Miracle-dz/UniFAR-FTUs huggingface dataset:
Positive reputation for altruism toward future generations regardless of the cost for current others

Recently, altruism toward future generations (future altruism) has become a hot research topic. Although future altruism has been observed in several previous experiments, it is not yet clear when and why people are more likely to engage in future altruism. Drawing upon the empirical literature of reputation and cooperation, we predicted that future altruism brings reputational disadvantages. Accordingly, we investigated whether future altruism was evaluated positively or negatively by others in the current generation in two vignette studies (total N = 1,237). Contrary to our initial prediction, we found that future altruism was positively evaluated even when it decreased the payoff of the members of the current generation. The difference in the evaluation of future altruism, as opposed to unsustainable current-generation focused behavior, was most pronounced when people do not know how a future altruist allocates rewards among individuals in the current generation. However, the positive evaluation of future altruism did not stem from the expectation that future altruists would also be altruistic toward the current generation. These results indicated that reputational benefits (i.e., positive reputation from others in the current generation) promote future altruism.
Removal of primary nutrient degraders reduces growth of soil microbial communities with genomic redundancy

Introduction Understanding how microorganisms within a soil community interact to support collective respiration and growth remains challenging. Here, we used a model substrate, chitin, and a synthetic Model Soil Consortium (MSC-2) to investigate how individual members of a microbial community contribute to decomposition and community growth. While MSC-2 can grow using chitin as the sole carbon source, we do not yet know how the growth kinetics or final biomass yields of MSC-2 vary when certain chitin degraders, or other important members, are absent. Methods To characterize specific roles within this synthetic community, we carried out experiments leaving out members of MSC-2 and measuring biomass yields and CO2 production. We chose two members to iteratively leave out (referred to by genus name): Streptomyces, as it is predicted via gene expression analysis to be a major chitin degrader in the community, and Rhodococcus as it is predicted via species co-abundance analysis to interact with several other members. Results Our results showed that when MSC-2 lacked Streptomyces, growth and respiration of the community was severely reduced. Removal of either Streptomyces or Rhodococcus led to major changes in abundance for several other species, pointing to a comprehensive shifting of the microbial community when important members are removed, as well as alterations in the metabolic profile, especially when Streptomyces was lacking. These results show that when keystone, chitin degrading members are removed, other members, even those with the potential to degrade chitin, do not fill the same metabolic niche to promote community growth. In addition, highly connected members may be removed with similar or even increased levels of growth and respiration. Discussion Our findings are critical to a better understanding of soil microbiology, specifically in how communities maintain activity when biotic or abiotic factors lead to changes in biodiversity in soil systems.
Machine-learning based automatic assessment of communication in interpreting

Communication assessment in interpreting has developed into an area with new models and continues to receive growing attention in recent years. The process refers to the assessment of messages composed of both “verbal” and “nonverbal” signals. A few relevant studies revolving around automatic scoring investigated the assessment of fluency based on objective temporal measures, and the correlation between the machine translation metrics and human scores. There is no research exploring machine-learning-based automatic scoring in-depth integrating parameters of delivery and information. What remains fundamentally challenging to demonstrate is which parameters, extracted through an automatic methodology, predict more reliable results. This study presents an original study with the aim to propose and test a machine learning approach to automatically assess communication in English/Chinese interpreting. It proposes to build predictive models using machine learning algorithms, extracting parameters for delivery, and applying a translation quality estimation model for information assessment to describe the final model. It employs the K-nearest neighbour algorithm and support vector machine for further analysis. It is found that the best machine-learning model built with all features by Support Vector Machine shows an accuracy of 62.96%, which is better than the K-nearest neighbour model with an accuracy of 55.56%. The assessment results of the pass level can be accurately predicted, which indicates that the machine learning models are able to screen the interpretations that pass the exam. The study is the first to build supervised machine learning models integrating both delivery and fidelity features to predict quality of interpreting. The machine learning models point to the great potential of automatic scoring with little human evaluation involved in the process. Automatic assessment of communication is expected to complete multi-tasks within a brief period by taking both holistic and analytical approaches to assess accuracy, fidelity and delivery. The proposed automatic scoring system might facilitate human-machine collaboration in the future. It can generate instant feedback for students by evaluating input renditions or abridge the workload for educators in interpreting education by screening performance for subsequent human scoring.
Role of mitochondrial metabolism in immune checkpoint inhibitors-related myocarditis

Background Immune checkpoint inhibitor-related myocarditis is the deadliest complication of immunotherapy. However, the underlying pathophysiological mechanisms of its occurrence and development remain unclear. Due to the long-term lack of effective early diagnosis and treatment options, it is of great significance to understand the pathophysiological mechanism of immune checkpoint inhibitor-related myocarditis. Methods Tissue samples from three patients with immune checkpoint inhibitor-related myocarditis and three control tissue samples were collected for protein analysis. Differentially expressed proteins were screened out using quantitative proteomics technology based on TMT markers. Protein–protein interaction (PPI) and Gene Ontology (GO) functional enrichment analyses of cross-factors were subsequently performed. Combined with the PD-L1 subcellular organelle- level protein interaction network, we searched for hub proteins involved in immune checkpoint inhibitor-related myocarditis and explored potential drug sensitivity and disease correlation. Results A total of 306 differentially expressed proteins were identified in immune checkpoint inhibitor-related myocarditis. Enrichment analysis showed that the differentially expressed proteins were closely related to mitochondrial metabolism. By analyzing mitochondria-related proteins and PD-L1-related proteins, we found four hub proteins, mammalian target of rapamycin (mTOR), Glycogen synthase kinase 3β (GSK3β), Protein tyrosine phosphatase non-receptor type 11 (PTPN11), and Mitofusin 2 (MFN2), indicating that they are closely related to immune checkpoint inhibitor-related myocarditis. Finally, we explored potential drugs for the treatment of immune checkpoint inhibitor-related myocarditis. Conclusion Mitochondrial metabolism is involved in the process of immune checkpoint inhibitor-related myocarditis, and we identified four hub proteins, which may become new biomarkers for the early diagnosis and treatment of immune checkpoint inhibitor-related myocarditis.
Implications of stimulus-induced, rhythmic, periodic, or ictal discharges (SIRPIDs) in hospitalized patients

Background Stimulus-induced electroencephalographic (EEG) patterns are commonly seen in acutely ill patients undergoing continuous EEG monitoring. Despite ongoing investigations, the pathophysiology, therapeutic and prognostic significance of stimulus-induced rhythmic, periodic or ictal discharges (SIRPIDs) and how it applies to specific pathologies remain unclear. We aimed to investigate the clinical implications of SIRPIDs in hospitalized patients. Methods This is a retrospective single-center study of hospitalized patients from May 2016 to August 2017. We included patients above the age of 18 years who underwent >16 h of EEG monitoring during a single admission. We excluded patients with cardiac arrest and anoxic brain injury. Demographic data were obtained as well as admission GCS, and discharge modified Rankin Score (mRS). EEGs were reviewed for background activity in addition to epileptiform, periodic, and rhythmic patterns. The presence or absence of SIRPIDs was recorded. Our outcome was discharge mRS defined as good outcome, mRS 0–4, and poor outcome mRS, 5–6. Results A total of 351 patients were included in the final analysis. The median age was 63 years and 175 (50%) were women. SIRPIDs were identified in 82 patients (23.4%). Patients with SIRPIDs had a median initial GCS of 12 (IQR, 6–15) and a length of stay of 12 days (IQR, 6–15). They were more likely to have absent posterior dominant rhythm, decreased reactivity, and more likely to have spontaneous periodic and rhythmic patterns and higher frequency of burst suppression. After adjusting for baseline clinical variables, underlying disease type and severity, and EEG background features, the presence of SIRPIDs was also associated with poor outcomes classified as MRS 5 or 6 (OR 4.75 [2.74–8.24] p ≤ 0.0001). Conclusion In our cohort of hospitalized patients excluding anoxic brain injury, SIRPIDs were identified in 23.4% and were seen most commonly in patients with primary systemic illness. We found SIRPIDs were independently associated with poor neurologic outcomes. Several studies are indicated to validate these findings and determine the risks vs. benefits of anti-seizure treatment.
Seismogenic structures and spatiotemporal seismicity patterns of the 2022 Ms6.0 Maerkang earthquake sequence, Sichuan, China

The 2022 Ms6.0 Maerkang earthquake sequence, Sichuan, China, occurred in an unexpected area with historically rare seismicity in the Bayan Har block. Here we relocated the earthquake sequence, inverted for the focal mechanisms of the larger events, and calculated the rupture directivity of the earthquake sequence to reveal the seismogenic structures and mechanisms of this sequence. The high-precision relocations indicate that the seismogenic structures consist of several clusters that are generally parallel to the nearby NW-trending Songgang fault, and relatively small-scale conjugate faults are also identified. The seismicity migrated from cluster one in the south to cluster two in the north during the sequence. Furthermore, the hypocenters were largely located at 5–10 km depth, thereby highlighting that the seismogenic structures are buried. The vertical fault planes of the seismogenic structures are consistent with the high-dip focal mechanism solutions from seven events. A stress field inversion based on the focal mechanisms indicates that the sequence occurred in a strike-slip environment that was controlled by a NNW–SSE-striking principal compressive stress. The different rupture directivities of the Ms5.8 (southwestward) and Ms6.0 (southeastward) events prove the existence of conjugate faults. The Ms5.8 event induced a coseismic Coulomb stress change of 1.6 MPa where the Ms6.0 event subsequently occurred, thereby highlighting that the Ms5.8 event triggered the Ms6.0 event and produced the spatiotemporal seismicity pattern of the sequence. We therefore conclude that the seismogenic structures of the 2022 Ms6.0 Maerkang earthquake sequence are previously unknown concealed conjugate structures associated with the main Songgang fault. The complex seismogenic structures and their potential to generate large earthquakes warrant the need to better understand the seismogenesis of this area and the seismic risks that may be present.
Effects of electroacupuncture on urinary metabolome and microbiota in presenilin1/2 conditional double knockout mice

Aim The treatment of Alzheimer’s disease (AD) is still a worldwide problem due to the unclear pathogenesis and lack of effective therapeutic targets. In recent years, metabolomic and gut microbiome changes in patients with AD have received increasing attention, and the microbiome–gut–brain (MGB) axis has been proposed as a new hypothesis for its etiology. Considering that electroacupuncture (EA) efficiently moderates cognitive deficits in AD and its mechanisms remain poorly understood, especially regarding its effects on the gut microbiota, we performed urinary metabolomic and microbial community profiling on EA-treated AD model mice, presenilin 1/2 conditional double knockout (PS cDKO) mice, to observe the effect of EA treatment on the gut microbiota in AD and find the connection between affected gut microbiota and metabolites. Materials and methods After 30 days of EA treatment, the recognition memory ability of PS cDKO mice was evaluated by the Y maze and the novel object recognition task. Urinary metabolomic profiling was conducted with the untargeted GC-MS method, and 16S rRNA sequence analysis was applied to analyze the microbial community. In addition, the association between differential urinary metabolites and gut microbiota was clarified by Spearman’s correlation coefficient analysis. Key findings In addition to reversed cognitive deficits, the urinary metabolome and gut microbiota of PS cDKO mice were altered as a result of EA treatment. Notably, the increased level of isovalerylglycine and the decreased levels of glycine and threonic acid in the urine of PS cDKO mice were reversed by EA treatment, which is involved in glyoxylate and dicarboxylate metabolism, as well as glycine, serine, and threonine metabolism. In addition to significantly enhancing the diversity and richness of the microbial community, EA treatment significantly increased the abundance of the genus Mucispirillum, while displaying no remarkable effect on the other major altered gut microbiota in PS cDKO mice, norank_f_Muribaculaceae, Lactobacillus, and Lachnospiraceae_NK4A136 group. There was a significant correlation between differential urinary metabolites and differential gut microbiota. Significance Electroacupuncture alleviates cognitive deficits in AD by modulating gut microbiota and metabolites. Mucispirillum might play an important role in the underlying mechanism of EA treatment. Our study provides a reference for future treatment of AD from the MGB axis.
Development and evaluation of an intervention to promote the use of eyeglasses among Romani families in Bulgaria

Objective Uncorrected refractive error (i.e., lack of eyeglasses for the treatment of refractive error) is one of the leading causes of visual impairment in Eastern Europe. Limited information is available on how to promote the use of eyeglasses among Romani families in Bulgaria. In step 1, the objective was to obtain suggestions by Romani mothers on how to promote the use of eyeglasses among children. In step 2, the objective was to evaluate an intervention to promote the use of eyeglasses based on suggestions received during step 1. Methods During step 1, 5 focus groups with Romani mothers took place in one neighborhood in Bulgaria. During step 2, the intervention used a one-group pre-test, post-test design. Families received eye examinations. Those who needed eyeglasses chose attractive eyeglasses. Parents received education on how to encourage their children to wear eyeglasses. Results During step 1, 54 mothers participated. Mothers suggested that the whole family should receive eye examinations and eyeglasses. During step 2, of 33 family members, 14 did not have refractive errors and 19 did. Of the 19 family members with refractive error, none had eyeglasses at pre-test. Approximately 6 months following the end of the intervention, 11 of the 19 family members (57.9%) wore eyeglasses and the remaining 8 (42.1%) did not. Conclusion Romani family members needed eyeglasses but did not have any at pre-test of the intervention. Future interventions that offer education on the importance of eye examinations may increase receipt of eye examinations and adherence to wearing eyeglasses.
Evaluation of probe-based ultra-sensitive detection of miRNA using a single-molecule fluorescence imaging method: miR-126 used as the model

This study proposed a new detection method of miRNA based on single-molecule fluorescence imaging, a method that has been successfully developed to measure the light signal of individual molecules labeled with proper fluorophores. We designed probes 1 and 2 to be labeled with Cy5 dye and BHQ2 quencher at the 3′terminals, respectively. Probe 1 consisted of two parts, the longer part complementary to miR-126 and the shorter part complementary to probe 2. After hybridization, miR-126 bound to probe 1 by replacing probe 2 and assembled into a double-stranded DNA with probe 1. The abundance of miR-126 was quantified by detecting image spots of Cy5 dye molecules from probe 1/miR-126 complexes. MiR-126 single-molecule imaging method showed high specificity and sensitivity for miR-126 with a detection limit of 50 fM. This method has good selectivity for miR-126 detection with 2.1-fold, 8.8-fold, and 26.9–41.3-fold higher than those of single-base mismatched miR-126, three-base mismatched miR-126 and non-complementary miRNAs (miR-221, miR-16, miR-143 and miR-141). The method to detect miR-126 was validated in breast cancer cell lines. Our single-molecule miRNA imaging showed high specificity and sensitivity for miRNAs. By changing the base pair sequence of the designed probes, our method would be able to detect different miRNAs.
SAS 3 survey of the soft X-ray background

The results of a survey of the soft X-ray sky in the C band (0.10-0.28keV) are reported. The observations were carried out using two independent flow proportional counters on board the SAS 3 X-ray satellite which had a total angular resolution of 2.9 deg FWHM, and a total exposure of 2.2 x 10 to the 4th per sq cm s sr. It is found that C band counting rates were generally inversely correlated with the column density of the neutral hydrogen on all angular scales down to the lowest angular resolution of the detectors. In the region 90-180 deg l and 0-10 deg b, the relation between C-band rates and the column densities of neutral hydrogen was fitted with a residual rms deviation of less than 13 percent by a two-component numerical model of the X-ray background. For the apparent attenuation column density a value of 2.7 x 10 to the 20th per sq cm was obtained. On the basis of a computer simulation of the SAS 3 data, it is shown that the observed clumping of interstellar matter was consistent with the magnitude of spatial fluctuations in the C-band map. When the background rates were subtracted from the survey map, the subsequent map showed foreground emission and absorption features with improved sensitivity and clarity. A series of computer-generated maps incorporating the SAS 3 data is given in an appendix.
Heterogeneous response of the stock market to CO2 emissions in China

CO2 emissions have been a great challenge in China, especially in recent years. Meanwhile, the CO2 emissions allowance price cannot accurately reflect the CO2 emissions information in China because of the limited efficiency in China’s carbon market. Accordingly, this study constructs a CO2 emissions index and provides an empirical investigation of the heterogeneous response of stock markets to CO2 emissions. With a quantile regression approach, we document that the effect of CO2 emissions on stock returns is significant in 2021, while it is insignificant in 2019 and 2020. In addition, its influence is more significant at the upper and lower quantiles than at the median quantile. Our findings indicate that investors and the government should pay more attention to carbon risk in the future and under extreme market conditions.
Large animal models in the study of gynecological diseases

Gynecological diseases are a series of diseases caused by abnormalities in the female reproductive organs or breast, which endanger women’s fertility and even their lives. Therefore, it is important to investigate the mechanism of occurrence and treatment of gynecological diseases. Animal models are the main objects for people to study the development of diseases and explore treatment options. Large animals, compared to small rodents, have reproductive organs with structural and physiological characteristics closer to those of humans, and are also better suited for long-term serial examinations for gynecological disease studies. This review gives examples of large animal models in gynecological diseases and provides a reference for the selection of animal models for gynecological diseases.
Impact of authentic leadership on employee turnover intention: Perceived supervisor support as mediator and organizational identification as moderator

Authentic leadership is considered a critical factor for retaining talented employees. However, despite fruitful findings, researchers have paid little attention to how authentic leadership is associated with employee turnover intention. Drawing on organizational support theory, justice literature, and social identity theory, we examine the effects of supervisors’ authentic leadership on employee turnover intention to better understand how authentic leaders reduce employees’ turnover intention in Asian context. In this study, we focus on the mediating role of perceived supervisor support (PSS) and the moderating role of organizational identification in the relationship between supervisors’ authentic leadership and employee turnover intention. To test our hypothesized research model, we adopted a cross-sectional design with a convenience data sampling. We also used a self-report research design in the current study. We collected data from 433 employees from several organizations in Korea. Our respondents rated their immediate supervisors’ authentic leadership and their PSS, turnover intention and organizational identification. Confirmatory factor analysis, regression analysis, and moderated mediation analysis revealed that: authentic leadership negatively predicted employee turnover intention. In addition, PSS completely mediates the relationship between authentic leadership and employee turnover intention. Furthermore, organizational identification moderates the relationship between PSS and turnover intention. Lastly, organizational identification moderates the mediating effect of PSS on the relationships between perceptions of authentic leadership and employee turnover intention. Herein, we discuss the managerial implications and future research directions arising from our study.
Fine structure in the profiles of strong diffuse interstellar bands

High-resolution echelle spectra of five reddened OB stars are used to analyse details of the profiles of diffuse interstellar bands (DIBs) at 4726, 4735, 5418, 5850, 6196, 6376, 6379 A together with the well studied 5797, 5780 and 6614 ones. All targets do not show Doppler splitting in the interstellar CH 4300 band with the applied resolving power R = 115 000. The profiles of DIBs differ from object to object except 5418 which looks invariant in our sample: the DIB is a good candidate for further study of possible isotopic effect. We also found that the width of bands at 5797 and 6614 A probably is more sensitive to the temperature (and density) effects than that of other DIBs in the sample, though almost all diffuse bands are narrowest in most ζ -type object (HD 179406) of the sample. On the other hand, it can be just peculiar effect as in a case of unusual line of sight HD 147889 which demonstrates very broad 5780 and 6614 A diffuse bands what hardly can be explained by temperature effects.