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Aims: to prepare Indomethacin mouth wash and study some of its properties (IR, pH, Density, Viscosity, Surface tension). Also, the effect on gingival index score were evaluated. Indomethacin mouth wash was prepared in a concentration of (0.05%) distil water from pure Indomethacin powder. Methods: The study was carried out on 40 subjects aged (20-30) years old. They were divided into four groups ten for each, three groups complaining of gingivitis. The gingival index score for all were measured before and after treatment, treatment involved mechanical treatment by scaling and polishing at dental clinic and drug treatment in which the first group received Indomethacin mouth wash, second group received Chlorhexidine mouth wash and third group received distal water as a mouth wash three times daily for three days, while the fourth group consisted of 10 volunteer subjects without gingivitis. Data were analyzed using paired t-test, ANOVA test and Duncan's Multiple analysis range test. Results: The results showed that the gingival index score levels were decreased significantly in all treatment groups between pre and post treatment at the same group. Conclusions: Indomethacin mouth wash have anti inflammatory effect that can decrease gingival index level.

Abstract In the field of tissue engineering, achieving precise spatiotemporal control over engineered cells is critical for sculpting functional 2D cell cultures into intricate morphological shapes. In this study, we engineer light-responsive mammalian cells and target them with dynamic light patterns to realize 2D cell culture patterning control. To achieve this, we developed μPatternScope (μPS), a modular framework for software-controlled projection of high-resolution light patterns onto microscope samples. μPS comprises hardware and software suite governing pattern projection and microscope maneuvers. Together with a 2D culture of the engineered cells, we utilize μPS for controlled spatiotemporal induction of apoptosis to generate desired 2D shapes. Furthermore, we introduce interactive closed-loop patterning, enabling a dynamic feedback mechanism between the measured cell culture patterns and the light illumination profiles to achieve the desired target patterning trends. Our work offers innovative tools for advanced tissue engineering applications through seamless fusion of optogenetics, optical engineering, and cybernetics.

Abstract Recent advances in tissue engineering have been remarkable, yet the precise control of cellular behavior in 2D and 3D cultures remains challenging. One approach to address this limitation is to genomically engineer optogenetic control of cellular processes into tissues using gene switches that can operate with only a few genomic copies. Here, we implement blue and red light-responsive gene switches to engineer genomically stable two- and three-dimensional mammalian tissue models. Notably, we achieve precise control of cell death and morphogen-directed patterning in 2D and 3D tissues by optogenetically regulating cell necroptosis and synthetic WNT3A signaling at high spatiotemporal resolution. This is accomplished using custom-built patterned LED systems, including digital mirrors and photomasks, as well as laser techniques. These advancements demonstrate the capability of precise spatiotemporal modulation in tissue engineering and open up new avenues for developing programmable 3D tissue and organ models, with significant implications for biomedical research and therapeutic applications.

Abstract To evaluate the effect of combining different bioactive root-end filling materials with composite bone graft (xenogeneic mixed with autogenous bone fragments) on the healing process of periapical tissues after endodontic micro-surgery procedure. In this triple-blinded clinical trial, 56 patients were divided into 2 main groups (28 each) according to the root-end filling material and 2 subgroups according to the presence or absence of the composite bone graft material. Group I: MTA root-end filling (n = 28) in which there are Sub-group A: without bone graft (n = 14) and Sub-group B: with composite bone graft (n = 14). Group II: TotalFill root-end filling (n = 28) in which there are Sub-group A: without bone graft (n = 14) and Sub-group B: with composite bone graft (n = 14). Healthy patients whose ages range from 20 to 50 years with small-to-medium size radiolucency in CBCT related to single-rooted maxillary teeth were included in this study. Patients were assigned a number starting from 1 to 56 and were randomly allocated to four test groups (2 main groups and 2 sub-groups) following simple randomization procedure guidelines described by IBM SPSS V23 (IBM USA) statistical analysis software. This trial was triple-blind where the patient, the outcome assessors, and the main operator were blinded to the applied intervention. Every patient was evaluated clinically and by CBCT at two main observation periods: presurgical and 12-month post-operative. They were also examined and evaluated clinically and radiographically through periapical x-rays after one week, three, and six months. Statistical analysis was performed with IBM SPSS Statistics for Windows Version 23.0. Armonk, NY: IBM Corp. Of the 56 patients enrolled in the study, 49 patients were available for the final analysis. All groups showed no statistically significant differences with regard to healing or success rates at the 12-month follow-up mark. No adverse effects were encountered. Results showed that high success rates were achieved using MTA and TotalFill in the healing of periapical lesions after endodontic surgery. The addition of bone graft in small-to-medium size lesions did not affect the success rate of endodontic surgeries.

Abstract Background The ultimate aim of medical education is to produce successful practitioners, which is a goal that educators, students and stakeholders support. These groups consider success to comprise optimum patient care with consequently positive career progression. Accordingly, identification of the common educational features of such high-achieving doctors will facilitate the generation of clinical excellence amongst future medical trainees. In our study we source data from British clinical merit award schemes and subsequently identify the medical school origins of anaesthetists who have achieved at least national distinction. Methods Britain operates Distinction Award/Clinical Excellence Award schemes which honour National Health Service doctors in Scotland, Wales and England who are identified as high achievers. This quantitative observational study used these awards as an outcome measure in an analysis of the 2019–20 dataset of all 901 national award-winning doctors. Where appropriate, Pearson's Chi-Square test was applied. Results The top five medical schools (London university medical schools, Edinburgh, Dundee, Aberdeen and Glasgow) were responsible for 56.4% of the anaesthetist award-winners, despite the dataset representing 85 medical schools. 93.6% of the anaesthetist merit award-winners were from European medical schools. 8.06% of the anaesthetist award-winners were international medical graduates compared with 11.5% non-anaesthetist award-winners being international medical graduates. Conclusions The majority of anaesthetists who were national merit award-winners originated from only five, apparently overrepresented, UK university medical schools. In contrast, there was a greater diversity of medical school origins among the lower grade national award-winners; tier 3 award-winners represented 20 different medical schools from three continents. As well as ranking educationally successful university medical schools, this study assists UK and international students, by providing a roadmap for rational decision making when selecting anaesthetist and non-anaesthetist medical education pathways that are more likely to fulfil their career ambitions.

This review explores recent advancements in using biomass-derived materials for alkali metal-sulfur and selenium batteries, which are rapidly evolving in the field of high-energy–density storage systems. At the core of our discussion is the utilization of biomass-derived carbon (BDCs), emphasizing its vital role in enhancing the performance of these batteries. We examine the applications of carbon derived from biomass as hosts, extending our exploration beyond lithium-sulfur (Li-S) batteries to include a broader range of alkali metal combinations with sulfur and selenium. We emphasize the rational design and strategic use of biomass-derived materials in addressing challenges such as polysulfide and polyselenide dissolution and slow redox kinetics. The review highlights how these carbon materials contribute to high energy density and long cycling lifespans in sulfur and selenium-based batteries, enhancing stability and efficiency. Concluding with a forward-looking perspective, it identifies the ongoing need for innovation in biomass-derived carbon applications to advance alkali metal-sulfur and selenium batteries’ capabilities.

As load-bearing components, metallic implants are frequently used for orthopedic prostheses due to their superiority over conventional ceramic and polymeric biomaterials. Metal-based orthopedic implants have been subjected to various fabrication and treatment methods to enhance their biological activities at the host site. Modifying the structure, improving the hydrophilicity, and developing controlled-release drug delivery systems can improve cellular adhesion, proliferation, osseointegration, and differentiation. Ultrafast lasers have recently attracted interest in surface engineering. Laser surface structuring permits the alteration of sample topography, the chemical makeup of the surface, and the material physical properties. This study presents the surface modification of a TiNbZrSn shape memory alloy using a femtosecond laser to produce laser-induced periodic structures with better drug release than that of a pristine sample. We also present the in vitro cell viability and biocompatibility of the alloy system. All samples structured with femtosecond laser exhibited superhydrophilic nature with 0° contact angle. In addition, the laser structured surfaces showed cell viability above 80 % and minimal cytotoxicity towards human keratinocytes. Moreover, a well-defined hydroxyapatite layer developed on the laser structured surface. In general, the laser structuring process and the induced changes on the surface in terms of roughness and oxide formation result in slower drug release (up to 10 %) compared to pristine specimens.

Abstract Incorporating selenium into high-surface-area carbon with hierarchical pores, derived from red kidney bean peels via simple carbonization/activation, yields a superior Li–Se battery cathode material. This method produces a carbon framework with 568 m2 g−1 surface area, significant pore volume, and improves the composite’s electronic conductivity and stability by mitigating volume changes and reducing lithium polyselenide dissolution. The Se@ACRKB composite, containing 45 wt% selenium, shows high discharge capacities (609.13 mAh g−1 on the 2nd cycle, maintaining 470.76 mAh g−1 after 400 cycles at 0.2 C, and 387.58 mAh g−1 over 1000 cycles at 1 C). This demonstrates exceptional long-term stability and performance, also applicable to Na–Se batteries, with 421.36 mAh g−1 capacity after 200 cycles at 0.1 C. Our study showcases the potential of using sustainable materials for advanced battery technologies, emphasizing cost-effective and scalable solutions for energy storage.

Abstract Pediatric cardiomyopathies are mostly attributed to variants in sarcomere-related genes. Unfortunately, the genetic architecture of pediatric cardiomyopathies has never been previously studied in Jordan. We sought to uncover the genetic landscape of 14 patients from nine families with several subtypes of pediatric cardiomyopathies in Jordan using Exome sequencing (ES). Our investigation identified pathogenic and likely pathogenic variants in seven out of nine families (77.8%), clustering in sarcomere-related genes. Surprisingly, phenocopies of sarcomere-related hypertrophic cardiomyopathies were evident in probands with glycogen storage disorder and mitochondrial-related disease. Our study underscored the significance of streamlining ES or expanding cardiomyopathy-related gene panels to identify plausible phenocopies of sarcomere-related cardiomyopathies. Our findings also pointed out the need for genetic testing in patients with cardiomyopathy and their at-risk family members. This can potentially lead to better management strategies, enabling early interventions, and ultimately enhancing their prognosis. Finally, our findings provide an initial contribution to the currently absent knowledge about the molecular underpinnings of cardiomyopathies in Jordan.

Norhayati Mustafa Khalid,1 Pavapriya Ponvel,1 Azianah Mohamad Ibrahim,1 A’isyah Mohd Safien,1 Nurul Hidayah Md Fadzil,1 Devinder Kaur Ajit Singh,1 Arimi Fitri Mat Ludin,1 Norhayati Ibrahim,1 Ponnusamy Subramaniam,1 Hasnah Haron,1 Roslee Rajikan,1 Divya Vanoh,2 Suzana Shahar1 1Center for Healthy Aging and Wellness, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia; 2Dietetics Programme, School of Health Sciences, Universiti Sains Malaysia, Kelantan, MalaysiaCorrespondence: Suzana Shahar, Center for Healthy Aging and Wellness, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, Kuala Lumpur, 50300, Malaysia, Tel +60 392897163, Email suzana.shahar@ukm.edu.myPurpose: There is a limited availability of multidomain interventions that target cognitive frailty. Thus, the aim of the present study was to develop and evaluate the content validity and acceptance of the multidomain intervention module to reverse cognitive frailty among older adults (iAGELESS).Patients and Methods: This study was conducted in two phases: Phase I included the development of the multidomain intervention module iAGELESS and evaluation of content validity, while Phase II consisted of evaluating the acceptance of the module among 18 healthcare and social care providers, 13 older adults with cognitive frailty, and 13 caregivers. Content validity index (CVI) was used to quantify the content validity. Respondents completed a questionnaire which consisted of information on sociodemographic, followed by module acceptance evaluation with respect to content, terminologies, and graphics. The data was then analyzed descriptively.Results: A multidomain intervention module, iAGELESS was developed. The module was found to have appropriate content validity (overall CVI = 0.83). All the caregivers, 92% of older adults with cognitive frailty and 83% of healthcare and social care providers were satisfied with the overall content of the module. More than 50% of those who accepted the module had satisfactory consensus on the ease of the terminologies, length of sentences, pictures, information, color, and font size included in the module.Conclusion: The iAGELESS module demonstrated good content validity and was well accepted, thus warranting its utilization in future studies to determine its effectiveness in reversing cognitive frailty among older adults.Keywords: aging, cognitive frailty, multidomain intervention module, older adults, reversal

Abstract Central to analyzing noisy gene expression systems is solving the Chemical Master Equation (CME), which characterizes the probability evolution of the reacting species’ copy numbers. Solving CMEs for high-dimensional systems suffers from the curse of dimensionality. Here, we propose a computational method for improved scalability through a divide-and-conquer strategy that optimally decomposes the whole system into a leader system and several conditionally independent follower subsystems. The CME is solved by combining Monte Carlo estimation for the leader system with stochastic filtering procedures for the follower subsystems. We demonstrate this method with high-dimensional numerical examples and apply it to identify a yeast transcription system at the single-cell resolution, leveraging mRNA time-course experimental data. The identification results enable an accurate examination of the heterogeneity in rate parameters among isogenic cells. To validate this result, we develop a noise decomposition technique exploiting time-course data but requiring no supplementary components, e.g., dual-reporters.

Highlights Si/C Composite and Nanostructure Engineering: Advanced Si/C composites and multidimensional nanostructures address key challenges in silicon anodes, like volume expansion and unstable SEI, enhancing LIBs performance. Artificial SEI, Prelithiation, and Binders: Focus on stable artificial SEI layers, efficient prelithiation, and cutting-edge binders to improve Coulombic efficiency and reduce capacity loss, enhancing Si anode durability and efficiency. Real-World Application and Scalability: Analysis of these strategies highlights scalability and commercial viability, transitioning Si-anode technologies to practical, high-performance LIBs applications.

Autism is a challenging brain disorder affecting children at global and national scales. Applied behavior analysis is commonly conducted as an efficient medical therapy for children. This paper focused on one paradigm of applied behavior analysis, imitation, where children mimic certain lessons to enhance children’s social behavior and play skills. This paper introduces IMITASD, a practical monitoring assessment model designed to evaluate autistic children’s behaviors efficiently. The proposed model provides an efficient solution for clinics and homes equipped with mid-specification computers attached to webcams. IMITASD automates the scoring of autistic children’s videos while they imitate a series of lessons. The model integrates two core modules: attention estimation and imitation assessment. The attention module monitors the child’s position by tracking the child’s face and determining the head pose. The imitation module extracts a set of crucial key points from both the child’s head and arms to measure the similarity with a reference imitation lesson using dynamic time warping. The model was validated using a refined dataset of 268 videos collected from 11 Egyptian autistic children during conducting six imitation lessons. The analysis demonstrated that IMITASD provides fast scoring, takes less than three seconds, and shows a robust measure as it has a high correlation with scores given by medical therapists, about 0.9, highlighting its effectiveness for children’s training applications.

During recent years, research on authenticated encryption has been thriving through two highly active and practically motivated research directions: provable leakage resilience and key- or context-commitment security. However, the intersection of both fields had been overlooked until very recently. In ToSC 1/2024, Struck and Weishäupl studied generic compositions of encryption schemes and message authentication codes for building committing leakage-resilient schemes. They showed that, in general, Encrypt-then-MAC (EtM) and MAC-then-Encrypt (MtE) are not committing while Encrypt-and-MAC (EaM) is, under plausible and weak assumptions on the components. However, real-world schemes are rarely strict blackbox constructions. Instead, while various leakage-resilient schemes follow blueprints inspired by generic compositions, they often tweak them for security or efficiency. In this paper, we study two blueprints, the first one based on EtM for one of the strongest possible levels of leakage resilience. The second one is a single-pass framework based on leveled implementations. We show that, with a careful selection of the underlying primitives such as with identical encryption and authentication keys and a collision-resistant PRF as the MAC, these blueprints are committing. Our results do not contradict the results by Struck and Weishäupl since we pose more, but practically-motivated, requirements on the components. We demonstrate the practical relevance of our results by showing that our results on those blueprints allow us to easily derive proofs that several state-of-the-art leakage-resilient schemes are indeed committing, including TEDT and its descendants TEDT2 and Romulus-T, as well as the single-pass scheme Triplex.

The cathode in lithium-selenium (Li-Se) batteries has garnered extensive attention owing to its superior specific capacity and enhanced conductivity compared to sulfur. Nonetheless, the adoption and advancement of Li-Se batteries face significant challenges due to selenium’s low reactivity, substantial volume fluctuations, and the shuttle effect associated with polyselenides. Single-atom catalysts (SACs) are under the spotlight for their outstanding catalytic efficiency and optimal atomic utilization. To address the challenges of selenium’s low chemical activity and volume expansion in Li-Se batteries, through electrospun, we have developed a lotus root-inspired carbon nanofiber (CNF) material, featured internal multi-channels and anchored with molybdenum (Mo) single atoms (Mo@CNFs). Mo single atoms significantly enhance the conversion kinetics of selenium (Se), facilitating rapid formation of Li2Se. The internally structured multi-channel CNF serves as an effective host matrix for Se, mitigating its volume expansion during the electrochemical process. The resulting cathode, Se/Mo@CNF composite, exhibits a high discharge specific capacity, superior rate performance, and impressive cycle stability in Li-Se batteries. After 500 cycles at a current density of 1 C, it maintains a capacity retention rate of 82% and nearly 100% coulombic efficiency (CE). This research offers a new avenue for the application of single-atom materials in enhancing advanced Li-Se battery performance.

Several factors impact the durability of concrete bridge decks, including traffic loads, fatigue, temperature changes, environmental stress, and maintenance activities. Detecting problems such as corrosion, delamination, or concrete degradation early on can lower maintenance costs. Nondestructive evaluation (NDE) techniques can detect these issues at early stages. Each NDE method, meanwhile, has limitations that reduce the accuracy of the assessment. In this study, multiple NDE technologies were combined with machine learning algorithms to improve the interpretation of half-cell potential (HCP) and electrical resistivity (ER) measurements. A parametric study was performed to analyze the influence of five parameters on HCP and ER measurements, such as the degree of saturation, corrosion length, delamination depth, concrete cover, and moisture condition of delamination. The results were obtained through finite element simulations and used to build two machine learning algorithms, a classification algorithm and a regression algorithm, based on Random Forest methodology. The algorithms were tested using data collected from a bridge deck in the BEAST® facility. Both machine learning algorithms were effective in improving the interpretation of the ER and HCP measurements using data from multiple NDE technologies.