Photonic bandgap microcombs at 1064 nm.

Microresonator frequency combs and their design versatility have revolutionized research areas from data communication to exoplanet searches. While microcombs in the 1550 nm band are well documented, there is interest in using microcombs in other bands. Here, we demonstrate the formation and spectral control of normal-dispersion dark soliton microcombs at 1064 nm. We generate 200 GHz repetition rate microcombs by inducing a photonic bandgap of the microresonator mode for the pump laser with a photonic crystal. We perform the experiments with normal-dispersion microresonators made from Ta2O5 and explore unique soliton pulse shapes and operating behaviors. By adjusting the resonator dispersion through its nanostructured geometry, we demonstrate control over the spectral bandwidth of these combs, and we employ numerical modeling to understand their existence range. Our results highlight how photonic design enables microcomb spectra tailoring across wide wavelength ranges, offering potential in bioimaging, spectroscopy, and photonic-atomic quantum technologies.

Loss of circulating CD8α+ NK cells during human Mycobacterium tuberculosis infection.

Natural Killer (NK) cells can recognize and kill Mtb-infected cells in vitro, however their role after natural human exposure has not been well-studied. To identify Mtb-responsive NK cell populations, we analyzed the peripheral blood of healthy household contacts of active Tuberculosis (TB) cases and source community donors in an endemic region of Port-au-Prince, Haiti by flow cytometry. We observed higher CD8α expression on NK cells in putative resistors (IGRA-contacts) with a progressive loss of these circulating cells during household-associated latent infection and disease. In vitro assays and CITE-seq analysis of CD8α+ NK cells demonstrated enhanced maturity, cytotoxic gene expression, and response to cytokine stimulation relative to CD8α- NK cells. CD8α+ NK cells also displayed dynamic surface expression dependent on MHC I in contrast to conventional CD8+ T cells. Together, these results support a specialized role for CD8α+ NK cell populations during Mtb infection correlating with disease resistance.

Cooperative involvement of zipper-interacting protein kinase (ZIPK) and the dual-specificity cell-division cycle 14A phosphatase (CDC14A) in vascular smooth muscle cell migration.

Zipper-interacting protein kinase (ZIPK) is a Ser/Thr protein kinase with regulatory involvement in vascular smooth muscle cell (VSMC) actin polymerization and focal adhesion assembly dynamics. ZIPK silencing can induce cytoskeletal remodeling with disassembly of actin stress fiber networks and coincident loss of focal adhesion kinase (FAK)-pY397 phosphorylation. The link between ZIPK inhibition and FAK phosphorylation is unknown, and critical interactor(s) and regulator(s) are not yet defined. In this study, we further analyzed the ZIPK-FAK relationship in VSMCs. The application of HS38, a selective ZIPK inhibitor, to coronary artery vascular smooth muscle cells (CASMCs) suppressed cell migration, myosin light chain phosphorylation (pT18&pS19) and FAK-pY397 phosphorylation as well. This was associated with the translocation of cytoplasmic FAK to the nucleus. ZIPK inhibition with HS38 was consistently found to suppress the activation of FAK and attenuate the phosphorylation of other focal adhesion protein components (i.e., pCas130, paxillin, ERK). In addition, our study showed a decrease in human cell-division cycle 14A phosphatase (CDC14A) levels with ZIPK-siRNA treatment and increased CDC14A with transient transfection of ZIPK. Proximity ligation assays (PLA) revealed CDC14A localized with ZIPK and FAK. Silencing CDC14A showed an increase of FAK-pY397 phosphorylation. Ultimately, the data presented herein strongly support a regulatory mechanism of FAK in CASMCs by a ZIPK-CDC14A partnership; ZIPK may act as a key signal integrator to control CDC14A and FAK during VSMC migration.

Testing an implementation package in a housing skills training pilot for homeless-experienced persons with serious mental illness.

Background: Evidence-based practices (EBPs) improve housing and health for persons who have experienced homelessness with serious mental illness (PEH-SMI) but are challenging to implement. We tested a strategy to support pilot implementation of a 12-session housing skills training intervention for PEH-SMI, tailored from effective social skills training interventions. We aimed to optimize the implementation strategy and intervention prior to an implementation trial. Method: We provided training and technical assistance to nine providers to support pilot implementation of this intervention to six groups of PEH-SMI (n = 35) engaged in VA Greater Los Angeles' homeless services. We used scales and semi-structured interviews with 14 PEH-SMI and all interventionists to inform implementation strategy adaptations, identify factors that impacted implementation, and assess perceptions of the intervention. Attendance was tracked and we observed a random sample of each interventionist's groups to assess treatment fidelity. Results: Interventionists perceived the implementation strategy and the intervention favorably. However, interventionists often lacked physical space, staff, and resources (e.g., computers) to conduct the intervention. Interventionists found the content valuable for participants and a few suggested that group engagement should be a prerequisite for obtaining housing services. PEH-SMI were interested in the intervention's content and receptive to the group-based format. Participants attended a mean of 4 ± 3/12 groups; all groups observed had acceptable fidelity. Problems with intervention retention were described, suggesting challenges maintaining group participation when participants transitioned between VA homeless services. Conclusions: To support the implementation of an EBP for PEH-SMI in homeless programs, these data suggest the value of training/technical assistance and strategies that enhance program-level buy-in to address resource concerns. Intervention adaptations, e.g., using a drop-in, open group format, in community-based settings that are easily accessible to PEH-SMI, may also increase adoption. This project was registered as "Improving Housing Outcomes for Homeless Veterans" Trial registration NCT03646149, registered 8/24/2018.

There are effective social skills programs for people with serious psychiatric disorders; we adapted these programs into a 12-session housing skills program for people who had experienced homelessness. We then tested a training and technical assistance package to support the program's delivery by nine providers (e.g., social workers) to six groups of homeless people with serious psychiatric disorders (n = 35). We used surveys and interviews with some participants (n = 14) and all involved providers (n = 9) to understand their perspectives on our training and technical assistance, as well as the program itself; and to assess their views on factors that affected the program's use in real-world settings. We tracked participants' attendance at the groups and observed a random selection of groups to see if providers adhered to key program elements. We found that participants attended an average of one-third of the program's groups (4/12) but that providers were able to deliver the program to include all key elements. Some providers lacked important resources (e.g., classroom space or computers) to deliver the program as it was intended; they liked the training and technical assistance offered. Participants liked the program's content and format. Difficulties with participant retention may relate to drop-out from homeless services in which the program was delivered. This pilot project suggests that getting buy-in from leaders across levels and structuring the program as a drop-in group, in the community, or in places where attendance is easy for participants may increase its likelihood of being used as part of routine homeless services.

Prevalence of bias against neurodivergence-related terms in artificial intelligence language models.

Given the increasing role of artificial intelligence (AI) in many decision-making processes, we investigate the presence of AI bias towards terms related to a range of neurodivergent conditions, including autism, ADHD, schizophrenia, and obsessive-compulsive disorder (OCD). We use 11 different language model encoders to test the degree to which words related to neurodiversity are associated with groups of words related to danger, disease, badness, and other negative concepts. For each group of words tested, we report the mean strength of association (Word Embedding Association Test [WEAT] score) averaged over all encoders and find generally high levels of bias. Additionally, we show that bias occurs even when testing words associated with autistic or neurodivergent strengths. For example, embedders had a negative average association between words related to autism and words related to honesty, despite honesty being considered a common strength of autistic individuals. Finally, we introduce a sentence similarity ratio test and demonstrate that many sentences describing types of disabilities, for example, "I have autism" or "I have epilepsy," have even stronger negative associations than control sentences such as "I am a bank robber."

Tantalum pentoxide: a new material platform for high-performance dielectric metasurface optics in the ultraviolet and visible region.

Dielectric metasurfaces, composed of planar arrays of subwavelength dielectric structures that collectively mimic the operation of conventional bulk optical elements, have revolutionized the field of optics by their potential in constructing high-efficiency and multi-functional optoelectronic systems on chip. The performance of a dielectric metasurface is largely determined by its constituent material, which is highly desired to have a high refractive index, low optical loss and wide bandgap, and at the same time, be fabrication friendly. Here, we present a new material platform based on tantalum pentoxide (Ta2O5) for implementing high-performance dielectric metasurface optics over the ultraviolet and visible spectral region. This wide-bandgap dielectric, exhibiting a high refractive index exceeding 2.1 and negligible extinction coefficient across a broad spectrum, can be easily deposited over large areas with good quality using straightforward physical vapor deposition, and patterned into high-aspect-ratio subwavelength nanostructures through commonly-available fluorine-gas-based reactive ion etching. We implement a series of high-efficiency ultraviolet and visible metasurfaces with representative light-field modulation functionalities including polarization-independent high-numerical-aperture lensing, spin-selective hologram projection, and vivid structural color generation, and the devices exhibit operational efficiencies up to 80%. Our work overcomes limitations faced by scalability of commonly-employed metasurface dielectrics and their operation into the visible and ultraviolet spectral range, and provides a novel route towards realization of high-performance, robust and foundry-manufacturable metasurface optics.

Estimating the effects of vegetation and increased albedo on the urban heat island effect with spatial causal inference.

The urban heat island effect causes increased heat stress in urban areas. Cool roofs and urban greening have been promoted as mitigation strategies to reduce this effect. However, evaluating their efficacy remains a challenge, as potential temperature reductions depend on local characteristics. Existing methods to characterize their efficacy, such as computational fluid dynamics and urban canopy models, are computationally burdensome and require a high degree of expertise to employ. We propose a data-driven approach to overcome these hurdles, inspired by recent innovations in spatial causal inference. This approach allows for estimates of hypothetical interventions to reduce the urban heat island effect. We demonstrate this approach by modeling evening temperature in Durham, North Carolina, using readily retrieved air temperature, land cover, and satellite data. Hypothetical interventions such as lining streets with trees, cool roofs, and changing parking lots to green space are estimated to decrease evening temperatures by a maximum of 0.7-0.9   [Formula: see text], with reduced effects on temperature as a function of distance from the intervention. Because of the ease of data access, this approach may be applied to other cities in the U.S. to help them come up with city-specific solutions for reducing urban heat stress.

Threshold and Laser Conversion in Nanostructured-Resonator Parametric Oscillators.

We explore optical parametric oscillation (OPO) in nanophotonic resonators, enabling arbitrary, nonlinear phase matching and nearly lossless control of energy conversion. Such pristine OPO laser converters are determined by nonlinear light-matter interactions, making them both technologically flexible and broadly reconfigurable. We utilize a nanostructured inner-wall modulation in the resonator to achieve universal phase matching for OPO-laser conversion, but coherent backscattering also induces a counterpropagating pump laser. This depletes the intraresonator optical power in either direction, increasing the OPO threshold power and limiting laser-conversion efficiency, the ratio of optical power in target signal and idler frequencies to the pump. We develop an analytical model of this system that emphasizes an understanding of optimal laser-conversion and threshold behaviors, and we use the model to guide experiments with nanostructured-resonator OPO laser-conversion circuits, fully integrated on chip and unlimited by group-velocity dispersion. Our Letter demonstrates the fundamental connection between OPO laser-conversion efficiency and the resonator coupling rate, subject to the relative phase and power of counterpropagating pump fields. We achieve (40±4) mW of on-chip power, corresponding to (41±4)% conversion efficiency, and discover a path toward near-unity OPO laser-conversion efficiency.

Electome network factors: Capturing emotional brain networks related to health and disease.

Therapeutic development for mental disorders has been slow despite the high worldwide prevalence of illness. Unfortunately, cellular and circuit insights into disease etiology have largely failed to generalize across individuals that carry the same diagnosis, reflecting an unmet need to identify convergent mechanisms that would facilitate optimal treatment. Here, we discuss how mesoscale networks can encode affect and other cognitive processes. These networks can be discovered through electrical functional connectome (electome) analysis, a method built upon explainable machine learning models for analyzing and interpreting mesoscale brain-wide signals in a behavioral context. We also outline best practices for identifying these generalizable, interpretable, and biologically relevant networks. Looking forward, translational electome analysis can span species and various moods, cognitive processes, or other brain states, supporting translational medicine. Thus, we argue that electome analysis provides potential translational biomarkers for developing next-generation therapeutics that exhibit high efficacy across heterogeneous disorders.

In Vivo Verification of Electron Paramagnetic Resonance Biodosimetry Using Patients Undergoing Radiation Therapy Treatment.

PURPOSE: Electron paramagnetic resonance (EPR) biodosimetry, used to triage large numbers of individuals incidentally exposed to unknown doses of ionizing radiation, is based on detecting a stable physical response in the body that is subject to quantifiable variation after exposure. In vivo measurement is essential to fully characterize the radiation response relevant to a living tooth measured in situ. The purpose of this study was to verify EPR spectroscopy in vivo by estimating the radiation dose received in participants' teeth. METHODS AND MATERIALS: A continuous wave L-band spectrometer was used for EPR measurements. Participants included healthy volunteers and patients undergoing head and neck and total body irradiation treatments. Healthy volunteers completed 1 measurement each, and patients underwent measurement before starting treatment and between subsequent fractions. Optically stimulated luminescent dosimeters and diodes were used to determine the dose delivered to the teeth to validate EPR measurements. RESULTS: Seventy measurements were acquired from 4 total body irradiation and 6 head and neck patients over 15 months. Patient data showed a linear increase of EPR signal with delivered dose across the dose range tested. A linear least-squares weighted fit of the data gave a statistically significant correlation between EPR signal and absorbed dose (P < .0001). The standard error of inverse prediction (SEIP), used to assess the usefulness of fits, was 1.92 Gy for the dose range most relevant for immediate triage (≤7 Gy). Correcting for natural background radiation based on patient age reduced the SEIP to 1.51 Gy. CONCLUSIONS: This study demonstrated the feasibility of using spectroscopic measurements from radiation therapy patients to validate in vivo EPR biodosimetry. The data illustrated a statistically significant correlation between the magnitude of EPR signals and absorbed dose. The SEIP of 1.51 Gy, obtained under clinical conditions, indicates the potential value of this technique in response to large radiation events.

Fatty acid binding protein 5 inhibition attenuates pronociceptive cytokine/chemokine expression and suppresses osteoarthritis pain: A comparative human and rat study.

OBJECTIVE: Osteoarthritis (OA) is often accompanied by debilitating pain that is refractory to available analgesics due in part to the complexity of signaling molecules that drive OA pain and our inability to target these in parallel. Fatty acid binding protein 5 (FABP5) is a lipid chaperone that regulates inflammatory pain; however, its contribution to OA pain has not been characterized. DESIGN: This combined clinical and pre-clinical study utilized synovial tissues obtained from subjects with end-stage OA and rats with monoiodoacetate-induced OA. Cytokine and chemokine release from human synovia incubated with a selective FABP5 inhibitor was profiled with cytokine arrays and ELISA. Immunohistochemical analyses were conducted for FABP5 in human and rat synovium. The efficacy of FABP5 inhibitors on pain was assessed in OA rats using incapacitance as an outcome. RNA-seq was then performed to characterize the transcriptomic landscape of synovial gene expression in OA rats treated with FABP5 inhibitor or vehicle. RESULTS: FABP5 was expressed in human synovium and FABP5 inhibition reduced the secretion of pronociceptive cytokines (interleukin-6 [IL6], IL8) and chemokines (CCL2, CXCL1). In rats, FABP5 was upregulated in the OA synovium and its inhibition alleviated incapacitance. The transcriptome of the rat OA synovium exhibited >6000 differentially expressed genes, including the upregulation of numerous pronociceptive cytokines and chemokines. FABP5 inhibition blunted the upregulation of the majority of these pronociceptive mediators. CONCLUSIONS: FABP5 is expressed in the OA synovium and its inhibition suppresses pronociceptive signaling and pain, indicating that FABP5 inhibitors may constitute a novel class of analgesics to treat OA.

Estimating a brain network predictive of stress and genotype with supervised autoencoders.

Targeted brain stimulation has the potential to treat mental illnesses. We develop an approach to help design protocols by identifying relevant multi-region electrical dynamics. Our approach models these dynamics as a superposition of latent networks, where the latent variables predict a relevant outcome. We use supervised autoencoders (SAEs) to improve predictive performance in this context, describe the conditions where SAEs improve predictions, and provide modelling constraints to ensure biological relevance. We experimentally validate our approach by finding a network associated with stress that aligns with a previous stimulation protocol and characterizing a genotype associated with bipolar disorder.

Managing medical and psychiatric multimorbidity in older patients.

Aging increases susceptibility both to psychiatric and medical disorders through a variety of processes ranging from biochemical to pharmacologic to societal. Interactions between aging-related brain changes, emotional and psychological symptoms, and social factors contribute to multimorbidity - the presence of two or more chronic conditions in an individual - which requires a more patient-centered, holistic approach than used in traditional single-disease treatment guidelines. Optimal treatment of older adults with psychiatric and medical multimorbidity necessitates an appreciation and understanding of the links between biological, psychological, and social factors - including trauma and racism - that underlie physical and psychiatric multimorbidity in older adults, all of which are the topic of this review.

Death-associated protein kinase 3 regulates the myogenic reactivity of cerebral arteries.

NEW FINDINGS: What is the central question of this study? DAPK3 contributes to the Ca2+ -sensitization of vascular smooth muscle contraction: does this protein kinase participate in the myogenic response of cerebral arteries? What is the main finding and its importance? Small molecule inhibitors of DAPK3 effectively block the myogenic responses of cerebral arteries. HS38-dependent changes to vessel constriction occur independent of LC20 phosphorylation, and therefore DAPK3 appears to operate via the actin cytoskeleton. A role for DAPK3 in the myogenic response was not previously reported, and the results support a potential new therapeutic target in the cerebrovascular system. ABSTRACT: The vascular smooth muscle (VSM) of resistance blood vessels is a target of intrinsic autoregulatory responses to increased intraluminal pressure, the myogenic response. In the brain, the myogenic reactivity of cerebral arteries is critical to homeostatic blood flow regulation. Here we provide the first evidence to link the death-associated protein kinase 3 (DAPK3) to the myogenic response of rat and human cerebral arteries. DAPK3 is a Ser/Thr kinase involved in Ca2+ -sensitization mechanisms of smooth muscle contraction. Ex vivo administration of a specific DAPK3 inhibitor (i.e., HS38) could attenuate vessel constrictions invoked by serotonin as well as intraluminal pressure elevation. The HS38-dependent dilatation was not associated with any change in myosin light chain (LC20) phosphorylation. The results suggest that DAPK3 does not regulate Ca2+ sensitization pathways during the myogenic response of cerebral vessels but rather operates to control the actin cytoskeleton. A slow return of myogenic tone was observed during the sustained ex vivo exposure of cerebral arteries to HS38. Recovery of tone was associated with greater LC20 phosphorylation that suggests intrinsic signalling compensation in response to attenuation of DAPK3 activity. Additional experiments with VSM cells revealed HS38- and siDAPK-dependent effects on the actin cytoskeleton and focal adhesion kinase phosphorylation status. The translational importance of DAPK3 to the human cerebral vasculature was noted, with robust expression of the protein kinase and significant HS38-dependent attenuation of myogenic reactivity found for human pial vessels.

Estimating Causal Effects using a Multi-task Deep Ensemble.

A number of methods have been proposed for causal effect estimation, yet few have demonstrated efficacy in handling data with complex structures, such as images. To fill this gap, we propose Causal Multi-task Deep Ensemble (CMDE), a novel framework that learns both shared and group-specific information from the study population. We provide proofs demonstrating equivalency of CDME to a multi-task Gaussian process (GP) with a coregionalization kernel a priori. Compared to multi-task GP, CMDE efficiently handles high-dimensional and multi-modal covariates and provides pointwise uncertainty estimates of causal effects. We evaluate our method across various types of datasets and tasks and find that CMDE outperforms state-of-the-art methods on a majority of these tasks.