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.

Integrating Graphene Oxide-Hydrogels and Electrical Stimulation for Controlled Neurotrophic Factor Encapsulation: A Promising Approach for Efficient Nerve Tissue Regeneration.

Nerve growth factor (NGF) plays a crucial role in cellular growth and neurodifferentiation. To achieve significant neuronal regeneration and repair using in vitro NGF delivery, spatiotemporal control that follows the natural neuronal processes must be developed. Notably, a challenge hindering this is the uncontrolled burst release from the growth factor delivery systems. The rapid depletion of NGF reduces treatment efficacy, leading to poor cellular response. To address this, we developed a highly controllable system using graphene oxygen (GO) and GelMA hydrogels modulated by electrical stimulation. Our system showed superior control over the release kinetics, reducing the burst up 30-fold. We demonstrate that the system is also able to sequester and retain NGF up to 10-times more efficiently than GelMA hydrogels alone. Our controlled release system enabled neurodifferentiation, as revealed by gene expression and immunostaining analysis. The increased retention and reduced burst release from our system show a promising pathway for nerve tissue engineering research toward effective regeneration.

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.

Development of an advanced multiwavelength emission detector for the analytical ultracentrifuge.

An advanced design of the analytical ultracentrifuge with multiwavelength emission detection (MWE-AUC) is presented which offers outstanding performance concerning the spectral resolution and range flexibility as well as the quality of the data acquired. The excitation by a 520 nm laser is complemented with a 405 nm laser. An external spectrograph with three switchable tunable gratings permits optimisation of the spectral resolution in an order of magnitude range while keeping the spectral region broad. The new system design leads also to a significant reduction of systematic signal noise and allows the assessment and control of inner filter effects. Details regarding the very large signal dynamic range are presented, an important aspect when studying samples in a broad concentration range of up to five orders of magnitude. Our system is validated by complementary studies on two biological systems, fluorescent BSA and GFP, using the commercial Optima AUC with absorbance detection for comparison. Finally, we demonstrate the capabilities of our second generation MWE-AUC with respect to multiwavelength characterisation of gold nanoclusters, which exhibit specific fluorescence depending on their structure. Overall, this work depicts an important stepping stone for the concept of multiwavelength emission detection in AUC. The MWE-AUC developed, being to our knowledge the first and sole one of its kind, has reached the development level suitable for the future in-depth studies of size-, shape- and composition-dependent emission properties of colloids.

Wired for Success: Probing the Effect of Tissue-Engineered Neural Interface Substrates on Cell Viability.

This study investigates the electrochemical behavior of GelMA-based hydrogels and their interactions with PC12 neural cells under electrical stimulation in the presence of conducting substrates. Focusing on indium tin oxide (ITO), platinum, and gold mylar substrates supporting conductive scaffolds composed of hydrogel, graphene oxide, and gold nanorods, we explored how the substrate materials affect scaffold conductivity and cell viability. We examined the impact of an optimized electrical stimulation protocol on the PC12 cell viability. According to our findings, substrate selection significantly influences conductive hydrogel behavior, affecting cell viability and proliferation as a result. In particular, the ITO substrates were found to provide the best support for cell viability with an average of at least three times higher metabolic activity compared to platinum and gold mylar substrates over a 7 day stimulation period. The study offers new insights into substrate selection as a platform for neural cell stimulation and underscores the critical role of substrate materials in optimizing the efficacy of neural interfaces for biomedical applications. In addition to extending existing work, this study provides a robust platform for future explorations aimed at tailoring the full potential of tissue-engineered neural interfaces.

Controlled oxygen delivery to power tissue regeneration.

Oxygen plays a crucial role in human embryogenesis, homeostasis, and tissue regeneration. Emerging engineered regenerative solutions call for novel oxygen delivery systems. To become a reality, these systems must consider physiological processes, oxygen release mechanisms and the target application. In this review, we explore the biological relevance of oxygen at both a cellular and tissue level, and the importance of its controlled delivery via engineered biomaterials and devices. Recent advances and upcoming trends in the field are also discussed with a focus on tissue-engineered constructs that could meet metabolic demands to facilitate regeneration.

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.

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.

Repeatability of Online Circular Contrast Perimetry Compared to Standard Automated Perimetry.

PRCIS: Online circular contrast perimetry provides visual field assessment on any computer or tablet with no extra hardware. It has good test repeatability and reliability that is comparable with standard automated perimetry. It holds promise for use in disease screening and surveillance to expand the provision of glaucoma care. PURPOSE: To evaluate the repeatability of online circular contrast perimetry (OCCP) compared to standard automated perimetry (SAP) in normal participants and patients with stable glaucoma over 18 weeks. METHODS: Thirty-six participants (13 normal controls and 23 patients with open angle glaucoma) were recruited. OCCP and SAP perimetry tests were performed twice at baseline, then at 6, 12, and 18 weeks. Global perimetric indices were compared between perimetry types and analyzed for short-term and intermediate-term repeatability. RESULTS: There were no statistically significant changes over time for both OCCP and SAP across all groups for mean deviation (MD), pattern standard deviation, and visual index/visual field index ( P >0.05). Test-retest intraclass correlation coefficients (ICCs) for OCCP MD were excellent at baseline (0.98, 95% CI: 0.89-0.99) and good at 18 weeks (0.88, 95% CI: 0.51-0.98). SAP test-retest ICCs were excellent at baseline (0.94, 95% CI: 0.70-0.99) and 18 weeks (0.97, 95% CI: 0.84-0.99). Inter-test ICCs were good, ranging from 0.84 to 0.87. OCCP testing time was shorter than SAP (5:29 ± 1:24 vs. 6:00 ± 1:05, P <0.001). OCCP had similar false-positive (3.84 ± 3.32 vs. 3.66 ± 4.53, P =0.48) but lower false-negative (0.73 ± 1.52 vs. 4.48 ± 5.00, P <0.001) and fixation loss responses (0.91 ± 1.32 vs. 2.02 ± 2.17, P <0.001). CONCLUSIONS: OCCP allows visual field assessment on any computer screen with no additional hardware. It demonstrated good repeatability and reliability with similar performance indices to SAP in both the short term and intermediate term. OCCP has the potential to be utilized as a glaucoma screening and surveillance tool for in-clinic and at-home testing, expanding the provision of care.

Which antiseptic to use for a caesarean section? A systematic review and network meta-analysis of randomized controlled trials.

Guidelines for pre-operative skin antisepsis recommend using chlorhexidine in an alcohol-based solution. However, other antiseptics such as aqueous povidone-iodine or alcohol-based solutions continue to be used. Randomized controlled trials (RCTs) in caesarean section are rare and do not include all possible comparisons of antiseptics. The aim of this study was to assess the efficacy (reduction of surgical site infections) of chlorhexidine at two different concentrations (0.3% and 2%) and povidone-iodine in aqueous or alcohol-based solutions using a network meta-analysis, including only RCTs of caesarean sections. Fragility indices and prediction intervals were also estimated. A systematic literature review and network meta-analysis were performed. RCTs published up to February 2024 were collected from PubMed, ScienceDirect and the Cochrane Library. Interventions included alcohol-based povidone-iodine, aqueous povidone-iodine, and alcohol-based chlorhexidine 2% and 0.3%. The primary outcome measure was surgical site infection. Nine RCTs with 4915 patients and four interventions were included in the network meta-analysis. All credible intervals of the compared interventions overlapped. Alcohol-based 2% chlorhexidine had the highest probability of being effective in preventing surgical site infections, followed by alcohol-based povidone-iodine. The fragility index ranged from 4 to 18. The prediction intervals were wide. On the basis of rank probabilities, chlorhexidine 2% in an alcohol-based solution was most likely to be effective in preventing surgical site infections after caesarean section, followed by alcohol-based povidone-iodine. Given the paucity of literature and the relatively small difference between povidone-iodine and chlorhexidine found in our meta-analysis, we suggest that either can be used in an alcohol-based solution as antisepsis for planned or emergency caesarean section.

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.

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.

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.

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.

The Association Between Stuttering Burden and Psychosocial Aspects of Life in Adults.

PURPOSE: Stuttering is a speech condition that can have a major impact on a person's quality of life. This descriptive study aimed to identify subgroups of people who stutter (PWS) based on stuttering burden and to investigate differences between these subgroups on psychosocial aspects of life. METHOD: The study included 618 adult participants who stutter. They completed a detailed survey examining stuttering symptomatology, impact of stuttering on anxiety, education and employment, experience of stuttering, and levels of depression, anxiety, and stress. A two-step cluster analytic procedure was performed to identify subgroups of PWS, based on self-report of stuttering frequency, severity, affect, and anxiety, four measures that together inform about stuttering burden. RESULTS: We identified a high- (n = 230) and a low-burden subgroup (n = 372). The high-burden subgroup reported a significantly higher impact of stuttering on education and employment, and higher levels of general depression, anxiety, stress, and overall impact of stuttering. These participants also reported that they trialed more different stuttering therapies than those with lower burden. CONCLUSIONS: Our results emphasize the need to be attentive to the diverse experiences and needs of PWS, rather than treating them as a homogeneous group. Our findings also stress the importance of personalized therapeutic strategies for individuals with stuttering, considering all aspects that could influence their stuttering burden. People with high-burden stuttering might, for example, have a higher need for psychological therapy to reduce stuttering-related anxiety. People with less emotional reactions but severe speech distortions may also have a moderate to high burden, but they may have a higher need for speech techniques to communicate with more ease. Future research should give more insights into the therapeutic needs of people highly burdened by their stuttering. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.25582980.

Exome-wide analysis implicates rare protein-altering variants in human handedness.

Handedness is a manifestation of brain hemispheric specialization. Left-handedness occurs at increased rates in neurodevelopmental disorders. Genome-wide association studies have identified common genetic effects on handedness or brain asymmetry, which mostly involve variants outside protein-coding regions and may affect gene expression. Implicated genes include several that encode tubulins (microtubule components) or microtubule-associated proteins. Here we examine whether left-handedness is also influenced by rare coding variants (frequencies ≤ 1%), using exome data from 38,043 left-handed and 313,271 right-handed individuals from the UK Biobank. The beta-tubulin gene TUBB4B shows exome-wide significant association, with a rate of rare coding variants 2.7 times higher in left-handers than right-handers. The TUBB4B variants are mostly heterozygous missense changes, but include two frameshifts found only in left-handers. Other TUBB4B variants have been linked to sensorineural and/or ciliopathic disorders, but not the variants found here. Among genes previously implicated in autism or schizophrenia by exome screening, DSCAM and FOXP1 show evidence for rare coding variant association with left-handedness. The exome-wide heritability of left-handedness due to rare coding variants was 0.91%. This study reveals a role for rare, protein-altering variants in left-handedness, providing further evidence for the involvement of microtubules and disorder-relevant genes.

Molecular-Scale Imaging Enables Direct Visualization of Molecular Defects and Chain Structure of Conjugated Polymers.

Conjugated polymers have become materials of choice for applications ranging from flexible optoelectronics to neuromorphic computing, but their polydispersity and tendency to aggregate pose severe challenges to their precise characterization. Here, the combination of vacuum electrospray deposition (ESD) with scanning tunneling microscopy (STM) is used to acquire, within the same experiment, assembly patterns, full mass distributions, exact sequencing, and quantification of polymerization defects. In a first step, the ESD-STM results are successfully benchmarked against NMR for low molecular mass polymers, where this technique is still applicable. Then, it is shown that ESD-STM is capable of reaching beyond its limits by characterizing, with the same accuracy, samples that are inaccessible to NMR. Finally, a recalibration procedure is proposed for size exclusion chromatography (SEC) mass distributions, using ESD-STM results as a reference. The distinctiveness of the molecular-scale information obtained by ESD-STM highlights its role as a crucial technique for the characterization of conjugated polymers.

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.