Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiac and Autonomic Dysfunctions Assessed Through Recurrence Quantitative Analysis of Electrocardiogram Signals and an Application to the 6-Hydroxydopamine Parkinson’s Disease Animal Model

A classic method to evaluate autonomic dysfunction is through the evaluation of heart rate variability (HRV). HRV provides a series of coefficients, such as Standard Deviation of n-n intervals (SDNN) and Root Mean Square of Successive Differences (RMSSD), which have well-established physiological associations. However, using only electrocardiogram (ECG) signals, it is difficult to identify proper autonomic activity, and the standard techniques are not sensitive and robust enough to distinguish pure autonomic modulation in heart dynamics from cardiac dysfunctions. In this proof-of-concept study we propose the use of Poincaré mapping and Recurrence Quantification Analysis (RQA) to identify and characterize stochasticity and chaoticity dynamics in ECG recordings. By applying these non-linear techniques in the ECG signals recorded from a set of Parkinson’s disease (PD) animal model 6-hydroxydopamine (6-OHDA), we showed that they present less variability in long time epochs and more stochasticity in short-time epochs, in their autonomic dynamics, when compared with those of the sham group. These results suggest that PD animal models present more “rigid heart rate” associated with “trembling ECG” and bradycardia, which are direct expressions of Parkinsonian symptoms. We also compared the RQA factors calculated from the ECG of animal models using four computational ECG signals under different noise and autonomic modulatory conditions, emulating the main ECG features of atrial fibrillation and QT-long syndrome.
Virtual Interface Environment Workstations

A head-mounted, wide-angle, stereoscopic display system controlled by operator position, voice and gesture has been developed at NASA's Ames Research Center for use as a multipurpose interface environment. This Virtual Interface Environment Workstation (VIEW) system provides a multisensory, interactive display environment in which a user can virtually explore a 360—degree synthesized or remotely sensed environment and can viscerally interact with its components. Primary applications of the system are in telerobotics, management of large-scale integrated information systems, and human factors research. System configuration, research scenarios, and research directions are described.
Longer Poly(U) Stretches in the 3′UTR Are Essential for Replication of the Hepatitis C Virus Genotype 4a Clone in in vitro and in vivo

The 3′ untranslated region (UTR) of the hepatitis C virus (HCV) genome plays a significant role in replication including the poly(U) tract (You and Rice, 2008). Here we established an HCV clone that is infectious in vitro and in vivo, from an Egyptian patient with chronic HCV infection and hepatocellular carcinoma (HCC). First, we inoculated the patient plasma into a humanized chimeric mouse and passaged. We observed HCV genotype 4a propagation in the chimeric mouse sera at 1.7 × 107 copies/mL after 6 weeks. Next, we cloned the entire HCV sequence from the HCV-infected chimeric mouse sera using RT-PCR, and 5′ and 3′ RACE methodologies. We obtained first a shorter clone (HCV-G4 KM short, GenBank: AB795432.1), which contained 9,545 nucleotides with 341 nucleotides of the 5′UTR and 177 nucleotides of the 3′UTR, and this was frequently obtained for unknown reasons. We also obtained a longer clone by dividing the HCV genome into three fragments and the poly (U) sequences. We obtained a longer 3′UTR sequence than that of the HCV-G4 KM short clone, which contained 9,617 nucleotides. This longer clone possessed a 3′-UTR of 249 nucleotides (HCV-G4 KM long, GenBank: AB795432.2), because of a 71-nucleotide longer poly (U) stretch. The HCV-G4-KM long clone, but not the HCV-G4-KM short clone, could establish infection in human hepatoma HuH-7 cells. HCV RNAs carrying a nanoluciferase (NL) reporter were also constructed and higher replication activity was observed with G4-KM long-NL in vitro. Next, both short and long RNAs were intra-hepatically injected into humanized chimeric mice. Viral propagation was only observed for the chimeric mouse injected with the HCV-G4 KM long RNA in the sera after 21 days (1.64 × 106 copies/mL) and continued until 10 weeks post inoculation (wpi; 1.45–4.74 × 107 copies/mL). Moreover, sequencing of the HCV genome in mouse sera at 6 wpi revealed the sequence of the HCV-G4-KM long clone. Thus, the in vitro and in vivo results of this study indicate that the sequence of the HCV-G4-KM long RNA is that of an infectious clone.
Assessment of Prognostic Value of Aspartate Aminotransferase-to-Platelet Ratio Index in Patients With Hepatocellular Carcinoma: Meta-Analysis of 28 Cohort Studies

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally; it is valuable to predict its prognosis after treatment. Aspartate aminotransferase-to-platelet index (APRI), a non-invasive biomarker consists of two routine test parameters easily available in all the patients. Our study aimed to investigate whether APRI can serve as an independent prognostic marker in the patients with HCC. Methods: We extensively searched PubMed, Embase, and Web of Science databases on June 20, 2021 to determine all relevant literature. The studies that explored the association between the APRI levels and prognosis of patients with HCC and reported risk estimate data were included. The Newcastle-Ottawa Scale was used to assess the quality of the included studies. Results: A total of 1,097 articles were initially identified, of which 28 studies involving 11,041 patients met the eligibility criteria for the meta-analysis. The pooled hazard ratios (HRs) for overall survival (OS) and disease-free survival (DFS) were 1.77 (95% CI: 1.53–2.05, P < 0.001) and 1.59 (95% CI: 1.47–1.71, P < 0.001), respectively, suggesting a significant correlation between the increased APRI levels and poor prognosis in the patients with HCC. In the subgroup analyses, statistical significance of the correlation disappeared in the Korean and Japanese population and in the patients undergoing transarterial chemoembolization (TACE). Of note, the current results may be overestimated due to publication bias, but the conclusion remained unchanged when the bias was adjusted. Conclusion: High APRI levels are associated with poor OS and DFS in the patients with HCC. In most cases, pretreatment APRI can be used as an independent prognostic factor, but it is necessary to incorporate other predictive prognostic systems to ensure accuracy. Further studies are needed to determine the specific beneficiary population and the optimal cutoff value.
Optical Characteristics and Applications of AIE Racemic C6-Unsubstituted Tetrahydropyrimidines

Racemic C6-unsubstituted tetrahydropyrimidines (THPs) are the products of an efficient five-component reaction that we developed. THPs show strong AIE characteristics, that is, completely no fluorescence in different solvents but strong emission with fluorescence quantum yields (Φ F) up to 100% upon aggregation. However, the Φ F values of their pure enantiomers are lower than 46%. Unlike common AIE compounds with crowded aryl rotors on a π-bond or on an aryl ring, THPs have three completely non-crowded aryl rotors on a non-aromatic chiral central ring (tetrahydropyrimidine). In this mini review, we first discuss the AIE characteristics of THPs and the influences of molecular structures on their molecular packing modes and optical properties, and then present their applications and forecast the development of other racemic AIE compounds.
Comprehensive Analyses of Type 1 Diabetes Ketosis- or Ketoacidosis-Related Genes in Activated CD56+CD16+ NK Cells

Objectives Alterations in natural killer (NK) cells activity cause damage to pancreatic islets in type 1 diabetes mellitus (T1DM). The aim of this study is to identify T1DM ketosis- or ketoacidosis-related genes in activated CD56+CD16+ NK cells. Methods Microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed using the GEO2R tool. Enrichment analyses were performed using Metascape online database and GSEA software. Cell-specific gene co-expression network was built using NetworkAnalyst tools. Cytoscape software was used to identify hub genes and construct co-expressed networks. Target miRNAs were predicted based on the DIANA-micro T, miRDB, and miRWalk online databases. Results A total of 70 DEGs were identified between T1DM patients recovered from ketosis or ketoacidosis and healthy control blood samples in GSE44314. Among the DEGs, 10 hub genes were screened out. The mature NK cell-specific gene co-expression network for DEGs in T1DM was built using NetworkAnalyst tools. DEGs between activated CD56+CD16+ NK cells and CD56brightCD16- NK cells were identified from GSE1511. After intersection, 13 overlapping genes between GSE44314 and GSE1511 microarray datasets were screened out, in which 7 hub genes were identified. Additionally, 59 target miRNAs were predicted according to the 7 hub genes. After validating with the exosome miRNA expression profile dataset of GSE97123, seven differentially expressed miRNAs (DEmiRNAs) in plasma-derived exosome were selected. Finally, a mRNA–miRNA network was constructed, which was involved in the T1DM ketosis or ketoacidosis process. Conclusion This work identified seven hub genes in activated CD56+CD16+ NK cells and seven miRNAs in plasma-derived exosome as potential predictors of T1DM ketoacidosis, which provided a novel insight for the pathogenesis at the transcriptome level.
Genetic Diversity and Natural Selection of Plasmodium vivax Duffy Binding Protein-II From China-Myanmar Border of Yunnan Province, China

Malaria incidence has declined dramatically over the past decade and China was certified malaria-free in 2021. However, the presence of malaria in border areas and the importation of cases of malaria parasites are major challenges for the consolidation of the achievements made by China. Plasmodium vivax Duffy binding protein (PvDBP) performs a significant role in erythrocyte invasion, and is considered a promising P. vivax vaccine. However, the highly polymorphic region of PvDBP (PvDBP-II) impedes the development of blood-stage vaccine against P. vivax. In this study, we investigated the genetic diversity and natural selection of PvDBP-II among 124 P. vivax isolates collected from the China-Myanmar border (CMB) in Yunnan Province, China, during 2009–2011. To compare genetic diversity, natural selection, and population structure with CMB isolates, 85 pvdbp-II sequences of eastern Myanmar isolates were obtained from GenBank. In addition, global sequences of pvdbp-II were retrieved from GenBank to establish genetic differentiation relationships and networks with the CMB isolates. In total, 22 single nucleotide polymorphisms reflected in 20 non-synonymous and two synonymous mutations were identified. The overall nucleotide diversity of PvDBP-II from the 124 CMB isolates was 0.0059 with 21 haplotypes identified (Hd = 0.91). The high ratio of non-synonymous to synonymous mutations suggests that PvDBP-II had evolved under positive selection. Population structure analysis of the CMB and eastern Myanmar isolates were optimally grouped into five sub-populations (K = 5). Polymorphisms of PvDBP-II display that CMB isolates were genetically diverse. Mutation, recombination, and positive selection promote polymorphism of PvDBP-II of P. vivax population. Although low-level genetic differentiation in eastern Myanmar was identified along with the more effective malaria control measures, the complexity of population structure in malaria parasites has maintained. In conclusion, findings from this study advance knowledge of the understanding of the dynamic of P. vivax population, which will contribute to guiding the rational design of a PvDBP-II based vaccine.
Media Exposure and the Risk of Post-Traumatic Stress Disorder Following a Mass traumatic Event: An In-silico Experiment

Introduction: Following mass traumatic events, greater exposure to traditional media like television (TV) about the event is associated with higher burden of post-traumatic stress disorder (PTSD). However, we know little about how social media exposure, combined with other media sources, shapes the population burden of PTSD following mass traumatic events. Materials and Methods: We built a microsimulation of 1,18,000 agents that was demographically comparable to the population of Parkland and Coral Springs, Florida that experienced the Stoneman Douglas High School shooting in 2018. We parametrized the model using data from prior traumatic events and built an internal social network structure to facilitate the estimation of community PTSD prevalence following exposure to TV and social media coverage of the shooting. Results: Overall, PTSD prevalence in the community due to exposure to TV coverage of the shooting was 3.1%. Shifting the whole population's hours of TV watching to the lower half of the population distribution decreased PTSD prevalence to 1.3% while increasing TV watching to the upper half of the distribution increased the prevalence to 3.5%. Casual (i.e., viewing posts) social media use in addition to exposure to TV coverage increased PTSD prevalence to 3.4%; overall prevalence increased to 5.3% when agents shared videos related to the shooting on social media. Conclusion: This microsimulation shows that availability and exposure to media coverage of mass traumatic events, particularly as social media becomes more ubiquitous, has the potential to increase community PTSD prevalence following these events. Future research could fruitfully examine the mechanisms that might explain these associations and potential interventions that can mitigate the role of media in shaping the mental health of populations following traumatic events.
Effect of Time Interval From Diagnosis to Treatment on Economic Burden in Families of Children With Autism Spectrum Disorder

The study aimed to investigate the economic costs in families of children with autism spectrum disorder (ASD) and explored how the time interval from diagnosis to treatment time interval from the date children first diagnosed with ASD to the date of first speech/behavior treatment influenced the economic costs. It was a cross-sectional study that recruited families with autistic children in Changsha, Hunan Province of China during March to November 2018. A self-designed questionnaire was applied to collect ASD-related economic costs in the two vital periods including the 12-month period after diagnosis and the most recent 12 months during the course of ASD. In total, 136 families with autistic children completed the interview. The results showed that 46.3% of children started intervention within 1 month. The median of total economic costs of these families in the 12-month period after diagnosis and the most recent 12 months was 26,502.26 RMB and 29,411.91 RMB, respectively. Compared with the time interval shorter than 1 month, time interval over 6 months was significantly associated with high direct economic costs (βSD = 0.308, 95% CI = 0.177, 1.254), inpatient/outpatient and drugs costs (βSD = 0.276, 95% CI = 0.104, 1.181), direct non-medical costs (βSD = 0.287, 95% CI = 0.140, 1.206), and total economic burden (βSD = 0.311, 95% CI = 0.186, 1.262); besides, time interval between 4 and 6 months was significantly related to large indirect costs (βSD = 0.230, 95% CI = 0.098, 1.363) in the 12-month period after diagnosis. Similarly, time interval between 1 and 3 months was significantly associated with high direct non-medical costs (βSD = 0.198, 95% CI = 0.004, 1.013) in the 12-month period after diagnosis. However, time interval from diagnosis to treatment was not correlated to economic costs in the recent 12 months. In the long term, shortening the time interval from diagnosis to treatment would reduce the economic burden on families, especially in the 12-month period after diagnosis.
Magnetic Seizure Therapy Compared to Electroconvulsive Therapy for Schizophrenia: A Randomized Controlled Trial

Background: Magnetic seizure therapy (MST) is a potential alternative to electroconvulsive therapy (ECT). However, reports on the use of MST for patients with schizophrenia, particularly in developing countries, which is a main indication for ECT, are limited. Methods: From February 2017 to July 2018, 79 inpatients who met the DSM-5 criteria for schizophrenia were randomized to receive 10 sessions of MST (43 inpatients) or ECT (36 inpatients) over the course of 4 weeks. At baseline and 4-week follow-up, the Positive and Negative Syndrome Scale (PANSS) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) were used to assess symptom severity and cognitive functions, respectively. Results: Seventy-one patients who completed at least half of the treatment protocol were included in the per-protocol analysis. MST generated a non-significant larger antipsychotic effect in terms of a reduction in PANSS total score [g = 0.17, 95% confidence interval (CI) = −0.30, 0.63] and response rate [relative risk (RR) = 1.41, 95% CI = 0.83–2.39]. Twenty-four participants failed to complete the cognitive assessment as a result of severe psychotic symptoms. MST showed significant less cognitive impairment over ECT in terms of immediate memory (g = 1.26, 95% CI = 0.63–1.89), language function (g =1.14, 95% CI = 0.52–1.76), delayed memory (g = 0.75, 95% CI = 0.16–1.35), and global cognitive function (g = 1.07, 95% CI = 0.45–1.68). The intention-to-treat analysis generated similar results except for the differences in delayed memory became statistically insignificant. Better baseline cognitive performance predicted MST and ECT response. Conclusions: Compared to bitemporal ECT with brief pulses and age-dose method, MST had similar antipsychotic efficacy with fewer cognitive impairments, indicating that MST is a promising alternative to ECT as an add-on treatment for schizophrenia. Clinical Trial Registration: ClinicalTrials.gov, identifier: NCT02746965.
Automated Individual Cattle Identification Using Video Data: A Unified Deep Learning Architecture Approach

Individual cattle identification is a prerequisite and foundation for precision livestock farming. Existing methods for cattle identification require radio frequency or visual ear tags, all of which are prone to loss or damage. Here, we propose and implement a new unified deep learning approach to cattle identification using video analysis. The proposed deep learning framework is composed of a Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory (BiLSTM) with a self-attention mechanism. More specifically, the Inception-V3 CNN was used to extract features from a cattle video dataset taken in a feedlot with rear-view. Extracted features were then fed to a BiLSTM layer to capture spatio-temporal information. Then, self-attention was employed to provide a different focus on the features captured by BiLSTM for the final step of cattle identification. We used a total of 363 rear-view videos from 50 cattle at three different times with an interval of 1 month between data collection periods. The proposed method achieved 93.3% identification accuracy using a 30-frame video length, which outperformed current state-of-the-art methods (Inception-V3, MLP, SimpleRNN, LSTM, and BiLSTM). Furthermore, two different attention schemes, namely, additive and multiplicative attention mechanisms were compared. Our results show that the additive attention mechanism achieved 93.3% accuracy and 91.0% recall, greater than multiplicative attention mechanism with 90.7% accuracy and 87.0% recall. Video length also impacted accuracy, with video sequence length up to 30-frames enhancing identification performance. Overall, our approach can capture key spatio-temporal features to improve cattle identification accuracy, enabling automated cattle identification for precision livestock farming.
3D Computational Modeling of Bleb Initiation Dynamics

Blebbing occurs in cells under high cortical tension when the membrane locally detaches from the actin cortex, resulting in pressure-driven flow of the cytosol and membrane expansion. Some cells use blebs as leading edge protrusions during cell migration, particularly in 3D environments such as a collagen matrix. Blebs can be initiated through either a localized loss of membrane-cortex adhesion or ablation of the cortex in a region. Bleb morphologies resulting from different initiation mechanisms have not been studied in detail, either experimentally or with theoretical models. Additionally, material properties of the cytoplasm, such as elasticity, have been shown to be important for limiting bleb size. A 3D dynamic computational model of the cell is presented that includes mechanics and the interactions of the cytoplasm, the actin cortex, the cell membrane, and the cytoskeleton. The model is used to quantify bleb expansion dynamics and shapes that result from simulations using different initiation mechanisms. The cytoplasm is modeled as a both viscous fluid and as a poroelastic material. Results from model simulations with a viscous fluid cytoplasm model show much broader blebs that expand faster when they are initiated via cortical ablation than when they are initiated by removing only membrane-cortex adhesion. Simulation results using the poroelastic model of the cytoplasm provide qualitatively similar bleb morphologies regardless of the initiation mechanism. Parameter studies on bleb expansion time, cytoplasmic stiffness, and permeability reveal different scaling properties, namely a smaller power-law exponent, in 3D simulations compared to 2D ones.
Versatile Interferometer For Shop Use

The Shack interferometer described i this paper is an unequal-path instrument which has demonstrated its utility in an optical shop environment. Its light weight and compact size make it a favored test instrument. In its standard configuration it is used in a variety of optical shop tests. ty the addition of a knife blade or wire, the instrument is converted to a monochromatic Foucault or wire tester thereby increasing its versatility. Its simplicity and low cost allow it to be readily built into special purpose test fixtures.
Explicit High Order One-Step Methods for Decoupled Forward Backward Stochastic Differential Equations

By using the Feynman-Kac formula and combining with Itô-Taylor expansion and finite difference approximation, we first develop an explicit third order onestep method for solving decoupled forward backward stochastic differential equations. Then based on the third order one, an explicit fourth order method is further proposed. Several numerical tests are also presented to illustrate the stability and high order accuracy of the proposed methods. AMS subject classifications: 65C20, 65C30, 60H35, 65H30