Background: The burden of unintentional injuries among youth (15-24 years) is high. There is paucity of data on unintentional injuries in youth working in Vocational Training Institutes.
Objective: To determine the incidence, characteristics, and risk factors of unintentional injuries among youth.
Methods: Design:: A retrospective cross-sectional survey was conducted among select vocational school youth in Peshawar, Pakistan between February 2022 to October 2022.Participants:: A total of 547 study participants participated in the survey, 356 were males while 191 were females. Data were collected on using the World Health Organization community survey guide for injuries and violence. Multilevel Negative Binomial Regression model was used to report incidence rate ratios of all unitentional injuries.
Results: A total of 503 injuries were reported by the youth, with road traffic injuries being the most common (n=197, 39%), followed by burns (n=89, 18%), falls (n=79, 16%) and poisonings (n=15, 3%), drownings (n=23, 7.1%). Occupational injuries reported during vocational training were (n=95, 18%). Males had a higher incidence rates of RTI 3.24[2.35-5.3], falls 1.30 [0.74-2.27], poisonings 2.14 [0.57-7.58] and drownings 2.46(0.84-7.21), while females had a higher incidence rate of burns 2.19 [1.785-3.46].Lack of education 4.6 [1.12 -18.91] (p=0.034), smoking 1.25 [1.05 -2.69] (p=0.049), lack of fathers education 4.71 [2.12 -10.49] (p=<0.001), carrying a gun 6.59 [2.54 -17.11] (p=<0.001), crowded families 3.59 [3.11 -5.07] (p=<0.001), lower family income 2.04 [1.04 -4.02](p=0.039*), lack of helmet use 4.54 [2.12 -9.76] (p=<0.001) and lack of seat belt use 1.3 [1.14 -1.69] (p= <0.001) were significant risk factors for unintentional injuries in youth.
Conclusion added value of the study: This study is one of the first research studies conducted in vocational school youth in Pakistan. It provides the recent rate of unintentional injuries among the youth of Pakistan. High occupational injuries among vocational school youth were reported which needs further research.
Migrate3D is a cell migration analysis tool whose purpose is to computationally process positional cell tracking data generated via other image acquisition/analysis software and generate biologically meaningful results. The functionalities of Migrate3D include step-based calculations of each cell track, single-cell-level summary statistics, mean squared displacement analysis, and machine learning-based evaluation of the entire dataset and subpopulations of cells found within it. The parameters calculated within Migrate3D have been previously developed and validated by other groups, and were selected to facilitate extraction of the maximum depth of information possible from input datasets. Variables are user-adjustable to enable customized analyses of diverse motility patterns and cell types, both in three-and two-dimensional timelapse data. Independent of any particular upstream image analysis or cell tracking software, Migrate3D only needs positional data over time to execute the suite of calculations. This presents a unique opportunity to standardize and streamline cell migration analysis.
The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Many important neurocognitive states, such as performing natural activities and fluctuations of arousal, shift over minutes-to-hours in the real-world. We harnessed 3-12 days of continuous multi-electrode intracranial recordings in twenty humans during natural behavior (socializing, using digital devices, sleeping, etc.) to study real-world neurodynamics. Applying deep learning with dynamical systems approaches revealed that brain networks formed consistent stable states that predicted behavior and physiology. Changes in behavior were associated with bursts of rapid neural fluctuations where brain networks chaotically explored many configurations before settling into new states. These trajectories traversed an hourglass-shaped structure anchored around a set of networks that slowly tracked levels of outward awareness related to wake-sleep stages, and a central attractor corresponding to default mode network activation. These findings indicate ways our brains use rapid, chaotic transitions that coalesce into neurocognitive states slowly fluctuating around a stabilizing central equilibrium to balance flexibility and stability during real-world behavior.
Background: Diarrhea remains a leading cause of childhood illness throughout the world that is increasing due to climate change and is caused by various species of ecologically sensitive pathogens. The emerging Planetary Health movement emphasizes the interdependence of human health with natural systems, and much of its focus has been on infectious diseases and their interactions with environmental and human processes. Meanwhile, the era of big data has engendered a public appetite for interactive web-based dashboards for infectious diseases. However, enteric infectious diseases have been largely overlooked by these developments.
Methods: The Planetary Child Health and Enterics Observatory (Plan-EO) is a new initiative that builds on existing partnerships between epidemiologists, climatologists, bioinformaticians, and hydrologists as well as investigators in numerous low- and middle-income countries. Its objective is to provide the research and stakeholder community with an evidence base for the geographical targeting of enteropathogen-specific child health interventions such as novel vaccines. The initiative will produce, curate, and disseminate spatial data products relating to the distribution of enteric pathogens and their environmental and sociodemographic determinants.
Discussion: As climate change accelerates there is an urgent need for etiology-specific estimates of diarrheal disease burden at high spatiotemporal resolution. Plan-EO aims to address key challenges and knowledge gaps by making rigorously obtained, generalizable disease burden estimates freely available and accessible to the research and stakeholder communities. Pre-processed environmental and EO-derived spatial data products will be housed, continually updated, and made publicly available to the research and stakeholder communities both within the webpage itself and for download. These inputs can then be used to identify and target priority populations living in transmission hotspots and for decision-making, scenario-planning, and disease burden projection.
Study registration: PROSPERO protocol #CRD42023384709.
BRAF V600E mutation is a driver mutation in the serrated pathway to colorectal cancers. BRAFV600E drives tumorigenesis through constitutive downstream extracellular signal-regulated kinase (ERK) activation, but high-intensity ERK activation can also trigger tumor suppression. Whether and how oncogenic ERK signaling can be intrinsically adjusted to a "just-right" level optimal for tumorigenesis remains undetermined. In this study, we found that FAK (Focal adhesion kinase) expression was reduced in BRAFV600E-mutant adenomas/polyps in mice and patients. In Vill-Cre;BRAFV600E/+;Fakfl/fl mice, Fak deletion maximized BRAFV600E's oncogenic activity and increased cecal tumor incidence to 100%. Mechanistically, our results showed that Fak loss, without jeopardizing BRAFV600E-induced ERK pathway transcriptional output, reduced EGFR (epidermal growth factor receptor)-dependent ERK phosphorylation. Reduction in ERK phosphorylation increased the level of Lgr4, promoting intestinal stemness and cecal tumor formation. Our findings show that a "just-right" ERK signaling optimal for BRAFV600E-induced cecal tumor formation can be achieved via Fak loss-mediated downregulation of ERK phosphorylation.
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：