Miracle-dz/UniFAR-FTUs huggingface dataset:
X-Ray Structure and enzymatic study of a Bacterial NADPH oxidase highlight the activation mechanism of eukaryotic NOX

NADPH oxidases (NOX) are transmembrane proteins that professionally produce reactive oxygen species (ROS) and are distributed widely in both eukaryotes and prokaryotes. Eukaryotes use the ROS products for innate immune defense and signaling; the seven human isoforms of NOX participate in critical physiological and pathophysiological processes. Recently solved structures of two human NOX isoforms provide much new information, but do not fully elucidate controls on the electron transfer pathway from NAD(P)H substrate through FAD and heme cofactors to the final ROS product. SpNOX, a bacterial NOX homolog from Streptococcus pneumoniae, shows robust constitutive activity in detergent solution, making it a good prototype for exploring electron transfer in the NOX family. Here we present crystal structures of wildtype and mutant full-length and dehydrogenase (DH) domain-only constructs of SpNOX. The isolated DH domain acts as a flavin reductase, and both DH and full-length constructs use either NADPH or NADH as substrate. Our data supports hydride transfer from NAD(P)H to FAD as the rate limiting step in electron transfer. Using the DH domain, we demonstrate the role of F397 in allowing access of nicotinamide to the flavin isoalloxazine, while in the full-length construct, we used mutants and flavin analogs to confirm the contribution of both domains to flavin binding observed in the structure. Comparison with homologous enzymes suggests distal heme access may influence the final electron acceptor, while the relative position of DH and TM does not necessarily correlate with activity of a given NOX family member. Based on this comparison, SpNOX appears to be a good model of active NOX2, which allows us to propose an explanation for NOX2’s requirement for activation.
Widespread B-vitamin auxotrophy in marine particle-associated bacteria

Microbial community assembly is governed by complex interaction networks based on the secretion and exchange of metabolites. While the importance of trophic interactions (e.g. cross-feeding of metabolic byproducts) in structuring microbial communities is well-established, the roles of myriad natural products such as vitamins, siderophores, and antibiotics remain unclear. Here, we focus on the role of B vitamins in coastal marine bacterial communities that degrade particulate organic matter. We find that natural seawater particle-associated communities are vitamin limited and almost a third of bacterial isolates from these communities are B vitamin auxotrophs. Auxotroph growth rates are limited under even maximal environmental vitamin concentrations, indicating that auxotrophs likely survive through cross-feeding with community members. We find that polysaccharide-degrading bacteria tend to be vitamin prototrophs, suggesting that the initial arrival of degraders to a particle may promote a succession to auxotrophic taxa partially through vitamin cross-feeding. However, auxotrophs with complementary vitamin requirements were generally not able to grow in co-culture, and auxotroph growth was only partially rescued by prototrophs. We conclude that while vitamin auxotrophies are important metabolic dependencies shaping community structure, vitamin cross-feeding may primarily take place through cell lysis.
Devising reliable and accurate epigenetic predictors: choosing the optimal computational solution

Illumina DNA methylation arrays are frequently used for the discovery of methylation signatures associated with aging and disease. One of the major hurdles to overcome when training trait prediction models is the high dimensionality of the data, with the number of features (target CpGs) greatly exceeding the typical number of samples assessed. In addition, most large-scale DNA methylation-based studies do not include replicate measurements for a given sample, making it impossible to estimate the degree of measurement uncertainty. Hence, the robustness of the assay and reliability of the prediction models are critical to ensure potential clinical utility. Here, we test the performance of different versions of age and cancer prediction models trained either directly on the original features (CpGs) or derived principal components (PCs). Utilizing PCA for dimension reduction consistently led to small improvements in the reliability of the age prediction models, measured in terms of the repeatability of technical replication. However, this improvement came at the cost of a notable reduction in their predictive accuracy. Moreover, by modeling prediction performance as a function of the training set size, we show that the PC-based models need far larger training set sizes to be similarly accurate as CpG-based models. Dimension reduction by PCA also resulted in a markedly lower predictive accuracy when replacing simple penalized regression models by weighted ensembles of deep-learning models for cancer prediction.
GUANinE v1.0: Benchmark Datasets for Genomic AI Sequence-to-Function Models

Computational genomics increasingly relies on machine learning methods for genome interpretation, and the recent adoption of neural sequence-to-function models highlights the need for rigorous model specification and controlled evaluation, problems familiar to other fields of AI. Research strategies that have greatly benefited other fields — including benchmarking, auditing, and algorithmic fairness — are also needed to advance the field of genomic AI and to facilitate model development. Here we propose a genomic AI benchmark, GUANinE, for evaluating model generalization across a number of distinct genomic tasks. Compared to existing task formulations in computational genomics, GUANinE is large-scale, de-noised, and suitable for evaluating pretrained models. GUANinE v1.0 primarily focuses on functional genomics tasks such as functional element annotation and gene expression prediction, and it also draws upon connections to evolutionary biology through sequence conservation tasks. The current GUANinE tasks provide insight into the performance of existing genomic AI models and non-neural baselines, with opportunities to be refined, revisited, and broadened as the field matures. Finally, the GUANinE benchmark allows us to evaluate new self-supervised T5 models and explore the tradeoffs between tokenization and model performance, while showcasing the potential for self-supervision to complement existing pretraining procedures.
Continuous Tracking using Deep Learning-based Decoding for Non-invasive Brain-Computer Interface

Brain-computer interfaces (BCI) using electroencephalography (EEG) provide a non-invasive method for users to interact with external devices without the need for muscle activation. While noninvasive BCIs have the potential to improve the lives of both healthy and motor impaired individuals, they currently have limited applications due to inconsistent performance and low degrees of freedom. In this study, we use deep-learning (DL)-based decoders for online Continuous Pursuit (CP), a complex BCI task requiring the user to track an object in 2D space. We developed a new labelling system to use CP data for supervised learning, trained DL-based decoders based on two architectures, including a newly proposed adaptation of the PointNet architecture, and evaluated the performance over several online sessions. We rigorously evaluated the DL-based decoders in a total of 28 human subjects, and found that the DL-based models improved throughout the sessions as more training data became available and significantly outperformed a traditional BCI decoder by the last session. We also performed additional experiments to test an implementation of transfer learning by pre-training models on data from other subjects, and mid-session training to reduce inter-session variability. The results from these experiments show that pre-training did not significantly improve performance, but updating the models mid-session may have some benefit. Overall, these findings support the use of DL-based decoders for improving BCI performance in complex tasks like CP, which can expand the potential applications of BCI devices and help improve the lives of both healthy individuals and motor-impaired patients.
Sleep stages antagonistically modulate reactivation drift

Hippocampal reactivation of waking neuronal assemblies in sleep is a key initial step of systems consolidation. Nevertheless, it is unclear whether reactivated assemblies are static or whether they reorganize gradually over prolonged sleep. Here, we tracked reactivated CA1 assembly patterns over ∼20 hours of sleep/rest periods and related them to assemblies seen before or after in a spatial learning paradigm. We found that reactivated assembly patterns were gradually transformed and started to resemble those seen in the subsequent recall session. Periods of rapid eye movement (REM) sleep and non-REM (NREM) had antagonistic roles: while NREM accelerated the assembly drift, REM countered it. Moreover, only a subset of rate-changing pyramidal cells contributed to the drift, while stable firing rate cells maintained unaltered reactivation patterns. Our data suggest that prolonged sleep promotes the spontaneous reorganization of spatial assemblies, which can contribute to daily cognitive map changes or encoding new learning situations.
Overleaf Example

The vast majority of techniques to train fair models require access to the protected attribute (e.g., race, gender), either at train time or in production. However, in many important applications this protected attribute is largely unavailable. In this paper, we develop methods for measuring and reducing fairness violations in a setting with limited access to protected attribute labels. Specifically, we assume access to protected attribute labels on a small subset of the dataset of interest, but only probabilistic estimates of protected attribute labels (e.g., via Bayesian Improved Surname Geocoding) for the rest of the dataset. With this setting in mind, we propose a method to estimate bounds on common fairness metrics for an existing model, as well as a method for training a model to limit fairness violations by solving a constrained non-convex optimization problem. Unlike similar existing approaches, our methods take advantage of contextual information – specifically, the relationships between a model’s predictions and the probabilistic prediction of protected attributes, given the true protected attribute, and vice versa – to provide tighter bounds on the true disparity. We provide an empirical illustration of our methods using voting data. First, we show our measurement method can bound the true disparity up to 5.5x tighter than previous methods in these applications. Then, we demonstrate that our training technique effectively reduces disparity while incurring lesser fairness-accuracy trade-offs than other fair optimization methods with limited access to protected attributes.
A CASE STUDY ON THE IMPACT OF VIDEO GAMES TOWARDS MALAYSIAN YOUTH

Due to the rapid growth of technology in recent years, the technology is revolutionising the video game industry and opening the door for a new generation of gamers. However, spending hours a day playing video games could possibly affect our life as we indulge ourselves in video games for a long period of time. So, we would like to provide some insights on the effects of video games in this study. The aim of this study was to determine the effect of video games towards youth on academic performance, prosocial behaviour, physical health and mental health. The data collection was carried out by sending questionnaires to youths in Malaysia, aged 15 to 24. There were a total of 201 respondents who completed the questionnaire and the data collected were analysed using a bivariate correlation test. Pearson correlation between the level of video games addiction and each independent variable (academic performance, social behaviour, physical health and mental health) are calculated for the results. The results of our study showed that there is a moderately weak positive correlation between the level of video games of addiction and prosocial behaviour (r = 0.231, p = 0.001). The correlation between video games and academic performance (r = -0.119, p = 0.092), physical health (in terms of BMI (r = 0.123, p = 0.081) and physical health score (r = -0.138, p = 0.051)) and mental health are not statistically significant. The results proved that video games will positively affect prosocial behaviour. The results of this research can help in expanding the knowledge of the positive effects of video games towards the youth on prosocial behaviour.
-Adrenoceptor blockade modulates fusiform gyrus activity to black versus white faces.

Introduction The beta-adrenoceptor antagonist propranolol is known to reduce peripheral and central activity of noradrenaline. A recent study found that intervention with propranolol diminished negative implicit racial bias. Materials and method The current study used functional magnetic resonance imaging (fMRI) in order to determine the neural correlates of this effect. Healthy volunteers ( N =40) of white ethnic origin received a single oral dose (40 mg) of propranolol, in a randomised, double-blind, parallel group, placebo-controlled design, before viewing unfamiliar faces of same and other race. Results and discussion We found significantly reduced activity in the fusiform gyrus and thalamus following propranolol to out-group faces only. Additionally, propranolol lowered the implicit attitude score, without affecting explicit prejudice measure. Conclusion These findings suggest that noradrenaline pathways might modulate racial bias by acting on the processing of categorisation in the fusiform gyrus.
Preseason Forecasts of Pink Salmon Harvests in Southeast Alaska Using Bayesian Model Averaging

Competing models for generating a forecast of salmon returns may give differing predictions yet have similar credibility. Within a single model, a wide range of alternative parameter values may also have similar credibility. Bayesian methods allow us to incorporate a wide range of models, weighting their forecasts by the posterior probability of each model and parameter combination. I illustrate this procedure by forecasting pink salmon harvests for the year 2002 for northern and southern Southeast Alaska.
Digital Commons @ University of South Florida Digital Commons @ University of South Florida

: Norm-based grading has been associated with a reduction in student incentives to learn. Thus, it is important to understand faculty incentives for using norm-based grading. This paper used two waves of the National Study of Postsecondary Faculty to examine faculty characteristics related to the use of norm-based grading. Results suggest that norm-based grading is more likely when faculty and departments are more research oriented. Faculty who are at lower rank, male, younger, in science and social science departments are more likely to use norm-based grading, while faculty who feel that teaching should be the primary promotion criterion use criteria-based grading
IMPACT OF ENVIRONMENTAL TOBACCO SMOKE ON OLFACTORY FUNCTION IN NON-SMOKERS: AN OBSERVATIONAL STUDY

Background: Environmental tobacco smoke (ETS) is a noxious combination of chemicals and particulate matter released from burning tobacco products. The aim is to investigate the impact of ETS exposure on olfactory function in non-smokers, focusing on differences in odor identification, discrimination, and threshold scores between individuals with regular ETS exposure (n=120) and those with minimal or no exposure (n=130). Materials and Methods: We recruited 250 non-smokers aged 18-60 years from public spaces, workplaces, and residential areas. ETS exposure was assessed through self-reported questionnaires, recording frequency and duration of exposure in various environments. Validated olfactory tests, the Sniffin' Sticks Identification Test (SSIT) for odor identification and the Connecticut Chemosensory Clinical Research Center (CCCRC) Test for discrimination and threshold, were used to evaluate olfactory function. Descriptive statistics compared mean scores between the ETS-exposed and non-exposed groups, and linear regression analysis adjusted for age, gender, and respiratory health status to explore associations. Result: Participants regularly exposed to ETS showed significantly lower olfactory function scores than their non-exposed counterparts. Odor identification scores were reduced by 12.5% in the ETS-exposed group, indicating difficulty in correctly identifying odors during the SSIT. Additionally, the ETS-exposed group demonstrated a 9.8% decrease in odor discrimination scores during the CCCRC Test, suggesting impaired ability to differentiate between odors. Moreover, their mean odor threshold score was reduced by 14.2%, indicating a higher threshold for detecting odors, necessitating higher concentrations to perceive them. The p-value (p<0.001) demonstrated statistical significance for the relationship between ETS exposure and olfactory function scores. Conclusion: This study provides compelling evidence of a significant negative association between ETS exposure and olfactory function in non-smokers. Regular ETS exposure was associated with impaired odor identification, discrimination, and threshold abilities. These findings underscore the importance of reducing second-hand smoke exposure to safeguard non-smokers' olfactory health. Implementing effective public health policies to minimize ETS exposure in public spaces, workplaces, and residential areas is crucial.
Governors

Chapter 3 focuses on the administration of empire, from the Colonial Office in London to the experiences of governors and civil servants around the globe, whose lives were increasingly dominated by tedious meetings and dull dispatches. It shows that the empire became more bureaucratic during the nineteenth century, as the British implemented a system of centralized administrative rule that sheds light on the origins of Weber’s modern bureaucratic state. The volume of paperwork grew dramatically, and high-level officials, who relished the leisured lifestyle that characterized the aristocratic ideal, complained regularly about the quantity of deskwork and the frequency of ritualized public duties. Moreover, there were increasing numbers of officials who had to work in remote locations performing menial tasks. This chapter thus challenges the “great man” view of history, highlighting the limits on individual action and the impact of bureaucratization on administrators’ sense of mission.
Cardiovascular and neuropsychiatric safety of varenicline and bupropion compared with nicotine replacement therapy for smoking cessation: study protocol of a retrospective cohort study using the QResearch general practice database

Introduction: Cigarette smoking continues to be the leading cause of preventable death and is the main risk factor of major diseases such as chronic obstructive pulmonary disease (COPD). The best treatment to help smokers quit is a combination of behavioural support with pharmacotherapy. Varenicline is the newest drug on the market and has been shown to be effective in the general smoking population and in smokers with COPD. The safety profile of varenicline was initially established using standard approaches to pharmacovigilance, but postmarketing reports have raised concerns about a possible association between the use of varenicline and cardiovascular and neuropsychiatric events. Although recent studies have not confirmed such an association, further research is needed given the large number of smokers who are being prescribed varenicline, including important subgroups such as smokers with COPD who may be particularly vulnerable to side effects of drugs. The aim of this study is to assess the cardiovascular and neuropsychiatric safety of varenicline using data from the QResearch general practice (GP) database. Methods and analysis: We will conduct a retrospective cohort study in the QResearch GP database. Patients will be categorised into three exposure groups: prescription of (1) varenicline, (2) bupropion or (3) nicotine replacement therapy (NRT Rx; =reference group). We will separately consider major incident neuropsychiatric and cardiovascular outcomes that occur during 6 months of follow-up using Cox proportional hazards models, adjusted for confounders. Furthermore, propensity score analysis will be used as an analytical approach to account for potential confounding by indication. Ethics and dissemination: This work involves analysis of anonymised, routinely collected data. The protocol has been independently peer-reviewed by the QResearch Scientific Board and meets the requirements of the Trent research ethics committee. We plan to disseminate the results from this study via articles in international peer-reviewed journals and presentations at relevant national and international health conferences.
Steady state sediment transport through an area of net deposition: Multisize class solutions

In this paper, analytical solutions are developed for the multisize class equations derived by Hairsine et al. [2002] for steady state sediment transport over areas of net deposition. Under conditions of a constant flow velocity we are able to decouple the equations and reduce the solution to a straightforward integral for the largest size class. All other size class solutions are then given by an algebraic equation. For practical applications we also derive simple but accurate approximations to this integral, resulting in solutions for all size classes being known explicitly as a function of distance. The effect of infiltration within a net deposition zone is then considered; however, decoupling of the governing equations is no longer possible as the flow velocities are now spatially dependent, and a full numerical solution is required.
Soil fertility and ﬁne root dynamics in response to 4 years of nutrient (N, P, K) fertilization in a lowland tropical moist forest, Panama

The question of how tropical trees cope with infertile soils has been challenging to address, in part, because ﬁne root dynamics must be studied in situ . We used annual fertilization with nitrogen (N as urea, 12.5 g N m - 2 year - 1 ), phosphorus (P as superphosphate, 5 g P m - 2 year - 1 ) and potassium (K as KCl, 5 g K m - 2 year - 1 ) within 38 ha of old-growth lowland tropical moist forest in Panama and examined ﬁne root dynamics with minirhizotron images.We expected that added P, above all, would (i) decrease ﬁne root biomass but, (ii) have no impact on ﬁne root turnover. Soil in the study area was moderately acidic (pH = 5.28), had moderate concentrations of exchangeable base cations (13.4 cmol kg - 1 ), low concentrations of Bray-extractable phosphate (PO 4 = 2.2 mg kg - 1 ), and modest concentrations of KCl-extractable nitrate (NO 3 = 5.0 mg kg - 1 ) and KCl-extractable ammonium (NH 4 = 15.5 mg kg - 1 ). Added N increased concentrations of KCl-extractable NO 3 and acidiﬁed the soil by one pH unit. Added P increased concentrations of Bray-extractable PO 4 and P in the labile fraction. Concentrations of exchangeable K were elevated in K addition plots but reduced by N additions. Fine root dynamics responded to added K rather than added P. After 2 years, added K decreased ﬁne root biomass from 330 to 275 g m - 2 . The turnover coefﬁcient of ﬁne roots < 1 mm diameter ranged from 2.6 to 4.4 per year, and the largest values occurred in plots with added K. This study supported the view that biomass and dynamics of ﬁne roots respond to soil nutrient availability in species-rich, lowland tropical moist forest. However, K rather than P elicited root responses. Fine roots smaller than 1 mm have a short lifetime ( < 140 days), and control of ﬁne root production by nutrient availability in tropical forests deserves more study.