Miracle-dz/UniFAR-FTUs huggingface dataset:
Wild grapevines as rootstock regulate the oxidative defense system of in vitro grafted scion varieties under drought stress

The narrow genetic base of modern cultivars is becoming a key bottleneck for crop improvement and the use of wild relatives is an appropriate approach to improve the genetic diversity of crops to manage the sustainable production under different abiotic and biotic constraints. In Pakistan, wild germplasm of grapevine viz Dakh, Toran, and Zarishk belong to Vitis vinifera subsp. sylvestris and Fatati belong to Vitis vinifera subsp. sativa is naturally present in humid and sub-humid areas of mountainous and sub-mountainous regions and showed varying level of tolerance against drought stress but have not been evaluated as rootstock. In this study, different tolerant behavior of wild grapevines as rootstock in grafted scion varieties were explored under different levels of PEG-6000 mediated drought stress i.e., -4.00, -6.00, and -8.00 bars. In response to drought stress, wild grapevines evoked several non-enzymatic and enzymatic activities. Among non-enzymatic activities, total chlorophyll contents of commercial varieties were sustained at higher level when grafted on wild grapevines Dakh and Fatati which subsequently reduced the damage of cell membrane via MDA. Whereas, to cope the membranous damage due to excessive cellular generation of ROS, wild grapevines triggered the enhanced activities of SOD to dismutase the free oxygen radicals into H2O2, then CAT enzyme convert the H2O2 into water molecules. Higher accumulation of ROS in commercial scion varieties were also coped by wild grapevines Dakh and Fatati through the upregulation of POD and APX enzymes activities. Based on these enzymatic and non-enzymatic indices, biplot and cluster analysis classified the wild grapevines as rootstock into three distinct categories comprises on relatively tolerant i.e., Dakh (Vitis vinifera subsp. sylvestris) and Fatati (Vitis vinifera subsp. sativa), moderate tolerant i.e., Toran (Vitis vinifera subsp. sylvestris) and relatively susceptible category i.e., Zarishk (Vitis vinifera subsp. sylvestris).
Montmorillonite K10 Clay Catalyzed Synthesis of Novel β‐Aminocarbonyl Compounds and Their Biological Evaluation

An efficient and reusable green catalyst for the synthesis of β‐aminocarbonyl compounds has been developed. In this new and greener approach, β‐aminocarbonyl compounds (1a–1r) were obtained by Montmorillonite K10 clay catalyzed reaction of aryl amines, aliphatic/aromatic aldehydes and β‐ketoesters. Molecular docking investigations were performed for all compounds (1a–1r) with the proteins PDB ID: 1JIJ and 1KZN for S. aureus and E. coli, respectively. For all compounds good to strong interactions with the active sites were observed. The biological activities of β‐aminocarbonyl compounds were further assessed for their antibacterial and antioxidant activities. The results confirmed that β‐aminocarbonyl compounds could be further developed into new drugs with potent antibacterial and antioxidant activities.
Improving diabetes care of community-dwelling underserved older adults

ABSTRACT Background: Diabetes care among rural underserved older adults is negatively affected by social determinants of health (SDOH). Although there is an increased awareness of this problem, evidence-based clinical and community interventions are not widely integrated. This project implemented telemedicine and community health worker (CHW) interventions to improve diabetes management and outcomes. Local Problem: One in five older adults with diabetes mellitus (DM) at a Federally Qualified Health Center in southwest Ohio has uncontrolled disease, largely due to their limited resources and ability to participate in routine clinical management. Methods: This quality improvement project used a pre–post intervention design. Participants were adults aged ≥65 years with uncontrolled DM type 1 or 2. The outcomes of interest included A1C values, diabetes self-care activities, diabetes knowledge, and patient and health care provider (HCP) satisfaction levels. Interventions: The project involved biweekly CHW home visits and diabetes self-management education for 12 weeks. The CHWs, with supervision from a nurse practitioner, conducted SDOH assessments and basic education, and facilitated same-day telemedicine appointments with the HCP to reinforce disease management. Results: The A1C levels and diabetes knowledge of older adults significantly improved after three months. However, there were no statistically significant changes in diabetes self-care activities. The patients and HCPs were highly satisfied with the project interventions. Conclusions: This project delivered patient-centered and equitable diabetes care services that were previously unavailable to underserved older patients, while demonstrably improving outcomes. Future research should evaluate the cost-effectiveness, long-term impact, and sustainability of the project in other primary care settings.
Diffusion magnetic resonance imaging connectome features are predictive of functional lateralization of semantic processing in the anterior temporal lobes

Assessment of regional language lateralization is crucial in many scenarios, but not all populations are suited for its evaluation via task‐functional magnetic resonance imaging (fMRI). In this study, the utility of structural connectome features for the classification of language lateralization in the anterior temporal lobes (ATLs) was investigated. Laterality indices for semantic processing in the ATL were computed from task‐fMRI in 1038 subjects from the Human Connectome Project who were labeled as stronger rightward lateralized (RL) or stronger leftward to bilaterally lateralized (LL) in a data‐driven approach. Data of unrelated subjects (n = 432) were used for further analyses. Structural connectomes were generated from diffusion‐MRI tractography, and graph theoretical metrics (node degree, betweenness centrality) were computed. A neural network (NN) and a random forest (RF) classifier were trained on these metrics to classify subjects as RL or LL. After classification, comparisons of network measures were conducted via permutation testing. Degree‐based classifiers produced significant above‐chance predictions both during cross‐validation (NN: AUC–ROC[CI] = 0.68[0.64–0.73], accuracy[CI] = 68.34%[63–73.2%]; RF: AUC–ROC[CI] = 0.7[0.66–0.73], accuracy[CI] = 64.81%[60.9–68.5]) and testing (NN: AUC–ROC[CI] = 0.69[0.53–0.84], accuracy[CI] = 68.09[53.2–80.9]; RF: AUC–ROC[CI] = 0.68[0.53–0.84], accuracy[CI] = 68.09[55.3–80.9]). Comparison of network metrics revealed small effects of increased node degree within the right posterior middle temporal gyrus (pMTG) in subjects with RL, while degree was decreased in the right posterior cingulate cortex (PCC). Above‐chance predictions of functional language lateralization in the ATL are possible based on diffusion‐MRI connectomes alone. Increased degree within the right pMTG as a right‐sided homologue of a known semantic hub, and decreased hubness of the right PCC may form a structural basis for rightward‐lateralized semantic processing.
Emerging stock market reactions to shocks during various crisis periods

This study investigates granger causal linkages among six Asian emerging stock markets and the US market over the period 2002–2020, taking into account several crisis periods. The pairwise Granger causality tests for investigating the short-run causality show significant bi- and uni-directional causal relationships in those markets and evidence that they have become more internationally integrated after every crisis period. An exception is Bangladesh with almost no significant short-term causal linkages with other markets. For understanding, how the financial linkages amplify volatility spillover effects, we apply the GARCH-M model and find that volatility and return spillovers act very inversely over time. However, market interface is weak before the crisis periods and becomes very strong during the financial crisis and US-China economic policy uncertainty periods. The US market plays a dominant role during the financial crisis and COVID-19 periods. Further analysis using the VAR model shows that a large proportion of the forecast variance of the Asian emerging stock markets is affected by the S&P 500 and that market shock starts to rise notably from the 1 to 10 period. The overall findings could provide important policy implications in the six countries under study regarding hedging, trading strategies, and financial market regulation.
The role of interfacial intermixing on HAMR dynamics in bilayer media

We use an atomistic spin model to simulate FePt-based bilayers for heat assisted magnetic recording (HAMR) devices and investigate the effect of various degrees intermixing that might arise throughout the fabrication, growth and annealing processes, as well as different interlayer exchange couplings, on HAMR magnetisation dynamics. Intermixing can impact the device functionality, but interestingly does not deteriorate the properties of the system. Our results suggest that modest intermixing can prove beneficial and yield an improvement in the magnetisation dynamics for HAMR processes, also relaxing the requirement for weak exchange coupling between the layers. Therefore, we propose that a certain intermixing across the interface could be engineered in the fabrication process to improve HAMR technology further.
Active forgetting requires Sickie function in a dedicated dopamine circuit in Drosophila

Significance Forgetting, the flip side of memory acquisition and consolidation, provides a balance to memory formation processes by removing unused or unwanted memories, or by suppressing their expression. However, the mechanisms underlying forgetting are poorly understood. Here, we identify a molecular and circuit mechanism for active forgetting. Reducing Sickie levels in a single dopamine neuron (DAn) impairs active forgetting by decreasing the ongoing DAn activity. Sickie regulates forgetting by interacting with the presynaptic active zone (AZ) protein Bruchpilot, and altering the structure of the DAn AZ. We propose that Sickie maintains the integrity and function of the DAn AZ by interacting with presynaptic AZ proteins, including Bruchpilot, allowing for the normal ongoing release of DA for active forgetting.
A spatiotemporal atlas of organogenesis in the development of orchid flowers

Abstract Development of floral organs exhibits complex molecular mechanisms involving the co-regulation of many genes specialized and precisely functioning in various tissues and developing stages. Advance in spatial transcriptome technologies allows for quantitative measurement of spatially localized gene abundance making it possible to bridge complex scenario of flower organogenesis with genome-wide molecular phenotypes. Here, we apply the 10× Visium technology in the study of the formation of floral organs through development in an orchid plant, Phalaenopsis Big Chili. Cell-types of early floral development including inflorescence meristems, primordia of floral organs and identity determined tissues, are recognized based on spatial expression distribution of thousands of genes in high resolution. In addition, meristematic cells on the basal position of floral organs are found to continuously function in multiple developmental stages after organ initiation. Particularly, the development of anther, which primordium starts from a single spot to multiple differentiated cell-types in later stages including pollinium and other vegetative tissues, is revealed by well-known MADS-box genes and many other downstream regulators. The spatial transcriptome analyses provide comprehensive information of gene activity for understanding the molecular architecture of flower organogenesis and for future genomic and genetic studies of specific cell-types.
Common Errors in Statistics (and How to Avoid Them)

The provocative title of the book struck me immediately as having potential as a reference for statisticians and practitioners alike. A book that could help users of statistics understand common mistakes and successfully avoid them would be a wonderful asset for many. However, it does seem like a difficult mandate for a 220-page book to satisfy. The authors state in the Preface that the purpose of the book is “to provide a mathematically rigorous but readily understandable foundation for statistical procedures. ” They suggest that the book will be useful “whether you are a practicing statistician or a well-trained scientist who just happens to apply statistics in the pursuit of other science. ”
Intravenous immunoglobulin (IVIg) therapy in hospitalised adult COVID‐19 patients: A systematic review and meta‐analysis

Intravenous immunoglobulin (IVIg) therapy has been suggested as a potential treatment option for hospitalised COVID‐19 patients. The aim of this systematic review and meta‐analysis was to investigate the potential impact of IVIg on mortality and length of hospitalisation in adult COVID‐19 patients. PubMed, Scopus, Web of Science and medRxiv were searched in the week of 20.12. 2021 for English language, prospective trials, and retrospective studies with control groups, reporting on the use of intravenous immunoglobulin therapy in adult hospitalised COVID‐19 patients. Exclusion criteria were: studies evaluating the use of IVIg in paediatric COVID‐19 cases, trials using convalescent anti‐SARS‐CoV‐2 plasma or immunoglobulins derived from convalescent anti‐SARS‐CoV‐2 plasma. A random effects meta‐analysis with subgroup analyses regarding study design and patient disease severity according to WHO criteria was also performed. A total of 13 studies were included, of which 6 were prospective, on a total of 2313 (IVIg = 1104, control = 1209) patient outcomes. Meta‐analysis results indicated that IVIg therapy had no statistically significant effect on mortality (RR 0.91 [0.59; 1.39], p = 0.65, I2 = 69% [46%; 83%]) or length of hospital stay (MD 0.51 [−2.80; 3.81], p = 0.76, I2 = 96% [94%; 98%]). Subgroup analyses indicated no statistically significant impact on either outcome, but prospective studies' results suggested that IVIg may increase the length of hospitalisation in the severe COVID‐19 patient group (MD 2.66 [1.43; 3.90], p < 0.01, I2 = 0% [0%; >90%]). The results of this meta‐analysis do not support use of IVIg in hospitalised adult COVID‐19 patients.
Criterion validity of the brief test of adult cognition by telephone (BTACT) for mild traumatic brain injury

ABSTRACT Objectives There is a growing demand for remote assessment options for measuring cognition after mild traumatic brain injury (mTBI). The current study evaluated the criterion validity of the Brief Test of Adult Cognition by Telephone (BTACT) in distinguishing between adults with mTBI and trauma controls (TC) who sustained injuries not involving the head or neck. Methods The BTACT was administered to the mTBI (n = 46) and TC (n = 35) groups at 1–2 weeks post-injury. Participants also completed the Rivermead Post Concussion Symptoms Questionnaire. Results The BTACT global composite score did not significantly differ between the groups (t(79) = −1.04, p = 0.30); the effect size was small (d = 0.23). In receiver operating characteristic curve analyses, the BTACT demonstrated poor accuracy in differentiating between the groups (AUC = 0.567, SE = 0.065, 95% CI [0.44, 0.69]). The BTACT’s ability to discriminate between mTBI and TCs did not improve after excluding mTBI participants (n = 15) who denied ongoing cognitive symptoms (AUC = 0.567, SE = 0.072, 95% CI [0.43, 0.71]). Conclusions The BTACT may lack sensitivity to subacute cognitive impairment attributable to mTBI (i.e., not explained by bodily pain, post-traumatic stress, and other nonspecific effects of injury).
Developing and validating a prediction model of adolescent major depressive disorder in the offspring of depressed parents

Background Parental depression is common and is a major risk factor for depression in adolescents. Early identification of adolescents at elevated risk of developing major depressive disorder (MDD) in this group could improve early access to preventive interventions. Methods Using longitudinal data from 337 adolescents at high familial risk of depression, we developed a risk prediction model for adolescent MDD. The model was externally validated in an independent cohort of 1,384 adolescents at high familial risk. We assessed predictors at baseline and MDD at follow‐up (a median of 2–3 years later). We compared the risk prediction model to a simple comparison model based on screening for depressive symptoms. Decision curve analysis was used to identify which model‐predicted risk score thresholds were associated with the greatest clinical benefit. Results The MDD risk prediction model discriminated between those adolescents who did and did not develop MDD in the development (C‐statistic = .783, IQR (interquartile range) = . 779, . 778) and the validation samples (C‐statistic = .722, IQR = −.694, .741). Calibration in the validation sample was good to excellent (calibration intercept = .011, C‐slope = .851). The MDD risk prediction model was superior to the simple comparison model where discrimination was no better than chance (C‐statistic = .544, IQR = .536, .572). Decision curve analysis found that the highest clinical utility was at the lowest risk score thresholds (0.01–0.05). Conclusions The developed risk prediction model successfully discriminated adolescents who developed MDD from those who did not. In practice, this model could be further developed with user involvement into a tool to target individuals for low‐intensity, selective preventive intervention.
Measurements of the spin relaxation rate at low magnetic fields in a quantum dot

We measure the relaxation rate $W \equiv T_{1}^{-1}$ of a single electron spin in a quantum dot at magnetic fields from 7 T down to 1.75 T, much lower than previously measured. At 1.75 T we find that $T_{1}$ is 170 ms. We find good agreement between our measurements and theoretical predictions of the relaxation rate caused by the spin-orbit interaction, demonstrating that spin-orbit coupling can account for spin relaxation in quantum dots.
Remarks on the Pressure Distribution over the Surface of an Ellipsoid, Moving Translationally Through a Perfect Fluid

This note, prepared for the National Advisory Committee for Aeronautics, contains a discussion of the pressure distribution over ellipsoids when in translatory motion through a perfect fluid. An easy and convenient way to determine the magnitude of the velocity and of the pressure at each point of the surface of an ellipsoid of rotation is described. The knowledge of such pressure distribution is of great practical value for the airship designer. The pressure distribution over the nose of an airship hull is known to be in such good agreement with the theoretical distribution as to permit basing the computation of the nose stiffening structure on the theoretical distribution of pressure.
Successful combination treatment with azacitidine and venetoclax for a patient with acute myeloid leukemia undergoing hemodialysis

A 49-year-old man visited our hospital due to pancytopenia and presence of myeloblasts in peripheral blood. Complete blood count showed normal white blood cell counts with increased myeloblasts (4.09 (cid:1) 10 9 /L, with 39% myeloblasts), anemia (hemoglobin, 94g/L), and thrombocytopenia (plate-let count, 10.8 (cid:1) 10 9 /L). Laboratory tests showed elevated lactate hydrogenase (398U/L) and creatinine levels (12.10mg/dL). Bone marrow aspiration revealed hypercellu-larity with 82% myeloblasts. G-banded metaphase analysis showed a normal karyotype (46, XY [20]). Nucleophosmin member 1 mutations, FMS-like tyrosine kinase 3 internal tandem duplications, and CCAAT/enhancer-binding protein A mutations were not detected. Hence, the patient was diagnosed with acute myeloid leukemia (AML, not other-wise specified; AML without maturation). He was at inter-mediate risk according to the European leukemia net 2017 recommendation [1]. Unfortunately, the patient was thought to be ineligible for allogenic stem cell transplant-ation (allo-SCT) because he had end-stage chronic kidney disease (CKD) and was undergoing hemodialysis regularly. He received a standard induction chemotherapy with con-tinuous cytarabine and daunorubicin
COVID-19 cases and deaths in the United States follow Taylor’s law for heavy-tailed distributions with infinite variance

Significance Variations in the cumulative reported SARS-CoV-2 cases and COVID-19 deaths by US county, state, and date exemplify Taylor’s law of fluctuation scaling, a widespread ecological and epidemiological pattern. Specifically, on day 1 of each month from April 2020 through June 2021, each state’s variance (across its counties) of cases is nearly proportional to its squared mean of cases. COVID-19 deaths behave similarly. The largest 1% of counts are approximately Pareto distributed, with a finite mean and an infinite variance. Finding infinite variance has practical consequences. Local jurisdictions (counties, states, and countries) that plan for prevention and care of largely unvaccinated people should anticipate rare but extremely high counts of cases and deaths, by preparing collaborative responses across boundaries.
Self-supervised motion descriptor for cardiac phase detection in 4D CMR based on discrete vector field estimations

Cardiac magnetic resonance (CMR) sequences visualise the cardiac function voxel-wise over time. Simultaneously, deep learning-based deformable image registration is able to estimate discrete vector fields which warp one time step of a CMR sequence to the following in a self-supervised manner. However, despite the rich source of information included in these 3D+t vector fields, a standardised interpretation is challenging and the clinical applications remain limited so far. In this work, we show how to efficiently use a deformable vector field to describe the underlying dynamic process of a cardiac cycle in form of a derived 1D motion descriptor. Additionally, based on the expected cardiovascular physiological properties of a contracting or relaxing ventricle, we define a set of rules that enables the identification of five cardiovascular phases including the end-systole (ES) and end-diastole (ED) without the usage of labels. We evaluate the plausibility of the motion descriptor on two challenging multi-disease, -center, -scanner short-axis CMR datasets. First, by reporting quantitative measures such as the periodic frame difference for the extracted phases. Second, by comparing qualitatively the general pattern when we temporally resample and align the motion descriptors of all instances across both datasets. The average periodic frame difference for the ED, ES key phases of our approach is $0.80\pm{0.85}$, $0.69\pm{0.79}$ which is slightly better than the inter-observer variability ($1.07\pm{0.86}$, $0.91\pm{1.6}$) and the supervised baseline method ($1.18\pm{1.91}$, $1.21\pm{1.78}$). Code and labels will be made available on our GitHub repository. https://github.com/Cardio-AI/cmr-phase-detection