Miracle-dz/UniFAR-FTUs huggingface dataset:
MAITabolism2 – the emerging understanding of MAIT cell metabolism and their role in metabolic disease

Mucosal associated invariant T (MAIT) cells are a population of unconventional innate T cells due to their non-MHC restriction and rapid effector responses. MAIT cells can recognise bacterial derived antigens presented on the MHC-like protein via their semi-restricted T cell receptor (TCR). Upon TCR triggering MAIT cells rapidly produce a range of effector molecules including cytokines, lytic granules and chemokines. This rapid and robust effector response makes MAIT cells critical in host responses against many bacterial pathogens. MAIT cells can also respond independent of their TCR via innate cytokines such as interleukin (IL)-18, triggering cytokine production, and are important in anti-viral responses. In addition to their protective role, MAIT cells have been implicated in numerous inflammatory diseases, including metabolic diseases often contributing to the pathogenesis via their robust cytokine production. Effector cells such as MAIT cells require significant amounts of energy to support their potent responses, and the type of nutrients available can dictate the functionality of the cell. Although data on MAIT cell metabolism is just emerging, several recent studies are starting to define the intrinsic metabolic requirements and regulators of MAIT cells. In this review we will outline our current understanding of MAIT cell metabolism, and outline their role in metabolic disease, and how disease-related changes in extrinsic metabolism can alter MAIT cell responses.
On the existence of almost-periodic solutions for the 2D dissipative Euler equations

In this paper we study the two-dimensional dissipative Euler equations in a smooth and bounded domain. In the presence of a sufficiently large dissipative term (or equivalently a sufficiently small external force) precise uniform estimates on the modulus of continuity of the vorticity are proved. These allow us to show existence of Stepanov almost-periodic solutions.
Personalized antiplatelet therapy guided by clopidogrel pharmacogenomics in acute ischemic stroke and transient ischemic attack: A prospective, randomized controlled trial

Background: Clopidogrel is frequently used in patients with ischemic stroke or transient ischemic attack (TIA), but its efficacy is hampered by inter-individual variability, due to genetic differences associated with clopidogrel metabolism. We conducted this randomized controlled trial to validate whether the personalized antiplatelet therapy based on clopidogrel pharmacogenomics and clinical characteristics leads to better clinical outcomes compared with standard treatment. Methods: Patients were randomly divided into the standard group or pharmacogenetic group, in which the pharmacogenetic group required the detection of the genotyping of CYP2C19*2, CYP2C19*3, and CYP2C19*17. Patients were followed up for 90 days for the primary efficacy endpoint of new stroke events, secondary efficacy endpoint of individual or composite outcomes of the new clinical vascular events, and the incidence of disability. The primary safety outcome was major bleeding. Results: A total of 650 patients underwent randomization, among which 325 were in the pharmacogenomics group while 325 were in the standard group. Our study found after a 90-day follow-up, the risk of stroke and composite vascular events in the pharmacogenomics group was lower than that in the standard group. The incidence of disability significantly decreased in the pharmacogenomics group. In addition, no statistically significant differences were observed in bleeding events between the two groups. Conclusion: The present study demonstrates that personalized antiplatelet therapy guided by clopidogrel pharmacogenomics and clinical characteristics can significantly improve the net clinical benefit of ischemic stroke or TIA patients during the 90-day treatment period without increasing bleeding risk.
Moral contamination: Perceptions of good (but not bad) deeds depend on the ethical history of the actor

In the majority of moral decision-making research, we are asked to consider the action of someone we know little about—an anonymous actor. This is inconsistent with our everyday judgments of the actions of others. Here we test the novel prediction of whether actions are considered as comparably virtuous or malignant when performed by a good person, an immoral person, or the standard anonymous actor. Across four sets of experiments (nine studies in total), we show that the moral status of the actor contaminates peoples’ evaluations of the virtue of their actions. Even without ulterior motives, people do not judge good acts consistently across actors. We also discover a dose–response relationship where the more immoral the actor has been in the past—the less credit they are given for a good action in the present. This process does not occur for good people performing bad acts, however. Bad acts are bad regardless of who commits them. These results give new insights into the way people evaluate the behaviors of others.
Water model determines thermosensitive and physicochemical properties of poly(N-isopropylacrylamide) in molecular simulations

Poly (N-isopropylacrylamide) (PNIPAM) is a famous representative of thermosensitive polymers. Thermosensitive polymers undergo a phase transition with lower critical solution temperature. Commonly, their phase behavior is linked to a conformational collapse above a certain temperature. This thermosensitive conformational transition is called Coil-Globule transition. In contrast, most other polymers usually show inverse temperature behavior, i.e., an upper critical solution temperature, corresponding to a Globule-Coil transition. Besides their numerous possible applications, thermosensitive polymers are of interest for fundamental research, because of similarities to macromolecular conformational transitions, e.g., protein folding. The counter-intuitive behavior of thermosensitive polymers is commonly associated with solvation effects. Thus, an accurate description of the solvent is crucial for the investigation of thermosensitive polymers in molecular simulations. Here, we investigate the influence of the in silico water model on the thermosensitive Coil-Globule transition in molecular dynamics simulations. To this end, we performed extensive atomistic simulations of the syndiotactic PNIPAM 20-mer at multiple temperatures with eight different water models–four of which are 3-point water models (TIP3P-type) and four are 4-point water models (TIP4P-type). We found that the thermosensitive Coil-Globule transition is strongly influenced by the water model in the simulations. Depending on the water model, the conformational ensemble of the polymer is shifted significantly, which leads to dramatically different results: The estimated transition temperature may span between 255 and 350 K. Consequently, depending on the description of the solvent, the physicochemical and mechanical properties of these polymers, e.g., the polymer-solvent affinity and persistence length, vary. These divergent results originate from the strength of interactions between polymer and solvent, but also on the bulk state of the solvent. Both these quantities vary between water models. We found that the Lennard-Jones interaction parameter ϵ of the water model correlates with the transition temperature of the polymer. Indeed, the quadrupole moment of the water model shows an even higher correlation with this quantity. Our results suggest a connection between the phase diagram of the solvent and the thermosensitive transition of the polymer.
Symbiotic effectiveness of Bradyrhizobium strains on soybean growth and productivity in Northern Mozambique

Inoculation of soybean [Glycine max (L.) Merr. ] with rhizobia strains is a low-cost investment which can increase yields of smallholder farmers in Mozambique. The performance of four Bradyrhizobium strains was evaluated to identify the best strain to inoculate soybean grown in different agro-ecologies. Field experiments were conducted in three ecological zones in 2018 and 2019 using soybean variety Zamboane inoculated with Bradyrhizobium diazoefficiens strain USDA 110, B. japonicum strains USDA 136, USDA 442 and WB74, and a non-inoculated control in a randomized complete block design with four replications. Indigenous rhizobia populations at the sites ranged from 9.0 x 101 to 2.2 x 103 cells g−1 soil. All four strains increased nodulation, but USDA 110 was superior at two sites with low native rhizobia population, whereas USDA 442 and WB74 were the best at the site with relatively high native rhizobia population. On an average, the strains doubled the number of nodules and increased the dry weight up to 5.8-fold. Inoculation increased shoot dry weight and N content at podding, plant biomass, and number of pods plant−1 across sites but the effects of the strains on seeds per pod, and 100-seed weight were inconsistent. Shoot N content did not differ among inoculant strains and ranged from 15.70 g kg−1 in the control to 38.53 g kg−1 across inoculation. All four strains increased soybean grain yield across sites in 2018 but USDA 110 outperformed the other strains and was also the best at one of the two sites in 2019. Grain yield responses associated with USDA 110 ranged from 552 kg ha−1 (56%) to 1,255 kg ha−1 (76%). Positive correlations between nodule dry weight plant−1 and seed yield, and number of pods plant−1 and grain yield were observed. The gross margin ranged from $343.50–$606.80 ha−1 for the control, but it increased to $688.34–$789.36 when inoculants were applied. On an average, inoculation increased gross margin by $182.57-$395.35 ha−1 over that of non-inoculated control in 2018 but drought stress in 2019 reduced the benefit. The results demonstrate that USDA 110 was the best inoculant strain and has the potential of increasing smallholder productivity and net returns.
Classification and Identification of IRAS Sources with Low-Resolution Spectra

IRAS low-resolution spectra were extracted for 11,224 IRAS sources. These spectra were classified into astrophysical classes, based on the presence of emission and absorption features and on the shape of the continuum. Counterparts of these IRAS sources in existing optical and infrared catalogs are identified, and their optical spectral types are listed if they are known. The correlations between the photospheric/optical and circumstellar/infrared classification are discussed.
Retrieval-induced forgetting in declarative and procedural memory: Inhibitory suppression resolves interference between motor responses

Over a century's worth of research suggests that, for a variety of verbal and perceptual memory phenomena, retrieval modifies memory in two ways. First, retrieved information is strengthened and thus more easily retrieved on subsequent recall tests. Secondly, when information is stored or organized in memory in such a way that multiple representations share a common retrieval cue, and are thus subject to interference, related information that is not retrieved becomes less recallable. Such retrieval-induced forgetting is a highly robust and well-understood phenomenon. Over the past decade, several experiments have demonstrated that retrieval-induced forgetting also persists for motor responses–both simple and complex, and that this impairment is observed for representations stored in both declarative and procedural memory. While several review papers have focused on retrieval-induced forgetting of verbal and perceptual information, to date no literature review has focused exclusively on retrieval-induced forgetting of motor responses or actions. In addition, while retrieval-induced forgetting has been documented extensively within the domain of declarative memory, only a few papers have been published documenting retrieval-induced forgetting in procedural memory. Therefore, this review paper will explore these findings and their primary implications, most notably that when multiple motor programs are initiated via a shared retrieval cue, inhibitory suppression is recruited to decrease accessibility of related, but inappropriate actions in service of potentiating retrieval of appropriate actions. More broadly, the same processes that govern selective retrieval in cognition are implicated in the selective retrieval of motor actions.
Virus induced dysbiosis promotes type 1 diabetes onset

Autoimmune disorders are complex diseases of unclear etiology, although evidence suggests that the convergence of genetic susceptibility and environmental factors are critical. In type 1 diabetes (T1D), enterovirus infection and disruption of the intestinal microbiota are two environmental factors that have been independently associated with T1D onset in both humans and animal models. However, the possible interaction between viral infection and the intestinal microbiota remains unknown. Here, we demonstrate that Coxsackievirus B4 (CVB4), an enterovirus that accelerates T1D onset in non-obese diabetic (NOD) mice, induced restructuring of the intestinal microbiome prior to T1D onset. Microbiome restructuring was associated with an eroded mucosal barrier, bacterial translocation to the pancreatic lymph node, and increased circulating and intestinal commensal-reactive antibodies. The CVB4-induced change in community composition was strikingly similar to that of uninfected NOD mice that spontaneously developed diabetes, implying a mutual “diabetogenic” microbiome. Notably, members of the Bifidobacteria and Akkermansia genera emerged as conspicuous members of this diabetogenic microbiome, implicating these taxa, among others, in diabetes onset. Further, fecal microbiome transfer (FMT) of the diabetogenic microbiota from CVB4-infected mice enhanced T1D susceptibility and led to diminished expression of the short chain fatty acid receptor GPR43 and fewer IL-10-expressing regulatory CD4+ T cells in the intestine of naïve NOD recipients. These findings support an overlap in known environmental risk factors of T1D, and suggest that microbiome disruption and impaired intestinal homeostasis contribute to CVB-enhanced autoreactivity and T1D.
Brain responses to negated and affirmative meanings in the auditory modality

Negation is frequently used in natural language, yet relatively little is known about its processing. More importantly, what is known regarding the neurophysiological processing of negation is mostly based on results of studies using written stimuli (the word-by-word paradigm). While the results of these studies have suggested processing costs in connection to negation (increased negativities in brain responses), it is difficult to know how this translates into processing of spoken language. We therefore developed an auditory paradigm based on a previous visual study investigating processing of affirmatives, sentential negation (not), and prefixal negation (un-). The findings of processing costs were replicated but differed in the details. Importantly, the pattern of ERP effects suggested less effortful processing for auditorily presented negated forms (restricted to increased anterior and posterior positivities) in comparison to visually presented negated forms. We suggest that the natural flow of spoken language reduces variability in processing and therefore results in clearer ERP patterns.
Calculation method for reinforcement spacing of bilaterally wrapped reinforced embankments under seismic force

The vertical spacing among reinforcements in geosynthetic-reinforced earth embankment is crucial to its overall stability. Based on the upper bound theorem of plastic limit analysis and pseudo-static approach, an overall stability analysis method for bilaterally wrapped reinforced embankments under strip surcharge and seismic action is put forward in view of the planar and log-spiral failure mechanism of the reinforced embankments, which quantitatively expresses the relationship between the reinforcement spacing and the factor of safety of the embankments. Some examples show that the maximum relative error of the factor of safety between the proposed method and some existing methods is around 10% under a specified reinforcement spacing. The factor of safety is nonlinearly decreasing as the reinforcement spacing increases, and the results by the log-spiral mode are slightly more conservative than those by the planar mode. The proposed method can quantitatively reflect the influence of the filling properties, reinforcement strength, seismic forces, strip surcharge, and embankment geometry on the reinforcement spacing. The nonlinear negative relationship between the factor of safety and the reinforcement spacing is noticeable under different reinforcement strengths. The reinforcement spacing is almost linearly reducing with the increase of the vertical seismic coefficient increases, while it decreases clearly nonlinearly as the horizontal seismic coefficient increases.
A Novel Online Calculator Predicting Acute Kidney Injury After Liver Transplantation: A Retrospective Study

Acute kidney injury (AKI) after liver transplantation (LT) is a common complication, and its development is thought to be multifactorial. We aimed to investigate potential risk factors and build a model to identify high-risk patients. A total of 199 LT patients were enrolled and each patient data was collected from the electronic medical records. Our primary outcome was postoperative AKI as diagnosed and classified by the KDIGO criteria. A least absolute shrinkage and selection operating algorithm and multivariate logistic regression were utilized to select factors and construct the model. Discrimination and calibration were used to estimate the model performance. Decision curve analysis (DCA) was applied to assess the clinical application value. Five variables were identified as independent predictors for post-LT AKI, including whole blood serum lymphocyte count, RBC count, serum sodium, insulin dosage and anhepatic phase urine volume. The nomogram model showed excellent discrimination with an AUC of 0.817 (95% CI: 0.758–0.876) in the training set. The DCA showed that at a threshold probability between 1% and 70%, using this model clinically may add more benefit. In conclusion, we developed an easy-to-use tool to calculate the risk of post-LT AKI. This model may help clinicians identify high-risk patients. Graphical Abstract
Five genes as diagnostic biomarkers of dermatomyositis and their correlation with immune cell infiltration

Background Dermatomyositis (DM) is a rare autoimmune disease characterized by severe muscle dysfunction, and the immune response of the muscles plays an important role in the development of DM. Currently, the diagnosis of DM relies on symptoms, physical examination, and biopsy techniques. Therefore, we used machine learning algorithm to screen key genes, and constructed and verified a diagnostic model composed of 5 key genes. In terms of immunity, The relationship between 5 genes and immune cell infiltration in muscle samples was analyzed. These diagnostic and immune-cell-related genes may contribute to the diagnosis and treatment of DM. Methods GSE5370 and GSE128470 datasets were utilised from the Gene Expression Omnibus database as DM test sets. And we also used R software to merge two datasets and to analyze the results of differentially expressed genes (DEGs) and functional correlation analysis. Then, we could detect diagnostic genes adopting least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine recursive feature elimination (SVM-RFE) analyses. The validity of putative biomarkers was assessed using the GSE1551 dataset, and we confirmed the area under the receiver operating characteristic curve (AUC) values. Finally, CIBERSORT was used to evaluate immune cell infiltration in DM muscles and the correlations between disease-related biomarkers and immune cells. Results In this study, a total of 414 DEGs were screened. ISG15, TNFRSF1A, GUSBP11, SERPINB1 and PTMA were identified as potential DM diagnostic biomarkers(AUC > 0.85),and the expressions of 5 genes in DM group were higher than that in healthy group (p < 0.05). Immune cell infiltration analyses indicated that identified DM diagnostic biomarkers may be associated with M1 macrophages, activated NK cells, Tfh cells, resting NK cells and Treg cells. Conclusion The study identified that ISG15, TNFRSF1A, GUSBP11, SERPINB1 and PTMA as potential diagnostic biomarkers of DM and these genes were closely correlated with immune cell infiltration.This will contribute to future studies in diagnosis and treatment of DM.
Predictors of 30-day mortality among patients with stroke admitted at a tertiary teaching hospital in Northwestern Tanzania: A prospective cohort study

Background Stroke is the second leading cause of death worldwide, with the highest mortality rates in low- to middle-income countries, particularly in sub-Saharan Africa. We aimed to investigate the predictors of 30-day mortality among patients with stroke admitted at a tertiary teaching hospital in Northwestern Tanzania. Methods This cohort study recruited patients with the World Health Organization's clinical definition of stroke. Data were collected on baseline characteristics, the degree of neurological impairment at admission (measured using the National Institutes of Health Stroke Scale), imaging and electrocardiogram (ECG) findings, and post-stroke complications. The modified Rankin scale (mRS) was used to assess stroke outcomes. Kaplan–Meier analysis was used to describe survival, and the Cox proportional hazards model was used to examine predictors of mortality. Results A total of 135 patients were enrolled, with a mean age of 64.5 years. Hypertension was observed in 76%, and 20% were on regular anti-hypertensive medications. The overall 30-day mortality rate was 37%. Comparing patients with hemorrhagic and ischemic stroke, 25% had died by day 5 [25th percentile survival time (in days): 5 (95% CI: 2–14)] versus day 23 [25th percentile survival time (in days): 23 (95% CI: 11–30) (log-rank p < 0.001)], respectively. Aspiration pneumonia was the most common medical complication, occurring in 41.3% of patients. ECG abnormalities were observed in 54.6 and 46.9% of patients with hemorrhagic and ischemic stroke, respectively. The most common patterns were as follows: ST changes 29.6 vs. 30.9%, T-wave inversion 34.1 vs. 38.3%, and U-waves 18.2 vs. 1.2% in hemorrhagic and ischemic stroke, respectively. Independent predictors for case mortality were as follows: mRS score at presentation (4–5) [aHR 5.50 (95% CI: 2.02–15.04)], aspiration pneumonia [aHR 3.69 (95% CI: 1.71–13.69)], ECG abnormalities [aHR 2.28 (95% CI: 1.86–5.86)], and baseline stroke severity [aHR 1.09 (95% CI: 1.02–1.17)]. Conclusion Stroke is associated with a high 30-day mortality rate in Northwestern Tanzania. Concerted efforts are warranted in managing patients with stroke, with particular attention to individuals with severe strokes, ECG abnormalities, and swallowing difficulties to reduce early morbidity and mortality.