Adaptive Time Synchronization for Homogeneous WSNs

Wireless sensor networks (WSNs) are being used for observing real‐world phenomenon. It is important that sensor nodes (SNs) must be synchronized to a common time in order to precisely map the data collected by SNs. Clock synchronization is very challenging in WSNs as the sensor networks are resource constrained networks. It is essential that clock synchronization protocols designed for WSNs must be light weight i.e. SNs must be synchronized with fewer synchronization message exchanges. In this paper, we propose a clock synchronization protocol for WSNs where first of all cluster heads (CHs) are synchronized with the sink and then the cluster nodes (CNs) are synchronized with their respective CHs. CNs are synchronized with the help of time synchronization node (TSN) chosen by the respective CHs. Simulation results show that proposed protocol requires considerably fewer synchronization messages as compared with the reference broadcast synchronization (RBS) protocol and minimum variance unbiased estimation (MUVE) method. Clock skew correction mechanism applied in proposed protocol guarantees long term stability and hence decreases re‐ synchronization frequency thereby conserving more energ

A Virtual Grid Based Energy Efficient Data Gathering Scheme for Heterogeneous Sensor Networks

Traditional Wireless Sensor Networks (WSNs) generally use static sinks to collect data from the sensor nodes via multiple forwarding. Therefore, network suffers with some problems like long message relay time, bottle neck problem which reduces the performance of the network. Many approaches have been proposed to prevent this problem with the help of mobile sink to collect the data from the sensor nodes, but these approaches still suffer from the buffer overflow problem due to limited memory size of sensor nodes. This paper proposes an energy efficient scheme for data gathering which overcomes the buffer overflow problem. The proposed scheme creates virtual grid structure of heterogeneous nodes. Scheme has been designed for sensor nodes having variable sensing rate. Every node finds out its buffer overflow time and on the basis of this cluster heads are elected. A controlled traversing approach is used by the proposed scheme in order to transmit data to sink. The effectiveness of the proposed scheme is verified by simulation

Wood polymer composite bonded veneer based hybrid composites

Wood veneer based composites have a great demand in present market as the material can  utilize small diameter plantation timbers grown at short rotation cycle. This paper presents preparation and characterization of hybrid composites made of wood veneer and wood polymer composite. The study explored utilization of wood polymer composite as an adhesive for bonding veneers replacing formaldehyde-based adhesives. Wood polymer composite containing 40 % bamboo particles embedded in the matrix of polypropylene was used in sheet form to bind the veneers of Melia dubia wood. The composites were prepared in both laminated veneer lumber and plywood configurations. The assessment of physical and mechanical properties indicated that the properties of wood polymer composite contribute significantly to the properties of the hybrid composites. The density of the resultant composites was significantly higher (0,69 g/cm3 – 0,75 g/cm3) than conventional plywood or laminated veneer lumber. Among mechanical properties, there was no statistical difference in tensile and flexural strength of plywood and laminated veneer lumber configuration. Modulus of elasticity and compressive strength of laminated veneer lumber configuration were significantly higher than plywood. Glue shear strength and internal bond strength of the composites indicated acceptable bonding properties of wood polymer composite which suggests the potential application of these composites as a binding agent for wood veneers. These composites could be a special class of laminated composites with no formaldehyde emission hazards

Analysis of gut bacteriome of in utero arsenic-exposed mice using 16S rRNA-based metagenomic approach

IntroductionApproximately 200 million people worldwide are affected by arsenic toxicity emanating from the consumption of drinking water containing inorganic arsenic above the prescribed maximum contaminant level. The current investigation deals with the role of prenatal arsenic exposure in modulating the gut microbial community and functional pathways of the host.Method16S rRNA-based next-generation sequencing was carried out to understand the effects of in utero 0.04 mg/kg (LD) and 0.4 mg/kg (HD) of arsenic exposure. This was carried out from gestational day 15 (GD-15) until the birth of pups to understand the alterations in bacterial diversity.ResultsThe study focused on gestational exposure to arsenic and the altered gut microbial community at phyla and genus levels, along with diversity indices. A significant decrease in firmicutes was observed in the gut microbiome of mice treated with arsenic. Functional analysis revealed that a shift in genes involved in crucial pathways such as insulin signaling and non-alcoholic fatty liver disease pathways may lead to metabolic diseases in the host.DiscussionThe present investigation may hypothesize that in utero arsenic exposure can perturb the gut bacterial composition significantly as well as the functional pathways of the gestationally treated pups. This research paves the way to further investigate the probable mechanistic insights in the field of maternal exposure environments, which may play a key role in epigenetic modulations in developing various disease endpoints in the progeny

Overexpression of Prothymosin Alpha Predicts Poor Disease Outcome in Head and Neck Cancer

In our recent study, tissue proteomic analysis of oral pre-malignant lesions (OPLs) and normal oral mucosa led to the identification of a panel of biomarkers, including prothymosin alpha (PTMA), to distinguish OPLs from histologically normal oral tissues. This study aimed to determine the clinical significance of PTMA overexpression in oral squamous cell hyperplasia, dysplasia and head and neck squamous cell carcinoma (HNSCC).Immunohistochemistry of PTMA protein was performed in HNSCCs (n = 100), squamous cell hyperplasia (n = 116), dysplasia (n = 50) and histologically normal oral tissues (n = 100). Statistical analysis was carried out to determine the association of PTMA overexpression with clinicopathological parameters and disease prognosis over 7 years for HNSCC patients.<0.001). Chi-square analysis showed significant association of nuclear PTMA with advanced tumor stages (III+IV). Kaplan Meier survival analysis indicated reduced disease free survival (DFS) in HNSCC patients (p<0.001; median survival 11 months). Notably, Cox-multivariate analysis revealed nuclear PTMA as an independent predictor of poor prognosis of HNSCC patients (p<0.001, Hazard's ratio, HR = 5.2, 95% CI = 2.3–11.8) in comparison with the histological grade, T-stage, nodal status and tumor stage.Nuclear PTMA may serve as prognostic marker in HNSCC to determine the subset of patients that are likely to show recurrence of the disease

Nuclear S100A7 Is Associated with Poor Prognosis in Head and Neck Cancer

Tissue proteomic analysis of head and neck squamous cell carcinoma (HNSCC) and normal oral mucosa using iTRAQ (isobaric tag for relative and absolute quantitation) labeling and liquid chromatography-mass spectrometry, led to the identification of a panel of biomarkers including S100A7. In the multi-step process of head and neck tumorigenesis, the presence of dysplastic areas in the epithelium is proposed to be associated with a likely progression to cancer; however there are no established biomarkers to predict their potential of malignant transformation. This study aimed to determine the clinical significance of S100A7 overexpression in HNSCC.Immunohistochemical analysis of S100A7 expression in HNSCC (100 cases), oral lesions (166 cases) and 100 histologically normal tissues was carried out and correlated with clinicopathological parameters and disease prognosis over 7 years for HNSCC patients. Overexpression of S100A7 protein was significant in oral lesions (squamous cell hyperplasia/dysplasia) and sustained in HNSCC in comparison with oral normal mucosa (p(trend)<0.001). Significant increase in nuclear S100A7 was observed in HNSCC as compared to dysplastic lesions (p = 0.005) and associated with well differentiated squamous cell carcinoma (p = 0.031). Notably, nuclear accumulation of S100A7 also emerged as an independent predictor of reduced disease free survival (p = 0.006, Hazard ratio (HR = 7.6), 95% CI = 1.3-5.1) in multivariate analysis underscoring its relevance as a poor prognosticator of HNSCC patients.Our study demonstrated nuclear accumulation of S100A7 may serve as predictor of poor prognosis in HNSCC patients. Further, increased nuclear accumulation of S100A7 in HNSCC as compared to dysplastic lesions warrants a large-scale longitudinal study of patients with dysplasia to evaluate its potential as a determinant of increased risk of transformation of oral premalignant lesions

Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021

This online publication has been corrected. The corrected version first appeared at thelancet.com on September 28, 2023BACKGROUND : Diabetes is one of the leading causes of death and disability worldwide, and affects people regardless of country, age group, or sex. Using the most recent evidentiary and analytical framework from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD), we produced location-specific, age-specific, and sex-specific estimates of diabetes prevalence and burden from 1990 to 2021, the proportion of type 1 and type 2 diabetes in 2021, the proportion of the type 2 diabetes burden attributable to selected risk factors, and projections of diabetes prevalence through 2050. METHODS : Estimates of diabetes prevalence and burden were computed in 204 countries and territories, across 25 age groups, for males and females separately and combined; these estimates comprised lost years of healthy life, measured in disability-adjusted life-years (DALYs; defined as the sum of years of life lost [YLLs] and years lived with disability [YLDs]). We used the Cause of Death Ensemble model (CODEm) approach to estimate deaths due to diabetes, incorporating 25 666 location-years of data from vital registration and verbal autopsy reports in separate total (including both type 1 and type 2 diabetes) and type-specific models. Other forms of diabetes, including gestational and monogenic diabetes, were not explicitly modelled. Total and type 1 diabetes prevalence was estimated by use of a Bayesian meta-regression modelling tool, DisMod-MR 2.1, to analyse 1527 location-years of data from the scientific literature, survey microdata, and insurance claims; type 2 diabetes estimates were computed by subtracting type 1 diabetes from total estimates. Mortality and prevalence estimates, along with standard life expectancy and disability weights, were used to calculate YLLs, YLDs, and DALYs. When appropriate, we extrapolated estimates to a hypothetical population with a standardised age structure to allow comparison in populations with different age structures. We used the comparative risk assessment framework to estimate the risk-attributable type 2 diabetes burden for 16 risk factors falling under risk categories including environmental and occupational factors, tobacco use, high alcohol use, high body-mass index (BMI), dietary factors, and low physical activity. Using a regression framework, we forecast type 1 and type 2 diabetes prevalence through 2050 with Socio-demographic Index (SDI) and high BMI as predictors, respectively. FINDINGS : In 2021, there were 529 million (95% uncertainty interval [UI] 500–564) people living with diabetes worldwide, and the global age-standardised total diabetes prevalence was 6·1% (5·8–6·5). At the super-region level, the highest age-standardised rates were observed in north Africa and the Middle East (9·3% [8·7–9·9]) and, at the regional level, in Oceania (12·3% [11·5–13·0]). Nationally, Qatar had the world’s highest age-specific prevalence of diabetes, at 76·1% (73·1–79·5) in individuals aged 75–79 years. Total diabetes prevalence—especially among older adults—primarily reflects type 2 diabetes, which in 2021 accounted for 96·0% (95·1–96·8) of diabetes cases and 95·4% (94·9–95·9) of diabetes DALYs worldwide. In 2021, 52·2% (25·5–71·8) of global type 2 diabetes DALYs were attributable to high BMI. The contribution of high BMI to type 2 diabetes DALYs rose by 24·3% (18·5–30·4) worldwide between 1990 and 2021. By 2050, more than 1·31 billion (1·22–1·39) people are projected to have diabetes, with expected age-standardised total diabetes prevalence rates greater than 10% in two super-regions: 16·8% (16·1–17·6) in north Africa and the Middle East and 11·3% (10·8–11·9) in Latin America and Caribbean. By 2050, 89 (43·6%) of 204 countries and territories will have an age-standardised rate greater than 10%. INTERPRETATION : Diabetes remains a substantial public health issue. Type 2 diabetes, which makes up the bulk of diabetes cases, is largely preventable and, in some cases, potentially reversible if identified and managed early in the disease course. However, all evidence indicates that diabetes prevalence is increasing worldwide, primarily due to a rise in obesity caused by multiple factors. Preventing and controlling type 2 diabetes remains an ongoing challenge. It is essential to better understand disparities in risk factor profiles and diabetes burden across populations, to inform strategies to successfully control diabetes risk factors within the context of multiple and complex drivers.Bill & Melinda Gates Foundation.http://www.thelancet.comam2024School of Health Systems and Public Health (SHSPH)SDG-03:Good heatlh and well-bein