Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of Traditional Chinese Exercise for Symptoms of Knee Osteoarthritis: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background: Growing evidences have advocated the potential benefits of traditional Chinese exercise (TCE) on symptomatic improvement of knee osteoarthritis (KOA). However, most of them have been derived from cross-sectional studies or case reports; the effectiveness of TCE therapies has not been fully assessed with a randomized control trial (RCT). In order to evaluate the combined clinical effectiveness of TCE for KOA, we conducted a systematic review and meta-analysis on the existing RCTs on KOA. Methods: A systematic search was performed in four electronic databases: PubMed, Web of Science, Cochrane Library, and EMBASE from the time of their inception to February 2020. All eligible RCTs were included in which TCE was utilized for treating KOA as compared to a control group. Two reviewers independently extracted the data and evaluated the risk of bias following the Cochrane Risk of Bias Tool for RCT. The symptoms of KOA evaluated by the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and the Knee Injury and Osteoarthritis Outcome Score (KOOS) were regarded as the primary outcomes in this study. Each outcome measure was pooled by a standardized mean difference (SMD) with 95% confidence intervals (CI). A meta-analysis was applied with a random or fixed effect model for the collected data to calculate the summary SMD with 95% CI based on different statistical heterogeneity. In addition, subgroup analyses were used to investigate heterogeneity and sensitivity analysis was carried out for the results of the meta-analysis. Egger’s test and the funnel plots were used to examine the potential bias in the RCTs. Results: A total of 14 RCTs involving 815 patients with KOA were included. Compared with a control group; the synthesized data of TCE showed a significant improvement in WOMAC/KOOS pain score (SMD = −0.61; 95% CI: −0.86 to −0.37; p < 0.001), stiffness score (SMD = −0.75; 95% CI: −1.09 to −0.41; p < 0.001), and physical function score (SMD = −0.67; 95% CI: −0.82 to −0.53; p < 0.001). Conclusions: Our meta-analysis suggested that TCE may be effective in alleviating pain; relieving stiffness and improving the physical function for patients with KOA. Yet; given the methodological limitations of included RCTs in this meta-analysis; more high-quality RCTs with large sample size and long-term intervention are required to further confirm the effectiveness and underlying mechanisms of TCE for treating KOA.
FE-SEM Characterization of α-Mannose Density and Surface Mapping Changes in Human Sperm Head During In Vitro Capacitation

Abstract Sperm capacitation includes the reorganization of plasma membrane components and the outstanding modification of the glycocalyx. The α-mannose presence and location during in vitro capacitation have been commonly described in human spermatozoa using Concanavalin A (Con A) lectin. However, it is still unclear to date how in vitro capacitation time affects the α-mannose residues and their topographic spatial distribution on sperm membrane. Here, we characterized the α-mannose density and specific membrane domain locations before and after in vitro capacitation (1–4 h) using high-resolution field emission scanning electron microscopy (FE-SEM). Results showed that α-mannose residues were present preferably on the acrosome domains for all physiological conditions. Uncapacitated sperm comparatively exhibits significant highest labeling densities of α-mannose residues. In addition, as in vitro capacitation takes place, significant and progressive decreasing of sugar residues was combined with their relocation mostly affecting acrosomal domain apical areas. Our findings reveal that combined approach using FE-SEM and gold nanoparticle topographical mapping offers new human sperm biomolecular and structural details during capacitation events.
Psychological symptoms of the outbreak of the COVID-19 confinement in Spain

We studied the short-term psychological effects of the COVID-19 crisis and the quarantine on 3550 adults from the Spanish population in a cross-sectional survey. Symptoms of anxiety, depression, and stress were analyzed using the 21-item version of the Depression Anxiety Stress Scale. Symptoms of posttraumatic stress disorder were analyzed using the Impact of Event Scale. Symptomatic scores of anxiety, depression, and stress were observed in 20% to 30% of respondents. Symptomatic scores indicating psychological stress were found in 47.5% of respondents. Similar to the findings of other multiple studies, confinement has been found to have significant emotional impact in the Spanish population.
Image-Based Plant Disease Identification by Deep Learning Meta-Architectures

The identification of plant disease is an imperative part of crop monitoring systems. Computer vision and deep learning (DL) techniques have been proven to be state-of-the-art to address various agricultural problems. This research performed the complex tasks of localization and classification of the disease in plant leaves. In this regard, three DL meta-architectures including the Single Shot MultiBox Detector (SSD), Faster Region-based Convolutional Neural Network (RCNN), and Region-based Fully Convolutional Networks (RFCN) were applied by using the TensorFlow object detection framework. All the DL models were trained/tested on a controlled environment dataset to recognize the disease in plant species. Moreover, an improvement in the mean average precision of the best-obtained deep learning architecture was attempted through different state-of-the-art deep learning optimizers. The SSD model trained with an Adam optimizer exhibited the highest mean average precision (mAP) of 73.07%. The successful identification of 26 different types of defected and 12 types of healthy leaves in a single framework proved the novelty of the work. In the future, the proposed detection methodology can also be adopted for other agricultural applications. Moreover, the generated weights can be reused for future real-time detection of plant disease in a controlled/uncontrolled environment.
Development of aptamer-based inhibitors for CRISPR/Cas system

Abstract The occurrence of accidental mutations or deletions caused by genome editing with CRISPR/Cas9 system remains a critical unsolved problem of the technology. Blocking excess or prolonged Cas9 activity in cells is considered as one means of solving this problem. Here, we report the development of an inhibitory DNA aptamer against Cas9 by means of in vitro selection (systematic evolution of ligands by exponential enrichment) and subsequent screening with an in vitro cleavage assay. The inhibitory aptamer could bind to Cas9 at low nanomolar affinity and partially form a duplex with CRISPR RNA, contributing to its inhibitory activity. We also demonstrated that improving the inhibitory aptamer with locked nucleic acids efficiently suppressed Cas9-directed genome editing in cells and reduced off-target genome editing. The findings presented here might enable the development of safer and controllable genome editing for biomedical research and gene therapy.
Identification, Characterization, and Mutational Analysis of a Probable KEAP1 Ortholog in Rice (Oryza sativa L.)

The Kelch-like ECH-associated protein 1 (KEAP1)-nuclear factor E2-related factor 2 (NRF2) module is a key component in the detoxification and antioxidant system in animals, which plays crucial roles in cell homeostasis and cytoprotection, and consequently in carcinogenesis and disease development. However, this system seems to have diverged throughout evolution across different organisms, and the question of whether a similar system exists in plants has thus far remained unresolved. In this study, a KEAP1 ortholog was identified in rice (Oryza sativa L., OsKEAP1) and its properties were characterized via in silico and laboratory studies. To reveal OsKEAP1’s function, two knockdown mutants, oskeap1-1 and oskeap1-2, were generated by targeted mutagenesis in the 5′ untranslated region (UTR) using the CRISPR-Cas9 system. In silico analysis showed that OsKEAP1 has a Kelch-repeat domain which is identical to those of animals and a plant-specific development and cell death (DCD) domain in place of the broad-complex, tramtrack, bric-a-brac (BTB) domain found in animals. Orthologs of OsKEAP1 are present across plant species and all have the DCD domain and the Kelch-repeat domain. OsKEAP1 was proven to be localized to both the cytoplasm and nucleus, in contrast to the exclusive cytoplasm localization of animal KEAP1. Single nucleotide insertions in the 5′ UTR significantly reduced the transcription level of OsKEAP1 in the oskeap1-1 and oskeap1-2 mutants. The oskeap1 mutations greatly impaired plant growth and development, resulting in significant declines in a majority of agronomic and yield-related traits, i.e., plant height, panicle length, grain number per plant, and seed-set rate. The downregulation of OsKEAP1 increased the levels of H2O2, malondialdehyde, and proline while significantly decreasing the expression of two catalase genes in seedlings grown under normal and salt-stressed conditions. The changes in the above phenotypes are either positively or negatively correlated with the degree of OsKEAP1 downregulation. Altogether, we identified a probable KEAP1 ortholog in rice, revealed its unique subcellular localization, and demonstrated its important functions in vegetative and reproductive growth via regulation of the antioxidant response in plants.
Impaired recovery is associated with increased injury and illness: A retrospective study of 536 female netball athletes

Sport science and medicine practitioners are interested in the relationships between training load, injury, and illness. The extent to which training preparedness is associated with workload‐related injury and illness risk is debated. Therefore, this study applied multi‐level mixed effect logistic regression to investigate time‐dependent (±7‐ and ±28‐day) relationships between training preparedness (fatigue, mood, motivation, soreness, stress, sleep duration, and quality), training load, injury, and illness in 536 elite and pre‐elite female netball athletes. Absolute risk (AR ± 95% CI) of sustaining an injury (0.98 ± 0.06%, n = 1122 injuries, N = 254 athletes) or illness (1.09 ± 0.10%, n = 2881, N = 432 athletes) was calculated. All training preparedness variables combined resulted in an absolute risk of 0.88%‐5.88% and 0.87%‐20% for injury and illness, respectively. Injury and illness had significant (P < .05) bidirectional (ie, both increased and decreased) associations with physical (soreness) and physiological (sleep duration and quality), while illness also had negative (mood, motivation) and positive (stress) associations with psychological training preparedness variables. Low sleep duration in the 48‐h period prior was associated (P = .005) with increased injury risk (OR = 0.91 ± 0.03; AR = 4.00%), while “very poor” sleep quality (OR = 0.59 ± 0.02; AR = 7.83%) or extremes of too little (<5 hours, OR = 1.01 ± 0.03; AR = 3.13%‐14.29%) and too much (>10 hours, OR = 1.01 ± 0.03; AR = 2.61%‐10.98%) sleep had bidirectional associations (P < .001) with an increased illness risk. Changes in training preparedness variables demonstrated bidirectional associations with injury and illness. These outcomes suggest that sport science and medicine practitioners should monitor sleep, physical, and psychological recovery status, to aid early detection and intervention regarding injury and illness symptomology.
Promoting Clinical Conversations about Lung Cancer Screening: Exploring the Role of Perceived Online Social Support

The perceived availability of online social support may contribute to patient-provider conversations about lung cancer screening. This study examines how the perceived availability of instrumental and emotional online social support is associated with patient-provider communication about lung cancer screening among adults who meet U.S. Preventive Services Taskforce (USPSTF) eligibility criteria and live with a COPD diagnosis. In April 2018, 575 adults completed an online survey after being recruited from a large southeastern academic medical center’s broad research registry and website listing. Nearly half of the participants were 55-to-80 years old (41%), a current or former smoker who had quit smoking within the past 15 years (42%), and reported a smoking prevalence of 30 pack years or more (PPY; 41%). Results demonstrate that having a COPD diagnosis, identifying as male, and being a current or former tobacco smoker resulted in greater odds of having a clinical conversation about lung cancer screening. Conversely, meeting the 30 PPY smoking and 55-to-80 age thresholds lowered the odds of having these conversations. A high degree of instrumental and emotional online social support was associated with a greater incidence of annual patient-provider conversations about screening. This combination of perceived online social support was especially useful for patients with COPD.
Intestinal absorption and hepatic elimination of drugs in high‐fat high‐cholesterol diet‐induced non‐alcoholic steatohepatitis rats: exemplified by simvastatin

Altered drug pharmacokinetics is a significant concern in non‐alcoholic steatohepatitis (NASH) patients. Although high‐fat high‐cholesterol (HFHC) diet‐induced NASH (HFHC‐NASH) rats could simulate the typical dysregulation of cholesterol in NASH patients, experimental investigation on the altered drug pharmacokinetics in this model are limited. Thus, the present study comprehensive investigates the nature of such altered pharmacokinetics using simvastatin as the model drug.
The Value of Strain Elastography in Predicting Autoimmune Thyroiditis

Chronic autoimmune thyroiditis (CAT) defines a diffuse intrathyroidal lymphocytic infiltration associating a destructive process of the thyroid follicles, most commonly in evolution developing hypothyroidism. Typical ultrasound changes may suggest the presence of the disease. This study aims to evaluate the performance of strain elastography in detecting autoimmune thyroiditis as an additional tool to the conventional ultrasound examination. A total of 250 patients were enrolled in the study; 180 had biochemical confirmation of CAT, the other 70 healthy subjects represented the control group. All patients were examined clinically and by means of conventional thyroid ultrasound (US) and real-time elastography using a Hitachi Preirus machine (5–15 MHz linear probe). Five valid measurements for the parenchyma/muscle strain ratios (SR) were taken for each subject, considering the mean value for analysis. A mean SR value above 1.64 was found to predict the presence of CAT with sensitivity (Sen) 69%, specificity p92%, positive predictive value (PPV) 95.4%, negative predictive value (NPV) 54% and area under receiver operating characteristic (AUROC) 0.87. Moreover, when comparing the mean values for SR, significantly higher values were found in CAT patients compared with the controls (2.81 ± 2.11 vs. 1.03 ± 0.51; p < 0.0001). Of the 180 CAT subjects, 92 were on thyroid hormone replacement therapy; significantly higher values were detected for patients under therapy compared with asymptomatic cases (3.45 ± 2.53 vs. 2.15 ± 1.27, p < 0.0001). A cut-off value of 2.94 was established for identifying CAT patients who needed hormonal treatment (Sen 52.3%, Sp 83.7%, PPV 75.4%, NPV 64.7% and AUROC 0.66). No correlation was found between stiffness and antibody titers nor for functional status. Elastography does add valuable information to the US evaluation of cases with autoimmune thyroiditis.
Twisted Intramolecular Charge Transfer State of a “Push-Pull” Emitter

The excited state Raman spectra of 4-dicyanomethylene-2-methyl-6-(p-dimethylaminostyryl)-4H-pyran (DCM) in the locally-excited (LE) and the intramolecular charge transfer (ICT) states have been separately measured by time-resolved stimulated Raman spectroscopy. In a polar dimethylsulfoxide solution, the ultrafast ICT of DCM with a time constant of 1.0 ps was observed in addition to the vibrational relaxation in the ICT state of 4–7 ps. On the other hand, the energy of the ICT state of DCM becomes higher than that of the LE state in a less polar chloroform solution, where the initially-photoexcited ICT state with the LE state shows the ultrafast internal conversion to the LE state with a time constant of 300 fs. The excited-state Raman spectra of the LE and ICT state of DCM showed several major vibrational modes of DCM in the LE and ICT conformer states coexisting in the excited state. Comparing to the time-dependent density functional theory simulations and the experimental results of similar push-pull type molecules, a twisted geometry of the dimethylamino group is suggested for the structure of DCM in the S1/ICT state.
Automatic segmentation of prostate magnetic resonance imaging using generative adversarial networks.

BACKGROUND Automatic and detailed segmentation of the prostate using magnetic resonance imaging (MRI) plays an essential role in prostate imaging diagnosis. Traditionally, prostate gland was manually delineated by the clinician in a time-consuming process that requires professional experience of the observer. Thus, we proposed an automatic prostate segmentation method, called SegDGAN, which is based on a classic generative adversarial network model. MATERIAL AND METHODS The proposed method comprises a fully convolutional generation network of densely con- nected blocks and a critic network with multi-scale feature extraction. In these computations, the objective function is optimized using mean absolute error and the Dice coefficient, leading to improved accuracy of segmentation results and correspondence with the ground truth. The common and similar medical image segmentation networks U-Net, FCN, and SegAN were selected for qualitative and quantitative comparisons with SegDGAN using a 220-patient dataset and the public datasets. The commonly used segmentation evaluation metrics DSC, VOE, ASD, and HD were used to compare the accuracy of segmentation between these methods. RESULTS SegDGAN achieved the highest DSC value of 91.66%, the lowest VOE value of 15.28%, the lowest ASD values of 0.51 mm and the lowest HD value of 11.58 mm with the clinical dataset. In addition, the highest DSC value, and the lowest VOE, ASD and HD values obtained with the public data set PROMISE12 were 86.24%, 23.60%, 1.02 mm and 7.57 mm, respectively. CONCLUSIONS Our experimental results show that the SegDGAN model have the potential to improve the accuracy of MRI-based prostate gland segmentation. Code has been made available at: https://github.com/w3user/SegDGAN.
Nitro-fatty acids as activators of hSIRT6 deacetylase activity

Sirtuin 6, SIRT6, is critical for both glucose and lipid homeostasis and is involved in maintaining genomic stability under conditions of oxidative DNA damage such as those observed in age-related diseases. There is an intense search for modulators of SIRT6 activity, however, not many specific activators have been reported. Long acyl-chain fatty acids have been shown to increase the weak in vitro deacetylase activity of SIRT6 but this effect is modest at best. Herein we report that electrophilic nitro-fatty acids (nitro-oleic acid and nitro-conjugated linoleic acid) potently activate SIRT6. Binding of the nitro-fatty acid to the hydrophobic crevice of the SIRT6 active site exerted a moderate activation (2-fold at 20 μm), similar to that previously reported for non-nitrated fatty acids. However, covalent Michael adduct formation with Cys-18, a residue present at the N terminus of SIRT6 but absent from other isoforms, induced a conformational change that resulted in a much stronger activation (40-fold at 20 μm). Molecular modeling of the resulting Michael adduct suggested stabilization of the co-substrate and acyl-binding loops as a possible additional mechanism of SIRT6 activation by the nitro-fatty acid. Importantly, treatment of cells with nitro-oleic acid promoted H3K9 deacetylation, whereas oleic acid had no effect. Altogether, our results show that nitrated fatty acids can be considered a valuable tool for specific SIRT6 activation, and that SIRT6 should be considered as a molecular target for in vivo actions of these anti-inflammatory nitro-lipids.
Automatic Gene Function Prediction in the 2020’s

The current rate at which new DNA and protein sequences are being generated is too fast to experimentally discover the functions of those sequences, emphasizing the need for accurate Automatic Function Prediction (AFP) methods. AFP has been an active and growing research field for decades and has made considerable progress in that time. However, it is certainly not solved. In this paper, we describe challenges that the AFP field still has to overcome in the future to increase its applicability. The challenges we consider are how to: (1) include condition-specific functional annotation, (2) predict functions for non-model species, (3) include new informative data sources, (4) deal with the biases of Gene Ontology (GO) annotations, and (5) maximally exploit the GO to obtain performance gains. We also provide recommendations for addressing those challenges, by adapting (1) the way we represent proteins and genes, (2) the way we represent gene functions, and (3) the algorithms that perform the prediction from gene to function. Together, we show that AFP is still a vibrant research area that can benefit from continuing advances in machine learning with which AFP in the 2020s can again take a large step forward reinforcing the power of computational biology.
Impact of sars-cov-2 interventions on dengue transmission

An estimated 105 million dengue infections occur per year across 120 countries, where traditional vector control is the primary control strategy to reduce contact between mosquito vectors and people. The ongoing sars-cov-2 pandemic has resulted in dramatic reductions in human mobility due to social distancing measures; the effects on vector-borne illnesses are not known. Here we examine the pre and post differences of dengue case counts in Malaysia, Singapore and Thailand, and estimate the effects of social distancing as a treatment effect whilst adjusting for temporal confounders. We found that social distancing is expected to lead to 4.32 additional cases per 100,000 individuals in Thailand per month, which equates to 170 more cases per month in the Bangkok province (95% CI: 100–242) and 2008 cases in the country as a whole (95% CI: 1170–2846). Social distancing policy estimates for Thailand were also found to be robust to model misspecification, and variable addition and omission. Conversely, no significant impact on dengue transmission was found in Singapore or Malaysia. Across country disparities in social distancing policy effects on reported dengue cases are reasoned to be driven by differences in workplace-residence structure, with an increase in transmission risk of arboviruses from social distancing primarily through heightened exposure to vectors in elevated time spent at residences, demonstrating the need to understand the effects of location on dengue transmission risk under novel population mixing conditions such as those under social distancing policies.