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Historically, wheat (Triticum aestivum L.) cultivars developed by the cooperative University of Nebraska–USDA‐ARS wheat improvement project were hard red winter wheat. With the expanding hard white wheat market, there is a greater emphasis on developing hard white winter wheat lines adapted to the Great Plains. 'NW13493' (tested as NW13493) (Reg. no. CV‐1197, PI 699380) was selected for its white kernels, agronomic performance, relevant disease resistances, and end‐use quality and is adapted to the central Great Plains. NW13493 was licensed to Bay State Milling Company on the basis of its superior agronomic and end‐use quality performance and also the need to ensure hard white wheat growers have a known market for their grain. NW13493 hard white winter wheat was released in February 2021 by the developing institutions and the licensee. NW13493 was a selection in 2013 from the cross 'SD98W175‐1'/'NW03666', which was made in 2007. The pedigree of SD98W175‐1 is 'KS84273BB‐10'/'KSSB110‐9'//'KS831374‐141B'/'YE1110'/3/ 'KS82W418'/'Stephens' and the pedigree of NW03666 is 'N94S097KS'/'NE93459'. The F1 generation was grown in the greenhouse in 2008, and the F2 to F3 generations were advanced as bulks at Mead, NE, in 2009–2010. NW13493 was evaluated in replicated trials beginning in 2014. It has excellent winter survival and agronomic performance, acceptable disease reactions to many of the common diseases in its target area, and good end‐use quality for bread making. Core Ideas: NW13493 is a new white wheat cultivar adapted to the upper Great Plains.NW13493 has excellent agronomic performance and good disease resistance.The end‐use quality of NW13493 is very good, and it has been licensed to Bay State Milling Company. [ABSTRACT FROM AUTHOR]

Historically cultivars developed jointly by the University of Nebraska‐Lincoln and USDA‐ARS wheat (Triticum aestivum L.) improvement project tend to be late and better adapted to the northern Great Plains. LCS 'Valiant' (Reg. no. CV‐1196, PI 693223; tested as NE10478‐1) was released based on the merits of its earliness, agronomic performance, relevant disease resistances, and end‐use quality characteristics and its adaptation to the central Great Plains. As such, the line was licensed to Limagrain Cereal Seeds for their ability to market outside of Nebraska. LCS Valiant hard red winter wheat was released in March 2020 by the developing institutions and the licensee. NE10478‐1 was a selection in 2011 for uniformity and grain yield from NE10478, which was derived from the cross NI03418/'Camelot'. The pedigree of NI03418 is W91‐248/NE95544 (=McVey 78015/NE88521)//'Thunderbird'. The final cross of NE10478 was made in 2004. The F1 generation was grown in Yuma, AZ, in 2005, and the F2 to F3 generations were advanced as bulks at Mead, NE, in 2006–2007 or sent for Hessian fly resistance screening by the USDA. In 2007, single F3‐derived F4 rows were planted for selection. There was no further selection in NE10478 other than to remove off‐types thereafter until 2011 when heads were selected to increase uniformity. LCS Valiant was evaluated in replicated trials thereafter. It has excellent winter survival, acceptable reactions to many of the common diseases in its target area, and good end‐use quality for bread making. Core Ideas: Valiant is an early hard red winter wheat adapted to the central Great Plains for dryland production. Valiant has excellent winter survival and stem rust resistance and good Hessian fly resistance. The end‐use quality for bread making of Valiant is very good. [ABSTRACT FROM AUTHOR]

Image super-resolution is a research endeavour that has gained notoriety in computer vision. The research goal is to increase the spatial dimensions of an image using corresponding low-resolution and high-resolution image pairs to enhance the perceptual quality. The challenge of maintaining such perceptual quality lies in developing appropriate algorithms that learn to reconstruct higher-quality images from their lower-resolution counterparts. Recent methods employ deep learning algorithms to reconstruct textural details prevalent in low-resolution images. Since corresponding image pairs are non-trivial to collect, researchers attempt super-resolution by creating synthetic low-resolution representations of high-resolution images. Unfortunately, such methods employ ineffective downscaling operations to achieve synthetic low-resolution images. These methods fail to generalize well on real-world images that may suffer different degradations. A different angle is offered to solve the task of image super-resolution by investigating the plausibility of learning the degradational operation using generative adversarial networks. A two-stage generative adversarial network along with two architectural variations is proposed to solve the task of real-world super-resolution from low-resolution images with unknown degradations. It is demonstrated that learning to downsample images in a weakly supervised manner is an impactful and viable approach for super-resolution.

Yamanaka factors (YFs) can reverse some aging features in mammalian tissues, but their effects on the brain remain largely unexplored. Here, we induced YFs in the mouse brain in a controlled spatiotemporal manner in two different scenarios: brain development and adult stages in the context of neurodegeneration. Embryonic induction of YFs perturbed cell identity of both progenitors and neurons, but transient and low-level expression is tolerated by these cells. Under these conditions, YF induction led to progenitor expansion, an increased number of upper cortical neurons and glia, and enhanced motor and social behavior in adult mice. Additionally, controlled YF induction is tolerated by principal neurons in the adult dorsal hippocampus and prevented the development of several hallmarks of Alzheimer's disease, including cognitive decline and altered molecular signatures, in the 5xFAD mouse model. These results highlight the powerful impact of YFs on neural proliferation and their potential use in brain disorders., Competing Interests: Declaration of interests M.S. is a shareholder of Senolytic Therapeutics, Life Biosciences, Rejuveron Senescence Therapeutics, and Altos Labs. M.S. was a consultant of Rejuveron Senescence Therapeutics and Altos Labs until the end of 2022. M.A. is a shareholder of Altos Labs., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Introduction: The COVID-19 pandemic impacted mental health, as demonstrated by numerous studies. In recent years, especially during the pandemic, the use of social networks, including Twitter, increased. This suggests that this media could help with mental health monitoring, as attested by previous studies., Method: We conducted a multidisciplinary study on French tweets that were posted between January 1, 2019, and December 31, 2021. We selected the tweets via the Twitter API (Application Programming Interface) using five keywords relating to suicide: want to die, suicidal ideation, commit suicide, suicidal, and suicide attempt. A word frequency analysis was performed, and the data were compared with the number of emergency visits for suicidal ideation before and during the COVID-19 pandemic as recorded by the French national suicide observatory., Results: We observed that 189,005 tweets were related to suicide in 2019, 261,993 in 2020 (+38.62% of that observed in 2019), and 301,177 in 2021 (+59.35% of that observed in 2019). We also observed an increase in the number of tweets containing control words in 2020 (+30.07% of that observed in 2019), but in 2021, the number almost fell back to the level of that in 2019 (+5.96% of that observed in 2019). Furthermore, the difference between both ratios (of suicide-related tweets and of tweets containing control words) was most significant during the third lockdown. The change in the number of suicide-related tweets followed a curve that overlapped with the change in the number of emergency visits following suicidal ideations, as reported by the French national suicide observatory. In conclusion, Twitter can be an adequate and reliable tool for screening for suicidal ideation in the general population., (Copyright © 2023 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.)

Purpose: Competency-based medical education relies on equitable assessment. This study examined the influence of faculty and trainee gender on assessments of internal medicine (IM) resident performance over time., Method: A longitudinal analysis of clinical performance assessments from 7 U.S. IM residency programs (July 2014-June 2019) was conducted. Core competency scores (patient care [PC], medical knowledge [MK], practice-based learning and improvement [PBLI], systems-based practice [SBP], professionalism [PROF], and interpersonal and communication skills [ICS]) were standardized across programs. Cross-classified mixed-effects linear regression evaluated the relationship between gender and standardized competency scores within training programs, while adjusting for multiple variables including IM In Training Examination percentile rank., Results: Data included 9,346 evaluations by 1,011 faculty (552 [55%] men, 459 [45%] women) for 664 residents (358 [54%] men, 306 [46%] women). Initially, women residents' scores were significantly lower than men's in PC (estimated difference [standard error ] -0.097 [0.033], P = .004), MK (-0.145 [0.034], P < .001), and PBLI -0.090 [0.040], P = .022). PC, MK, PBLI, and SBP scores increased more over time for women residents than men (PC: 0.050 [0.015], P = .001; MK: 0.052 [0.015], P = .001; PBLI: 0.036 [0.018], P = .048; SBP: 0.036 [0.016], P = .027). PROF and ICS scores were comparable across gender. There was a significant interaction between faculty gender and postgraduate year (PGY) across all competencies but none between resident gender, faculty gender, and PGY, indicating that men and women faculty rated residents differently over time but were consistent in how they rated men and women residents., Conclusions: Gender-based assessment differences were variable across competencies and time. Women residents had lower scores initially but greater gains in "hard skill" (MK, PC, and PBLI) than in "soft skill" (ICS and PROF) competencies, suggesting assessment inequities. Efforts to ensure equitable assessment are needed., (Copyright © 2024 Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

Inflammation has an essential role in healing. However, over-active inflammation disrupts normal cellular functions and can be life-threatening when not resolved. The NLRP3 inflammasome, a component of the innate immune system, is an intracellular multiprotein complex that senses stress-associated signals, and, for this reason is a promising therapeutic target for treating unresolved, pathogenic inflammation. Alternative splicing of NLRP3 RNA has been suggested as a regulatory mechanism for inflammasome activation, as some spliced isoforms encode NLRP3 proteins with compromised function. Here, we take advantage of this natural regulatory mechanism and devise a way to control pathogenic inflammation using splice-switching antisense oligonucleotides (ASOs). To identify and induce NLRP3 spliced isoforms lacking inflammatory activity, we tested a series of ASOs, each targeting a different exon, to determine the most effective strategy for down-regulating NLRP3. We identify several ASOs that modulate NLRP3 splicing, reduce NLRP3 protein, and decrease inflammasome signaling in vitro . The most effective ASO suppresses systemic inflammation in vivo in mouse models of acute inflammation and cryopyrin-associated periodic syndrome (CAPS). Our results demonstrate a systematic approach to protein engineering using splice-switching ASOs to generate isoforms with altered activity, and identify an ASO that can treat pathological inflammation in mice by reducing functional NLRP3.