Miracle-dz/UniFAR-FTUs huggingface dataset:
[Dragon-tiger fighting needling therapy in treatment of painful diabetic peripheral neuropathy: a randomized controlled trial].

OBJECTIVE To compare the clinical therapeutic effect on painful diabetic peripheral neuropathy (PDPN) between dragon-tiger fighting needling and pregabalin capsules. METHODS A total of 60 patients with PDPN were randomized into an observation group and a control group, 30 cases in each one. On the base of treatment with routine anti-hyperglycaemic measures and nutritional neurotherapy, the dragon-tiger fighting needling was exerted at Sanyinjiao (SP 6), Zusanli (ST 36), Yinlingquan (SP 9) and Xuehai (SP 10) in the observation group, once daily. Pregabalin capsules were prescribed for oral administration in the control group, 75 mg, twice a day. The treatment for 2 weeks was as one course and 2 courses of treatment were required in total. The score of visual analogue scale (VAS), the score of MOS item short form health survey (SF-36) and nerve conduction velocity before and after treatment were compared between the two groups. The clinical therapeutic effect was evaluated in the two groups. RESULTS After treatment, VAS score was reduced as compared with before treatment in the two groups (P<0.05). The reducing range of VAS score in the observation group was larger than the control group (P<0.05). After treatment, the sensory nerve conduction velocity (SNCV) and motor nerve conduction velocity (MNCV) of median nerve and posterior tibial nerve were all improved as compared with before treatment in the two groups (P<0.05). SNCV and MNCV in the observation group were higher than the control group (P<0.05). After treatment, the score of each item in SF-36 was increased as compared with before treatment in the two groups (P<0.05) and the score of each item in SF-36 in the observation group was higher than the control group (P<0.05). The total effective rate was 86.7% (26/30) in the observation group, better than 60.0% (18/30) in the control group (P<0.05). CONCLUSION The dragon-tiger fighting needling therapy relieves painful symptoms, improves the quality of life and increases nerve conduction velocity in the patients with diabetic peripheral neuropathy, and the therapeutic effect is better than oral administration of pregabalin capsules.
Fundamental Studies of Rapidly Fabricated On-Chip Passive Micromixer for Modular Microfluidics

Micromixers play an important role in many modular microfluidics. Complex on-chip mixing units and smooth channel surfaces ablated by lasers on polymers are well-known problems for microfluidic chip fabricating techniques. However, little is known about the ablation of rugged surfaces on polymer chips for mixing uses. This paper provides the first report of an on-chip compact micromixer simply, easily and quickly fabricated using laser-ablated irregular microspheric surfaces on a polymethyl methacrylate (PMMA) microfluidic chip for continuous mixing uses in modular microfluidics. The straight line channel geometry is designed for sequential mixing of nanoliter fluids in about 1 s. The results verify that up to about 90% of fluids can be mixed in a channel only 500 µm long, 200 µm wide and 150 µm deep using the developed micromixer fabricating method under optimized conditions. The computational flow dynamics simulation and experimental result agree well with each other.
Identification of Multi-Class Drugs Based on Near Infrared Spectroscopy and Bidirectional Generative Adversarial Networks

Drug detection and identification technology are of great significance in drug supervision and management. To determine the exact source of drugs, it is often necessary to directly identify multiple varieties of drugs produced by multiple manufacturers. Near-infrared spectroscopy (NIR) combined with chemometrics is generally used in these cases. However, existing NIR classification modeling methods have great limitations in dealing with a large number of categories and spectra, especially under the premise of insufficient samples, unbalanced samples, and sensitive identification error cost. Therefore, this paper proposes a NIR multi-classification modeling method based on a modified Bidirectional Generative Adversarial Networks (Bi-GAN). It makes full utilization of the powerful feature extraction ability and good sample generation quality of Bi-GAN and uses the generated samples with obvious features, an equal number between classes, and a sufficient number within classes to replace the unbalanced and insufficient real samples in the courses of spectral classification. 1721 samples of four kinds of drugs produced by 29 manufacturers were used as experimental materials, and the results demonstrate that this method is superior to other comparative methods in drug NIR classification scenarios, and the optimal accuracy rate is even more than 99% under ideal conditions.
Reconstructing the social network of HIV key populations from locally observed information

ABSTRACT Traditional surveys only provide local observations about the topological structure of isolated individuals. This study aims to develop a novel data-driven approach to reconstructing the social network of men who have sex with men (MSM) communities from locally observed information by surveys. A large social network consisting of 1075 users and their public relationships was obtained manually from BlueD.com. We followed the same survey-taking procedure to sample locally observed information and adapted an Exponential Random Graph Model (ERGM) to model the full structure of the BlueD social network (number of local nodes N = 1075, observed average degree k = 6.46). The parameters were learned and then used to reconstruct the MSM social networks by two real-world survey datasets in Hong Kong (N = 600, k = 5.61) and Guangzhou (N = 757, k = 5). Our method performed well on reconstructing the BlueD social network, with a high accuracy (90.3%). In conclusion, this study demonstrates the feasibility of using parameters learning methods to reconstruct the social networks of HIV key populations. The method has the potential to inform data-driven intervention programs that need global social network structures.
Semantics-Aware Spatial-Temporal Binaries for Cross-Modal Video Retrieval

With the current exponential growth of video-based social networks, video retrieval using natural language is receiving ever-increasing attention. Most existing approaches tackle this task by extracting individual frame-level spatial features to represent the whole video, while ignoring visual pattern consistencies and intrinsic temporal relationships across different frames. Furthermore, the semantic correspondence between natural language queries and person-centric actions in videos has not been fully explored. To address these problems, we propose a novel binary representation learning framework, named Semantics-aware Spatial-temporal Binaries (<inline-formula> <tex-math notation="LaTeX">$\text{S}^{2}$ </tex-math></inline-formula>Bin), which simultaneously considers spatial-temporal context and semantic relationships for cross-modal video retrieval. By exploiting the semantic relationships between two modalities, <inline-formula> <tex-math notation="LaTeX">$\text{S}^{2}$ </tex-math></inline-formula>Bin can efficiently and effectively generate binary codes for both videos and texts. In addition, we adopt an iterative optimization scheme to learn deep encoding functions with attribute-guided stochastic training. We evaluate our model on three video datasets and the experimental results demonstrate that <inline-formula> <tex-math notation="LaTeX">$\text{S}^{2}$ </tex-math></inline-formula>Bin outperforms the state-of-the-art methods in terms of various cross-modal video retrieval tasks.
From Genetic Maps to QTL Cloning: An Overview for Durum Wheat

Durum wheat is one of the most important cultivated cereal crops, providing nutrients to humans and domestic animals. Durum breeding programs prioritize the improvement of its main agronomic traits; however, the majority of these traits involve complex characteristics with a quantitative inheritance (quantitative trait loci, QTL). This can be solved with the use of genetic maps, new molecular markers, phenotyping data of segregating populations, and increased accessibility to sequences from next-generation sequencing (NGS) technologies. This allows for high-density genetic maps to be developed for localizing candidate loci within a few Kb in a complex genome, such as durum wheat. Here, we review the identified QTL, fine mapping, and cloning of QTL or candidate genes involved in the main traits regarding the quality and biotic and abiotic stresses of durum wheat. The current knowledge on the used molecular markers, sequence data, and how they changed the development of genetic maps and the characterization of QTL is summarized. A deeper understanding of the trait architecture useful in accelerating durum wheat breeding programs is envisioned.
Double functions of porous TiO2 electrodes on CH3NH3PbI3 perovskite solar cells: Enhancement of perovskite crystal transformation and prohibition of short circuiting

In order to analyze the crystal transformation from hexagonal PbI2 to CH3NH3PbI3 by the sequential (two-step) deposition process, perovskite CH3NH3PbI3 layers were deposited on flat and/or porous TiO2 layers. Although the narrower pores using small nanoparticles prohibited the effective transformation, the porous-TiO2 matrix was able to help the crystal transformation of PbI2 to CH3NH3PbI3 by sequential two-step deposition. The resulting PbI2 crystals in porous TiO2 electrodes did not deteriorate the photovoltaic effects. Moreover, it is confirmed that the porous TiO2 electrode had served the function of prohibiting short circuits between working and counter electrodes in perovskite solar cells.
Third Generation Cephalosporin Resistant Enterobacterales Infections in Hospitalized Horses and Donkeys: A Case–Case–Control Analysis

In human medicine, infections caused by third-generation cephalosporin-resistant Enterobacterales (3GCRE) are associated with detrimental outcomes. In veterinary medicine, controlled epidemiological analyses are lacking. A matched case–case–control investigation (1:1:1 ratio) was conducted in a large veterinary hospital (2017–2019). In total, 29 infected horses and donkeys were matched to 29 animals with third-generation cephalosporin-susceptible Enterobacterales (3GCSE) infections, and 29 uninfected controls (overall n = 87). Despite multiple significant associations per bivariable analyses, the only independent predictor for 3GCRE infection was recent exposure to antibiotics (adjusted odds ratio (aOR) = 104, p < 0.001), but this was also an independent predictor for 3GCSE infection (aOR = 22, p < 0.001), though the correlation with 3GCRE was significantly stronger (aOR = 9.3, p = 0.04). In separated multivariable outcome models, 3GCRE infections were independently associated with reduced clinical cure rates (aOR = 6.84, p = 0.003) and with 90 days mortality (aOR = 3.6, p = 0.003). Klebsiella spp. were the most common 3GCRE (36%), and blaCTX-M-1 was the major β-lactamase (79%). Polyclonality and multiple sequence types were evident among all Enterobacterales (e.g., Klebsiella pneumoniae, Escherichia coli, Enterobacter cloacae). The study substantiates the significance of 3GCRE infections in equine medicine, and their independent detrimental impact on cure rates and mortality. Multiple Enterobacterales genera, subtypes, clones and mechanisms of resistance are prevalent among horses and donkeys with 3GCRE infections.
mmW Rotman Lens-Based Sensing: An Investigation Study

A Rotman lens is a wideband true-time delay device. Due to its simplistic structure with wave/signal routing capabilities, it has been widely utilized as a beamforming device in numerous communication systems. Since the basic Rotman lens design incorporates multiple input, output, and dummy ports, in this study, and for the first time, we utilized a Rotman lens as a sensor. The main idea was to gather abundant information from available Rotman lens ports to obtain better sensing performance. The realized lens is optimized to work in the millimeter wave (mmW) band from 27 to 29 GHz with a focus on a central frequency of 28 GHz. The design has a footprint of 140 × 103 × 0.8 mm3. The polarity correlator was used to characterize the material under investigation.
Structural and Material Determinants Influencing the Behavior of Porous Ti and Its Alloys Made by Additive Manufacturing Techniques for Biomedical Applications

One of the biggest challenges in tissue engineering is the manufacturing of porous structures that are customized in size and shape and that mimic natural bone structure. Additive manufacturing is known as a sufficient method to produce 3D porous structures used as bone substitutes in large segmental bone defects. The literature indicates that the mechanical and biological properties of scaffolds highly depend on geometrical features of structure (pore size, pore shape, porosity), surface morphology, and chemistry. The objective of this review is to present the latest advances and trends in the development of titanium scaffolds concerning the relationships between applied materials, manufacturing methods, and interior architecture determined by porosity, pore shape, and size, and the mechanical, biological, chemical, and physical properties. Such a review is assumed to show the real achievements and, on the other side, shortages in so far research.
Smartphones and the Neuroscience of Mental Health.

Improvements in understanding the neurobiological basis of mental illness have unfortunately not translated into major advances in treatment. At this point, it is clear that psychiatric disorders are exceedingly complex and that, in order to account for and leverage this complexity, we need to collect longitudinal datasets from much larger and more diverse samples than is practical using traditional methods. We discuss how smartphone-based research methods have the potential to dramatically advance our understanding of the neuroscience of mental health. This, we expect, will take the form of complementing lab-based hard neuroscience research with dense sampling of cognitive tests, clinical questionnaires, passive data from smartphone sensors, and experience-sampling data as people go about their daily lives. Theory- and data-driven approaches can help make sense of these rich data sets, and the combination of computational tools and the big data that smartphones make possible has great potential value for researchers wishing to understand how aspects of brain function give rise to, or emerge from, states of mental health and illness. Expected final online publication date for the Annual Review of Neuroscience, Volume 44 is July 2021. Please see http://www.annualreviews. org/page/journal/pubdates for revised estimates.
How do labels using lower strength verbal descriptors, %ABV, or their combination impact wine consumption? A bar laboratory adaptive randomised controlled trial.

BACKGROUND AND AIM A previous research study concluded that wine and beer labelled as lower in strength increase consumption compared with the same drinks labelled as regular strength. The label included both a verbal and numerical descriptor of strength. The present study aimed to estimate the effect of each of these label components. DESIGN Adaptive, parallel group randomised controlled trial, comprising an internal pilot sample (N1 = 90) and a confirmatory sample (N2 = 57). SETTING University bar laboratory in London UK. PARTICIPANTS One-hundred and forty-seven weekly wine drinkers were sampled from a nationally representative English panel. INTERVENTION Participants were randomised to one of three groups to taste test wine in a bar-laboratory, varying only in the label displayed: (i) verbal descriptor only (Super Low); (ii) numerical descriptor only (4%ABV); and (iii) verbal descriptor and numerical descriptor combined (Super Low 4%ABV) [each group n = 49]. MEASUREMENTS The primary outcome was total volume (ml) of wine consumed. FINDINGS Participants randomised to the numerical descriptor label group (4%ABV: M = 155.12ml, B = 20.30, 95% CI = 3.92, 36.69, p-value = 0.016) and combined verbal and numerical descriptor label group (Super Low 4%ABV: M = 154.59ml, B = 20.68, 95%CI = 4.32, 37.04, p-value = 0.014) drank significantly greater amounts than those randomised to the verbal descriptor label group (Super Low: M = 125.65ml). CONCLUSIONS This bar laboratory study estimated that a greater quantity of 'lower' strength wine was consumed when the label included a numerical strength descriptor compared with a verbal only strength descriptor.
Structural Characterization of Daunomycin-Peptide Conjugates by Various Tandem Mass Spectrometric Techniques

The use of peptide-drug conjugates has generated wide interest as targeted antitumor therapeutics. The anthracycline antibiotic, daunomycin, is a widely used anticancer agent and it is often conjugated to different tumor homing peptides. However, comprehensive analytical characterization of these conjugates via tandem mass spectrometry (MS/MS) is challenging due to the lability of the O-glycosidic bond and the appearance of MS/MS fragment ions with little structural information. Therefore, we aimed to investigate the optimal fragmentation conditions that suppress the prevalent dissociation of the anthracycline drug and provide good sequence coverage. In this study, we comprehensively compared the performance of common fragmentation techniques, such as higher energy collisional dissociation (HCD), electron transfer dissociation (ETD), electron-transfer higher energy collisional dissociation (EThcD) and matrix-assisted laser desorption/ionization–tandem time-of-flight (MALDI-TOF/TOF) activation methods for the structural identification of synthetic daunomycin-peptide conjugates by high-resolution tandem mass spectrometry. Our results showed that peptide backbone fragmentation was inhibited by applying electron-based dissociation methods to conjugates, most possibly due to the “electron predator” effect of the daunomycin. We found that efficient HCD fragmentation was largely influenced by several factors, such as amino acid sequences, charge states and HCD energy. High energy HCD and MALDI-TOF/TOF combined with collision induced dissociation (CID) mode are the methods of choice to unambiguously assign the sequence, localize different conjugation sites and differentiate conjugate isomers.
Is It Time To Kill the Survival Curve? A Case for Disease Progression Factors in Microbial Pathogenesis and Host Defense Research

The molecular mechanisms of microbial virulence and host defense are most often studied using animal models and Koch’s molecular postulates. A common rationale for these types of experiments is to identify therapeutic targets based on the assumption that microbial or host factors that confer extreme animal model survival phenotypes represent critical virulence and host defense factors. ABSTRACT The molecular mechanisms of microbial virulence and host defense are most often studied using animal models and Koch’s molecular postulates. A common rationale for these types of experiments is to identify therapeutic targets based on the assumption that microbial or host factors that confer extreme animal model survival phenotypes represent critical virulence and host defense factors. Yet null mutant strains of microbial (or host) factors often yield extreme survival curve phenotypes because they fail to establish an infection. The lack of infection and disease establishment prevents true assessment of the given factor’s role(s) in disease progression. Here, we posit that the emphasis on extreme survival curve phenotypes in fungal infectious disease models is leading to missed opportunities to identify new fungal and host factors critical for disease progression. We simply do not yet have a sufficient understanding of fungal virulence and host defense mechanisms throughout the temporal course of an infection. We propose that there is a need to develop new approaches and to revisit tried and true methods to define infection site biology beyond the analysis of survival curve phenotypes. To stimulate these new approaches, we propose the (new) terms “disease initiation factor” and “disease progression factor” to distinguish functional roles at distinct temporal stages of an infection and give us targets to foster new discoveries.
Nigellothionins from Black Cumin (Nigella sativa L.) Seeds Demonstrate Strong Antifungal and Cytotoxic Activity

High-cationic biologically active peptides of the thionins family were isolated from black cumin (Nigella sativa L.) seeds. According to their physicochemical characteristics, they were classified as representatives of the class I thionin subfamily. Novel peptides were called “Nigellothionins”, so-called because of their source plant. Thionins are described as components of plant innate immunity to environmental stress factors. Nine nigellothionins were identified in the plant in different amounts. Complete amino acid sequences were determined for three of them, and a high degree of similarity was detected. Three nigellothionins were examined for antifungal properties against collection strains. The dominant peptide, NsW2, was also examined for activity against clinical isolates of fungi. Cytotoxic activity was determined for NsW2. Nigellothionins activity against all collection strains and clinical isolates varied from absence to a value comparable to amphotericin B, which can be explained by the presence of amino acid substitutions in their sequences. Cytotoxic activity in vitro for NsW2 was detected at sub-micromolar concentrations. This has allowed us to propose an alteration of the molecular mechanism of action at different concentrations. The results obtained suggest that nigellothionins are natural compounds that can be used as antimycotic and anti-proliferative agents.
Predictors of Depression and Anxiety Among Senior High School Students During COVID-19 Pandemic: The Context of Home Quarantine and Online Education

This study aimed to examine the prevalence and predictors of depression and anxiety among senior high school students in Jordan during the COVID-19 pandemic. The study used an anonymous online survey that targeted senior high school students in Jordan. Almost two thirds of students reported depressive symptoms and anxiety. Father’s level of education, mothers’ level of education, perceived difficulties in online education, gender, and age were significant predictors of depression, while father’s level of education, difficulties in online education, gender, and age were significant predictors of anxiety (p < .05). Among those identified as having depression, 30.7% were male and 50.7% were female. The prevalence of anxiety among students was high, and the prevalence of anxiety in females (46.9%) is greater than males (27.6%). School health nurses and mental health counselors at schools need to emphasize the mental health and psychosocial support needs for senior high school students.