Imaging Anisotropic Waveguide Exciton Polaritons in Tin Sulfide.

In recent years, novel materials supporting in-plane anisotropic polaritons have attracted a great deal of research interest due to their capability of shaping nanoscale field distributions and controlling nanophotonic energy flows. Here we report a nano-optical imaging study of waveguide exciton polaritons (EPs) in tin sulfide (SnS) in the near-infrared (near-IR) region using scattering-type scanning near-field optical microscopy (s-SNOM). With s-SNOM, we mapped in real space the propagative EPs in SnS, which show sensitive dependence on the excitation energy and sample thickness. Moreover, we found that both the polariton wavelength and propagation length are anisotropic in the sample plane. In particular, in a narrow spectral range from 1.32 to 1.44 eV, the EPs demonstrate quasi-one-dimensional propagation, which is rarely seen in natural polaritonic materials. A further analysis indicates that the observed polariton anisotropy originates from the different optical band gaps and exciton binding energies along the two principal crystal axes of SnS.

Micro-RNA-451 Reduces Proliferation of B-CPAP Human Papillary Thyroid Cancer Cells by Downregulating Expression of Activating Transcription Factor 2.

BACKGROUND MicroRNAs (miRNAs) are novel biomarkers that are important in tumorigenesis and cancer treatment resistance. miR-451 is expressed in human papillary thyroid carcinoma (PTC) tissues and is associated with tumor progression. This study investigated the molecular mechanism associated with the effects of miR-451 on B-CPAP human PTC cells in vitro. MATERIAL AND METHODS Binding of miRNAs to the 3' untranslated region (3'UTR) of messenger RNA (mRNA) was determined with a luciferase reporter assay. miRNAs and plasmids were transfected into human PTC B-CPAP cells with Lipofectamine 2000 Transfection Reagent. Cell viability was tested with a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide assay. The levels of miRNAs and mRNA were determined with quantitative polymerase chain reaction and protein levels were analyzed with immunoblotting. RESULTS miR-451 bound to wild-type but not mutant 3'-UTR of activating transcription factor 2 (ATF2). MiR-451 mimics inhibited the growth of B-CPAP cells and reduced mRNA and protein levels in ATF2, whereas miR-451 inhibitors promoted the growth of B-CPAP cells and increased mRNA and protein levels in ATF2. CONCLUSIONS miR-451 directly bound to the 3'UTR of ATF2, decreased mRNA and protein levels in ATF2, and inhibited growth of B-CPAP cells. Our findings suggest that miR-451 may be a potential therapeutic target for PTC.

Author Correction: Antiviral agents: Targeting vesicle size.

In the version of this News & Views originally published, 'amphipathic' was incorrectly spelled 'amphiphatic' in the standfirst. This has been corrected in the online versions of the News & Views.

Drawing inferences for high-dimensional linear models: A selection-assisted partial regression and smoothing approach.

Drawing inferences for high-dimensional models is challenging as regular asymptotic theories are not applicable. This article proposes a new framework of simultaneous estimation and inferences for high-dimensional linear models. By smoothing over partial regression estimates based on a given variable selection scheme, we reduce the problem to low-dimensional least squares estimations. The procedure, termed as Selection-assisted Partial Regression and Smoothing (SPARES), utilizes data splitting along with variable selection and partial regression. We show that the SPARES estimator is asymptotically unbiased and normal, and derive its variance via a nonparametric delta method. The utility of the procedure is evaluated under various simulation scenarios and via comparisons with the de-biased LASSO estimators, a major competitor. We apply the method to analyze two genomic datasets and obtain biologically meaningful results.

Inter-unit reliability for nonlinear models.

In monitoring dialysis facilities, various quality measures are used in order to assess the performance and quality of care. The inter-unit reliability (IUR) describes the proportion of variation in the quality measure that is due to the between-facility variation. If the measure under evaluation is a simple average across normally distributed patient outcomes for each facility, the IUR is based on a one-way analysis of variance (ANOVA). However, more complex quality measures are not simple averages of individual outcomes. Even the standard bootstrap methods are inadequate because the computational burden increases quickly as the sample size grows, prohibiting its application in large-scale studies. To generalize the IUR to complex quality measures used in nonlinear models, we propose an approach combining the strengths of ANOVA and resampling. The proposed method is computationally efficient and can be applied to large-scale biomedical data with complex data structures. The method is exemplified in various measures of dialysis facilities using national dialysis data.

Efficiency of Launching Highly Confined Polaritons by Infrared Light Incident on a Hyperbolic Material.

We investigated phonon-polaritons in hexagonal boron nitride-a naturally hyperbolic van der Waals material-by means of the scattering-type scanning near-field optical microscopy. Real-space nanoimages we have obtained detail how the polaritons are launched when the light incident on a thin hexagonal boron nitride slab is scattered by various intrinsic and extrinsic inhomogeneities, including sample edges, metallic nanodisks deposited on its top surface, random defects, and surface impurities. The scanned tip of the near-field microscope is itself a polariton launcher whose efficiency proves to be superior to all the other types of polariton launchers we studied. Our work may inform future development of polaritonic nanodevices as well as fundamental studies of collective modes in van der Waals materials.

Designing graphene absorption in a multispectral plasmon-enhanced infrared detector.

We have examined graphene absorption in a range of graphene-based infrared devices that combine either monolayer or bilayer graphene with three different gate dielectrics. Electromagnetic simulations show that the optical absorption in graphene in these devices, an important factor in a functional graphene-based detector, is strongly dielectric-dependent. These simulations reveal that plasmonic excitation in graphene can significantly influence the percentage of light absorbed in the entire device, as well as the graphene layer itself, with graphene absorption exceeding 25% in regions where plasmonic excitation occurs. Notably, the dielectric environment of graphene has a dramatic influence on the strength and wavelength range over which the plasmons can be excited, making dielectric choice paramount to final detector tunability and sensitivity.

Tuning and Persistent Switching of Graphene Plasmons on a Ferroelectric Substrate.

We characterized plasmon propagation in graphene on thin films of the high-κ dielectric PbZr0.3Ti0.7O3 (PZT). Significant modulation (up to ±75%) of the plasmon wavelength was achieved with application of ultrasmall voltages (< ±1 V) across PZT. Analysis of the observed plasmonic fringes at the graphene edge indicates that carriers in graphene on PZT behave as noninteracting Dirac Fermions approximated by a semiclassical Drude response, which may be attributed to strong dielectric screening at the graphene/PZT interface. Additionally, significant plasmon scattering occurs at the grain boundaries of PZT from topographic and/or polarization induced graphene conductivity variation in the interior of graphene, reducing the overall plasmon propagation length. Lastly, through application of 2 V across PZT, we demonstrate the capability to persistently modify the plasmonic response of graphene through transient voltage application.

PGS: a tool for association study of high-dimensional microRNA expression data with repeated measures.

MOTIVATION: MicroRNAs (miRNAs) are short single-stranded non-coding molecules that usually function as negative regulators to silence or suppress gene expression. Owning to the dynamic nature of miRNA and reduced microarray and sequencing costs, a growing number of researchers are now measuring high-dimensional miRNA expression data using repeated or multiple measures in which each individual has more than one sample collected and measured over time. However, the commonly used univariate association testing or the site-by-site (SBS) testing may underutilize the longitudinal feature of the data, leading to underpowered results and less biologically meaningful results. RESULTS: We propose a penalized regression model incorporating grid search method (PGS), for analyzing associations of high-dimensional miRNA expression data with repeated measures. The development of this analytical framework was motivated by a real-world miRNA dataset. Comparisons between PGS and the SBS testing revealed that PGS provided smaller phenotype prediction errors and higher enrichment of phenotype-related biological pathways than the SBS testing. Our extensive simulations showed that PGS provided more accurate estimates and higher sensitivity than the SBS testing with comparable specificities. AVAILABILITY AND IMPLEMENTATION: R source code for PGS algorithm, implementation example and simulation study are available for download at https://github.com/feizhe/PGS.

Ultrafast dynamics of surface plasmons in InAs by time-resolved infrared nanospectroscopy.

We report on time-resolved mid-infrared (mid-IR) near-field spectroscopy of the narrow bandgap semiconductor InAs. The dominant effect we observed pertains to the dynamics of photoexcited carriers and associated surface plasmons. A novel combination of pump-probe techniques and near-field nanospectroscopy accesses high momentum plasmons and demonstrates efficient, subpicosecond photomodulation of the surface plasmon dispersion with subsequent tens of picoseconds decay under ambient conditions. The photoinduced change of the probe intensity due to plasmons in InAs is found to exceed that of other mid-IR or near-IR media by 1-2 orders of magnitude. Remarkably, the required control pulse fluence is as low as 60 µJ/cm(2), much smaller than fluences of ∼ 1-10 mJ/cm(2) previously utilized in ultrafast control of near-IR plasmonics. These low excitation densities are easily attained with a standard 1.56 µm fiber laser. Thus, InAs--a common semiconductor with favorable plasmonic properties such as a low effective mass--has the potential to become an important building block of optically controlled plasmonic devices operating at infrared frequencies.

Ultrafast and nanoscale plasmonic phenomena in exfoliated graphene revealed by infrared pump-probe nanoscopy.

Pump-probe spectroscopy is central for exploring ultrafast dynamics of fundamental excitations, collective modes, and energy transfer processes. Typically carried out using conventional diffraction-limited optics, pump-probe experiments inherently average over local chemical, compositional, and electronic inhomogeneities. Here, we circumvent this deficiency and introduce pump-probe infrared spectroscopy with ∼ 20 nm spatial resolution, far below the diffraction limit, which is accomplished using a scattering scanning near-field optical microscope (s-SNOM). This technique allows us to investigate exfoliated graphene single-layers on SiO2 at technologically significant mid-infrared (MIR) frequencies where the local optical conductivity becomes experimentally accessible through the excitation of surface plasmons via the s-SNOM tip. Optical pumping at near-infrared (NIR) frequencies prompts distinct changes in the plasmonic behavior on 200 fs time scales. The origin of the pump-induced, enhanced plasmonic response is identified as an increase in the effective electron temperature up to several thousand Kelvin, as deduced directly from the Drude weight associated with the plasmonic resonances.

Gestational diabetes mellitus and risk of neurodevelopmental disorders in young offspring: does the risk differ by race and ethnicity?

BACKGROUND: Previous studies examined the associations of gestational diabetes mellitus with autism spectrum disorder and attention deficit hyperactivity disorder. However, the associations between gestational diabetes mellitus and other neurodevelopmental disorders, such as the common speech/language disorder and developmental coordination disorder, are rarely studied, and whether the associations vary by race/ethnicity remains unknown. OBJECTIVE: This study aimed to examine the associations of gestational diabetes mellitus with individual neurodevelopmental disorders in young offspring, and to investigate whether the associations vary by race/ethnicity. STUDY DESIGN: This retrospective cohort study (Glucose in Relation to Women and Babies' Health [GrownB]) included 14,480 mother-offspring pairs in a large medical center in the United States from March 1, 2013 to August 31, 2021. We ascertained gestational diabetes mellitus using the validated ICD (International Classification of Diseases) codes (ICD-9: 648.8x; ICD-10: O24.4x), and identified neurodevelopmental disorders (speech/language disorder, developmental coordination disorder, autism spectrum disorder, and other neurodevelopmental disorders [attention deficit hyperactivity disorder, behavioral disorder, intellectual disability, and learning difficulty]) and their combinations using validated algorithms. We compared the hazard of neurodevelopmental disorders during the entire follow-up period between offspring born to mothers with and without gestational diabetes mellitus using multivariable Cox regression models. RESULTS: Among all mothers, 19.9% were Asian, 21.8% were Hispanic, 41.0% were non-Hispanic White, and 17.3% were of other/unknown race/ethnicity. During the median follow-up of 3.5 years (range, 1.0-6.3 years) after birth, 8.7% of offspring developed at least 1 neurodevelopmental disorder. Gestational diabetes mellitus was associated with a higher risk of speech/language disorder (adjusted hazard ratio, 1.59 [95% confidence interval, 1.07-2.35]), developmental coordination disorder (2.36 [1.37-4.04]), autism spectrum disorder (3.16 [1.36-7.37]), other neurodevelopmental disorders (3.12 [1.51-6.47]), any neurodevelopmental disorder (1.86 [1.36-2.53]), the combination of speech/language disorder and autism spectrum disorder (3.79 [1.35-10.61]), and the combination of speech/language disorder and developmental coordination disorder (4.22 [1.69-10.51]) among offspring born to non-Hispanic White mothers. No associations between gestational diabetes mellitus and any neurodevelopmental disorders or their combinations were observed among offspring born to mothers of other racial/ethnic groups. CONCLUSION: We observed an elevated risk of neurodevelopmental disorders among young offspring born to non-Hispanic White mothers with gestational diabetes mellitus, but not among other racial/ethnic groups.

Prevalence of maternal hyperglycemic subtypes by race/ethnicity and associations between these subtypes with adverse pregnancy outcomes: Findings from a large retrospective multi-ethnic cohort in the United States.

AIMS: With the two-step gestational diabetes mellitus (GDM) screening approach, hyperglycemic subtypes can be identified. We aimed to investigate racial/ethnic differences in the prevalence of hyperglycemic subtypes and to examine the associations between these subtypes and adverse pregnancy outcomes. METHODS: In this retrospective cohort, 11,405 pregnancies were screened using the two-step approach. Hyperglycemic subtypes included: pregnancy-impaired glucose intolerance-I (PIGT-I), PIGT-II, GDM-I (abnormal post-load glucose only), and GDM-II (abnormal fasting & post-load glucose). Modified Poisson regressions with robust error variance were used to estimate age-adjusted prevalence ratios (PR) of hyperglycemic subtypes and multivariable-adjusted risk ratios (RR) of adverse pregnancy outcomes. RESULTS: The prevalence of hyperglycemic subtypes was higher in Asians (PIGT-I: 1.51 [95% confidence interval 1.35-1.69]; PIGT-II: 2.18 [1.78-2.68]; GDM-I: 2.55 [2.10-3.10]; GDM-II: 1.55 [1.08-2.21]) and Hispanics (PIGT-I: 1.32 [1.16-1.50]; PIGT-II: 2.07 [1.67-2.57]; GDM-I: 1.69 [1.35-2.13]; GDM-II: 2.68 [1.93-3.71]) than non-Hispanic Whites (NHW). Despite low GDM prevalence, Japanese and Koreans had higher PIGT prevalence than NHW. PIGT-II was positively associated with hypertensive disorders of pregnancy (1.19 [1.02-1.38]), large-for-gestational age (1.73 [1.37-2.18]), and preterm birth (PB, 1.33 [1.05-1.68]). PIGT-I (1.23 [1.04-1.45]) and GDM-I (1.56 [0.87-1.71]) were positively related to PB. CONCLUSIONS: The prevalence of hyperglycemic subtypes varies by race/ethnicity and they have distinct health implications.

Social Determinants of Health and Continuity of Medications for Opioid Use Disorder Among Patients Receiving Treatment in Rural Primary Care Settings.

OBJECTIVES: Factors associated with treatment retention on medications for opioid use disorder (MOUD) in rural settings are poorly understood. This study examines associations between social determinants of health (SDoH) and MOUD retention among patients with opioid use disorder (OUD) in rural primary care settings. METHODS: We analyzed patient electronic health records from 6 rural clinics. Participants (N = 575) were adult patients with OUD and had any prescription for MOUD from October 2019 to April 2020. MOUD retention was measured by MOUD days and continuity defined as continuous 180 MOUD days with no more than a 7-day gap. Mixed-effect regressions assessed associations between the outcomes and SDoH (Medicaid insurance, social deprivation index [SDI], driving time from home to the clinic), telehealth use, and other covariates. RESULTS: Mean patient MOUD days were 127 days (SD = 50.7 days). Living in more disadvantaged areas (based on SDI) (adjusted relative risk [aRR]: 0.98; 95% confidence interval [CI], 0.98-0.99) and having more than an hour (compared with an hour or less) driving time from home to clinic (aRR: 0.95; 95% CI, 0.93-0.97) were associated with fewer MOUD days. Using telehealth was associated with more MOUD days (aRR: 1.23; 95% CI, 1.21-1.26). In this cohort, 21.7% of the participants were retained on MOUD for at least 180 days. SDoH and use of telehealth were not associated with having continuity of MOUD. CONCLUSIONS: Addressing SDoH (eg, SDI) and providing telehealth (eg, improvements in public transportation, internet access) may improve MOUD days in rural settings.

Efficacy of Smoothing Algorithms to Enhance Detection of Visual Field Progression in Glaucoma.

Purpose: To evaluate and compare the effectiveness of nearest neighbor (NN)- and variational autoencoder (VAE)-smoothing algorithms to reduce variability and enhance the performance of glaucoma visual field (VF) progression models. Design: Longitudinal cohort study. Subjects: 7150 eyes (4232 patients), with ≥ 5 years of follow-up and ≥ 6 visits. Methods: Vsual field thresholds were smoothed with the NN and VAE algorithms. The mean total deviation (mTD) and VF index rates, pointwise linear regression (PLR), permutation of PLR (PoPLR), and the glaucoma rate index were applied to the unsmoothed and smoothed data. Main Outcome Measures: The proportion of progressing eyes and the conversion to progression were compared between the smoothed and unsmoothed data. A simulation series of noiseless VFs with various patterns of glaucoma damage was used to evaluate the specificity of the smoothing models. Results: The mean values of age and follow-up time were 62.8 (standard deviation: 12.6) years and 10.4 (standard deviation: 4.7) years, respectively. The proportion of progression was significantly higher for the NN and VAE smoothed data compared with the unsmoothed data. VF progression occurred significantly earlier with both smoothed data compared with unsmoothed data based on mTD rates, PLR, and PoPLR methods. The ability to detect the progressing eyes was similar for the unsmoothed and smoothed data in the simulation data. Conclusions: Smoothing VF data with NN and VAE algorithms improves the signal-to-noise ratio for detection of change, results in earlier detection of VF progression, and could help monitor glaucoma progression more effectively in the clinical setting. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Association Between Gestational Diabetes Mellitus and Hypertension: A Systematic Review and Meta-Analysis of Cohort Studies With a Quantitative Bias Analysis of Uncontrolled Confounding.

BACKGROUND: Whether individuals with gestational diabetes mellitus (GDM) had an increased risk of hypertension remains unclear. We conducted a systematic literature review and meta-analysis to examine the association between GDM and hypertension and performed a quantitative bias analysis to quantify the impact of uncontrolled confounding due to antenatal psychological stress. METHODS: We searched databases (PUBMED, EMBASE, and Web of Science) through 2022/11. Eligible studies were cohort studies that reported the association of GDM with hypertension. We assessed the risk of bias using the Newcastle-Ottawa Scale for cohort studies. We pooled adjusted risk ratios with 95% CIs using a random effects model. We performed the quantitative bias analysis using the bias formula. RESULTS: We included 15 cohort studies, with a total of 3 959 520 (GDM, 175 378; non-GDM, 3 784 142) individuals. During the follow-up of 2 to 20 years, 106 560 cases of hypertension were reported. We found that GDM was associated with a higher risk of hypertension (pooled risk ratio, 1.78 [95% CI, 1.47, 2.17]). The risk ratio was lower among cohorts assessing incident (1.58 [95% CI, 1.29, 1.95]) than prevalent hypertension (2.60 [95% CI, 2.40, 2.83]). However, other subgroup analyses showed no differences. The quantitative bias analysis revealed that if the uncontrolled confounder of antenatal psychological stress was additionally adjusted, the positive association between GDM and hypertension would attenuate slightly (≤18%) but remains positive. CONCLUSIONS: Limitations of this study included residual confounding and discrepancies in GDM and hypertension ascertainments. Our findings indicate that GDM is positively associated with hypertension after the index pregnancy.

Epigenetic predictors of species maximum life span and other life-history traits in mammals.

By analyzing 15,000 samples from 348 mammalian species, we derive DNA methylation (DNAm) predictors of maximum life span (R = 0.89), gestation time (R = 0.96), and age at sexual maturity (R = 0.85). Our maximum life-span predictor indicates a potential innate longevity advantage for females over males in 17 mammalian species including humans. The DNAm maximum life-span predictions are not affected by caloric restriction or partial reprogramming. Genetic disruptions in the somatotropic axis such as growth hormone receptors have an impact on DNAm maximum life span only in select tissues. Cancer mortality rates show no correlation with our epigenetic estimates of life-history traits. The DNAm maximum life-span predictor does not detect variation in life span between individuals of the same species, such as between the breeds of dogs. Maximum life span is determined in part by an epigenetic signature that is an intrinsic species property and is distinct from the signatures that relate to individual mortality risk.

Inference for High-Dimensional Censored Quantile Regression.

With the availability of high dimensional genetic biomarkers, it is of interest to identify heterogeneous effects of these predictors on patients' survival, along with proper statistical inference. Censored quantile regression has emerged as a powerful tool for detecting heterogeneous effects of covariates on survival outcomes. To our knowledge, there is little work available to draw inference on the effects of high dimensional predictors for censored quantile regression. This paper proposes a novel procedure to draw inference on all predictors within the framework of global censored quantile regression, which investigates covariate-response associations over an interval of quantile levels, instead of a few discrete values. The proposed estimator combines a sequence of low dimensional model estimates that are based on multi-sample splittings and variable selection. We show that, under some regularity conditions, the estimator is consistent and asymptotically follows a Gaussian process indexed by the quantile level. Simulation studies indicate that our procedure can properly quantify the uncertainty of the estimates in high dimensional settings. We apply our method to analyze the heterogeneous effects of SNPs residing in lung cancer pathways on patients' survival, using the Boston Lung Cancer Survivor Cohort, a cancer epidemiology study on the molecular mechanism of lung cancer.

Psychosis among individuals with methamphetamine use disorder is associated with elevated rates of hospitalizations and emergency department visits across an academic health care system.

INTRODUCTION: Methamphetamine (MA) is increasingly available in the United States and manufactured with increasing potency. Although psychosis is a known harm related to MA use, we know little about the clinical outcomes and prognosis of individuals who use MA and experience psychosis. Some evidence exists that psychosis among people who use methamphetamine leads to a high utilization of emergency and acute inpatient services, but the extent of this use is unclear. METHODS: Using an electronic health record (EHR) database, this study assessed acute care visits of individuals receiving diagnostic codes of the following disorders: methamphetamine use disorder with undifferentiated psychosis (MUDp), schizophrenia (MUDs) and no history of psychosis (MUD) in addition to individuals without MUD diagnosis but with diagnoses of either undifferentiated psychosis (Psy) or schizophrenia (Scz) from 2006 to 2019. The study explored potential clinical risk factors associated with rate of acute care visits. RESULTS: Receiving diagnoses of psychotic disorders and MUD were both associated with high rates of acute care utilization. The incidence rate ratio (IRR) was highest in the MUDp group 6.30 (95% CI: 5.73, 6.93) followed by the MUDs group 4.03 (95% CI: 3.87, 4.20), the Psy group 3.77 (95% CI: 3.45, 4.11), the Scz group 3.11 (95% CI: 2.99, 3.23), and the MUD group 2.17 (95% CI: 2.09, 2.25). Receiving another SUD diagnosis was identified as a risk factor for acute care visits in the MUDp group, and mood and anxiety disorder diagnoses were a risk factor in the MUDs group. CONCLUSIONS: In a general health care system, individuals receiving diagnoses of MUD and co-occurring psychotic disorders were observed to have particularly high rates of acute care service utilization, suggesting a high degree of disease burden and the need for development of targeted treatment interventions with both MUD and psychosis.