Perspectives on label-free microscopy of heterogeneous and dynamic biological systems.

Significance: Advancements in label-free microscopy could provide real-time, non-invasive imaging with unique sources of contrast and automated standardized analysis to characterize heterogeneous and dynamic biological processes. These tools would overcome challenges with widely used methods that are destructive (e.g., histology, flow cytometry) or lack cellular resolution (e.g., plate-based assays, whole animal bioluminescence imaging). Aim: This perspective aims to (1) justify the need for label-free microscopy to track heterogeneous cellular functions over time and space within unperturbed systems and (2) recommend improvements regarding instrumentation, image analysis, and image interpretation to address these needs. Approach: Three key research areas (cancer research, autoimmune disease, and tissue and cell engineering) are considered to support the need for label-free microscopy to characterize heterogeneity and dynamics within biological systems. Based on the strengths (e.g., multiple sources of molecular contrast, non-invasive monitoring) and weaknesses (e.g., imaging depth, image interpretation) of several label-free microscopy modalities, improvements for future imaging systems are recommended. Conclusion: Improvements in instrumentation including strategies that increase resolution and imaging speed, standardization and centralization of image analysis tools, and robust data validation and interpretation will expand the applications of label-free microscopy to study heterogeneous and dynamic biological systems.

Neurodevelopmental outcome in preterm infants with intraventricular hemorrhages: the potential of quantitative brainstem MRI.

OBJECTIVES: This retrospective study aimed to identify quantitative magnetic resonance imaging markers in the brainstem of preterm neonates with intraventricular hemorrhages. It delves into the intricate associations between quantitative brainstem magnetic resonance imaging metrics and neurodevelopmental outcomes in preterm infants with intraventricular hemorrhage, aiming to elucidate potential relationships and their clinical implications. MATERIALS AND METHODS: Neuroimaging was performed on preterm neonates with intraventricular hemorrhage using a multi-dynamic multi-echo sequence to determine T1 relaxation time, T2 relaxation time, and proton density in specific brainstem regions. Neonatal outcome scores were collected using the Bayley Scales of Infant and Toddler Development. Statistical analysis aimed to explore potential correlations between magnetic resonance imaging metrics and neurodevelopmental outcomes. RESULTS: Sixty preterm neonates (mean gestational age at birth 26.26 ± 2.69 wk; n = 24 [40%] females) were included. The T2 relaxation time of the midbrain exhibited significant positive correlations with cognitive (r = 0.538, P < 0.0001, Pearson's correlation), motor (r = 0.530, P < 0.0001), and language (r = 0.449, P = 0.0008) composite scores at 1 yr of age. CONCLUSION: Quantitative magnetic resonance imaging can provide valuable insights into neurodevelopmental outcomes after intraventricular hemorrhage, potentially aiding in identifying at-risk neonates. Multi-dynamic multi-echo sequence sequences hold promise as an adjunct to conventional sequences, enhancing the sensitivity of neonatal magnetic resonance neuroimaging and supporting clinical decision-making for these vulnerable patients.

A containerised approach for multiform robotic applications.

As the area of robotics achieves promising results, there is an increasing need to scale robotic software architectures towards real-world domains. Traditionally, robotic architectures are integrated using common frameworks, such as ROS. Therefore, systems with a uniform structure are produced, making it difficult to integrate third party contributions. Virtualisation technologies can simplify the problem, but their use is uncommon in robotics and general integration procedures are still missing. This paper proposes and evaluates a containerised approach for designing and integrating multiform robotic architectures. Our approach aims at augmenting preexisting architectures by including third party contributions. The integration complexity and computational performance of our approach is benchmarked on the EU H2020 SecondHands robotic architecture. Results demonstrate that our approach grants simplicity and flexibility of setup when compared to a non-virtualised version. The computational overhead of using our approach is negligible as resources were optimally exploited.

SVhawkeye: an ultra-fast software for user-friendly visualization of targeted structural fragments from BAM files.

SVhawkeye is a novel visualization software created to rapidly extract essential structural information from third-generation sequencing data, such as data generated by PacBio or Oxford Nanopore Technologies. Its primary focus is on visualizing various structural variations commonly encountered in whole-genome sequencing (WGS) experiments, including deletions, insertions, duplications, inversions, and translocations. Additionally, SVhawkeye has the capability to display isoform structures obtained from iso-seq data and provides interval depth visualization for deducing local copy number variation (CNV). One noteworthy feature of SVhawkeye is its capacity to genotype structural variations, a critical function that enhances the accuracy of structural variant genotyping. SVhawkeye is an open-source software developed using Python and R languages, and it is freely accessible on GitHub (https://github.com/yywan0913/SVhawkeye).

Prediction of Age-Related MicroRNA Signature in Mesenchymal Stem Cells by using Computational Methods.

BACKGROUND: Aging is a phenomenon which occurs over time and leads to the decay of living organisms. During the progression of aging, some age-associated diseases including cardiovascular disease, cancers, and neurological, mental, and physical disorders could develop. Genetic and epigenetic factors like microRNAs, as one of the post-transcriptional regulators of genes, play important roles in senescence. The self-renewal and differentiation capacity of mesenchymal stem cells makes them good candidates for regenerative medicine. OBJECTIVE: The objective of this study is to evaluate senescence-related miRNAs in human MSCs using bioinformatics analysis. METHODS: In this study, the Gene Expression Omnibus (GEO) database was used to investigate the senescence-related genome profile. Then, down-regulated genes were selected for further bioinformatics analysis with the assumption that their decreased expression is associated with an increased aging process. Considering that miRNAs can interfere in gene expression, miRNAs complementary to these genes were identified using bioinformatics software. RESULTS: Through bioinformatics analysis, we predicted hsa-miR-590-3p, hsa-miR-10b-3p, hsamiR- 548 family, hsa-miR-144-3p, and hsa-miR-30b-5p which involve in cellular senescence and the aging of human MSCs. CONCLUSION: miRNA mimics or anti-miRNA agents have the potential to be used as anti-aging tools for MSCs.

In silico simulation of glycosylation and related pathways.

Glycans participate in a vast number of recognition systems in diverse organisms in health and in disease. However, glycans cannot be sequenced because there is no sequencer technology that can fully characterize them. There is no "template" for replicating glycans as there are for amino acids and nucleic acids. Instead, glycans are synthesized by a complicated orchestration of multitudes of glycosyltransferases and glycosidases. Thus glycans can vary greatly in structure, but they are not genetically reproducible and are usually isolated in minute amounts. To characterize (sequence) the glycome (defined as the glycans in a particular organism, tissue, cell, or protein), glycosylation pathway prediction using in silico methods based on glycogene expression data, and glycosylation simulations have been attempted. Since many of the mammalian glycogenes have been identified and cloned, it has become possible to predict the glycan biosynthesis pathway in these systems. By then incorporating systems biology and bioprocessing technologies to these pathway models, given the right enzymatic parameters including enzyme and substrate concentrations and kinetic reaction parameters, it is possible to predict the potentially synthesized glycans in the pathway. This review presents information on the data resources that are currently available to enable in silico simulations of glycosylation and related pathways. Then some of the software tools that have been developed in the past to simulate and analyze glycosylation pathways will be described, followed by a summary and vision for the future developments and research directions in this area.

Fabrication of Human Milk Fat Substitute: Based on the Similarity Evaluation Model and Computer Software.

We aimed to obtain the optimal formula for human milk fat substitute (HMFS) through a combination of software and an evaluation model and further verify its practicability through an animal experiment. The results showed that a total of 33 fatty acid (FA) and 63 triglyceride (TAG) molecular species were detected in vegetable oils. Palmitic acid, oleic acid, linoleic acid, 18:1/16:0/18:1, 18:2/16:0/18:2, 18:1/18:1/18:1 and 18:1/18:2/18:1, were the main molecular species among the FAs and TAGs in the vegetable oils. Based on the HMFS evaluation model, the optimal mixed vegetable oil formula was blended with 21.3% palm oil, 2.8% linseed oil, 2.6% soybean oil, 29.9% rapeseed oil and 43.4% maize oil, with the highest score of 83.146. Moreover, there was no difference in the weight, blood routine indices or calcium and magnesium concentrations in the feces of the mice between the homemade mixed vegetable oil (HMVO) group and the commercial mixed vegetable oil (CMVO) group, while nervonic acid (C24:1) and octanoic acid (C8:0) were absorbed easily in the HMVO group. Therefore, these results demonstrate that the mixing of the different vegetable oils was feasible via a combination of computer software and an evaluation model and provided a new way to produce HMFS.

Paradigm Shift in Rhinoplasty with Virtual 3D Surgery Software and 3D Printing Technology.

Most Asians have a nose with a short columella and a low dorsum; augmentation rhinoplasty using implants is commonly performed in Asian countries to achieve a taller and more well-defined nasal dorsum. However, the current knowledge is insufficient to fully understand the various subjective desires of patients, reflect on them during surgery, or to objectively analyze the results after surgery. Advances in digital imaging technologies, such as 3D printing and 3D scanning, have transformed the medical system from hospital-centric to patient-centric throughout the medical field. In this study, we applied these techniques to rhinoplasty. First, we used virtual 3D plastic surgery software to enable surgical planning through objectified numerical calculations based on the visualized data of the patient's medical images rather than simple virtual plastic surgery. Second, the customized nasal implant was manufactured by reflecting the patient's anatomical shape and virtual 3D plastic surgery data. Taken together, we describe the surgical results of applying these rhinoplasty solutions in four patients. Our experience indicates that high fidelity and patient satisfaction can be achieved by applying these techniques.

Low-carbon scheduling of electricity consumption in wastewater treatment plant by using photovoltaic system.

Sewage treatment as a high energy consumption industry, its electricity consumption accounts for 3 % of the total electricity consumption of society. That means significant greenhouse gas emissions. In the context of China's goal of "reaching carbon peak by 2030 and achieving carbon neutrality by 2060", reducing the energy consumption of wastewater treatment systems has emerged as an important issue in recent years. In this paper, the GPS-X simulation software was employed to conduct a simulation study of a modified Anoxic-Aerobic-Oxic wastewater treatment plant (WWTP) in Wuhan, and the response surface methodology (RSM) was utilized to ascertain the interactive effects of DO, IRF, ERR, and SD on the effluent quality, thereby identifying the operational parameters that minimize energy consumption while maintaining satisfactory effluent quality. Additionally, the PVsyst software was employed to design the solar power generation system of the WWTP and analyze its power generation potential. On this basis, through the coupling of photovoltaic power, electricity load, time-of-use pricing, and the water quality simulation model, and taking the WWTP data in September as a case study, the electricity usage strategies under various illumination conditions were formulated. The aim is to maximize the use of photovoltaic power to reduce the cost and carbon emissions of the WWTP. The results show that the optimal combination of operational parameters, including an external reflux ratio of 0.3, the internal recycle flow of 50,000 m3/d, and the sludge discharge of 448 m3/d, resulted in a reduction in power of 208.5 kW, and after the combination optimization of operational parameters and electricity utilization, the operation cost of the WWTP in September was reduced by 40 % âˆ¼ 60 %, and the carbon emission attributable to electricity was reduced by 30 % âˆ¼ 50 %.

Global hotspots and trends in microbial-mediated grassland carbon cycling: a bibliometric analysis.

Grasslands are among the most widespread environments on Earth, yet we still have poor knowledge of their microbial-mediated carbon cycling in the context of human activity and climate change. We conducted a systematic bibliometric analysis of 1,660 literature focusing on microbial-mediated grassland carbon cycling in the Scopus database from 1990 to 2022. We observed a steep increase in the number of multidisciplinary and interdisciplinary studies since the 2000s, with focus areas on the top 10 subject categories, especially in Agricultural and Biological Sciences. Additionally, the USA, Australia, Germany, the United Kingdom, China, and Austria exhibited high levels of productivity. We revealed that the eight papers have been pivotal in shaping future research in this field, and the main research topics concentrate on microbial respiration, interaction relationships, microbial biomass carbon, methane oxidation, and high-throughput sequencing. We further highlight that the new research hotspots in microbial-mediated grassland carbon cycling are mainly focused on the keywords "carbon use efficiency," "enzyme activity," "microbial community," and "high throughput sequencing." Our bibliometric analysis in the past three decades has provided insights into a multidisciplinary and evolving field of microbial-mediated grassland carbon cycling, not merely summarizing the literature but also critically identifying research hotspots and trends, the intellectual base, and interconnections within the existing body of collective knowledge and signposting the path for future research directions.

Comparison of qualitative and fully automated quantitative tools for classifying severity of white matter hyperintensity.

OBJECTIVE: In this study, we aimed to compare the Fazekas scoring system and quantitative white matter hyperintensity volume in the classification of white matter hyperintensity severity using a fully automated analysis software to investigate the reliability of quantitative evaluation. MATERIALS AND METHODS: Patients with suspected cognitive impairment who underwent medical examinations at our institution between January 2010 and May 2021 were retrospectively examined. White matter hyperintensity volumes were analyzed using fully automated analysis software and Fazekas scoring (scores 0-3). Using one-way analysis of variance, white matter hyperintensity volume differences across Fazekas scores were assessed. We employed post-hoc pairwise comparisons to compare the differences in the mean white matter hyperintensity volume between each Fazekas score. Spearman's rank correlation test was used to investigate the association between Fazekas score and white matter hyperintensity volume. RESULTS: Among the 839 patients included in this study, Fazekas scores 0, 1, 2, and 3 were assigned to 68, 198, 217, and 356 patients, respectively. White matter hyperintensity volumes significantly differed according to Fazekas score (F=623.5, p<0.001). Post-hoc pairwise comparisons revealed significant differences in mean white matter hyperintensity volume between all Fazekas scores (p<0.05). We observed a significantly positive correlation between the Fazekas scores and white matter hyperintensity volume (R=0.823, p<0.01). CONCLUSIONS: Quantitative white matter hyperintensity volume and the Fazekas scores are highly correlated and may be used as indicators of white matter hyperintensity severity. In addition, quantitative analysis may be more effective in classifying advanced white matter hyperintensity lesions than the Fazekas classification.

Developmental validation of the ForenSeq® Kintelligence kit, MiSeq FGx® sequencing system and ForenSeq Universal Analysis Software.

Forensic Investigative Genetic Genealogy, a recent sub discipline of forensic genomics, leverages the high throughput and sensitivity of detection of next generation sequencing and established genetic and genealogical approaches to support the identification of human remains from missing persons investigations and investigative lead generation in violent crimes. To facilitate forensic DNA evidence analysis, the ForenSeq® Kintelligence multiplex, consisting of 10,230 SNPs, was developed. Design of the ForenSeq Kintelligence Kit, the MiSeq FGx® Sequencing System and the ForenSeq Universal Analysis Software is described. Developmental validation in accordance with SWGDAM guidelines and forensic quality assurance standards, using single source samples, is reported for the end-to-end workflow from library preparation to data interpretation. Performance metrics support the conclusion that more genetic information can be obtained from challenging samples compared to other commercially available forensic targeted DNA assays developed for capillary electrophoresis (CE) or other current next generation sequencing (NGS) kits due to the higher number of markers, the overall shorter amplicon sizes (97.8% <150 bp), and kit design. Data indicate that the multiplex is robust and fit for purpose for a wide range of quantity and quality samples. The ForenSeq Kintelligence Kit and the Universal Analysis Software allow transfer of the genetic component of forensic investigative genetic genealogy to the operational forensic laboratory.

Effect of emphysema on AI software and human reader performance in lung nodule detection from low-dose chest CT.

BACKGROUND: Emphysema influences the appearance of lung tissue in computed tomography (CT). We evaluated whether this affects lung nodule detection by artificial intelligence (AI) and human readers (HR). METHODS: Individuals were selected from the "Lifelines" cohort who had undergone low-dose chest CT. Nodules in individuals without emphysema were matched to similar-sized nodules in individuals with at least moderate emphysema. AI results for nodular findings of 30-100 mm3 and 101-300 mm3 were compared to those of HR; two expert radiologists blindly reviewed discrepancies. Sensitivity and false positives (FPs)/scan were compared for emphysema and non-emphysema groups. RESULTS: Thirty-nine participants with and 82 without emphysema were included (n = 121, aged 61 ± 8 years (mean ± standard deviation), 58/121 males (47.9%)). AI and HR detected 196 and 206 nodular findings, respectively, yielding 109 concordant nodules and 184 discrepancies, including 118 true nodules. For AI, sensitivity was 0.68 (95% confidence interval 0.57-0.77) in emphysema versus 0.71 (0.62-0.78) in non-emphysema, with FPs/scan 0.51 and 0.22, respectively (p = 0.028). For HR, sensitivity was 0.76 (0.65-0.84) and 0.80 (0.72-0.86), with FPs/scan of 0.15 and 0.27 (p = 0.230). Overall sensitivity was slightly higher for HR than for AI, but this difference disappeared after the exclusion of benign lymph nodes. FPs/scan were higher for AI in emphysema than in non-emphysema (p = 0.028), while FPs/scan for HR were higher than AI for 30-100 mm3 nodules in non-emphysema (p = 0.009). CONCLUSIONS: AI resulted in more FPs/scan in emphysema compared to non-emphysema, a difference not observed for HR. RELEVANCE STATEMENT: In the creation of a benchmark dataset to validate AI software for lung nodule detection, the inclusion of emphysema cases is important due to the additional number of FPs. KEY POINTS: • The sensitivity of nodule detection by AI was similar in emphysema and non-emphysema. • AI had more FPs/scan in emphysema compared to non-emphysema. • Sensitivity and FPs/scan by the human reader were comparable for emphysema and non-emphysema. • Emphysema and non-emphysema representation in benchmark dataset is important for validating AI.

Human-Centered Design and Benefit Realization Management in Digital Health Care Solution Development: Protocol for a Systematic Review.

BACKGROUND: Earlier research shows that a significant number of resources are wasted on software projects delivering less than the planned benefits. It has, however, been evidenced that adopting a human-centered design approach when designing health devices can be beneficial. This understanding from earlier research has raised our interest in investigating how human-centered design might contribute to realizing the potential benefits of health care software projects. To our current knowledge, this intersection of human-centered design and benefit realization management has not yet comprehensively and consistently been researched within the context of digital health care solutions. Therefore, there is a need for evidence synthesis using systematic reviews to address this potential research gap. OBJECTIVE: The objective of this study is to examine if human-centered design helps benefit realization management processes in the development of digital health care solutions and thereby enables better benefit realization. We explore the evidence of assumed or confirmed benefits of using human-centered design in the health care domain and whether better results have been reported when the benefit realization management process is followed. METHODS: This protocol was developed following the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines. The proposed review would use a planned and systematic approach to identify, evaluate, and synthesize relevant and recent studies (reported in English) to see if there is evidence that using human-centered design and benefit realization management has a positive effect on realizing set benefits in those projects. We will commence a systematic literature search using human-centered design, benefit realization management, and health care-related search terms within 5 repositories (ACM Digital Library, PubMed Central, Scopus, PubMed, and Web of Science). After removing duplicate results, a preliminary scan for titles and abstracts will be done by at least 2 reviewers. Any incongruities regarding whether to include articles for full-text review will be resolved by a third reviewer based on the predefined criteria. RESULTS: Initial queries of 2086 records have been executed and papers are being prescreened for inclusion. The search was initiated in December 2023 and the results are expected in 2024. We anticipate finding evidence of the use of human-centered design in the development of digital health care solutions. However, we expect evidence of benefitting from both human-centered design and benefit realization management in this context to be scarce. CONCLUSIONS: This protocol will guide the review of existing literature on the use of human-centered design and benefit realization management when developing digital health care solutions. The review will specifically focus on finding evidence of confirmed benefits derived from the use of human-centered design and benefit realization management. There may be an opportunity to gain a broader understanding of the tools or approaches that provide evidence of increased benefit realization within the health care domain. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56125.

Development of web-based software for environmental impact assessment focusing on road traffic noise.

In the Republic of Korea, Environmental Impact Assessment (EIAs) precedes development projects to predict and analyze potential environmental effects. Generally, EIA noise evaluations utilize 2D noise prediction equations and correction coefficients. This method, however, offers only a sectional noise evaluation and has limitations in complex environments with diverse noise sources. Moreover, the determination of various variables during the EIA process based on subjective human judgment raises concerns about the reliability of the results. Thus, this study aims to develop software accessible via a web environment for user-friendly EIA noise evaluations. This software supports integrated data management and generates a 3D noise prediction model for more precise and realistic analysis of noise impacts, specifically focusing on road-traffic noise at this stage of development. The 3D noise prediction model and noise map generated by the developed software have been validated against through comparison with the results of onsite noise measurements and commercial EIA software, SoundPLAN. This validation aimed to assess the practical utility of the application.

Svetlana a supervised segmentation classifier for Napari.

We present Svetlana (SuperVised sEgmenTation cLAssifier for NapAri), an open-source Napari plugin dedicated to the manual or automatic classification of segmentation results. A few recent software tools have made it possible to automatically segment complex 2D and 3D objects such as cells in biology with unrivaled performance. However, the subsequent analysis of the results is oftentimes inaccessible to non-specialists. The Svetlana plugin aims at going one step further, by allowing end-users to label the segmented objects and to pick, train and run arbitrary neural network classifiers. The resulting network can then be used for the quantitative analysis of biophysical phenoma. We showcase its performance through challenging problems in 2D and 3D and provide a comprehensive discussion on its strengths and limits.

Gender differences in patterns of cartilage loss: Data from the Osteoarthritis Initiative.

OBJECTIVE: Understanding gender-specific differences in patterns of cartilage loss can improve our knowledge of the pathogenesis of knee osteoarthritis (KOA) development and progression and may inform clinical trials of treatments for KOA. The goal of our observational study was to examine gender differences in patterns of cartilage loss in the central weight-bearing regions of the femur. METHODS: We measured cartilage volume change in the indexed knee of 700 subjects with Kellgren-Lawrence 1, 2, or 3 from the Osteoarthritis Initiative for four follow-up periods (baseline [BL] to 24 mo, BL to 48 mo, BL to 72 mo, and BL to 96 mo) using the local area cartilage segmentation (LACS) method. Briefly, the LACS method uses robust coordinate systems fixed to anatomical landmarks to measure patterns of change in cartilage volume in sub-regions using responsiveness heat maps. RESULTS: We observed a statistically significant gender difference in cartilage change in the medial femur (MF), lateral femur (LF), and medial tibia. The heat maps showed loss was primarily in the posterior central weight-bearing portion of the LF and more general in the LT and MF. Similar patterns were observed for each of the four follow-up periods. CONCLUSIONS: The LACS method was capable of illustrating gender-specific differences in patterns of cartilage loss that may offer insight into the variation of gender differences in the natural history of KOA and may be useful in evaluating the benefit of interventions for KOA.

Assessing environmental impacts of a textile company using life cycle assessment approach-a case study.

The textile industry is known for its significant environmental impact, and as such, there is a growing need to assess the industry's production practices. Life cycle assessment (LCA) is an effective tool for measuring the environmental impact of textile products from raw material production to end-of-life disposal. Surat city, known as textile hub of India, has multiple industrial clusters that play host to different elements of the textile value chain. This research aims to evaluate the environmental performance of a Surat-based textile company. The study involves the collection of data from textile manufacturing facilities, including gray cloth production and wet processes (gate-to-gate approach). The data collected has been analyzed using the GABI (9.2.1 version) software. The study provides potential environmental impact data on present textile technology and production situation. Significant hotspots have been determined throughout supply chain and the associated drivers identified. However, the industry's environmental impact can be reduced by practicing ecoefficiency, immaterialization, and recycling textile waste. This research highlights the importance of LCA in identifying the environmental impact of the textile industry and provides a basis for developing sustainable practices to minimize the industry's environmental impact.

Normative values of skeletal muscle mass, strength and performance in the Indian population.

BACKGROUND AND OBJECTIVES: Skeletal muscle is characterized by its mass, strength and performance. These normative values are pivotal in defining sarcopenia. Sarcopenia is associated with poor outcome of numerous medical and surgical conditions. This study aimed to establish normative benchmarks for skeletal muscle mass, strength and performance within the context of the Asian (Indian) population. METHODS: Our investigation utilized the computed tomography (CT) skeletal muscle index (SMI), handgrip strength (HGS), gait velocity and chair-stand test to construct reference values for muscle characteristics in the Indian population. RESULTS: The SMI analysis incorporated 1485 cases of acute abdomen (54.7%) males). The calculated SMI (kg/m2) was 38.50 (35.05-42.30) in males and 36.30 (32.20-41.20) in females (p = 0.510). The study also involved 3083 healthy individuals (67.6% males) evaluated for muscle strength and performance between August 2017 and August 2018. Notably, HGS (kg force) was recorded at 34.95 (26.50-43.30) in males and 25.50 (18.60-31.20) in females (p < 0.001). Gait velocity (metres/second) exhibited values of 1.25 (1.04-1.56) in males and 1.24 (1.03-1.56) in females (p = 0.851). Additionally, chair-stand test (seconds) results were 10.00 (9.00-13.00) in males and 12.00 (10.00-14.00) in females (p < 0.001). CONCLUSIONS: The investigation determined that males had greater muscle strength and performance than females. But gender wise, there was no significant difference in muscle mass. Interestingly, our population's muscle parameters were consistently lower compared to western literature benchmarks. These normative values will help to define sarcopenia parameters in our population, which have prognostic value in multiple ailments.

Use of Digital Tools for the Assessment of Food Consumption in Brazil: A Scoping Review.

This is a scoping review on mapping the use of digital tools to assess food consumption in Brazil. Searches were carried out in nine electronic databases (Medline, Lilacs, Scopus, Embase, Web of Science, Science Direct, Ovid, Free Medical Journal and Crossref) to select studies published from October 2020 to December 2023. This review identified forty-eight digital tools in the 94 publications analyzed, the most frequent being web-based technologies (60%) and mobile devices (40%). Among these studies, 55% (n = 52) adopted a population-based approach, while 45% (n = 42) focused on specific regions. The predominant study design observed was cross-sectional (n = 63). A notable trend observed was the increasing frequency of validation studies in recent years. Although the use of digital tools in the assessment of food consumption in Brazil has grown in recent years, studies did not describe the process of creating and validating the tools, which would contribute to the improvement of data quality. Investments that allow the expansion of the use of the internet and mobile devices; the improvement of digital literacy; and the development of open-access tools, especially in the North and Northeast regions, are challenges that require a concerted effort towards providing equal opportunities, fostering encouragement, and delving deeper into the potential of digital tools within studies pertaining to food consumption in Brazil.