Rigorous science demands support of transgender scientists.

To build a just, equitable, and diverse academy, scientists and institutions must address systemic barriers that sex and gender minorities face. This Commentary summarizes (1) critical context informing the contemporary oppression of transgender people, (2) how this shapes extant research on sex and gender, and (3) actions to build an inclusive and rigorous academy for all.

The neocortical infrastructure for language involves region-specific patterns of laminar gene expression.

The language network of the human brain has core components in the inferior frontal cortex and superior/middle temporal cortex, with left-hemisphere dominance in most people. Functional specialization and interconnectivity of these neocortical regions is likely to be reflected in their molecular and cellular profiles. Excitatory connections between cortical regions arise and innervate according to layer-specific patterns. Here, we generated a gene expression dataset from human postmortem cortical tissue samples from core language network regions, using spatial transcriptomics to discriminate gene expression across cortical layers. Integration of these data with existing single-cell expression data identified 56 genes that showed differences in laminar expression profiles between the frontal and temporal language cortex together with upregulation in layer II/III and/or layer V/VI excitatory neurons. Based on data from large-scale genome-wide screening in the population, DNA variants within these 56 genes showed set-level associations with interindividual variation in structural connectivity between the left-hemisphere frontal and temporal language cortex, and with the brain-related disorders dyslexia and schizophrenia which often involve affected language. These findings identify region-specific patterns of laminar gene expression as a feature of the brain's language network.

Fluorescent Probes for Disease Diagnosis.

The identification and detection of disease-related biomarkers is essential for early clinical diagnosis, evaluating disease progression, and for the development of therapeutics. Possessing the advantages of high sensitivity and selectivity, fluorescent probes have become effective tools for monitoring disease-related active molecules at the cellular level and in vivo. In this review, we describe current fluorescent probes designed for the detection and quantification of key bioactive molecules associated with common diseases, such as organ damage, inflammation, cancers, cardiovascular diseases, and brain disorders. We emphasize the strategies behind the design of fluorescent probes capable of disease biomarker detection and diagnosis and cover some aspects of combined diagnostic/therapeutic strategies based on regulating disease-related molecules. This review concludes with a discussion of the challenges and outlook for fluorescent probes, highlighting future avenues of research that should enable these probes to achieve accurate detection and identification of disease-related biomarkers for biomedical research and clinical applications.

Genetic neurodevelopmental clustering and dyslexia.

Dyslexia is a learning difficulty with neurodevelopmental origins, manifesting as reduced accuracy and speed in reading and spelling. It is substantially heritable and frequently co-occurs with other neurodevelopmental conditions, particularly attention deficit-hyperactivity disorder (ADHD). Here, we investigate the genetic structure underlying dyslexia and a range of psychiatric traits using results from genome-wide association studies of dyslexia, ADHD, autism, anorexia nervosa, anxiety, bipolar disorder, major depressive disorder, obsessive compulsive disorder, schizophrenia, and Tourette syndrome. Genomic Structural Equation Modelling (GenomicSEM) showed heightened support for a model consisting of five correlated latent genomic factors described as: F1) compulsive disorders (including obsessive-compulsive disorder, anorexia nervosa, Tourette syndrome), F2) psychotic disorders (including bipolar disorder, schizophrenia), F3) internalising disorders (including anxiety disorder, major depressive disorder), F4) neurodevelopmental traits (including autism, ADHD), and F5) attention and learning difficulties (including ADHD, dyslexia). ADHD loaded more strongly on the attention and learning difficulties latent factor (F5) than on the neurodevelopmental traits latent factor (F4). The attention and learning difficulties latent factor (F5) was positively correlated with internalising disorders (.40), neurodevelopmental traits (.25) and psychotic disorders (.17) latent factors, and negatively correlated with the compulsive disorders (-.16) latent factor. These factor correlations are mirrored in genetic correlations observed between the attention and learning difficulties latent factor and other cognitive, psychological and wellbeing traits. We further investigated genetic variants underlying both dyslexia and ADHD, which implicated 49 loci (40 not previously found in GWAS of the individual traits) mapping to 174 genes (121 not found in GWAS of individual traits) as potential pleiotropic variants. Our study confirms the increased genetic relation between dyslexia and ADHD versus other psychiatric traits and uncovers novel pleiotropic variants affecting both traits. In future, analyses including additional co-occurring traits such as dyscalculia and dyspraxia will allow a clearer definition of the attention and learning difficulties latent factor, yielding further insights into factor structure and pleiotropic effects.

Comparison of stochastic and deterministic models for gambiense sleeping sickness at different spatial scales: A health area analysis in the DRC.

The intensification of intervention activities against the fatal vector-borne disease gambiense human African trypanosomiasis (gHAT, sleeping sickness) in the last two decades has led to a large decline in the number of annually reported cases. However, while we move closer to achieving the ambitious target of elimination of transmission (EoT) to humans, pockets of infection remain, and it becomes increasingly important to quantitatively assess if different regions are on track for elimination, and where intervention efforts should be focused. We present a previously developed stochastic mathematical model for gHAT in the Democratic Republic of Congo (DRC) and show that this same formulation is able to capture the dynamics of gHAT observed at the health area level (approximately 10,000 people). This analysis was the first time any stochastic gHAT model has been fitted directly to case data and allows us to better quantify the uncertainty in our results. The analysis focuses on utilising a particle filter Markov chain Monte Carlo (MCMC) methodology to fit the model to the data from 16 health areas of Mosango health zone in Kwilu province as a case study. The spatial heterogeneity in cases is reflected in modelling results, where we predict that under the current intervention strategies, the health area of Kinzamba II, which has approximately one third of the health zone's cases, will have the latest expected year for EoT. We find that fitting the analogous deterministic version of the gHAT model using MCMC has substantially faster computation times than fitting the stochastic model using pMCMC, but produces virtually indistinguishable posterior parameterisation. This suggests that expanding health area fitting, to cover more of the DRC, should be done with deterministic fits for efficiency, but with stochastic projections used to capture both the parameter and stochastic variation in case reporting and elimination year estimations.

Neuroimaging genomics as a window into the evolution of human sulcal organization.

Primate brain evolution has involved prominent expansions of the cerebral cortex, with largest effects observed in the human lineage. Such expansions were accompanied by fine-grained anatomical alterations, including increased cortical folding. However, the molecular bases of evolutionary alterations in human sulcal organization are not yet well understood. Here, we integrated data from recently completed large-scale neuroimaging genetic analyses with annotations of the human genome relevant to various periods and events in our evolutionary history. These analyses identified single-nucleotide polymorphism (SNP) heritability enrichments in fetal brain human-gained enhancer (HGE) elements for a number of sulcal structures, including the central sulcus, which is implicated in human hand dexterity. We zeroed in on a genomic region that harbors DNA variants associated with left central sulcus shape, an HGE element, and genetic loci involved in neurogenesis including ZIC4, to illustrate the value of this approach for probing the complex factors contributing to human sulcal evolution.

Fluorescent small molecule donors.

Small molecule donors (SMDs) play subtle roles in the signaling mechanism and disease treatments. While many excellent SMDs have been developed, dosage control, targeted delivery, spatiotemporal feedback, as well as the efficiency evaluation of small molecules are still key challenges. Accordingly, fluorescent small molecule donors (FSMDs) have emerged to meet these challenges. FSMDs enable controllable release and non-invasive real-time monitoring, providing significant advantages for drug development and clinical diagnosis. Integration of FSMDs with chemotherapeutic, photodynamic or photothermal properties can take full advantage of each mode to enhance therapeutic efficacy. Given the remarkable properties and the thriving development of FSMDs, we believe a review is needed to summarize the design, triggering strategies and tracking mechanisms of FSMDs. With this review, we compiled FSMDs for most small molecules (nitric oxide, carbon monoxide, hydrogen sulfide, sulfur dioxide, reactive oxygen species and formaldehyde), and discuss recent progress concerning their molecular design, structural classification, mechanisms of generation, triggered release, structure-activity relationships, and the fluorescence response mechanism. Firstly, from the large number of fluorescent small molecular donors available, we have organized the common structures for producing different types of small molecules, providing a general strategy for the development of FSMDs. Secondly, we have classified FSMDs in terms of the respective donor types and fluorophore structures. Thirdly, we discuss the mechanisms and factors associated with the controlled release of small molecules and the regulation of the fluorescence responses, from which universal guidelines for optical properties and structure rearrangement were established, mainly involving light-controlled, enzyme-activated, reactive oxygen species-triggered, biothiol-triggered, single-electron reduction, click chemistry, and other triggering mechanisms. Fourthly, representative applications of FSMDs for trackable release, and evaluation monitoring, as well as for visible in vivo treatment are outlined, to illustrate the potential of FSMDs in drug screening and precision medicine. Finally, we discuss the opportunities and remaining challenges for the development of FSMDs for practical and clinical applications, which we anticipate will stimulate the attention of researchers in the diverse fields of chemistry, pharmacology, chemical biology and clinical chemistry. With this review, we hope to impart new understanding thereby enabling the rapid development of the next generation of FSMDs.

Subnational Projections of Lymphatic Filariasis Elimination Targets in Ethiopia to Support National Level Policy.

BACKGROUND: Lymphatic filariasis (LF) is a debilitating, poverty-promoting, neglected tropical disease (NTD) targeted for worldwide elimination as a public health problem (EPHP) by 2030. Evaluating progress towards this target for national programmes is challenging, due to differences in disease transmission and interventions at the subnational level. Mathematical models can help address these challenges by capturing spatial heterogeneities and evaluating progress towards LF elimination and how different interventions could be leveraged to achieve elimination by 2030. METHODS: Here we used a novel approach to combine historical geo-spatial disease prevalence maps of LF in Ethiopia with 3 contemporary disease transmission models to project trends in infection under different intervention scenarios at subnational level. RESULTS: Our findings show that local context, particularly the coverage of interventions, is an important determinant for the success of control and elimination programmes. Furthermore, although current strategies seem sufficient to achieve LF elimination by 2030, some areas may benefit from the implementation of alternative strategies, such as using enhanced coverage or increased frequency, to accelerate progress towards the 2030 targets. CONCLUSIONS: The combination of geospatial disease prevalence maps of LF with transmission models and intervention histories enables the projection of trends in infection at the subnational level under different control scenarios in Ethiopia. This approach, which adapts transmission models to local settings, may be useful to inform the design of optimal interventions at the subnational level in other LF endemic regions.

An Ensemble Framework for Projecting the Impact of Lymphatic Filariasis Interventions Across Sub-Saharan Africa at a Fine Spatial Scale.

BACKGROUND: Lymphatic filariasis (LF) is a neglected tropical disease targeted for elimination as a public health problem by 2030. Although mass treatments have led to huge reductions in LF prevalence, some countries or regions may find it difficult to achieve elimination by 2030 owing to various factors, including local differences in transmission. Subnational projections of intervention impact are a useful tool in understanding these dynamics, but correctly characterizing their uncertainty is challenging. METHODS: We developed a computationally feasible framework for providing subnational projections for LF across 44 sub-Saharan African countries using ensemble models, guided by historical control data, to allow assessment of the role of subnational heterogeneities in global goal achievement. Projected scenarios include ongoing annual treatment from 2018 to 2030, enhanced coverage, and biannual treatment. RESULTS: Our projections suggest that progress is likely to continue well. However, highly endemic locations currently deploying strategies with the lower World Health Organization recommended coverage (65%) and frequency (annual) are expected to have slow decreases in prevalence. Increasing intervention frequency or coverage can accelerate progress by up to 5 or 6 years, respectively. CONCLUSIONS: While projections based on baseline data have limitations, our methodological advancements provide assessments of potential bottlenecks for the global goals for LF arising from subnational heterogeneities. In particular, areas with high baseline prevalence may face challenges in achieving the 2030 goals, extending the "tail" of interventions. Enhancing intervention frequency and/or coverage will accelerate progress. Our approach facilitates preimplementation assessments of the impact of local interventions and is applicable to other regions and neglected tropical diseases.

Accelerating Progress Towards the 2030 Neglected Tropical Diseases Targets: How Can Quantitative Modeling Support Programmatic Decisions?

Over the past decade, considerable progress has been made in the control, elimination, and eradication of neglected tropical diseases (NTDs). Despite these advances, most NTD programs have recently experienced important setbacks; for example, NTD interventions were some of the most frequently and severely impacted by service disruptions due to the coronavirus disease 2019 (COVID-19) pandemic. Mathematical modeling can help inform selection of interventions to meet the targets set out in the NTD road map 2021-2030, and such studies should prioritize questions that are relevant for decision-makers, especially those designing, implementing, and evaluating national and subnational programs. In September 2022, the World Health Organization hosted a stakeholder meeting to identify such priority modeling questions across a range of NTDs and to consider how modeling could inform local decision making. Here, we summarize the outputs of the meeting, highlight common themes in the questions being asked, and discuss how quantitative modeling can support programmatic decisions that may accelerate progress towards the 2030 targets.

Auditory discrimination learning and acoustic cue weighing in female zebra finches with localized FoxP1 knockdowns.

Rare disruptions of the transcription factor FOXP1 are implicated in a human neurodevelopmental disorder characterized by autism and/or intellectual disability with prominent problems in speech and language abilities. Avian orthologues of this transcription factor are evolutionarily conserved and highly expressed in specific regions of songbird brains, including areas associated with vocal production learning and auditory perception. Here, we investigated possible contributions of FoxP1 to song discrimination and auditory perception in juvenile and adult female zebra finches. They received lentiviral knockdowns of FoxP1 in one of two brain areas involved in auditory stimulus processing, HVC (proper name) or CMM (caudomedial mesopallium). Ninety-six females, distributed over different experimental and control groups were trained to discriminate between two stimulus songs in an operant Go/Nogo paradigm and subsequently tested with an array of stimuli. This made it possible to assess how well they recognized and categorized altered versions of training stimuli and whether localized FoxP1 knockdowns affected the role of different features during discrimination and categorization of song. Although FoxP1 expression was significantly reduced by the knockdowns, neither discrimination of the stimulus songs nor categorization of songs modified in pitch, sequential order of syllables or by reversed playback were affected. Subsequently, we analyzed the full dataset to assess the impact of the different stimulus manipulations for cue weighing in song discrimination. Our findings show that zebra finches rely on multiple parameters for song discrimination, but with relatively more prominent roles for spectral parameters and syllable sequencing as cues for song discrimination.NEW & NOTEWORTHY In humans, mutations of the transcription factor FoxP1 are implicated in speech and language problems. In songbirds, FoxP1 has been linked to male song learning and female preference strength. We found that FoxP1 knockdowns in female HVC and caudomedial mesopallium (CMM) did not alter song discrimination or categorization based on spectral and temporal information. However, this large dataset allowed to validate different cue weights for spectral over temporal information for song recognition.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Determination and correction of spectral phase from principal component analysis of coherent phonons.

Measuring the spectral phase of a pulse is key for performing wavelength resolved ultrafast measurements in the few femtosecond regime. However, accurate measurements in real experimental conditions can be challenging. We show that the reflectivity change induced by coherent phonons in a quantum material can be used to infer the spectral phase of an optical probe pulse with few-femtosecond accuracy.

Development of Redox-Active Lyotropic Lipid Cubic Phases for Biosensing Platforms.

Enzyme-based electrochemical biosensors play an important role in point-of-care diagnostics for personalized medicine. For such devices, lipid cubic phases (LCP) represent an attractive method to immobilize enzymes onto conductive surfaces with no need for chemical linking. However, research has been held back by the lack of effective strategies to stably co-immobilize enzymes with a redox shuttle that enhances the electrical connection between the enzyme redox center and the electrode. In this study, we show that a monoolein (MO) LCP system doped with an amphiphilic redox mediator (ferrocenylmethyl)dodecyldimethylammonium bromide (Fc12) can be used for enzyme immobilization to generate an effective biosensing platform. Small-angle X-ray scattering (SAXS) showed that MO LCP can incorporate Fc12 while maintaining the Pn3m symmetry morphology. Cyclic voltammograms of Fc12/MO showed quasi-reversible behavior, which implied that Fc12 was able to freely diffuse in the lipid membrane of LCP with a diffusion coefficient of 1.9 ± 0.2 × 10-8 cm2 s-1 at room temperature. Glucose oxidase (GOx) was then chosen as a model enzyme and incorporated into 0.2%Fc12/MO to evaluate the activity of the platform. GOx hosted in 0.2%Fc12/MO followed Michaelis-Menten kinetics toward glucose with a KM and Imax of 8.9 ± 0.5 mM and 1.4 ± 0.2 µA, respectively, and a linearity range of 2-17 mM glucose. Our results therefore demonstrate that GOx immobilized onto 0.2% Fc12/MO is a suitable platform for the electrochemical detection of glucose.

The impact of the COVID-19 pandemic on 397 631 elective dental admissions among the under-25s in England: a retrospective study.

BACKGROUND: COVID-19 caused widespread disruptions to health services worldwide, including reductions in elective surgery. Tooth extractions are among the most common reasons for elective surgery among children and young people (CYP). It is unclear how COVID-19 affected elective dental surgeries in hospitals over multiple pandemic waves at a national level. METHODS: Elective dental tooth extraction admissions were selected using Hospital Episode Statistics. Admission trends for the first 14 pandemic months were compared with the previous five years and results were stratified by age (under-11s, 11-16s, 17-24s). RESULTS: The most socioeconomically deprived CYP comprised the largest proportion of elective dental tooth extraction admissions. In April 2020, admissions dropped by >95%. In absolute terms, the biggest reduction was in April (11-16s: -1339 admissions, 95% CI -1411 to -1267; 17-24s: -1600, -1678 to -1521) and May 2020 (under-11s: -2857, -2962 to -2752). Admissions differed by socioeconomic deprivation for the under-11s (P < 0.0001), driven by fewer admissions than expected by the most deprived and more by the most affluent during the pandemic. CONCLUSION: Elective tooth extractions dropped most in April 2020, remaining below pre-pandemic levels throughout the study. Despite being the most likely to be admitted, the most deprived under-11s had the largest reductions in admissions relative to other groups.

Using the 'Leapfrog' Design as a Simple Form of Adaptive Platform Trial to Develop, Test, and Implement Treatment Personalization Methods in Routine Practice.

The route for the development, evaluation and dissemination of personalized psychological therapies is complex and challenging. In particular, the large sample sizes needed to provide adequately powered trials of newly-developed personalization approaches means that the traditional treatment development route is extremely inefficient. This paper outlines the promise of adaptive platform trials (APT) embedded within routine practice as a method to streamline development and testing of personalized psychological therapies, and close the gap to implementation in real-world settings. It focuses in particular on a recently-developed simplified APT design, the 'leapfrog' trial, illustrating via simulation how such a trial may proceed and the advantages it can bring, for example in terms of reduced sample sizes. Finally it discusses models of how such trials could be implemented in routine practice, including potential challenges and caveats, alongside a longer-term perspective on the development of personalized psychological treatments.

Unusual Regio- and Chemoselectivity in Oxidation of Pyrroles and Indoles Enabled by a Thianthrenium Salt Intermediate.

A dearomative oxidation of pyrroles to Δ3-pyrrol-2-ones is described, which employs a sulfoxide as oxidant, in conjunction with a carboxylic acid anhydride and a Brønsted acid additive. 3-substituted pyrroles undergo regioselective oxidation to give the product isomer in which oxygen has been introduced at the more hindered position. Regioselectivity is rationalized by a proposed mechanism that proceeds by initial thianthrenium introduction at the less-hindered pyrrole α-position, followed by distal attack of an oxygen nucleophile and subsequent elimination of thianthrene. The same reaction conditions are also able to effect a chemoselective oxidation of indoles to indolin-3-ones and additionally of indolin-3-ones to 2-hydroxyindolin-3-ones. Here again, the regio- and chemoselectivities are rationalized through the intermediacy of a thianthrenium salt.

Emergency Food Support Preference and Usage During COVID-19: A Neighborhood Study of Low-Income Black Mothers? Use of School-Based Food Distribution and P-EBT.

COVID-19 disrupted families' food supply. Based on in-depth interviews with 45 Black low-income mothers of young children in an underserved Houston, Texas, neighborhood from April 2020 to June 2021, we compared two aid programs-Pandemic Electronic Benefits Transfer cash assistance and in-kind food distributions. We found that mothers preferred cash assistance for boosting existing food strategies, while food distributions presented new challenges for already burdened families. We argue that food assistance interventions can be more successful and equitable by integrating service user context, needs, and preferences. (Am J Public Health. 2023;113(S3):S227-S230. https://doi.org/10.2105/AJPH.2023.307458).

Online Circular Contrast Perimetry via a Web-Application: Establishing a Normative Database for Central 10-Degree Perimetry.

Purpose: To establish a normative database using a central 10-degree grid pattern for the online circular contrast perimetry (OCCP) application. Participants: Fifty participants with mean age 65 ± 13 years were selected for this study. One eye from each participant that met inclusion criteria was randomly included in the cohort. Methods: The web-application delivered online 52-loci perimetry in a central 10-degree pattern using circular flickering targets. These targets consist of concentric sinusoidal alternating contrast rings. Users were guided by the application to the correct viewing distance and head position using in-built blind spot localization and webcam monitoring. A spinning golden star was used as the fixation target and patients performed the test in a darkened room following standard automated perimetry (SAP). Results: The reliability rates and global indices for OCCP were similar to SAP. OCCP mean sensitivity reduced with age at a similar rate to SAP. Mean sensitivity per loci of 10-degree OCCP was greater than SAP by 1.24 log units (95% CI 1.23 to 1.26) and obeyed a physiological hill of vision. Small differences existed in mean sensitivities between OCCP and SAP which increased with increasing spot eccentricity. Mean deviation (MD) displayed good agreement between the two tests. Conclusion: Central 10-degree online circular contrast perimetry via a computer-based application has comparable perimetric results to standard automated perimetry in a normal cohort.