NIR Hyperspectral Imaging for Mapping of Moisture Content Distribution in Tea Buds during Dehydration

This work employed hyperspectral imaging technique to map the spatial distribution of moisture content (MC) in tea buds during dehydration. Hyperspectral images (874–1734 nm) of tea buds were acquired in six dehydrated periods (0, 3, 6, 9, 14 and 21 min) at 80°C. The spectral reflectance of tea buds were extracted from region of interests (ROIs) in the hyperspectral images. Competitive adaptive reweighted sampling (CARS) was used to select effective wavelengths (EWs) and ten representing the wavelengths were selected. The quantitative relationship between spectral reflectance and the measured MC values of tea buds was built using partial least square regression (PLSR) based on full spectra and EWs. The quantitative model established using EWs, which had a result of coefficient of correlation (RP) of 0.941 and root mean square error of prediction (RMSEP) of 5.31%, was considered as the optimal model for mapping MC distribution. The optimal model was finally applied to predict the MC of each pixel within of the tea bud sample and built the MC distribution maps by utilization of a developed image processing procedure. Results demonstrated that the hyperspectral imaging technique has the potential of mapping the MC spatial distribution in tea buds in dehydrated process

Human Preference Score: Better Aligning Text-to-Image Models with Human Preference

Recent years have witnessed a rapid growth of deep generative models, with text-to-image models gaining significant attention from the public. However, existing models often generate images that do not align well with human preferences, such as awkward combinations of limbs and facial expressions. To address this issue, we collect a dataset of human choices on generated images from the Stable Foundation Discord channel. Our experiments demonstrate that current evaluation metrics for generative models do not correlate well with human choices. Thus, we train a human preference classifier with the collected dataset and derive a Human Preference Score (HPS) based on the classifier. Using HPS, we propose a simple yet effective method to adapt Stable Diffusion to better align with human preferences. Our experiments show that HPS outperforms CLIP in predicting human choices and has good generalization capability toward images generated from other models. By tuning Stable Diffusion with the guidance of HPS, the adapted model is able to generate images that are more preferred by human users. The project page is available here: https://tgxs002.github.io/align_sd_web/ .Comment: Accepted by ICCV 202

A Blue Native-PAGE analysis of membrane protein complexes in Clostridium thermocellum

Background Clostridium thermocellum is a Gram-positive thermophilic anaerobic bacterium with the unusual capacity to convert cellulosic biomass into ethanol and hydrogen. Identification and characterization of protein complexes in C. thermocellum are important toward understanding its metabolism and physiology. Results A two dimensional blue native/SDS-PAGE procedure was developed to separate membrane protein complexes of C. thermocellum. Proteins spots were identified by MALDI-TOF/TOF Mass spectrometry. 24 proteins were identified representing 13 distinct protein complexes, including several putative intact complexes. Interestingly, subunits of both the F1-F0-ATP synthase and the V1-V0-ATP synthase were detected in the membrane sample, indicating C. thermocellum may use alternative mechanisms for ATP generation. Conclusion Two dimensional blue native/SDS-PAGE was used to detect membrane protein complexes in C. thermocellum. More than a dozen putative protein complexes were identified, revealing the simultaneous expression of two sets of ATP synthase. The protocol developed in this work paves the way for further functional characterization of these protein complexes

Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Recent text-to-image generative models can generate high-fidelity images from text inputs, but the quality of these generated images cannot be accurately evaluated by existing evaluation metrics. To address this issue, we introduce Human Preference Dataset v2 (HPD v2), a large-scale dataset that captures human preferences on images from a wide range of sources. HPD v2 comprises 798,090 human preference choices on 433,760 pairs of images, making it the largest dataset of its kind. The text prompts and images are deliberately collected to eliminate potential bias, which is a common issue in previous datasets. By fine-tuning CLIP on HPD v2, we obtain Human Preference Score v2 (HPS v2), a scoring model that can more accurately predict human preferences on generated images. Our experiments demonstrate that HPS v2 generalizes better than previous metrics across various image distributions and is responsive to algorithmic improvements of text-to-image generative models, making it a preferable evaluation metric for these models. We also investigate the design of the evaluation prompts for text-to-image generative models, to make the evaluation stable, fair and easy-to-use. Finally, we establish a benchmark for text-to-image generative models using HPS v2, which includes a set of recent text-to-image models from the academic, community and industry. The code and dataset is available at https://github.com/tgxs002/HPSv2 .Comment: Revisio

Integrated Multilayer Omics Reveals the Genomic, Proteomic, and Metabolic Influences of Histidyl Dipeptides on the Heart

Background: Histidyl dipeptides such as carnosine are present in a micromolar to millimolar range in mammalian hearts. These dipeptides facilitate glycolysis by proton buffering. They form conjugates with reactive aldehydes, such as acrolein, and attenuate myocardial ischemia-reperfusion injury. Although these dipeptides exhibit multifunctional properties, a composite understanding of their role in the myocardium is lacking. Methods and Results: To identify histidyl dipeptide-mediated responses in the heart, we used an integrated triomics approach, which involved genome-wide RNA sequencing, global proteomics, and unbiased metabolomics to identify the effects of cardiospecific transgenic overexpression of the carnosine synthesizing enzyme, carnosine synthase (Carns), in mice. Our result showed that higher myocardial levels of histidyl dipeptides were associated with extensive changes in the levels of several microRNAs, which target the expression of contractile proteins, β-fatty acid oxidation, and citric acid cycle (TCA) enzymes. Global proteomic analysis showed enrichment in the expression of contractile proteins, enzymes of β-fatty acid oxidation, and the TCA in the Carns transgenic heart. Under aerobic conditions, the Carns transgenic hearts had lower levels of short- and long-chain fatty acids as well as the TCA intermediate-succinic acid; whereas, under ischemic conditions, the accumulation of fatty acids and TCA intermediates was significantly attenuated. Integration of multiple data sets suggested that β-fatty acid oxidation and TCA pathways exhibit correlative changes in the Carns transgenic hearts at all 3 levels. Conclusions: Taken together, these findings reveal a central role of histidyl dipeptides in coordinated regulation of myocardial structure, function, and energetics

The Effect of Chinese Herbal Medicine on Albuminuria Levels in Patients with Diabetic Nephropathy: A Systematic Review and Meta-Analysis

To evaluate the effect of Chinese herbal medicine (CHM) on albuminuria levels in patients with diabetic nephropathy (DN), we performed comprehensive searches on Medline database, Cochrane Library, CNKI database, CBM database, Wanfang database, and VIP database up to December 2012. A total of 29 trials including 2440 participants with DN met the selection criteria. CHM was tested to be more effective in reducing urinary albumin excretion rate (UAER) (MD −82.95 μg/min, [−138.64, −27.26]) and proteinuria (MD −565.99 mg/24 h, [−892.41, −239.57]) compared with placebo. CHM had a greater beneficial effect on reduction of UAER (MD −13.41 μg/min, [−20.63, −6.19]) and proteinuria (MD −87.48 mg/24 h, [−142.90, −32.06]) compared with angiotensin converting enzyme inhibitors (ACEI) or angiotensin receptor blockers (ARB). Combination therapy with CHM and ACEI/ARB showed significant improvement in UAER (MD −28.18 μg/min, [−44.4, −11.97]), urinary albumin-creatinine ratio (MD −347.00, [−410.61, −283.39]), protein-creatinine ratio (MD −2.49, [−4.02, −0.96]), and proteinuria (MD −26.60 mg/24 h, [−26.73, −26.47]) compared with ACEI/ARB alone. No serious adverse events were reported. CHM seems to be an effective and safe therapy option to treat proteinuric patients with DN, suggesting that further study of CHM in the treatment of DN is warranted in rigorously designed, multicentre, large-scale trials with higher quality worldwide

MicroRNA Expression Analysis in the Cellulosic Biofuel Crop Switchgrass (Panicum virgatum) under Abiotic Stress

Switchgrass has increasingly been recognized as a dedicated biofuel crop for its broad adaptation to marginal lands and high biomass. However, little is known about the basic biology and the regulatory mechanisms of gene expression in switchgrass, particularly under stress conditions. In this study, we investigated the effect of salt and drought stress on switchgrass germination, growth and the expression of small regulatory RNAs. The results indicate that salt stress had a gradual but significant negative effect on switchgrass growth and development. The germination rate was significantly decreased from 82% for control to 36% under 1% NaCl treatment. However, drought stress had little effect on the germination rate but had a significant effect on the growth of switchgrass under the severest salinity stress. Both salt and drought stresses altered the expression pattern of miRNAs in a dose-dependent manner. However, each miRNA responded to drought stress in a different pattern. Salt and drought stress changed the expression level of miRNAs mainly from 0.9-fold up-regulation to 0.7-fold down-regulation. miRNAs were less sensitive to drought treatment than salinity treatment, as evidenced by the narrow fold change in expression levels. Although the range of change in expression level of miRNAs was similar under salt and drought stress, no miRNAs displayed significant change in expression level under all tested salt conditions. Two miRNAs, miR156 and miR162, showed significantly change in expression level under high drought stress. This suggests that miR156 and miR162 may attribute to the adaption of switchgrass to drought stress and are good candidates for improving switchgrass as a biofuel crop by transgenic technology