Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Different Filler Wires on Mechanical Property and Conductivity of Aluminum-Copper Joints

The 1060 aluminum and T2 copper were joined by the pulsed double electrode gas metal arc welding (DE-GMAW) brazing method by using four types of filler wires, namely pure aluminum (Al) ER1100, aluminum-magnesium (Al–Mg) ER5356, aluminum-silicon (Al–Si) ER4043, and Al–Si ER4047, respectively. The effects of different types of filler wires on intermetallic compounds, microhardness tensile strength, and conductivity of joints were investigated. The results showed that a lot of brittle intermetallic compounds laying in the copper side brazing interface zone were generated using pure Al, Al–Mg, and Al–Si filler wires, which caused the change of microhardness, tensile strength, and the conductivity of joints. Meanwhile, with the increase in Si elements contents for Al–Sifiller wires, the thickness of the intermetallic compound layers decreased obviously, which was only up to 3 µm and the conductivity of the joints decreased. In addition, the microhardness, tensile strength, and the conductivity of the joints, when using Al–Sifiller wires, was higher than that using pure Al and Al–Mg filler wires. Hence, in comparison to the pure filler wires and Al–Mg filler wires, the Al–Si filler wires were more suitable for Al–Cu joints by DE-GMAW as Si element content was lower.
Optimization and a Kinetic Study on the Acidic Hydrolysis of Dialkyl α-Hydroxybenzylphosphonates

The two-step acidic hydrolysis of α-hydroxybenzylphosphonates and a few related derivatives was monitored in order to determine the kinetics and to map the reactivity of the differently substituted phosphonates in hydrolysis. Electron-withdrawing substituents increased the rate, while electron-releasing ones slowed down the reaction. Both hydrolysis steps were characterized by pseudo-first-order rate constants. The fission of the second P-O-C bond was found to be the rate-determining step.
Estradiol Induces Epithelial to Mesenchymal Transition of Human Glioblastoma Cells

The mesenchymal phenotype of glioblastoma multiforme (GBM), the most frequent and malignant brain tumor, is associated with the worst prognosis. The epithelial–mesenchymal transition (EMT) is a cell plasticity mechanism involved in GBM malignancy. In this study, we determined 17β-estradiol (E2)-induced EMT by changes in cell morphology, expression of EMT markers, and cell migration and invasion assays in human GBM-derived cell lines. E2 (10 nM) modified the shape and size of GBM cells due to a reorganization of actin filaments. We evaluated EMT markers expression by RT-qPCR, Western blot, and immunofluorescence.We found that E2 upregulated the expression of the mesenchymal markers, vimentin, and N-cadherin. Scratch and transwell assays showed that E2 increased migration and invasion of GBM cells. The estrogen receptor-α (ER-α)-selective agonist 4,4’,4’’-(4-propyl-[1H]-pyrazole-1,3,5-triyl)trisphenol (PPT, 10 nM) affected similarly to E2 in terms of the expression of EMT markers and cell migration, and the treatment with the ER-α antagonist methyl-piperidino-pyrazole (MPP, 1 μM) blocked E2 and PPT effects. ER-β-selective agonist diarylpropionitrile (DNP, 10 nM) and antagonist 4-[2-phenyl-5,7-bis(trifluoromethyl)pyrazole[1,5-a]pyrimidin-3-yl]phenol (PHTPP, 1 μM) showed no effects on EMT marker expression. These data suggest that E2 induces EMT activation through ER-α in human GBM-derived cells.
Is There Scope for a Novel Mycelium Category of Proteins alongside Animals and Plants?

In the 21st century, we face a troubling trilemma of expanding populations, planetary and public wellbeing. Given this, shifts from animal to plant food protein are gaining momentum and are an important part of reducing carbon emissions and consumptive water use. However, as this fast-pace of change sets in and begins to firmly embed itself within food-based dietary guidelines (FBDG) and food policies we must raise an important question—is now an opportunistic time to include other novel, nutritious and sustainable proteins within FBGD? The current paper describes how food proteins are typically categorised within FBDG and discusses how these could further evolve. Presently, food proteins tend to fall under the umbrella of being ‘animal-derived’ or ‘plant-based’ whilst other valuable proteins i.e., fungal-derived appear to be comparatively overlooked. A PubMed search of systematic reviews and meta-analytical studies published over the last 5 years shows an established body of evidence for animal-derived proteins (although some findings were less favourable), plant-based proteins and an expanding body of science for mycelium/fungal-derived proteins. Given this, along with elevated demands for alternative proteins there appears to be scope to introduce a ‘third’ protein category when compiling FBDG. This could fall under the potential heading of ‘fungal’ protein, with scope to include mycelium such as mycoprotein within this, for which the evidence-base is accruing.
Near-Linear Responsive and Wide-Range Pressure and Stretch Sensor Based on Hierarchical Graphene-Based Structures via Solvent-Free Preparation

Flexible and wearable electronics have huge potential applications in human motion detection, human–computer interaction, and context identification, which have promoted the rapid development of flexible sensors. So far the sensor manufacturing techniques are complex and require a large number of organic solvents, which are harmful not only to human health but also to the environment. Here, we propose a facile solvent-free preparation toward a flexible pressure and stretch sensor based on a hierarchical layer of graphene nanoplates. The resulting sensor exhibits many merits, including near-linear response, low strain detection limits to 0.1%, large strain gauge factor up to 36.2, and excellent cyclic stability withstanding more than 1000 cycles. Besides, the sensor has an extraordinary pressure range as large as 700 kPa. Compared to most of the reported graphene-based sensors, this work uses a completely environmental-friendly method that does not contain any organic solvents. Moreover, the sensor can practically realize the delicate detection of human body activity, speech recognition, and handwriting recognition, demonstrating a huge potential for wearable sensors.
ZnO Nanoparticle/Graphene Hybrid Photodetectors via Laser Fragmentation in Liquid

By combining the enhanced photosensitive properties of zinc oxide nanoparticles and the excellent transport characteristics of graphene, UV-sensitive, solar-blind hybrid optoelectronic devices have been demonstrated. These hybrid devices offer high responsivity and gain, making them well suited for photodetector applications. Here, we report a hybrid ZnO nanoparticle/graphene phototransistor that exhibits a responsivity up to 4 × 104 AW−1 and gain of up to 1.3 × 105 with high UV wavelength selectivity. ZnO nanoparticles were synthesized by pulsed laser fragmentation in liquid to attain a simple, efficient, ligand-free method for nanoparticle fabrication. By combining simple fabrication processes with a promising device architecture, highly sensitive ZnO nanoparticle/graphene UV photodetectors were successfully demonstrated.
Verification of Saliva Matrix Metalloproteinase-1 as a Strong Diagnostic Marker of Oral Cavity Cancer

Oral squamous cell carcinoma (OSCC) accounts for >90% of cases of oral cancer, including cancer at the lip and oral cavity and cancer at the oropharynx. Most OSCCs develop from oral potentially malignant disorders (OPMDs), which consist of heterogeneous lesions with different malignant transformation potentials that make early detection of OSCC a challenge. Using a targeted mass spectrometry-based assay to compare multiple candidate proteins, we previously identified matrix metalloproteinase-1 (MMP-1) as one of the most promising salivary OSCC biomarkers. To explore the clinical utility of MMP-1 in OSCC detection, we developed an in-house, sensitive enzyme-linked immunosorbent assay (ELISA) for measuring MMP-1 content, and tested it on saliva samples from 1160 subjects (313 healthy controls, and 578 OPMD and 269 OSCC patients) collected at two medical centers. Salivary MMP-1 levels measured by our in-house ELISA significantly discriminated OSCC patients from non-cancerous groups. A receiver operating characteristic curve analysis showed that MMP-1 was effective in separating non-cancer groups from patients with OSCCs at the oral cavity. Additionally, salivary MMP-1 levels in oral cavity cancer patients were highly correlated with tumor progression (tumor size, lymph node metastasis, and overall stage). Collectively, our results indicate that salivary MMP-1 is an effective biomarker for OSCC that can be sensitively detected using our newly developed ELISA. The newly developed MMP-1 ELISA may be used as a new adjunctive tool to aid in detecting and monitoring OSCC.
Caveolin-1-Mediated Tumor Suppression Is Linked to Reduced HIF1α S-Nitrosylation and Transcriptional Activity in Hypoxia

Caveolin-1 (CAV1) is a well-established nitric oxide synthase inhibitor, whose function as a tumor suppressor is favored by, but not entirely dependent on, the presence of E-cadherin. Tumors are frequently hypoxic and the activation of the hypoxia-inducible factor-1α (HIF1α) promotes tumor growth. HIF1α is regulated by several post-translational modifications, including S-nitrosylation. Here, we evaluate the mechanisms underlying tumor suppression by CAV1 in cancer cells lacking E-cadherin in hypoxia. Our main findings are that CAV1 reduced HIF activity and Vascular Endothelial Growth Factor expression in vitro and in vivo. This effect was neither due to reduced HIF1α protein stability or reduced nuclear translocation. Instead, HIF1α S-nitrosylation observed in hypoxia was diminished by the presence of CAV1, and nitric oxide synthase (NOS) inhibition by Nω-Nitro-L-arginine methyl ester hydrochloride (L-NAME) reduced HIF1α transcriptional activity in cells to the same extent as observed upon CAV1 expression. Additionally, arginase inhibition by (S)-(2-Boronoethyl)-L-cysteine (BEC) partially rescued cells from the CAV1-mediated suppression of HIF1α transcriptional activity. In vivo, CAV1-mediated tumor suppression was dependent on NOS activity. In summary, CAV1-dependent tumor suppression in the absence of E-cadherin is linked to reduced HIF1α transcriptional activity via diminished NOS-mediated HIF1α S-nitrosylation.
High Sensitivity Microfiber Interferometer Sensor in Aqueous Solution

The need for environmental protection and water pollution control has led to the development of different sensors for determining many kinds of pollutants in water. Ammonia nitrogen presence is an important indicator of water quality in environmental monitoring applications. In this paper, a high sensitivity sensor for monitoring ammonia nitrogen concentration in water using a tapered microfiber interferometer (MFI) as a sensor platform and a broad supercontinuum laser as the light source is realized. The MFI is fabricated to the waist diameter of 8 µm producing a strong interference pattern due to the coupling of the fundamental mode with the cladding mode. The MFI sensor is investigated for a low concentration of ammonia nitrogen in water in the wide wavelength range from 1500–1800 nm with a high-power signal provided by the supercontinuum source. The broad source allows optical sensing characteristics of the MFI to be evaluated at four different wavelengths (1505, 1605, 1705, and 1785 nm) upon exposure towards various ammonia nitrogen concentrations. The highest sensitivity of 0.099 nm/ppm that indicates the wavelength shift is observed at 1785 nm operating wavelength. The response is linear in the ammonia nitrogen range of 5–30 ppm with the best measurement resolution calculated to be 0.5 ppm. The low concentration ammonia nitrogen detected by the MFI in the unique infrared region reveals the potential application of this optical fiber-based sensor for rivers and drinking water monitoring.
Oxidative Stress, Telomere Shortening, and Apoptosis Associated to Sarcopenia and Frailty in Patients with Multimorbidity

Background: The presence of oxidative stress, telomere shortening, and apoptosis in polypathological patients (PP) with sarcopenia and frailty remains unknown. Methods: Multicentric prospective observational study in order to assess oxidative stress markers (catalase, glutathione reductase (GR), total antioxidant capacity to reactive oxygen species (TAC-ROS), and superoxide dismutase (SOD)), absolute telomere length (aTL), and apoptosis (DNA fragmentation) in peripheral blood samples of a hospital-based population of PP. Associations of these biomarkers to sarcopenia, frailty, functional status, and 12-month mortality were analyzed. Results: Of the 444 recruited patients, 97 (21.8%), 278 (62.6%), and 80 (18%) were sarcopenic, frail, or both, respectively. Oxidative stress markers (lower TAC-ROS and higher SOD) were significantly enhanced and aTL significantly shortened in patients with sarcopenia, frailty or both syndromes. No evidence of apoptosis was detected in blood leukocytes of any of the patients. Both oxidative stress markers (GR, p = 0.04) and telomere shortening (p = 0.001) were associated to death risk and to less survival days. Conclusions: Oxidative stress markers and telomere length were enhanced and shortened, respectively, in blood samples of polypathological patients with sarcopenia and/or frailty. Both were associated to decreased survival. They could be useful in the clinical practice to assess vulnerable populations with multimorbidity and of potential interest as therapeutic targets.
Label-Free Electrochemical Biosensors for the Determination of Flaviviruses: Dengue, Zika, and Japanese Encephalitis

A highly effective way to improve prognosis of viral infectious diseases and to determine the outcome of infection is early, fast, simple, and efficient diagnosis of viral pathogens in biological fluids. Among a wide range of viral pathogens, Flaviviruses attract a special attention. Flavivirus genus includes more than 70 viruses, the most familiar being dengue virus (DENV), Zika virus (ZIKV), and Japanese encephalitis virus (JEV). Haemorrhagic and encephalitis diseases are the most common severe consequences of flaviviral infection. Currently, increasing attention is being paid to the development of electrochemical immunological methods for the determination of Flaviviruses. This review critically compares and evaluates recent research progress in electrochemical biosensing of DENV, ZIKV, and JEV without labelling. Specific attention is paid to comparison of detection strategies, electrode materials, and analytical characteristics. The potential of so far developed biosensors is discussed together with an outlook for further development in this field.
Evaluation of Hyperparameter Optimization in Machine and Deep Learning Methods for Decoding Imagined Speech EEG

Classification of electroencephalography (EEG) signals corresponding to imagined speech production is important for the development of a direct-speech brain–computer interface (DS-BCI). Deep learning (DL) has been utilized with great success across several domains. However, it remains an open question whether DL methods provide significant advances over traditional machine learning (ML) approaches for classification of imagined speech. Furthermore, hyperparameter (HP) optimization has been neglected in DL-EEG studies, resulting in the significance of its effects remaining uncertain. In this study, we aim to improve classification of imagined speech EEG by employing DL methods while also statistically evaluating the impact of HP optimization on classifier performance. We trained three distinct convolutional neural networks (CNN) on imagined speech EEG using a nested cross-validation approach to HP optimization. Each of the CNNs evaluated was designed specifically for EEG decoding. An imagined speech EEG dataset consisting of both words and vowels facilitated training on both sets independently. CNN results were compared with three benchmark ML methods: Support Vector Machine, Random Forest and regularized Linear Discriminant Analysis. Intra- and inter-subject methods of HP optimization were tested and the effects of HPs statistically analyzed. Accuracies obtained by the CNNs were significantly greater than the benchmark methods when trained on both datasets (words: 24.97%, p < 1 × 10–7, chance: 16.67%; vowels: 30.00%, p < 1 × 10–7, chance: 20%). The effects of varying HP values, and interactions between HPs and the CNNs were both statistically significant. The results of HP optimization demonstrate how critical it is for training CNNs to decode imagined speech.
Can Active Aerobic Exercise Reduce the Risk of Cardiovascular Disease in Prehypertensive Elderly Women by Improving HDL Cholesterol and Inflammatory Markers?

This study aims to verify the efficacy of exercise programs designed to prevent and treat hypertension-induced cardiovascular disease (CVD) by analyzing the effects of a 6-month active aerobic exercise program, administered to prehypertensive elderly women, on reducing the risk of developing CVD by enhancing their physical fitness level and improving the detailed markers of high-density lipoprotein cholesterol (HDL-C) and inflammatory markers. We assigned the elderly women (≥65 years) recruited into normal blood pressure (120–129/80–84; NBP, n = 18) and high-normal blood pressure (130–139/85–89; HNBP, n = 12) groups according to the European guidelines for the management of arterial hypertension. The exercise program was made up of combined workouts of elastic band resistance exercise and aerobics with dance music. The program took place three times a week for six months, with each session lasting 60 min. We measured pre- and post-intervention body composition, blood pressure, physical fitness level, blood lipids profile, HDL-C, SAA, TNF-α, IL-6, IL-4, IL-15, CRP, and HSP70 and calculated the Framingham risk scores for comparison. A significant post-intervention reduction in the mean systolic blood pressure (SBP) was observed in the HNBP group (p < 0.001), with significant increase in HDL-C (p < 0.01) and significant decrease in serum amyloid A (SAA) concentration (p < 0.01). A significant improvement in physical fitness factors such as physical efficiency index (PEI) was also observed in the HNBP group (p < 0.05). The post-intervention TNF-α, IL-6, and SAA concentrations were more significantly lower in the HNBP than in the NBP group (p < 0.05). Compared to the baseline values, a significant decrease in SAA concentration (p < 0.01) and significant increase in HSP70 concentration (p < 0.001) were observed in the HNBP group. The HNBP group’s 10-year CVD risk was also significantly reduced (p < 0.05). The pre–post differences in SBP and DBP were significantly correlated with those in the anti-inflammatory markers IL-4 and IL-15 (p < 0.01). In conclusion, the 6-month active aerobic exercise program of moderate intensity administered to prehypertensive elderly women (≥65 years) had the effect of reducing the 10-year CVD risk through a substantial reduction in SBP, overall physical fitness improvement, increase in HDL-C, decrease in SAA concentration, and substantial decrease in inflammatory biomarkers. It was also confirmed that an increase in anti-inflammatory markers, which showed a small range of increase with respect to the decrease in blood pressure, may have a major effect.
Plasmodium falciparum Knockout for the GPCR-Like PfSR25 Receptor Displays Greater Susceptibility to 1,2,3-Triazole Compounds That Block Malaria Parasite Development

The search for new compounds with antimalarial activity is urgent, as resistance to ones in the classical drug, has already been described in more than one continent. Compounds derived from 1,2,3-triazoles are effective against parasites and bacteria. Here, we evaluated the potential antimalarial activity against the human malaria parasite Plasmodium falciparum in a culture of fifty-four triazole compounds derived from 1H-and 2H-1,2,3-triazole. We identified thirty-one compounds with potential antimalarial activity at concentrations in the micromolar order (µM) and IC50 values ranging from 2.80 µM (9) to 29.27 µM (21). Then, we selected some of these compounds to perform the same tests on the PfSR25- strain (knockout for P. falciparum G-protein coupled receptor-like, SR25). Our experiences with the PfSR25- strain showed that both compounds with higher antimalarial activity for the 3D7 strain and those with less activity resulted in lower IC50 values for the knockout strain. The cytotoxicity of the compounds was evaluated in human renal embryonic cells (HEK 293), using MTT assays. This demonstrated that the compounds with the highest activity (9, 13, 19, 22, 24, 29), showed no toxicity at the tested concentrations.
Genome-Wide Association Mapping for Stripe Rust Resistance in Pakistani Spring Wheat Genotypes

Stripe rust caused by the pathogen Puccinia striiformis f. sp. tritici (Pst) is a major threat for wheat, resulting in low yield and grain quality loss in many countries. Genetic resistance is a prevalent method to combat the disease. Mapping the resistant loci and their association with traits is highly exploited in this era. A panel of 465 Pakistani spring wheat genotypes were evaluated for their phenotypic response to stripe rust at the seedling and adult plant stages. A total of 765 single nucleotide polymorphism (SNP) markers were applied on 465 wheat genotypes to evaluate their stripe rust response against nine races during the seedling test and in three locations for the field test. Currently, twenty SNPs dispersed on twelve chromosomal regions (1A, 1B, 1D, 2A, 2B, 4A, 4B, 5B, 6A, 6B, 6D and 7B) have been identified that were associated with rust race-specific resistance at the seedling stage. Thirty SNPs dispersed on eighteen chromosomal regions (1A, 1B, 1D, 2A, 2B, 2D, 3A, 3B, 3D, 4B, 5A, 5B, 6A, 6B, 6D, 7A, 7B and 7D) are associated with adult plant resistance. SNP loci IWB3662 was linked with all three Pakistani races, and likewise IWA2344 and IWA4096 were found to be linked with three different USA races. The present research findings can be applied by wheat breeders to increase their resistant capability and yield potential of their cultivars, through marker-assisted selection.
Using Deep Learning with Convolutional Neural Network Approach to Identify the Invasion Depth of Endometrial Cancer in Myometrium Using MR Images: A Pilot Study

Myometrial invasion affects the prognosis of endometrial cancer. However, discrepancies exist between pre-operative magnetic resonance imaging staging and post-operative pathological staging. This study aims to validate the accuracy of artificial intelligence (AI) for detecting the depth of myometrial invasion using a deep learning technique on magnetic resonance images. We obtained 4896 contrast-enhanced T1-weighted images (T1w) and T2-weighted images (T2w) from 72 patients who were diagnosed with surgico-pathological stage I endometrial carcinoma. We used the images from 24 patients (33.3%) to train the AI. The images from the remaining 48 patients (66.7%) were used to evaluate the accuracy of the model. The AI then interpreted each of the cases and sorted them into stage IA or IB. Compared with the accuracy rate of radiologists’ diagnoses (77.8%), the accuracy rate of AI interpretation in contrast-enhanced T1w was higher (79.2%), whereas that in T2w was lower (70.8%). The diagnostic accuracy was not significantly different between radiologists and AI for both T1w and T2w. However, AI was more likely to provide incorrect interpretations in patients with coexisting benign leiomyomas or polypoid tumors. Currently, the ability of this AI technology to make an accurate diagnosis has limitations. However, in hospitals with limited resources, AI may be able to assist in reading magnetic resonance images. We believe that AI has the potential to assist radiologists or serve as a reasonable alternative for pre-operative evaluation of the myometrial invasion depth of stage I endometrial cancers.