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Catherine Teng,1 Unnikrishna Thampy,1 Ju Young Bae,1 Peng Cai,2 Richard AF Dixon,3 Qi Liu,3 Pengyang Li4 1Department of Medicine, Yale New Haven Health – Greenwich Hospital, Greenwich, CT, USA; 2Department of Mathematical Sciences, Worcester Polytechnic Institute, Worcester, MA, USA; 3Molecular Cardiology Research, Texas Heart Institute, Houston, TX, USA; 4Division of Cardiology, Pauley Heart Center, Virginia Commonwealth University, Richmond, VA, USACorrespondence: Pengyang LiPauley Heart Center, Virginia Commonwealth University, 1200 E Marshall St, Richmond, VA, 23219, USATel +1 626-420-5811Fax +1 508-363-9798Email leelpy0109@gmail.comQi LiuTexas Heart Institute, 6770 Bertner Avenue, MC 2-255, Houston, TX, 77030, USATel +1 832-355-8006Fax +1 832-355-9692Email QLiu@texasheart.orgBackground: Coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) is a heterogeneous disorder with a complex pathogenesis. Recent studies from Spain and France have indicated that underlying phenotypes may exist among patients admitted to the hospital with COVID-19. Whether those same phenotypes exist in the United States (US) remains unclear. Using latent class analysis (LCA), we sought to determine whether clinical phenotypes exist among patients admitted for COVID-19.Methods: We reviewed the charts of adult patients who were hospitalized primarily for COVID-19 at Greenwich Hospital and performed LCA using variables based on patient demographics and comorbidities. To further examine the reliability and replicability of the clustering results, we repeated LCA on the cohort of patients who died during hospitalization for COVID-19.Results: Two phenotypes were identified in patients admitted for COVID-19 (N = 483). According to phenotype, patients were designated as cluster 1 (C1) or cluster 2 (C2). C1 (n = 193) consisted of older individuals with more comorbidities and a higher mortality rate (25.4% vs 8.97%, p < 0.001) than patients in C2. C2 (n = 290) consisted of younger individuals who were more likely to be obese, male, and nonwhite, with higher levels of the inflammatory markers C-reactive protein and alanine aminotransferase. When we performed LCA on the cohort of patients who died during hospitalization for COVID-19 (n = 75), we found that the distribution of patient baseline characteristics and comorbidities was similar to that of the entire cohort of patients admitted for COVID-19.Conclusion: Using LCA, we identified two clinical phenotypes of patients who were admitted to our hospital for COVID-19. These findings may reflect different pathophysiologic processes that lead to moderate to severe COVID-19 and may be useful for identifying treatment targets and selecting patients with severe COVID-19 disease for future clinical trials.Keywords: COVID-19 (United States), hospitalization, death, phenotypes, latent class analysis, comorbidities

Con el objetivo de evaluar el efecto de la sustitución del ensilaje de maíz por pasto de corte (Pennisetum purpureum cultivar CT-22), en la producción de leche, en fincas doble propósito, durante la época seca; se realizó un ensayo en la Estación Experimental El Ejido, Los Santos, Panamá. Se utilizó un diseño cruzado (crossover), en bloque completo balanceado, con cuatro tratamientos con diferentes niveles de ensilaje de maíz y pasto de corte. No se encontraron diferencias significativas en la producción de leche y en el cambio de peso vivo entre tratamientos. Sin embargo, el costo de alimentación disminuyó a medida que se incrementó el nivel de pasto de corte en la ración. El análisis de presupuesto parcial mostró dominancia del tratamiento con mayor nivel de pasto de corte, con respecto a los demás tratamientos que incluían ensilaje de maíz, logrando un mayor beneficio neto con menor costo de alimentación. Se concluye que el uso de pasto de corte como única fuente de forraje en las raciones para la producción de leche en fincas doble propósito, en vacas con potenciales de producción de leche total de hasta 12 kg vaca-1 día-1, generó el mayor beneficio económico, en comparación a las raciones donde se incluyó ensilaje de maíz.

The latest evaluation of the World Health Organization (WHO) on the health situation in Africa recognizes that District Health Management Teams (DHMT) are not as efficient and effective at delivering primary healthcare as they could be. The 'weakness of information support is acknowledged by most member states as a persistent obstacle to vigorous and objective management'. A shift towards decentralization in many low-income countries has meant that more skills are demanded of primary healthcare (PHC) managers including data and information handling at all levels of the healthcare system. Ministries of Health (MOH) are changing from centralized reporting health information systems, to health management information systems (HMIS), with emphasis on managers utilizing information at the point of collection. The new information management strategies are intended to promote an informational approach to management at the district and operational health service level. Organizations that have an interest in training health service managers also recognize the need for more skills, and the Aga Khan Foundation (AKF) initiated the development of a training package for PHC managers known as the Primary Healthcare Management Advancement Programme (PHC MAP). [ABSTRACT FROM AUTHOR]

Abstract Background The metabolic capacity for nitrogen fixation is known to be present in several prokaryotic species scattered across taxonomic groups. Experimental detection of nitrogen fixation in microbes requires species-specific conditions, making it difficult to obtain a comprehensive census of this trait. The recent and rapid increase in the availability of microbial genome sequences affords novel opportunities to re-examine the occurrence and distribution of nitrogen fixation genes. The current practice for computational prediction of nitrogen fixation is to use the presence of the nifH and/or nifD genes. Results Based on a careful comparison of the repertoire of nitrogen fixation genes in known diazotroph species we propose a new criterion for computational prediction of nitrogen fixation: the presence of a minimum set of six genes coding for structural and biosynthetic components, namely NifHDK and NifENB. Using this criterion, we conducted a comprehensive search in fully sequenced genomes and identified 149 diazotrophic species, including 82 known diazotrophs and 67 species not known to fix nitrogen. The taxonomic distribution of nitrogen fixation in Archaea was limited to the Euryarchaeota phylum; within the Bacteria domain we predict that nitrogen fixation occurs in 13 different phyla. Of these, seven phyla had not hitherto been known to contain species capable of nitrogen fixation. Our analyses also identified protein sequences that are similar to nitrogenase in organisms that do not meet the minimum-gene-set criteria. The existence of nitrogenase-like proteins lacking conserved co-factor ligands in both diazotrophs and non-diazotrophs suggests their potential for performing other, as yet unidentified, metabolic functions. Conclusions Our predictions expand the known phylogenetic diversity of nitrogen fixation, and suggest that this trait may be much more common in nature than it is currently thought. The diverse phylogenetic distribution of nitrogenase-like proteins indicates potential new roles for anciently duplicated and divergent members of this group of enzymes.

Little is known about potential longitudinal relationships between participation in social, physical, and intellectual activities and later cognitive performance. Data from the Victoria Longitudinal Study (n = 530) were used to test whether baseline and change in lifestyle engagement were related to corresponding indicators of cognitive speed (measured by mean-level and intraindividual variability). Regressions based on random effects model estimates showed that cross-sectional activity participation predicted corresponding values of both mean-level and intraindividual variability, but few longitudinal relationships were significant. Overall, a higher frequency of participation in cognitively complex activities was related to faster response times and lower intraindividual variability. Findings suggest that activity level at one point in time may be a more important predictor of cognition than an individual's changes in activity level. [ABSTRACT FROM AUTHOR]

A previous investigation reported that cross-sectional age differences in Digit Symbol Substitution (DSS) test performance reflect declines in perceptual processing speed. Support for the tenability of the processing speed hypothesis requires examining whether longitudinal age-related change in DSS performance is largely mediated by changes in speed. The present study used data from the Victoria Longitudinal Study to examine patterns and predictors of longitudinal change in DSS for 512 older adults (M(age) = 68.37 years, SD = 7.43). On the basis of multilevel modeling, baseline DSS performance was poorer for older participants and men, with longitudinal declines more pronounced with increasing age and decreasing speed. In contrast to the present cross-sectional findings, statistical control of change trajectories in perceptual speed using the same data did not substantially attenuate age changes. These discrepancies suggest different sources of variance may underlie cross-sectional age differences and longitudinal age changes for DSS. [ABSTRACT FROM AUTHOR]

Research has shown that psychosocial and health characteristics may affect older adults' cognitive performance, self-referent beliefs, and general adaptive resilience. Are such characteristics related specifically to older adults' reported efforts to compensate for memory losses? The Memory Compensation Questionnaire (MCQ) measures 5 mechanisms of everyday memory compensation as well as 2 general aspects of compensatory motivation and awareness. Correlates were derived from indicators of specific health conditions, subjective health ratings, personality, well-being, and memory self-efficacy (MSE). All measures were administered to a cross-sectional sample of 528 healthy older adults between 55 and 94 years of age from the Victoria Longitudinal Study. Specific health composites (i.e., infirmities, respiratory illness), several personality dimensions (e.g., agreeableness, neuroticism), negative affect, and low MSE were associated with more frequent use of everyday memory compensation strategies. Linking healthy older adults' cognitive resilience with individual characteristics is an important contribution to emerging conceptions of adaptation and success in late life. [ABSTRACT FROM AUTHOR]

Recent research has documented associations between subjective health ratings and objective indicators of disease and death. Less is known about relations between subjective health ratings and level of cognitive performance in older adults. In this study, we explored whether subjective health ratings are related to episodic memory performance, both concurrently and across a three-year longitudinal interval. Persons aged 75-84 years, and participating in the Swedish Kungsholmen Project (n = 105) or the Canadian Victoria Longitudinal Study (n = 71), were examined. Results showed that in both samples, while the cross-sectional relationship was non-significant, longitudinal change in perceptions of subjective health were related to change in episodic memory performance. Next, the two samples were combined in additional analyses. Here, results further revealed that the associations between longitudinal change in subjective health and memory performance generalized across samples independently of demographic, changing physical health status, and subjective memory decline differences. Thus, the present findings suggest that subjective health may be added to the growing number of individual-difference variables that are predictive of episodic memory change in very old age. [ABSTRACT FROM AUTHOR]

Background: Bilateral oophorectomy (BO) confers immediate estradiol loss. We examined prevalence and predictors of Alzheimer's disease (AD) in women with early BO comparing their odds ratios of AD to those of women with spontaneous menopause (SM)., Methods: A cohort from UK Biobank (n = 34,603) included women aged 60 + at baseline with and without AD who had early BO or SM. AD was determined based on AD related ICD-10 or ICD-9 code. We used logistic regression to model the association of menopause type with AD. Model predictors included age, education, age at menopause, hormone therapy (HT), APOE4 , body mass index (BMI), cancer history, and smoking history., Results: Those with early BO had four times the odds of developing AD (OR = 4.12, 95% CI [2.02, 8.44]) compared to those with SM. APOE4 (OR = 4.29, 95% CI [2.43, 7.56]), and older age (OR = 1.16, 95% CI [1.05, 1.28]) were associated with increased odds of AD in the BO group. Greater years of education were associated with reduced odds of AD for both BO (OR = 0.91, 95% CI [0.85, 0.98]), and SM (OR = 0.95, 95% CI [0.90, 0.99]), while ever use of HT was associated with decreased odds of AD only for the BO group (OR = 0.43, 95% CI [0.23, 0.82])., Conclusions: Women with early BO, particularly with an APOE4 allele, are at high risk of AD. Women with early BO who use HT and those with increased education have lower odds of developing AD.

Despite lignin having long been viewed as an impediment to the processing of biomass for the production of paper, biofuels, and high-value chemicals, the valorization of lignin to fuels, chemicals, and materials is now clearly recognized as a critical element for the lignocellulosic bioeconomy. However, the intended application for lignin will likely require a preferred lignin composition and form. To that end, effective lignin valorization will require the integration of plant biology, providing optimal feedstocks, with chemical process engineering, providing efficient lignin transformations. Recent advances in our understanding of lignin biosynthesis have shown that lignin structure is extremely diverse and potentially tunable, while simultaneous developments in lignin refining have resulted in the development of several processes that are more agnostic to lignin composition. Here, we review the interface between in planta lignin design and lignin processing and discuss the advances necessary for lignin valorization to become a feature of advanced biorefining.

Glutathione S-transferases (GSTs) constitute a protein superfamily encoded by a large gene family and play a crucial role in plant growth and development. However, their precise functions in wood plant responses to abiotic stress are not fully understood. In this study, we isolated a Phi class glutathione S-transferase-encoding gene, PtrGSTF8, from poplar (Populus alba × P. glandulosa), which is significantly up-regulated under salt stress. Moreover, compared with wild-type (WT) plants, transgenic tobacco plants exhibited significant salt stress tolerance. Under salt stress, PtrGSTF8-overexpressing tobacco plants showed a significant increase in plant height and root length, and less accumulation of reactive oxygen species. In addition, these transgenic tobacco plants exhibited higher superoxide dismutase, peroxidase, and catalase activities and reduced malondialdehyde content compared with WT plants. Quantitative real-time PCR experiments showed that the overexpression of PtrGSTF8 increased the expression of numerous genes related to salt stress. Furthermore, PtrMYB108, a MYB transcription factor involved in salt resistance in poplar, was found to directly activate the promoter of PtrGSTF8, as demonstrated by yeast one-hybrid assays and luciferase complementation assays. Taken together, these findings suggest that poplar PtrGSTF8 contributes to enhanced salt tolerance and confers multiple growth advantages when overexpressed in tobacco., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

Mythology is replete with good and evil shapeshifters, who, by definition, display great adaptability and assume many different forms-with several even turning themselves into trees. Cell walls certainly fit this definition as they can undergo subtle or dramatic changes in structure, assume many shapes, and perform many functions. In this review, we cover the evolution of knowledge of the structures, biosynthesis, and functions of the 5 major cell wall polymer types that range from deceptively simple to fiendishly complex. Along the way, we recognize some of the colorful historical figures who shaped cell wall research over the past 100 years. The shapeshifter analogy emerges more clearly as we examine the evolving proposals for how cell walls are constructed to allow growth while remaining strong, the complex signaling involved in maintaining cell wall integrity and defense against disease, and the ways cell walls adapt as they progress from birth, through growth to maturation, and in the end, often function long after cell death. We predict the next century of progress will include deciphering cell type-specific wall polymers; regulation at all levels of polymer production, crosslinks, and architecture; and how walls respond to developmental and environmental signals to drive plant success in diverse environments., Competing Interests: Conflict of interest statement. None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists.)

Over the past century, early advances in understanding the identity of the chemicals that collectively form a living plant have led scientists to deeper investigations exploring where these molecules localize, how they are made, and why they are synthesized in the first place. Many small molecules are specific to the plant kingdom and have been termed plant secondary metabolites, despite the fact that they can play primary and essential roles in plant structure, development, and response to the environment. The past 100 yr have witnessed elucidation of the structure, function, localization, and biosynthesis of selected plant secondary metabolites. Nevertheless, many mysteries remain about the vast diversity of chemicals produced by plants and their roles in plant biology. From early work characterizing unpurified plant extracts, to modern integration of 'omics technology to discover genes in metabolite biosynthesis and perception, research in plant (bio)chemistry has produced knowledge with substantial benefits for society, including human medicine and agricultural biotechnology. Here, we review the history of this work and offer suggestions for future areas of exploration. We also highlight some of the recently developed technologies that are leading to ongoing research advances., Competing Interests: Conflict of interest statement. None declared., (© The Author(s) 2024. Published by Oxford University Press on behalf of American Society of Plant Biologists.)

Background: Apathy and depression are common neuropsychiatric symptoms across neurodegenerative disorders and are associated with impairment in several cognitive domains, yet little is known about the influence of sex on these relationships., Objectives: We examined the relationship between these symptoms with neuropsychological performance across a combined cohort with mild or major neurodegenerative disorders, then evaluated the impact of sex., Design, Setting and Participants: We conducted a cohort analysis of participants in the COMPASS-ND study with mild cognitive impairment (MCI), vascular MCI, Alzheimer's disease, mixed dementia, Parkinson's disease, frontotemporal dementia, and cognitively unimpaired (CU) controls., Measurements: Participants with neurodegenerative disease and CU controls were stratified by the presence (severity ≥1 on Neuropsychiatric Inventory Questionnaire) of either depressive symptoms alone, apathy symptoms alone, both symptoms, or neither. A neuropsychological battery evaluated executive function, verbal fluency, verbal learning, working memory, and visuospatial reasoning. Analysis of covariance was used to assess group differences with age, sex, and education as covariates., Results: Groups included depressive symptoms only (n = 70), apathy symptoms only (n = 52), both (n = 68), or neither (n = 262). The apathy and depression + apathy groups performed worse than the neither group on tests of working memory (t (312)  = -2.4, p = 0.02 and t (328)  = -3.8, p = 0.001, respectively) and visuospatial reasoning (t (301)  = -2.3, p = 0.02 and t (321)  = -2.6, p = 0.01, respectively). The depression, apathy, and depression + apathy groups demonstrated a similar degree of impairment on tests of executive function, processing speed, verbal fluency, and verbal learning when compared to participants without apathy or depression. Sex-stratified analyses revealed that compared to the male neither group, the male apathy and depression + apathy groups were impaired broadly across all cognitive domains except for working memory. Females with depression alone showed deficits on tests of executive function (t (166)  = 2.4, p = 0.01) and verbal learning (t (167)  = -4.3, p = 0.001) compared to the female neither group., Conclusions: This study demonstrated that in neurodegenerative diseases, apathy with or without depression in males was associated with broad cognitive impairments. In females, depression was associated with deficits in executive function and verbal learning. These findings highlight the importance of effectively treating apathy and depression across the spectrum of neurodegenerative disorders with the goal of optimizing neuropsychological outcomes., (© 2024 The Authors. International Journal of Geriatric Psychiatry published by John Wiley & Sons Ltd.)

Introduction: We investigated whether novel plasma biomarkers are associated with cognition, cognitive decline, and functional independence in activities of daily living across and within neurodegenerative diseases., Methods: Glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), phosphorylated tau (p-tau)181 and amyloid beta (Aβ) 42/40 were measured using ultra-sensitive Simoa immunoassays in 44 healthy controls and 480 participants diagnosed with Alzheimer's disease/mild cognitive impairment (AD/MCI), Parkinson's disease (PD), frontotemporal dementia (FTD) spectrum disorders, or cerebrovascular disease (CVD)., Results: GFAP, NfL, and/or p-tau181 were elevated among all diseases compared to controls, and were broadly associated with worse baseline cognitive performance, greater cognitive decline, and/or lower functional independence. While GFAP, NfL, and p-tau181 were highly predictive across diseases, p-tau181 was more specific to the AD/MCI cohort. Sparse associations were found in the FTD and CVD cohorts and for Aβ 42/40 ., Discussion: GFAP, NfL, and p-tau181 are valuable predictors of cognition and function across common neurodegenerative diseases, and may be useful in specialized clinics and clinical trials., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Background: Alzheimer's disease (AD) and Lewy body disease (LBD) are characterized by early and gradual worsening perturbations in speeded cognitive responses., Objective: Using simple and choice reaction time tasks, we compared two indicators of cognitive speed within and across the AD and LBD spectra: mean rate (average reaction time across trials) and inconsistency (within person variability)., Methods: The AD spectrum cohorts included subjective cognitive impairment (SCI, n = 28), mild cognitive impairment (MCI, n = 121), and AD (n = 45) participants. The LBD spectrum included Parkinson's disease (PD, n = 32), mild cognitive impairment in PD (PD-MCI, n = 21), and LBD (n = 18) participants. A cognitively unimpaired (CU, n = 39) cohort served as common benchmark. We conducted multivariate analyses of variance and discrimination analyses., Results: Within the AD spectrum, the AD cohort was slower and more inconsistent than the CU, SCI, and MCI cohorts. The MCI cohort was slower than the CU cohort. Within the LBD spectrum, the LBD cohort was slower and more inconsistent than the CU, PD, and PD-MCI cohorts. The PD-MCI cohort was slower than the CU and PD cohorts. In cross-spectra (corresponding cohort) comparisons, the LBD cohort was slower and more inconsistent than the AD cohort. The PD-MCI cohort was slower than the MCI cohort. Discrimination analyses clarified the group difference patterns., Conclusions: For both speed tasks, mean rate and inconsistency demonstrated similar sensitivity to spectra-related comparisons. Both dementia cohorts were slower and more inconsistent than each of their respective non-dementia cohorts.

Recent research aimed at the discovery, integration, and communication of health outcome measures (or "biomarkers") in Alzheimer's disease has raised challenging questions related to whether, how and when results from these investigations should be disclosed to research participants. Reflecting the apparent heterogeneity of many neurodegenerative diseases, biomarker or other risk factor results are often probabilistic, interactive, multi-modal, and selective. Such characteristics make it very complex to summarize and communicate to clinicians, researchers, and research participants. Whereas the format and content of academic literature is well-managed by the peer-review process, reporting individualized results to participants involves complex, sensitive, and ethical considerations. This paper describes three key factors to consider in decisions about the return of results to research participants: complexity, precision, and responsibility. The paper also presents six practical recommendations for implementing meaningful and ethical communication with research participants.

Background: Older adults presenting with dual-decline in cognition and walking speed face a 6-fold higher risk for dementia compared with those showing no decline. We hypothesized that the metabolomics profile of dual-decliners would be unique even before they show signs of decline in cognition and gait speed., Objective: The objective of this study was to determine if plasma metabolomics signatures can discriminate dual-decliners from no decliners, purely cognitive decliners, and purely motor decliners prior to decline., Methods: A retrospective cross-sectional study using baseline plasma for untargeted metabolomics analyses to investigate early signals of later dual-decline status in study participants (n = 76) with convenient sampling. Dual-decline was operationalized as decline in gait speed (>10 cm/s) and cognition (>2 points decline in Montreal Cognitive Assessment score) on at least two consecutive 6-monthly assessments. The participants' decliner status was evaluated 3 years after the blood sample was collected. Pair-wise comparison of detected compounds was completed using principal components and hierarchical clustering analyses., Results: Analyses did not detect any cluster separation in untargeted metabolomes across baseline groups. However, follow-up analyses of specific molecules detected 4 compounds (17-Hydroxy-12-(hydroxymethyl)-10-oxo-8 oxapentacyclomethyl hexopyranoside, Fleroxacin, Oleic acid, and 5xi-11,12-Dihydroxyabieta-8(14),9(11),12-trien-20-oic acid) were at significantly higher concentration among the dual-decliners compared to non-decliners. The pure cognitive decliner group had significantly lower concentration of six compounds (1,3-nonanediol acetate, 4-(2-carboxyethyl)-2-methoxyphenyl beta-D-glucopyranosiduronic acid, oleic acid, 2E-3-[4-(sulfo-oxy)phenyl] acrylic acid, palmitelaidic acid, and myristoleic acid) compared to the non-decliner group., Conclusions: The unique metabolomics profile of dual-decliners warrants follow-up metabolomics analysis. Results may point to modifiable pathways.

Background: Frailty indicators can operate in dynamic amalgamations of disease conditions, clinical symptoms, biomarkers, medical signals, cognitive characteristics, and even health beliefs and practices. This study is the first to evaluate which, among these multiple frailty-related indicators, are important and differential predictors of clinical cohorts that represent progression along an Alzheimer's disease (AD) spectrum. We applied machine-learning technology to such indicators in order to identify the leading predictors of three AD spectrum cohorts; viz., subjective cognitive impairment (SCI), mild cognitive impairment (MCI), and AD. The common benchmark was a cohort of cognitively unimpaired (CU) older adults., Methods: The four cohorts were from the cross-sectional Comprehensive Assessment of Neurodegeneration and Dementia dataset. We used random forest analysis (Python 3.7) to simultaneously test the relative importance of 83 multi-modal frailty indicators in discriminating the cohorts. We performed an explainable artificial intelligence method (Tree Shapley Additive exPlanation values) for deep interpretation of prediction effects., Results: We observed strong concurrent prediction results, with clusters varying across cohorts. The SCI model demonstrated excellent prediction accuracy (AUC = 0.89). Three leading predictors were poorer quality of life ([QoL]; memory), abnormal lymphocyte count, and abnormal neutrophil count. The MCI model demonstrated a similarly high AUC (0.88). Five leading predictors were poorer QoL (memory, leisure), male sex, abnormal lymphocyte count, and poorer self-rated eyesight. The AD model demonstrated outstanding prediction accuracy (AUC = 0.98). Ten leading predictors were poorer QoL (memory), reduced olfaction, male sex, increased dependence in activities of daily living (n = 6), and poorer visual contrast., Conclusions: Both convergent and cohort-specific frailty factors discriminated the AD spectrum cohorts. Convergence was observed as all cohorts were marked by lower quality of life (memory), supporting recent research and clinical attention to subjective experiences of memory aging and their potentially broad ramifications. Diversity was displayed in that, of the 14 leading predictors extracted across models, 11 were selectively sensitive to one cohort. A morbidity intensity trend was indicated by an increasing number and diversity of predictors corresponding to clinical severity, especially in AD. Knowledge of differential deficit predictors across AD clinical cohorts may promote precision interventions., (© 2023. The Author(s).)

The focus of this review was to assess what evidence exists on whether, and to what extent, the use of biocides (disinfectants and sanitizers) and certain metals (used in feed and other uses) in animal production (both land and aquatic) leads to the development and spread of AMR within the food chain. A comprehensive literature search identified 3434 publications, which after screening were reduced to 154 relevant publications from which some data were extracted to address the focus of the review. The review has shown that there is some evidence that biocides and metals used in food animal production may have an impact on the development of AMR. There is clear evidence that metals used in food animal production will persist, accumulate, and may impact on the development of AMR in primary animal and food production environments for many years. There is less evidence on the persistence and impact of biocides. There is also particularly little, if any, data on the impact of biocides/metal use in aquaculture on AMR. Although it is recognized that AMR from food animal production is a risk to human health there is not sufficient evidence to undertake an assessment of the impact of biocide or metal use on this risk and further focused in-field studies are needed provide the evidence required.

Proanthocyanidins (PAs), flavonoid polymers involved in plant defense, are also beneficial to human health and ruminant nutrition. To date, there is little evidence for accumulation of PAs in maize (Zea mays), although maize makes anthocyanins and possesses the key enzyme of the PA pathway, anthocyanidin reductase (ANR). Here, we explore whether there is a functional PA biosynthesis pathway in maize using a combination of analytical chemistry and genetic approaches. The endogenous PA biosynthetic machinery in maize preferentially produces the unusual PA precursor (+)-epicatechin, as well as 4β-(S-cysteinyl)-catechin, as potential PA starter and extension units. Uncommon procyanidin dimers with (+)-epicatechin as starter unit are also found. Expression of soybean (Glycine max) anthocyanidin reductase 1 (ANR1) in maize seeds increases the levels of 4β-(S-cysteinyl)-epicatechin and procyanidin dimers mainly using (-)-epicatechin as starter units. Introducing a Sorghum bicolor transcription factor (SbTT2) specifically regulating PA biosynthesis into a maize inbred deficient in anthocyanin biosynthesis activates both anthocyanin and PA biosynthesis pathways, suggesting conservation of the PA regulatory machinery across species. Our data support the divergence of PA biosynthesis across plant species and offer perspectives for future agricultrural applications in maize., (© 2023. The Author(s).)

The conversion of lignocellulosic feedstocks to fermentable sugar for biofuel production is inefficient, and most strategies to enhance efficiency directly target lignin biosynthesis, with associated negative growth impacts. Here we demonstrate, for both laboratory- and field-grown plants, that expression of Pag-miR408 in poplar (Populus alba × P. glandulosa) significantly enhances saccharification, with no requirement for acid-pretreatment, while promoting plant growth. The overexpression plants show increased accessibility of cell walls to cellulase and scaffoldin cellulose-binding modules. Conversely, Pag-miR408 loss-of-function poplar shows decreased cell wall accessibility. Overexpression of Pag-miR408 targets three Pag-LACCASES, delays lignification, and modestly reduces lignin content, S/G ratio and degree of lignin polymerization. Meanwhile, the LACCASE loss of function mutants exhibit significantly increased growth and cell wall accessibility in xylem. Our study shows how Pag-miR408 regulates lignification and secondary growth, and suggest an effective approach towards enhancing biomass yield and saccharification efficiency in a major bioenergy crop., (© 2023. The Author(s).)

Background: Persons with Parkinson's disease (PD) differentially progress to cognitive impairment and dementia. With a 3-year longitudinal sample of initially non-demented PD patients measured on multiple dementia risk factors, we demonstrate that machine learning classifier algorithms can be combined with explainable artificial intelligence methods to identify and interpret leading predictors that discriminate those who later converted to dementia from those who did not., Method: Participants were 48 well-characterized PD patients ( M baseline age = 71.6; SD = 4.8; 44% female). We tested 38 multi-modal predictors from 10 domains (e.g., motor, cognitive) in a computationally competitive context to identify those that best discriminated two unobserved baseline groups, PD No Dementia (PDND), and PD Incipient Dementia (PDID). We used Random Forest (RF) classifier models for the discrimination goal and Tree SHapley Additive exPlanation (Tree SHAP) values for deep interpretation., Results: An excellent RF model discriminated baseline PDID from PDND ( AUC = 0.84; normalized Matthews Correlation Coefficient = 0.76). Tree SHAP showed that ten leading predictors of PDID accounted for 62.5% of the model, as well as their relative importance, direction, and magnitude (risk threshold). These predictors represented the motor (e.g., poorer gait), cognitive (e.g., slower Trail A), molecular (up-regulated metabolite panel), demographic (age), imaging (ventricular volume), and lifestyle (activities of daily living) domains., Conclusion: Our data-driven protocol integrated RF classifier models and Tree SHAP applications to selectively identify and interpret early dementia risk factors in a well-characterized sample of initially non-demented persons with PD. Results indicate that leading dementia predictors derive from multiple complementary risk domains., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 McFall, Bohn, Gee, Drouin, Fah, Han, Li, Camicioli and Dixon.)

Background: C-lignin is a homopolymer of caffeyl alcohol present in the seed coats of a variety of plant species including vanilla orchid, various cacti, and the ornamental plant Cleome hassleriana. Because of its unique chemical and physical properties, there is considerable interest in engineering C-lignin into the cell walls of bioenergy crops as a high-value co-product of bioprocessing. We have used information from a transcriptomic analysis of developing C. hassleriana seed coats to suggest strategies for engineering C-lignin in a heterologous system, using hairy roots of the model legume Medicago truncatula., Results: We systematically tested strategies for C-lignin engineering using a combination of gene overexpression and RNAi-mediated knockdown in the caffeic acid/5-hydroxy coniferaldehyde 3/5-O-methyltransferase (comt) mutant background, monitoring the outcomes by analysis of lignin composition and profiling of monolignol pathway metabolites. In all cases, C-lignin accumulation required strong down-regulation of caffeoyl CoA 3-O-methyltransferase (CCoAOMT) paired with loss of function of COMT. Overexpression of the Selaginella moellendorffii ferulate 5-hydroxylase (SmF5H) gene in comt mutant hairy roots resulted in lines that unexpectedly accumulated high levels of S-lignin., Conclusion: C-Lignin accumulation of up to 15% of total lignin in lines with the greatest reduction in CCoAOMT expression required the strong down-regulation of both COMT and CCoAOMT, but did not require expression of a heterologous laccase, cinnamyl alcohol dehydrogenase (CAD) or cinnamoyl CoA reductase (CCR) with preference for 3,4-dihydroxy-substituted substrates in M. truncatula hairy roots. Cell wall fractionation studies suggested that the engineered C-units are not present in a heteropolymer with the bulk of the G-lignin., (© 2023. The Author(s).)

Although APOE ɛ4 has been identified as the strongest genetic risk factor for Alzheimer's Disease, there are some APOE ɛ4 carriers who do not go on to develop Alzheimer's disease or cognitive impairment. This study aims to investigate factors contributing to this "resilience" separately by gender. Data were drawn from APOE ɛ4 positive participants who were aged 60 + at baseline in the Personality and Total Health Through Life (PATH) Study (N = 341, Women = 46.3%). Participants were categorised into "resilient" and "non-resilient" groups using Latent Class Analysis based on their cognitive impairment status and cognitive trajectory across 12 years. Logistic regression was used to identify the risk and protective factors that contributed to resilience stratified by gender. For APOE ɛ4 carriers who have not had a stroke, predictors of resilience were increased frequency of mild physical activity and being employed at baseline for men, and increased number of mental activities engaged in at baseline for women. The results provide insights into a novel way of classifying resilience among APOE ɛ4 carriers and risk and protective factors contributing to resilience separately for men and women., (© 2023. The Author(s).)

Proanthocyanidins (PAs) are natural flavan-3-ol polymers that contribute protection to plants under biotic and abiotic stress, benefits to human health, and bitterness and astringency to food products. They are also potential targets for carbon sequestration for climate mitigation. In recent years, from model species to commercial crops, research has moved closer to elucidating the flux control and channeling, subunit biosynthesis and polymerization, transport mechanisms, and regulatory networks involved in plant PA metabolism. This review extends the conventional understanding with recent findings that provide new insights to address lingering questions and focus strategies for manipulating PA traits in plants., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Altering the content or composition of the cell wall polymer lignin is a favored approach to valorize lignin toward biomaterial and chemical production in the biorefinery. However, modifying lignin or cellulose in transgenic plants can induce expression of defense responses and negatively affect growth. Through genetic screening for suppressors of defense gene induction in the low lignin ccr1-3 mutant of Arabidopsis thaliana , we found that loss of function of the receptor-like kinase FERONIA, although not restoring growth, affected cell wall remodeling and blocked release of elicitor-active pectic polysaccharides as a result of the ccr1-3 mutation. Loss of function of multiple wall-associated kinases prevented perception of these elicitors. The elicitors are likely heterogeneous, with tri-galacturonic acid the smallest but not necessarily the most active component. Engineering of plant cell walls will require development of ways to bypass endogenous pectin signaling pathways.