Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of a Cardiovascular Disease Risk Prediction Model: A Preliminary Retrospective Cohort Study of a Patient Sample in Saudi Arabia

Saudi Arabia has an alarmingly high incidence of cardiovascular disease (CVD) and its associated risk factors. To effectively assess CVD risk, it is essential to develop tailored models for diverse regions and ethnicities using local population variables. No CVD risk prediction model has been locally developed. This study aims to develop the first 10-year CVD risk prediction model for Saudi adults aged 18 to 75 years. The electronic health records of Saudi male and female patients aged 18 to 75 years, who were seen in primary care settings between 2002 and 2019, were reviewed retrospectively via the Integrated Clinical Information System (ICIS) database (from January 2002 to February 2019). The Cox regression model was used to identify the risk factors and develop the CVD risk prediction model. Overall, 451 patients were included in this study, with a mean follow-up of 12.05 years. Thirty-five (7.7%) patients developed a CVD event. The following risk factors were included: fasting blood sugar (FBS) and high-density lipoprotein cholesterol (HDL-c), heart failure, antihyperlipidemic therapy, antithrombotic therapy, and antihypertension therapy. The Bayesian information criterion (BIC) score was 314.4. This is the first prediction model developed in Saudi Arabia and the second in any Arab country after the Omani study. We assume that our CVD predication model will have the potential to be used widely after the validation study.
Cellular and Genomic Features of Muscle Differentiation from Isogenic Fibroblasts and Myoblasts

The ability to recapitulate muscle differentiation in vitro enables the exploration of mechanisms underlying myogenesis and muscle diseases. However, obtaining myoblasts from patients with neuromuscular diseases or from healthy subjects poses ethical and procedural challenges that limit such investigations. An alternative consists in converting skin fibroblasts into myogenic cells by forcing the expression of the myogenic regulator MYOD. Here, we directly compared cellular phenotype, transcriptome, and nuclear lamina-associated domains (LADs) in myo-converted human fibroblasts and myotubes differentiated from myoblasts. We used isogenic cells from a 16-year-old donor, ruling out, for the first time to our knowledge, genetic factors as a source of variations between the two myogenic models. We show that myo-conversion of fibroblasts upregulates genes controlling myogenic pathways leading to multinucleated cells expressing muscle cell markers. However, myotubes are more advanced in myogenesis than myo-converted fibroblasts at the phenotypic and transcriptomic levels. While most LADs are shared between the two cell types, each also displays unique domains of lamin A/C interactions. Furthermore, myotube-specific LADs are more gene-rich and less heterochromatic than shared LADs or LADs unique to myo-converted fibroblasts, and they uniquely sequester developmental genes. Thus, myo-converted fibroblasts and myotubes retain cell type-specific features of radial and functional genome organization. Our results favor a view of myo-converted fibroblasts as a practical model to investigate the phenotypic and genomic properties of muscle cell differentiation in normal and pathological contexts, but also highlight current limitations in using fibroblasts as a source of myogenic cells.
Xylanase Production by Solid-State Fermentation for the Extraction of Xylooligosaccharides from Soybean Hulls§

SUMMARY Research background The development of a novel process for the production of xylooligosaccharides (XOS) based on the 4R concept is made possible by the integration of numerous techniques, especially enzymatic modification together with the physical pretreatment of renewable materials. This study aims to integrate the use of agricultural wastes for the production of xylanase by a new strain of Penicillium sp. and value-added products, XOS. Experimental approach For the production of xylanase, a solid-state fermentation was performed using wheat bran as substrate. To obtain the most active crude extract of xylanase, the time frame of cultivation was first adjusted. Then, the downstream process for xylanase purification was developed by combining different membrane separation units with size exclusion chromatography. Further characterisation included determination of the optimal pH and temperature, determination of the molecular mass of the purified xylanase and analysis of kinetic parameters. Subsequently, the hydrolytic ability of the partially purified xylanase in the hydrolysis of alkali-extracted hemicellulose from soybean hulls was investigated. Results and conclusions Our results show that Penicillium rubens produced extracellular xylanase at a yield of 21 U/g during solid-state fermentation. Using two ultrafiltration membranes of 10 and 3 kDa in combination with size exclusion chromatography, a yield of 49 % and 13-fold purification of xylanase was achieved. The purified xylanase (35 kDa) cleaved linear bonds β-(1→4) in beechwood xylan at a maximum rate of 0.64 μmol/(min·mg) and a Michaelis constant of 44 mg/mL. At pH=6 and 45 °C, the purified xylanase showed its maximum activity. The xylanase produced showed a high ability to hydrolyse the hemicellulose fraction isolated from soybean hulls, as confirmed by thin-layer chromatography. In the hydrothermally pretreated hemicellulose hydrolysate, the content of XOS with different degrees of polymerisation was detected, while in the non-pretreated hemicellulose hydrolysate, the content of xylotriose and glucose was confirmed. Novelty and scientific contribution Future research focusing on the creation of new enzymatic pathways for use in processes to convert renewable materials into value-added products can draw on our findings.
In Silico–Ex Vitro Iteration Strategy for Affinity Maturation of Anti-Ricin Peptides and the SPR Biosensing Application

The highly toxic plant toxin ricin is one of the most known threatening toxins. Accurate and sensitive biosensing methods for the first emergency response and intoxication treatment, are always pursued in the biodefense field. Screening affinity molecules is the fundamental mainstream approach for developing biosensing methods. Compared with common affinity molecules such as antibodies and oligonucleotide aptamers, peptides have great potential as biosensing modules with more accessible chemical synthesis capability and better batch-to-batch stability than antibodies, more abundant interaction sites, and robust sensing performance towards complex environments. However, anti-ricin peptides are so scant to be screened and discovered, and an advanced screening strategy is the utmost to tackle this issue. Here, we present a new in silico-in vitro iteration-assisted affinity maturation strategy of anti-ricin peptides. We first obtained affinity peptides targeting ricin through phage display with five panning rounds of “coating-elution-amplification-enrichment” procedures. The binding affinity and kinetic parameters characterized by surface plasmon resonance (SPR) showed that we had obtained four peptides owning dissociation constants (KD) around 2~35 μM, in which peptide PD-2-R5 has the lower KD of 4.7 μM and higher stable posture to interact with ricin. We then constructed a new strategy for affinity maturity, composing two rounds of in silico-in vitro iterations. Firstly, towards the single-site alanine scanning mutation peptide library, the molecular docking predictions match the SPR evaluation results well, laying a solid foundation for designing a full saturation mutated peptide library. Secondly, plenty of in silico saturation mutation prediction results guided the discovery of peptides PD2-R5-T3 and PD-2-R5-T4 with higher affinity from only a limited number of SPR evaluation experiments. Both evolved peptides had increased affinity by about 5~20 times, i.e., KD of 230 nM and 900 nM. A primary cellular toxicity assay indicated that both peptides could protect cells against ricin damage. We further established an SPR assay based on PD-2-R5-T3 and PD-2-R5-T4 elongated with an antifouling peptide linkage and achieved good linearity with a sensitivity of 1 nM and 0.5 nM, respectively. We hope this new affinity-mature strategy will find its favorable position in relevant peptide evolution, biosensing, and medical countermeasures for biotoxins to protect society’s security and human life better.
Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-Squares Estimation ( IDEAL ) Fast Spin-Echo Imaging of the Ankle : Initial Clinical Experience

2GE Global Applied Science Laboratory, Menlo Park, CA. OBJECTIVE. Reliable, uniform fat suppression is important. Multiple approaches currently exist, many of which suffer from either suboptimal signal-to-noise ratio (SNR), or the inability to obtain consistent fat suppression around the ankle joint. Our purpose was to test iterative decomposition of water and fat with echo asymmetry and the least-squares estimation (IDEAL) method in combination with fast spin-echo imaging, which is able to achieve reliable high SNR images with uniform fat–water separation. SUBJECTS AND METHODS. We compared IDEAL fast spin-echo with conventional fat-suppressed fast spin-echo imaging in 33 ankles in 32 patients. Quantitative measurements of SNR and contrast-to-noise ratio efficiency were made, and qualitative diagnostic image quality and fat-suppression scores were determined. RESULTS. We found that the SNR efficiency for both cartilage and fluid was similar for both techniques, and fluid/cartilage contrast-to-noise ratio efficiency was higher with IDEAL fast spin-echo imaging. Fat suppression and diagnostic quality scores using the IDEAL method were superior (p < 0.01) to fat-suppressed fast spin-echo imaging. CONCLUSION. IDEAL fast spin-echo imaging is a promising technique for MRI of the ankle.
Phase portraits of a family of Kolmogorov systems depending on six parameters

We consider a general 3-dimensional Lotka-Volterra system with a rational first integral of degree two of the form \(H=x^i y^j z^k\). The restriction of this Lotka-Volterra system to each surface \(H(x,y,z)=h\) varying \(h\in \mathbb{R}\) provide Kolmogorov systems. With the additional assumption that they have a Darboux invariant of the form \(x^\ell y^m e^{st}\) they reduce to the Kolmogorov systems $$\displaylines{ \dot{x}=x\big(a_0- \mu (c_1 x + c_2 z^2 + c_3 z)\big),\cr \dot{z}=z\big(c_0+ c_1 x + c_2 z^2 + c_3 z\big). }$$ We classify the phase portraits in the Poincare disc of all these Kolmogorov systems which depend on six parameters. For more information see https://ejde.math.txstate.edu/Volumes/2021/35/abstr.html
Lipidic Formulations Inspired by COVID Vaccines as Smart Coatings to Enhance Nanoparticle-Based Cancer Therapy

Recent advances in nanomedicine have led to the introduction and subsequent establishment of nanoparticles in cancer treatment and diagnosis. Nonetheless, their application is still hindered by a series of challenges related to their biocompatibility and biodistribution. In this paper, we take inspiration from the recently produced and widely spread COVID vaccines, based on the combinational use of ionizable solid lipid nanoparticles, cholesterol, PEGylated lipids, and neutral lipids able to incorporate mRNA fragments. Here, we focus on the implementation of a lipidic formulation meant to be used as a smart coating of solid-state nanoparticles. The composition of this formulation is finely tuned to ensure efficient and stable shielding of the cargo. The resulting shell is a highly customized tool that enables the possibility of further functionalizations with targeting agents, peptides, antibodies, and fluorescent moieties for future in vitro and in vivo tests and validations. Finally, as a proof of concept, zinc oxide nanoparticles doped with iron and successively coated with this lipidic formulation are tested in a pancreatic cancer cell line, BxPC-3. The results show an astonishing increase in cell viability with respect to the same uncoated nanoparticles. The preliminary results presented here pave the way towards many different therapeutic approaches based on the massive presence of highly biostable and well-tolerated nanoparticles in tumor tissues, such as sonodynamic therapy, photodynamic therapy, hyperthermia, and diagnosis by means of magnetic resonance imaging.
Development of an efficiency ranking system for beef cows and effects on feed intake, ruminal fermentation, NDF turnover, and apparent total tract digestibility

Abstract Beef cows (n = 100) were ranked for efficiency based on cow rump fat thickness at calving, calving date, and calf weaning weight (% dam BW) over 2 years. The nine most (ME) and least efficient (LE) cows were used to compare feed intake and ruminal fermentation using four 26-day periods with decreasing dietary nutrient density. There were no phenotype × diet interactions for variables of primary interest. Rump fat and calf weaning weight were greater, and the calving date was earlier for ME cows than LE cows (P ≤ 0.032). The ME cows were lighter (P < 0.001) but had similar DMI (P = 0.93) to the LE cows, resulting in greater dry matter intake (DMI) %BW (P < 0.001). Ruminal contraction amplitude height and area (P ≤ 0.015) and ruminal digesta weight were greater for LE than ME cows (P = 0.043). Ruminal ash-free neutral detergent fiber (aNDFom) passage was greater for ME cows than LE cows (P = 0.047), but the rate of aNDFom degradation did not differ (P = 0.69). Total tract digestibility did not differ. Efficient cows had greater rump fat, weaned heavier calves, ate more relative to their BW, had a smaller ruminal digesta mass, and had greater ruminal passage of aNDFom without reducing digestibility.
Cascade Windows-Based Multi-Stream Convolutional Neural Networks Framework for Early Detecting In-Sleep Stroke Using Wristbands

A stroke, particularly when it occurs during sleep, is likely to have a negative prognosis due to delayed detection. Timely and early detection plays a vital role in ensuring prompt administration of reperfusion therapy and preventing permanent disabilities. To address this, we propose a wearable system comprising two wristbands that monitor asymmetric motion patterns (hemiparesis) during sleep. A novel deep learning framework called Early Detection of In-sleep Stroke (EDIS) serves as the core engine for stroke detection during sleep. The framework employs cascading windows of various sizes for convolutional neural networks (CNNs) to enhance both the detection performance and the detection time. We utilize 1D accelerometer sensor data from both hands to generate 2D matrix images, which serve as input for multiple CNN models. Predictions from these models are combined using blending ensemble learning to make a final decision. Although the EDIS framework requires a larger parameter size and longer inference time due to its network architecture with multiple CNNs, it outperforms five single-CNN models by improving detection performance and reducing detection time. Extensive evaluation results demonstrate that EDIS framework accurately and quickly detects in-sleep stroke within the deadline (3 hours). EDIS-Resnet50 has the best classification performance out of the ten DL model candidates, with an F1-score of 0.955 (0.950, 0.960). We believe that our framework will be a fundamental component of real-time stroke monitoring systems, contributing to a reduction in mortality rates among patients suspected of having a stroke.
EXPLORATION OF THE CHARACTER OF COOPERATION IN PHYSICS

This study aims to identify how the character of student cooperation through indicators of good listeners and respect for others. This type of research is a mixed-method type of explanatory approach. While the research instrument uses questionnaires and interviews, data analysis uses descriptive tests and descriptions. The sampling technique used purposive sampling. The results of the study showed students on the mutually encouraging aspect of the cooperation character indicator Junior High School 16 Muaro Jambi with a percentage of 70% in the good category, Junior High School 18 Kerinci with a percentage of 66% in the good category, Valmiera Secondary School with a percentage of 45% in the very good category, and Valmiera Viesturs secondary school percentage is 54% very good category. Furthermore, students in the aspect of helping each other from the indicator of the character of cooperation Junior High School 16 Muaro Jambi with a percentage of 46% in the very good category, Junior High School 18 Kerinci with a percentage of 75.5% in the good category, Valmiera Secondary School with a percentage of 79.1% in the good category, and Valmiera Viesturs secondary school percentage of 54% very good category.
Formation of Cu–Au porphyry deposits: hydraulic quartz veins, magmatic processes and constraints from chlorine

Abstract Copper–gold porphyry deposits are the world’s main source of copper and a significant source of gold. They consist of vein networks and their surrounding alteration zones. Commonly the deposits are centred on narrow intrusions (stocks), but calling these deposits ‘porphyries’ is unjustified because the name carries little descriptive or genetic value. Extensional veins were formed by hydraulic fracturing of the stocks, at depths where open spaces could not be maintained and where fluid pressure approaches lithostatic pressure. The post-crystallisation timing of the veins is important because it indicates that the host stocks could not have been the direct sources of either metals or ore-forming fluids. In the traditional magmatic model, precursor batholiths, lying at depth, are inferred to be the sources of the Cu and Au in the overlying host stocks. In this model, the batholiths are assumed to have crystallised and produced the mineralising aqueous fluids, Cu and Au. However, in many porphyry deposits, the concept of metal and fluid supply from deeper batholiths is problematic. Neither Cu nor Au is strongly enriched during the crystallisation of silicate magmas, and although hypersaline fluids are a characteristic of Cu–Au porphyry deposits globally, the source of the Cl remains unconstrained. There is little evidence that silicate magmas can release such Cl-rich fluids, and it remains unexplained how elevated levels of Cl may be achieved in a silicate magma. Therefore, the starting assumption that these deposits formed predominantly from magmatic sources and processes is questioned. This study has selectively focused on the roles of rheology, rock mechanics, vein control, metal-enrichment processes and the sources of Cl. Non-magmatic processes may be enough to facilitate strong partitioning of Cu and Au into high-temperature, oxidising, high-salinity, hydrothermal fluids to form Cu–Au porphyry deposits. KEY POINTS Mineralised quartz veins were introduced in fluids during hydraulic fracturing of their host intrusions when these stocks were brittle and had cooled significantly below their solidus temperatures. The porphyry intrusions hosting Cu–Au (copper–gold) mineralisation were not the direct sources of either the fluids or the metals. The sources of Cu and Au included large volumes of surrounding and underlying rocks up to kilometres from the sites of deposition. Cu and Au do not become strongly concentrated during crystal fractionation in evolving silicate magmas. Unaltered igneous rocks have relatively low Cl contents, and experiments suggest low Cl solubilities in granitic to granodioritic magmas. It is highly unlikely that all the Cl required for metal complexing and transport was available from within silicate magmas.
Improved Detection of Ice Accretion Status on Transmission Lines Using YOLOv5s

Ice accretion on transmission lines is one of the major hidden dangers to the safe operation of power systems. The current ice image monitoring system of power companies urgently needs to quickly and accurately detect the ice accretion status from massive real-time image data to assist in the smooth implementation of de-icing work. Based on the original dataset constructed with the help of Shanxi Power Company, this paper establishes a transmission line ice accretion image dataset through image screening, image enhancement, image sliding window segmentation, and image annotation. On the basis of the original YOLOv5s model, this paper proposes three improvements: 1. Designing a feature enhancement module based on atrous convolution to increase the receptive field and obtain more contextual information while preserving the texture details of the feature map. 2. This paper simplifies cross-scale connections and contextual information weighting operations in the feature pyramid to enhance the network's feature extraction capabilities. 3. Introducing Swin-Transformer network structure in the process of feature fusion, further enhancing the semantic information and global perception of small targets. It can be seen from the ablation experiment analysis that the mAP0.5:0.5 of the proposed algorithm has increased by 7.6% compared with the original YOLOv5s. At the same time, the performance comparison experiment validated that the detection accuracy of the proposed algorithm achieved better performance with little sacrifice in detection speed.
An Isolated Three-Way Power Combiner via Magnetically Coupled Microstrip Ring Probes

This research presents a Ka-band isolated three-way power combiner using a six-port $E$ -plane waveguide coupler (SEWC) and a magnetically coupled transition from the waveguide to the microstrip line. To achieve phase coherency, magnetic ring probes with different rotation directions are designed. The experimental results indicate an amplitude imbalance within the range of ±0.8 dB at frequencies between 30 and 40 GHz. The isolation exceeds 22 dB, and all return losses are better than 16.2 dB. When three GaN power amplifiers with output power ranging from 8 to 10 W are integrated, the active combiner generates radio frequency (RF) power up to 25.8 W within the 30 to 40 GHz band. This translates to an average combining efficiency of 88.6% and a power-added efficiency exceeding 14.7%.
Large surface charge accumulation in 2D MoS2/Sb2Te3 junction and its effect on junction properties: KPFM based study

In the present study, 2D-3D MoS2/Sb2Te3 (n-p) and MoS2/Bi2Te3 (n-n) heterojunctions with varying MoS2 thicknesses have been investigated using the Kelvin Probe Force Microscopy technique. Nanoscale maps of interface measurements based on the difference of surface potential (SP) maps in surface charge and back natural modes have been carried out. The 2D-3D heterojunctions with lower MoS2 thickness show a large difference in SP values in the two modes, which is observed to increase with a decrease in the MoS2 thickness. In comparison, samples with larger (bulk-like) MoS2 thickness show negligible SP differences, indicating complete Fermi level alignment, as expected in a normal bulk junction. The difference in the SP value in two modes represents large surface charge accumulation in the 2D layer due to a relatively high value of the depletion width required for achieving equilibrium in comparison to the atomic scale thickness of 2D MoS2. In limited earlier reports, the current-voltage behavior of metal—2D MoS2 junctions is explained on the basis of the Fermi level pinning effect, which is a very generic explanation given for bulk p-n heterojunctions and may not be applicable in 2D materials. The present study shows that surface charge accumulation has a large influence on the I-V characteristic of 2D junctions, and this may be a key factor influencing the physics of the 2D interface and their potential applications.