Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of Toll-like receptors 3, 7, 9 and cytokines in feline infectious peritonitis virus-infected CRFK cells and feline peripheral monocytes

Background The role of Toll-like receptors (TLRs) in a feline infectious peritonitis virus (FIPV) infection is not completely understood. Objectives This study examined the expression of TLR3, TLR7, TLR9, tumor necrosis factor-alpha (TNF-α), interferon (IFN)-β, and interleukin (IL)-10 upon an FIPV infection in Crandell-Reese feline kidney (CRFK) cells and feline monocytes. Methods CRFK cells and monocytes from feline coronavirus (FCoV)-seronegative cats and FCoV-seropositive cats were infected with type II FIPV-79-1146. At four, 12, and 24 hours post-infection (hpi), the expression of TLR3, TLR7, TLR9, TNF-α, IFN-β, and IL-10, and the viral load were measured using reverse transcription quantitative polymerase chain reaction. Viral protein production was confirmed using immunofluorescence. Results FIPV-infected CRFK showed the upregulation of TLR9, TNF-α, and IFN-β expression between 4 and 24 hpi. Uninfected monocytes from FCoV-seropositive cats showed lower TLR3 and TLR9 expression but higher TLR7 expression compared to uninfected monocytes from FCoV-seronegative cats. FIPV-infected monocytes from FCoV-seropositive cats downregulated TLR7 and TNF-α expression between 4 and 24 hpi, and 4 and 12 hpi, respectively. IFN-β was upregulated early in FIPV-infected monocytes from FCoV-seropositive cats, with a significant difference observed at 12 hpi compared to FCoV-seronegative cats. The viral load in the CRFK and FIPV-infected monocytes in both cohorts of cats was similar over time. Conclusion TLR7 may be the key TLR involved in evading the innate response against inhibiting TNF-α production. Distinct TLR expression profiles between FCoV-seronegative and FCoV-seropositive cats were observed. The associated TLR that plays a role in the induction of IFN-β needs to be explored further.
The Carbon Sink Potential of Southern China After Two Decades of Afforestation

Afforestation and land use changes that sequester carbon from the atmosphere in the form of woody biomass have turned southern China into one of the largest carbon sinks globally, which contributes to mitigating climate change. However, forest growth saturation and available land that can be forested limit the longevity of this carbon sink, and while a plethora of studies have quantified vegetation changes over the last decades, the remaining carbon sink potential of this area is currently unknown. Here, we train a model with multiple predictors characterizing the heterogeneous landscapes of southern China and predict the biomass carbon carrying capacity of the region for 2002–2017. We compare observed and predicted biomass carbon density and find that during about two decades of afforestation, 2.34 PgC have been sequestered between 2002 and 2017, and a total of 5.32 Pg carbon can potentially still be sequestrated. This means that the region has reached 73% of its aboveground biomass carbon carrying capacity in 2017, which is 12% more than in 2002, equal to a decrease of 0.77% per year. We identify potential afforestation areas that can still sequester 2.39 PgC, while old and new forests have reached 87% of their potential with 1.85 PgC remaining. Our work locates areas where vegetation has not yet reached its full potential but also shows that afforestation is not a long‐term solution for climate change mitigation.
Task Scheduling With UAV-Assisted Dispersed Computing for Disaster Scenario

Unmanned aerial vehicles (UAVs) are beginning to make a splash in emergency disaster scenarios owing to its excellent air mobility and flexibility. Considering that large base stations often cannot be deployed to disaster areas in the first place and the variation of communication links between UAVs, we formulate the task scheduling problem for disaster scenarios as a two-stage Lyapunov optimization problem and propose a dispersed computing network consisting of UAVs and ground mobile devices, which is used for collaborative computing. We decouple the long-term stability of the task queues of the nodes in the system in terms of time slots as a deterministic optimization problem by Lyapunov techniques. By jointly optimizing the task size transmitted from the control center to the UAVs, the task size computed locally and offloaded by the UAVs and mobile devices, the energy consumption of the dispersed computation system is minimized while ensuring the stability of the computation queues. The simulation results verify that our proposed algorithm is close to the optimal case in terms of queue stability, and our algorithm is able to reduce the system energy consumption by more than 50% compared to the local computation of UAVs.
Fiber Bragg Grating Sensor System with Interferometric Demodulation Technique

A Fiber Bragg Grating sensor system is introduced with interferometric demodulation technique.The system translates the FBG wavelength signal related the strain into phase signal and measures the change of the phase with a phase measurement system based on the micro-controller 89C51.With the characteristic of high resolution、wide measurement range,this sensor system has the capability of measuring static strain as well as dynamic strain.The sensing sensitivity of the system is 0.395 0°/μe.
The Regulation of ManLAM-Related Gene Expression in Mycobacterium tuberculosis with Different Drug Resistance Profiles Following Isoniazid Treatment

Introduction Tuberculosis (TB) caused by Mycobacterium tuberculosis (MTB) remains a global health concern because of the development of drug resistance. The adaptability of MTB in response to a variety of environmental stresses is a crucial strategy that supports their survival and evades host defense mechanisms. Stress regulates gene expression, particularly virulence genes, leading to the development of drug tolerance. Mannose-capped lipoarabinomannan (ManLAM) is a critical component of the cell wall, functions as a virulence factor and influences host defense mechanisms. Purpose This study focuses on the effect of isoniazid (INH) stress on the regulation of ManLAM-related genes, to improve our understanding of virulence and drug resistance development in MTB. Materials and Methods MTB with distinct drug resistance profiles were used for gene expression analysis. Multiplex-real time PCR assay was performed to monitor stress-related genes (hspX, tgs1, and sigE). The expression levels of ManLAM-related genes (pimB, mptA, mptC, dprE1, dprE2, and embC) were quantified by qRT-PCR. Sequence analysis of drug resistance-associated genes (inhA, katG, and rpoB) and ManLAM-related genes were performed to establish a correlation between genetic variation and gene expression. Results INH treatment activates the stress response mechanism in MTB, resulting in a distinct gene expression pattern between drug resistance and drug-sensitive TB. In response to INH, hspX was up-regulated in RIF-R and MDR. tgs1 was strongly up-regulated in MDR, whereas sigE was dramatically up-regulated in the drug-sensitive TB. Interestingly, ManLAM-related genes were most up-regulated in drug resistance, notably MDR (pimB, mptA, dprE1, and embC), implying a role for drug resistance and adaptability of MTB via ManLAM modulation. Conclusion This study establishes a relationship between the antibiotic stress response mechanism and the expression of ManLAM-related genes in MTB samples with diverse drug resistance profiles. The novel gene expression pattern in this work is valuable knowledge that can be applied for TB monitoring and treatment in the future.
A Novel DC Ice-melting Equipment Based on Modular Multilevel Cascade Converter

In view of the problems such as huge bulk,harmonic pollution,and complicated switching with the currently widely used ice-melting equipment based on the state var compensator(SVC),a new design based on the modular multilevel cascade converter is proposed.The double-star bridge-cells modular multilevel cascade converter(DSBC-MMC)discussed in this paper is a combination of H-bridge static synchronous compensator(STATCOM)and half bridge modular multilevel converter(MMC),which can be used as a reactive power compensator and high voltage DC source.Thus it is suitable for DC ice-melting application.A control method which takes into account both the DC ice-melting and reactive power compensation is proposed.The simulation performed has verified the effectiveness of the solution and control method proposed.
Human Capital Investment and Industrial Productivity, as a Correlate of Sustainable Development in Nigeria

The effects of low investment in human capital on industrial productivity have being the bane of sustainable development in the Nigeria industrial sector. The study examined the nexus between human capital investment and industrial productivity as a correlate of sustainable development in Nigeria. Secondary data which spanned from 1981 through 2019 were used for the study. Multiple regression analysis was used to achieve the objectives of the study. Stationarity tests were conducted on all the series before the estimations to affirm absence of stochastic processes. The study, due to the strong evidence of long run relationship among the variables, conducted ARDL model to determine the nature of the relationship between the variables. The findings showed that human capital investment is beneficial and remains an essential tool of industrial productivity in Nigeria. The primary, secondary and tertiary school enrolments, total government expenditure on health and on education were significantly related to industrial productivity in Nigeria. The study concluded that government expenditure on education both capital and recurrent positively influence economic growth in Nigeria. Also, the study revealed that government expenditure policy and implementation capacity are important, especially for determining education and health care contribution to the GDP. Based on the findings and conclusion, the study recommended among others that; there should be establishments of special agencies with the responsibility of improving the skills and capabilities of human capital, improved infrastructural facilities should also be provided for existing schools and hospitals while new training institutions should be established to provide quality education and training so as to improve the skills of the Nigerian labour force.
Relationship between Hearing Impairment and Cognitive, Functional and Psychosocial Status of Community Dwelling Older Adults

Hearing impairment is a common health problem affecting older adults and its prevalence increases with age. It had a significant effect on all aspects of life of older adults. Objective: This study aims to identify identify the relationship between hearing impairment and cognitive, functional and psychosocial status of community dwelling older adults. Setting: The study was conducted in the Ear, Nose and Throat (E.N.T) Outpatient clinic of Damanhur National Medical Institute El-Behaira Governorate, Egypt. Subjects: All older adults attending the outpatient clinic at the time of the study were included in the study. Their number amounted to 200 older adults. They were divided randomly into two equal groups study group (n=100) and control group (n=100). Tools: Socio-demographic and clinical data of the older adults with hearing impairment structured interview schedule, The Mini-Mental State Examination (MMS), Barthel Index Scale, Lawton and Brody scale, The General WellBeing Schedule and UCLA Loneliness Scale (version 3). Results: A statistical significant difference was observed between both groups as regards cognition, performance of IADLs and psychosocial status while no significant difference was found concerning performance of ADLs. Conclusion: Hearing impairment is associated with mild cognitive impairment, severe psychological disturbance and moderate loneliness. Also, performance of IADLs is affected while ADLs is not affected. Recommendations: Teach older adults with hearing impairment about the importance of using hearing aids. This will help to improve their cognitive, functional and psychosocial status. Encourage older adults with hearing impairment to do annual ear examination to prevent further deterioration.
A Transfer-Learning-Based Deep Convolutional Neural Network for Predicting Leukemia-Related Phosphorylation Sites from Protein Primary Sequences

As one of the most important post-translational modifications (PTMs), phosphorylation refers to the binding of a phosphate group with amino acid residues like Ser (S), Thr (T) and Tyr (Y) thus resulting in diverse functions at the molecular level. Abnormal phosphorylation has been proved to be closely related with human diseases. To our knowledge, no research has been reported describing specific disease-associated phosphorylation sites prediction which is of great significance for comprehensive understanding of disease mechanism. In this work, focusing on three types of leukemia, we aim to develop a reliable leukemia-related phosphorylation site prediction models by combing deep convolutional neural network (CNN) with transfer-learning. CNN could automatically discover complex representations of phosphorylation patterns from the raw sequences, and hence it provides a powerful tool for improvement of leukemia-related phosphorylation site prediction. With the largest dataset of myelogenous leukemia, the optimal models for S/T/Y phosphorylation sites give the AUC values of 0.8784, 0.8328 and 0.7716 respectively. When transferred learning on the small size datasets, the models for T-cell and lymphoid leukemia also give the promising performance by common sharing the optimal parameters. Compared with other five machine-learning methods, our CNN models reveal the superior performance. Finally, the leukemia-related pathogenesis analysis and distribution analysis on phosphorylated proteins along with K-means clustering analysis and position-specific conversation profiles on the phosphorylation site all indicate the strong practical feasibility of our easy-to-use CNN models.
Relation between Mean Velocity Index, Time Constant and Critical Closing Pressure in Patients with Subarachnoid Hemorrhage

Background: In patients suffering from Subarachnoid Hemorrhage (SAH), Delayed Cerebral Ischemia (DCI) is partly associated with Vasospasm (VS) and impaired cerebral autoregulation. We investigated the pattern of changes of different Transcranial Doppler (TCD)-derived indices of cerebrovascular dynamics during VS, in patients dichotomized by the presence of DCI. Methods: A retrospective analysis was performed using recordings from 32 SAH patients, diagnosed with VS through bilateral TCD measurements. Patients were divided in 2 groups, depending on development of DCI. Cerebral autoregulation was estimated using the moving correlation coefficient Mxa, calculated from spontaneous fluctuations of Cerebral Blood Flow Velocity (CBFV) and Arterial Blood Pressure (ABP). We also measured cerebral arterial time constant (tau) as the product of resistance (Ra) and Compliance (Ca) and Critical Closing Pressure (CrCP), using two different methods of assessment (CrCPAaslid and CrCPVarsos). Results: In the whole population (N=32), VS caused shortening of tau (ipsilateral to spasm: 0.17 ± 0.08 vs before: 0.25 ± 0.17 sec, p = 0.04), decrease in CrCPAaslid (ipsilateral to spasm: 9.69 ± 23.28 vs before: 27.23 ± 23.31 mmHg, p = 0.01) and interhemispheric asymmetry with lower values on ipsilateral side (p < 0.01). Ipsilateral CrCPAaslid during VS was negatively correlated with Mxa (r =-0.43, p=0.01), whereas CrCPVarsos exhibited positive correlation with tau (r=0.74, p < 0.001). In patients with DCI (N=19), VS caused increase in Mxa (ipsilateral to spasm: 0.36 ± 0.18 vs before: 0.26 ± 0.23, p = 0.04), decrease in CrCPAaslid (ipsilateral to spasm: 6.61 ± 24.5 vs before: 17.24 ± 19.4 mmHg, p = 0.04) and lower values on ipsilateral side (p < 0.01). Arch Clin Biomed Res 2022; 6 (1): 119-133 DOI: 10.26502/acbr.50170230 Archives of Clinical and Biomedical Research Vol. 6 No. 1 – February 2022. [ISSN 2572-9292]. 120 Conclusions: During VS, tau and CrCP were reduced in both temporal and spatial assessments, whereas DCI was associated with loss of autoregulation and vasoparalysis.
Religious change and post-traumatic growth following EMDR trauma therapy

ABSTRACT This systematic review examined the question whether positive religious/spiritual (R/S) change is facilitated by EMDR trauma therapy. The question is asked whether any such R/S change is simply a feature of overall post-traumatic growth (PTG), or is it a form of change specific to EMDR? This systematic review found a number of articles showing that R/S change could follow EMDR, and also could be a feature of overall PTG. Further quantitative studies are needed to discover whether and how R/S change following EMDR is independent of PTG, or related to other aspects of PTG.
Hypertension Prediction in Adolescents Using Anthropometric Measurements: Do Machine Learning Models Perform Equally Well?

The use of anthropometric measurements in machine learning algorithms for hypertension prediction enables the development of simple, non-invasive prediction models. However, different machine learning algorithms were utilized in conjunction with various anthropometric data, either alone or in combination with other biophysical and lifestyle variables. It is essential to assess the impacts of the chosen machine learning models using simple anthropometric measurements. We developed and tested 13 machine learning methods of neural network, ensemble, and classical categories to predict hypertension in adolescents using only simple anthropometric measurements. The imbalanced dataset of 2461 samples with 30.1% hypertension subjects was first partitioned into 90% for training and 10% for validation. The training dataset was reduced to eight simple anthropometric measurements: age, C index, ethnicity, gender, height, location, parental hypertension, and waist circumference using correlation coefficient. The Synthetic Minority Oversampling Technique (SMOTE) combined with random under-sampling was used to balance the dataset. The models with optimal hyperparameters were assessed using accuracy, precision, sensitivity, specificity, F1-score, misclassification rate, and AUC on the testing dataset. Across all seven performance measures, no model consistently outperformed the others. LightGBM was the best model for all six performance metrics, except sensitivity, whereas Decision Tree was the worst. We proposed using Bayes’ Theorem to assess the models’ applicability in the Sarawak adolescent population, resulting in the top four models being LightGBM, Random Forest, XGBoost, and CatBoost, and the bottom four models being Logistic Regression, LogitBoost, SVM, and Decision Tree. This study demonstrates that the choice of machine learning models has an effect on the prediction outcomes.
Generalized hyperbolic secant distribution: Properties, estimation, and applications

In this study, we define a generalized hyperbolic secant distribution. Poor fit to heavy tailed data sets is repeatedly obtained by existing three-parameter distributions. Only three parameters are considered in the proposed new distribution and it fits a heavy left- and right-tailed data better than various existing distributions. We study some properties of the new distribution, namely, mode, skewness, kurtosis, hazard function, moments, mean deviation, and Shannon entropy. Seven different frequentist methods for estimating the parameters are briefly described. A simulation study is also conducted to compare the performances of the proposed methods of estimation. The usefulness of the new model is demonstrated by applying it to fit two real-life data.
Optimizing Procedures for Antioxidant Phenolics Extraction from Skin and Kernel of Peanuts with Contrasting Levels of Drought Tolerance

Peanut is an affordable legume known for its nutritional value and phenolic content. The kernel and skin of 14 peanut genotypes contrasting in drought tolerance had their phenolic profiles determined and reactive oxygen species (ROS) scavenging activity evaluated. Firstly, temperature and % EtOH to extract antioxidant phenolic compounds were optimized using response surface methodology (RSM). The optimized extraction conditions, 60 °C and 35% EtOH for kernels and 40 °C and 60% EtOH for skins, were further adopted, and phenolic compounds were identified and quantified using high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (HPLC-ESI-QTOF-MS) and high-performance liquid chromatography with photodiode array detector (HPLC-PDA). As a result, phenolic acids and glycosidic/non-glycosidic flavonoids were found. Principal component analysis was conducted, and the pairwise score plot of the skin extracts based on individual phenolic compounds showed a trend of genotype clustering based not only on drought tolerance but also on botanical type of germplasm. Therefore, our results demonstrate the status quo for antioxidant phenolic compounds of peanut genotypes contrasting in drought tolerance grown under natural field conditions.
Bio and mineral-N fertilization of Sunflower (Helianthus annuus L.) Grown on Sandy Soil Using 15N Technique

Biofertilization using Azotobacter chroococcum (B1), Azospirillum brasilense (B2) and Bacillus megaterium (B3), were assessed vs. Mineral-N fertilization using ammonium sulphate with 2% N atom excess on sunflower grown on a virgin sand during 2014 summer season. Plants grew for 45 days. The highest plant height (64.87 cm) with an increase about 93.6% over the non-fertilized was given by the Azospirillum bacteria combined with the high N rate (N3B2). Total chlorophyll ranged from 17.8% by (N2B1) to 34.9% by (N3B0). The highest dry matter yield of 44.20 kg ha was by N3B0. The highest N uptake was given by plants receiving high N without biofertilization (N3B0) with an increase 141.4%. The highest fertilizer N recovery of 18.45% was by high N without biofertilization (N3B0) with an increase 99.7%.
Lifespan Increase of Podospora anserina by Oleic Acid Is Linked to Alterations in Energy Metabolism, Membrane Trafficking and Autophagy

The maintenance of cellular homeostasis over time is essential to avoid the degeneration of biological systems leading to aging and disease. Several interconnected pathways are active in this kind of quality control. One of them is autophagy, the vacuolar degradation of cellular components. The absence of the sorting nexin PaATG24 (SNX4 in other organisms) has been demonstrated to result in impairments in different types of autophagy and lead to a shortened lifespan. In addition, the growth rate and the size of vacuoles are strongly reduced. Here, we report how an oleic acid diet leads to longevity of the wild type and a PaAtg24 deletion mutant (ΔPaAtg24). The lifespan extension is linked to altered membrane trafficking, which abrogates the observed autophagy defects in ΔPaAtg24 by restoring vacuole size and the proper localization of SNARE protein PaSNC1. In addition, an oleic acid diet leads to an altered use of the mitochondrial respiratory chain: complex I and II are bypassed, leading to reduced reactive oxygen species (ROS) production. Overall, our study uncovers multiple effects of an oleic acid diet, which extends the lifespan of P. anserina and provides perspectives to explain the positive nutritional effects on human aging.