A Bayesian Approach Toward Robust Multidimensional Ellipsoid-Specific Fitting.

This work presents a novel and effective method for fitting multidimensional ellipsoids (i.e., ellipsoids embedded in [Formula: see text]) to scattered data in the contamination of noise and outliers. Unlike conventional algebraic or geometric fitting paradigms that assume each measurement point is a noisy version of its nearest point on the ellipsoid, we approach the problem as a Bayesian parameter estimate process and maximize the posterior probability of a certain ellipsoidal solution given the data. We establish a more robust correlation between these points based on the predictive distribution within the Bayesian framework, i.e., considering each model point as a potential source for generating each measurement. Concretely, we incorporate a uniform prior distribution to constrain the search for primitive parameters within an ellipsoidal domain, ensuring ellipsoid-specific results regardless of inputs. We then establish the connection between measurement point and model data via Bayes' rule to enhance the method's robustness against noise. Due to independent of spatial dimensions, the proposed method not only delivers high-quality fittings to challenging elongated ellipsoids but also generalizes well to multidimensional spaces. To address outlier disturbances, often overlooked by previous approaches, we further introduce a uniform distribution on top of the predictive distribution to significantly enhance the algorithm's robustness against outliers. Thanks to the uniform prior, our maximum a posterior probability coincides with a more tractable maximum likelihood estimation problem, which is subsequently solved by a numerically stable Expectation Maximization (EM) framework. Moreover, we introduce an ε-accelerated technique to expedite the convergence of EM considerably. We also investigate the relationship between our algorithm and conventional least-squares-based ones, during which we theoretically prove our method's superior robustness. To the best of our knowledge, this is the first comprehensive method capable of performing multidimensional ellipsoid-specific fitting within the Bayesian optimization paradigm under diverse disturbances. We evaluate it across lower and higher dimensional spaces in the presence of heavy noise, outliers, and substantial variations in axis ratios. Also, we apply it to a wide range of practical applications such as microscopy cell counting, 3D reconstruction, geometric shape approximation, and magnetometer calibration tasks. In all these test contexts, our method consistently delivers flexible, robust, ellipsoid-specific performance, and achieves the state-of-the-art results.

Plasticity of Adipose Tissues: Interconversion among White, Brown, and Beige Fat and Its Role in Energy Homeostasis.

Obesity, characterized by the excessive accumulation of adipose tissue, has emerged as a major public health concern worldwide. To develop effective strategies for treating obesity, it is essential to comprehend the biological properties of different adipose tissue types and their respective roles in maintaining energy balance. Adipose tissue serves as a crucial organ for energy storage and metabolism in the human body, with functions extending beyond simple fat storage to encompass the regulation of energy homeostasis and the secretion of endocrine factors. This review provides an overview of the key characteristics, functional differences, and interconversion processes among white adipose tissue (WAT), brown adipose tissue (BAT), and beige adipose tissue. Moreover, it delves into the molecular mechanisms and recent research advancements concerning the browning of WAT, activation of BAT, and whitening of BAT. Although targeting adipose tissue metabolism holds promise as a potential approach for obesity treatment, further investigations are necessary to unravel the intricate biological features of various adipose tissue types and elucidate the molecular pathways governing their interconversion. Such research endeavors will pave the way for the development of more efficient and targeted therapeutic interventions in the fight against obesity.

A TrkB cleavage fragment in hippocampus promotes Depressive-Like behavior in mice.

Decreased hippocampal tropomyosin receptor kinase B (TrkB) level is implicated in the pathophysiology of stress-induced mood disorder and cognitive decline. However, how TrkB is modified and mediates behavioral responses to chronic stress remains largely unknown. Here the effects and mechanisms of TrkB cleavage by asparagine endopeptidase (AEP) were examined on a preclinical murine model of chronic restraint stress (CRS)-induced depression. CRS activated IL-1ß-C/EBPß-AEP pathway in mice hippocampus, accompanied by elevated TrkB 1-486 fragment generated by AEP. Specifi.c overexpression or suppression of AEP-TrkB axis in hippocampal CaMKIIα-positive cells aggravated or relieved depressive-like behaviors, respectively. Mechanistically, in addition to facilitating AMPARs internalization, TrkB 1-486 interacted with peroxisome proliferator-activated receptor-δ (PPAR-δ) and sequestered it in cytoplasm, repressing PPAR-δ-mediated transactivation and mitochondrial function. Moreover, co-administration of 7,8-dihydroxyflavone and a peptide disrupting the binding of TrkB 1-486 with PPAR-δ attenuated depression-like symptoms not only in CRS animals, but also in Alzheimer's disease and aged mice. These findings reveal a novel role for TrkB cleavage in promoting depressive-like phenotype.

A tau fragment links depressive-like behaviors and cognitive declines in Alzheimer's disease mouse models through attenuating mitochondrial function.

Introduction: Alzheimer's disease (AD) is the most prevalent neurodegenerative disease characterized by extracellular senile plaques including amyloid-ß peptides and intracellular neurofibrillary tangles consisting of abnormal Tau. Depression is one of the most common neuropsychiatric symptoms in AD, and clinical evidence demonstrates that depressive symptoms accelerate the cognitive deficit of AD patients. However, the underlying molecular mechanisms of depressive symptoms present in the process of AD remain unclear. Methods: Depressive-like behaviors and cognitive decline in hTau mice were induced by chronic restraint stress (CRS). Computational prediction and molecular experiments supported that an asparagine endopeptidase (AEP)-derived Tau fragment, Tau N368 interacts with peroxisome proliferator-activated receptor delta (PPAR-δ). Further behavioral studies investigated the role of Tau N368-PPAR-δ interaction in depressive-like behaviors and cognitive declines of AD models exposed to CRS. Results: We found that mitochondrial dysfunction was positively associated with depressive-like behaviors and cognitive deficits in hTau mice. Chronic stress increased Tau N368 and promoted the interaction of Tau N368 with PPAR-δ, repressing PPAR-δ-mediated transactivation in the hippocampus of mice. Then we predicted and identified the binding sites of PPAR-δ. Finally, inhibition of AEP, clearance of Tau N368 and pharmacological activation of PPAR-δ effectively alleviated CRS-induced depressive-like behaviors and cognitive decline in mice. Conclusion: These results demonstrate that Tau N368 in the hippocampus impairs mitochondrial function by suppressing PPAR-δ, facilitating the occurrence of depressive-like behaviors and cognitive decline. Therefore, our findings may provide new mechanistic insight in the pathophysiology of depression-like phenotype in mouse models of Alzheimer's disease.

INVESTIGATION OF ENVIRONMENTAL RADIOACTIVITY AT A DECOMMISSIONED URANIUM MINE IN SOUTHERN CHINA.

An environmental radioactivity survey was performed on a uranium mine that has been decommissioned for >10 y. According to the characteristics of this uranium mine, the relevant parameters, such as the surface-absorbed dose rate in air, the radon and radon progeny concentrations in the air, the radon exhalation rate from the soil surface and the concentrations of natural radionuclides in soil and surface water, were measured. The results show that the maximum annual effective doses of residents and employees in the uranium mine caused by radon and radon progenies inhalation were 1.48 and 1.74 mSv, respectively, and the maximum annual effective doses of residents and employees caused by gamma-ray external radiation were 1.16 and 1.32 mSv, respectively.