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An autism diagnosis can be a critical milestone toward effective and affirming support. Despite the sharp increase in the number of studies focused on late diagnosis over the last 15 years, there remains no consensus as to what constitutes a late diagnosis of autism, with cutoffs ranging from infancy to middle adulthood. This preregistered systematic review evaluated (a) the field's current quantification of late diagnosis in autism, (b) how the threshold for late diagnosis varies as a function of demographic and population factors, and (c) trends over time. Of the 11,697 records retrieved, N = 420 articles met inclusion criteria and were extracted. Articles spanned 35 years (1989-2024) and included participants from every continent except Antarctica. Only 34.7% of included studies provided a clear threshold for "late diagnosis" (n = 146/420). Late diagnosis cutoffs averaged 11.53 years (range = 2-55 years; median = 6.5 years) with a bimodal distribution (3 and 18 years). The threshold for late diagnosis varied by participant location, F(5,140) = 10.4, p < 0.0001, and sample age, F(5,140) = 20.1, p < 0.0001. Several key rationales for age determinations emerged, including access to services, considerations for adult diagnoses, and data driven approaches. What authors consider to be a "late" diagnosis of autism varies greatly according to research context. Justifications for a specific late-diagnosis age cutoff varied, underscoring the need for authors to contextualize their conceptualizations., (© 2024 International Society for Autism Research and Wiley Periodicals LLC.)

This brief report provides an overview of lessons learned through evaluation of the first five years of the NIA-funded South Carolina-Advancing Diversity in Aging Research (SC-ADAR) undergraduate program, whose goal is to increase the number of qualified underrepresented minority (URM) students who pursue scientific graduate studies in programs focusing on medicine, science, technology, engineering, and mathematics and aging. Partnering with five Historically Black Colleges and Universities in South Carolina, we implemented a research training approach that included two consecutive summers of research training in a University of South Carolina faculty laboratory, as part of a comprehensive 24-month research education program. In addition to the mentored research experience in a laboratory, students had coursework in the biology of aging and social gerontology, with additional workshops tailored to emergent student needs including basic academic skills development, work-life management skills, reflective social experiences, and enhanced support in the transition from undergraduate to graduate school. We provide an overview of lessons learned throughout the early program period, and a description of the iterative changes we made in the program in response to this learning, all of which have been incorporated into the existing SC-ADAR program.

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that have provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses the three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this article, we discuss the models and capabilities that have recently been implemented within the APBS software package including a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory-based algorithm for determining pK a values, and an improved web-based visualization tool for viewing electrostatics., (© 2017 The Protein Society.)

In many photosynthetic organisms, tight-binding Rubisco inhibitors are released by the motor protein Rubisco activase (Rca). In higher plants, Rca plays a pivotal role in regulating CO2 fixation. Here, the ATPase activity of 0.005 mm tobacco Rca was monitored under steady-state conditions, and global curve fitting was utilized to extract kinetic constants. The kcat was best fit by 22.3 ± 4.9 min(-1), the Km for ATP by 0.104 ± 0.024 mm, and the Ki for ADP by 0.037 ± 0.007 mm. Without ADP, the Hill coefficient for ATP hydrolysis was extracted to be 1.0 ± 0.1, indicating noncooperative behavior of homo-oligomeric Rca assemblies. However, the addition of ADP was shown to introduce positive cooperativity between two or more subunits (Hill coefficient 1.9 ± 0.2), allowing for regulation via the prevailing ATP/ADP ratio. ADP-mediated activation was not observed, although larger amounts led to competitive product inhibition of hydrolytic activity. The catalytic efficiency increased 8.4-fold upon cooperative binding of a second magnesium ion (Hill coefficient 2.5 ± 0.5), suggesting at least three conformational states (ATP-bound, ADP-bound, and empty) within assemblies containing an average of about six subunits. The addition of excess Rubisco (24:1, L8S8/Rca6) and crowding agents did not modify catalytic rates. However, high magnesium provided for thermal Rca stabilization. We propose that magnesium mediates the formation of closed hexameric toroids capable of high turnover rates and amenable to allosteric regulation. We suggest that in vivo, the Rca hydrolytic activity is tuned by fluctuating [Mg(2+)] in response to changes in available light., (© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.)