Early Postoperative Weight Bearing Following the Reconstruction of Traumatic Complex Tibial Bone Defects by Vascularized Free Fibula and Ilizarov External Fixator: A Case Series.

Objective: Post-traumatic tibial bone defects represent a significant challenge to orthopedic surgeons. Various reconstructive methods are available based on associated local soft tissue injury and defect size. Free vascularized fibular graft represents a major successful technique; combined with a rigid Ilizarov external fixator, it allows safe, immediate postoperative weight bearing.

Technological innovations fuel carbon prices and transform environmental management across Europe.

This study investigates the impact of recent Artificial Intelligence (AI)-driven technological innovations on carbon prices across different quantiles, assessing the influence of AI stock prices on energy prices based on European carbon allowances while controlling for other macroeconomic factors. Using robust methods such as quantile-on-quantile regression, wavelet analysis, and transfer entropy, the research quantifies the information flow between the AI market and carbon allowances. Using daily data with four alternative AI stock prices from September 14, 2016, to December 29, 2023, the findings reveal a strong effect of AI returns on carbon prices, with significant fluctuations across price quantiles and consistent long-term average growth in market returns.

New thiazolidin-4-ones as anti-cervical cancer agents targeting EGFR: design, synthesis, and computational studies.

Aim: A new series of 3,4-dihydronaphthalen-1(2 h)-ylidene)hydrazineylidene)-5-substituted thiazolidin-4-one derivatives were designed and synthesized.

Results & Methodology: The new compounds were screened for in vitro antitumor activity against Hela cancer cell line. The compounds 7b, 7 h, and 7i produced more potent cytotoxicity than doxorubicin with IC values of 1.

The role of artificial intelligence literacy and innovation mindset in shaping nursing students' career and talent self-efficacy.

Background: As artificial intelligence (AI) transforms nursing education, AI literacy is becoming a critical necessity for increasing the career potential and talent of nursing students. Additionally, fostering an innovation mindset promotes adaptability, creativity and openness to new approaches, further boosting students' confidence in their careers. However, few studies have examined the impact of these competencies on nursing students' career and talent self-efficacy, underscoring the need for further investigation.

Regulatory T-cells: The Face-off of the Immune Balance.

Regulatory T-cells (Tregs) play a crucial role in maintaining immune homeostasis, ensuring a balanced immune response. Tregs primarily operate in an antigen-specific fashion, facilitated by their distinct distribution within discrete niches. Tregs have been studied extensively, from their point of origin in the thymus origin to their fate in the periphery or organs.

International nursing students' culture shock and academic engagement: The moderating role of resilience.

Background: The nursing profession has experienced a growing influx of international nursing students pursuing nursing degrees in the current era. Predicting and controlling culture shock among this special group is a critical issue as it shapes their academic engagement. Building resilience capabilities among this set of students is a pivotal necessity to buffer the effect of culture shock on their academic engagement.

Navigating transition shock: The role of system thinking in enhancing nursing process competency among early career nurses.

Background: Building nursing process competency among beginner nurses is a pivotal need in contemporary, complex, fast-paced nursing practice. However, transitioning from the educational phase to practicing as a nurse can be a significant adjustment. New practitioners often experience a period of shock, which may present challenges in developing nurse competency.

Machine learning models for prediction of nutrient concentrations in surface water in an agricultural watershed.

Prediction and quantification of nutrient concentrations in surface water has gained substantial attention during recent decades because excess nutrients released from agricultural and urban watersheds can significantly deteriorate surface water quality. Machine learning (ML) models are considered an effective tool for better understanding and characterization of nutrient release from agricultural fields to surface water. However, to date, no systematic investigations have examined the implementation of different classification and regression ML models in agricultural settings to predict nutrient concentrations in surface water using a group of input variables including climatological (e.

Novel 5-Fluorouracil analogues versus perfluorophenyl ureas as potent anti-breast cancer agents: Design, robust synthesis, in vitro, molecular docking, pharmacokinetics ADMET analysis and dynamic simulations.

To investigate the therapeutic potential of 5-Fluorouracil-based analogues, a straightforward synthetic technique was employed to synthesize a novel series of 5-arylurea uracil derivatives (AUFU01-03) and aryl-urea derivatives bearing perfluorophenyl (AUPF01-03). Reliable tools such as infrared (IR), Nuclear Magnetic Resonance (NMR) spectra, and elemental analyses were utilized to confirm the chemical structures and purity of these compounds. In comparison to healthy noncancerous control skin fibroblast cells (BJ-1), we examined the antiproliferative efficacy of compounds (AUFU01-03) and (AUPF01-03) against specific human malignant cell lines of the breast (MCF-7), and colon (HCT-116).

"Molecular Characterization of Extended Spectrum Beta-Lactamase Resistance in Pediatric Shigella Isolates in Egypt".

Shigellosis is a major cause of morbidity and mortality among children, especially in developing countries. The increased extended-spectrum beta-lactamase (ESBL) resistance in Shigella poses a challenge for effective treatment. To examine the antibiotic resistance and ESBL profile of Shigella isolates from children with acute diarrhea.

Decentralized fault-tolerant control of multi-mobile robot system addressing LiDAR sensor faults.

The control of multi-robot formations is a crucial aspect in various applications, such as transport, surveillance and monitoring environments. Maintaining robots in a specific formation pose or performing a cooperative task is a significant challenge when a fault occurs among any of the robots. This work presents a Decentralized Fault-Tolerant Control (DFTC) scheme that addresses lidar sensor faults within a system of multiple differential wheeled mobile robots.

The full-length transcriptional of the multiple spatiotemporal embryo-gonad tissues in chicken (Gallus gallus).

Objectives: Chicken (Gallus gallus), as the most economically important poultry, is a classical and ideal model for studying the mechanism of vertebrate developmental biology and embryology. However, the sex determination and differentiation in chicken is still elusive, which limited the application and slowed down many basic studies in chicken.

Data Description: We applied PacBio Iso-seq to multiple spatiotemporal embryo-gonad tissues in the male and female chicken, which contain the blastoderm (E0, un-differentiation stage), genital ridge (E3.

The Climate-Asthma Connection: Examining the Influence of Climate Change Anxiety on Asthma Control and Quality of Life: A Multi-National Study.

Aims: This study aims to identify the impact of climate change anxiety and asthma control on asthmatics' quality of life and examine the moderating role of climate change anxiety in this linkage.

Method: A multi-national cross-sectional study was conducted in four Arabian countries on 1266 asthmatics selected by convenience sampling. Data were collected from November 2023 to February 2024 using a climate anxiety scale, mini-asthma quality of life questionnaire, and an asthma control questionnaire.

The impact of FinTech technology on financial stability of the UAE.

Financial markets have witnessed significant disruptions driven by ongoing waves of financial innovation, and digitalization brought about by technological advances which are referred to as "FinTech". Consequently, this paper examines connectedness and risk transmission between FinTech industry, Blockchain, and stability of the financial sector in the UAE. Furthermore, it explores the impact of economic and financial turbulences such as COVID-19 pandemic on the transmission of shocks across FinTech and financial instability using a Time-varying Parameter Vector Autoregressive model.

Apolipoproteins have a major role in cellular tumor dormancy in triple negative breast cancer: In-silico study.

Triple-negative breast cancer (TNBC) lacks estrogen, progesterone, and human epidermal growth factor receptors and has a poor prognosis as it is resistant to chemotherapy. A new treatment option for this type of cancer may be by putting these malignant cells into dormancy. The oocyte's embryonic milieu presents a unique tumor reversion microenvironment by inducing growth arrest and changing cells' phenotypes.

Predictors of climate change literacy in the era of global boiling: a cross-sectional survey of Egyptian nursing students.

Background: Climate changes have led to health and environmental risks, so it has become essential to measure climate change literacy among the entire population, especially nursing students. The significant role of nursing students in raising public awareness and future healthcare roles emphasizes assessing the predictors of climate change literacy among nursing students.

Aims: This study seeks to identify the predictors of climate change literacy among nursing students in A Multi-Site Survey.

An Investigation on the Potential of Utilizing Aluminum Alloys in the Production and Storage of Hydrogen Gas.

The interest in hydrogen is rapidly expanding because of rising greenhouse gas emissions and the depletion of fossil resources. The current work focuses on employing affordable Al alloys for hydrogen production and storage to identify the most efficient alloy that performs best in each situation. In the first part of this work, hydrogen was generated from water electrolysis.