Miracle-dz/UniFAR-FTUs huggingface dataset:
IL-33/ST2 Axis Protects Against Traumatic Brain Injury Through Enhancing the Function of Regulatory T Cells

Traumatic brain injury (TBI) is a devastating condition due to its long-term sequelae on neurological functions. Inflammatory responses after TBI are critical for injury expansion and repair. Recent research in central nervous system (CNS) disorders reveals the importance of IL-33 and its receptor (ST2) as an alarmin system to initiate immune responses. This study explored the role of IL-33/ST2 signaling in TBI. TBI was induced in adult male C57BL/6J mice using a controlled cortical impact (CCI) model. We found that the expression of IL-33 increased in the injured brain and blood, and ST2 was elevated in the circulating and infiltrating regulatory T cells (Tregs) early after TBI. ST2 deficient mice exhibited reduced Treg numbers in the blood and brain 5 days after TBI. The brain lesion size was enlarged in ST2 knockout mice, which was accompanied by deteriorated sensorimotor function 5 days after TBI. In contrast, post-TBI treatment with IL-33 (2 μg/30 g body weight, intranasal) for 3 days significantly reduced brain lesion size and improved neurological functions 5 days after TBI. Meanwhile, IL-33 treatment increased ST2 expression in circulating and brain infiltrating Tregs. To further explore the involvement of Tregs in IL-33/ST2-mediated neuroprotection, Tregs were depleted by CD25 antibody injection. The absence of Tregs significantly reduced the protective effect of IL-33 after TBI. In vitro study confirmed that IL-33 (50 ng/ml) increased the production of IL-10 and TGFβ from activated Tregs and boosted the inhibitory effect of Tregs on T effector cell proliferation. Taken together, this study suggests that the activation of IL-33/ST2 signaling reduces brain lesion size and alleviates functional deficits after TBI at least partially through regulating the Treg response. IL-33 may represent a new immune therapeutic strategy to improve TBI outcomes.
Right Heart Chambers Longitudinal Strain Provides Enhanced Diagnosis and Categorization in Patients With Pulmonary Hypertension

Background Increased systolic pulmonary arterial pressure (sPAP) could lead to the mechanical dysfunction and myocardial fibrosis of the right heart chambers. Echocardiographic strain analysis has not been adequately studied in patients with pulmonary hypertension (PH). Study design and methods A cross-sectional cohort of patients with suspected PH and echocardiographic strain evaluation was recruited. The cut-off values of peak tricuspid regurgitation velocity (TRV) with the low probability of PH (≤2.8 m/s), intermediate probability (2.9–3.4 m/s, without other echo PH signs), and high probability of PH (2.9–3.4 m/s with other echo PH signs and >3.4 m/s) categories were studied by right ventricular and right atrial (RA) strain analysis in a sample of 236 patients. Results The results showed that 58 (56.9%) patients had low, 15 (14.7%) had intermediate, and 29 (28.4%) had a high probability of PH. We observed a negative association between right ventricular free wall strain (RV-FWS) and atrial global strain with sPAP. With the increase in PH severity, RA reservoir, conduit, and contraction (booster) strain values decreased. The identified cut-off values of strain parameters had an adequate ability to detect PH severity categories. In addition, the post-mortem biopsies of right heart chambers from subjects with known severe PH were analyzed to quantify myocardial fibrosis. Our sample of right heart biopsies (n = 12) demonstrated an association between increased sPAP before death and right ventricular and RA fibrosis. Conclusion Mechanical dysfunction and fibrosis in the right chambers are associated with increased sPAP. Right ventricular and atrial strain could provide enhancement in the diagnosis and categorization of subjects with suspected PH.
Who plays nice? A surprising meta-meta analysis of 1259 experimental studies

Scientific, social, and political policies in all countries and locations act upon and within a foundation of basic human interaction. Exploring the relationship between cooperative decision making and societal level institutions is an important job of social science, but such work has historically faced difficulty. Survey measures of behaviors and preferences face the problem of a lack of salience. Observed behavior within each society, from field, laboratory, and observational data is fundamentally constrained by the institutions governing those behaviors, preventing clean behavioral comparisons across institutions due to a lack of comparable counterfactuals. As such, it remains an open question whether and how macro level institutions are fundamentally related to underlying social and decision making behaviors of people living under those institutions. Here we combine and connect independent measures of institutional economic freedom at the societal level from 50 countries to the salient decision making data from 1259 laboratory experiments found within six meta-analyses. In experiments conducted within countries characterized by high levels of economic freedom, we find a positive relationship between additional economic freedom and pro-social choices. In countries with low levels of economic freedom, we find a negative relationship. We find the oppo-site relationship (an inverted U-shaped) between additional economic freedom and Nash equilibrium strategies. A similar pattern is repeated in a secondary analysis of institutions and experimental data across U.S. Metropolitan Statistical Areas. Our results indicate that when designing policy interventions that influence economic freedom, the effect on pro-social behavior, itself an important driver of economic development, will likely depend on the baseline institutional environment inside the intervening country.
A meta-analysis of allopurinol therapy and the risk of prostate cancer

Abstract Objective: The aim of the study was to investigate the risk of prostate cancer among people with gout and/or hyperuricemia who used allopurinol and who did not use allopurinol. Methods: We conducted a meta-analysis to identify the cohort and case-control studies by searching PubMed and Web of Science. We used the random-effects model to calculate the pooled risk ratio with 95% confidence interval for the risk of prostate cancer associated with allopurinol treatment. Results: There were 5 cohort studies and 2 case-control studies included in the meta-analysis. All 7 eligible studies were published between 2012 and 2021. The study period ranged from 8 to 13years. The number of study subjects ranged from 25,770 to 1,623,550. The age of study subjects ranged from 20 to 99years. Overall, allopurinol treatment was not associated with the risk of prostate cancer (risk ratio = 1.13, 95% confidence interval = 0.96-1.34 and P = .13). The heterogeneity was high between studies (I2 = 93%). Conclusions: Our meta-analysis reveals that no association can be found between allopurinol treatment and the risk of prostate cancer among people with gout and/or hyperuricemia. We propose that the inhibition of xanthine oxidase and the reduction of serum uric acid via allopurinol treatment do not affect the probability of developing prostate cancer. Further studies are needed to confirm our findings. Key Points No association can be found between allopurinol treatment and the risk of prostate cancer. The inhibition of xanthine oxidase and the reduction of serum uric acid via allopurinol treatment do not affect the probability of developing prostate cancer.
Oral pigmentation as an adverse effect of chloroquine and hydroxychloroquine use

Abstract Background Chloroquine and hydroxychloroquine are 2 medications used to treat some systemic diseases. Objective The aim of this scoping review was to assess the occurrence of oral pigmentation induced by chloroquine or hydroxychloroquine and to understand the pathogenic mechanism behind this phenomenon. Methods The review was performed according to the list of PRISMA SrC recommendations and the JBI Manual for Evidence Synthesis for Scoping Reviews. MEDLINE (PubMed), Scopus, EMBASE, SciELO, Web of Science, Lilacs, and LIVIVO were primary sources, and “gray literature” was searched in OpenThesis and Open Access Thesis and Dissertations (OATD). Studies that screened the occurrence of oral pigmentation associated to the use of chloroquine or hydroxychloroquine were considered eligible. No restrictions of year and language of publication were applied. Study selection and data extraction were performed by 2 independent reviewers. The risk of bias was assessed through the JBI tool, depending on the design of the selected studies. Results The initial search resulted in 2238 studies, of which 19 were eligible. Sixteen studies were case reports, 2 had case-control design and 1 was cross-sectional. Throughout the studies, 44 cases of oral pigmentation were reported. The hard palate was the anatomic region most affected with pigmentation (66%). According to the case reports, most of the lesions (44%) were bluish-gray. The minimum time from the beginning of treatment (chloroquine or hydroxychloroquine) to the occurrence of pigmentation was 6 months. The mean treatment time with the medications was 4.9 years, and the mean drug dosage was 244 mg. Most of the studies (63.1%) had low risk of bias (high methodological quality). Conclusions The outcomes of this study suggest that hyperpigmentation depend on drug dosage and treatment length. Hyperpigmentation was detected after a long period of treatment with chloroquine or hydroxychloroquine.
Methods for Phenotyping Adult Patients in Sepsis and Septic Shock: A Scoping Review

OBJECTIVE: Despite its heterogeneous phenotypes, sepsis or life-threatening dysfunction in response to infection is often treated empirically. Identifying patient subgroups with unique pathophysiology and treatment response is critical to the advancement of sepsis care. However, phenotyping methods and results are as heterogeneous as the disease itself. This scoping review evaluates the prognostic capabilities and treatment implications of adult sepsis and septic shock phenotyping methods. DATA SOURCES: Medline and Embase. STUDY SELECTION: We included clinical studies that described sepsis or septic shock and used any clustering method to identify sepsis phenotypes. We excluded conference abstracts, literature reviews, comments, letters to the editor, and in vitro studies. We assessed study quality using a validated risk of bias tool for observational cohort and cross-sectional studies. DATA EXTRACTION: We extracted population, methodology, validation, and phenotyping characteristics from 17 studies. DATA SYNTHESIS: Sepsis phenotyping methods most frequently grouped patients based on the degree of inflammatory response and coagulopathy using clinical, nongenomic variables. Five articles clustered patients based on genomic or transcriptomic data. Seven articles generated patient subgroups with differential response to sepsis treatments. Cluster clinical characteristics and their associations with mortality and treatment response were heterogeneous across studies, and validity was evaluated in nine of 17 articles, hindering pooled analysis of results and derivation of universal truths regarding sepsis phenotypes, their prognostic capabilities, and their associations with treatment response. CONCLUSIONS: Sepsis phenotyping methods can identify high-risk patients and those with high probability of responding well to targeted treatments. Research quality was fair, but achieving generalizability and clinical impact of sepsis phenotyping will require external validation and direct comparison with alternative approaches.
Effect of a Multispecialty Faculty Handoff Initiative on Safety Culture and Handoff Quality

Introduction: Structured handoffs at transitions of care are vital components of patient safety. A safety culture survey showed that “handoffs and transitions” were among the lowest scoring dimensions at our hospital. We sought to improve physician handoffs and safety culture scores by implementing standardized handoff communication across multiple divisions of an academic pediatric department. Methods: We used a modified learning collaborative model to implement an I-PASS program, including training, standardized verbal handoff processes, observation and feedback, and sustainment. The setting was the Department of Pediatrics (DoP) within a tertiary academic children’s hospital encompassing 13 clinical divisions. The primary outcome was a change in the DoP staff physician “handoffs and transitions” score on the Agency for Healthcare Quality (AHRQ) Hospital Survey on Patient Safety Culture. Process measures included handoff duration and proportion of handoffs using the complete I-PASS mnemonic. Results: Five hundred sixty-seven physicians from clinical divisions participated over 14 months. One hundred percent of eligible physicians completed an introductory online I-PASS training module. The “handoffs and transitions” score improved from 46% to 54% from 2018 to 2020. From May 2019 to February 2020, the proportion of observed handoffs with all five elements of the I-PASS mnemonic improved from 62% to 100%, and the duration of handoffs per patient did not change. Conclusions: We successfully implemented an I-PASS program across an academic department of pediatrics. The departmental staff physician safety culture “handoff and transitions” score improved. The adherence to the I-PASS mnemonic improved. The duration of handoffs did not change over the study period.
Machine learning accelerated calculation and design of electrocatalysts for CO2 reduction

In the past decades, machine learning (ML) has impacted the field of electrocatalysis. Modern researchers have begun to take advantage of ML‐based data‐driven techniques to overcome the computational and experimental limitations to accelerate rational catalyst design. Hence, significant efforts have been made to perform ML to accelerate calculation and aid electrocatalyst design for CO2 reduction. This review discusses recent applications of ML to discover, design, and optimize novel electrocatalysts. First, insights into ML aided in accelerating calculation are presented. Then, ML aided in the rational design of the electrocatalyst is introduced, including establishing a data set/data source selection and validation of descriptor selection of ML algorithms validation and predictions of the model. Finally, the opportunities and future challenges are summarized for the future design of electrocatalyst for CO2 reduction with the assistance of ML.
Recent development of nanomaterials for carbon dioxide electroreduction

Electrochemical CO2 reduction reaction (CO2RR) to produce value‐added products has received tremendous research attention in recent years. With research efforts across the globe, remarkable advancement has been achieved, including the improvement of selectivity for the reduction products, the realization of efficient reduction beyond two electrons, and the delivery of industrially relevant current densities. In this review, we introduce the recent development of nanomaterials for CO2RR, including the zero‐dimensional graphene quantum dots, two‐dimensional materials such as metal chalcogenides and metal/covalent organic framework, single‐atom catalysts, and nanostructured metal catalysts. The engineering of materials into three‐dimensional structure will also be discussed. Finally, we will provide a summary of the catalytic performance and perspectives on future development.
Application Method of Task Ontology Technology for Recommendation of Automobile Parts

Abstract This research proposes the method to develop the recommendation system of automobile parts using task ontology technology. The proposed intelligent recommendation system is designed to learn the assembly process of automobile parts and the automobile parts are composed by ontology method for the recommendation of the parts. Using hierarchical taxonomy based on is-a relationship, the relationship between each part that makes up automotive engine was set. Each part has each different weighted value according to the knowledge of automobile experts. The weighted value is created by the number of selection that the users of the automobile recommendation system select while using the system and the final value calculated by the multiplication of the weighted value, which is recorded within the system. As a result, the users can easily identify which factor in which part is important by the output in the order of the priority. The intelligent recommendation system for automobile parts is a system to inform of the assembly, the usage and the importance of automobile parts without any specialized knowledge by expressing the parts that are closely related with the applicable parts when selecting any part on the basis of the generated data for the automobile parts that are difficult to access by users.
R wave duration as a measure of body position changes during sleep

Any change in body position alters the relative angle between the ECG electrodes and the electric axis of the heart. Thus it influences the time interval during which the projection of the electric dipole, on any ECG lead is positive. We used the R wave duration (RWD) as representing this positive projection and as indicator of body position changes. Two experimental setups were used: (1) Simultaneous ECG recordings from leads I, II, and III during a sequence of well-defined body positions, (controlled conditions). (2) Lead II and video recordings from healthy subjects, who underwent whole night sleep studies. Using data of any of the leads, we could identify over 90% of the changes in body position, in both experimental setups. RWD calculated from lead II was the most reproducible upon reassuming the same body position. Measuring RWD from ECG may help to reduce the number of sensors required in full sleep studies, and to obtain better interpretation of non-attended ones.
Truck Driver Safety: An Evolutionary Research Approach

Abstract: Driver safety is consistently a top concern of motor-carrier industry leaders at all levels. Efforts to improve safety performance span a variety of domains, and one key element of the safety problem is the behavior of the commercial motor-vehicle operator—the driver of the “big rigs” we share the highways with on a daily basis. The purpose of this article is to tell the story of an ongoing research program designed to understand safe/unsafe driving in the unique occupational context of the North American commercial motor-vehicle driver (i.e., truck driver). As part of a broad, multiyear effort, the investigators who immersed themselves in that culture at several motor carriers were granted unique access to their employees. By allowing the employees (safety professionals and drivers alike) to inform the research direction, overlaid with extant psychosocial behavioral models post hoc, a promising stream of research was developed that led to a more integrated and comprehensive theoretical framework. The framework informs the development of interventions in hiring and training designed to improve driver safety. Recommendations for how this approach can be applied to other domains are provided.
Dynamic commutation torque-ripple reduction for brushless DC motor based on quasi-Z-source net

The commutation torque ripple in the six-step square-wave driving mode of the brushless DC motor affects the motor performance and generates mechanical vibrations and noise when used for industrial applications. The cause of commutation torque ripple is analysed in this study and a non-linear transient model of the phase current during the commutation interval is developed. According to the transient-current model, the commutation voltage and the time required to produce a constant torque can be calculated without current sampling; this makes the control system easier to realise in industrial applications, and reduces the need for a high performance controller. Based on the pulse-with modulated chopping method and quasi-Z-source net, the proposed control system can adjust the motor speed using a constant-voltage power supply and reduce the commutation torque ripple over the entire speed-adjustable range. A torque transducer is used to measure the dynamic torque ripple in the experiment. The results show that the proposed commutation torque-ripple reduction strategy can reduce the dynamic torque ripple by about 70% in both simulation and experiment compared with the traditional driving methods.
Deforestation beyond borders: Addressing the disparity between production and consumption of global resources

Analysis of production and trade data from 176 countries reveals that patterns of wood product consumption and harvest differ significantly across income groups. Poorer countries’ consumption consists primarily of domestic fuelwood, yet between 1972 and 2009, low‐income countries harvested >171 million hectares of forest products for export. High‐income countries were the only group to act as net importers, suggesting that rich countries practice preservation within borders but appropriate resources from poorer countries to sustain consumption. Harvests in poorer countries do occur at relatively low harvest efficiencies, implying that losses may be attenuated via technological improvement. However, efficiency does not mitigate the effects of high consumption. Despite exceptionally high efficiencies, high‐income countries are still responsible for just as much (or more) consumption‐driven forest loss as any other group. These findings highlight the importance of reducing consumption and suggest that neither technocentric solutions nor national‐level conservation policies are sufficient means to preserve global forests.
Agile IT Organization Design: For Digital Transformation and Continuous Delivery

To gain the full benefits of agility in any software organization, you need to extend it beyond developers to the organization as a whole. Aspiring digital businesses need overall agility, not just development team agility. Now, Sriram Narayan, IT management consultant at Thought Works, shows how to do just that. Drawing on 15+ years working with leaders in telecommunications, finance, energy, retail, and beyond, he introduces a comprehensive agile approach to "Business-IT Effectiveness" that is as practical as it is valuable. Sriram demonstrates how to integrate agility throughout sales, marketing, product development, engineering, and operations, helping each function deliver more value individually and through its linkages with the rest of the business. Addressing people, process, and technology, he guides you in improving both the dynamic and static aspects of organization design, addressing team structure, accountability structures, organizational norms and culture, metrics, and more. Using real examples, Sriram helps you evaluate and improve organization designs to enhance autonomy, mastery, and purpose. You'll learn how to eliminate the specific organizational silos that cause the most problems. improve communication in organizations that claim to be (but aren't really) non-hierarchical. optimize the way you build teams, design office space, and even choose tools. Simply put, Agile IT Organization Design will help you improve the performance of any software organization.