Miracle-dz/UniFAR-FTUs huggingface dataset:
Metabolomics approach to study in vivo toxicity of graphene oxide nanosheets

Although graphene oxide (GO) nanosheets are widely used in different fields, the mechanism of their toxicity remains relatively unknown. NMR‐based metabolomics was used to study in vivo time and dose‐dependent toxicity of GO nanosheets in mice. Sixty serum samples from mice in four different time intervals including 24 and 72 h and 7 and 21 days after injection of 0‐, 1‐, and 10‐mg/kg b.w. were analyzed based on 1HNMR spectra of each sample and multivariate methods. In comparison with the control group, 12 changed metabolites were identified in GO nanosheet‐treated mice groups. These metabolites are involved in steroid hormone biosynthesis and steroid biosynthesis pathways. It was seen that the time factor is more important than the dose factor and the groups were separated in a time direction, completely. We found that GO nanosheets has toxicity and can affect steroidal hormones. However, this study shows that after 21 days, the treated groups regardless of their GO nanosheet dose are very close to the control group. This means that in one step exposure to GO nanosheets, their toxicity diminished after 21 days.
Globalization mitigates the risk of conflict caused by strategic territory

Significance In an era where global trade is under pressure, it is heatedly debated whether a more integrated, globalized world is fueling or appeasing conflicts. Past studies have focused on how trade links impact interstate wars, but the effects of globalization on domestic conflict have been severely understudied. Our dataset of the strategic importance of each point of the globe allows us to shed light on this controversy. This algorithm-based measure is constructed by using exclusively natural terrain features, thereby avoiding common methodological pitfalls confounding results. We find that while strategic locations may often be the object of armed competition, periods of international trade booms increase the incentives to protect trade routes and attenuate the conflict risk at strategically important locations. Globalization is routinely blamed for various ills, including fueling conflict in strategic locations. To investigate whether these accusations are well founded, we have built a database to assess any given location’s strategic importance. Consistent with our game-theoretic model of strategic interaction, we find that overall fighting is more frequent in strategic locations close to maritime choke points (e.g., straits or capes), but that booming world trade openness considerably reduces the risks of conflict erupting in such strategic locations. The impact is quantitatively sizable, as moving one SD (1,100 km) closer to a choke point increases the conflict likelihood by 25% of the baseline risk in periods of low globalization, while reducing it during world trade booms. Our results have important policy implications for supranational coordination.
The Si-Ge substitutional series in the chiral STW Zeolite Structure Type

The whole compositional range (Gef = Ge/(Ge + Si) = 0 to 1) of zeolite STW has been synthesized and studied by a comprehensive combined experimental–theoretical approach. The yield of the zeolite goes through a maximum and then drops at the GeO2 side of the series, following the inverse of the calculated free energy curve. The unit cell generally expands, roughly linearly, as the Gef increases, but a notable resilience to expansion is observed at the high silica side. This can be attributed to the more rigid character of SiO2 and the ability of Ge units to deform. Density functional theory calculations provide a new assignment of the previously controversial 19F MAS NMR resonances for occluded fluoride, which is based not only on the number of Ge atoms in the double-4-ring units but also on the way they are associated (namely, no Ge, isolated Ge, Ge pairs or closed Ge clusters). While we found an overall good agreement between the experimental and theoretical trends in preferential occupation of different crystallographic sites by Ge, the theoretical models show more sharp and abrupt tendencies, likely due both to limitations of the approach and to kinetic factors that allow metastable configurations to actually exist.
Complete Genome Sequence of Escherichia Phage 590B, Active against an Extensively Drug-Resistant Uropathogenic Escherichia coli Isolate

Escherichia phage 590B, which was isolated from community sewage water in Chandigarh, India, exhibited lytic activity against an extensively drug-resistant uropathogenic Escherichia coli isolate. The genome of the phage is linear, double-stranded, and 44.39 kb long. Phage 590B is a member of the Siphoviridae family and is closest to phage vB_EcoS_XY2, which was isolated in China. ABSTRACT Escherichia phage 590B, which was isolated from community sewage water in Chandigarh, India, exhibited lytic activity against an extensively drug-resistant uropathogenic Escherichia coli isolate. The genome of the phage is linear, double stranded, and 44.39 kb long. Phage 590B is a member of the Siphoviridae family and is closest to phage vB_EcoS_XY2, which was isolated in China.
CAR T-cell therapy for secondary CNS DLBCL

Abstract Management of secondary central nervous system (SCNS) involvement in relapsed or refractory aggressive B-cell lymphomas remains an area of unmet medical need. We report a single-center retrospective analysis of 7 adult patients with SCNS lymphoma (SCNSL) who underwent chimeric antigen receptor (CAR) T-cell therapy for their refractory disease, and we describe the safety of whole brain radiation therapy (WBRT) as a bridging therapy. Six patients (85.7%) achieved a complete response at day 28, and 1 patient had progressive disease. The median progression-free survival was 83 days (range, 28-219 days), and median overall survival was 129 days (range, 32-219 days). Three patients died as a result of disease progression. Of the 5 patients who received WBRT as bridging therapy, 3 had no immune effector cell–associated neurotoxicity syndrome (ICANS), but 2 patients had grade 1 or grade 3 ICANS. No grade 4 ICANS was reported in this subset of patients. We conclude that SCNSL should not preclude patients from receiving CAR T-cell therapy as a treatment option because of concerns regarding ICANS, and bridging with WBRT is not associated with increased ICANS.
Hydrogel plus growth factors treatment after 2940nm erbium:YAG lattice laser improves periorbital wrinkles and wound healing: a case report

Skin aging is an inevitable physiological process and periorbital wrinkling is an active sign of the process. Laser therapy is an effective method for improving periorbital wrinkles and wound care after laser therapy can accelerate the wound healing process. This case report describes a typical case of a 47-year-old male that presented with a 10-year history of gradually-worsening bilateral periorbital wrinkles. These were treated using a 2940 nm erbium (Er):YAG lattice laser combined with recombinant bovine basic fibroblast growth factor (bFGF) gel and hydrogel (HG) treatment on the left side of his face compared with laser therapy and bFGF gel on the right side of his face. HG combined with bFGF gel treatment after 2940 nm Er:YAG lattice laser therapy improved postoperative swelling and pigmentation compared with bFGF gel alone; and it promoted periorbital wrinkle improvement and wound healing. In conclusion, HG combined with GFs after laser therapy could be an alternative therapy for periorbital wrinkles.
Outcomes following out-of-hours acute cholecystectomy: A systematic review and meta-analysis

Supplemental digital content is available in the text. BACKGROUND Cholecystectomy is one of the most commonly performed abdominal operations. Rising demands on acute operating theater availability and resource utilization in the daytime have led to acute cholecystectomy being performed out-of-hours (in the evenings, at night, or on weekends), although it remains unknown whether outcomes differ between out-of-hours and in-hours (during the daytime on weekdays) acute cholecystectomy. This systematic review and meta-analysis aimed to compare outcomes following out-of-hours versus in-hours acute cholecystectomy. METHODS The study protocol was prospectively registered on PROSPERO (ID: CRD42021226127). MEDLINE, EMBASE, and Scopus databases were systematically searched for studies comparing outcomes following out-of-hours and in-hours acute cholecystectomy in adults with any acute benign gallbladder disease. The outcomes of interest were rates of bile leakage, bile duct injury, overall postoperative complications, conversion to open cholecystectomy, specific intraoperative and postoperative complications, length of stay, readmission, and mortality. Subgroup (evening/night-time vs. daytime, weekend vs. weekday, acute surgical unit [ASU]-only, non-ASU, and laparoscopic-only) and sensitivity analyses of adjusted multivariate regression analysis results was also performed. RESULTS Eleven studies were included. There were no differences between out-of-hours and in-hours acute cholecystectomy for rates of bile leakage, bile duct injury, overall postoperative complications, conversion to open cholecystectomy, operative duration, readmission, mortality, and postoperative length of stay. Higher rates of postoperative sepsis (odds ratio, 1.58; 95% confidence interval, 1.04–2.41; p = 0.03) and pneumonia (odds ratio, 1.55; 95% confidence interval, 1.06–2.26; p = 0.02) were observed following out-of-hours acute cholecystectomy on univariate meta-analysis, but not after the adjusted multivariate meta-analysis. Higher conversion rates were observed when out-of-hours cholecystectomy was performed in centers without an ASU. CONCLUSION This systematic review and meta-analysis has not shown an increased risk in overall or specific complications associated with out-of-hours compared with in-hours acute cholecystectomy. However, future studies should assess the potential impact of structural hospital factors, such as an ASU, on outcomes following out-of-hours acute cholecystectomy. LEVEL OF EVIDENCE Systematic Review and Meta-Analysis Study, Level IV.
Discovery and Evaluation of Entry Inhibitors for SARS-CoV-2 and Its Emerging Variants

The ongoing coronavirus infectious disease 2019 (COVID-19) pandemic is caused by a novel coronavirus named Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). More than 207 million people have been infected globally, and 4.3 million have died due to this viral outbreak. ABSTRACT The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the coronavirus disease 19 (COVID-19) pandemic. Despite unprecedented research and developmental efforts, SARS-CoV-2-specific antivirals are still unavailable for the treatment of COVID-19. In most instances, SARS-CoV-2 infection initiates with the binding of Spike glycoprotein to the host cell ACE2 receptor. Utilizing the crystal structure of the ACE2/Spike receptor-binding domain (S-RBD) complex (PDB file 6M0J) in a computer-aided drug design approach, we identified and validated five potential inhibitors of S-RBD and ACE-2 interaction. Two of the five compounds, MU-UNMC-1 and MU-UNMC-2, blocked the entry of pseudovirus particles expressing SARS-CoV-2 Spike glycoprotein. In live SARS-CoV-2 infection assays, both compounds showed antiviral activity with IC50 values in the micromolar range (MU-UNMC-1: IC50 = 0.67 μM and MU-UNMC-2: IC50 = 1.72 μM) in human bronchial epithelial cells. Furthermore, MU-UNMC-1 and MU-UNMC-2 effectively blocked the replication of rapidly transmitting variants of concern: South African variant B.1. 351 (IC50 = 9.27 and 3.00 μM) and Scotland variant B.1. 222 (IC50 = 2.64 and 1.39 μM), respectively. Following these assays, we conducted “induced-fit (flexible) docking” to understand the binding mode of MU-UNMC-1/MU-UNMC-2 at the S-RBD/ACE2 interface. Our data showed that mutation N501Y (present in B.1.351 variant) alters the binding mode of MU-UNMC-2 such that it is partially exposed to the solvent and has reduced polar contacts. Finally, MU-UNMC-2 displayed high synergy with remdesivir, the only approved drug for treating hospitalized COVID-19 patients. IMPORTANCE The ongoing coronavirus infectious disease 2019 (COVID-19) pandemic is caused by a novel coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). More than 207 million people have been infected globally, and 4.3 million have died due to this viral outbreak. While a few vaccines have been deployed, a SARS-CoV-2-specific antiviral for the treatment of COVID-19 is yet to be approved. As the interaction of SARS-CoV-2 Spike protein with ACE2 is critical for cellular entry, using a combination of a computer-aided drug design (CADD) approach and cell-based in vitro assays, we report the identification of five potential SARS-CoV-2 entry inhibitors. Out of the five, two compounds (MU-UNMC-1 and MU-UNMC-2) have antiviral activity against ancestral SARS-CoV-2 and emerging variants from South Africa and Scotland. Furthermore, MU-UNMC-2 acts synergistically with remdesivir (RDV), suggesting that RDV and MU-UNMC-2 can be developed as a combination therapy to treat COVID-19 patients.
Persuasive robots should avoid authority: The effects of formal and real authority on persuasion in human-robot interaction

Description For social robots to persuade people, they should behave as peers providing positive incentives and avoid being authoritative. Social robots must take on many roles when interacting with people in everyday settings, some of which may be authoritative, such as a nurse, teacher, or guard. It is important to investigate whether and how authoritative robots can influence people in applications ranging from health care and education to security and in the home. Here, we present a human-robot interaction study that directly investigates the effect of a robot’s peer or authority role (formal authority) and control of monetary rewards and penalties (real authority) on its persuasive influence. The study consisted of a social robot attempting to persuade people to change their answers to the robot’s suggestion in a series of challenging attention and memory tasks. Our results show that the robot in a peer role was more persuasive than when in an authority role, contrary to expectations from human-human interactions. The robot was also more persuasive when it offered rewards over penalties, suggesting that participants perceived the robot’s suggestions as a less risky option than their own estimates, in line with prospect theory. In general, the results show an aversion to the persuasive influence of authoritative robots, potentially due to the robot’s legitimacy as an authority figure, its behavior being perceived as dominant, or participant feelings of threatened autonomy. This paper explores the importance of persuasion for robots in different social roles while providing critical insight into the perception of robots in these roles, people’s behavior around these robots, and the development of human-robot relationships.
The distribution of a missense mutation in SDK1 gene across native Chinese breeds

Abstract Sidekick cell adhesion molecule 1 (SDK1) gene belonging to the immunoglobulin superfamily (IgSF) is reported to be associated with disease resistance. A novel missense mutation (XM_015469413.1: c.2678 A > G: p. Asp893Gly) in bovine SDK1 gene was observed in the Bovine Genome Variation Database (BGVD). The purpose of the current study was to determine the allelic frequency distribution of XM_015469413. 1: c.2678 A > G: p. Asp893Gly and analyze its association with disease resistance in native Chinese cattle. Here, we explored the allele frequency of the missense mutation (M_015469413.1: c.2678 A > G: p. Asp893Gly) in 542 individuals from 27 Chinese indigenous cattle breeds using PCR and DNA sequencing methods. The frequency of the mutant allele (G) gradually decreased from the southern cattle groups to the northern cattle groups, whereas the frequency of the wild-type allele A showed an opposite pattern, consistent with the distribution of indicine and taurine cattle in China. Thus, our results proved that the bovine SDK1 gene might be candidate genes associated with disease resistance in Chinese cattle.
Enhanced and Selective Lipid Extraction from the Microalga P. tricornutum by Dimethyl Carbonate and Supercritical CO2 Using Deep Eutectic Solvents and Microwaves as Pretreatment

Microalgae are promising alternative sources of several bioactive compounds that are useful for human applications. However, lipids are traditionally extracted with toxic organic solvents (e.g., mixtures of chloroform and methanol or hexane). In this work, we develop a new lipid extraction protocol for obtaining a fatty-acids-rich extract from the diatom Phaeodactylum tricornutum. Deep eutectic solvents (DESs) and microwaves (MWs) were investigated as pretreatments for environmentally friendly solvent extractions using dimethyl carbonate (DMC) and supercritical CO2 (scCO2). Pretreatments with various DESs formed by choline chloride (ChCl) and different hydrogen-bond donors (oxalic acid, levulinic acid, urea, ethylene glycol, and sorbitol) were tested in combination with DMC extraction. DESs formed by ChCl and carboxylic acids gave the best results, increasing both the selectivity and the total fatty acid (TFA) extraction yield of DMC (by 16% and 80%, respectively). DESs combined with MW heating followed b.
A Poster on Intestinal Parasite Detection in Stool Sample Using AlexNet and GoogleNet Architectures

Intestinal parasitic infections can cause serious health problems with relatively high infections in the developing world. Microscopy of stool remains the gold standard method for the diagnosis of intestinal parasites. However, this method can be time-consuming, and it is also challenging to maintain consistency in diagnosis across different technicians. This is also hindered by the few competent and skilled technicians in the developing countries where the prevalence of intestinal parasites is high. Deep learning has increasingly gained application ground in different challenging computer vision tasks. There is also growing literature of the use of the same technologies in health diagnostic fields such as microscopy. What is used in the state-of-art computer vision challenges, oftentimes gets applied to real-world challenges. However, this has met different limitations in sensitivity and specificity given the broader range of diversity in data sets; for example, in this study of intestinal parasite detection. In general, deep learning continues to provide good performance to computer vision problems across multiple disciplines. In this paper, we evaluate the use of AlexNet and GoogleNet models’ performance on the diagnosis of intestinal parasite eggs in stool samples. This work goes ahead to compare these out-of-the-box fine-tuned models with a custom-trained Convolutional Neural Network on the same task. In all cases, accuracy from the out-of-the-box models is very high with GoogleNet ROC AUC of 0.99 and AlexNet ROC AUC of 1.00, and runs on a very low computing resource system, which speaks to the fact that out-of-box models can re-purposed for real-world health diagnostic challenges.
Action recognition method based on wavelet transform and neural network in wireless network

With the popularization of wireless networks in life, wireless network-based action recognition methods developed better prospects in the fields of human-computer interaction, security and Internet of Things. In order to perform action recognition efficiently and stably, this paper considers combining Butterworth filtering and wavelet transform for denoising, and extracting features through self-organizing competitive neural network, and finally using Softmax regression function for action classification and recognition. Experimental results show that this method has a higher recognition rate and a strong stability.
Understanding the influence of stress on sedentary workers’ sitting behavior in screen-based interaction context

Sedentary work has become a significant part of a workday context, and this situation becomes more salient due to the COVID-19 pandemic. Existing studies show that body posture can be a good indicator of emotional states. However, to our knowledge, there are no studies that investigated the relationship between the characteristics of whole-body regions while seated and affective information related to stress for sedentary workers in screen-based working scenarios. This paper conducted a preliminary within-subjects study with eight participants performing three types of screen-based tasks at different difficulty levels for simulating natural working conditions. We developed a rapid posture coding technique to analyze sedentary workers’ real-time sitting behavior and deployed multiple methods for continuously detecting their stress conditions. The results indicated that stress conditions and task determinants play an essential role in the postural changes of different body regions while seated. Our preliminary findings provide design implications and recommendations for developing a more unobtrusive health-promoting system in the real-life working context.
Accelerate Binarized Neural Networks with Processing-in-Memory Enabled by RISC-V Custom Instructions

As the speed of processing units grows rapidly, the bottleneck of system’s performance is usually the speed of memory, and the situation is the so-called ”Memory Wall”. There are emerging technologies trying to take down the ”Memory Wall”, and one of them is Processing-in-Memory (PIM). Processing-in-Memory means that the data are processed just inside the memory itself. It does not need to take time to travel between CPU and Memory. Moreover, for very little modifications to memory devices, the memory can do primitive bit-wise operations at the memory side. Binarized Neural Network (BNN), which replaces the convolution’s multiplication and addition operations with bit-wise AND and population count operations, is therefore suited for utilizing PIM to gain performance. This work architects PIM AND, NOT, and population count operations and enables PIM operations working under RISC-V custom instruction encodings. Besides, we also utilize TVM’s support of BNN for application sources. In addition, we offer a new design for BNN’s convolution in which a better memory layout is considered. With our design, the results of the speedup range from 3.7x to 57.3x comparing with CPU-based system for the execution time of end-to-end BNN model inferences.
An Improved Object Detection Model for Autonomous pilot of Engineering Inspection

Previously, Engineering maintenance vehicle mainly through human operations, which has higher labor costs and lower efficiency. In order to obtain complete images needed in the field of engineering maintenance quickly and easily, auto pilot of engineering maintenance vehicle can play a huge role in engineering fields such as power maintenance and highway maintenance. Automatic ground key information detection is the most important part of auto pilot of engineering maintenance vehicle. In this study, we propose a new model that uses an improved form of the You Only Look Once (YOLO) model to enhance the real-time detection of key information problems. This model is mainly realized by optimizing the network structure of original YOLOv3 model. The experimental results show that in the highway center marking data set, the precision of the trained model is 95.76%, and an average accuracy of 90.43% for the test setup. By comparing with YOLOv3, the detection accuracy of the proposed improved method is mainly improved. At the same time, under GPU acceleration, the average detection speed is 29.20 frames/s, which can meet the real-time detection by the engineering maintenance vehicle platform.