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Leaves are the most significant parts of forage crops such as alfalfa. Senescence is the terminal stage of leaf development and is controlled by an integrated myriad of endogenous signals and environmental stimuli. WRKY transcription factors (TFs) play essential roles in regulating leaf senescence; however, only a few studies on the analysis and identification of the WRKY TF family in Medicago Sativa have been reported. In this study, we identified 198 WRKY family members from the alfalfa (M. sativa L.) cultivar 'XinjiangDaye' using phylogenetic analysis and categorized them into three subfamilies, Groups I, II, and III, based on their structural characteristics. Group II members were further divided into five subclasses. In addition, several hormone- and stress-related cis-acting elements were identified in the promoter regions of MsWRKYs. Furthermore, 14 aging-related MsWRKYs genes from a previous transcriptome in our laboratory were selected for RT-qPCR validation of their expression patterns, and subsequently cloned for overexpression examination. Finally, MsWRKY5, MsWRKY66, MsWRKY92, and MsWRKY141 were confirmed to cause leaf yellowing in Nicotiana benthaminana using a transient expression system. Our findings lay a groundwork for further studies on the mechanism of M. sativa leaf aging and for the creation of new germplasm resources. [ABSTRACT FROM AUTHOR]

Leaves are a key forage part for livestock, and the aging of leaves affects forage biomass and quality. Preventing or delaying premature leaf senescence leads to an increase in pasture biomass accumulation and an improvement in alfalfa quality. NAC transcription factors have been reported to affect plant growth and abiotic stress responses. In this study, 48 NAC genes potentially associated with leaf senescence were identified in alfalfa under dark or salt stress conditions. A phylogenetic analysis divided MsNACs into six subgroups based on similar gene structure and conserved motif. These MsNACs were unevenly distributed in 26 alfalfa chromosomes. The results of the collinearity analysis show that all of the MsNACs were involved in gene duplication. Some cis-acting elements related to hormones and stress were screened in the 2-kb promoter regions of MsNACs. Nine of the MsNAC genes were subjected to qRT-PCR to quantify their expression and Agrobacterium-mediated transient expression to verify their functions. The results indicate that Ms.gene031485, Ms.gene032313, Ms.gene08494, and Ms.gene77666 might be key NAC genes involved in alfalfa leaf senescence. Our findings extend the understanding of the regulatory function of MsNACs in leaf senescence. [ABSTRACT FROM AUTHOR]

The abundance of distractors in the world poses a major challenge to our brain's limited processing capacity, but little is known about how selective attention modulates stimulus representations in the brain to reduce interference and support durable target memory. Here, we collected functional magnetic resonance imaging (fMRI) data in a selective attention task in which target and distractor pictures of different visual categories were simultaneously presented. Participants were asked to selectively process the target according to the effective cue, either before the encoding period (i.e., perceptual attention) or the maintenance period (i.e., reflective attention). On the next day, participants were asked to perform a memory recognition task in the scanner in which the targets, distractors, and novel items were presented in a pseudorandom order. Behavioral results showed that perceptual attention was better at enhancing target memory and reducing distractor memory than reflective attention, although the overall memory capacity (memory for both target and distractor) was comparable. Using multiple-voxel pattern analysis of the neural data, we found more robust target representation and weaker distractor representation in working memory for perceptual attention than for reflective attention. Interestingly, perceptual attention partially shifted the regions involved in maintaining the target representation from the visual cortex to the parietal cortex. Furthermore, the targets and distractors simultaneously presented in the perceptual attention condition showed reduced pattern similarity in the parietal cortex during retrieval compared to items not presented together. This neural pattern repulsion positively correlated with individuals' recognition of both targets and distractors. These results emphasize the critical role of selective attention in transforming memory representations to reduce interference and improve long-term memory performance. Selective attention helps humans to overcome our brain's limited processing capacity. This neuroimaging study shows how selective attention transforms memory representations to reduce interference and support long-term memory. [ABSTRACT FROM AUTHOR]

Contractors are the main implementers to achieve green construction, and the contractor's green construction capability (CGCC) is far-reaching for green construction. Research on CGCC exists in a number of disciplines, with major contributions in construction management, environment management, and sustainable management research. Despite the fact that CGCC is widely utilised in both research and practice, its formation and action mechanism remain obscure due to the multi-disciplinary nature of CGCC. This study is motivated by this research gap. This study conducted a comprehensive investigation of CGCC by using a systematic review covering 74 relevant publications published from 2005 to the first half of 2022. Five main research clusters were identified: (1) CGCC implementation; (2) CGCC performance; (3) CGCC profound impact; (4) CGCC and green building; and (5) CGCC and sustainability. Existing research collaborations on CGCC are infrequent, although this is an area of research that requires multi-disciplinary collaboration. Studies such as CGCC enhancement mechanisms and evaluation systems have received less attention. An integrative framework was proposed for future scholars to build upon as well as a guidance for executives. [ABSTRACT FROM AUTHOR]

Background: The COVID‐19 pandemic has highlighted the need for targeted local interventions given substantial heterogeneity within cities and counties. Publicly available case data are typically aggregated to the city or county level to protect patient privacy, but more granular data are necessary to identify and act upon community‐level risk factors that can change over time. Methods: Individual COVID‐19 case and mortality data from Massachusetts were geocoded to residential addresses and aggregated into two time periods: "Phase 1" (March–June 2020) and "Phase 2" (September 2020 to February 2021). Institutional cases associated with long‐term care facilities, prisons, or homeless shelters were identified using address data and modeled separately. Census tract sociodemographic and occupational predictors were drawn from the 2015–2019 American Community Survey. We used mixed‐effects negative binomial regression to estimate incidence rate ratios (IRRs), accounting for town‐level spatial autocorrelation. Results: Case incidence was elevated in census tracts with higher proportions of Black and Latinx residents, with larger associations in Phase 1 than Phase 2. Case incidence associated with proportion of essential workers was similarly elevated in both Phases. Mortality IRRs had differing patterns from case IRRs, decreasing less substantially between Phases for Black and Latinx populations and increasing between Phases for proportion of essential workers. Mortality models excluding institutional cases yielded stronger associations for age, race/ethnicity, and essential worker status. Conclusions: Geocoded home address data can allow for nuanced analyses of community disease patterns, identification of high‐risk subgroups, and exclusion of institutional cases to comprehensively reflect community risk. [ABSTRACT FROM AUTHOR]