RESUMEN
Accurate discrimination of pathogenic and nonpathogenic variation remains an enormous challenge in clinical genetic testing of inherited retinal diseases (IRDs) patients. Computational methods for predicting variant pathogenicity are the main solutions for this dilemma. The majority of the state-of-the-art variant pathogenicity prediction tools disregard the differences in characteristics among different genes and treat all types of mutations equally. Since missense variants are the most common type of variation in the coding region of the human genome, we developed a novel missense mutation pathogenicity prediction tool, named Prediction of Deleterious Missense Mutation for IRDs (PdmIRD) in this study. PdmIRD was tailored for IRDs-related genes and constructed with the conditional random forest model. Population frequencies and a newly available prediction tool were incorporated into PdmIRD to improve the performance of the model. The evaluation of PdmIRD demonstrated its superior performance over nonspecific tools (areas under the curves, 0.984 and 0.910) and an existing eye abnormalities-specific tool (areas under the curves, 0.975 and 0.891). We also demonstrated the submodel that used a smaller gene panel further slightly improved performance. Our study provides evidence that a disease-specific model can enhance the prediction of missense mutation pathogenicity, especially when new and important features are considered. Additionally, this study provides guidance for exploring the characteristics and functions of the mutated proteins in a greater number of Mendelian disorders.
Asunto(s)
Mutación Missense , Enfermedades de la Retina , Humanos , Biología Computacional/métodos , Predisposición Genética a la Enfermedad , Pruebas Genéticas/métodos , Enfermedades de la Retina/diagnóstico , Enfermedades de la Retina/genéticaRESUMEN
Microbial interactions determine ecosystem carbon (C) and nutrient cycling, yet it remains unclear how interguild fungal interactions modulate microbial residue contribution to soil C pools (SOC) during forest succession. Here, we present a region-wide investigation of the relative dominance of saprophytic versus symbiotic fungi in litter and soil compartments, exploring their linkages to soil microbial residue pools and potential drivers along a chronosequence of secondary Chinese pine (Pinus tabulaeformis) forests on the Loess Plateau. Despite minor changes in C and nitrogen (N) stocks in the litter or soil layers across successional stages, we found significantly lower soil phosphorus (P) stocks, higher ratios of soil C: N, soil N: P and soil C: P but lower ratios of litter C: N and litter C: P in old (>75 years) than young stands (<30 years). Pine stand development altered the saprotroph: symbiotroph ratios of fungal communities to favor the soil symbiotrophs versus the litter saprotrophs. The dominance of saprotrophs in litter is positively related to microbial necromass contribution to SOC, which is negatively related to the dominance of symbiotrophs in soils. Antagonistic interguild fungal competition in litter and soil layers, in conjunction with increased fungal but decreased bacterial necromass contribution to SOC, jointly contribute to unchanged total necromass contribution to SOC with stand development. The saprotroph: symbiotroph ratios in litter and soil layers are mainly driven by soil P stocks and stand parameters (e.g., stand age and slope), respectively, while substrate stoichiometries primarily regulate microbial necromass accumulation and fungal: bacterial necromass ratios. These results provide novel insights into how microbial interactions at local spatial scales modulate temporal changes in SOC pools, with management implications for mitigating regional land degradation.
Asunto(s)
Ecosistema , Pinus , Suelo/química , Bosques , Fósforo , Carbono/química , Microbiología del Suelo , BacteriasRESUMEN
Tree-ring widths contain valuable historical information related to both forest disturbances and climate variability and changes within forests. However, current methods are still unable to accurately distinguish between disturbances and climate signals in tree rings, especially in the case of climate anomalies. To address this issue, we developed a novel method, called Growth Trends Clustering (GTC) that uses the distribution characteristics of tree-ring widths within a stand to distinguish the effects of climate and other forest disturbances. GTC employed a Gaussian mixture model to fit the probability density distribution of annual ring-width index (RWI) in a stand. Discriminative criteria were established to cluster diverse sub-distributions from the Gaussian mixture model into categories of growth release, suppression, or normal trends. This approach allowed us to identify the occurrence, duration, and severity of forest disturbances based on percentage changes in the growth release or suppression categories of trees. And the effect of climate on tree growth was assessed according to the mean statistics of the growth normal categories. Using common forest disturbances such as defoliating insects and thinning as examples, we validated our method using tree-ring collections from six sites in British Columbia and Quebec, Canada. We found that the GTC method was superior to traditional time-series analysis methods (e.g., Radial Growth Averaging, Boundary Line, Absolute Increase, and Curve Intervention Detection) for detecting past forest disturbances and was able to significantly enhance climate signals. In summary, the GTC method presented in this study introduces a novel statistical approach for accurately distinguishing between forest disturbances and climate signals in tree rings. This is particularly important for understanding forest disturbance regimes under climate change and for developing future disturbance mitigation strategies.
RESUMEN
AIM: To analyze the relationship between optical coherence tomography (OCT) and OCT angiography (OCTA) imaging in patients with diabetic macular edema (DME) who are treated with a combination of aflibercept and triamcinolone acetonide (TA). METHODS: A total of 76 eyes newly diagnosed DME were included in this study. They were randomly assigned to receive either aflibercept or a combination of aflibercept and TA. Injections once a month for a total of three injections. Central macular thickness (CMT), number of hyperreflective foci (HRF), height of subretinal fluid (SRF), and area of foveal avascular zone (FAZ) were evaluated using OCT and OCTA at baseline and after each monthly treatment. RESULTS: Both groups showed improvement in best corrected visual acuity (BCVA) and reduction in macular edema after treatment, and the difference in BCVA between the two groups was statistically significant after each treatment (P<0.05). The difference in CMT between the two groups was statistically significant after the first two injections (P<0.01), but not after the third injection (P=0.875). The number of HRF (1mo: 7.41±8.25 vs 10.86±7.22, P=0.027; 2mo: 5.33±6.13 vs 9.12±8.61, P=0.034; 3mo: 3.58±3.00 vs 6.37±5.97, P=0.007) and height of SRF (1mo: 82.39±39.12 vs 105.77±42.26 µm, P=0.011; 2mo: 36.84±10.02 vs 83.59±37.78 µm, P<0.01; 3mo: 11.57±3.29 vs 45.43±12.60 µm, P<0.01) in combined group were statistically significant less than aflibercept group after each injection, while the area of FAZ showed no significant change before and after treatment in both groups. CONCLUSION: The combination therapy of aflibercept and TA shows more significant effects on DME eyes with decreased HRF and SRF. However, both aflibercept and combination therapy show no significant change in the area of FAZ.
RESUMEN
Wood growth is key to understanding the feedback of forest ecosystems to the ongoing climate warming. An increase in spatial synchrony (i.e., coincident changes in distant populations) of spring phenology is one of the most prominent climate responses of forest trees. However, whether temperature variability contributes to an increase in the spatial synchrony of spring phenology and its underlying mechanisms remains largely unknown. Here, we analyzed an extensive dataset of xylem phenology observations of 20 conifer species from 75 sites over the Northern Hemisphere. Along the gradient of increase in temperature variability in the 75 sites, we observed a convergence in the onset of cell enlargement roughly toward the 5th of June, with a convergence in the onset of cell wall thickening toward the summer solstice. The increase in rainfall since the 5th of June is favorable for cell division and expansion, and as the most hours of sunlight are received around the summer solstice, it allows the optimization of carbon assimilation for cell wall thickening. Hence, the convergences can be considered as the result of matching xylem phenological activities to favorable conditions in regions with high temperature variability. Yet, forest trees relying on such consistent seasonal cues for xylem growth could constrain their ability to respond to climate warming, with consequences for the potential growing season length and, ultimately, forest productivity and survival in the future.
Asunto(s)
Tracheophyta , Temperatura , Ecosistema , Cambio Climático , Xilema , Estaciones del Año , ÁrbolesRESUMEN
As major terrestrial carbon sinks, forests play an important role in mitigating climate change. The relationship between the seasonal uptake of carbon and its allocation to woody biomass remains poorly understood, leaving a significant gap in our capacity to predict carbon sequestration by forests. Here, we compare the intra-annual dynamics of carbon fluxes and wood formation across the Northern hemisphere, from carbon assimilation and the formation of non-structural carbon compounds to their incorporation in woody tissues. We show temporally coupled seasonal peaks of carbon assimilation (GPP) and wood cell differentiation, while the two processes are substantially decoupled during off-peak periods. Peaks of cambial activity occur substantially earlier compared to GPP, suggesting the buffer role of non-structural carbohydrates between the processes of carbon assimilation and allocation to wood. Our findings suggest that high-resolution seasonal data of ecosystem carbon fluxes, wood formation and the associated physiological processes may reduce uncertainties in carbon source-sink relationships at different spatial scales, from stand to ecosystem levels.