Early Patterns Research Articles

Early childhood sleep quantity, but not caregiver-reported sleep problems, predicts impulse control in children at age 8 years

ABSTRACT Short duration of sleep and poor sleep quality have been linked to poor attention and impulse control in children. We aimed to determine the longitudinal predictive value of sleep quantity and quality during early childhood on objective and caregiver-report measures of attention, impulse control, and executive function in children at age 8 years. We used data from the Health Outcomes and Measures of the Environment (HOME) Study, a pregnancy and birth cohort. Caregivers reported on their child’s sleep at ages 2, 2.5, 3, 4, and 5 years. Analysis included 410 participants. We used longitudinal growth curve models of early childhood sleep patterns to predict neurobehavioral functioning at age 8 years. Sleep problems did not predict any of our outcome measures at age 8 years. Sleep duration trended shorter as children matured, so predictive models examined both intercept and slope. Children with the least decline in sleep duration across early childhood had fewer impulsive errors at age 8 years on a continuous performance test (unadjusted p = .013; adjusted p = .013). Children with shorter duration of sleep across early childhood had worse caregiver-reported behavioral regulation at age 8 years (unadjusted p = .002; adjusted p = .043). Neither sleep duration slope nor intercept predicted inattention or metacognitive skills at age 8 years (p > .05). Total sleep time across early childhood predicts behavior regulation difficulties in school-aged children. Inadequate sleep during early childhood may be a marker for, or contribute to, poor development of a child’s self-regulatory skills.

Evaluation of cardiac electromechanics in patients with newly diagnosed hypertension.

This study aimed to investigate the relationship between subclinical left ventricular (LV) systolic dysfunction and ECG parameters in newly diagnosed hypertension patients. In this cross-sectional study, adults diagnosed with hypertension based on 24-h ambulatory blood pressure monitor recordings were included. The patients were classified into two groups based on the presence of subclinical LV systolic dysfunction according to LV global longitudinal strain (LVGLS). Findings were compared between the two groups. A total of 244 patients (female, 55.7%) were included. Based on LVGLS, 82 (33.6%) patients had subclinical LV systolic dysfunction. The proportion of early repolarization pattern (ERP) on ECG was significantly higher in patients with subclinical LV systolic dysfunction than in patients with normal LV systolic function [24 (28.6%) vs. 8 (5%), P < 0.001]. PR and corrected QT intervals were also significantly longer in patients with subclinical LV systolic dysfunction than in patients with normal LV systolic function [median (interquartile range), 148 (132-158) vs. 141 (127-152), P = 0.036 and 443 (427-459) vs. 431 (411-455), P = 0.007, respectively]. According to multivariate regression analysis ERP, early (E) wave velocity/late (A) wave velocity (E/A), and LV mass index were independently associated with subclinical LV systolic dysfunction. In newly diagnosed hypertension patients, the ERP on admission ECG could be a sign of subclinical systolic dysfunction.

Nailfold videocapillaroscopy patterns in systemic sclerosis: implications for cutaneous subsets, disease features and prognostic value for survival.

To assess the associations and prognostic value of scleroderma patterns by nailfold videocapillaroscopy (NVC) in patients with systemic sclerosis (SSc) and cutaneous subsets. At baseline, 1356 SSc patients from the RESCLE registry were compared according to the scleroderma pattern as Late pattern and non-Late pattern, which included Early and Active patterns. Patient characteristics, disease features, survival time and causes of death were analysed. Late pattern was identified in 540 (39.8%), and non-Late pattern in 816 (60.2%) patients (88% women; 987 lcSSc/251 dcSSc). Late pattern was associated to dcSSc (OR=1.96; p<0.001), interstitial lung disease (ILD) (OR=1.29; p=0.031), and scleroderma renal crisis (OR=3.46; p<0.001). Once the cutaneous subset was disregarded in an alternative analysis, both digital ulcers (DU) (OR=1.29; p<0.037) and anti-topoisomerase I antibodies (OR=1.39; p< 0.036) emerged associated with the Late pattern. By cutaneous subsets, associations with Late pattern were: (1) in dcSSc, acro-osteolysis (OR=2.13; p=0.022), and systolic pulmonary artery pressure >40 mmHg by Doppler echocardiogram (OR=2.24; p<0.001); and (2) in lcSSc, ILD (OR=1.38; p=0.028). Survival was reduced in dcSSc with Late pattern compared to non-Late pattern (p=0.049). Risk factors for SSc mortality in multivariate regression Cox analysis were age at diagnosis (HR=1.03; p<0.001), dcSSc (HR=2.48; p<0.001), DU (HR=1.38; p=0.046), ILD (HR=2.81; p<0.001), and pulmonary arterial hypertension (HR=1.99; p<0.001). SSc patients with Late pattern more frequently present dcSSc and develop more fibrotic and vascular manifestations. Advanced microangiopathy by NVC identifies dcSSc patients at risk of reduced survival due to SSc-related causes.

Presymptomatic and early pathological features of MAPT-associated frontotemporal lobar degeneration

Early pathological features of frontotemporal lobar degeneration (FTLD) due to MAPT pathogenic variants (FTLD-MAPT) are understudied, since early-stage tissue is rarely available. Here, we report unique pathological data from three presymptomatic/early-stage MAPT variant carriers (FTLD Clinical Dementia Rating [FTLD-CDR] = 0–1). We examined neuronal degeneration semi-quantitatively and digitally quantified tau burden in 18 grey matter (9 cortical, 9 subcortical) and 13 white matter (9 cortical, 4 subcortical) regions. We compared presymptomatic/early-stage pathology to an intermediate/end-stage cohort (FTLD-CDR = 2–3) with the same variants (2 L315R, 10 P301L, 6 G272V), and developed a clinicopathological staging model for P301L and G272V variants. The 68-year-old presymptomatic L315R carrier (FTLD-CDR = 0) had limited tau burden morphologically similar to L315R end-stage carriers in middle frontal, antero-inferior temporal, amygdala, (para-)hippocampus and striatum, along with age-related Alzheimer’s disease neuropathological change. The 59-year-old prodromal P301L carrier (FTLD-CDR = 0.5) had highest tau burden in anterior cingulate, anterior temporal, middle/superior frontal, and fronto-insular cortex, and amygdala. The 45-year-old early-stage G272V carrier (FTLD-CDR = 1) had highest tau burden in superior frontal and anterior cingulate cortex, subiculum and CA1. The severity and distribution of tau burden showed some regional variability between variants at presymptomatic/early-stage, while neuronal degeneration, mild-to-moderate, was similarly distributed in frontotemporal regions. Early-stage tau burden and neuronal degeneration were both less severe than in intermediate-/end-stage cases. In a subset of regions (10 GM, 8 WM) used for clinicopathological staging, clinical severity correlated strongly with neuronal degeneration (rho = 0.72, p < 0.001), less strongly with GM tau burden (rho = 0.57, p = 0.006), and did not with WM tau burden (p = 0.9). Clinicopathological staging showed variant-specific patterns of early tau pathology and progression across stages. These unique data demonstrate that tau pathology and neuronal degeneration are present already at the presymptomatic/early-stage of FTLD-MAPT, though less severely compared to intermediate/end-stage disease. Moreover, early pathological patterns, especially of tau burden, differ partly between specific MAPT variants.

Comparative evaluation of early postpartum breast feeding patterns in women undergoing caesarean section and vaginal delivery

Comparative evaluation of early postpartum breast feeding patterns in women undergoing caesarean section and vaginal delivery

Longitudinal mapping of the development of cortical thickness and surface area in rhesus macaques during the first three years

Studying dynamic spatiotemporal patterns of early brain development in macaque monkeys is critical for understanding the cortical organization and evolution in humans, given the phylogenetic closeness between humans and macaques. However, due to huge challenges in the analysis of early brain Magnetic Resonance Imaging (MRI) data typically with extremely low contrast and dynamic imaging appearances, our knowledge of the early macaque cortical development remains scarce. To fill this critical gap, this paper characterizes the early developmental patterns of cortical thickness and surface area in rhesus macaques by leveraging advanced computing tools tailored for early developing brains based on a densely sampled longitudinal dataset with 140 rhesus macaque MRI scans seamlessly covering from birth to 36 mo of age. The average cortical thickness exhibits an inverted U-shaped trajectory with peak thickness at around 4.3 mo of age, which is remarkably in line with the age of peak thickness at 14 mo in humans, considering the around 3:1 age ratio of human to macaque. The total cortical surface area in macaques increases monotonically but with relatively lower expansions than in humans. The spatial distributions of thicker and thinner regions are quite consistent during development, with gyri having a thicker cortex than sulci. By 4 mo of age, over 81% of cortical vertices have reached their peaks in thickness, except for the insula and medial temporal cortices, while most cortical vertices keep expanding in surface area, except for the occipital cortex. These findings provide important insights into early brain development and evolution in primates.

A Clinical Review of Physical Rehabilitation Protocol and Early Mobilization Patterns for Post-COVID-19 Patients: Tertiary Healthcare Facility Experience

Several studies have emphasized the urgent need for Physical Rehabilitation guidelines for COVID-19 patients and the effect of Early Mobilization in these patients. Previous reports revealed that dealing with COVID-19 patients was based on expert opinion, evidence from patients with other lung diseases, and not on the recent literature concerning COVID-19. International guidelines have also reported that early mobilization is safe and feasible, starting in the ICU setting. Therefore, this clinical literature review aimed to designate the indications for physical rehabilitation programs and early mobilization benefits to add to the existing literature the necessary up-to-date recommendations and to share the experience of a tertiary healthcare facility in the Kingdom of Saudi Arabia (KSA) in dealing with different stages of post-COVID-19 patients. Conclusion: The multidisciplinary approach of KFSH&amp;RC for rehabilitating COVID-19 patients was integrated through early mobilization and remarkable follow-up of different clinical service divisions, including physical and occupational rehabilitation, respiratory therapy, and nutrition, with the collaboration of the medical and psychological teams aiming to regain optimal physical function, psychological well-being, and better quality of life for those populations.

A brain-wide analysis maps structural evolution to distinct anatomical module.

The vertebrate brain is highly conserved topologically, but less is known about neuroanatomical variation between individual brain regions. Neuroanatomical variation at the regional level is hypothesized to provide functional expansion, building upon ancestral anatomy needed for basic functions. Classically, animal models used to study evolution have lacked tools for detailed anatomical analysis that are widely used in zebrafish and mice, presenting a barrier to studying brain evolution at fine scales. In this study, we sought to investigate the evolution of brain anatomy using a single species of fish consisting of divergent surface and cave morphs, that permits functional genetic testing of regional volume and shape across the entire brain. We generated a high-resolution brain atlas for the blind Mexican cavefish Astyanax mexicanus and coupled the atlas with automated computational tools to directly assess variability in brain region shape and volume across all populations. We measured the volume and shape of every grossly defined neuroanatomical region of the brain and assessed correlations between anatomical regions in surface fish, cavefish, and surface × cave F2 hybrids, whose phenotypes span the range of surface to cave. We find that dorsal regions of the brain are contracted, while ventral regions have expanded, with F2 hybrid data providing support for developmental constraint along the dorsal-ventral axis. Furthermore, these dorsal-ventral relationships in anatomical variation show similar patterns for both volume and shape, suggesting that the anatomical evolution captured by these two parameters could be driven by similar developmental mechanisms. Together, these data demonstrate that A. mexicanus is a powerful system for functionally determining basic principles of brain evolution and will permit testing how genes influence early patterning events to drive brain-wide anatomical evolution.

Early-season and refined mapping of winter wheat based on phenology algorithms -a case of Shandong, China.

Winter wheat is one of the major food crops in China, and timely and effective early-season identification of winter wheat is crucial for crop yield estimation and food security. However, traditional winter wheat mapping is based on post-season identification, which has a lag and relies heavily on sample data. Early-season identification of winter wheat faces the main difficulties of weak remote sensing response of the vegetation signal at the early growth stage, difficulty of acquiring sample data on winter wheat in the current season in real time, interference of crops in the same period, and limited image resolution. In this study, an early-season refined mapping method with winter wheat phenology information as priori knowledge is developed based on the Google Earth Engine cloud platform by using Sentinel-2 time series data as the main data source; these data are automated and highly interpretable. The normalized differential phenology index (NDPI) is adopted to enhance the weak vegetation signal at the early growth stage of winter wheat, and two winter wheat phenology feature enhancement indices based on NDPI, namely, wheat phenology differential index (WPDI) and normalized differential wheat phenology index (NDWPI) are developed. To address the issue of " different objects with the same spectra characteristics" between winter wheat and garlic, a plastic mulched index (PMI) is established through quantitative spectral analysis based on the differences in early planting patterns between winter wheat and garlic. The identification accuracy of the method is 82.64% and 88.76% in the early overwintering and regreening periods, respectively, These results were consistent with official statistics (R2 = 0.96 and 0.98, respectively). Generalization analysis demonstrated the spatiotemporal transferability of the method across different years and regions. In conclusion, the proposed methodology can obtain highly precise spatial distribution and planting area information of winter wheat 4_6 months before harvest. It provides theoretical and methodological guidance for early crop identification and has good scientific research and application value.

Quantitative Analyses for Early Tempo-spatial Patterning of Differentiated Human Induced Pluripotent Stem Cells on Micropatterns using Time-lapse Bright-field Microscopy Images.

Three germ layer formation on micropatterns are extremely useful for quantitative analysis of hiPSC (human induced pluripotent stem cells) pluripotency. Spatial patterns of stem cells differentiated on the micropatterns will be formed from about 24 hours after differentiation induction and usually quantitated near 48 hours. To delineate the germ layer formation process, temporal changes in spatial patterning of germ layers should be analyzed by noninvasive microscopy. This study proposed a series of image processing methods combined with a U-net automatic segmentation to segment differentiated hiPSCs captured by bright-field microscopy. High segmentation accuracy (83.3%) for the test bright-field images compared with their concurrent Hoechst images (85%) was achieved. Tempo-spatial patterning and formation process of germ layers on the micropatterns can be visualized and quantified by segmenting time-lapse bright-field microscopy images using our method.

Self-Similarity and Spatial Periodicity in Cerebral Cortical Patterning: Structural Design Notes for Neural Tissue Architects

Tissue engineering is a powerful tool with which to systematically identify the determinants of biological functions. Applied to the design and fabrication of biomimetic brains, tissue engineering serves to disentangle the complex anatomy of neural circuits and pathways by recapitulating structure-function relationships in simplified model systems. The complex neuroanatomy of the cerebral cortex, with its enigmatic columnar and stratified cytoarchitectonic organization, represents a major challenge toward isolating the minimal set of elements that are required to assemble neural tissues with cognitive functions. Whereas considerable efforts have highlighted important genetic and physical correlates of early cortical tissue patterning, no substantive attempt to identify the determinants of how the cortices acquire their relatively conserved, narrow range of numbered layers is evident in the literature. Similarly, it is not yet clear whether cortical columns and laminae are functionally relevant or epiphenomena of embryonic neurodevelopment. Here, we demonstrate that spatial frequencies (m−1) derived from the width-to-height ratios of cerebral cortical columns predict sinusoids with a narrow range of spatial cycles over the average cortical thickness. The resulting periodicities, denoted by theoretical wavenumbers, reflect the number of observed cortical layers among humans and across several other species as revealed by a comparative anatomy approach. We present a hypothesis that cortical columns and their periodic layers are emergent of the intrinsic spatial dimensions of neurons and their nested, self-similar aggregate structures including minicolumns. Finally, we discuss the implications of periodic tissue patterns in the context of neural tissue engineering.

CFOS as a biomarker of activity maturation in the hippocampal formation.

We explored the potential for cFOS expression as a marker of functional development of "resting-state" waking activity in the extended network of the hippocampus and entorhinal cortex. We examined sleeping and awake mice at (P)ostnatal days 5, 9, 13, and 17 as well as in adulthood. We find that cFOS expression is state-dependent even at 5 days old, with reliable staining occurring only in the awake mice. Even during waking, cFOS expression was rare and weak at P5. The septal nuclei, entorhinal cortex layer (L)2, and anterodorsal thalamus were exceptional in that they had robust cFOS expression at P5 that was similar to or greater than in adulthood. Significant P5 expression was also observed in the dentate gyrus, entorhinal cortex L6, postsubiculum L4-6, ventral subiculum, supramammillary nucleus, and posterior hypothalamic nucleus. The expression in these regions grew stronger with age, and the expression in new regions was added progressively at P9 and P13 by which point the overall expression pattern in many regions was qualitatively similar to the adult. Six regions-CA1, dorsal subiculum, postsubiculum L2-3, reuniens nucleus, and perirhinal and postrhinal cortices-were very late developing, mostly achieving adult levels only after P17. Our findings support a number of developmental principles. First, early spontaneous activity patterns induced by muscle twitches during sleep do not induce robust cFOS expression in the extended hippocampal network. Second, the development of cFOS expression follows the progressive activation along the trisynaptic circuit, rather than birth date or cellular maturation. Third, we reveal components of the egocentric head-direction and theta-rhythm circuits as the earliest cFOS active circuits in the forebrain. Our results suggest that cFOS staining may provide a reliable and sensitive biomarker for hippocampal formation activity development, particularly in regard to the attainment of a normal waking state and synchronizing rhythms such as theta and gamma.

Early Pregnancy Systolic Blood Pressure Patterns Predict Early- and Later-Onset Preeclampsia and Gestational Hypertension Among Ostensibly Low-to-Moderate Risk Groups.

Background Clinical risk factors, a single blood pressure (BP) measurement, current biomarkers, and biophysical parameters can effectively identify risk of early-onset preeclampsia but have limited ability to predict later-onset preeclampsia and gestational hypertension. Clinical BP patterns hold promise to improve early risk stratification for hypertensive disorders of pregnancy. Methods and Results After excluding preexisting hypertension, heart, kidney, or liver disease, or prior preeclampsia, the retrospective cohort (n=249 892) all had systolic BP <140 mm Hg and diastolic BP <90 mm Hg or a single BP elevation ≤20 weeks' gestation, prenatal care at <14 weeks' gestation, and a still or live birth delivery at Kaiser Permanente Northern California hospitals (2009-2019). The sample was randomly split into development (N=174 925; 70%) and validation (n=74 967; 30%) data sets. Predictive performance of multinomial logistic regression models for early-onset (<34 weeks) preeclampsia, later-onset (≥34 weeks) preeclampsia, and gestational hypertension was evaluated in the validation data set. There were 1008 (0.4%), 10 766 (4.3%), and 11 514 (4.6%) patients with early-onset preeclampsia, later-onset preeclampsia, and gestation hypertension, respectively. Models with 6 systolic BP trajectory groups (0-20 weeks' gestation) plus standard clinical risk factors performed substantially better than risk factors alone to predict early- and later-onset preeclampsia and gestational hypertension, with C-statistics (95% CIs) of 0.747 (0.720-0.775), 0.730 (0.722-0.739), and 0.768 (0.761-0.776) versus 0.688 (0.659-0.717), 0.695 (0.686-0.704) and 0.692 (0.683-0.701), respectively, with excellent calibration (Hosmer-Lemeshow P=0.99, 0.99, and 0.74, respectively). Conclusions Early pregnancy BP patterns up to 20 weeks' gestation plus clinical, social, and behavioral factors more accurately discriminate hypertensive disorders of pregnancy risk among low-to-moderate risk pregnancies. Early pregnancy BP trajectories improve risk stratification to reveal higher-risk individuals hidden within ostensibly low-to-moderate risk groups and lower-risk individuals considered at higher risk by US Preventive Services Task Force criteria.

Early Expansion of the User Base for Mobile Applications: Evidence from the US Apple App Store

Mobile applications (apps) have grown drastically since their birth in 2008. Acquiring more app users as quickly as possible after the app is released in the app stores is one of the key rules for app developers to survive in this emerging and competitive digital market. This paper uses cumulative weekly downloading data from the US Apple App Store during a two-year period of 2015 and 2016 to study the early expansion curves and diffusion patterns of mobile apps in the app market. Downloading payment methods (free or paid to download an app) and hedonic or utilitarian value-orientated app types (games and productivity apps) are considered when we study the diffusion pattern of mobile apps. The Bass model is used as the baseline model, and the logistic model and Gompertz model are used to conduct a robustness check. Nonlinear least squares (NLS) is the measurement to obtain parameters of diffusion models. The results show that the Bass model is the best-fitting model compared with the other two models, and the diffusion pattern of mobile apps is S-shaped at the market level. The first 35 weeks are essential for the app developers to attract app users’ downloads. More app data from different app stores and more diffusion models can be tested for mobile app diffusion and early expansion patterns in future research.

How enhancers regulate wavelike gene expression patterns.

A key problem in development is to understand how genes turn on or off at the right place and right time during embryogenesis. Such decisions are made by non-coding sequences called 'enhancers.' Much of our models of how enhancers work rely on the assumption that genes are activated de novo as stable domains across embryonic tissues. Such a view has been strengthened by the intensive landmark studies of the early patterning of the anterior-posterior (AP) axis of the Drosophila embryo, where indeed gene expression domains seem to arise more or less stably. However, careful analysis of gene expression patterns in other model systems (including the AP patterning in vertebrates and short-germ insects like the beetle Tribolium castaneum) painted a different, very dynamic view of gene regulation, where genes are oftentimes expressed in a wavelike fashion. How such gene expression waves are mediated at the enhancer level is so far unclear. Here, we establish the AP patterning of the short-germ beetle Tribolium as a model system to study dynamic and temporal pattern formation at the enhancer level. To that end, we established an enhancer prediction system in Tribolium based on time- and tissue-specific ATAC-seq and an enhancer live reporter system based on MS2 tagging. Using this experimental framework, we discovered several Tribolium enhancers, and assessed the spatiotemporal activities of some of them in live embryos. We found our data consistent with a model in which the timing of gene expression during embryonic pattern formation is mediated by a balancing act between enhancers that induce rapid changes in gene expression patterns (that we call 'dynamic enhancers') and enhancers that stabilize gene expression patterns (that we call 'static enhancers'). However, more data is needed for a strong support for this or any other alternative models.

Physical Activity Pattern of Adults With Metabolic Syndrome Risk Factors: Time-Series Cluster Analysis.

Physical activity plays a crucial role in maintaining a healthy lifestyle, and wrist-worn wearables, such as smartwatches and smart bands, have become popular tools for measuring activity levels in daily life. However, studies on physical activity using wearable devices have limitations; for example, these studies often rely on a single device model or use improper clustering methods to analyze the wearable data that are extracted from wearable devices. This study aimed to identify methods suitable for analyzing wearable data and determining daily physical activity patterns. This study also explored the association between these physical activity patterns and health risk factors. People aged >30 years who had metabolic syndrome risk factors and were using their own wrist-worn devices were included in this study. We collected personal health data through a web-based survey and measured physical activity levels using wrist-worn wearables over the course of 1 week. The Time-Series Anytime Density Peak (TADPole) clustering method, which is a novel time-series method proposed recently, was used to identify the physical activity patterns of study participants. Additionally, we defined physical activity pattern groups based on the similarity of physical activity patterns between weekdays and weekends. We used the χ2 or Fisher exact test for categorical variables and the 2-tailed t test for numerical variables to find significant differences between physical activity pattern groups. Logistic regression models were used to analyze the relationship between activity patterns and health risk factors. A total of 47 participants were included in the analysis, generating a total of 329 person-days of data. We identified 2 different types of physical activity patterns (early bird pattern and night owl pattern) for weekdays and weekends. The physical activity levels of early birds were less than that of night owls on both weekdays and weekends. Additionally, participants were categorized into stable and shifting groups based on the similarity of physical activity patterns between weekdays and weekends. The physical activity pattern groups showed significant differences depending on age (P=.004) and daily energy expenditure (P<.001 for weekdays; P=.003 for weekends). Logistic regression analysis revealed a significant association between older age (≥40 y) and shifting physical activity patterns (odds ratio 8.68, 95% CI 1.95-48.85; P=.007). This study overcomes the limitations of previous studies by using various models of wrist-worn wearables and a novel time-series clustering method. Our findings suggested that age significantly influenced physical activity patterns. It also suggests a potential role of the TADPole clustering method in the analysis of large and multidimensional data, such as wearable data.

Serum kynurenic acid is lower in systemic sclerosis patients with microvascular damage of hands.

Endothelial dysfunction occurs early in systemic sclerosis (SSc), leading to tissue hypoxia, vasoconstriction and fibrosis. It has been demonstrated that endothelial cells (ECs) are able to produce kynurenic acid (KYNA) in response to vascular inflammation, due to its anti-inflammatory and anti-oxidants activity. In SSc patients, blood perfusion of hands, assessed by laser speckle contrast analysis (LASCA), correlated negatively with the extent of the nailfold microvascular damage, scored according to nailfold videocapillaroscopy (NVC) classification. Aim of this study was to evaluate the difference of serum KYNA in SSc patients with different stages of microvascular damage. Serum KYNA was assessed in 40 SSc patients at the enrolment. NVC was performed to evaluate capillaroscopic patterns (early, active and late). LASCA was performed to evaluate mean peripheral blood perfusion (PBP) of both hands and to evaluate the proximal-distal gradient (PDG). Median PDG was significantly lower in SSc patients with late NVC pattern compared to SSc patients with early and active NVC pattern [3.79pU (IQR -8.55-18.16) vs 23.55pU (IQR 14.92-43.80), p<0.01]. Serum KYNA was significantly lower in SSc patients with late NVC pattern compared to SSc patient with early and active NVC pattern [45.19ng/mL (IQR 42.70-54.74) vs 52.65ng/mL (IQR 49.99-60.29), p<0.05]. Moreover, SSc patients without PDG had significantly lower serum KYNA than in SSc patients with PDG [48.03ng/mL (IQR 43.87-53.68) vs 59.27ng/mL (IQR 49.15-71.00), p<0.05]. KYNA is lower in SSc patients with late NCV pattern and without PDG. KYNA may be associated with early endothelial dysfunction.

A Clinical Review of Physical Rehabilitation Protocol and Early Mobilization Patterns for Post-Covid-19 Patients: Tertiary Health-Care Facility Experience

Several studies have emphasized the urgent need for Physical Rehabilitation guidelines for COVID-19 patients and the effect of Early Mobilization (EM) in these patients. previous reports revealed that dealing with COVID-19 patients was based on expert opinion, evidence from patients with other lung diseases, and not on the recent literature concerning COVID-19. International guidelines also reported that early mobilization is safe and feasible, starting in the ICU setting. Therefore, this clinical literature review aimed to designate the indications of physical rehabilitation programs and early mobilization benefits to add to the existing literature the necessary up-to-date recommendations and share the experience of a tertiary healthcare facility in dealing with different stages of post-COVID-19 patients. Conclusion: The multidisciplinary approach of KFSH&amp;RC for rehabilitating COVID-19 patients was integrated through early mobilization and remarkable follow-up of different clinical services divisions including physical and occupational rehabilitation, respiratory therapy, and nutrition, with the collaboration of the medical and psychological teams aiming to regain optimal physical function, psychological well-being, and better quality of life for those populations.

Pola Pembinaan Usia Dini pada Klub-Klub Bola Basket di Kabupaten Temanggung

The purpose of this study was to determine the Achievement Development and Early Childhood Development Patterns in Basketball Clubs in Temanggung Regency in 2020. This study used a descriptive quantitative research approach. The results of the study show that according to the indicators of infrastructure for achievement development are in the poor category, organizational indicators for achievement development are in the medium category, environmental indicators for achievement development are in the medium category, management indicators for achievement development are in the medium category and funding indicators for coaching achievement is in the medium category. The results showed that according to the physical indicators the majority of respondents were in the good category, and the mental aspect indicators of the majority of the respondents were in the good category. Based on the results of the study, it can be concluded that the development of achievement in basketball clubs in Temanggung Regency in 2020 consists of facilities and infrastructure that are in the less category, organizations that are in the medium category, the environment which is in the medium category, management which is in the middle category. moderate, and funding is in the medium category and the physical aspect is in the good category, the mental aspect is in the good category and the social aspect is in the good category

An AI-Based Early Fire Detection System Utilizing HD Cameras and Real-Time Image Analysis

Wildfires pose a significant threat to human lives, property, and the environment. Rapid response during a fire's early stages is critical to minimizing damage and danger. Traditional wildfire detection methods often rely on reports from bystanders, leading to delays in response times and the possibility of fires growing out of control. In this paper, ask the question: “Can AI object detection improve wildfire detection and response times?”. We present an innovative early fire detection system that leverages state-of-the-art hardware, artificial intelligence (AI)-powered object detection, and seamless integration with emergency services to significantly improve wildfire detection and response times. Our system employs high-definition panoramic cameras, solar-powered energy sources, and a sophisticated communication infrastructure to monitor vast landscapes in real-time. The AI model at the core of the system analyzes images captured by the cameras every 60 seconds, identifying early smoke patterns indicative of fires, and promptly notifying the fire department. We detail the system architecture, AI model framework, training process, and results obtained during testing and validation. The system demonstrates its effectiveness in detecting and reporting fires, reducing response times, and improving emergency services coordination. We have demonstrated that AI object detection can be an invaluable tool in the ongoing battle against wildfires, ultimately saving lives, property, and the environment.