cancer detection. This study compares the performance of these suggested models to previous studies, all of which used the publicly accessible Dartmouth Kidney Cancer Histology Dataset. This study showed that the Vision Transformers, with an average accuracy of over 99%, were able to achieve high detection accuracy across all complete slide picture patches. In particular, the CAiT, DeiT, ViT, and Swin models outperformed ResNet. All things considered, the vision Transformers consistently produced an average accuracy of 98.51% across all five folds 5 folds. These results demonstrated that Vision Transformers might perform well and successfully identify important features from smaller patches. Through utilizing histo-pathological images, our findings will assist pathologists in diagnosing kidney cancer, resulting in early detection and increased patient survival rates

Abstract: The accumulation of lipofuscin, i.e., indigestible intracellular debris, might be the main cause of age-related diseases that we see today. However, without being able to replace mutated mitochondrial DNA (mtDNA) and damaged and mutated nuclear DNA (nDNA), we will still eventually succumb to aging. Thus, we must save copies of mitochondrial and nuclear DNA at as young an age as possible, or at least from cell types with the lowest rates of mutation. MtDNA has a 10-100x higher rate of mutation than nDNA, as mitochondria are sites of free radical production. We may need to replace mtDNA before damaged and mutated nDNA. If so, we will need a strategy to deliver pristine mtDNA to cells around the the body and destroy the old mtDNA. A strategy for doing so is described herein.

Abstract: In 2022, an outbreak of H5N1 highly pathogenic avian influenza (HPAI) killed 60% of the largest breeding colony of Dalmatian pelican (DP) in the world, at Mikri Prespa Lake (Greece), prompting a multidisciplinary study on HPAI and other pathogens. This study determines the antimicrobial resistance rates of cloacal enterococci and Escherichia coli in DPs. Fifty-two blood and cloacal swab samples were collected from 31 nestlings (20 DP/11 great white pelicans) hatched after the H5N1 outbreak at the Prespa colony and 21 subadult/adult DPs captured at a spring migration stopover. Swabs were inoculated in non-selective and chromogenic selective media. Identification was performed by MALDI-TOF, and antimicrobial susceptibility was tested. The genetic content was characterized by PCR-sequencing and the clonality of extended-spectrum-betalactamase (ESBL)-producing-E. coli isolates by Multi-Locus-Sequence-Typing. Twenty-eight non-repetitive E. coli and 45 enterococci isolates were recovered in non-selective media; most of them were susceptible to all antibiotics tested (85.7% E. coli/91.1% enterococci). Three of 52 samples (6%, all adults) contained ESBL-E. coli isolates (detected in chromogenic ESBL plates), all carrying the bla_CTX-M-15 gene and belonging to the lineage ST69. Despite the susceptibility of most fecal E. coli and enterococci isolates to all antibiotics tested, the identification of E. coli of lineage ST69 carrying blaCTX-M-15 is of concern. This high-risk clone needs further investigation to elucidate its primary sources and address the growing threat of antimicrobial resistance from an integrated 'One Health' perspective. Furthermore, it is imperative to further study the potential impacts of ESBL-E. coli on the endangered DP.

Abstract: As urban areas face increasing challenges, integrating smart infrastructure, particularly IoT and AI technologies, has become vital for enhancing resilience. This study focuses on Baltimore as a case study to explore how scalable and adaptable smart infrastructure solutions can address diverse urban needs within a mid-sized U.S. city. Through a comprehensive review of Baltimore’s socioeconomic indicators and the development of a composite resilience score, this paper identifies key factors that facilitate or hinder the scalability and adaptability of smart infrastructure in economically and demographically varied urban contexts. The resilience score provides a quantitative measure of urban resilience, enabling the analysis of trends and dependencies among socioeconomic indicators over time. Findings reveal critical roles for both community engagement and policy support in adapting technologies to local needs, while economic and technical factors influence the scalability of IoT and AI projects. Based on these insights, the study proposes a framework that offers practical guidance for expanding Baltimore’s smart infrastructure in ways that are economically feasible, technically viable, and socially inclusive. This framework aims to assist Baltimore’s policymakers, urban planners, and technologists in advancing resilient, scalable solutions that align with the city's unique infrastructure needs and resource constraints.

Abstract: Understanding the mechanical properties of the grid component of textile-reinforced mortars (TRM) is critical because they directly influence the behaviour and strengthening capabilities of the composite. This study explored the dynamic tensile behaviour of a bi-directional basalt fibre grid using a high-speed servo-hydraulic direct tensile testing machine with specialised grips. Failure mode and deformation were captured with a high-speed camera. Tensile strain values were extracted from the recorded images using a Matlab computer vision tool - 'vision.PointTracker'. Specimen sizes of one and four rovings were tested at intermediate (1-8/s) and quasi-static (10-3/s) strain rates for comparison. After the tensile tests, scanning electron microscopy (SEM) analyses were performed to examine the microscopic failure of the grid. Linear and non-linear stress-strain behaviours were observed in the range of 10-3 to 1/s and 4 to 8/s, respectively. Increased strain rate enhanced tensile strength, ultimate strain, toughness, and elastic modulus. Overall, the dynamic increase factors for these properties, except for the elastic modulus, were between 1.4 and 2.3. At the macroscopic level, the grid generally failed in a brittle manner. However, microscopic analysis revealed that the fibre and polymer coating were strain rate sensitive. The enhanced tensile performance of the grid under dynamic loading circumstances makes it suitable for retrofitting structures prone to extreme loading conditions.

Abstract: Background Cancer is one of the most concerning public health issues in the world. One of cancer hallmarks wildly accepted is sustaining proliferative signaling, which involved most of the cell cycle biological activities. Centromeric histone, Centromere Protein A (CENPA), a variant of canonical histone H3, plays an essential role in selective chromosome segregation in the cell cycle. However, so far, a systematic pan-cancer bioinformatic analysis has not been done yet. Methods We accessed genome, transcriptome, and clinical information from open databases. The genetic alteration, mRNA expression, functional enrichment, stemness, mutation association, expression in cell populations and cellular locations, cell cycle association, survival association of CENPA, and immune association were analyzed. A prognostic model for glioma patients was constructed as an example application of CENPA as a biomarker. Drugs targeting CENPA in cancer cells were also screened and predicted by the CENPA correlation of drug sensitivity and protein-ligand docking. Results CENPA had low gene mutation in cancers. CENPA was overexpressed in almost all cancer types in TCGA compared to their normal control. CENPA was highly expressed in the nucleus of malignant cells. CENPA was associated with the cell cycle of cancer cells. CENPA is a biomarker for the cell cycle G2 phase in cancer cells. CENPA was a diagnostic and prognostic biomarker across multiple cancer types. The prognosis of glioma with CENPA was reliable and can be applied with other prognostic factors. CENPA was associated with the immune microenvironment. Drugs CD-437, 3-Cl-AHPC, Trametinib, BI-2536, and GSK461364 were predicted to target CENPA in cancer cells. Conclusion CENPA was a cell cycle biomarker in cancers with diagnostic and prognostic value.