Self-assembled photonic cavities with atomic-scale confinement.

Despite tremendous progress in research on self-assembled nanotechnological building blocks, such as macromolecules1, nanowires2 and two-dimensional materials3, synthetic self-assembly methods that bridge the nanoscopic to macroscopic dimensions remain unscalable and inferior to biological self-assembly. By contrast, planar semiconductor technology has had an immense technological impact, owing to its inherent scalability, yet it seems unable to reach the atomic dimensions enabled by self-assembly. Here, we use surface forces, including Casimir-van der Waals interactions4, to deterministically self-assemble and self-align suspended silicon nanostructures with void features well below the length scales possible with conventional lithography and etching5, despite using only conventional lithography and etching. The method is remarkably robust and the threshold for self-assembly depends monotonically on all the governing parameters across thousands of measured devices. We illustrate the potential of these concepts by fabricating nanostructures that are impossible to make with any other known method: waveguide-coupled high-Q silicon photonic cavities6,7 that confine telecom photons to 2 nm air gaps with an aspect ratio of 100, corresponding to mode volumes more than 100 times below the diffraction limit. Scanning transmission electron microscopy measurements confirm the ability to build devices with sub-nanometre dimensions. Our work constitutes the first steps towards a new generation of fabrication technology that combines the atomic dimensions enabled by self-assembly with the scalability of planar semiconductors.

Single-Molecule Sizing through Nanocavity Confinement.

An approach relying on nanocavity confinement is developed in this paper for the sizing of nanoscale particles and single biomolecules in solution. The approach, termed nanocavity diffusional sizing (NDS), measures particle residence times within nanofluidic cavities to determine their hydrodynamic radii. Using theoretical modeling and simulations, we show that the residence time of particles within nanocavities above a critical time scale depends on the diffusion coefficient of the particle, which allows the estimation of the particle's size. We demonstrate this approach experimentally through the measurement of particle residence times within nanofluidic cavities using single-molecule confocal microscopy. Our data show that the residence times scale linearly with the sizes of nanoscale colloids, protein aggregates, and single DNA oligonucleotides. NDS thus constitutes a new single molecule optofluidic approach that allows rapid and quantitative sizing of nanoscale particles for potential applications in nanobiotechnology, biophysics, and clinical diagnostics.

Efficient low-reflection fully etched vertical free-space grating couplers for suspended silicon photonics.

We design and fabricate a grating coupler for interfacing suspended silicon photonic membranes with free-space optics while being compatible with single-step lithography and etching in 220 nm silicon device layers. The grating coupler design simultaneously and explicitly targets both high transmission into a silicon waveguide and low reflection back into the waveguide by means of a combination of a two-dimensional shape-optimization step followed by a three-dimensional parameterized extrusion. The designed coupler has a transmission of -6.6 dB (21.8 %), a 3 dB bandwidth of 75 nm, and a reflection of -27 dB (0.2 %). We experimentally validate the design by fabricating and optically characterizing a set of devices that allow the subtraction of all other sources of transmission losses as well as the inference of back-reflections from Fabry-Pérot fringes, and we measure a transmission of 19 % ± 2 %, a bandwidth of 65 nm and a reflection of 1.0 % ± 0.8 %.

Profiling of Fusarium head blight resistance QTL haplotypes through molecular markers, genotyping-by-sequencing, and machine learning.

KEY MESSAGE: Marker-assisted selection is important for cultivar development. We propose a system where a training population genotyped for QTL and genome-wide markers may predict QTL haplotypes in early development germplasm. Breeders screen germplasm with molecular markers to identify and select individuals that have desirable haplotypes. The objective of this research was to investigate whether QTL haplotypes can be accurately predicted using SNPs derived by genotyping-by-sequencing (GBS). In the SunGrains program during 2020 (SG20) and 2021 (SG21), 1,536 and 2,352 lines submitted for GBS were genotyped with markers linked to the Fusarium head blight QTL: Qfhb.nc-1A, Qfhb.vt-1B, Fhb1, and Qfhb.nc-4A. In parallel, data were compiled from the 2011-2020 Southern Uniform Winter Wheat Scab Nursery (SUWWSN), which had been screened for the same QTL, sequenced via GBS, and phenotyped for: visual Fusarium severity rating (SEV), percent Fusarium damaged kernels (FDK), deoxynivalenol content (DON), plant height, and heading date. Three machine learning models were evaluated: random forest, k-nearest neighbors, and gradient boosting machine. Data were randomly partitioned into training-testing splits. The QTL haplotype and 100 most correlated GBS SNPs were used for training and tuning of each model. Trained machine learning models were used to predict QTL haplotypes in the testing partition of SG20, SG21, and the total SUWWSN. Mean disease ratings for the observed and predicted QTL haplotypes were compared in the SUWWSN. For all models trained using the SG20 and SG21, the observed Fhb1 haplotype estimated group means for SEV, FDK, DON, plant height, and heading date in the SUWWSN were not significantly different from any of the predicted Fhb1 calls. This indicated that machine learning may be utilized in breeding programs to accurately predict QTL haplotypes in earlier generations.

Nutritional Assessment of Denture Wearers Using Matched Electronic Dental-Health Record Data.

PURPOSE: To assess the nutritional profile of denture wearers through a retrospective cohort study using nutritional biomarkers from matched electronic dental and health record (EDR-EHR) data. MATERIALS AND METHODS: The case group (denture wearers) included matched EDR-EHR data of patients who received removable partial, complete, and implant-supported prosthodontic treatments between January 1, 2010 and December 31, 2018, study time. The control (nondenture wearers) group did not have recorded denture treatments and included patient records within 1 year of the denture index date (first date of case patients' receiving complete or partial denture) of the matching cases. The qualified patients' EDR were matched with their EHR based on the availability of laboratory reports within 2 years of receiving the dentures (index date). Nutritional biomarkers were selected from laboratory reports for complete blood count, comprehensive and basic metabolic profile, lipid, and thyroid panels. Summary statistics were performed, and general linear mixed effect models were used to evaluate the rate of change over time (slope) of nutritional biomarkers before and after the index date. Likelihood ratio tests were performed to determine the differences between dentures and controls. RESULTS: The final cohort included 10,481 matched EDR-EHR data with 3,519 denture wearers and 6,962 controls that contained laboratory results within the study time. The denture wearers' mean age was 57 ±10 years and the control group was 56 ±10 years with 55% females in both groups. Pre-post analysis among denture wearers revealed decreased serum albumin (p = 0.002), calcium (p = 0.039), creatinine (p < 0.001) during the post-index time. Hemoglobin (Hb) was higher pre-index, and was decreasing during the time period but did not change post-index (p < 0.001). Among denture wearers, completely edentulous patients had a significant decrease in serum albumin, creatinine, blood urea nitrogen (BUN), but increased estimated glomerular filtration rate (eGFR). In partially edentulous patients, total cholesterol decreased (p = 0.018) and TSH (p = 0.004), BUN (p < 0.001) increased post-index. Patients edentulous in either upper or lower arch had decreased BUN and eGFR during post-index. Compared to controls, denture wearers showed decreased serum albumin and protein (p = 0.008), serum calcium (p = 0.001), and controls showed increased Hb (p = 0.035) during post-index. CONCLUSIONS: The study results indicate nutritional biomarker variations among denture wearers suggesting a risk for undernutrition and the potential of using selected nutritional biomarkers to monitor nutritional profile.

Training population selection and use of fixed effects to optimize genomic predictions in a historical USA winter wheat panel.

KEY MESSAGE: The optimization of training populations and the use of diagnostic markers as fixed effects increase the predictive ability of genomic prediction models in a cooperative wheat breeding panel. Plant breeding programs often have access to a large amount of historical data that is highly unbalanced, particularly across years. This study examined approaches to utilize these data sets as training populations to integrate genomic selection into existing pipelines. We used cross-validation to evaluate predictive ability in an unbalanced data set of 467 winter wheat (Triticum aestivum L.) genotypes evaluated in the Gulf Atlantic Wheat Nursery from 2008 to 2016. We evaluated the impact of different training population sizes and training population selection methods (Random, Clustering, PEVmean and PEVmean1) on predictive ability. We also evaluated inclusion of markers associated with major genes as fixed effects in prediction models for heading date, plant height, and resistance to powdery mildew (caused by Blumeria graminis f. sp. tritici). Increases in predictive ability as the size of the training population increased were more evident for Random and Clustering training population selection methods than for PEVmean and PEVmean1. The selection methods based on minimization of the prediction error variance (PEV) outperformed the Random and Clustering methods across all the population sizes. Major genes added as fixed effects always improved model predictive ability, with the greatest gains coming from combinations of multiple genes. Maximum predictabilities among all prediction methods were 0.64 for grain yield, 0.56 for test weight, 0.71 for heading date, 0.73 for plant height, and 0.60 for powdery mildew resistance. Our results demonstrate the utility of combining unbalanced phenotypic records with genome-wide SNP marker data for predicting the performance of untested genotypes.

Mortality and Discharge Location of Intensive Care Patients With Alzheimer Disease and Related Dementia.

BACKGROUND: Intensive care unit (ICU) utilization has increased among patients with Alzheimer disease and related dementia (ADRD), although outcomes are poor. OBJECTIVES: To compare ICU discharge location and subsequent mortality between patients with and patients without ADRD enrolled in Medicare Advantage. METHODS: This observational study used Optum's Clinformatics Data Mart Database from years 2016 to 2019 and included adults aged >67 years with continuous Medicare Advantage coverage and a first ICU admission in 2018. Alzheimer disease and related dementia and comorbid conditions were identified from claims. Outcomes included discharge location (home vs other facilities) and mortality (within the same calendar month of discharge and within 12 months after discharge). RESULTS: A total of 145 342 adults met inclusion criteria; 10.5% had ADRD and were likely to be older, female, and have more comorbid conditions. Only 37.6% of patients with ADRD were discharged home versus 68.6% of patients who did not have ADRD (odds ratio [OR], 0.40; 95% CI, 0.38-0.41). Both death in the same month as discharge (19.9% vs 10.3%; OR, 1.54; 95% CI, 1.47-1.62) and death in the 12 months after discharge (50.8% vs 26.2%; OR, 1.95; 95% CI, 1.88-2.02) were twice as common among patients with ADRD. CONCLUSIONS: Patients with ADRD have lower home discharge rates and greater mortality after an ICU stay than patients without ADRD.

In situ-gelling starch nanoparticle (SNP)/O-carboxymethyl chitosan (CMCh) nanoparticle network hydrogels for the intranasal delivery of an antipsychotic peptide.

Existing oral or injectable antipsychotic drug delivery strategies typically demonstrate low bioavailability to targeted brain regions, incentivizing the development of alternative delivery strategies. Delivery via the nasal cavity circumvents multiple barriers for reaching the brain but requires drug delivery vehicles with very specific properties to be effective. Herein, we report in situ-gelling and degradable bulk nanoparticle network hydrogels consisting of oxidized starch nanoparticles (SNPs) and carboxymethyl chitosan (CMCh) that enable intranasal delivery via spray, high nasal mucosal retention, and functional controlled release of the peptide drug PAOPA, a positive allosteric modulator of dopamine D2 receptor. PAOPA-loaded SNP-CMCh hydrogels can alleviate negative symptoms like behavioural abnormalities associated with schizophrenia (i.e. decreased social interaction time) for up to 72 h in an MK-801-induced pre-clinical rat model of schizophrenia at a low drug dosage (0.5 mg/kg); in comparison, conventional PAOPA administration via the intraperitoneal route requires twice the PAOPA dose to achieve a therapeutic effect that persists for only a few hours. This strategy offers potential for substantially decreasing re-administration frequencies and overall drug doses (and thus side-effects) of a range of potential antipsychotic drugs via a minimally-invasive administration route.

Arsenic exposure through groundwater to the rural and urban population in the Allahabad-Kanpur track in the upper Ganga plain.

This preliminary study reports for the first time that part of the rural population in the Allahabad district and the urban population in the Suklaganj-Kanpur of Unnao district in the Allahabad-Kanpur track of the upper Ganga plain are drinking and using for agricultural irrigation arsenic contaminated water (maximum arsenic concentrations in drinking water and urine are 707 and 1744 microg L(-1) respectively) mostly from shallow hand tube-wells (depth 7.5-40 m) without knowing that these are arsenic contaminated.

Pattern of bear maul maxillofacial injuries in Kashmir.

OBJECTIVE: Bears are strong and agile wild animals that defend themselves, their young ones and their territory, if they feel threatened. Conflicts between humans and bears are common in bear-prevalent areas of the world. Our valley, which is surrounded all around by forests, is a habitat for black bears (U. thiabetanus) only. Maulings inflicted by these black bears are catastrophic events and such attacks have increased considerably in the recent past due to merciless deforestation. The rising incidences of such attacks, especially in maxillofacial region, have urged our department to undertake a study of such attacks and injuries. MATERIALS AND METHODS: The present study is both a retrospective and prospective study of 200 patients of bear maulings who were admitted and treated in the Department of OMFS, Govt. Dental College, Srinagar, from January 2005 to October 2009. RESULTS: Majority of the patients were from villages. Most of them belonged to fourth decade and majority was males. Black bears only were involved in all the encounters. Claws, paws and combination of both, were the used for attack. In majority of cases, no defense was used for the termination of attack. All the patients had soft tissue injury, deep lacerations, facial viscera, eyes, salivary glands and facial nerve commonly involved.