Miracle-dz/UniFAR-FTUs huggingface dataset:
Association of leaf spectral variation with functional genetic variants

The application of in-field and aerial spectroscopy to assess functional and phylogenetic variation in plants has led to novel ecological insights and promises to support global assessments of plant biodiversity. Understanding the influence of plant genetic variation on reflectance spectra will help to harness this potential for biodiversity monitoring and improve our understanding of why plants differ in their functional responses to environmental change. Here, we use an unusually well-resolved genetic mapping population in a wild plant, the coyote tobacco Nicotiana attenuata, to associate genetic differences with differences in leaf spectra for plants in a field experiment in their natural environment. We analyzed the leaf reflectance spectra using FieldSpec 4 spectroradiometers on plants from 325 fully genotyped recombinant inbred lines (RILs) of N. attenuata grown in a blocked and randomized common garden experiment. We then tested three approaches to conducting Genome-Wide Association Studies (GWAS) on spectral variants. We introduce a new Hierarchical Spectral Clustering with Parallel Analysis (HSC-PA) method which efficiently captured the variation in our high-dimensional dataset and allowed us to discover a novel association, between a locus on Chromosome 1 and the 445-499 nm spectral range, which corresponds to the blue light absorption region of chlorophyll, indicating a genetic basis for variation in photosynthetic efficiency. These associations lie in close proximity to candidate genes known to be expressed in leaves and having annotated functions as methyltransferases, indicating possible underlying mechanisms governing these spectral differences. In contrast, an approach using well-established spectral indices related to photosynthesis, reducing complex spectra to a few dimensionless numbers, was not able to identify any robust associations, while an approach treating single wavelengths as phenotypes identified the same associations as HSC-PA but without the statistical power to pinpoint significant associations. The HSC-PA approach we describe here can support a comprehensive understanding of the genetic determinants of leaf spectral variation which is datadriven but human-interpretable, and lays a robust foundation for future research in plant genetics and remote sensing applications.
Voluntary effort to read reshapes stimulus selectivity in the visual word form area and increases its communication with the language network

Reading depends on a brain region known as the “visual word form area” (VWFA). Although this region responds most strongly to written words, its selectivity is not absolute, and it exhibits top-down modulations related to task demands. We used fMRI to characterize the combination of factors that most strongly activate VWFA. We presented three stimulus types (English words, pseudowords, and visually matched false fonts) while the participant performed three different tasks: discriminating the lexicality of the character string, discriminating the color of the character string, and discriminating the color of the fixation mark while ignoring the character strings. We found a strong interaction between stimulus type and task: compared to the fixation task, the VWFA’s response to text was elevated in the lexical task but not in the character string color task. Thus, the enhanced response requires voluntary effort to read words and does not automatically occur when words are attended. Moreover, this effect of reading effort is stimulus-selective: false fonts presented during the lexical task evoked smaller responses compared to when they were ignored. These patterns were absent in other visual regions but were present in a putative Broca’s area in the left frontal cortex. Additionally, we found strengthened functional connectivity between Broca’s area and the VWFA during the lexical decision task. In sum, strong activation of the VWFA is not merely dependent on the presence of words nor on engagement in a linguistic task, but on the conjunction of both. Significance Statement Neuroscientists have long debated whether a region of ventral temporal cortex, often termed the visual word form area (VWFA), is specialized for identifying written words or whether it serves more general language functions. We used fMRI to characterize what drives VWFA activity: seeing words, attending visually to words, or explicitly trying to read words. We found the VWFA prefers letter strings over visually-matched shapes even when attention is withdrawn, but it is maximally engaged only when letter strings are present and the participant voluntarily tries to read them. These response patterns, combined with functional connectivity analyses, support a hybrid model: the VWFA has inherent visual selectivity for text, but its function is actively reshaped by language processing.
Improving vocal communication with a ketogenic diet in a mouse model of autism

Background Deficits in social communication and language development is a hallmark of autism spectrum disorder currently with no cure. Interventional studies using animal models have been very limited in demonstrating improved vocal communication. Autism has been proposed to involve metabolic dysregulation. Ketogenic diet (KD) is a metabolism-based therapy for medically intractable epilepsy, and its applications in other neurological conditions have been increasingly tested. However, how it would affect vocal communication has not been explored. The BTBR mouse strain is considered a model of idiopathic autism. They display robust deficits in vocalization during social interaction, and have metabolic changes implicated in autism. Methods We investigated the effects of KD on ultrasonic vocalizations (USVs) in juvenile and adult BTBR mice during male-female social encounters. Results After a brief treatment with KD, the amount, spectral bandwidth, and much of the temporal structure of USVs were robustly improved in both juvenile and adult BTBR mice. Composition of call categories and transitioning between individual call subtypes was more effectively improved in juvenile BTBR mice. Limitations Although sharing certain attributes, mouse vocalization is unlikely to model all aspects in the development and deficits of human language. KD is highly restrictive and can be difficult to administer, especially for many people with autism who have narrow food selections. Side effects and potential influence on development should also be considered. Future studies are required to tease apart the molecular mechanisms of KD’s effects on vocalization. Conclusions Together, our data provide further support to the hypothesis that metabolism-based dietary intervention could modify disease expression, including core symptoms, in autism.
Nphos: Database and Predictor of Protein N-phosphorylation

Protein N-phosphorylation widely present in nature and participates in various biological functions. However, current knowledge on N-phosphorylation is extremely limited compared to that on O-phosphorylation. In this study, we collected 11,710 experimentally verified N-phosphosites of 7344 proteins from 39 species and subsequently constructed the database Nphos to share up-to-date information on protein N-phosphorylation. Upon these substantial data, we characterized the sequential and structural features of protein N-phosphorylation. Moreover, after comparing of hundreds of learning models, we chose and optimized gradient boosting decision tree (GBDT) models to predict three types of human N-phosphorylation, achieving mean areas under the receiver operating characteristic curve (AUC) of 90.56%, 91.24%, and 92.01% for pHis, pLys, and pArg, respectively. Meanwhile, we discovered 488,825 distinct N-phosphosites in the human proteome. The models were also deployed in Nphos for interactive N-phosphosite prediction. In summary, this work provides new insights and points for both flexible and focused investigations of N-phosphorylation. It will also facilitate a deeper and more systematic understanding of protein N-phosphorylation modification by providing a data and technical foundation. Nphos is freely available at http://www.bio-add.org and http://ppodd.org. cn/Nphos/.
Multiple origins of cephalic sutures in trilobites and their relatives

Euarthropods are an extremely diverse phylum in the modern, and have been since their origination in the early Palaeozoic. They grow through moulting the exoskeleton (ecdysis) facilitated by breaking along lines of weakness (sutures). Artiopodans, a group that includes trilobites and their non-biomineralizing relatives, dominated arthropod diversity in benthic communities during the Palaeozoic. Most trilobites – a hyperdiverse group of tens of thousands of species -moult by breaking the exoskeleton along cephalic sutures, a strategy that has contributed to their high diversity during the Palaeozoic. However, the recent description of similar sutures in early diverging non-trilobite artiopodans mean that it is unclear whether these sutures were evolved deep within Artiopoda, or evolved multiple times within the group. Here we describe new well-preserved material of Acanthomeridion, a putative early diverging artiopodan, including hitherto unknown details of its ventral anatomy and appendages revealed through CT scanning, highlighting additional possible homologous features between Acanthomeridion and trilobites. We used two coding strategies treating structures as homologous or independently derived across multiple phylogenetic analysis techniques (parsimony or Bayesian inference), and showed that regardless of these variables, the sutures crucial for the success and growth of the hyperdiverse trilobites evolved multiple times within Artiopoda.
Comparative spatial transcriptomics of peach and nectarine fruits elucidates the mechanism underlying fruit trichome development

Peach (Prunus persica) is an economically significant fruit-bearing tree. The trichomes of peach fruits are essential for their growth and development by playing a protective role against abiotic stresses, such as intense ultraviolet (UV) light, high temperature, cold-induced stress, and biotic stresses, such as pests and disease infestation. However, the mechanism underlying trichome development in peach fruits is unknown. Therefore, spatial transcriptome sequencing technology was used to compare the transcriptomic information seven days after flowering (DAF) of peach and nectarine fruits at an ultra-high resolution. The results revealed significant variations in how fruits at the early development stage responded to stress exposure. Comparatively, nectarine response to stress was significantly magnified than peach. Notably, a novel trichome-related marker gene, Prupe.7G196500, was identified in peach, which showed a robust function in response to jasmonic acid and wounding. Further, the Prupe.7G196500pro::GUS construct was found to specifically expressed in the trichomes of the true leaves of 10-day-old Arabidopsis thaliana (Arabidopsis) seedlings and induced by drought treatment. Finally, gain-of-function analysis showed that Prupe.7G196500 promoted trichomes development. In conclusion, this study identified the cell types and novel marker genes associated with peach fruit. The role of Prupe.7G196500 in positively regulating trichome development was also characterized, thereby laying the foundation for analyzing the mechanism involved in trichome development in peach fruits.
FedGMMAT: Federated Generalized Linear Mixed Model Association Tests

Increasing genetic and phenotypic data size is critical for understanding the genetic determinants of diseases. Evidently, establishing practical means for collaboration and data sharing among institutions is a fundamental methodological barrier for performing high-powered studies. As the sample sizes become more heterogeneous, complex statistical approaches, such as generalized linear mixed effects models, must be used to correct for confounders that may bias results. On another front, due to the privacy concerns around Protected Health Information (PHI), genetic information is restrictively protected by sharing according to regulations such as Health Insurance Portability and Accountability Act (HIPAA). This limits data sharing among institutions and hampers efforts around executing high-powered collaborative studies. Federated approaches are promising to alleviate the issues around privacy and performance, since sensitive data never leaves the local sites. Motivated by these, we developed FedGMMAT, a federated genetic association testing tool that utilizes a federated statistical testing approach for efficient association tests that can correct for arbitrary fixed and random effects among different collaborating sites. Genetic data is never shared among collaborating sites, and the intermediate statistics are protected by homomorphic encryption. Using simulated and real datasets, we demonstrate FedGMMAT can achieve the virtually same results as pooled analysis under a privacy-preserving framework with practical resource requirements.
Unravelling the origins of boldness: A common garden experiment with cave fish (Barbatula barbatula)

Many animals show an aversion to bright, open spaces, with significant variability seen across species, populations, and individuals within populations. Although there is much interest in the underlying causes of this behaviour, few studies have been able to systematically isolate the role of heritable and environmental effects. Here we addressed this gap using a common garden experiment with cave fish. Specifically, we bred and cross-bred cave loaches (Barbatula barbatula) in the lab, raised the offspring in complete darkness or normal light conditions, and studied their light avoidance behaviour. Cave fish spent much more time in a light area and ventured further out, while surface fish spent considerable time on the edge between light and dark areas. Hybrids behaved most similarly to cave fish. Light treatment and eye size and quality only had a modest effect. Our results suggest light avoidance behaviour of cave fish has a heritable basis and is fundamentally linked to increased boldness rather than reduced vision, which is likely adaptive given the complete lack of macropredators in the cave environment. Our study provides novel experimental insights into the behavioural divergence of cave fish and contributes to our broader understanding of the evolution of boldness and behavioural adaptation.
Afanc: a Metagenomics Tool for Variant Level Disambiguation of NGS Datasets

Genomics is amongst the most powerful tools available for mounting a clinical response to infectious disease. The accurate and precise taxonomic evaluation of pathogens is essential when building a picture of pathogenicity, virulence, transmission, and drug resistance. Carrying out such profiling in a high throughput manner necessitates the development of reliable bioinformatic tools. Here we present Afanc, a novel metagenomic profiler which is sensitive down to species and strain level taxa, and capable of elucidating the complex pathogen profile of compound datasets. We compared Afanc against currently available cutting edge profilers using 3 datasets: single species read sets simulated from the full Mycobacteriaceae taxonomic landscape; compound read sets containing multiple Mycobacteriaceae species and variants; and real data covering the majority of the M. tuberculosis lineage taxonomic space. Afanc outperformed all profilers, both generic and Mycobacteriaceae specific, across all tested fields. As a species agnostic profiler, we predict that Afanc will be of great utility when carrying out highly specific and sensitive pathogen profiling of clinical datasets. Such analyses are essential in advising both the clinical response to an individual disease case, and in forming the foundation of epidemiological surveys.
Empirical analysis of countdown signals on pedestrian behaviour

The installation of countdown pedestrian signal display at signalised intersections was proposed as part of an overall strategy for improving pedestrian safety, especially at such intersections. Based on field observations of critical pedestrian-related parameters at five similar intersections (three with countdown signals and two without countdown signals) in Shanghai, this research evaluated the impact of countdown signals on intersection safety and efficiency. Three categories of data were collected using a video detection system and questionnaire methods – crossing behaviour data (e.g. pedestrian speed and number of pedestrians obeying signals), questionnaire data (e.g. understanding of countdown signals) and crosswalk-related data (e.g. cycle length and length of the crosswalk). Statistical analysis results based on t-tests and analysis of variance revealed that the impacts of countdown signals on older and younger people are different in terms of compliance ratio and successful crossing ratio. Count.
Dynamic Heights and Zonal Geostrophic Transports in the Central Tropical Pacific during 1979–84

Abstract Dynamic height is calculated from XBT and surface salinity data in the central Pacific using a mean temperature–salinity (T–S) relation in the usual way below the thermocline but assuming isohaline water in the upper layer where the temperatures are isothermal. This scheme produces a better estimate of dynamic height than the use of a mean T–S relationship alone and produces significant improvements near the equator where small pressure gradients imply large geostrophic currents. During the El Nino of 1982–83, water of very low surface salinity was observed spanning the equator; this event is attributed both to extreme local rainfall and anomalous advection from the western Pacific. Geostrophic transports of the major surface currants are estimated for the period January 1979 through December 1984. The North and South Equatorial countercurrents are found to have the largest annual fluctuations, and the vertical displacements of the thermocline associated with these fluctuations are qualitatively .
Towards Verifying Monotonicity and Robustness Properties for Domain-Specific DRL Algorithms

Deep Reinforcement Learning (DRL) algorithms have demonstrated significant performance benefits compared to traditional heuristics in various systems and networking applications. However, concerns surrounding their explainability, generalizability, and robustness pose obstacles to their widespread deployment. In response, the research community has explored the application of formal verification techniques to ensure the safe deployment of DRL algorithms. This study focuses on DRL algorithms with discrete numerical action spaces, which are commonly utilized in systems and networking domains but have been under-explored when it comes to formal analysis. We investigate two fundamental properties: monotonicity and robustness. We employ formal methods to verify these properties beyond the confines of the training set, thereby enhancing generalization and validating robustness. To explore the effectiveness and tractability of the proposed verification approach, we implement a proof of concept using Gurobi and present a case study involving two systems and networking DRL algorithms.
Separating Soil Respiration into Plant and Soil Components Using Analyses of the Natural Abundance of Carbon‐13

In presence of vegetation, the CO 2 -C produced by respiration activity in soils originates from plant C (rhizosphere respiration, R rh ) and from soil C (soil respiration, R s ). Quantitative estimates of the CO 2 produced by each source are required in many studies of C dynamics in the soil-plant system. In this study, we (i) used measurements of the 13 C value of soil CO 2 to separate total soil respiration (R t ) into subeomponents R rh and R, in a maize (Zea mays L.) field under undisturbed conditions and (ii) compared these R rh estimates with values obtained using the root-exclusion approach. The maximum contribution of R rh to total respiration was 45%, observed in August. Estimates of R rh increased from zero 30 d after planting to 2 g CO 2 -C m -2 d -1 70 d after planting, remained relatively constant at that level in August, and then decreased until the end of the growing season. The total C losses as R rh were 17% of the crop net assimilation. Estimates of R s gradually declined from 3.3 g CO 2 -C m -2 d -1 in late June to 1.4 g CO 2 -C m -2 d -1 at the end of the season. Losses of soil C represented 6% of total soil C. Variable values of δ 13 C of the soil CO 2 in the control plot after Day 250 made the technique less reliable late in the season. However, several observations indicated that the approach has potential to provide quantitative estimates of R rh and R,. First, the seasonal pattern of the R rh estimates coincided with that of the plant growth and physiological activity. Second, the cumulated R rh across the growing season agreed well with published data obtained using 14 C labeling techniques. Third, in the maize plot, variation in the estimated R, was closely correlated with changes in soil temperature with a Q 10 of 1.99 (r 2 = 0.87). Finally, the estimates of R rh obtained using the isotopic approach agreed well with those obtained using the root exclusion technique.
Outcomes of cardiopulmonary resuscitation in the emergency department of a tertiary hospital in Malaysia

Introduction: There are insufficient data available regarding the outcome of cardiac arrest (CA) resuscitated in the emergency department in Malaysia. This study aims to determine the incidence of CA, the return of spontaneous circulation (ROSC), survival to admission (STA), survival to discharge (STD) and factors influencing the overall outcome of CA. Material and Methods: This is a retrospective observational study done in Hospital Sg Buloh (HSB), a tertiary referral centre in an urban area located north of Kuala Lumpur, Malaysia's capital city, from January until December 2018, involving 289 patients. All cases with CPR and a sustained return of spontaneous circulation (ROSC) were included in the study and followed up until discharged or died in the hospital. Results: Out of 236 patients recruited, 25.8% achieved ROSC, 15.7% survived on admission, and 4.2% of patients were discharged alive. Of 74.1% of witnessed OHCA, only 17.5% received bystander CPR. Factors with favourable outcomes include CA in ED (p<0.001), the initial rhythm of ventricular fibrillation (p=0.003), defibrillation (p=0.024), OHCA witnessed by emergency medical services (EMS) (p=0.024) and intravenous adrenaline administration (p=0.001). When using multivariate regression analysis, positive outcomes were associated with the cardiac and respiratory cause of CA (Adjusted Odd Ratio (AOR) 3.66; 95% Confidence Intervals, 95%CI: 2.52 - 12.61 and AOR 8.76; 95%CI: 5.76-15.46, respectively) as well as OHCA witnessed by EMS (AOR 10.81; 95%CI: 1.84-19.52). Conclusions: Despite being an upper-middle-income country and having advancements in the healthcare system, a relatively lower STD rate among survivors of CA in the ED was observed in this study. There was underutilization of the EMS among patients with CA. The bystander CPR rate among patients with CA in
Penalized maximum likelihood estimator for normal mixtures

The estimation of the parameters of a mixture of Gaussian densities is considered, within the framework of maximum likelihood. Due to unboundedness of the likelihood function, the maximum likelihood estimator fails to exist. We adopt a solution to likelihood function degeneracy which consists in penalizing the likelihood function. The resulting penalized likelihood function is then bounded over the parameter space and the existence of the penalized maximum likelihood estimator is granted. As original contribution we provide asymptotic properties, and in particular a consistency proof, for the penalized maximum likelihood estimator. Numerical examples are provided in the finite data case, showing the performances of the penalized estimator compared to the standard one.