Global Structure-Aware Diffusion Process for Low-Light Image Enhancement

This paper studies a diffusion-based framework to address the low-light image enhancement problem. To harness the capabilities of diffusion models, we delve into this intricate process and advocate for the regularization of its inherent ODE-trajectory. To be specific, inspired by the recent research that low curvature ODE-trajectory results in a stable and effective diffusion process, we formulate a curvature regularization term anchored in the intrinsic non-local structures of image data, i.e., global structure-aware regularization, which gradually facilitates the preservation of complicated details and the augmentation of contrast during the diffusion process. This incorporation mitigates the adverse effects of noise and artifacts resulting from the diffusion process, leading to a more precise and flexible enhancement. To additionally promote learning in challenging regions, we introduce an uncertainty-guided regularization technique, which wisely relaxes constraints on the most extreme regions of the image. Experimental evaluations reveal that the proposed diffusion-based framework, complemented by rank-informed regularization, attains distinguished performance in low-light enhancement. The outcomes indicate substantial advancements in image quality, noise suppression, and contrast amplification in comparison with state-of-the-art methods. We believe this innovative approach will stimulate further exploration and advancement in low-light image processing, with potential implications for other applications of diffusion models. The code is publicly available at https://github.com/jinnh/GSAD.Comment: Accepted to NeurIPS 202

Enhanced production of highly methylated brGDGTs linked to anaerobic bacteria from sediments of the Mariana Trench

Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are bacterial membrane lipids that are widely used in terrestrial paleoclimatic reconstructions. Recent studies have reported that brGDGTs can also be produced by marine bacteria. However, the environmental factors influencing marine-derived brGDGTs and their source organisms remain largely unknown. Here, we investigated the distribution and composition of brGDGTs and a suite of their putative derivatives called overly branched GDGTs (obGDGTs) in the Mariana Trench core sediments (water depth 8300 m, core length 320 cm), as well as the composition of bacterial communities. The ratio of the branched over isoprenoid tetraethers (BIT) was 0.03-0.21 (average 0.07; SD = 0.04; n = 21) and the ratio ΣIIIa/ΣIIa of brGDGTs was 0.93-7.47 (average 3.39; SD = 1.73; n = 21), which support the in situ production of brGDGTs. Co-occurrence network analysis revealed that a total of 33 types of bacteria at the order level (e.g., Armatimonadota DG-56, Proteobacteria Rhodospirillales, Chloroflexi SAR202_clade) were closely related to the distribution of brGDGTs and obGDGTs, which could be potential sources for these compounds. The abrupt increase in brGDGT and obGDGT concentrations in deeper oxygen-depleted sediments and their good correlations with anaerobic bacterial abundances suggest that these brGDGTs and obGDGTs may be produced by anaerobic bacteria residing in the anoxic sediments. Considerable variation in the degrees of methylation and cyclization of brGDGTs (obGDGTs) under different redox conditions indicate that sediment oxygen levels may have a profound impact on the presence and abundance of brGDGTs and obGDGTs, which should be considered when applying them for paleo-temperature or pH reconstructions. This study shows that brGDGTs and obGDGTs obtained from the Mariana Trench were probably produced by a variety of bacterial phyla indigenous in the hadal ocean, which are different from Acidobacteria commonly considered to be major terrestrial sources of brGDGTs

NLRP3 Inflammasome as a Molecular Marker in Diabetic Cardiomyopathy

Diabetic cardiomyopathy (DCM), a common consequence of longstanding diabetes mellitus, is initiated by death of cardiomyocyte. Hyperglycemia-induced reactive oxygen species (ROS) overproduction is a major contributor of the chronic low-grade inflammation that characterizes as the DCM. ROS may promote the activation of nucleotide-binding oligomerization domain like receptor (NLR) pyrin domain containing 3 (NLRP3) inflammasome, a novel regulator of inflammation and cell death, by nuclear factor-kB (NF-κB) and thioredoxin interacting/inhibiting protein (TXNIP). NLRP3 inflammasome regulates the death of cardiomyocyte and activation of fibroblast in DCM, which is involved in the structural and functional disorder of DCM. However, comprehensive understanding of molecular mechanisms linking NLRP3 inflammasome and disorder of cardiomyocyte and fibroblast in DCM is lacking. Here, we review the molecular mechanism(s) of NLRP3 inflammasome activation in response to hyperglycemia in DCM

Correlation Analysis Between Required Surgical Indexes and Complications in Patients With Coronary Heart Disease

A total of 215 patients with coronary heart disease (CHD) were analyzed with SPSS. Samples of different genders showed significance in the obtuse marginal branch of the left circumflex branch × 1, the diagonal branch D1 × 1, and the ms PV representation. Patients with left circumflex branch occlusion are more male and tend to be younger. Age displayed a positive correlation with left intima-media thickness (IMT) and right IMT. This indicated that as age increases, the values of left IMT and right IMT increase. Samples of different CHD types showed significance in the obtuse marginal branch of the left circumflex branch × 1, the middle part of RCA × 1, and the middle part of the left anterior descending branch × 1.5. For non-ST-segment elevation angina pectoris with acute total vascular occlusion, the left circumflex artery is the most common, followed by the right coronary artery and anterior descending branch. Ultrasound of carotid IMT in patients with CHD can predict changes in left ventricular function, but no specific correlation between left and right common carotid IMT was found. Samples with or without the medical history of ASCVD showed significance in the branch number of coronary vessel lesions. The value of the branch number of coronary vessel lesions in patients with atherosclerotic cardiovascular disease (ASCVD) was higher than in those without ASCVD. The occurrence of complication is significantly relative with the distance of left circumflex branch × 1, the middle segment of left anterior descending branch × 1.5, and the distance of left anterior descending branch × 1. For patients without complications, the values in the distal left circumflex branch × 1, the middle left anterior descending branch × 1.5, and the distal left anterior descending branch × 1 were higher than those for patients with complications. The VTE scores showed a positive correlation with the proximal part of RCA × 1, the branch number of coronary vessel lesions, the posterior descending branch of left circumflex branch × 1, the distal part of left circumflex branch × 1, and the middle part of left anterior descending branch × 1.5

An integrative multi-platform analysis for discovering biomarkers of osteosarcoma

<p>Abstract</p> <p>Background</p> <p>SELDI-TOF-MS (Surface Enhanced Laser Desorption/Ionization-Time of Flight-Mass Spectrometry) has become an attractive approach for cancer biomarker discovery due to its ability to resolve low mass proteins and high-throughput capability. However, the analytes from mass spectrometry are described only by their mass-to-charge ratio (<it>m</it>/<it>z</it>) values without further identification and annotation. To discover potential biomarkers for early diagnosis of osteosarcoma, we designed an integrative workflow combining data sets from both SELDI-TOF-MS and gene microarray analysis.</p> <p>Methods</p> <p>After extracting the information for potential biomarkers from SELDI data and microarray analysis, their associations were further inferred by link-test to identify biomarkers that could likely be used for diagnosis. Immuno-blot analysis was then performed to examine whether the expression of the putative biomarkers were indeed altered in serum from patients with osteosarcoma.</p> <p>Results</p> <p>Six differentially expressed protein peaks with strong statistical significances were detected by SELDI-TOF-MS. Four of the proteins were up-regulated and two of them were down-regulated. Microarray analysis showed that, compared with an osteoblastic cell line, the expression of 653 genes was changed more than 2 folds in three osteosarcoma cell lines. While expression of 310 genes was increased, expression of the other 343 genes was decreased. The two sets of biomarkers candidates were combined by the link-test statistics, indicating that 13 genes were potential biomarkers for early diagnosis of osteosarcoma. Among these genes, cytochrome c1 (CYC-1) was selected for further experimental validation.</p> <p>Conclusion</p> <p>Link-test on datasets from both SELDI-TOF-MS and microarray high-throughput analysis can accelerate the identification of tumor biomarkers. The result confirmed that CYC-1 may be a promising biomarker for early diagnosis of osteosarcoma.</p

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Parallel multigrid preconditioning on graphics processing units (GPUs) for robust power grid analysis

Leveraging the power of nowadays graphics processing units for robust power grid simulation remains a challenging task. Existing preconditioned iterative methods that require in-complete matrix factorizations can not be effectively accel-erated on GPU due to its limited hardware resource as well as data parallel computing. This work presents an efficient GPU-based multigrid preconditioning algorithm for robust power grid analysis. An ELL-like sparse matrix data struc-ture is adopted and implemented specifically for power grid analysis to assure coalesced GPU device memory access and high arithmetic intensity. By combining the fast geometrical multigrid solver with the robust Krylov-subspace iterative solver, power grid DC and transient analysis can be per-formed efficiently on GPU without loss of accuracy (largest errors &lt; 0.5 mV). Unlike previous GPU-based algorithms that rely on good power grid regularities, the proposed algo-rithm can be applied for more general power grid structures. Experimental results show that the DC and transient analy-sis on GPU achieves more than 25X speedups over the best available CPU-based solvers. An industrial power grid with 10.5 million nodes can be accurately solved in 12 seconds