High-resolution crystal structures of transient intermediates in the phytochrome photocycle

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Apoptosis signal-regulating kinase-1 aggravates ROS-mediated striatal degeneration in 3-nitropropionic acid-infused mice

Apoptosis signal-regulating kinase-1 (ASK1), an early signaling element in the cell death pathway, has been suggested to participate in the pathology of neurodegenerative diseases, which may be associated with environmental factors that impact the diseases. Although it is not entirely elucidated, 3-nitropropionic acid (3-NP) provokes mitochondrial dysfunction and selectively forms striatal lesions similar to those found in Huntington’s disease. The current study investigated whether ASK1 is involved in striatal pathology following chronic systemic infusion of 3-NP. The results show that ASK1 acts as a primary mediator of there active oxygen species (ROS) cell death signal cascade in the 3-NP-damaged striatal region by disrupting the positive feedback cycle. In 3-NP-infused striatal lesions, ROS increased ASK1. Superoxide dismutase transgenic (SOD-tg) mice reduced ASK1by scavenging ROS, and reduction of ASK1leads to a reduction in cell death. However, ASK1 down-regulation in 3-NP infusion mice also decreased striatal cell death without scavenging ROS. In contrast decreasing cell death by si-ASK1 treatment along with 3-NP in both SOD tg and wild-type mice (wt), cell death rebounded when ASK1 peptide was added to SOD tg mice. The present study suggests that ROS-inducing ASK1 may be an important step in the pathogenesis of 3-NP infused striatal lesions in murine brains.     

G-CSF Prevents Progression of Diabetic Nephropathy in Rat

Background

The protective effects of granulocyte colony-stimulating factor (G-CSF) have been demonstrated in a variety of renal disease models. However, the influence of G-CSF on diabetic nephropathy (DN) remains to be examined. In this study, we investigated the effect of G-CSF on DN and its possible mechanisms in a rat model.

Methods

Otsuka Long-Evans Tokushima Fatty (OLETF) rats with early DN were administered G-CSF or saline intraperitoneally. Urine albumin creatinine ratio (UACR), creatinine clearance, mesangial matrix expansion, glomerular basement membrane (GBM) thickness, and podocyte foot process width (FPW) were measured. The levels of interleukin (IL)-1β, transforming growth factor (TGF)-β1, and type IV collagen genes expression in kidney tissue were also evaluated. To elucidate the mechanisms underlying G-CSF effects, we also assessed the expression of G-CSF receptor (G-CSFR) in glomeruli as well as mobilization of bone marrow (BM) cells to glomeruli using sex-mismatched BM transplantation.

Results

After four weeks of treatment, UACR was lower in the G-CSF treatment group than in the saline group (p<0.05), as were mesangial matrix expansion, GBM thickness, and FPW (p<0.05). In addition, the expression of TGF-β1 and type IV collagen and IL-1β levels was lower in the G-CSF treatment group (p<0.05). G-CSFR was not present in glomerular cells, and G-CSF treatment increased the number of BM-derived cells in glomeruli (p<0.05).

Conclusions

G-CSF can prevent the progression of DN in OLETF rats and its effects may be due to mobilization of BM cells rather than being a direct effect.     

Genetic variation,demographic history and phylogeography of tire track eel,Mastacembelus favus (Synbranchiformes: Mastacembelidae) in Southeast Asia

The complex climatic and geological history of Southeast Asia has been hypothesised to determine the most important aspects of the current phylogeographical structure and distribution of living organisms throughout the region. To test existing hypotheses, the genetic structure of the tire track eel, Mastacembelus favus, was investigated using 823 bp of mitochondrial DNA cytochrome b from 469 individuals from 51 localities encompassing its native range. The results classified all haplotypes into two major lineages, Lineage 1, which was further divided into Lineages 1a (lower Mekong, eastern Gulf of Thailand and Malay—Thai Peninsula), 1b (Banpakong River), 1c (Chao Phraya, Gulf of Thailand and Malay—Thai Peninsula) and 1d (Khlang Yai River), and Lineage 2, the upper reaches of the lower Mekong and the middle Mekong. Strong genetic discontinuities dated approximately 5 MYA were discovered in the Mekong with limited geographical overlap, suggesting a historically dissected drainage between two sections and species colonisation via different routes. The widespread Lineage 1 showed a strong signature of population expansion during the Pleistocene climate oscillation. Haplotype characteristics in the Malay—Thai Peninsula are hypothesised to result from postglacial dispersal from the Mekong and Chao Phraya through an extended Pleistocene drainage network.

     

Clinical Features and Mortality of COVID-19-Associated Mucormycosis: A Systematic Review and Meta-Analysis

The recent increase of COVID-19-associated mucormycosis (CAM) has been commanding global attention. However, basic epidemiologic characteristics have not firmly been established. In this systematic review and meta-analysis, we sought to determine the clinical manifestations, potential risk factors, and outcomes of CAM. Observational studies reporting CAM were searched with PubMed and EMBASE databases in January 2022. We collected data on comorbidities and treatment for COVID-19, and performed a one-group meta-analysis on the frequency of orbital exenteration procedure and mortality of CAM using a random-effect model. Fifty-one observational studies, including a total of 2,312 patients with proven CAM, were identified. Among the 51 studies, 37 were conducted in India, 8 in Egypt, and 6 in other countries. The most common comorbidity was diabetes mellitus (82%). While 57% required oxygenation, 77% received systemic corticosteroids. Among CAM, 97% were rhino-orbital-cerebral (ROCM), and 2.7% were pulmonary mucormycosis. Usual presentations were headache (54%), periorbital swelling/pain (53%), facial swelling/pain (43%), ophthalmoplegia (42%), proptosis (41%), and nasal discharge/congestion (36%). Regarding the outcomes, orbital exenteration was performed in 17% (95% CI: 12–21%, I²?=?83%) of the COVID-19-associated ROCM patients. The mortality of CAM was 29% (95% CI; 22–36%, I²?=?92%). In conclusion, this systematic review and meta-analysis indicated that the most prevalent type of CAM was ROCM, and most CAM patients had diabetes mellitus and received systemic glucocorticoids. Clinicians in the endemic areas should have a high index of suspicion for this invasive fungal complication of COVID-19 when a diabetic patient who received high-dose systemic glucocorticoids developed rhino-orbital symptoms.

     

Genome-Wide Association of Carbon and Nitrogen Metabolism in the Maize Nested Association Mapping Population

Carbon (C) and nitrogen (N) metabolism are critical to plant growth and development and are at the basis of crop yield and adaptation. We performed high-throughput metabolite analyses on over 12,000 samples from the nested association mapping population to identify genetic variation in C and N metabolism in maize (Zea mays ssp. mays). All samples were grown in the same field and used to identify natural variation controlling the levels of 12 key C and N metabolites, namely chlorophyll a, chlorophyll b, fructose, fumarate, glucose, glutamate, malate, nitrate, starch, sucrose, total amino acids, and total protein, along with the first two principal components derived from them. Our genome-wide association results frequently identified hits with single-gene resolution. In addition to expected genes such as invertases, natural variation was identified in key C₄ metabolism genes, including carbonic anhydrases and a malate transporter. Unlike several prior maize studies, extensive pleiotropy was found for C and N metabolites. This integration of field-derived metabolite data with powerful mapping and genomics resources allows for the dissection of key metabolic pathways, providing avenues for future genetic improvement.Carbon (C) and nitrogen (N) metabolism are the basis for life on Earth. The production, balance, and tradeoffs of C and N metabolism are critical to all plant growth, yield, and local adaptation (Coruzzi and Bush, 2001; Coruzzi et al., 2007). In plants, there is a critical balance between the tissues that are producing energy (sources) and those using it (sinks), as the identities and locations of these vary through time and developmental stage (Smith et al., 2004). While a great deal of research has focused on the key genes and proteins involved in these processes (Wang et al., 1993; Kim et al., 2000; Takahashi et al., 2009), relatively little is known about the natural variation within a species that fine-tunes these processes in individual plants.In addition, a key aspect of core C metabolism involves the nature of plant photosynthesis. While the majority of plants use standard C₃ photosynthetic pathways, some, including maize (Zea mays) and many other grasses, use C₄ photosynthesis to concentrate CO₂ in bundle sheath cells to avoid wasteful photorespiration (Sage, 2004). Under some conditions (such as drought or high temperatures), C₄ photosynthesis is much more efficient than C₃ photosynthesis. Since these conditions are expected to become more prevalent in the near future due to climate change, various research groups are working to convert C₃ crop species to C₄ metabolism in order to boost crop production and food security (Sage and Zhu, 2011). Beyond this, better understanding of both C₃ and C₄ metabolic pathways will aid efforts to breed crops for superior yield, N-use efficiency, and other traits important for global food production.In the last two decades, quantitative trait locus (QTL) mapping, first with linkage analysis and later with association mapping, has been used to dissect C and N metabolism in several species, including Arabidopsis (Arabidopsis thaliana; Mitchell-Olds and Pedersen, 1998; Keurentjes et al., 2008; Lisec et al., 2008; Sulpice et al., 2009), tomato (Solanum lycopersicum; Schauer et al., 2006), and maize (Hirel et al., 2001; Limami et al., 2002; Zhang et al., 2006, 2010a, 2010b). These studies identified key genetic regions underlying variation in core C and N metabolism, many of which include candidate genes known to be involved in these processes.Previous studies of genetic variation for C and N metabolism are limited by the fact that they identified trait loci only through linkage mapping in artificial families or through association mapping across populations of unrelated individuals. Linkage mapping benefits from high statistical power due to many individuals sharing the same genotype at any given location, but it suffers from low resolution due to the limited number of generations (and hence recombination events) since the initial founders. Association mapping, in turn, enjoys high resolution due to the long recombination histories of natural populations but suffers from low power, since most genotypes occur in only a few individuals. In addition, many of these studies focused on C and N in artificial settings (e.g. greenhouses or growth chambers) instead of field conditions, running the risk that important genetic loci could be missed if the conditions do not include important (and potentially unknown) natural environmental variables.To address these issues and improve our understanding of C and N metabolism in maize, we used a massive and diverse germplasm resource, the maize nested association mapping (NAM) population (Buckler et al., 2009; McMullen et al., 2009), to evaluate genetic variation underlying the accumulation of 12 targeted metabolites in maize leaf tissue under field conditions. This population was formed by mating 25 diverse maize lines to the reference line, B73, and creating a 200-member biparental family from each of these crosses. The entire 5,000-member NAM population thus combines the strengths of both linkage and association mapping (McMullen et al., 2009), and it has been used to identify QTLs for important traits such as flowering time (Buckler et al., 2009), disease resistance (Kump et al., 2011; Poland et al., 2011), and plant architecture (Tian et al., 2011; Peiffer et al., 2013). Most importantly, this combination of power and resolution frequently resolves associations down to the single-gene level, even when using field-based data.The metabolites we profiled are key indicators of photosynthesis, respiration, glycolysis, and protein and sugar metabolism in the plant (Sulpice et al., 2009). By taking advantage of a robotized metabolic phenotyping platform (Gibon et al., 2004), we performed more than 100,000 assays across 12,000 samples, with two independent samples per experimental plot. Raw data and the best linear unbiased predictors (BLUPs) of these data were included as part of a study of general functional variation in maize (Wallace et al., 2014), but, to our knowledge, this is the first in-depth analysis of these metabolic data. We find strong correlations among several of the metabolites, and we also find extensive pleiotropy among the different traits. Many of the top QTLs are also near or within candidate genes relating to C and N metabolism, thus identifying targets for future breeding and selection. These results provide a powerful resource for those working with core C and N metabolism in plants and for improving maize performance in particular.     

Loss Mechanisms in Thick‐Film Low‐Bandgap Polymer Solar Cells

Polymer bulk heterojunction solar cells based on low bandgap polymer:fullerene blends are promising for next generation low‐cost photovoltaics. While these solution‐processed solar cells are compatible with large‐scale roll‐to‐roll processing, active layers used for typical laboratory‐scale devices are too thin to ensure high manufacturing yields. Furthermore, due to the limited light absorption and optical interference within the thin active layer, the external quantum efficiencies (EQEs) of bulk heterojunction polymer solar cells are severely limited. In order to produce polymer solar cells with high yields, efficient solar cells with a thick active layer must be demonstrated. In this work, the performance of thick‐film solar cells employing the low‐bandgap polymer poly(dithienogermole‐thienopyrrolodione) (PDTG‐TPD) was demonstrated. Power conversion efficiencies over 8.0% were obtained for devices with an active layer thickness of 200 nm, illustrating the potential of this polymer for large‐scale manufacturing. Although an average EQE > 65% was obtained for devices with active layer thicknesses > 200 nm, the cell performance could not be maintained due to a reduction in fill factor. By comparing our results for PDTG‐TPD solar cells with similar P3HT‐based devices, we investigated the loss mechanisms associated with the limited device performance observed for thick‐film low‐bandgap polymer solar cells.     

A real-time PCR diagnostic method for detection of Naegleria fowleri

Naegleria fowleri is a free-living amoeba that can cause primary amoebic meningoencephalitis (PAM). While, traditional methods for diagnosing PAM still rely on culture, more current laboratory diagnoses exist based on conventional PCR methods; however, only a few real-time PCR processes have been described as yet. Here, we describe a real-time PCR-based diagnostic method using hybridization fluorescent labelled probes, with a LightCycler instrument and accompanying software (Roche), targeting the Naegleria fowleriMp2Cl5 gene sequence.Using this method, no cross reactivity with other tested epidemiologically relevant prokaryotic and eukaryotic organisms was found. The reaction detection limit was 1 copy of the Mp2Cl5 DNA sequence. This assay could become useful in the rapid laboratory diagnostic assessment of the presence or absence of Naegleria fowleri.