Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution of Signal Transducer and Activator of Transcription 3 (STAT3) to Bone Development and Repair

Signal transducer and activator of transcription 3 (STAT3) is a transcription factor activated canonically by numerous cytokines and other factors, with significant roles in immunity, immune diseases, and cancer. It has also been implicated in several human skeletal disorders, with loss-of-function (LOF) mutations associated with aberrant skeletal development. To gain further insights, two zebrafish STAT3 lines were investigated: a complete LOF knockout (KO) mutant and a partial LOF mutant with the transactivation domain truncated (ΔTAD). Consistent with other studies, the KO mutants were smaller, with reduced length in early embryos exacerbated by a decreased growth rate from 5 days postfertilization (dpf). They displayed skeletal deformities that approached 80% incidence by 30 dpf, with a significant reduction in early bone but not cartilage formation. Further analysis additionally identified considerable abrogation of caudal fin regeneration, concomitant with a paucity of infiltrating macrophages and neutrophils, which may be responsible for this. Most of these phenotypes were also observed in the ΔTAD mutants, indicating that loss of canonical STAT3 signaling was the likely cause. However, the impacts on early bone formation and regeneration were muted in the ΔTAD mutant, suggesting the potential involvement of noncanonical functions in these processes.
Adaptive Control of Strict-Feedback Nonlinear Systems Under Denial-of-Service: A Synthetic Analysis

This paper investigates the adaptive control for a class of uncertain nonlinear systems under denial-of-service (DoS) attacks. We analyze the closed-loop system stability under DoS attacks in terms of attack duration, attack frequency and resting time duration respectively. Three scenarios of DoS attacks against the system stability are considered. Firstly, it is shown that if the duration of each attack is less than a given constant, asymptotical convergence of system output is still preserved. Secondly, if the bounds on the frequency and duration of attacks with respect to overall intervals meet certain conditions, the proposed event-triggered control scheme guarantees that all the closed-loop signals are globally bounded and the stabilization error converges to a ball with a radius arbitrarily small. Thirdly, if resting time duration meets certain conditions after an arbitrarily long attack, closed-loop boundedness is still preserved. Simulation results are shown to illustrate the effectiveness of the proposed control schemes.
Glutamic Acid-Grafted Metal-Organic Framework: Preparation, Characterization, and Heavy Metal Ion Removal Studies

Fast industrial and agricultural expansion result in the production of heavy metal ions (HMIs). These are exceedingly hazardous to both humans and the environment, and the necessity to eliminate them from aqueous systems prompts the development of novel materials. In the present study, a UIO-66 (COOH) 2 metal-organic framework (MOF) containing free carboxylic acid groups was post-synthetically modified with L-glutamic acid via the solid-solid reaction route. Pristine and glutamic acid-treated MOF materials were characterized in detail using several physicochemical techniques. Single-ion batch adsorption studies of Pb(II) and Hg(II) ions were carried out using pristine as well as amino acid-modified MOFs. We further examined parameters that influence removal efficiency, such as the initial concentration and contact time. The bare MOF had a higher ion adsorption capacity for Pb(II) (261.87 mg/g) than for Hg(II) ions (10.54 mg/g) at an initial concentration of 150 ppm. In contrast, an increased Hg(II) ion adsorption capacity was observed for the glutamic acid-modified MOF (80.6 mg/g) as compared to the bare MOF. The Hg(II) ion adsorption capacity increased by almost 87% after modification with glutamic acid. Fitting results of isotherm and kinetic data models indicated that the adsorption of Pb(II) on both pristine and glutamic acid-modified MOFs was due to surface complexation of Pb(II) ions with available – COOH groups (pyromellitic acid). Adsorption of Hg(II) on the glutamic acid-modified MOF was attributed to chelation, in which glutamic acid grafted onto the surface of the MOF formed chelates with Hg(II) ions.
Phylogeography and hybridization of corvid birds in the Palearctic Region

Natural hybridization increases a lot phenotypic and genetic diversity and shapes intra-species patterns, which is a subject of phylogeography. We studied mitochondrial and complete genome variation in the bird family Corvidae, genera Corvus, Pica, Cyanopica, Perisoreus and Nucifraga. In the classic case of natural hybridization between carrion and hooded crows in Siberia, we found no decreased fitness of hybrids, but instead positive assortative mating which should restrict hybrid zone width. Several genetic markers were unable to discriminate between pure carrion and hooded crows. Mitochondrial DNA sequences revealed no difference between carrion and hooded crows, but instead two diverged haplogroups within the eastern part of the distribution range of the carrion crow. NGS resulted in a clear pattern of diversification of pure forms and hybrids (by using SNPs), and showed genomic regions of increased variability, the so-called “speciation islands”. Comparing European and Siberian crow hybrid zones, differences in genome regions bearing genes of melanogenesis supposedly under divergent selection were found. Comparative phylogeographic analysis of 10 widely distributed Palearctic species revealed two kinds of patterns: one with a division into two haplogroups, western and eastern, and another one without such a division. These two phylogeographic patterns might be explained by different habitat preferences: mainly open fields for the first group and forests for the second one. One glacial refuge was assigned to the latter group, while west-east group species might have survived in several refuges. One of such species, the Eurasian magpie (Pica pica) has a gap in its range in Transbaikalia, which is currently shrinking before our eyes. The two subspecies divided by this gap differ in phenotype, mtDNA and vocalization. In their young contact zone, some hybridization occurs with small introgression limited by certain post-zygotic isolation.
Suppression of rainfall by fires in African drylands

Fire is a widespread agent of disturbance in African drylands, but the impact of fire on local precipitation remains poorly understood and large‐scale observational evidence has been lacking. Here we link fire to a reduction in precipitation across African drylands. Using 15 years of satellite observations over continental sub‐Saharan Africa, we find that more extensive and later dry season fires lead to wet season rainfall deficits of up to 30 mm (~10%). The effect is stronger in the Southern Hemisphere, a signal we attribute to the later timing of fires in the dry season. Given the coupling between rainfall, fuel loads, and fire in African drylands, a negative interannual feedback may arise between fire and precipitation, whereby fires suppress precipitation, thereby reducing fuel load and fire in the subsequent season. The reduced fuel load would, in turn, increase precipitation, completing the feedback loop. This feedback may contribute to a pervasive negative autocorrelation observed in Southern Hemisphere annual rainfall.
Effect of Mesorhizobium in chickpea root nodulation using transcriptome profiling approach

Root nodule development is a key event in legume plants for nitrogen fixation. In this process, Mesorhizobium forms a symbiotic relationship with chickpea (legume) crop that can produce nodule to fix the environmental nitrogen for necessary vital activities. Mesorhizobium infected chickpea shows enhanced function at different stages. We studied high throughput sequencing (454/Roche) data of control and three stages, viz. early, middle and late stages of Mesorhizobium infection (Bioproject: PRJNA214031) during nodule formation to identify the key regulatory genes in nitrogen fixation process and long non-coding RNAs (lncRNAs) participating in Mesorhizobium inoculation of chickpea root nodule. De novo assembly of raw reads resulted in 38835 contigs with the N50 value of 1019 bp. Differential expression analysis of assembled transcripts showed that 5615 genes were expressed differentially, out of which 1696 genes were differentially expressed in early infection while 1338 and 2581 genes were expressed in middle stage and late stage of infection, respectively. On analysis of DEGs, it was found that 392 genes were common in all three stages, 1304 were present in both early and late infection while 946 genes were uniquely expressed in the middle stage of infection. It has been evident from studies that long non-coding RNAs participate in host responses to infection but many lncRNAs are still unknown at the level of Mesorhizobium inoculated root nodules of chickpea. The present study aimed at identification of the lncRNAs in chickpea root nodules and to understand the transcriptomic mechanism during Mesorhizobium inoculation. Findings of this study characterize differential expression of lncRNAs in Mesorhizobium infected chickpea root nodules and it further gives understanding of symbiotic association in both aspects of coding and non-coding regulation.
Use of Cone Beam Computed Tomography to Identify the Morphology of Maxillary and Mandibular Premolars in Chennai Population

Objective: The complex root canal anatomy is inherently colonised by microbial flora. Endodontic treatment success is always related to adequate disinfection of the root canal space, which ultimately affects the treatment outcome. A thorough understanding of the external and internal root canal anatomy by using adequately imaging modalities is essential before planning any treatment. The aim of this study was to investigate the number and morphology of the root canals of maxillary and mandibular premolars in Chennai population. Material and Methods: Full-size cone-beam computed tomographic images were randomly collected from 100 patients, resulting in a total of 200 first and 200 second maxillary premolars as well as 200 first and 200 second mandibular premolars. All the eight premolars were analysed in single patients, who underwent cone-beam computed tomography scanning during pre-operative assessment (before implant surgery, orthodontic treatment, diagnosis of dental-alveolar trauma or difficult root canal treatment). Total number of roots and root canals, frequency and correlations between men and women were recorded and statistically analysed by using chi-square tests. The root canal configurations were rated according to the Vertucci’s classification. Results: In the maxillary first premolar group (n = 200), 36.3% had 1 root, 56.7% had 2 roots and 7.0% had 3 roots, with most exhibiting a type IV canal configuration. In the maxillary second premolar group (n = 200), 60% had 1 root, 29.8% had 2 roots and 10.2% had 3 roots, with the majority of single-rooted second premolars exhibiting a type I canal configuration. In the mandibular first premolar group (n = 200), 80.5% had 1 root, 9.8% had 2 roots and 5% had 3 roots. In the mandibular second premolar group (n=200), 90.1% had 1 root, 6.4% had 2 roots and 3.5 % had 3 roots, with most exhibiting a type I canal configuration. No statistical correlation was found between number of roots, gender and tooth position. Conclusion: This cone-beam computed tomographic study confirmed previous anatomical and morphological investigations. Therefore, the possibility of additional root canals should be considered when treating premolars. Keywords: Cone-beam computed tomography; Mandibular; Maxillary; Premolar; Root canal; Morphology.
Classification of Multiple H&E Images via an Ensemble Computational Scheme

In this work, a computational scheme is proposed to identify the main combinations of handcrafted descriptors and deep-learned features capable of classifying histological images stained with hematoxylin and eosin. The handcrafted descriptors were those representatives of multiscale and multidimensional fractal techniques (fractal dimension, lacunarity and percolation) applied to quantify the histological images with the corresponding representations via explainable artificial intelligence (xAI) approaches. The deep-learned features were obtained from different convolutional neural networks (DenseNet-121, EfficientNet-b2, Inception-V3, ResNet-50 and VGG-19). The descriptors were investigated through different associations. The most relevant combinations, defined through a ranking algorithm, were analyzed via a heterogeneous ensemble of classifiers with the support vector machine, naive Bayes, random forest and K-nearest neighbors algorithms. The proposed scheme was applied to histological samples representative of breast cancer, colorectal cancer, oral dysplasia and liver tissue. The best results were accuracy rates of 94.83% to 100%, with the identification of pattern ensembles for classifying multiple histological images. The computational scheme indicated solutions exploring a reduced number of features (a maximum of 25 descriptors) and with better performance values than those observed in the literature. The presented information in this study is useful to complement and improve the development of computer-aided diagnosis focused on histological images.
Sensitivity of the Middle East–North African Tropical Rainbelt to Dust Shortwave Absorption: A High-Resolution AGCM Experiment

AbstractShortwave absorption is one of the most important, but the most uncertain, components of direct radiative effect by mineral dust. It has a broad range of estimates from different observational and modeling studies and there is no consensus on the strength of absorption. To elucidate the sensitivity of the Middle East–North African (MENA) tropical summer rainbelt to a plausible range of uncertainty in dust shortwave absorption, AMIP-style global high-resolution (25 km) simulations are conducted with and without dust, using the High-Resolution Atmospheric Model (HiRAM). Simulations with dust comprise three different cases by assuming dust as a very efficient, as a standard, and as an inefficient absorber. Intercomparison of these simulations shows that the response of the MENA tropical rainbelt is extremely sensitive to the strength of shortwave absorption. Further analyses reveal that the sensitivity of the rainbelt stems from the sensitivity of the multiscale circulations that define the rainbelt.
Pharmacokinetic properties of a new sustained-release pregabalin tablet in subjects with reduced renal function

A new sustained-release (SR) pregabalin tablet, YHD1119, was formulated for once-daily dosing. In the current study, we aimed to evaluate the pharmacokinetics of YHD1119 tablets in patients with reduced renal function. Subjects were grouped by creatinine clearance: > 60 mL/min/1.73m2 (Cohort A) and 30–60 mL/min/1.73m2 (Cohort B). Eight subjects in Cohort A received a YHD1119 75 mg tablet (Y75T) and a YHD1119 150 mg tablet (Y150T) in each period, and eight subjects in Cohort B received a Y75T. Non-compartment analysis and population pharmacokinetic analysis using a one-compartment model with first-order elimination and first-order absorption with lag time were performed. Sixteen subjects completed the study. The geometric mean ratio (GMR) (90% confidence intervals [CI]) for maximum concentration (Cmax), and area under the concentration-time profile from 0 to the last measurable time (AUClast) after Y75T of Cohort B to those of Y75T of Cohort A were 1.2273 (1.0245–1.4701), and 2.4146 (1.8142–3.2138), respectively. The GMR (90% CI) for Cmax, and AUClast after Y75T of Cohort B to those of Y150T of Cohort A were 0.6476 (0.5229–0.8021), and 1.1471 (0.8418–1.5632), respectively. Simulated steady-steady pregabalin concentrations after once-daily Y75T dosing in subjects with eGFR 45 mL/min/1.73 m2 were within the range of steady-state concentrations simulated after once-daily Y150T dosing in subjects with eGFR 90 mL/min/1.73 m2. The total pregabalin exposure of Y75T in patients with moderate renal impairment was comparable with that of Y150T in subjects with near-normal renal function. Trial Registration ClinicalTrials.gov Identifier: NCT05012436
Evaluation of vancomycin use in university-affiliated hospitals in Southern Khorasan Province (East Iran) based on HICPAC guidelines

Background Vancomycin resistance has raised concerns about its effectiveness prospect in the treatment of patients with Gram-positive infections. The Healthcare Infection Control Practices Advisory Committee (HICPAC) has recently established guidelines to delineate improper use of vancomycin. In this light, we sought out to determine the appropriateness of vancomycin prescription using the HICPAC guidelines. Setting The study was carried out in two university-affiliated hospitals, Valiasr and Imam Reza, with 297 and 234 beds, respectively, from May 2012 to May 2013. Methods This retrospective study evaluated the vancomycin prescription and usage in the hospitals. Total vancomycin use was determined and expressed as vancomycin courses per 298 admitted patients. The patient information was collected on a data collection sheet as follows: demographic variables, etiology and localization of infection, microbiological data, duration of vancomycin treatment, reasons for vancomycin prescription, prescribed antibiotic dosing, and patient regimen. Results The average age of the patients and vancomycin treatment duration were 55.965 years and 10.5 days, respectively. Septicemia (15.7%) was the most common cause of vancomycin administration. Vancomycin use was documented to be appropriate and inappropriate in 236 (89.4%) and 28 (10.6%) patients, respectively. No statistically significant differences were found among the wards and hospitals (P values =0.66 and 0.54, respectively) in terms of appropriateness of vancomycin use based on the HICPAC criteria. In addition, 29.21% and 62% of all patients exhibited complete and partial recovery, respectively. We found that 90% of the cases showed compliance with the HICPAC recommendations. Conclusion Comprehensive programs are required to improve the vancomycin use in the hospitals. Vancomycin use should be monitored due to its large-scale empiric use. The rate of improper use of vancomycin in the infection and intensive care unit services may be high, and pharmacists must take appropriate action to optimize the use of the drug.
Effect of water use by smallholder farms in the Letaba basin : a case study using the SIMGRO model

For the Letaba basin situated in the South African part of the Limpopo basin, a hydrological study was carried out in order to quantify the effect of smallholder farming on river flows. Important was to study the consequences of improved agricultural systems on the river flows, in particular for the Kruger National Park situated in the lower part of the Letaba basin. The SIMGRO model was used in this study, which integrates groundwater and surface water. The model was calibrated, and furthermore a comparison of measured discharges and groundwater levels against calculated discharges and groundwater levels, revealed that the model is suiTable for practical analysis. For the smallholders farms different scenarios were defined with different levels of crop yield. An increase in crop yield has consequences on more water use as irrigation and crop water use. Because the area covering smallholder farming is only 0.5% of the basin, the effects of changes in water use are relatively small. In a scenario, the weather conditions for 2050 were analysed. This reveals that discharges will go down by 30% on average, which means a substantial reduction of the water resources.
An EEG-Based Computational Model for Decoding Emotional Intelligence, Personality, and Emotions

Emotional intelligence (EI), a critical aspect of regulating emotions and behavior in daily life, holds paramount significance in both psychology research and real-world applications. Understanding and assessing EI are essential for informed decision-making, nurturing relationships, and facilitating efficient communication. As human–computer interaction (HCI) continues to evolve, there is a growing need to develop systems capable of comprehending human emotions, personality traits, and moods through recognition models. This research endeavors to explore the potential of recognizing EI in the context of effective HCI. To address this challenge, we have developed a novel computational model based on electroencephalogram (EEG) data. Our work encompasses a carefully curated EEG dataset, featuring recordings from 40 participants who were exposed to a set of 16 emotional video clips selected from distinct quadrants of the valence-arousal (VA) space. Participants’ emotional responses were meticulously annotated through self-assessment of emotional dimensions for each video stimulus. In addition, participants’ feedback on the big-five personality traits and their responses to the trait emotional intelligence questionnaire (TEIQue) served as our ground truth for further analysis. Our study includes a comprehensive correlation analysis, using Pearson correlations to establish the relationships between personality traits and EI. Furthermore, we conducted EEG-based analysis to uncover connections between EEG signals and emotional attributes. Remarkably, our analysis reveals that EEG signals excel at capturing differences in EI levels. Leveraging machine learning algorithms, we have constructed binary classification models that yield average $F1$ scores of 0.72, 0.71, and 0.62 for emotions, personality traits, and EI, respectively. These experimental outcomes underscore the potential of EEG signals in the recognition of EI, personality traits, and emotions. We envision our proposed model as a foundational element in the development of effective HCI systems, enabling a deeper and better understanding of human behavior.
Megafire effects on spotted owls: elucidation of a growing threat and a response to Hanson et al. (2018)

The extent to which wildfire adversely affects spotted owls (Strix occidentalis) is a key consideration for ecosystem restoration efforts in seasonally dry forests of the western United States. Recently, Jones et al. (2016) demonstrated that the 2014 King Fire (a “megafire”) adversely affected a population of individually-marked California spotted owls (S. o. occidentalis) monitored as part of a long-term demographic study in the Sierra Nevada, California, USA because territory occupancy declined substantially at territories burned at high-severity and GPS-tagged spotted owls avoided large patches of high-severity fire. Hanson et al. (2018) attempted to reassess changes in territory occupancy of the Jones et al. (2016) study population and claimed that occupancy declined as a result of post-fire salvage logging not fire per se and suggested that the avoidance of GPS-marked owls from areas that burned at high-severity was due to post-fire logging rather than a response to high-severity fire. Here, we demonstrate that Hanson et al. (2018) used erroneous data, inadequate statistical analyses and faulty inferences to reach their conclusion that the King Fire did not affect spotted owls and, more broadly, that large, high-severity fires do not pose risks to spotted owls in western North American dry forest ecosystems. We also provide further evidence indicating that the King Fire exerted a clear and significant negative effect on our marked study population of spotted owls. Collectively, the additional evidence presented here and in Jones et al. (2016) suggests that large, high-severity fires can pose a threat to spotted owls and that restoration of natural low- to mixed-severity frequent fire regimes would likely benefit both old-forest species and dry forest ecosystems in this era of climate change. Meeting these dual objectives of species conservation and forest restoration will be complex but it is made more challenging by faulty science that does not acknowledge the full range of wildfire effects on spotted owls.