Gasdermin D and Gasdermin E Are Dispensable for Silica-Mediated IL-1ß Secretion from Mouse Macrophages.

Silica crystals activate the NLRP3 inflammasome in macrophages, resulting in the caspase-1-dependent secretion of the proinflammatory cytokine IL-1ß. Caspase-1-mediated cleavage of gasdermin D (GSDMD) triggers the formation of GSDMD pores, which drive pyroptotic cell death and facilitate the rapid release of IL-1ß. However, the role of GSDMD in silica-induced lung injury is unclear. In this study, we show that although silica-induced lung injury is dependent on the inflammasome adaptor ASC and IL-1R1 signaling, GSDMD is dispensable for acute lung injury. Although the early rapid secretion of IL-1ß in response to ATP and nigericin was GSDMD dependent, GSDMD was not required for IL-1ß release at later time points. Similarly, secretion of IL-1ß from macrophages in response to silica and alum proceeded in a GSDMD-independent manner. We further found that gasdermin E did not contribute to macrophage IL-1ß secretion in the absence of GSDMD in vitro and was also not necessary for silica-induced acute lung injury in vivo. These findings demonstrate that GSDMD and gasdermin E are dispensable for IL-1ß secretion in response to silica in vitro and in silica-induced acute lung injury in vivo.

Application of elastic net regression for modeling COVID-19 sociodemographic risk factors.

OBJECTIVES: COVID-19 has been at the forefront of global concern since its emergence in December of 2019. Determining the social factors that drive case incidence is paramount to mitigating disease spread. We gathered data from the Social Vulnerability Index (SVI) along with Democratic voting percentage to attempt to understand which county-level sociodemographic metrics had a significant correlation with case rate for COVID-19. METHODS: We used elastic net regression due to issues with variable collinearity and model overfitting. Our modelling framework included using the ten Health and Human Services regions as submodels for the two time periods 22 March 2020 to 15 June 2021 (prior to the Delta time period) and 15 June 2021 to 1 November 2021 (the Delta time period). RESULTS: Statistically, elastic net improved prediction when compared to multiple regression, as almost every HHS model consistently had a lower root mean square error (RMSE) and satisfactory R2 coefficients. These analyses show that the percentage of minorities, disabled individuals, individuals living in group quarters, and individuals who voted Democratic correlated significantly with COVID-19 attack rate as determined by Variable Importance Plots (VIPs). CONCLUSIONS: The percentage of minorities per county correlated positively with cases in the earlier time period and negatively in the later time period, which complements previous research. In contrast, higher percentages of disabled individuals per county correlated negatively in the earlier time period. Counties with an above average percentage of group quarters experienced a high attack rate early which then diminished in significance after the primary vaccine rollout. Higher Democratic voting consistently correlated negatively with cases, coinciding with previous findings regarding a partisan divide in COVID-19 cases at the county level. Our findings can assist regional policymakers in distributing resources to more vulnerable counties in future pandemics based on SVI.

Spatial Modeling of Sociodemographic Risk for COVID-19 Mortality.

In early 2020, the Coronavirus Disease 19 (COVID-19) rapidly spread across the United States (US), exhibiting significant geographic variability. While several studies have examined the predictive relationships of differing factors on COVID-19 deaths, few have looked at spatiotemporal variation at refined geographic scales. The objective of this analysis is to examine this spatiotemporal variation in COVID-19 deaths with respect to association with socioeconomic, health, demographic, and political factors. We use multivariate regression applied to Health and Human Services (HHS) regions as well as nationwide county-level geographically weighted random forest (GWRF) models. Analyses were performed on data from three separate time frames which correspond to the spread of distinct viral variants in the US: pandemic onset until May 2021, May 2021 through November 2021, and December 2021 until April 2022. Multivariate regression results for all regions across three time windows suggest that existing measures of social vulnerability for disaster preparedness (SVI) are predictive of a higher degree of mortality from COVID-19. In comparison, GWRF models provide a more robust evaluation of feature importance and prediction, exposing the value of local features for prediction, such as obesity, which is obscured by coarse-grained analysis. Overall, GWRF results indicate that this more nuanced modeling strategy is useful for determining the spatial variation in the importance of sociodemographic risk factors for predicting COVID-19 mortality.

New and emerging therapies for women, girls, and people with the potential to menstruate with VWD.

Innovation in therapies for patients with von Willebrand disease (VWD) has lagged far behind that for hemophilia, creating inequity in the bleeding disorder community. Although currently existing treatments of antifibrinolytics, desmopressin, and plasma-derived von Willebrand factor replacement are considered effective, multiple studies report poor quality of life in patients with VWD, especially those with heavy menstrual bleeding (HMB). This disconnect underscores the need for novel therapies that are safe and effective and that consider a patient's specific contraceptive and reproductive needs. Recombinant von Willebrand factor is the most recent new therapy for VWD; the data specific to women are reviewed. We also present emerging data on emicizumab for the treatment of VWD, BT200 (rondoraptivon pegol), generalized hemostatic therapies (VGA039 and HMB-011), as well as treatments based on nanotechnology (platelet-inspired nanoparticles and KB-V13A12). We are optimistic as we move toward pivotal clinical trials for these elegant and innovative treatments.

InAs nanowire arrays for room-temperature ultra-broadband infrared photodetection.

Detection of short-wave infrared (SWIR) and mid-wave infrared (MWIR) emissions remains challenging despite their importance in many emerging applications, including night vision, space imaging and remote sensing. III-V compound semiconductor materials such as InAs have an ideal band gap covering a spectral regime from near-infrared (NIR), SWIR to MWIR. However, due to their high dark current, InAs photodetectors normally require a low-temperature operation, which has greatly limited their practical applications. Here, we report the engineering of InAs nanowire arrays to achieve efficient photodetection of light at wavelengths ranging from NIR to MWIR (3500 nm). By using selective area metal-organic vapour-phase epitaxy, we optimise the nanowire growth temperature and V/III ratio to achieve wurtzite (WZ)-based InAs nanowire arrays with a high WZ density of ∼67%. Due to the n-type background doping of the InAs nanowires and the p-type InAs substrate used for nanowire growth, a p-n junction is formed, and an ultrawide room-temperature photoresponse ranging from 500 to 3500 nm is obtained under zero bias. It is found that the waveguide modes supported by the InAs nanowires result in a high peak responsivity of 0.44 A W-1 and a detectivity of 1.25 × 1010 cm √Hz W-1 at a wavelength of 1600 nm, a bias voltage of only -0.1 V and a relatively high operating temperature of 150 K. Such a strong light trapping effect in the InAs nanowires also leads to significantly lower reflection compared to that observed in planar photodetectors, and thus strong absorption in the substrate extending the photoresponse up to the InAs bandgap edge of 3500 nm. Our work shows that through careful material optimisation and device design, InAs nanowire arrays are promising for the development of high-performance ultra-broadband infrared photodetectors for wavelengths ranging from NIR, SWIR to MWIR.

Iron Deficiency among School-Aged Adolescents in Hong Kong: Prevalence, Predictors, and Effects on Health-Related Quality of Life.

Iron deficiency (ID) is a prevalent nutritional deficiency affecting children/adolescents worldwide. We reported (1) the prevalence of ID and ID with anemia (IDA) among Chinese school-aged adolescents, (2) clinical and dietary predictors of iron status, and (3) its impact on health-related qualities of life (HRQoL). This cross-sectional study recruited 183 boys and 340 girls (mean age = 17.55) from 16 schools in Hong Kong. ID is defined as serum ferritin <15 µg/L. The participants reported their dietary habits, menstrual patterns (girls), and HRQoL using structured questionnaires. The overall prevalence of ID was 11.1%. None of the boys had ID or IDA. Among girls, the rate of ID was 17.1% and IDA was 10.9%. One-third (36.3%) reported a regular habit of skipping ≥1 meal/day. Lower ferritin was found in adolescents who skipped meals (Est = -35.1, p = 0.017). Lower ferritin is correlated with poorer school functioning (Est = 0.81, p = 0.045) and fatigue (Est = 0.92, p = 0.016). Skipping meals is associated with poorer physical (p = 0.0017) and school functioning (p = 0.027). To conclude, 1 in 10 school-aged adolescents in Hong Kong are iron-deficient. The ID rate in girls (17.1%) is similar to that in other industrialized countries (5.2-16.6%). Future work should promote awareness on the potential health consequences of poor dietary habits on ID and the well-being of adolescents.

Application of Elastic Net Regression for Modeling COVID-19 Sociodemographic Risk Factors.

Objectives: COVID-19 has been at the forefront of global concern since its emergence in December of 2019. Determining the social factors that drive case incidence is paramount to mitigating disease spread. We gathered data from the Social Vulnerability Index (SVI) along with Democratic voting percentage to attempt to understand which county-level sociodemographic metrics had a significant correlation with case rate for COVID-19. Methods: We used elastic net regression due to issues with variable collinearity and model overfitting. Our modelling framework included using the ten Health and Human Services regions as submodels for the two time periods 22 March 2020 to 15 June 2021 (prior to the Delta time period) and 15 June 2021 to 1 November 2021 (the Delta time period). Results: Statistically, elastic net improved prediction when compared to multiple regression, as almost every HHS model consistently had a lower root mean square error (RMSE) and satisfactory R2 coefficients. These analyses show that the percentage of minorities, disabled individuals, individuals living in group quarters, and individuals who voted Democratic correlated significantly with COVID-19 attack rate as determined by Variable Importance Plots (VIPs). Conclusions: The percentage of minorities per county correlated positively with cases in the earlier time period and negatively in the later time period, which complements previous research. In contrast, higher percentages of disabled individuals per county correlated negatively in the earlier time period. Counties with an above average percentage of group quarters experienced a high attack rate early which then diminished in significance after the primary vaccine rollout. Higher Democratic voting consistently correlated negatively with cases, coinciding with previous findings regarding a partisan divide in COVID-19 cases at the county level. Our findings can assist policymakers in distributing resources to more vulnerable counties in future pandemics based on SVI.

Effects of trust, risk perception, and health behavior on COVID-19 disease burden: Evidence from a multi-state US survey.

Early public health strategies to prevent the spread of COVID-19 in the United States relied on non-pharmaceutical interventions (NPIs) as vaccines and therapeutic treatments were not yet available. Implementation of NPIs, primarily social distancing and mask wearing, varied widely between communities within the US due to variable government mandates, as well as differences in attitudes and opinions. To understand the interplay of trust, risk perception, behavioral intention, and disease burden, we developed a survey instrument to study attitudes concerning COVID-19 and pandemic behavioral change in three states: Idaho, Texas, and Vermont. We designed our survey (n = 1034) to detect whether these relationships were significantly different in rural populations. The best fitting structural equation models show that trust indirectly affects protective pandemic behaviors via health and economic risk perception. We explore two different variations of this social cognitive model: the first assumes behavioral intention affects future disease burden while the second assumes that observed disease burden affects behavioral intention. In our models we include several exogenous variables to control for demographic and geographic effects. Notably, political ideology is the only exogenous variable which significantly affects all aspects of the social cognitive model (trust, risk perception, and behavioral intention). While there is a direct negative effect associated with rurality on disease burden, likely due to the protective effect of low population density in the early pandemic waves, we found a marginally significant, positive, indirect effect of rurality on disease burden via decreased trust (p = 0.095). This trust deficit creates additional vulnerabilities to COVID-19 in rural communities which also have reduced healthcare capacity. Increasing trust by methods such as in-group messaging could potentially remove some of the disparities inferred by our models and increase NPI effectiveness.

Pharmacokinetics of XEN496, a Novel Pediatric Formulation of Ezogabine, Under Fed and Fasted Conditions: A Phase 1 Trial.

INTRODUCTION: XEN496 is a novel, granular, immediate-release formulation of ezogabine intended for pediatric use. The objective of this study was to assess the effect of food on the pharmacokinetics (PK) of XEN496 and its N-acetyl metabolite (NAMR) in healthy volunteers. METHODS: Twenty-four adult subjects were enrolled in this phase 1, single center, open-label, randomized, single-dose, two-way crossover study. Subjects received 400 mg XEN496 as an oral suspension in both fed and fasted states separated by a 6-day washout period. Serial blood samples were collected up to 48 h post-administration. PK parameters evaluated included maximum observed plasma concentration (Cmax), time of maximum observed plasma concentration (Tmax), and area under the concentration-time curve (AUC(0-t) and AUCinf). Safety was assessed by laboratory evaluations, physical exam, and adverse event monitoring. RESULTS: For XEN496, median Tmax was 3 and 2 h in the fed and fasted states, respectively. AUC parameters in the fed and fasted states were equivalent, whereas food decreased Cmax of XEN496 by 32% compared to the fasted state. The ratio of geometric means [90% CI] for Cmax was 72% [64-82%]. For NAMR, food delayed Tmax by 1 h, while Cmax and AUC parameters were equivalent in the fed and fasted states. The safety profile of XEN496 in this study appeared comparable to that previously reported for ezogabine tablets. CONCLUSION: The biopharmaceutical performance of XEN496 in this study was as expected for an immediate-release, granular dosage formulation, and generally comparable to that reported for ezogabine tablets. Future studies are needed to characterize the efficacy, safety, and PK of XEN496 in a pediatric population.

Waning antibody levels after COVID-19 vaccination with mRNA Comirnaty and inactivated CoronaVac vaccines in blood donors, Hong Kong, April 2020 to October 2021.

The mRNA vaccine Comirnaty and the inactivated vaccine CoronaVac are both available in Hong Kong's COVID-19 vaccination programme. We observed waning antibody levels in 850 fully vaccinated (at least 14 days passed after second dose) blood donors using ELISA and surrogate virus neutralisation test. The Comirnaty-vaccinated group's (n = 593) antibody levels remained over the ELISA and sVNT positive cut-offs within the first 6 months. The CoronaVac-vaccinated group's (n = 257) median antibody levels began to fall below the cut-offs 4 months after vaccination.

NKD2 mediates stimulation-dependent ORAI1 trafficking to augment Ca2+ entry in T cells.

Sustained activation of the Ca2+-release-activated Ca2+ (CRAC) channel is pivotal for effector T cell responses. The mechanisms underlying this sustainability remain poorly understood. We find that plasma membrane localization of ORAI1, the pore subunit of CRAC channels, is limited in effector T cells, with a significant fraction trapped in intracellular vesicles. From a targeted screen, we identify an essential component of ORAI1+ vesicles, naked cuticle homolog 2 (NKD2). Mechanistically, NKD2, an adaptor molecule activated by signaling pathways downstream of T cell receptors, orchestrates trafficking and insertion of ORAI1+ vesicles to the plasma membrane. Together, our findings suggest that T cell receptor (TCR)-stimulation-dependent insertion of ORAI1 into the plasma membrane is essential for sustained Ca2+ signaling and cytokine production in T cells.

Low vitamin D exposure and risk of nasopharyngeal carcinoma: Observational and genetic evidence from a multicenter case-control study.

BACKGROUND & AIMS: Little is known about the risk of nasopharyngeal carcinoma (NPC) in relation to vitamin D exposure. The aim of this study was to examine the associations of NPC risk with serum level of 25-hydroxyvitamin D (25OHD) and genetic predicted 25OHD, and potential effect modification by several putative risk factors of NPC. METHODS: Our multicenter case-control study in Hong Kong recruited 815 NPC cases and 1502 frequency-matched (by sex and age) hospital controls from five major regional hospitals, and recruited 299 healthy subjects from blood donation centers (2014-2017). Circulating level of 25-hydroxyvitamin D (25OHD) and genetic predicted 25OHD (rs12785878, rs11234027, rs12794714, rs4588 and rs6013897) were measured by validated enzyme immunoassay and the iPLEX assay on the MassARRAY System, respectively. Data were also collected on demographics, lifestyle factors, ultraviolet radiation exposure, and potential confounders using a computer-assisted, self-administered questionnaire with satisfactory test-retest reliability. Unconditional logistic regression models were used to estimate ORs and 95% CIs. RESULTS: Despite no significant association of NPC risk with circulating 25OHD and genetic predicted 25OHD, there was evidence for an inverse association in participants with normal body mass index (between 18.5 and 27.5) across categories of 25OHD (Ptrend = 0.003), and a positive association in those with low socioeconomic status across categories based on the genetic score (Ptrend = 0.005). In addition, risk of NPC diagnosed at an early stage was higher for genetically lower 25OHD level (adjusted OR = 3.09, 95% CI = 1.04-9.21, Ptrend = 0.022). CONCLUSIONS: Findings of this first comprehensive study to investigate the positive association of NPC risk with vitamin D deficiency need to be confirmed and be best interpreted with results of further similar studies. Our findings may inform possible etiological mechanisms of the associations with several putative risk/protective factors of NPC.

Understanding the role of facets and twin defects in the optical performance of GaAs nanowires for laser applications.

GaAs nanowires are regarded as promising building blocks of future optoelectronic devices. Despite progress, the growth of high optical quality GaAs nanowires is a standing challenge. Understanding the role of twin defects and nanowire facets on the optical emission and minority carrier lifetime of GaAs nanowires is key for the engineering of their optoelectronic properties. Here, we present new insights into the microstructural parameters controlling the optical properties of GaAs nanowires, grown via selective-area metal-organic vapor-phase epitaxy. We observe that these GaAs nanowires have a twinned zinc blende crystal structure with taper-free {110} side facets that result in an ultra-low surface recombination velocity of 3.5 × 104 cm s-1. This is an order of magnitude lower than that reported for defect-free GaAs nanowires grown by the vapor-liquid-solid technique. Using time-resolved photoluminescence and cathodoluminescence measurements, we untangle the local correlation between structural and optical properties demonstrating the superior role of the side facets in determining recombination rates over that played by twin defects. The low surface recombination velocity of these taper-free {110} side facets enable us to demonstrate, for the first time, low-temperature lasing from bare (unpassivated) GaAs nanowires, and also efficient room-temperature lasing after passivation with an AlGaAs shell.

Epidural cerebellar stimulation drives widespread neural synchrony in the intact and stroke perilesional cortex.

BACKGROUND: Cerebellar electrical stimulation has shown promise in improving motor recovery post-stroke in both rodent and human studies. Past studies have used motor evoked potentials (MEPs) to evaluate how cerebellar stimulation modulates ongoing activity in the cortex, but the underlying mechanisms are incompletely understood. Here we used invasive electrophysiological recordings from the intact and stroke-injured rodent primary motor cortex (M1) to assess how epidural cerebellar stimulation modulates neural dynamics at the level of single neurons as well as at the level of mesoscale dynamics. METHODS: We recorded single unit spiking and local field potentials (LFPs) in both the intact and acutely stroke-injured M1 contralateral to the stimulated cerebellum in adult Long-Evans rats under anesthesia. We analyzed changes in the firing rates of single units, the extent of synchronous spiking and power spectral density (PSD) changes in LFPs during and post-stimulation. RESULTS: Our results show that post-stimulation, the firing rates of a majority of M1 neurons changed significantly with respect to their baseline rates. These firing rate changes were diverse in character, as the firing rate of some neurons increased while others decreased. Additionally, these changes started to set in during stimulation. Furthermore, cross-correlation analysis showed a significant increase in coincident firing amongst neuronal pairs. Interestingly, this increase in synchrony was unrelated to the direction of firing rate change. We also found that neuronal ensembles derived through principal component analysis were more active post-stimulation. Lastly, these changes occurred without a significant change in the overall spectral power of LFPs post-stimulation. CONCLUSIONS: Our results show that cerebellar stimulation caused significant, long-lasting changes in the activity patterns of M1 neurons by altering firing rates, boosting neural synchrony and increasing neuronal assemblies' activation strength. Our study provides evidence that cerebellar stimulation can directly modulate cortical dynamics. Since these results are present in the perilesional cortex, our data might also help explain the facilitatory effects of cerebellar stimulation post-stroke.