Abstract
TRP channel-associated factor 1/2 (TCAF1/TCAF2) proteins antagonistically regulate the cold-sensor protein TRPM8 in multiple human tissues. Understanding their significance has been ...complicated given the locus spans a gap-ridden region with complex segmental duplications in GRCh38. Using long-read sequencing, we sequence-resolve the locus, annotate full-length
TCAF
models in primate genomes, and show substantial human-specific
TCAF
copy number variation. We identify two human super haplogroups, H4 and H5, and establish that
TCAF
duplications originated ~1.7 million years ago but diversified only in
Homo sapiens
by recurrent structural mutations. Conversely, in all archaic-hominin samples the fixation for a specific H4 haplotype without duplication is likely due to positive selection. Here, our results of
TCAF
copy number expansion, selection signals in hominins, and differential
TCAF2
expression between haplogroups and high
TCAF2
and
TRPM8
expression in liver and prostate in modern-day humans imply
TCAF
diversification among hominins potentially in response to cold or dietary adaptations.
Copy number variants (CNVs) are subject to stronger selective pressure than single-nucleotide variants, but their roles in archaic introgression and adaptation have not been systematically ...investigated. We show that stratified CNVs are significantly associated with signatures of positive selection in Melanesians and provide evidence for adaptive introgression of large CNVs at chromosomes 16p11.2 and 8p21.3 from Denisovans and Neanderthals, respectively. Using long-read sequence data, we reconstruct the structure and complex evolutionary history of these polymorphisms and show that both encode positively selected genes absent from most human populations. Our results collectively suggest that large CNVs originating in archaic hominins and introgressed into modern humans have played an important role in local population adaptation and represent an insufficiently studied source of large-scale genetic variation.
The development of the industry has increased the demand for energy storage, making the provision of energy storage devices essential. The supercapacitor is one of the potential energy storage ...devices, and carbon aerogel (CA) is a promising candidate for supercapacitor electrode fabrication. Ni-doped nipa palm shell-derived CA (Ni-NS-CA) was used to fabricate the electrode for supercapacitors to save production costs and utilize biomass wastes. Ni-NS-CA was synthesized via a three-step process: Hydrogel making through cross-linking (SA, Ni
2+
), freeze-drying, and pyrolysis. The characteristics of Ni-NS-CA are analyzed using a scanning electron microscope, field-emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray diffraction, Raman spectroscopy, and Nitrogen adsorption–desorption isotherm 77 K. The electrochemical properties of Ni-NS-CA was analyzed via cyclic voltammetry, galvanostatic charge–discharge, and electrochemical impedance spectroscopy. With stable energy storage results (104.15 F g
−1
) and the electrochemical system based on Ni-NS-CA extends its application to Hg
2+
sensing. Moreover, Ni-NS-CA was a potential material to solve oil spills, which has an oil adsorption capacity of 31.24 g g
−1
.
Graphical abstract
Data fusion is a multidisciplinary research area that involves different domains. It is used to attain minimum detection error probability and maximum reliability with the help of data retrieved from ...multiple healthcare sources. The generation of huge quantity of data from medical devices resulted in the formation of big data during which data fusion techniques become essential. Securing medical data is a crucial issue of exponentially-pacing computing world and can be achieved by Intrusion Detection Systems (IDS). In this regard, since singular-modality is not adequate to attain high detection rate, there is a need exists to merge diverse techniques using decision-based multimodal fusion process. In this view, this research article presents a new multimodal fusion-based IDS to secure the healthcare data using Spark. The proposed model involves decision-based fusion model which has different processes such as initialization, pre-processing, Feature Selection (FS) and multimodal classification for effective detection of intrusions. In FS process, a chaotic Butterfly Optimization (BO) algorithm called CBOA is introduced. Though the classic BO algorithm offers effective exploration, it fails in achieving faster convergence. In order to overcome this, i.e., to improve the convergence rate, this research work modifies the required parameters of BO algorithm using chaos theory. Finally, to detect intrusions, multimodal classifier is applied by incorporating three Deep Learning (DL)-based classification models. Besides, the concepts like Hadoop MapReduce and Spark were also utilized in this study to achieve faster computation of big data in parallel computation platform. To validate the outcome of the presented model, a series of experimentations was performed using the benchmark NSLKDDCup99 Dataset repository. The proposed model demonstrated its effective results on the applied dataset by offering the maximum accuracy of 99.21%, precision of 98.93% and detection rate of 99.59%. The results assured the betterment of the proposed model.
At menopause, the dramatic loss of ovarian estradiol (E2) necessitates the adaptation of estrogen-sensitive neurons in the hypothalamus to an estrogen-depleted environment. We developed a rat model ...to test the “critical window” hypothesis of the effects of timing and duration of E2 treatment after deprivation on the hypothalamic neuronal gene network in the arcuate nucleus and the medial preoptic area. Rats at 2 ages (reproductively mature or aging) were ovariectomized and given E2 or vehicle replacement regimes of differing timing and duration. Using a 48-gene quantitative low-density PCR array and weighted gene coexpression network analysis, we identified gene modules differentially regulated by age, timing, and duration of E2 treatment. Of particular interest, E2 status differentially affected suites of genes in the hypothalamus involved in energy balance, circadian rhythms, and reproduction. In fact, E2 status was the dominant factor in determining gene modules and hormone levels; age, timing, and duration had more subtle effects. Our results highlight the plasticity of hypothalamic neuroendocrine systems during reproductive aging and its surprising ability to adapt to diverse E2 replacement regimes.
Diabetic Retinopathy (DR) is a significant blinding disease that poses serious threat to human vision rapidly. Classification and severity grading of DR are difficult processes to accomplish. ...Traditionally, it depends on ophthalmoscopically-visible symptoms of growing severity, which is then ranked in a stepwise scale from no retinopathy to various levels of DR severity. This paper presents an ensemble of Orthogonal Learning Particle Swarm Optimization (OPSO) algorithm-based Convolutional Neural Network (CNN) Model EOPSO-CNN in order to perform DR detection and grading. The proposed EOPSO-CNN model involves three main processes such as preprocessing, feature extraction, and classification. The proposed model initially involves preprocessing stage which removes the presence of noise in the input image. Then, the watershed algorithm is applied to segment the preprocessed images. Followed by, feature extraction takes place by leveraging EOPSO-CNN model. Finally, the extracted feature vectors are provided to a Decision Tree (DT) classifier to classify the DR images. The study experiments were carried out using Messidor DR Dataset and the results showed an extraordinary performance by the proposed method over compared methods in a considerable way. The simulation outcome offered the maximum classification with accuracy, sensitivity, and specificity values being 98.47%, 96.43%, and 99.02% respectively.
Display omitted
•Controlled study with data from 17 subjects administered a single dose of tramadol.•Tramadol present in hair to at least 4 months after single ingestion.•Narrow segmental analysis of ...hair enabled a good estimate of time of drug ingestion.•Tramadol metabolite findings may depend on subject CYP2D6 phenotype.•Significant wash out and sweat effects were observed.
This controlled study aimed to measure concentrations of tramadol (TRA) and its two main metabolites, N-desmethyltramadol (NDMT) and O-desmethyltramadol (ODMT), in hair following a single dose ingestion and to investigate the distribution patterns in hair by segmental analysis of hair samples taken at several sampling time points after ingestion. An oral dose (50 or 100mg) of TRA was administered to 17 healthy volunteers. Hair samples were collected prior to drug administration and 14, 30, 60 and 120 days after ingestion. Each sample was segmented in 5mm segments and washed. The analytes were extracted from pulverized hair by incubation in extraction media for 18h at 37°C. A validated UHPLC–MS/MS method was used to quantify the analytes at a LLOQ of 0.001ng/mg. Hair segments corresponding to the time of ingestion were positive for TRA and the metabolites of each sampling time point, although neighboring segments also showed positive results. The highest concentrations for both dosage groups were observed in the proximal segment of hair collected 14 days after ingestion for all subjects: 0.061–0.95ng TRA/mg, 0.012–0.86ng NDMT/mg and 0.009–0.17ng ODMT/mg (n=16). Generally, the TRA concentration was higher than the metabolites concentrations but depended on the CYP2D6 phenotype. The metabolite to TRA ratios were stable within a subject over the sampling time points, however it varied greatly between subjects. No significant differences in hair concentrations were found between the two dosage groups at each sampling time. Several confounding factors were identified such as hair pigmentation and internal sweat. We showed that analysis of 5mm segments improved the determination of the exposure time after a single ingestion of TRA. In addition, in the later sampling time points the analytes were spread more between segments and the total drug amount of each later sampling time point declined up to a 100% (median: 75%) due to wash out. The presented results are important additions to the sparse literature reporting single dose of psychoactive drugs in hair.
Structural variation and single-nucleotide variation of the complement factor H (CFH) gene family underlie several complex genetic diseases, including age-related macular degeneration (AMD) and ...atypical hemolytic uremic syndrome (AHUS). To understand its diversity and evolution, we performed high-quality sequencing of this ∼360-kbp locus in six primate lineages, including multiple human haplotypes. Comparative sequence analyses reveal two distinct periods of gene duplication leading to the emergence of four CFH-related (CFHR) gene paralogs (CFHR2 and CFHR4 ∼25–35 Mya and CFHR1 and CFHR3 ∼7–13 Mya). Remarkably, all evolutionary breakpoints share a common ∼4.8-kbp segment corresponding to an ancestral CFHR gene promoter that has expanded independently throughout primate evolution. This segment is recurrently reused and juxtaposed with a donor duplication containing exons 8 and 9 from ancestral CFH, creating four CFHR fusion genes that include lineage-specific members of the gene family. Combined analysis of >5,000 AMD cases and controls identifies a significant burden of a rare missense mutation that clusters at the N terminus of CFH P = 5.81 × 10−8, odds ratio (OR) = 9.8 (3.67-Infinity). A bipolar clustering pattern of rare nonsynonymous mutations in patients with AMD (P < 10−3) and AHUS (P = 0.0079) maps to functional domains that show evidence of positive selection during primate evolution. Our structural variation analysis in >2,400 individuals reveals five recurrent rearrangement breakpoints that show variable frequency among AMD cases and controls. These data suggest a dynamic and recurrent pattern of mutation critical to the emergence of new CFHR genes but also in the predisposition to complex human genetic disease phenotypes.
Ruptured abdominal aortic aneurysm (RAAA) is an acute aortic condition that requires emergent intervention and appropriate continuity of care to optimize patient outcomes. We describe the ...standardized RAAA protocol at the Houston Methodist Hospital Acute Aortic Treatment Center, developed to navigate critical patient transfer periods safely and efficiently, make crucial decisions about surgical intervention, and clearly communicate these plans with other care team providers. Our workflow is organized into five phases: prehospital, preoperative, intraoperative, postoperative, and post-discharge. We identify the transfer center, anesthesia, operating room nursing staff, surgeons, and intensive care unit as key entities of our acute aortic pathology care team. This systematic protocol for the management of acute aortic emergencies such as RAAA identifies critical decision points, potential complications at each stage, and recommendations for best practice.
E-learning in the context of Industry 4.0 and the outbreak of the COVID-19 pandemic has transformed traditional education. However, the smooth transition from face-to-face education to e-learning ...remains a challenging task, given concerns about e-learning quality. This study aims to explore the quality criteria and the adoption of e-learning via the spherical fuzzy analytic hierarchy process (SF-AHP). The extended technical acceptance model is used as a theoretical framework for constructing quality in an adoption hierarchical model. The input data derived from in-depth interviews of 20 experts in the field and the SF-AHP calculator have generated the priority weights of quality criteria in the model of e-learning adoption. The findings confirm the role of three major criteria, in order of importance, as follows: system, resources and core factors. The results highlight system factors as most crucial, including aspects such as governmental policies and institutional leadership, which are essential for setting a conducive environment for e-learning. Resource factors are ranked second, emphasizing the importance of IT applications, human capital and facilities to support e-learning infrastructure. Core factors, though ranked lower, are vital in ensuring the effectiveness of e-learning through course materials, instruction, and learner support. The weights of 14 sub-criteria have further shed light on policies to promote e-learning quality and its adoption. The implied priority of each weight a valuable guideline for the stakeholders’ actions to reach the targeted goals under the constraint resources.
PDF
