How genomics can help biodiversity conservation.

The availability of public genomic resources can greatly assist biodiversity assessment, conservation, and restoration efforts by providing evidence for scientifically informed management decisions. Here we survey the main approaches and applications in biodiversity and conservation genomics, considering practical factors, such as cost, time, prerequisite skills, and current shortcomings of applications. Most approaches perform best in combination with reference genomes from the target species or closely related species. We review case studies to illustrate how reference genomes can facilitate biodiversity research and conservation across the tree of life. We conclude that the time is ripe to view reference genomes as fundamental resources and to integrate their use as a best practice in conservation genomics.

Gut Analysis Toolbox: Automating quantitative analysis of enteric neurons.

The enteric nervous system (ENS) consists of an extensive network of neurons and glial cells embedded within the wall of the gastrointestinal (GI) tract. Alterations in neuronal distribution and function are strongly associated with GI dysfunction. Current methods for assessing neuronal distribution suffer from undersampling, partly due to challenges associated with imaging and analyzing large tissue areas, and operator bias due to manual analysis. We present the Gut Analysis Toolbox (GAT), an image analysis tool designed for characterization of enteric neurons and their neurochemical coding using 2D images of GI wholemount preparations. It is developed in Fiji, has a user-friendly interface and offers rapid and accurate segmentation via custom deep learning (DL) based cell segmentation models developed using StarDist, and a ganglion segmentation model in deepImageJ. We use proximal neighbor-based spatial analysis to reveal differences in cellular distribution across gut regions using a public dataset. In summary, GAT provides an easy-to-use toolbox to streamline routine image analysis tasks in ENS research. GAT enhances throughput allowing unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples rapidly.

Development of a split-luciferase assay to establish optimal protein secretion conditions for protein production by Bacillus subtilis.

Bacillus subtilis is a Gram-positive bacterium that is frequently used in the bioindustry for the production of various proteins, because of its superior protein secretion capacities. To determine optimal conditions for protein secretion by B. subtilis, a quick and sensitive method for measuring protein secretion is crucial. A fast and universal assay is most useful for detecting diverse proteins in a high-throughput manner. In this study, we introduce a split-luciferase-based method for measuring protein secretion by B. subtilis. The NanoBiT system was used to monitor secretion of four different proteins: xylanase A, amylase M, protein glutaminase A, and GFP nanobody. Our findings underscore the split-luciferase system as a quick, sensitive, and user-friendly method.

Tools to make Stachybotrys chartarum genetically amendable: Key to unlocking cryptic biosynthetic gene clusters.

The soil and indoor fungus Stachybotrys chartarum can induce respiratory disorders, collectively referred to as stachybotryotoxicosis, owing to its prolific production of diverse bioactive secondary metabolites (SMs) or mycotoxins. Although many of these toxins responsible for the harmful effects on animals and humans have been identified in the genus Stachybotrys, however a number of SMs remain elusive. Through in silico analyses, we have identified 37 polyketide synthase (PKS) genes, highlighting that the chemical profile potential of Stachybotrys is far from being fully explored. Additionally, by leveraging phylogenetic analysis of known SMs produced by non-reducing polyketide synthases (NR-PKS) in other filamentous fungi, we showed that Stachybotrys possesses a rich reservoir of untapped SMs. To unravel natural product biosynthesis in S. chartarum, genetic engineering methods are crucial. For this purpose, we have developed a reliable protocol for the genetic transformation of S. chartarum and applied it to the ScPKS14 biosynthetic gene cluster. This cluster is homologous to the already known Claviceps purpurea CpPKS8 BGC, responsible for the production of ergochromes. While no novel SMs were detected, we successfully applied genetic tools, such as the generation of deletionand overexpression strains of single cluster genes. This toolbox can now be readily employed to unravel not only this particular BGC but also other candidate BGCs present in S. chartarum, making this fungus accessible for genetic engineering.

Initial results from the PHEFREE longitudinal natural history study: Cross-sectional observations in a cohort of individuals with phenylalanine hydroxylase (PAH) deficiency.

Over fifty years have passed since the last large scale longitudinal study of individuals with PAH deficiency in the U.S. Since then, there have been significant changes in terms of treatment recommendations as well as treatment options. The Phenylalanine Families and Researchers Exploring Evidence (PHEFREE) Consortium was recently established to collect a more up-to-date and extensive longitudinal natural history in individuals with phenylketonuria across the lifespan. In the present paper, we describe the structure and methods of the PHEFREE longitudinal study protocol and report cross-sectional data from an initial sample of 73 individuals (5 months to 54 years of age) with PAH deficiency who have enrolled. Looking forward, the study holds the promise for advancing the field on several fronts including the validation of novel neurocognitive tools for assessment in individuals with PKU as well as evaluation of the long-term effects of changes in metabolic control (e.g., effects of Phe-lowering therapies) on outcome.

Elliptical Halbach magnet and gradient modules for low-field portable magnetic resonance imaging.

This study aims to develop methods to design the complete magnetic system for a truly portable MRI scanner for neurological and musculoskeletal (MSK) applications, optimized for field homogeneity, field of view (FoV), and gradient performance compared to existing low-weight configurations. We explore optimal elliptic-bore Halbach configurations based on discrete arrays of permanent magnets. In this way, we seek to improve the field homogeneity and remove constraints to the extent of the gradient coils typical of Halbach magnets. Specifically, we have optimized a tightly packed distribution of magnetic Nd2Fe14B cubes with differential evolution algorithms and a second array of shimming magnets with interior point and differential evolution methods. We have also designed and constructed an elliptical set of gradient coils that extend over the whole magnet length, maximizing the distance between the lobe centers. These are optimized with a target field method minimizing a cost function that considers also heat dissipation. We have employed the new toolbox to build the main magnet and gradient modules for a portable MRI scanner designed for point-of-care and residential use. The elliptical Halbach bore has semi-axes of 10 and 14& cm, and the magnet generates a field of 87& mT homogeneous down to 5700& ppm (parts per million) in a 20-cm diameter FoV; it weighs 216& kg and has a width of 65& cm and a height of 72& cm. Gradient efficiencies go up to around 0.8& mT/m/A, for a maximum of 12& mT/m within 0.5& ms with 15& A and 15& V amplifier. The distance between lobes is 28& cm, significantly increased with respect to other Halbach-based scanners. Heat dissipation is around 25& W at maximum power, and gradient deviations from linearity are below 20% in a 20-cm sphere. Elliptic-bore Halbach magnets enhance the ergonomicity and field distribution of low-cost portable MRI scanners, while allowing for full-length gradient support to increase the FoV. This geometry can be potentially adapted for a prospective low-cost whole-body technology.

Looking beyond the mean: quantile regression for comparative physiologists.

Statistical analyses that physiologists use to test hypotheses predominantly centre on means, but the tail ends of the response distribution can behave quite differently and underpin important scientific phenomena. We demonstrate that quantile regression (QR) offers a way to bypass some limitations of least squares regression (LSR) by building a picture of independent variable effects across the whole distribution of a dependent variable. We used LSR and QR with simulated and real datasets. With simulated data, LSR showed no change in the mean response but missed significant effects in the tails of the distribution found using QR. With real data, LSR showed a significant change in the mean response but missed a lack of response in the upper quantiles which was biologically revealing. Together, this highlights that QR can help to ask and answer more questions about variation in nature.

Parameter estimation and forecasting with quantified uncertainty for ordinary differential equation models using QuantDiffForecast: A MATLAB toolbox and tutorial.

Mathematical models based on systems of ordinary differential equations (ODEs) are frequently applied in various scientific fields to assess hypotheses, estimate key model parameters, and generate predictions about the system's state. To support their application, we present a comprehensive, easy-to-use, and flexible MATLAB toolbox, QuantDiffForecast, and associated tutorial to estimate parameters and generate short-term forecasts with quantified uncertainty from dynamical models based on systems of ODEs. We provide software ( https://github.com/gchowell/paramEstimation_forecasting_ODEmodels/) and detailed guidance on estimating parameters and forecasting time-series trajectories that are characterized using ODEs with quantified uncertainty through a parametric bootstrapping approach. It includes functions that allow the user to infer model parameters and assess forecasting performance for different ODE models specified by the user, using different estimation methods and error structures in the data. The tutorial is intended for a diverse audience, including students training in dynamic systems, and will be broadly applicable to estimate parameters and generate forecasts from models based on ODEs. The functions included in the toolbox are illustrated using epidemic models with varying levels of complexity applied to data from the 1918 influenza pandemic in San Francisco. A tutorial video that demonstrates the functionality of the toolbox is included.

An improved CRISPR and CRISPR interference (CRISPRi) toolkit for engineering the model methanogenic archaeon Methanococcus maripaludis.

BACKGROUND: The type II based CRISPR-Cas system remains restrictedly utilized in archaea, a featured domain of life that ranks parallelly with Bacteria and Eukaryotes. Methanococcus maripaludis, known for rapid growth and genetic tractability, serves as an exemplary model for studying archaeal biology and exploring CO2-based biotechnological applications. However, tools for controlled gene regulation remain deficient and CRISPR-Cas tools still need improved in this archaeon, limiting its application as an archaeal model cellular factory. RESULTS: This study not only improved the CRISPR-Cas9 system for optimizing multiplex genome editing and CRISPR plasmid construction efficiencies but also pioneered an effective CRISPR interference (CRISPRi) system for controlled gene regulation in M. maripaludis. We developed two novel strategies for balanced expression of multiple sgRNAs, facilitating efficient multiplex genome editing. We also engineered a strain expressing Cas9 genomically, which simplified the CRISPR plasmid construction and facilitated more efficient genome modifications, including markerless and scarless gene knock-in. Importantly, we established a CRISPRi system using catalytic inactive dCas9, achieving up to 100-fold repression on target gene. Here, sgRNAs targeting near and downstream regions of the transcription start site and the 5'end ORF achieved the highest repression efficacy. Furthermore, we developed an inducible CRISPRi-dCas9 system based on TetR/tetO platform. This facilitated the inducible gene repression, especially for essential genes. CONCLUSIONS: Therefore, these advancements not only expand the toolkit for genetic manipulation but also bridge methodological gaps for controlled gene regulation, especially for essential genes, in M. maripaludis. The robust toolkit developed here paves the way for applying M. maripaludis as a vital model archaeal cell factory, facilitating fundamental biological studies and applied biotechnology development of archaea.

A genetic toolbox to empower Paracoccus pantotrophus DSM 2944 as a metabolically versatile SynBio chassis.

BACKGROUND: To contribute to the discovery of new microbial strains with metabolic and physiological robustness and develop them into successful chasses, Paracoccus pantotrophus DSM 2944, a Gram-negative bacterium from the phylum Alphaproteobacteria and the family Rhodobacteraceae, was chosen. The strain possesses an innate ability to tolerate high salt concentrations. It utilizes diverse substrates, including cheap and renewable feedstocks, such as C1 and C2 compounds. Also, it can consume short-chain alkanes, predominately found in hydrocarbon-rich environments, making it a potential bioremediation agent. The demonstrated metabolic versatility, coupled with the synthesis of the biodegradable polymer polyhydroxyalkanoate, positions this microbial strain as a noteworthy candidate for advancing the principles of a circular bioeconomy. RESULTS: The study aims to follow the chassis roadmap, as depicted by Calero and Nikel, and de Lorenzo, to transform wild-type P. pantotrophus DSM 2944 into a proficient SynBio (Synthetic Biology) chassis. The initial findings highlight the antibiotic resistance profile of this prospective SynBio chassis. Subsequently, the best origin of replication (ori) was identified as RK2. In contrast, the non-replicative ori R6K was selected for the development of a suicide plasmid necessary for genome integration or gene deletion. Moreover, when assessing the most effective method for gene transfer, it was observed that conjugation had superior efficiency compared to electroporation, while transformation by heat shock was ineffective. Robust host fitness was demonstrated by stable plasmid maintenance, while standardized gene expression using an array of synthetic promoters could be shown. pEMG-based scarless gene deletion was successfully adapted, allowing gene deletion and integration. The successful integration of a gene cassette for terephthalic acid degradation is showcased. The resulting strain can grow on both monomers of polyethylene terephthalate (PET), with an increased growth rate achieved through adaptive laboratory evolution. CONCLUSION: The chassis roadmap for the development of P. pantotrophus DSM 2944 into a proficient SynBio chassis was implemented. The presented genetic toolkit allows genome editing and therewith the possibility to exploit Paracoccus for a myriad of applications.

A molecular toolbox for fast and convenient diagnosis of emerging and reemerging bacterial pathogens causing fever of intermediate duration.

PURPOSE: Fever of intermediate duration (FID) is defined as a fever in the community without a specific origin or focus, with a duration between 7 and 28 days. FID is often caused by pathogens associated with animal contact or their arthropods parasites, such as ticks, fleas, or lice. The purpose of this work is to design a collection of molecular tools to promptly and accurately detect common bacterial pathogens causing FID, including bacteria belonging to genera Rickettsia, Bartonella, Anaplasma, and Ehrlichia, as well as Coxiella burnetii. METHODS: Reference DNA sequences from a collection of Rickettsia, Bartonella, Anaplasma, and Ehrlichia species were used to design genus-specific primers and FRET probes targeted to conserved genomic regions. For C. burnetii, primers previously described were used, in combination with a newly designed specific probe. Real-time PCR assays were optimized using reference bacterial genomic DNA in a background of human genomic DNA. RESULTS: The four real-time PCR assays can detect as few as ten copies of target DNA from those five genera of FDI-causing bacteria in a background of 300 ng of human genomic DNA, mimicking the low microbial load generally found in patient's blood. CONCLUSION: These assays constitute a fast and convenient "toolbox" that can be easily implemented in diagnostic laboratories to provide timely and accurate detection of bacterial pathogens that are typical etiological causes of febrile syndromes such as FID in humans.

Parafoveal and foveal N400 effects in natural reading: A timeline of semantic processing from fixation-related potentials.

The depth at which parafoveal words are processed during reading is an ongoing topic of debate. Recent studies using RSVP-with-flanker paradigms have shown that implausible words within sentences elicit an N400 component while they are still in parafoveal vision, suggesting that the semantics of parafoveal words can be accessed to rapidly update the sentence representation. To study this effect in natural reading, we combined the coregistration of eye movements and EEG with the deconvolution modeling of fixation-related potentials (FRPs) to test whether semantic plausibility is processed parafoveally during Chinese sentence reading. For one target word per sentence, both its parafoveal and foveal plausibility were orthogonally manipulated using the boundary paradigm. Consistent with previous eye movement studies, we observed a delayed effect of parafoveal plausibility on fixation durations that only emerged on the foveal word. Crucially, in FRPs aligned to the pretarget fixation, a clear N400 effect emerged already based on parafoveal plausibility, with more negative voltages for implausible previews. Once participants fixated the target, we again observed an N400 effect of foveal plausibility. Interestingly, this foveal N400 was absent whenever the preview had been implausible, indicating that when a word's (im)plausibility is already processed in parafoveal vision, this information is not revised anymore upon direct fixation. Implausible words also elicited a late positive component (LPC), but exclusively when in foveal vision. Our results not only provide convergent neural and behavioral evidence for the parafoveal uptake of semantic information, but also indicate different contributions of parafoveal versus foveal information toward higher level sentence processing.

Mobile toolbox (MTB) remote measures of executive function and processing speed: development and validation.

OBJECTIVE: The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties. METHOD: MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart. RESULTS: All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability. CONCLUSIONS: Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs.

SpatialWavePredict: a tutorial-based primer and toolbox for forecasting growth trajectories using the ensemble spatial wave sub-epidemic modeling framework.

BACKGROUND: Dynamical mathematical models defined by a system of differential equations are typically not easily accessible to non-experts. However, forecasts based on these types of models can help gain insights into the mechanisms driving the process and may outcompete simpler phenomenological growth models. Here we introduce a friendly toolbox, SpatialWavePredict, to characterize and forecast the spatial wave sub-epidemic model, which captures diverse wave dynamics by aggregating multiple asynchronous growth processes and has outperformed simpler phenomenological growth models in short-term forecasts of various infectious diseases outbreaks including SARS, Ebola, and the early waves of the COVID-19 pandemic in the US. RESULTS: This tutorial-based primer introduces and illustrates a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using an ensemble spatial wave sub-epidemic model based on ordinary differential equations. Scientists, policymakers, and students can use the toolbox to conduct real-time short-term forecasts. The five-parameter epidemic wave model in the toolbox aggregates linked overlapping sub-epidemics and captures a rich spectrum of epidemic wave dynamics, including oscillatory wave behavior and plateaus. An ensemble strategy aims to improve forecasting performance by combining the resulting top-ranked models. The toolbox provides a tutorial for forecasting time-series trajectories, including the full uncertainty distribution derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score. CONCLUSIONS: We have developed the first comprehensive toolbox to characterize and forecast time-series data using an ensemble spatial wave sub-epidemic wave model. As an epidemic situation or contagion occurs, the tools presented in this tutorial can facilitate policymakers to guide the implementation of containment strategies and assess the impact of control interventions. We demonstrate the functionality of the toolbox with examples, including a tutorial video, and is illustrated using daily data on the COVID-19 pandemic in the USA.

Clinical Validation of Selected NIH Cognitive Toolbox Tasks in Pediatric Epilepsy.

The NIH Toolbox Cognition Battery (NIHTB-CB) is designed to assess cognitive functioning across the lifespan. We aimed to evaluate the clinical validity of two NIHTB-CB tasks as cognitive screening tools in pediatric epilepsy by comparing them to standard neuropsychological measures and their association with epilepsy characteristics. Forty-seven patients with epilepsy ages 5-18, including ten repeat evaluations, were assessed. Correlational analyses and agreement statistics were conducted to validate NIHTB-CB tasks (Flanker Inhibitory Control and Attention test (Flanker) and Pattern Comparison Processing Speed test (Pattern Comparison)) with standard clinical measures. We also examined if performance was related to epilepsy characteristics, including polytherapy, age of seizure onset, seizure type, and history of Electrical Status Epilepticus in Sleep (ESES). The NIHTB-CB tests had moderate to strong correlations with neuropsychological measures of executive functioning, processing speed, and intelligence. Agreement statistics indicated better sensitivity than specificity. Polytherapy and later age of seizure onset were associated with lower performance on Pattern Comparison. ESES patients did not significantly differ in performance on the tests compared to non-ESES patients. Pilot data from a subset of repeated measures indicated a good range of change scores. These two NIHTB tasks are feasible as a screening tool in a clinic given their correlation with clinical measures that assess executive function, processing speed, and IQ. This study supports the use of these tasks as brief, easily accessible screener tools to identify cognitive dysfunction in domains commonly impacted in patients with epilepsy and potential use for monitoring over time.

Evaluation of the structural integrity of different spinal cord tracts with magnetization transfer ratio in degenerative cervical myelopathy.

PURPOSE: Degenerative cervical myelopathy (DCM) is a common cause of spinal cord dysfunction. In this study, we explored the potential of magnetization transfer ratio (MTR) for evaluating the structural integrity of spinal cord tracts in patients with clinically significant DCM. METHODS: Fifty-three patients with DCM and 41 patients with cervical radiculopathy were evaluated using high-resolution cervical spinal cord magnetic resonance imaging (MRI), which included the magnetization transfer technique. MRI data were analyzed with the Spinal Cord Toolbox (v5.5); MTR values in each spinal tract were calculated and compared between groups after correction for patient age and sex. Correlations between MTR values and patients' clinical disability rate were also evaluated. RESULTS: A statistically significant reduction in the average MTR of the spinal cord white matter, as well as the MTR of the ventral columns and lateral funiculi, was revealed in the DCM group (adjusted p < 0.01 for all comparisons). Furthermore, reductions in MTR values in the fasciculus cuneatus, spinocerebellar, rubrospinal, and reticulospinal tracts were found in patients with DCM (adjusted p < 0.01 for all comparisons). Positive correlations between the JOA score and the MTR within the ventral columns of the spinal cord (R = 0.38, adjusted p < 0.05) and the ventral spinocerebellar tract (R = 0.41, adjusted p < 0.05) were revealed. CONCLUSION: The findings of our study indicate that demyelination in patients with DCM primarily affects the spinal tracts of the extrapyramidal system, and the extent of these changes is related to the severity of the condition.

Metabolism of alcohol ethoxylates (AEs) in rat, hamster, and human hepatocytes and liver S9: a pilot study for metabolic stability, metabolic pathway, and metabolites identification in vitro and in silico.

Alcohol ethoxylates (AEs) are a well-known class of non-ionic surfactants widely used by the personal care market. The aim of this study was to evaluate and characterize the in vitro metabolism of AEs and identify metabolites. Five selected individual homologue AEs (C8EO4, C10EO5, C12EO4, C16EO8, and C18EO3) were incubated using human, rat, and hamster liver S9 fraction and cryopreserved hepatocytes. LC-MS was used to identify metabolites following the incubation of AEs by liver S9 and hepatocytes of all three species. All AEs were metabolized in these systems with a half-life ranging from 2 to 139 min. In general, incubation of AE with human liver S9 showed a shorter half-life compared to rat liver S9. While rat hepatocytes metabolized AEs faster than human hepatocytes. Both hydrophobic alkyl chain and hydrophilic EO head group groups of AEs were found to be target sites of metabolism. Metabolites were identified that show primary hydroxylation and dehydrogenation, followed by O-dealkylation (shortening of EO head groups) and glucuronidation. Additionally, the detection of whole EO groups indicates the cleavage of the ether bond between the alkyl chain and the EO groups as a minor metabolic pathway in the current testing system. Furthermore, no difference in metabolic patterns of each individual homologue AE investigated was observed, regardless of alkyl chain length or the number of EO groups. Moreover, there is an excellent agreement between the in vitro experimental data and the metabolite profile simulations using in silico approaches (OECD QSAR Toolbox). Altogether, these data indicate fast metabolism of all AEs with a qualitatively similar metabolic pathway with some quantitative differences observed in the metabolite profiles. These metabolic studies using different species can provide important reference values for further safety evaluation.

Evaluation of the NIH Toolbox Odor Identification Test across normal cognition, amnestic mild cognitive impairment, and dementia due to Alzheimer's disease.

INTRODUCTION: Olfactory decline is associated with cognitive decline in aging, amnestic mild cognitive impairment (aMCI), and amnestic dementia associated with Alzheimer's disease neuropathology (ADd). The National Institutes of Health Toolbox Odor Identification Test (NIHTB-OIT) may distinguish between these clinical categories. METHODS: We compared NIHTB-OIT scores across normal cognition (NC), aMCI, and ADd participants (N = 389, ≥65 years) and between participants positive versus negative for AD biomarkers and the APOE ε4 allele. RESULTS: NIHTB-OIT scores decreased with age (p < 0.001) and were lower for aMCI (p < 0.001) and ADd (p < 0.001) compared to NC participants, correcting for age and sex. The NIHTB-OIT detects aMCI (ADd) versus NC participants with 49.4% (56.5%) sensitivity and 88.8% (89.5%) specificity. NIHTB-OIT scores were lower for participants with positive AD biomarkers (p < 0.005), but did not differ based on the APOE ε4 allele (p > 0.05). DISCUSSION: The NIHTB-OIT distinguishes clinically aMCI and ADd participants from NC participants. HIGHLIGHTS: National Institutes of Health Toolbox Odor Identification Test (NIHTB-OIT) discriminated normal controls from mild cognitive impairment. NIHTB-OIT discriminated normal controls from Alzheimer's disease dementia. Rate of olfactory decline with age was similar across all diagnostic categories. NIHTB-OIT scores were lower in participants with positive Alzheimer's biomarker tests. NIHTB-OIT scores did not differ based on APOE genotype.

In Silico Phototoxicity Prediction of Drugs and Chemicals by using Derek Nexus and QSAR Toolbox.

Phototoxicity testing is crucial for evaluating the potential harmful effects of pharmaceuticals and chemicals on human skin when exposed to sunlight. Traditional in vivo models involving mice, rats, guinea pigs, as well as in vitro assays such as the 3T3 Neutral Red Uptake phototoxicity assay and methods based on the use of reconstructed human epidermis, have been established for phototoxicity testing. While these approaches are extremely valuable, they are costly in terms of both time and resources. Consequently, in silico approaches based on the use of predictive software tools can offer more rapid and cost-effective phototoxicity screening solutions. With this goal in mind, the current study evaluated two in silico tools - Derek Nexus 6.1.0/Derek Knowledge Base 2020 1.0 (Lhasa Limited, UK) and the QSAR Toolbox (v 4.5) developed by the Organisation for Economic Co-operation and Development (OECD) - for their capacity to predict the phototoxicity of several substances from diverse classes. Derek Nexus and the QSAR Toolbox were both found to be very useful for predicting the phototoxicity of drugs and other chemicals. Derek Nexus predicted phototoxicity of the compounds, with a sensitivity of 63%, specificity of 93%, Positive Predictive Values of 90% and Negative Predictive Value of 69%, overall accuracy of 77% and balanced accuracy of 78%. The QSAR Toolbox achieved sensitivity of 73%, specificity of 85%, Positive Predictive Value of 85% and Negative Predictive Value of 74%, overall accuracy of 79% and balanced accuracy of 79%. The results show that Derek Nexus and the QSAR Toolbox can be usefully incorporated in the workflow of phototoxicity testing for pharmaceuticals and chemicals.

How much data do we need to estimate computational models of decision-making? The COMPASS toolbox.

How much data are needed to obtain useful parameter estimations from a computational model? The standard approach to address this question is to carry out a goodness-of-recovery study. Here, the correlation between individual-participant true and estimated parameter values determines when a sample size is large enough. However, depending on one's research question, this approach may be suboptimal, potentially leading to sample sizes that are either too small (underpowered) or too large (overcostly or unfeasible). In this paper, we formulate a generalized concept of statistical power and use this to propose a novel approach toward determining how much data is needed to obtain useful parameter estimates from a computational model. We describe a Python-based toolbox (COMPASS) that allows one to determine how many participants are needed to fit one specific computational model, namely the Rescorla-Wagner model of learning and decision-making. Simulations revealed that a high number of trials per person (more than the number of persons) are a prerequisite for high-powered studies in this particular setting.