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Purpose The radiographic rectus width to hernia width ratio (RDR) has been shown to predict ability to close fascial defect without additional myofascial release in open Rives-Stoppa abdominal wall reconstruction (AWR), but it has not been studied in robotic AWR. We aimed to examine various CT measurements to determine their usability in predicting the need for transversus abdominis release (TAR) in robotic AWR. Methods We performed a single-center retrospective review of 137 patients with midline ventral hernias over a 5-year period who underwent elective robotic retrorectus AWR. We excluded patients with M1 or M5 hernias, lateral/flank hernias, and hybrid repairs. The CT measurements included hernia width (HW), hernia width/abdominal width ratio (HW/AW), and RDR. Univariate, multivariate and area under the curve (AUC) analyses were performed. Results 58/137 patients required TAR (32 unilateral, 26 bilateral). Patients undergoing TAR had a significantly higher average HW and HW/AW and lower RDR. Multivariate analysis revealed that prior hernia repair was independently associated with need for TAR ( p  = 0.03). ROC analysis and AUC values showed acceptable diagnostic ability of HW, HW/AW and RDR in predicting need for TAR. Cutoffs of RDR ≤ 2, HW/AW > 0.3, and HW > 10 cm yielded high specificity in determining need for any TAR (97.5% vs. 96.2% vs. 92.4%) or bilateral TAR (95.5% vs. 94.6% vs. 92.8%). Conclusion History of prior hernia repair was a risk factor for robotic TAR. CT measurements have some predictive value in determining need for TAR in robotic AWR. Further prospective analysis is needed in this patient population.

Interannual variability of wood density – an important plant functional trait and environmental proxy – in conifers is poorly understood. We therefore explored the anatomical basis of density. We hypothesized that earlywood density is determined by tracheid size and latewood density by wall dimensions, reflecting their different functional tasks. To determine general patterns of variability, density parameters from 27 species and 349 sites across the Northern Hemisphere were correlated to tree-ring width parameters and local climate. We performed the same analyses with density and width derived from anatomical data comprising two species and eight sites. The contributions of tracheid size and wall dimensions to density were disentangled with sensitivity analyses. Notably, correlations between density and width shifted from negative to positive moving from earlywood to latewood. Temperature responses of density varied intraseasonally in strength and sign. The sensitivity analyses revealed tracheid size as the main determinant of earlywood density, while wall dimensions become more influential for latewood density. Our novel approach of integrating detailed anatomical data with large-scale tree-ring data allowed us to contribute to an improved understanding of interannual variations of conifer growth and to illustrate how conifers balance investments in the competing xylem functions of hydraulics and mechanical support.

Teleost fishes account for 96% of all fish species and exhibit a spectacular variety of body forms. Teleost lineages range from deep bodied to elongate (e.g., eels, needlefish), laterally compressed (e.g., ribbonfish) to globular (e.g., pufferfish), and include uniquely shaped lineages such as seahorses, flatfishes, and ocean sunfishes. Adaptive body shape convergence within fishes has long been hypothesized but the nature of the relationships between fish form and ecological and environmental variables remain largely unknown at the macroevolutionary scale. To facilitate the investigation of the interacting factors influencing teleost body shape evolution we measured eight functionally relevant linear traits on adult-sized specimens along with specimen mass. Linear measurements of standard length, maximum body depth, maximum fish width, lower jaw length, mouth width, head depth, minimum caudal peduncle depth, and minimum caudal peduncle width were taken in millimeters with calipers, or tape measures for oversized specimens. We measured these traits on a total of 16,523 specimens (1—3 specimens per species) at the Smithsonian National Museum of Natural History and took approximately 7000 person hours of data collection to complete. The data went through a three-step error-checking process to clean and validate the data and then species averages were calculated. We present the complete specimen data set, which encompasses approximately one-fifth of extant teleost species diversity, spanning ~90% of teleost families and ~96% of orders. The species and family names are compatible with the taxonomy used by FishBase and the order information with the phylogenetically informed taxonomy of Betancur-R and colleagues published in 2014. This dataset is licensed under Creative Commons CC0 1.0 Universal (CC0 1.0) but please cite this paper when using the data or a subset of it.

• Understanding the genetic basis of natural variation in grain size among diverse rice varieties can help breeders develop high-yielding rice cultivars. • Here, we report the discovery of qTGW2, a new semidominant quantitative trait locus for grain width and weight. The corresponding gene, TGW2, encodes CELL NUMBER REGULATOR 1 (OsCNR1) localized to the plasma membrane. • A single nucleotide polymorphism (SNP) variation 1818 bp upstream of TGW2 is responsible for its different expression, leading to alteration in grain width and weight by influencing cell proliferation and expansion in glumes. TGW2 interacts with KRP1, a regulator of cell cycle in plants, to negatively regulate grain width and weight. Genetic diversity analysis of TGW2 in 141 rice accessions revealed it as a breeding target in a selective sweep region. • Our findings provide new insights into the genetic mechanism underlying grain morphology and grain weight, and uncover a promising gene for improving rice yield.

Background: It becomes extremely challenging for forensic artists to reconstruct the highly decomposed faces, especially during mass disasters. It would be of great help for the identifying team of experts if there was a method to determine the facial and cephalic dimensions. This study aims to provide a method to generate a simplified method to calculate the facial and cephalic indices of an individual based on the dentition since human dentition remains almost intact in most scenarios. Materials and Methods: The sample consisted of 200 participants with the age range of 18-23 years belonging to Kerala. The cephalic and facial indices were measured using a caliper. The interincisal, intercanine, interpremolar and intermolar widths of maxillary dentition were measured on study models using a digital vernier caliper. The mean cranial and facial index were calculated and were correlated with interdental measurements. Results: It was concluded that dominant head types in Kerala males were dolichocephalic (50.2%) followed by mesocephalic (29.8%). In females, the dominant head types were dolichocephalic (42.7%) followed by mesocephalic (42.2%). In the facial types, majority of individuals were found to be leptoprosopic. A good correlation was found between the intercanine width with facial width and cranial width and a simplified formula were derived to estimate the cranial and facial index for this population. Conclusion: The results of the study suggest that the facial index and cranial index of a particular population can be evaluated from interdental measurements of the maxillary cast, especially the intercanine width.

Rice leaf width (RLW) is a crucial determinant of photosynthetic area. Despite the discovery of several genes controlling RLW, the underlying genetic architecture remains unclear. In order to better understand RLW, this study conducted a genome-wide association study (GWAS) on 351 accessions from the rice diversity population II (RDP-II). The results revealed 12 loci associated with leaf width (LALW). In LALW4, we identified one gene, Narrow Leaf 22 (NAL22), whose polymorphisms and expression levels were associated with RLW variation. Knocking out this gene in Zhonghua11, using CRISPR/Cas9 gene editing technology, resulted in a short and narrow leaf phenotype. However, seed width remained unchanged. Additionally, we discovered that the vein width and expression levels of genes associated with cell division were suppressed in nal22 mutants. Gibberellin (GA) was also found to negatively regulate NAL22 expression and impact RLW. In summary, we dissected the genetic architecture of RLW and identified a gene, NAL22, which provides new loci for further RLW studies and a target gene for leaf shape design in modern rice breeding.

Finding narrow‐band, ultrapure blue thermally activated delayed fluorescence (TADF) materials is extremely important for developing highly efficient organic light‐emitting diodes (OLEDs). Here, spin–vibronic coupling (SVC)‐assisted ultrapure blue emitters obtained by joining two carbazole‐derived moieties at a para position of a phenyl unit and performing substitutions using several blocking groups are presented. Despite a relatively large singlet–triplet gap (∆EST) of >0.2 eV, efficient triplet‐to‐singlet crossover can be realized, with assistance from resonant SVC. To enhance the spin crossover, electronic energy levels are fine‐tuned, thereby causing ∆EST to be in resonance with a triplet–triplet gap (∆ETT). A sizable population transfer between spin multiplicities (>103 s−1) is achieved, and this result agrees well with theoretical predictions. An OLED fabricated using a multiple‐resonance‐type SVC‐TADF emitter with CIE color coordinates of (0.15, 0.05) exhibits ultrapure blue emissions, with a narrow full‐width‐at‐half‐maximum of 21 nm and a high external quantum efficiency of 23.1%. Spin‐vibronic coupling assisted ultrapure blue emitters demonstrate high external quantum efficiency of 23.1%, color coordinate of (0.15,0.05) and small full width at half maximum of 21 nm.

We propose a theoretical understanding of neural networks in terms of Wilsonian effective field theory. The correspondence relies on the fact that many asymptotic neural networks are drawn from Gaussian processes (GPs), the analog of non-interacting field theories. Moving away from the asymptotic limit yields a non-Gaussian process (NGP) and corresponds to turning on particle interactions, allowing for the computation of correlation functions of neural network outputs with Feynman diagrams. Minimal NGP likelihoods are determined by the most relevant non-Gaussian terms, according to the flow in their coefficients induced by the Wilsonian renormalization group. This yields a direct connection between overparameterization and simplicity of neural network likelihoods. Whether the coefficients are constants or functions may be understood in terms of GP limit symmetries, as expected from ’t Hooft’s technical naturalness. General theoretical calculations are matched to neural network experiments in the simplest class of models allowing the correspondence. Our formalism is valid for any of the many architectures that becomes a GP in an asymptotic limit, a property preserved under certain types of training.

BACKGROUND Peak‐width of skeletonized mean diffusivity (PSMD), a neuroimaging marker of cerebral small vessel disease (SVD), has shown excellent instrumental properties. Here, we extend our work to perform a biological validation of PSMD. METHODS We included 396 participants from the Biomarkers for Vascular Contributions to Cognitive Impairment and Dementia (MarkVCID‐1) Consortium and three replication samples (Cohorts for Heart and Aging Research in Genomic Epidemiology = 6172, Rush University Medical Center = 287, University of California Davis Alzheimer's Disease Research Center = 567). PSMD was derived from diffusion tensor imaging using an automated algorithm. We related PSMD to a composite measure of general cognitive function using linear regression models adjusting for confounders. RESULTS Higher PSMD was associated with lower general cognition in MarkVCID‐1 independent of age, sex, education, and intracranial volume (Beta [95% confidence interval], −0.8 [−1.2, −0.4], P < 0.001). These findings were replicated in independent samples. Furthermore, PSMD explained cognitive status above and beyond white matter hyperintensities. DISCUSSION Our biological validation work supports the pursuit of larger clinical validation studies evaluating PSMD as a susceptibility/risk biomarker of small vessel disease contributing to cognitive impairment and dementia. Highlights Peak‐width of skeletonized mean diffusivity (PSMD) is a novel small vessel disease neuroimaging biomarker. A prior instrumental validation study demonstrated that PSMD is a robust biomarker. This biological validation study shows that high PSMD relates to worse cognition. PSMD explains cognitive function above and beyond white matter hyperintensities. Future clinical validation will assess PSMD as a vascular contribution to cognitive impairment and dementia biomarker in clinical trials.

Purpose: To explore the association between red cell distribution width (RDW)-to-platelet ratio (RPR) and in- hospital mortality of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) patients and establish a prediction model based on RPR and other predictors. Material and Methods: This cohort study included 1922 AECOPD patients aged [greater than or equal to] 18 years in the Medical Information Mart for Intensive Care (MtMIC)-III and MIMIC-IV as well as 1738 AECOPD patients from elCU Collaborative Research Database (eICU-CRD). Possible confounding factors were screened out by univariate logistic regression, and multivariable logistic regression was applied to evaluate the association between RPR and in-hospital mortality of AECOPD patients. The area under the curve (AUC), calibration curve and decision curve analysis (DCA) curve were plotted to evaluate the predictive value of the model. The median follow-up time was 3.14 (1.87, 6.25) day. Results: At the end of follow-up, there were 1660 patients survived and 262 subjects died. After adjusting for confounders, we found that Log (RPR*1000) was linked with elevated risk of in-hospital mortality of AECOPD patients [odds ratio (OR)=1.36, 95% confidence interval (CI): 1.01-1.84]. The prediction model was constructed using predictors including Log (RPR*1000), age, malignant cancer, atrial fibrillation, ventilation, renal failure, diastolic blood pressure (DBP), temperature, Glasgow Coma Scale (GCS) score, white blood cell (WBC), creatinine, blood urea nitrogen (BUN), hemoglobin, infectious diseases and anion gap. The AUC of the prediction model was 0.785 (95% CI: 0.751-0.820) in the training set, 0.721 (95% CI: 0.662-0.780) in the testing set, and 0.795 (95% CI: 0.762-0.827) in the validation set. Conclusion: RPR was associated with the in-hospital mortality of AECOPD patients. The prediction model for the in- hospital mortality of AECOPD patients based on RPR and other predictors presented good predictive performance, which might help the clinicians to quickly identify AECOPD patients at high risk of in-hospital mortality. Keywords: red cell distribution width-to-platelet ratio, acute exacerbations of chronic obstructive pulmonary disease, red cell distribution width, platelet ratio