Miracle-dz/UniFAR-FTUs huggingface dataset:
Spoligotyping of Clinical Isolates of Mycobacterium tuberculosis Complex Species in the Oromia Region of Ethiopia

Background Tuberculosis (TB) is a leading cause of morbidity and mortality in Ethiopia. Investigation of the Mycobacterium tuberculosis complex (MTBC) species circulating in the Ethiopian population would contribute to the efforts made to control TB in the country. Therefore, this study was conducted to investigate the MTBC species and spoligo patterns in the Oromia region (central) of Ethiopia. Methods A cross-sectional study design was used to recruit 450 smear positive pulmonary TB (PTB) cases from the Oromia region between September 2017 and August 2018. Mycobacteria were isolated from sputum samples on the Lowenstein Jensen (LJ) medium. Molecular identification of the isolates was performed by spoligotyping. The results of spoligotyping were transferred into a query box in the SITVIT2 database and Run TB-Lineage in the TB Insight website for the identification of spoligo international type (SIT) number and linages of the isolates, respectively. Statistical Product and Service Solutions (SPSS) 20 was applied for statistical analysis. Results Three hundred and fifteen isolates were grouped under 181 different spoligotype patterns. The most dominantly isolated spoligotype pattern was SIT149 and it consisted of 23 isolates. The majority of the isolates were grouped under Euro-American (EA), East-African-Indian (EAI), and Indo-Oceanic (IO) lineages. These lineages consisted of 79.4, 9.8, and 9.8% of the isolates, respectively. One hundred and sixty-five of the isolates were classified under 31 clustered spoligotypes whereas the remaining 150 were singleton types. Furthermore, 91.1% of the total isolates were classified as orphan types. Clustering of spoligotypes was associated (p < 0.001) with EAI lineage. Conclusion SIT149 and EA lineage were predominantly isolated from the Oromia region substantiating the findings of the similar studies conducted in other regions of Ethiopia. The observation of significant number of singleton and orphan spoligotypes warrants for additional genetic typing of the isolates using method(s) with a better discriminatory power than spoligotyping.
The Regulatory Role of Non-coding RNA in Autophagy in Myocardial Ischemia-Reperfusion Injury

Following an acute myocardial infarction (AMI), thrombolysis, coronary artery bypass grafting and primary percutaneous coronary intervention (PPCI) are the best interventions to restore reperfusion and relieve the ischemic myocardium, however, the myocardial ischemia-reperfusion injury (MIRI) largely offsets the benefits of revascularization in patients. Studies have demonstrated that autophagy is one of the important mechanisms mediating the occurrence of the MIRI, while non-coding RNAs are the main regulatory factors of autophagy, which plays an important role in the autophagy-related mTOR signaling pathways and the process of autophagosome formation Therefore, non-coding RNAs may be used as novel clinical diagnostic markers and therapeutic targets in the diagnosis and treatment of the MIRI. In this review, we not only describe the effect of non-coding RNA regulation of autophagy on MIRI outcome, but also zero in on the regulation of non-coding RNA on autophagy-related mTOR signaling pathways and mitophagy. Besides, we focus on how non-coding RNAs affect the outcome of MIRI by regulating autophagy induction, formation and extension of autophagic vesicles, and the fusion of autophagosome and lysosome. In addition, we summarize all non-coding RNAs reported in MIRI that can be served as possible druggable targets, hoping to provide a new idea for the prediction and treatment of MIRI.
COVCOG 1: Factors Predicting Physical, Neurological and Cognitive Symptoms in Long COVID in a Community Sample. A First Publication From the COVID and Cognition Study

Since its first emergence in December 2019, coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has evolved into a global pandemic. Whilst often considered a respiratory disease, a large proportion of COVID-19 patients report neurological symptoms, and there is accumulating evidence for neural damage in some individuals, with recent studies suggesting loss of gray matter in multiple regions, particularly in the left hemisphere. There are a number of mechanisms by which COVID-19 infection may lead to neurological symptoms and structural and functional changes in the brain, and it is reasonable to expect that many of these may translate into cognitive problems. Indeed, cognitive problems are one of the most commonly reported symptoms in those experiencing “Long COVID”—the chronic illness following COVID-19 infection that affects between 10 and 25% of patients. The COVID and Cognition Study is a part cross-sectional, part longitudinal, study documenting and aiming to understand the cognitive problems in Long COVID. In this first paper from the study, we document the characteristics of our sample of 181 individuals who had experienced COVID-19 infection, and 185 who had not. We explore which factors may be predictive of ongoing symptoms and their severity, as well as conducting an in-depth analysis of symptom profiles. Finally, we explore which factors predict the presence and severity of cognitive symptoms, both throughout the ongoing illness and at the time of testing. The main finding from this first analysis is that that severity of initial illness is a significant predictor of the presence and severity of ongoing symptoms, and that some symptoms during the initial illness—particularly limb weakness—may be more common in those that have more severe ongoing symptoms. Symptom profiles can be well described in terms of 5 or 6 factors, reflecting the variety of this highly heterogenous condition experienced by the individual. Specifically, we found that neurological/psychiatric and fatigue/mixed symptoms during the initial illness, and that neurological, gastrointestinal, and cardiopulmonary/fatigue symptoms during the ongoing illness, predicted experience of cognitive symptoms.
A Zero-Padding Frequency Domain Convolutional Neural Network for SSVEP Classification

The brain-computer interface (BCI) of steady-state visual evoked potential (SSVEP) is one of the fundamental ways of human-computer communication. The main challenge is that there may be a nonlinear relationship between different SSVEP in other states. For improving the performance of SSVEP BCI, a novel CNN algorithm model is proposed in this study. Based on the discrete Fourier transform to calculate the signal's power spectral density (PSD), we perform zero-padding in the signal's time domain to improve its performance on the PSD and make it more refined. In this way, the frequency point interval in the PSD of the SSVEP is consistent with the minimum gap between the stimulation frequency. Combining the nonlinear transformation capabilities of CNN in deep learning, a zero-padding frequency domain convolutional neural network (ZPFDCNN) model is proposed. Extensive experiments based on the SSVEP dataset validate the effectiveness of our method. The study verifies that the proposed ZPFDCNN method can improve the effectiveness of the SSVEP-based high-speed BCI ITR. It has massive potential in the application of BCI.
So Similar, yet so Different: The Case of the Ionic Liquids N-Trimethyl-N (2-methoxyethyl)ammonium Bis (trifluoromethanesulfonyl)imide and N,N-Diethyl-N-methyl-N(2-methoxyethyl)ammonium bis(trifluoromethanesulfonyl)imide

Two ethoxy containing ionic liquids (ILs) sharing the same anion, N-trimethyl-N (2-methoxyethyl)ammonium bis(trifluoromethanesulfonyl)imide (N111(2O1)-TFSI) and N,N-diethyl-N-methyl-N (2-methoxyethyl)ammonium bis(trifluoromethanesulfonyl)imide (N122(2O1)-TFSI), and their mixtures are studied by means of differential scanning calorimetry and infrared spectroscopy combined with DFT calculations. The two ILs, slightly differing only for the length of two short chains, diverge significantly in the thermal properties: N111(2O1)-TFSI undergoes to a crystallization upon cooling, whereas N122(2O1)-TFSI is likely to become a glass. Experimental results indicate that in N111(2O1)-TFSI the occurrence of hydrogen bonding is energetically favored, and become particularly evident in the solid phase. The comparison with computational results indicates that it could be ascribed to the CH bonds involving the C atoms directly linked to the central N atom. In N122(2O1)-TFSI, DFT calculations suggest that hydrogen bonding could take place; however, IR measurements suggest that hydrogen bonding is not energetically favored. Moreover, in N122(2O1)-TFSI there is a larger conformational disorder that prevents from the alignment of cation and anion that contributes to the detection of clear hydrogen bonding infrared active bands. The mixtures rich in N111(2O1)-TFSI crystallize at lower temperatures than the pure ionic liquid. Progressively, the energy gain due to the instauration of hydrogen bonding decreases as the concentration of N122(2O1)-TFSI increases.
Metformin Inhibits NLR Family Pyrin Domain Containing 3 (NLRP)-Relevant Neuroinflammation via an Adenosine-5′-Monophosphate-Activated Protein Kinase (AMPK)-Dependent Pathway to Alleviate Early Brain Injury After Subarachnoid Hemorrhage in Mice

Neuroinflammation plays a key role in the pathogenesis of early brain injury (EBI) after subarachnoid hemorrhage (SAH). Previous studies have shown that metformin exerts anti-inflammatory effects and promotes functional recovery in various central nervous system diseases. We designed this study to investigate the effects of metformin on EBI after SAH. Our results indicate that the use of metformin alleviates the brain edema, behavioral disorders, cell apoptosis, and neuronal injury caused by SAH. The SAH-induced NLRP3-associated inflammatory response and the activation of microglia are also suppressed by metformin. However, we found that the blockade of AMPK with compound C weakened the neuroprotective effects of metformin on EBI. Collectively, our findings indicate that metformin exerts its neuroprotective effects by inhibiting neuroinflammation in an AMPK-dependent manner, by modulating the production of NLRP3-associated proinflammatory factors and the activation of microglia.
Spectral–Spatial Feature Tokenization Transformer for Hyperspectral Image Classification

In hyperspectral image (HSI) classification, each pixel sample is assigned to a land-cover category. In the recent past, convolutional neural network (CNN)-based HSI classification methods have greatly improved performance due to their superior ability to represent features. However, these methods have limited ability to obtain deep semantic features, and as the layer’s number increases, computational costs rise significantly. The transformer framework can represent high-level semantic features well. In this article, a spectral–spatial feature tokenization transformer (SSFTT) method is proposed to capture spectral–spatial features and high-level semantic features. First, a spectral–spatial feature extraction module is built to extract low-level features. This module is composed of a 3-D convolution layer and a 2-D convolution layer, which are used to extract the shallow spectral and spatial features. Second, a Gaussian weighted feature tokenizer is introduced for features transformation. Third, the transformed features are input into the transformer encoder module for feature representation and learning. Finally, a linear layer is used to identify the first learnable token to obtain the sample label. Using three standard datasets, experimental analysis confirms that the computation time is less than other deep learning methods and the performance of the classification outperforms several current state-of-the-art methods. The code of this work is available at https://github.com/zgr6010/HSI_SSFTT for the sake of reproducibility.
A Novel End-To-End Network for Reconstruction of Non-Regularly Sampled Image Data Using Locally Fully Connected Layers

Quarter sampling and three-quarter sampling are novel sensor concepts that enable the acquisition of higher resolution images without increasing the number of pixels. This is achieved by non-regularly covering parts of each pixel of a low-resolution sensor such that only one quadrant or three quadrants of the sensor area of each pixel is sensitive to light. Combining a properly designed mask and a high-quality reconstruction algorithm, a higher image quality can be achieved than using a low-resolution sensor and subsequent upsampling. For the latter case, the image quality can be further enhanced using super resolution algorithms such as the very deep super resolution network (VDSR). In this paper, we propose a novel end-to-end neural network to reconstruct high resolution images from non-regularly sampled sensor data. The network is a concatenation of a locally fully connected reconstruction network (LFCR) and a standard VDSR network. Altogether, using a three-quarter sampling sensor with our novel neural network layout, the image quality in terms of PSNR for the Urban100 dataset can be increased by 2.96 dB compared to the state-of-the-art approach. Compared to a low-resolution sensor with VDSR, a gain of 1.11 dB is achieved.
MICROBIAL RISK ASSESSMENT OF THE COMPOSTING TOILET

水を使わずかつ資源回収が可能なコンポスト型トイレが現在の流域・都市の水循環が抱える問題を解決するものとして注目されている. しかし, コンポスト型トイレは水洗トイレとは異なり, 排泄物を生活環境内にとどめておくため病原微生物の二次感染について留意する必要があると考えられる. 本論文では, コンポスト型トイレの衛生学的安全性を調べることを目的とし, 従来の水系病原微生物リスク評価をコンポスト型トイレに適用して, 病原微生物の二次感染リスク評価を行い, コンポスト型トイレに要求される病原微生物除去率や必要処理時間について考察した. 結果としてウイルスの方がリスクが高く, それに応じてトイレ内での必要除去率も高くなることが示唆された. また, 井戸水を介した間接暴露においても, 直接暴露に匹敵するリスクが生じる可能性についても示唆された.
Reactistan: Do the Subaltern Speak on YouTube?

The advent of digital user-created media platforms such as YouTube has made possible the spread of a wide range of information including novel forms and variants of what might have previously been characterized as anthropological content. The present paper examined YouTube videos on a specific channel featuring purported “tribal people” from Pakistan reacting to cultural items and stimuli that are common to Western (and domestic urban) audiences. We found significantly greater indications of agency in the videos than indicators of subalternity. While the videos focused primarily on presenting the views and opinions of the participants and allowing their voices to be heard, they also held a continuing focus on the subjects' isolation or lack of exposure to mainstream. While agency and subalternity indices did not differ by gender, male participants outnumbered females and enjoyed greater screen time in the videos while audiences sometimes responded differently to male and female participants. The paper concludes with a discussion of whether such representation and presence in online media constitute a meaningful step towards enabling the subaltern to “speak. ”
CTRQ 2021

—Large-scale storage systems employ erasure-coding redundancy schemes to protect against device failures. The adverse effect of latent sector errors on the Mean Time to Data Loss ( MTTDL ) and the Expected Annual Fraction of Data Loss ( EAFDL ) reliability metrics is evaluated. A theoretical model capturing the effect of latent errors and device failures is developed, and closed-form expressions for the metrics of interest are derived. The MTTDL and EAFDL of erasure-coded systems are obtained analytically for (i) the entire range of bit error rates, (ii) the symmetric, clustered, and declustered data placement schemes, and (iii) arbitrary device failure and rebuild time distributions under network rebuild bandwidth constraints. For realistic values of sector error rates, the results obtained demonstrate that MTTDL degrades, whereas EAFDL remains practically unaffected. It is also shown that the declustered data placement scheme offers superior reliability.
A CROSS-SECTIONAL METHOD FOR RIGHT-TAILED PANIC TESTS UNDER A MODERATELY LOCAL TO UNITY FRAMEWORK

The left-tailed unit-root tests of the panel analysis of nonstationarity in idiosyncratic and common components (PANIC) proposed by Bai and Ng (2004, Econometrica 72, 1127–1177) have standard local asymptotic power. We assess the size and power properties of the right-tailed version of the PANIC tests when the common and/or the idiosyncratic components are moderately explosive. We find that, when an idiosyncratic component is moderately explosive, the tests for the common components may have considerable size distortions, and those for an idiosyncratic component may suffer from the nonmonotonic power problem. We provide an analytic explanation under the moderately local to unity framework developed by Phillips and Magdalinos (2007, Journal of Econometrics 136, 115–130). We then propose a new cross-sectional (CS) approach to disentangle the common and idiosyncratic components in a relatively short explosive window. Our Monte Carlo simulations show that the CS approach is robust to the nonmonotonic power problem.
Improvement of Antioxidant Properties in Fruit from Two Blood and Blond Orange Cultivars by Postharvest Storage at Low Temperature

Numerous studies have revealed the remarkable health-promoting activities of citrus fruits, all of them related to the accumulation of bioactive compounds, including vitamins and phytonutrients. Anthocyanins are characteristic flavonoids present in blood orange, which require low-temperature for their production. Storage at low-temperature of blood oranges has been proven to be a feasible postharvest strategy to increase anthocyanins in those countries with warm climates. To our knowledge, no studies comparing the effect of postharvest storage effect on phenylpropanoid accumulation in cultivars with and without anthocyanins production have been published. We have investigated the effect of postharvest cold storage in flavonoid accumulation in juice from Citrus sinensis L. Osbeck in two different oranges: Pera, a blond cultivar, and Moro, a blood one. Our findings indicate a different response to low-temperature of fruit from both cultivars at biochemical and molecular levels. Little changes were observed in Pera before and after storage, while a higher production of phenylpropanoids (3.3-fold higher) and flavonoids (1.4-fold higher), including a rise in anthocyanins from 1.3 ± 0.7 mg/L to 60.0 ± 9.4 mg/L was observed in Moro concurrent with an upregulation of the biosynthetic genes across the biosynthetic pathway. We show that postharvest storage enhances not only anthocyanins but also other flavonoids accumulation in blood oranges (but not in blond ones), further stimulating the interest in blood orange types in antioxidant-rich diets.
Financial sustainability in Italian Organic Farms: An analysis of the FADN Sample

With the European Green Deal, presented in December 2019, the EU Commission aims at making Europe the world's first climate neutral continent by 2050. In this plan agriculture plays a key role and so does organic farming. The aim of this work is to assess the financial sustainability of organic farms compared to conventional ones, measuring the liquidity they generate, evaluating its adequacy and identifying the factors that influence its extent. Specifically, this study uses the Italian FADN sample, made up of 18 TFs, and measures the Free Cash Flow on Equity (FCFE) for both organic and conventional farms. The econometric analysis identifies the variables contributing to cash flow production and is based on three types of variables: structural, including the cash flow itself, relative to farm results. The analysis showed that financial sustainability is greater for organic than conventional farms, and in several cases the level reached by the former is very high especially in mixed TFs. Yet, a major part of the sustainability of organic farms is due to EU payments, mainly of the cap II type.Also, the balance of business relationships with customers and suppliers allows organic farms to increase liquidity almost as much as the total amount of public aid received. Still, this result should be supported by improving price and yield conditions, as much of the GMO is achieved with below-average value for both variables. Finally, our analytical approach can be used by Countries using the FADN to assess the situation of their agriculture and help direct policy support better.
Together Intra-Tumor Hypoxia and Macrophagic Immunity Are Driven Worst Outcome in Pediatric High-Grade Osteosarcomas

Simple Summary Radiological and immunohistochemical data were correlated with the outcome in a retrospective monocentric cohort of 30 pediatric osteosarcomas (OTS). A necrotic volume of more than 50 cm3 at diagnosis was significantly linked to a worse overall survival (OS). Regarding immunohistochemical analyses, an overexpression of hypoxic markers, such as HIF-1α and anhydrase carbonic IX (CAIX), was significantly linked to a worse OS, while pS6-RP hyperexpression was correlated with a better survival. We also featured that CD68 positive cells, representative of macrophagic M1 polarization, were mostly associated with HIF-1α and CAIX hyperexpressions and that M2-like polarization, mostly related to CD163 positivity, was correlated to mTor activation. These findings, involving clinical, radiological and biology data, allowed us to hypothesize a dual signature association ready to use routinely in future protocols. Abstract Background: Osteosarcomas (OTS) represent the most common primary bone cancer diagnosed in adolescents and young adults. Despite remarkable advances, there are no objective molecular or imaging markers able to predict an OTS outcome at diagnosis. Focusing on biomarkers contributing broadly to treatment resistance, we examine the interplay between the tumor-associated macrophages and intra-tumor hypoxia. Methods: Radiological and immunohistochemical (IHC) data were correlated with the outcome in a retrospective and monocentric cohort of 30 pediatric OTS. We studied hypoxic (pS6, phospho-mTor, HIF-1α and carbonic anhydrase IX (CAIX)) and macrophagic (CD68 and CD163) biomarkers. Results: The imaging analyses were based on MRI manual volumetric measures on axial post-contrast T1 weighted images, where, for each tumor, we determined the necrotic volume and its ratio to the entire tumor volume. When they were above 50 cm3 and 20%, respectively, they correlated with a worse overall survival (p = 0.0072 and p = 0.0136, respectively) and event-free survival (p = 0.0059 and p = 0.0143, respectively). IHC assessments enable a significant statistical link between HIF-1α/CAIX hyper-expressions, CD68+ cells and a worse outcome, whereas activation of mTor pathway was linked to a better survival rate and CD163+ cells. Conclusions: This study evidenced the links between hypoxia and immunity in OTS, as their poor outcome may be related to a larger necrotic volume on diagnostic MRI and, in biopsies, to a specific IHC profile.