Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Omic Analyses Reveal Habitat Adaptation of Marine Cyanobacterium Synechocystis sp. PCC 7338

Cyanobacteria are considered as promising microbial cell factories producing a wide array of bio-products. Among them, Synechocystis sp. PCC 7338 has the advantage of growing in seawater, rather than requiring arable land or freshwater. Nonetheless, how this marine cyanobacterium grows under the high salt stress condition remains unknown. Here, we determined its complete genome sequence with the embedded regulatory elements and analyzed the transcriptional changes in response to a high-salt environment. Complete genome sequencing revealed a 3.70 mega base pair genome and three plasmids with a total of 3,589 genes annotated. Differential RNA-seq and Term-seq data aligned to the complete genome provided genome-wide information on genetic regulatory elements, including promoters, ribosome-binding sites, 5′- and 3′-untranslated regions, and terminators. Comparison with freshwater Synechocystis species revealed Synechocystis sp. PCC 7338 genome encodes additional genes, whose functions are related to ion channels to facilitate the adaptation to high salt and high osmotic pressure. Furthermore, a ferric uptake regulator binding motif was found in regulatory regions of various genes including SigF and the genes involved in energy metabolism, suggesting the iron-regulatory network is connected to not only the iron acquisition, but also response to high salt stress and photosynthesis. In addition, the transcriptomics analysis demonstrated a cyclic electron transport through photosystem I was actively used by the strain to satisfy the demand for ATP under high-salt environment. Our comprehensive analyses provide pivotal information to elucidate the genomic functions and regulations in Synechocystis sp. PCC 7338.
Age-Associated Changes in Adverse Events Arising From Anti-PD-(L)1 Therapy

Background Immune-related adverse events (irAEs) may complicate the immune checkpoint inhibition (ICI) therapy. The effect of age on these irAEs is not elucidated. The aim of the study was to compare the occurrence of irAEs in different age groups. Methods Patients with lung cancer receiving anti-programmed death- (ligand)1 (PD-(L)1) were selected from the US Food and Drug Administration Adverse Event Reporting System (FAERS) database. Immune cell infiltration data set was obtained from TIMER 2.0 web server. The patients were stratified for age as follows: <65 year-old (young patients, YP), 65 to 75 year-old (middle aged patients, MP), ≥75 year-old (old patients, OP). The severity of irAEs was compared using logistic binary regression model. The distribution differences of immune cell infiltration were estimated using non-parametric tests. Results Of all the 17,006 patients treated by anti-PD-(L)1, 7,355 were <65 (YP), 6,706 were 65–75 (MP), and 2,945 were ≥75 (OP). In general, we analyzed a total of 16 irAEs in this article and found that pulmonary toxicity was more frequent in OP (OP vs. YP: OR = 1.45, 95% CI: 1.28–1.64) and MP (MP vs. YP: OR = 1.38, 95% CI: 1.24–1.52), but hepatitis was less frequent in OP (OP vs. YP: OR = 0.56, 95% CI: 0.32–0.97) and MP (MP vs. YP: OR = 0.57, 95%CI: 0.38–0.85). Further analysis demonstrated that older patients showed less B cell, CD8+ T cell and myeloid dendritic cell infiltration than younger patients. Conclusions Elderly patients exhibited higher incidences of pulmonary toxicity, while hepatitis was found at low incidence. Therefore, clinicians should carefully monitor comorbidities in elderly patients.
Increased Plasma Level of 24S-Hydroxycholesterol and Polymorphism of CYP46A1 SNP (rs754203) Are Associated With Mild Cognitive Impairment in Patients With Type 2 Diabetes

Background Abnormal cholesterol metabolism is common in type 2 diabetes mellitus (T2DM) and causes dementia. Cholesterol 24S-hydroxylase (CYP46A1) converts cholesterol into 24S-hydroxycholesterol (24-OHC) and maintains cholesterol homeostasis in the brain. Objective This study aimed to investigate the roles of 24-OHC and the CYP46A1 (rs754203) polymorphism in patients with T2DM and mild cognitive impairment (MCI). Methods A total of 193 Chinese patients with T2DM were recruited into two groups according to the Montreal Cognitive Assessment (MoCA). Demographic and clinical data were collected, and neuropsychological tests were conducted. Enzyme-linked immunosorbent assay (ELISA) and Seqnome method were used to detect the concentration of plasma 24-OHC and the CYP46A1 rs754203 genotype, respectively. Results Compared with 118 healthy cognition participants, patients with MCI (n = 75) displayed a higher plasma level of 24-OHC and total cholesterol concentration (all p = 0.031), while no correlation was found between them. In the overall diabetes population, the plasma level of 24-OHC was negatively correlated with MoCA (r = −0.150, p = 0.039), and it was further proved to be an independent risk factor of diabetic MCI (OR = 1.848, p = 0.001). Additionally, patients with MCI and the CC genotype of CYP46A1 rs754203 showed the highest plasma level of 24-OHC even though the difference was not statistically significant, and they obtained low scores in both the verbal fluency test and Stroop color and word test A (p = 0.008 and p = 0.029, respectively). Conclusion In patients with T2DM, high plasma level of 24-OHC and the CC genotype carrier of CYP46A1 rs754203 may portend a high risk of developing early cognitive impairment, including attention and executive deficits.
Endophytic Bacillus Bacteria Living in Sugarcane Plant Tissues and Telchin licus licus Larvae (Drury) (Lepidoptera: Castniidae): The Symbiosis That May Open New Paths in the Biological Control

Bacteria of the genus Bacillus can colonize endophytically and benefit several crops including the control of some pest orders. In view of the benefits provided by these microorganisms and in order to find out an efficient biotechnological control for the giant borer, our interest in studying the microorganisms in symbiosis with sugarcane and the giant borer has arisen, since there is no efficient chemical or biological control method for this pest. Therefore, endophytic Bacillus strains were isolated from three sugarcane niches (apoplast fluid, central internode cylinder and roots) and also from the giant borer larvae living inside sugarcane varieties grown in the Northeast region of Brazil. The taxonomical characterization (16S rRNA) of 157 Gram-positive isolates showed that 138 strains belonged to the Bacillus genus. The most representative species were phylogenetically closely related to B. megaterium (11.5%) followed by B. safensis (10.8%), B. cereus (8.9%), B. oleronius (8.9%), B. amyloliquefaciens (7.0%), and B. pacificus (6.4%). BOX-PCR analyses showed very distinct band pattern profiles suggesting a great diversity of Bacillus species within the sugarcane niches and the digestive tract, while the B. cereus group remained very closely clustered in the dendrogram. According to XRE biomarker analysis, eleven strains (FORCN005, 007, 008, 011, 012, 014, 067, 076, 092, 093, and 135) correspond to B. thuringiensis species. Additional studies using conserved genes (glp, gmk, pta, and tpi) indicated that most of these strains were phylogenetically closely related to B. thuringiensis and may be considered different subspecies. In conclusion, this study suggests that the culturable Bacillus species are greatly diversified within the plant niches and showed Bacillus species in the digestive tract of the giant borer for the first time. These results open new perspectives to understand the role and functions played by these microorganisms in symbiosis with this pest and also the possibility of developing an efficient biological control method for the giant borer using strains identified as the B. thuringiensis species.
Appling an Improved Method Based on ARIMA Model to Predict the Short-Term Electricity Consumption Transmitted by the Internet of Things (IoT)

The rapid development of the Internet of Things (IoT) has brought a data explosion and a new set of challenges. It has been an emergency to construct a more robust and precise model to predict the electricity consumption data collected from the Internet of Things (IoT). Accurately forecasting the electricity consumption is a crucial technology for the planning of the energy resource which could lead to remarkable conservation of the building electricity consumption. This paper is focused on the electricity consumption forecasting of an office building with a small-scale dataset, and 117 daily electricity consumption of the building are involved in the dataset, among which 89 values are selected as the training dataset and the remaining 28 values as the testing dataset. The hybrid model ARIMA (autoregression integrated moving average)-SVR (support vector regression) is proposed to predict the electricity consumption with different prediction horizons ranging from 1 day to 28 days. The model performances are assessed by three evaluation indicators, respectively, are the mean squared error (MSE), the root mean square error (RMSE), and the mean absolute percentage error (MAPE). The proposed model ARIMA-SVR is compared with the other four models, respectively, are the ARIMA, ARIMA-GBR (gradient boosting regression), LSTM (long short-term memory), and GRU (gated recurrent unit) models. The experiment result shows that the ARIMA-SVR model has lower prediction errors when the prediction horizon is within 20 days, and the ARIMA model is better when the prediction horizon is in the interval of 20 to 28 days. The provided method ARIMA-SVR has higher flexibility, and it is a great choice for electricity consumption prediction with more accurate results.
Distributed Blockchain-Based Authentication and Authorization Protocol for Smart Grid

Authentication and authorization (A & A) mechanisms are critical to the security of Internet of Things (IoT) applications. Smart grid system processing and exchanging data without human intervention, known as smart grids, are well-known as IoT scenarios. Entities in such smart grid systems need to identify and validate one another and ensure the integrity of data exchange mechanisms. However, at present, most commonly used A & A protocols are centralized, resulting in security risks such as information leaks, illegal access, and identity theft. In this study, we propose a new distributed A & A protocol for smart grid networks based on blockchain technology to address with these risks. The proposed protocol integrates the decentralized authentication and immutable ledger characteristics of blockchain architectures suitable for power systems with a novel blockchain technique to realize both identity authentication and resource authorization for smart grid systems. We discuss the security of and threat models for prior A & A protocols and demonstrate how our protocol protects against these threats. We further demonstrate an approach to a real deployment of our A & A protocol using the FISCO consortium platform, applying algorithms from smart contract systems. Finally, we present the results of experimental simulations showing the efficacy and efficiency of our proposed protocol.
Energy-Spectral Efficiency Trade-Offs in Full-Duplex MU-MIMO Cloud-RANs with SWIPT

The present paper investigates the trade-offs between the energy efficiency (EE) and spectral efficiency (SE) in the full-duplex (FD) multiuser multi-input multioutput (MU-MIMO) cloud radio access networks (CRANs) with simultaneous wireless information and power transfer (SWIPT). In the considered network, the central unit (CU) intends to concurrently not only transfer both energy and information toward downlink (DL) users using power splitting structures but also receive signals from uplink (UL) users. This communication is executed via FD radio units (RUs) which are distributed nearby users and connected to the CU through limited capacity fronthaul (FH) links. In order to unveil interesting trade-offs between the EE and SE metrics, we first introduce three conventional single-objective optimization problems (SOOPs) including (i) system sum rate maximization, (ii) total power minimization, and (iii) fractional energy efficiency maximization. Then, by making use of the multiobjective optimization (MOO) framework, the MOO problem (MOOP) with the objective vector of the achievable rate and power consumption is addressed. All considered problems are nonconvex with respect to designing variables comprising precoding matrices, compression matrices, and DL power splitting factors; thus, it is extremely intractable to solve these problems directly. To overcome these issues, we develop iterative algorithms by utilizing the sequential convex approximation (SCA) approach for the first two SOO problems and the SCA-based Dinkelbach method for the fractional EE problem. Regarding the MOOP, we first rewrite it as an SOOP by applying the modified weighted Tchebycheff method and, then, propose the iterative algorithm-based SCA to find its optimal Pareto set. Various numerical simulations are conducted to study the system performance and appealing EE-SE trade-offs in the considered system.
DNA Topoisomerase 3α Is Involved in Homologous Recombination Repair and Replication Stress Response in Trypanosoma cruzi

DNA topoisomerases are enzymes that modulate DNA topology. Among them, topoisomerase 3α is engaged in genomic maintenance acting in DNA replication termination, sister chromatid separation, and dissolution of recombination intermediates. To evaluate the role of this enzyme in Trypanosoma cruzi, the etiologic agent of Chagas disease, a topoisomerase 3α knockout parasite (TcTopo3α KO) was generated, and the parasite growth, as well as its response to several DNA damage agents, were evaluated. There was no growth alteration caused by the TcTopo3α knockout in epimastigote forms, but a higher dormancy rate was observed. TcTopo3α KO trypomastigote forms displayed reduced invasion rates in LLC-MK2 cells when compared with the wild-type lineage. Amastigote proliferation was also compromised in the TcTopo3α KO, and a higher number of dormant cells was observed. Additionally, TcTopo3α KO epimastigotes were not able to recover cell growth after gamma radiation exposure, suggesting the involvement of topoisomerase 3α in homologous recombination. These parasites were also sensitive to drugs that generate replication stress, such as cisplatin (Cis), hydroxyurea (HU), and methyl methanesulfonate (MMS). In response to HU and Cis treatments, TcTopo3α KO parasites showed a slower cell growth and was not able to efficiently repair the DNA damage induced by these genotoxic agents. The cell growth phenotype observed after MMS treatment was similar to that observed after gamma radiation, although there were fewer dormant cells after MMS exposure. TcTopo3α KO parasites showed a population with sub-G1 DNA content and strong γH2A signal 48 h after MMS treatment. So, it is possible that DNA-damaged cell proliferation due to the absence of TcTopo3α leads to cell death. Whole genome sequencing of MMS-treated parasites showed a significant reduction in the content of the multigene families DFG-1 and RHS, and also a possible erosion of the sub-telomeric region from chromosome 22, relative to non-treated knockout parasites. Southern blot experiments suggest telomere shortening, which could indicate genomic instability in TcTopo3α KO cells owing to MMS treatment. Thus, topoisomerase 3α is important for homologous recombination repair and replication stress in T. cruzi, even though all the pathways in which this enzyme participates during the replication stress response remains elusive.
Propofol Inhibits Ischemia/Reperfusion-Induced Cardiotoxicity Through the Protein Kinase C/Nuclear Factor Erythroid 2-Related Factor Pathway

Both hydrogen peroxide (H2O2, H) and ischemia/reperfusion (I/R) can damage cardiomyocytes, which was inhibited by propofol (P). The present research was designed to examine whether propofol can reduce myocardial I/R injury by activating protein kinase C (PKC)/nuclear factor erythroid-2-related factor 2 (NRF2) pathway in H9C2 cells and rat Langendorff models. H9C2 cells were disposed of no reagents (C), H2O2 for 24 h (H), propofol for 1 h before H2O2 (H+P), and chelerythrine (CHE, PKC inhibitor) for 1 h before propofol and H2O2 (H+P+CHE). N = 3. The PKC gene of H9C2 was knocked down by siRNA and overexpressed by phorbol 12-myristate 13-acetate (PMA, PKC agonist). The cell viability and the expressions of PKC, NRF2, or heme oxygenase-1(HO-1) were evaluated. Propofol significantly reduced H9C2 cell mortality induced by H2O2, and significantly increased NRF2 nuclear location and HO-1 expression, which were restrained by siRNA knockout of PKC and promoted by PMA. Rat hearts were treated with KrebsHenseleit solution for 120 min (C), with (I/R+P) or without (I/R) propofol for 20 min before stopping perfusion for 30 min and reperfusion for 60 min, and CHE for 10 min before treated with propofol. N = 6. The levels of lactate dehydrogenase (LDH), superoxide dismutase (SOD), and creatine kinase-MB (CK-MB) in perfusion fluid and antioxidant enzymes in the myocardium were assessed. I/R, which increased LDH and CK-MB expression and reduced SOD expression, boosted the pathological damage and infarcts of the myocardium after reperfusion. However, propofol restrained all these effects, an activity that was antagonized by CHE. The results suggest that propofol pretreatment protects against I/R injury by activating of PKC/NRF2 pathway.
Defining Spotting in Dance: A Delphi Method Study Evaluating Expert Opinions

Spotting is a typical isolated head coordination used by many dancers during rotation. However, with sporadic and inconclusive explanations as to why dancers spot, the critical characteristics and functionalities of spotting have yet to be identified. Therefore, a Delphi method survey was used as a novel methodology for providing greater insights into this under-examined motor behavior, bringing together experts from various disciplines to generate ideas and identify the crucial elements of spotting. Following the selection of experts, three rounds of data collection and analysis were conducted to narrow down relevant topics and evaluate consensus. To gather opinions in Round 1, experts were asked to respond freely to three prompts regarding the reasoning, characteristics, and uses of successfully spotting; responses were then grouped into predominant items. To rate agreement in Round 2, experts rated their agreement on the relevance of the grouped items from Round 1 on a 5-point Likert scale; items rated 4 or 5 by at least 70% of the experts were taken as those consensually relevant to the group. To rank importance in Round 3, Best-Worst Scaling was used to determine individual rankings of the relevant items from Round 2. In a series of comparisons, experts were prompted to select the most and least important items in multiple sub-groupings. Group mean ranking of items as well as ranking concordance and differentiation were analyzed to determine the most important items and the strength of consensus, respectively. Overall, consensus and differentiation in experts’ item rankings were low; however, novel insights were presented. As characteristics of successfully spotting, experts emphasized head isolation, timing, and gaze specificity alongside functional characteristics, substantiating spotting as purposeful action in rotation. Building on traditional notions of spotting for reduced dizziness and maintaining balance, successfully spotting was further deemed useful for multiple turns, orientation, and rhythm. The findings of this study thus provide informed guidelines for future analysis and training of this complex head coordination in rotations.
Psychological Distress, Early Behavioral Response, and Perception Toward the COVID-19 Pandemic Among Health Care Workers in North Shoa Zone, Oromiya Region

Background: The coronavirus disease 2019 (COVID-19) pandemic has had a significant psychological impact on health care workers (HCWs). Therefore, this study inspects the mental health status, behavioral response, and perception among HCWs (nurses, physicians, and medical laboratory workers) during the COVID-19 pandemic in public health care facilities. Methods: A facilities-based cross-sectional study was conducted in July 2020. A simple random sampling technique was used to select study participants. Data were collected by self-report administered questionnaires using Patient Health Questionnaire-9 (PHQ-9) for depression, General Anxiety Disorder-7 (GAD-7) for anxiety, Insomnia Severity Index (ISI) for insomnia, Impact of Event Scale-Revised (IES-R) for psychological distress, Perceived Threat Scale for perception, and Behavioral Response Inquiry for the behavioral response. Moreover, bivariable and multivariable logistic regressions analysis was used to identify the association between dependent and independent variables at p-value <0.05. Results: A total of 417 (98.6%) HCWs responded to a self-administered questionnaire. The proportion of HCWs who had moderate to severe symptoms of psychological distress, depression, anxiety, and insomnia during the COVID-19 pandemic were 58, 16.3, 30.7, and 15.9%, respectively. Three-fifth of the nurses, medical laboratory professionals (62.2%), and physicians (59.2%) had reported good behavioral responses toward the COVID-19 pandemic. More than three-fifths of the nurses had reported poor perception toward the COVID-19 pandemic. Conversely, 61.2% of physicians and three-fourths (75.5%) of medical laboratory professionals had reported good perception toward the COVID-19 pandemic. Female and married participants, those working in the emergency unit, those with poor behavioral responses, and those with poor perception toward the COVID-19 pandemic were significantly associated with symptoms of psychological distress, depression, anxiety, and insomnia. Conclusions: Psychological impacts among physicians, nurses, and medical laboratory professionals are high during the COVID-19 pandemic. The Ethiopian Federal Ministry of Health should aim to protect all HCWs' psychological well-being during the COVID-19 pandemic with appropriate interventions and accurate information response.
Identification of the Core MicroRNAs and Potential Molecular Mechanismsin Sarcoidosis Using Bioinformatics Analysis

Sarcoidosis is a systemic heterogeneous inflammatory disease; however, the etiology and pathogenesis of sarcoidosis are still unknown. Herein, we investigated the core microRNAs and potential molecular mechanisms in sarcoidosis. The DE-miRNAs were diagnosed using the LIMMA software package. DIANA-mirPath was employed to perform pathway and GO enrichment analysis of the DE-miRNAs. PPI networks and miRNA-target gene regulatory networks were used to obtain insight into the actions of DE-miRNAs. Expression of the hub genes along with miRNAs was validated in clinical specimens. Overall, 266 DE-miRNAs were screened. Among these DE-miRNAs, hsa-miR-144, hsa-miR-126, as well as hsa-miR-106a were the upmost upregulated miRNAs; hsa-miR-151-3p, hsa-miR-320d, and hsa-miR-324-3p were the top downregulated miRNAs. NR3C1, ZBTB7A, NUFIP2, BZW1, ERGIC2, and VEGFA were mapped as the most targeted hub genes in the upregulation of miRNAs, and MCL1 and SAE1 were the most targeted hub genes in the downregulation of miRNA. VEGFA and NR3C1 were selected and potentially modulated by hsa-miR-20b, hsa-miR-126, and hsa-miR-106a. In sarcoidosis pathological tissue, hsa-miR-126 was highly expressed, and VEGFA and NR3C1 were overexpressed. In conclusion, our results revealed the dysregulation of hsa-miR-126 and a potential regulatory mechanism for pathogenesis in sarcoidosis.