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This article provides a structured summary of "Leadership in Focus: Lessons Learned from Women Leaders," a conference panel organized by the American Psychological Association (APA) Division 40's Society for Clinical Neuropsychology (SCN)'s Women in Neuropsychology (WIN) committee at APA's annual conference in 2025. This panel brought together four prolific women leaders in neuropsychology and associated fields, Kim Gorgens, PhD, ABPP, Paula Shear, PhD, Chriscelyn Tussey, PsyD, ABPP, and Sara Weisenbach, PhD, ABPP, to discuss major themes related to women's leadership in neuropsychology, including: (1) a historical view of women in leadership positions, (2) systemic barriers faced by women in leadership, and (3) strategies used as a woman in leadership. Erin Sullivan-Baca, PhD, ABPP, and Rachael L. Ellison, PhD, co-moderated this panel discussion. The panel session and this resulting paper aim to disseminate the panelists' wisdom around best practices in knowledge and strategies for promoting gender equity and supporting the advancement of women in leadership within neuropsychology. Common themes across panelists and topics included celebrating and recognizing the strengths of women's unique leadership style, reflecting on personal strengths, seeking out mentorship and sponsorship, engaging in professional organizations, and not overplanning or waiting until conditions are perfect to volunteer for leadership opportunities. Panelists concluded by acknowledging continued barriers to women in leadership while also providing a vision of hope for the future of women leaders in neuropsychology.

State and local health departments and the Centers for Disease Control and Prevention (CDC) routinely investigate multistate outbreaks of salmonellosis associated with backyard poultry (BYP). Here, we describe antimicrobial resistance in multistate outbreaks of nontyphoidal salmonellosis associated with BYP from 2018 to 2023. We analyzed patient and outbreak data from CDC's National Antimicrobial Resistance Monitoring System and System for Enteric Disease Response, Investigation, and Coordination databases. Isolate resistance was determined by antimicrobial susceptibility testing or predicted by whole genome sequencing. We classified isolates as resistant, multi-drug resistant (MDR; resistant to ≥3 antimicrobial classes), or having clinically relevant resistance (CRR; resistant to ampicillin, azithromycin, ceftriaxone, or trimethoprim-sulfamethoxazole; or nonsusceptibility to ciprofloxacin), and outbreaks as resistant, MDR, or CRR if ≥3 isolates and ≥10% of isolates met the corresponding resistance definitions. Statistical analyses comparing patient variables, outbreak size, and annual number of outbreaks with resistance status were performed. Among 78 multistate BYP-associated salmonellosis outbreaks, 36 (46%) exhibited resistance, 10 (13%) were classified as MDR, and 12 (15%) were classified as CRR. Enteritidis was the most frequent serotype, causing 22 (28%) outbreaks; three were resistant (two CRR only outbreaks, one CRR and MDR outbreak). Among the 6,262 patient isolates included in multistate BYP-associated salmonellosis outbreaks, 2,248 (36%) were resistant, 209 (3%) were MDR, and 395 (6%) were CRR. Although nearly half of BYP-associated salmonellosis outbreaks and one-third of outbreak isolates were resistant, CRR and MDR outbreaks and isolates were infrequent. Continued monitoring for antimicrobial resistance is warranted because of the persistence of BYP-associated salmonellosis and the potential for BYP to serve as a reservoir for resistant Salmonella that can spread to people.

Strategies for tuning the optical properties of organic chromophores generally focus on shifting the edges of the spectrum: this might be red-shifting the longest absorbance band to improve solar absorbance, or blue-shifting of the highest energy emission band towards deep blue emission. In contrast, strategies to enhance molar absorptivity and control excited state rate constants are less obvious, with intermolecular excitons such as J-aggregates providing arguably the most powerful approach. Here, a homologous series of π-extended triptycenes is presented which reveal opportunities to control both aspects. These molecules have electronic spectra consisting of two distinct regimes, a low energy intramolecular charge transfer and a mid-spectral progression which has characteristics similar to that of a J-aggregate in several respects. This reveals that a homoconjugated framework can be utilised rationally to separate and independently control distinct regions of the electronic structure of the molecule, here leading to controllably amplified mid-spectrum absorbance intensities and high fluorescence quantum yields.

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We present a Q-learning framework for optimizing chemotherapy dosing schedules in a stochastic finite-cell model of tumor evolution under drug-induced selection. The tumor consists of three competing subpopulations: a chemosensitive lineage, S, and two single-drug-resistant lineages, R_{1} and R_{2}, each resistant to one of two cytotoxic agents, C_{1} and C_{2}. Drug administration is formulated as a discrete action space in a finite-state Markov process, where the state is defined by the composition (S,R_{1},R_{2}) constrained by a fixed population size N. Tumor volume evolves according to a separate growth equation, with expansion rate proportional to the difference between the population-averaged fitness and a fixed microenvironmental baseline. Using Q-learning, we derive optimal dosing policies that balance therapeutic pressure with the evolutionary dynamics of resistance. The reward function is engineered to promote long-term coexistence among subpopulations, thereby delaying fixation of resistance by penalizing population imbalance. We analyze the structure of the optimal policies to (i) infer dominant evolutionary trajectories under treatment, (ii) quantify robustness to partial observability of both initial conditions and state updates, and (iii) construct simplified, symmetry-informed heuristics that approximate the full learned policy. Our results highlight the potential of model-free adaptive control strategies to steer tumor evolution away from drug resistance in the presence of biological stochasticity and information constraints.

Visual imagery - the creation of images mentally without the corresponding sensory input - plays an important role in multiple cognitive processes. The lack of conscious visual imagery, known as aphantasia, has been linked to autistic traits. However, there is a lack of qualitative studies exploring the experiences of aphantasics, autistic or non-autistic. The current study aimed to investigate the experiences of autistic and non-autistic aphantasics qualitatively, exploring possible similarities and differences that might shed light on links or differential mechanisms. Qualitative framework analysis and quantifying methods were used to analyse data collected via an online survey. A total of 25 aphantasic adults with a clinical diagnosis of autism, and 25 age-matched non-autistic aphantasic comparison participants, completed a series of questionnaires and an open-ended question, providing data for the current analyses. Three themes were identified, each with four subthemes: imagery (auditory and other sensory imagery, inner speech, spatial and navigation, dreams), thinking (abstract thinking, thinking in words, creativity, memory), and emotions and socialization (own emotions, others' emotions, social relationship, feeling different). Significantly more non-autistic than autistic participants endorsed the subtheme concerning "auditory and other sensory imagery", while the opposite was the case for the subtheme "verbal thinking". This is the first study to explore the lived experience of autistic and non-autistic aphantasic adults through qualitative methods. We hope to promote wider public understanding and appreciation of the different, but certainly not deficient, experiences of aphantasia and its intersection with autism.

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Gene model for the ortholog of Protein tyrosine phosphatase 61F ( Ptp61F ) in the Drosophila ananassae May 2011 (Agencourt dana_caf1/DanaCAF1) Genome Assembly (GenBank Accession: GCA_000005115.1). This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.

Bats are major reservoirs of viruses that can be transmitted to humans in zoonotic outbreaks. Antibody-mediated immunity plays an important role in shaping viral evolution and immune evasion but remains understudied in bats. All known mammals have a single immunoglobulin heavy chain (IgH) gene locus and up to two light chain loci. We have identified dual IgH loci on separate chromosomes in 26 bat species, highlighting extreme variation of immunogenetic architecture in order Chiroptera. In a model species, Eptesicus fuscus, we leveraged single-cell transcriptomes to confirm functional rearrangement and expression of both loci, but with different mechanisms for generating antibody diversity and function. These results provide a foundation for analysis of humoral immunity and pathogen response in bats.

This study aimed to compare demographic and clinical information of teens and emerging adults with type 1 diabetes (T1D) by endocrinology visit completion status (no-showed, cancelled last minute [within 8&#x2009;days], attended). Three endocrinology clinic schedules (two paediatric, one adult) were reviewed weekly over a 6-month period to identify people with T1D (&#x2265;1&#x2009;year) ages 15-35. A1c, demographics and use of emergency department (ED)/inpatient care over the last year were recorded. We compared these factors by visit completion status using ANOVA, chi-squared and Fisher's exact tests. Of 529 individuals, 9% no-showed and 21% cancelled their visit last minute. Among those who cancelled, private insurance was more common than public (60% vs. 38%, respectively), which differed from those who no-showed (40% vs. 53%, p&#x2009;<&#x2009;0.001). A1c was higher in people who no-showed (79&#x2009;mmol/mol, 9.4%) than cancelled (67&#x2009;mmol/mol, 8.2%) or completed visits (62&#x2009;mmol/mol, 7.8%, p&#x2009;<&#x2009;0.001). Those who no-showed were more likely to have 2+ ED visits/hospitalizations in the last year compared with those who cancelled or attended (21% vs. 11% vs. 6%, respectively; p&#x2009;=&#x2009;0.013). Among 15-35-year-olds with T1D, no-shows and last-minute cancellations were common. Those who cancelled last minute had higher A1cs and greater ED/hospital use than those who completed visits, although these were not as high as in those who no-showed. Mechanisms to identify and ensure appropriate follow-up among individuals with last-minute cancellations should be explored.

Artificial intelligence (AI) has rapidly become the focal point of global governmental attention and investment. Nations are launching AI for science strategies on a scale comparable to historic endeavors such as Apollo and the Manhattan Project. These coordinated programs carry profound promise for people living with cancer, for those at risk of disease and for transformative public benefit. Central to this transformation is the rise of sovereign AI supercomputers which are fundamentally reshaping biomedical research. These publicly owned systems provide secure, large-scale computational capacity, enabling integration of complex health data and rapid analysis that was previously constrained. This review examines the geographic distribution, technical capabilities, and biomedical applications of these infrastructures. Key computational workloads that now benefit significantly from AI implementations include cancer imaging and diagnosis, personalized treatments, whole-genome and single-cell level analysis, and computational drug discovery. This approach has supercharged our efforts at the United Kingdom's Cancer Vaccine AI & Supercomputing Project, our flagship national initiative to create new AI foundation models to accelerate the development of tools to establish immunity from cancer. In addition, this review evaluates governance models that safeguard patient privacy and intellectual property as well as measures that promote international collaboration while preserving compliance with regional regulations and make safer, more precise and effective treatments for public benefit. Substantial challenges exist, however, including inequitable resource availability, heterogeneous data standards and regulatory frameworks, and unbalanced computational expertise impeding the effective use of sovereign compute. Global collaborations are key to providing equitable access to advanced analytics, shortening the path from bench to bedside, and developing critical innovative tools for people affected by cancer.

Bacteria-specific viruses, or phages, can modify host cell physiology to thwart competitors. The Pseudomonas aeruginosa-specific phage DMS3 encodes Aqs1, a protein inhibitor of type IV pilus (T4P) function. T4P are important virulence factors widely distributed in bacteria and archaea, but they are also common P. aeruginosa phage receptors. Disabling these structures therefore prevents host cell recognition by other phages that leverage these filaments for infection. Aqs1 disrupts pilus production by binding to PilB, the hexameric ATPase required to power T4P filament extension, though several mechanistic details remain unclear. We show that Aqs1 has broad-spectrum activity and can disrupt T4P ATPase-dependent surface motility, DNA uptake, and protein secretion by binding to PilB homologues in a variety of bacteria. Aqs1 inhibits multiple PilB orthologues by binding to a conserved solvent-exposed hydrophobic patch on its N2-domain, distal to the active site. Binding to this region destabilizes the hexamer, preventing PilB accumulation near T4P machines. We report that a flexible linker segment connecting the PilB N-terminal domains functionally interacts with the Aqs1-binding N2-patch, and that this interaction is required to promote PilB inter-subunit contact. The function of the linker represents a novel element of T4P ATPase allosteric regulation which has been exploited by phages to disrupt diverse functions. The Aqs1 mode-of-action therefore provides a design template for broad-spectrum inhibitors against diverse bacterial virulence factors.

We explore the design and performance of a "Health of Nations Fund," a proposed securitization of a biomedical "megafund" that pools capital to invest in a diversified set of global drug development projects. Incorporating assets from four stages of the drug development process as well as royalties from approved therapeutics across eight therapeutic areas, our Monte Carlo simulations show that such a megafund can deliver an annual expected return of 12.0% with a Sharpe ratio of 1.37, indicating a favorable balance between risk and return. At the same time, it finances an average of 25 approved drugs that potentially benefit approximately 44 million patients worldwide over a 14.5-year horizon. To enhance the fund's financial and therapeutic value, we integrate an optimization framework into our design that accounts for global disease prevalence and severity, allowing investors to adjust the allocation of capital according to their preferences for financial performance and healthcare impact. Sensitivity analyses indicate that this megafund typically generates double-digit annual returns across most scenarios.

Current scores that discriminate rupture status/rupture-associated morphology of aneurysm rupture rely on size being >7&#x2009;mm, ignoring important morphological parameters. This study applies advanced statistical methods on historical patient data to identify morphological features associated with aneurysms rupture. Data from 429 aneurysms along with demographics and morphological data, collected by a blinded research assistant, were utilised to explore associations between morphology and demographic features and aneurysm ruptures. Associations between morphology and rupture status were assessed with generalised estimating equations clustered by patient. The relative importance of morphological and historical/demographic factors in predicting the risk of aneurysm rupture were investigated applying a selected machine learning techniques (random forest, neural network and support vector machine). Demographic characteristics were not statistically associated with risk of aneurysm rupture, but morphological characteristics (parent vessel diameter and aneurysm dome diameter) had significant associations with rupture. Accounting for only morphological parameters in predicting ruptured aneurysm, support vector machine was superior in detecting ruptured aneurysm compared to random forest (RF) and neural network. Considering morphological data together with patients' historical and demographic features, RF had the best performance with a substantial increase in the risk of rupture accuracy. In the latter model, age, aneurysm dome diameter, irregularity of shape, years of smoking and bottleneck factor were the most important variables in aneurysm rupture prediction. An aneurysm likely to rupture can be identified with a reasonable degree of certainty from a single scan using morphological characteristics alone although the accuracy of prediction increases significantly when other factors are included in the model. Larger studies to investigate this further are required.

As longevity increases and the population over age 65 expands, advancing age remains the most reliable predictor of cognitive decline, highlighting the need to identify biological mechanisms that support exceptional cognitive aging. We tested whether lower inherited risk of Alzheimer's disease (AD) dementia predicts SuperAger status (adults&#x2009;&#x2265;&#x2009;80&#xa0;years with episodic memory at least as good as middle-age adults) using prospectively enrolled SuperAgers and Cognitively Average Controls (Controls) from the multisite SuperAging Research Initiative. We studied 231 participants (SuperAgers n&#x2009;=&#x2009;142; Controls n&#x2009;=&#x2009;89). We confirmed that the genetic ancestry structure across groups was comparable. We evaluated whether APOE status (&#x3b5;2, &#x3b5;3, &#x3b5;4) and three AD polygenic risk scores (PRS) derived from large contemporary Genome-Wide Association Studies (GWAS) (PRSLambert, PRSWightman, PRSBellenguez) predicted SuperAging status using logistic regression models adjusted for age, sex, and education, considering ancestry interactions. APOE allele and genotype distributions did not differ between groups, and neither APOE nor any of the three PRS predicted SuperAger status. Results were unchanged when accounting for global non-European or African ancestry or principal components. In this well-characterized cohort, neither APOE nor contemporary PRS explained SuperAger status. These findings suggest that the exceptional late-life memory phenotype that is characteristic of SuperAging is not explained by common-variant AD genetic risk captured by APOE or contemporary AD PRS, motivating a deeper investigation of potential rare genetic variations and experiential factors contributing to exceptional cognitive aging.

Insecticide resistance in Anopheles mosquitoes threatens the effectiveness of key malaria control tools such as insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in Ethiopia. Genomic analysis is essential to model known and novel molecular markers of insecticide resistance for effective resistance management. This study investigated insecticide resistance genes using whole-genome sequencing in a major malaria vector, Anopheles arabiensis sampled across the whole regions of Ethiopia and found high geographic and temporal variability in genes associated with insecticide resistance. The Vgsc-L995F target-site substitution in the voltage-gated sodium channel gene was highly prevalent in northern Ethiopia but less common at other sites. Metabolic modes of resistance in western Ethiopia were indicated by the high frequencies of copy number variants observed at the cytochrome P450 cluster Cyp6aa/p and the carboxylesterase Coeae2-7g. Frequencies of genetic markers associated with molecular target sites and metabolic resistance were generally lower in the Central Rift Valley. However, copy number variants (CNVs) at Gste2 and Cyp9k1 were observed at high frequency. We observed seasonal shifts in both target-site and metabolic marker frequencies, including increasing frequencies of Vgsc-L995F and several cytochrome P450 variants during the major transmission season. These patterns were specific to each location. Findings indicate that molecular insecticide resistance arises from a complex interplay of factors, including malaria control interventions, agricultural practices, human behavior, and possibly vector behavior. Selection scans revealed signals of selection on chromosome 2L, centered on the Coejhe1-5e genes in Werkamba, northernmost Ethiopia. Additional signals were detected on chromosome 3L (~&#x2009;20&#xa0;Mb), near genes that may regulate detoxification pathways, including those associated with the ubiquitin-proteasome system in Asossa, western Ethiopia. Findings highlight the importance of integrating genomic surveillance of resistance markers into entomological monitoring to strengthen insecticide resistance management. They also underscore the need to investigate lesser-known sources of adaptive change that may have significant consequences for vector control.