RESUMEN
MOTIVATION: Differential abundance analysis is an essential and commonly used tool to characterize the difference between microbial communities. However, identifying differentially abundant microbes remains a challenging problem because the observed microbiome data are inherently compositional, excessive sparse, and distorted by experimental bias. Besides these major challenges, the results of differential abundance analysis also depend largely on the choice of analysis unit, adding another practical complexity to this already complicated problem. RESULTS: In this work, we introduce a new differential abundance test called the MsRDB test, which embeds the sequences into a metric space and integrates a multiscale adaptive strategy for utilizing spatial structure to identify differentially abundant microbes. Compared with existing methods, the MsRDB test can detect differentially abundant microbes at the finest resolution offered by data and provide adequate detection power while being robust to zero counts, compositional effect, and experimental bias in the microbial compositional dataset. Applications to both simulated and real microbial compositional datasets demonstrate the usefulness of the MsRDB test. AVAILABILITY AND IMPLEMENTATION: All analyses can be found under https://github.com/lakerwsl/MsRDB-Manuscript-Code.
Asunto(s)
MicrobiotaRESUMEN
Microbiome sequencing data normalization is crucial for eliminating technical bias and ensuring accurate downstream analysis. However, this process can be challenging due to the high frequency of zero counts in microbiome data. We propose a novel reference-based normalization method called normalization via rank similarity (RSim) that corrects sample-specific biases, even in the presence of many zero counts. Unlike other normalization methods, RSim does not require additional assumptions or treatments for the high prevalence of zero counts. This makes it robust and minimizes potential bias resulting from procedures that address zero counts, such as pseudo-counts. Our numerical experiments demonstrate that RSim reduces false discoveries, improves detection power, and reveals true biological signals in downstream tasks such as PCoA plotting, association analysis, and differential abundance analysis.
Asunto(s)
Biología Computacional , Microbiota , Biología Computacional/métodosRESUMEN
Current workflows for colocalization analysis in fluorescence microscopic imaging introduce significant bias in terms of the user's choice of region of interest (ROI). In this work, we introduce an automatic, unbiased structured detection method for correlated region detection between two random processes observed on a common domain. We argue that although intuitive, using the maximum log-likelihood statistic directly suffers from potential bias and substantially reduced power. Therefore, we introduce a simple size-based normalization to overcome this problem. We show that scanning using the proposed statistic leads to optimal correlated region detection over a large collection of structured correlation detection problems.
RESUMEN
Recent results in coupled or temporal graphical models offer schemes for estimating the relationship structure between features when the data come from related (but distinct) longitudinal sources. A novel application of these ideas is for analyzing group-level differences, i.e., in identifying if trends of estimated objects (e.g., covariance or precision matrices) are different across disparate conditions (e.g., gender or disease). Often, poor effect sizes make detecting the differential signal over the full set of features difficult: for example, dependencies between only a subset of features may manifest differently across groups. In this work, we first give a parametric model for estimating trends in the space of SPD matrices as a function of one or more covariates. We then generalize scan statistics to graph structures, to search over distinct subsets of features (graph partitions) whose temporal dependency structure may show statistically significant group-wise differences. We theoretically analyze the Family Wise Error Rate (FWER) and bounds on Type 1 and Type 2 error. Evaluating on US census data, we identify groups of states with cultural and legal overlap related to baby name trends and drug usage. On a cohort of individuals with risk factors for Alzheimer's disease (but otherwise cognitively healthy), we find scientifically interesting group differences where the default analysis, i.e., models estimated on the full graph, do not survive reasonable significance thresholds.
RESUMEN
Dextromethorphan (DXM) is a widely utilized central antitussive agent, which is frequently abused by individuals seeking its recreational effect. But DXM overdose can cause some adverse effects, including brain damage, loss of consciousness, and cardiac arrhythmias, and hence its detection is significant. Herein, an electrochemical sensor based on a Cu-coordinated molecularly imprinted polymer (Cu-MIP) was fabricated for its detection. For constructing the sensor, nitrogen-doped carbon nanosheets (CCNs) were prepared through calcining chitin under an argon atmosphere, and molybdenum disulfide (MoS2) was allowed to grow on their surface. Subsequently, the obtained MoS2/CCNs composite was employed to modify a glassy carbon electrode (GCE), and the Cu-MIP was electrodeposited on the electrode in a Cu-1,10-phenanthroline (Cu-Phen) solution containing DXM, where Cu2+ played a role in facilitating electron transfer and binding DXM. Due to the large specific surface area, good electrocatalytic properties and recognition of the resulting composite, the resulting Cu-MIP/MoS2/CCNs/GCE showed high selectivity and sensitivity. Under optimized experimental conditions, the peak current of DXM and its concentration exhibited a good linear relationship over the concentration range of 0.1-100 µM, and the limit of detection (S/N = 3) was 0.02 µM. Furthermore, the electrochemical sensor presented good stability, and it was successfully used for the determination of DXM in pharmaceutical, human serum and urine samples.
Asunto(s)
Carbono , Cobre , Dextrometorfano , Disulfuros , Técnicas Electroquímicas , Polímeros Impresos Molecularmente , Molibdeno , Molibdeno/química , Disulfuros/química , Dextrometorfano/análisis , Dextrometorfano/química , Dextrometorfano/orina , Cobre/química , Técnicas Electroquímicas/métodos , Carbono/química , Polímeros Impresos Molecularmente/química , Quitina/química , Humanos , Límite de Detección , Electrodos , Antitusígenos/química , Antitusígenos/análisis , Antitusígenos/orinaRESUMEN
The sensitive, accurate and rapid detection of carbohydrate antigen 125 (CA125) is essential for the early diagnosis and clinical management of ovarian cancer, but there is still challenge. Herein, a photoelectrochemical (PEC) immunosensor based on CdS/Bi2S3/NiS ternary sulfide heterostructured photocatalyst was presented for the detection of CA125. The CdS/Bi2S3/NiS was synthesized by a one-step hydrothermal approach. The heterojunction comprising of CdS and Bi2S3 could separate photogenerated carriers, the introduced narrow bandgap NiS could act as electron-conducting bridge to facilitate the transfer of interfacial photogenerated electrons, thereby improving the photoelectric conversion efficiency. Due to their synergistic effect, the photocurrent response produced by the composite was up to 14.6 times of pure CdS. On the basis, a PEC immunosensor was constructed by introducing the CA125 antibody through thioglycolic acid linkage. It was found that the resulting immunosensor showed good performance. Under the optimized conditions, its linear detection range was as wide as 1 pg mL-1-50 ng mL-1, and the detection limit was low to 0.85 pg mL-1. Furthermore, we experimentally tested its anti-interference, stability and reproducibility, and satisfactory results were achieved. The practicable feasibility of the sensor was confirmed by testing serum sample. Thus this work provided a simple, fast and enough sensitive approach for CA125 monitoring.
Asunto(s)
Bismuto , Antígeno Ca-125 , Compuestos de Cadmio , Técnicas Electroquímicas , Sulfuros , Compuestos de Cadmio/química , Sulfuros/química , Humanos , Técnicas Electroquímicas/métodos , Antígeno Ca-125/sangre , Antígeno Ca-125/análisis , Bismuto/química , Límite de Detección , Inmunoensayo/métodos , Técnicas Biosensibles/métodosRESUMEN
Introduction: Res-FLNet presents a cutting-edge solution for addressing autonomous driving tasks in the context of multimodal sensing robots while ensuring privacy protection through Federated Learning (FL). The rapid advancement of autonomous vehicles and robotics has escalated the need for efficient and safe navigation algorithms that also support Human-Robot Interaction and Collaboration. However, the integration of data from diverse sensors like cameras, LiDARs, and radars raises concerns about privacy and data security. Methods: In this paper, we introduce Res-FLNet, which harnesses the power of ResNet-50 and LSTM models to achieve robust and privacy-preserving autonomous driving. The ResNet-50 model effectively extracts features from visual input, while LSTM captures sequential dependencies in the multimodal data, enabling more sophisticated learning control algorithms. To tackle privacy issues, we employ Federated Learning, enabling model training to be conducted locally on individual robots without sharing raw data. By aggregating model updates from different robots, the central server learns from collective knowledge while preserving data privacy. Res-FLNet can also facilitate Human-Robot Interaction and Collaboration as it allows robots to share knowledge while preserving privacy. Results and discussion: Our experiments demonstrate the efficacy and privacy preservation of Res-FLNet across four widely-used autonomous driving datasets: KITTI, Waymo Open Dataset, ApolloScape, and BDD100K. Res-FLNet outperforms state-of-the-art methods in terms of accuracy, robustness, and privacy preservation. Moreover, it exhibits promising adaptability and generalization across various autonomous driving scenarios, showcasing its potential for multi-modal sensing robots in complex and dynamic environments.
RESUMEN
Background: Thyroid dysfunction is common in patients with kidney disease. However, the relationship between thyroid dysfunction and idiopathic membranous nephropathy (IMN) remains unclear. This retrospective study aimed to investigate the clinicopathological characteristics and prognosis of patients with IMN and thyroid dysfunction compared to patients with IMN and without thyroid dysfunction. Methods: A total of 1052 patients with IMN diagnosed by renal biopsy were enrolled in this study, including 736 (70%) with normal thyroid function and 316 (30%) with abnormal thyroid function. We analyzed the clinicopathological features and prognostic data between the two groups, using propensity score matching (PSM) to reduce the bias. Logistic regression analysis was performed to investigate the risk factors for IMN combined with thyroid dysfunction. Kaplan-Meier curves and Cox regression analysis were used to evaluate the association between thyroid dysfunction and IMN. Results: Patients with IMN and thyroid dysfunction exhibited more severe clinical features. Female sex, lower albumin level, higher D-dimer level, severe proteinuria, and decreased estimated glomerular filtration rate were predictors of thyroid dysfunction in patients with IMN. After PSM, 282 pairs were successfully matched. Results from the Kaplan-Meier curves indicated that the thyroid dysfunction group had a lower complete remission rate (P = 0.044), higher relapse rate (P < 0.001), and lower renal survival rate (P = 0.004). The multivariate Cox regression analysis revealed that thyroid dysfunction was an independent risk factor for complete remission [hazard ratio (HR) = 0.810, P = 0.045], relapse (HR = 1.721, P = 0.001), and composite endpoint event (HR = 2.113, P = 0.014) in IMN. Conclusions: Thyroid dysfunction is relatively common in patients with IMN, and the clinical indicators are more severe in these patients. Thyroid dysfunction is an independent risk factor for poor prognosis in patients with IMN. More attention should be paid to thyroid function in patients with IMN.
Asunto(s)
Glomerulonefritis Membranosa , Humanos , Femenino , Glomerulonefritis Membranosa/complicaciones , Glomerulonefritis Membranosa/diagnóstico , Estudios Retrospectivos , Glándula Tiroides/patología , Pronóstico , RecurrenciaRESUMEN
Mild mesangial proliferative IgA nephropathy with minimal change disease (MCD-IgAN) and mild mesangial proliferative IgA nephropathy without minimal change disease (Non-MCD-IgAN) have similar characteristics on light microscopy. Nevertheless, their discrepancies in clinicopathological features and prognosis remain unknown. A total of 589 patients with biopsy-proven mild mesangial proliferative IgA nephropathy (M-IgAN) combined with light microscopy and immunofluorescence were enrolled. Firstly, the diagnoses of the patients by electron microscopy were recorded and used as the gold standard. We calculated the sensitivity and specificity using nephrotic syndrome (NS) as the diagnostic criteria to identify MCD-IgAN. Then, excluding patients with a 24-h urinary total protein less than 0.5 g/day, incomplete clinical data, or less than the six-month follow-up, we included 184 cases of non-MCD-IgAN and 98 cases of MCD-IgAN. The patients' clinicopathological and outcome data were collected and compared. Among the 589 patients, according to electron microscopy, 381 were diagnosed with non-MCD-IgAN, 167 with MCD-IgAN, and 41 with M-IgAN complicated by other glomerular diseases. Using NS as the diagnostic criteria to distinguish non-MCD-IgAN and MCD-IgAN, the sensitivity and specificity were 83.8% and 99.5%, respectively. The patients in the MCD-IgAN group tended to be younger, hypotensive, with lower urinary erythrocytes, and more likely to achieve complete remission, and fewer patients progressed to the endpoint than those in the non-MCD-IgAN group (all P < 0 .05). NS appears to be an objective indicator for differentiating MCD-IgAN from non-MCD-IgAN. Non-MCD-IgAN varies greatly from MCD-IgAN in clinicopathology and treatment response, with a poorer prognosis.
Asunto(s)
Glomerulonefritis por IGA , Nefrosis Lipoidea , Síndrome Nefrótico , Humanos , Glomerulonefritis por IGA/diagnóstico , Glomerulonefritis por IGA/complicaciones , Nefrosis Lipoidea/diagnóstico , Nefrosis Lipoidea/complicaciones , Nefrosis Lipoidea/tratamiento farmacológico , Síndrome Nefrótico/etiología , Pronóstico , Estudios RetrospectivosRESUMEN
BACKGROUND: IgAN is the most common primary glomerulonephritis worldwide. However, the pathogenesis of IgAN remains unknown. Currently, there is evidence that C3 deposition plays a role in disease development. This study aimed to investigate clinical, pathological features, and prognosis of adult IgAN patients with C3 deposition, as well as explore the role of complement activation in disease progression. METHODS: A total of 821 patients with biopsy-proven IgAN were included in this study. Patients were divided into three different groups according to their C3 deposition intensity. Clinical and pathological characteristics were compared between groups. Logistic analysis was used to estimate the relationship between C3 deposition and the Oxford scoring system. Univariate and multivariate Cox proportional hazard regression models were used to analyze the effect of the presence of C3 deposits on the prognosis of patients with IgA nephropathy. Kaplan-Meier survival analysis was used to evaluate the cumulative incidence of renal progression between groups. RESULTS: Patients with C3 deposition exhibited more severe clinical and pathological features and had a higher score according to the Oxford scoring system. With the increasing intensity of C3 deposition, patients present more hematuria, crescents, heavier interstitial inflammatory cell infiltration and a higher score on segmental sclerosis lesions. Logistic regression identified a positive relationship between C3 deposition and histopathology. Univariate and multivariate Cox regression indicated that C3 deposition was an independent risk factor for IgAN severity. The Kaplan-Meier survival curves indicated that patients with positive C3 deposition had a worse prognosis compared to those without C3 deposition. CONCLUSIONS: Patients with positive glomerular C3 deposition presented with more severe clinical and histopathological characteristics and a higher score on the Oxford scoring system. With the increasing intensity of C3 deposition, IgAN patients were more likely to present with high level of microscopic hematuria, fibrous crescents, interstitial inflammatory cell infiltration, and a higher score on segmental sclerosis lesions. C3 deposition at the time of renal biopsy is likely an independent risk factor for IgA nephropathy severity and progression.
Asunto(s)
Glomerulonefritis por IGA , Adulto , Humanos , Glomerulonefritis por IGA/patología , Pronóstico , Hematuria , Esclerosis/patología , Riñón/patología , Estudios RetrospectivosRESUMEN
Introduction: In the past two decades, mindfulness-based intervention programs have gradually become popular.Many studies have confirmed that these programs can effectively alleviate prenatal stress and negative emotion.The mindfulness-based stress-buffering hypothesis suggests that mindfulness training can induce changes in the levels of the cortisol secreted by the HPA axis, thereby reducing stress susceptibility. However, to date, only a few high-quality evidence-based medical studies have analyzed the effect of the mindfulness-based intervention in a maternal population.Thus, this study investigated the effects of a mindfulness-based psychosomatic intervention on pregnancy stress and the HYPERLINK "javascript:;" hypothalamic-pituitary-adrenal (HPA) axis of pregnant Chinese women. Methods: Women experiencing first-time pregnancy (n = 117) were randomly allocated to the intervention group or parallel active control group, and data were collected at baseline and post-intervention periods. The participants completed questionnaires regarding mindfulness and pregnancy stress. Saliva samples was collected at the time of waking up, and 30, 45, and 60 min after waking up for analyzing the salivary cortisol levels. We analyzed differences between the two groups and changes within the same group before and after the intervention. Results and discussion: A total of 95 participants completed the trial. Compared with the parallel active control group, the intervention group exhibited lower levels of stress after the intervention (P = 0.047). For HPA-axis-related indicators after the intervention, Delta value (P = 0.01) and AUCM value (P = 0.031) of the intervention group were significantly higher than that of the control group. Mindfulness-based interventions effectively reduced the level of pregnancy stress and adjusted the HPA axis function in pregnant women in China. Clinical Trial Registration: https://www.chictr.org.cn, identifier ChiCTR 2000033149.
RESUMEN
Long noncoding RNAs (lncRNAs) play crucial roles in melanoma initiation and development, serving as potential therapeutic targets and prognostic markers for melanoma. lncRNA survival-associated mitochondrial melanoma-specific oncogenic noncoding RNA (SAMMSON) is upregulated in many types of human cancers. However, the functions of SAMMSON in melanoma have not been fully elucidated. This study is aimed at investigating the expression and functions of SAMMSON in melanoma development. Bioinformatics analysis was performed to determine the expression of SAMMSON and its correlation with the 10-year overall survival (OS) in melanoma patients. Cell proliferation, migration, invasion, and tumorigenesis were detected by MTT, colony formation, Transwell assays, and mouse xenograft model. The expression of cell cycle-related factors, epithelial-to-mesenchymal transition (EMT) makers, and matrix metalloproteinases (MMPs) was assessed by RT-qPCR and western blotting analysis. The results demonstrated that SAMMSON expression was upregulated in melanoma tissues and cells, and lower SAMMSON expression was correlated with longer 10-year OS. SAMMSON knockdown decreased the proliferation, migration, and invasion of melanoma cells by regulating the expression of proliferation-related genes, EMT factors, and MMPs, respectively. Additionally, Forkhead box protein A2 (FOXA2) was confirmed to be a target of SAMMSON, and the biological effects induced by FOXA2 overexpression were similar to those induced by SAMMSON silencing in melanoma cells. Further studies showed that SAMMSON downregulated FOXA2 expression in melanoma cells by modulating the EZH2/H3K27me3 axis. Taken together, our data indicate that SAMMSON plays an important role in melanoma progression and can be a valuable biomarker and therapeutic target in melanoma.
RESUMEN
The value of a novel soybean male-sterile mutation msLC01 in breeding practice was determined by its outcrossing properties. Then, the effects of different planting arrangements on the pod set characteristics of male-sterile plants were assessed by using orthogonal experiments at two sites. At the same time, the effects of msLC01 male sterility on other traits were assessed in two C2F2 populations. In addition, the nectar secretion and natural outcross of male-sterile plants from four msLC01 lines were compared with one ms1 line and one ms6 line. The results of the orthogonal experiment showed that the pod numbers and pod set rates of male-sterile plants were decisively different between the two experimental sites but not between the two levels of the other factors. Both increasing the ratio of paternal parent to maternal parent and planting the parental seeds in a mixed way, the proportion of seeds pollinated by the target parent pollen could be increased. Except for the pod number per plant trait, there was no significant difference between male-sterile plants and their fertile siblings. The amount of nectar significantly differed among the lines. Compared with ms1 and ms6 male-sterile plants, the four msLC01 lines possessed significantly more or similar numbers of pod sets. The results of this study lay a foundation for the future use of this mutant in soybean breeding.
RESUMEN
WRKY transcription factors are known mostly for their function in plant defense, abiotic stress responses, senescence, seed germination, and development of the pollen, embryo, and seed. Here, we report the regulatory functions of two WRKY proteins in photomorphogenesis and PIF4 expression. PIF4 is a critical signaling hub in light, temperature, and hormonal signaling pathways. Either its expression or its accumulation peaks in the morning and afternoon. WRKY2 and WRKY10 form heterodimers and recognize their target site in the PIF4 promoter near the MYB element that is bound by CCA1 and LHY under red and blue light. WRKY2 and WRKY10 interact directly with CCA1/LHY to enhance their targeting but interact indirectly with SHB1. The two WRKY proteins also interact with phyB, and their interaction enhances the targeting of CCA1 and LHY to the PIF4 promoter. SHB1 associates with the WRKY2 and WRKY10 loci and enhances their expression in parallel with the PIF4 expression peaks. This forward regulatory loop further sustains the accumulation of the two WRKY proteins and the targeting of CCA1/LHY to the PIF4 locus. In summary, interactions of two WRKY proteins with CCA1/LHY and phyB maintain an optimal expression level of PIF4 toward noon and afternoon, which is essential to sketch the circadian pattern of PIF4 expression.
Asunto(s)
Proteínas de Arabidopsis , Arabidopsis , Arabidopsis/metabolismo , Proteínas de Arabidopsis/metabolismo , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/metabolismo , Ritmo Circadiano/genética , Proteínas de Unión al ADN/genética , Proteínas de Unión al ADN/metabolismo , Regulación de la Expresión Génica de las Plantas , Fitocromo B/metabolismo , Factores de Transcripción/genética , Factores de Transcripción/metabolismoRESUMEN
The weighted UniFrac distance, a plug-in estimator of the Wasserstein distance of read counts on a tree, has been widely used to measure the microbial community difference in microbiome studies. Our investigation however shows that such a plug-in estimator, although intuitive and commonly used in practice, suffers from potential bias. Motivated by this finding, we study the problem of optimal estimation of the Wasserstein distance between two distributions on a tree from the sampled data in the high-dimensional setting. The minimax rate of convergence is established. To overcome the bias problem, we introduce a new estimator, referred to as the moment-screening estimator on a tree (MET), by using implicit best polynomial approximation that incorporates the tree structure. The new estimator is computationally efficient and is shown to be minimax rate-optimal. Numerical studies using both simulated and real biological datasets demonstrate the practical merits of MET, including reduced biases and statistically more significant differences in microbiome between the inactive Crohn's disease patients and the normal controls.
RESUMEN
Quantitative comparison of microbial composition from different populations is a fundamental task in various microbiome studies. We consider two-sample testing for microbial compositional data by leveraging phylogenetic information. Motivated by existing phylogenetic distances, we take a minimum-cost flow perspective to study such testing problems. We first show that multivariate analysis of variance with permutation using phylogenetic distances, one of the most commonly used methods in practice, is essentially a sum-of-squares type of test and has better power for dense alternatives. However, empirical evidence from real datasets suggests that the phylogenetic microbial composition difference between two populations is usually sparse. Motivated by this observation, we propose a new maximum type test, detector of active flow on a tree, and investigate its properties. We show that the proposed method is particularly powerful against sparse phylogenetic composition difference and enjoys certain optimality. The practical merit of the proposed method is demonstrated by simulation studies and an application to a human intestinal biopsy microbiome dataset on patients with ulcerative colitis.
RESUMEN
BACKGROUND: Hypothalamic hamartomas (HHs) are rare, and it is even rarer when combined with gray matter heterotopia (GMH) and polymicrogyria (PMG). CASE DESCRIPTION: A 5-year-old boy with HH, GMH, and PMG was retrospectively evaluated. The clinical data, including the symptoms, examinations, diagnosis, and treatment, were collected. The patient had a chief complaint of gelastic seizures and intellectual deficiency. Brain magnetic resonance imaging showed HH, paraventricular nodular heterotopia, and PMG. Video electroencephalographs were normal. The patient underwent resection of the HH via transcallosal transseptal interforniceal approach. Seizures disappeared immediately after complete resection of HH, and the intellectual development improved. CONCLUSIONS: In this extremely rare case, resection of the HH eliminated the symptoms. Nonetheless, we still need to be cautious about the possible epilepsy that may be caused by GMH and PMG.
Asunto(s)
Sustancia Gris/patología , Hamartoma/patología , Enfermedades Hipotalámicas/patología , Polimicrogiria/patología , Preescolar , Hamartoma/cirugía , Humanos , Enfermedades Hipotalámicas/cirugía , Discapacidad Intelectual/etiología , Masculino , Procedimientos Neuroquirúrgicos/métodos , Convulsiones/etiologíaRESUMEN
Motivated by gene set enrichment analysis, we investigate the problem of combined hypothesis testing on a graph. A general framework is introduced to make effective use of the structural information of the underlying graph when testing multivariate means. A new testing procedure is proposed within this framework, and shown to be optimal in that it can consistently detect departures from the collective null at a rate that no other test could improve, for almost all graphs. We also provide general performance bounds for the proposed test under any specific graph, and illustrate their utility through several common types of graphs. Numerical experiments are presented to further demonstrate the merits of our approach.
RESUMEN
Fluorescence lifetime imaging microscopy (FLIM) is a powerful imaging tool used to study the molecular environment of flurophores. In time domain FLIM, extracting lifetime from fluorophores signals entails fitting data to a decaying exponential distribution function. However, most existing techniques for this purpose need large amounts of photons at each pixel and a long computation time, thus making it difficult to obtain reliable inference in applications requiring either short acquisition or minimal computation time. In this work, we introduce a new nonparametric empirical Bayesian framework for FLIM data analysis (NEB-FLIM), leading to both improved pixel-wise lifetime estimation and a more robust and computationally efficient integral property inference. This framework is developed based on a newly proposed hierarchical statistical model for FLIM data and adopts a novel nonparametric maximum likelihood estimator to estimate the prior distribution. To demonstrate the merit of the proposed framework, we applied it on both simulated and real biological datasets and compared it with previous classical methods on these datasets.
RESUMEN
Light and temperature are two important environmental signals to plants. After dawn, photo-activated phytochromes translocate into the nucleus and interact with a family of negative basic helix-loop-helix PIF regulators. Subsequent phosphorylation and degradation of PIFs triggers a series of photomorphogenic responses. However, excess light can damage the photosynthetic apparatus and leads to photoinhibition. Plants acclimate to a balanced state of photomorphogenesis to avoid photodamage. Here, we show that upregulation of PIF4 expression by SHB1 and CCA1 under red light represents a desensitization step. After dawn, the highly expressed circadian clock protein CCA1 brings circadian signals to the regulatory region of the PIF4 signaling hub. Recruitment of SHB1 by CCA1 modulates red light-specific induction of PIF4 expression thus integrating circadian and light signals. As noon approaches and light intensity and ambient temperature tend to increase, the SHB1-CCA1 interaction sustains PIF4 expression to trigger thermomorphogenic responses to changing light and temperature conditions.