Miracle-dz/UniFAR-FTUs huggingface dataset:
Gut Microbiome and Metabolome Modulation by High-Hydrostatic-Pressure-Processed Tomato Juice

High hydrostatic pressure (HHP) is a non-thermal pasteurization technology for the enhancement of food products’ safety and quality. The components of tomato juice can be affected by HHP processing. Little is known about the effects of HHP-processed tomato juice on the gut microbiome and metabolism. Here, we performed high-throughput sequencing and metabolomics profiling to determine the critical differences in gut microbiota structure and metabolic profiles in mice administered with HHP-processed tomato juice. Tomato juice administration significantly increased the gut bacterial alpha diversity and the relative abundance of Bacteroides. The mice administered with HHP-processed tomato juice were characterized by the enrichment of Bacteroidetes, Alistieps, and Faecalibaculum compared with those administered with HTST-processed tomato juice. Moreover, HHP-processed tomato juice promoted SCFA levels, which were positively correlated with the enriched Alistieps. Our results show that HHP-processed tomato juice may drive healthy gut microbes and metabolites.
Sub-pixel Edge Detection of Cubic Spline in HSV Color Space

In the process of image position and detection, the pixel-level edge image sometimes cannot meet the demand, which requires more precise sub-pixel edge detection technology. This article detected the pixel-level edge image using the sin cos HSV  color distance model in HSV space firstly, then obtained the sub-pixel edge image using Cubic spline to interpolate, and made a comparative study with B-spline to their results. The results showed that the entropy of the sub-pixel image is richer than the pixel-level image, and Cubic spline is better than B-spline.
An FPGA-based implementation of corner detection and matching with outlier rejection

ABSTRACT To meet the high frame rate requirements of correct point correspondences with a sub-pixel precision, this paper first proposes a Field Programmable Gate Array (FPGA) architecture that consists of corner detection, corner matching, outlier rejection, and sub-pixel precision localisation. In the architecture, a combined Features from Accelerated Segment Test (FAST)+ Binary Robust Independent Elementary Features (BRIEF) algorithm is adopted for detection and matching with pixel precision, a combined algorithm of Slope-based Rejection (SR) and Correlation-Coefficient-based Rejection (CCR) is used to reject the outliers, and a gradient centroid-based algorithm is used for sub-pixel precision localisation. The whole FPGA architecture is implemented on a single FPGA platform (Xilinx XC72K325T). Five image datasets with different spatial resolutions, textures, lights, rotate angles, and viewpoints are used to evaluate the performance of the FPGA-based implementation. The experimental results show that (1) the SR and CCR algorithms are effective for outlier rejection; (2) a higher correct matching rate is achieved for the image pairs that cover artificial textures than for those that cover natural textures; (3) the proposed architecture is also suitable for image pairs with small change of lights, rotate angles, and viewpoints; (4) the speed of the FPGA-based implementation can reach 280 Frames Per Second (FPS), which is 35 times faster than the Personal Computer (PC)-based implementation; and (5) the usage of FPGA resources is acceptable for the selected FPGA platform. The speed and usage of the FPGA resources can be improved when the whole FPGA-based implementation is further optimised.
The Interaction between Anesthetic Isoflurane and Model-Biomembrane Monolayer Using Simultaneous Quartz Crystal Microbalance (QCM) and Quartz Crystal Impedance (QCI) Methods

The interaction between anesthetic Isoflurane (Iso) and model-biomembrane on the water surface has been investigated using quartz crystal microbalance (QCM) and quartz crystal impedance (QCI) methods. The model-biomembranes used were dipalmitoyl phosphatidyl choline (DPPC), DPPC-palmitic acid (PA) mixture (DPPC:PA = 8:2), DPPC-Alamethicin (Al) mixture (DPPC:Al = 39:1), and DPPC-β-Lactoglobulin (βLG) mixture (DPPC:βLG = 139:1) monolayers, respectively. The quartz crystal oscillator (QCO) was attached horizontally to each monolayer, and QCM and QCI measurements were performed simultaneously. It was found that Iso hydrate physisorbed on each monolayer/water interface from QCM and changed those interfacial viscosities from QCI. With an increase in Iso concentration, pure DPPC, DPPC-PA mixed, and DPPC-Al mixed monolayers showed a two-step process of Iso hydrate on both physisorption and viscosity, whereas it was a one-step for the DPPC-βLG mixed monolayer. The viscosity change in the DPPC-βLG mixed monolayer with the physisorption of Iso hydrate was much larger than that of other monolayers, in spite of the one-step process. From these results, the action mechanism of anesthetics and their relevance to the expression of anesthesia were discussed, based on the “release of interfacial hydrated water” hypothesis on the membrane/water interface.
Chilean Supreme Court ruling on the protection of brain activity: neurorights, personal data protection, and neurodata

This paper discusses a landmark ruling by the Chilean Supreme Court of August 9, 2023 dealing with the right to mental privacy, originated with an action for constitutional protection filed on behalf of Guido Girardi Lavin against Emotiv Inc., a North American company based in San Francisco, California that is commercializing the device “Insight. ” This wireless device functions as a headset with sensors that collect information about the brain’s electrical activity (i.e., neurodata). The discussion revolves around whether neurodata can be considered personal data and whether they could be classified into a special category. The application of the present legislation on data (the most obsolete, such as the Chilean law, and the most recent EU law) does not seem adequate to protect neurodata. The use of neurodata raises ethical and legal concerns that are not fully addressed by current regulations on personal data protection. Despite not being necessarily considered personal data, neurodata represent the most intimate aspects of human personality and should be protected in light of potential new risks. The unique characteristics of neurodata, including their interpretive nature and potential for revealing thoughts and intentions, pose challenges for regulation. Current data protection laws do not differentiate between different types of data based on their informational content, which is relevant for protecting individual rights. The development of new technologies involving neurodata requires particular attention and careful consideration to prevent possible harm to human dignity. The regulation of neurodata must account for their specific characteristics and the potential risks they pose to privacy, confidentiality, and individual rights. The answer lies in the reconfiguration of human rights known as “neurorights” that goes beyond the protection of personal data.
Integrating ecosystem services evaluation and landscape pattern analysis into urban planning based on scenario prediction and regression model

ABSTRACT Urban planning has become a widely concern for minimizing the negative effects of urban expansion on terrestrial ecosystems. We developed an interdisciplinary modeling framework to evaluate the effectiveness and shortcomings of urban expansion management strategies. A three-step method was applied to Yinchuan Plain in the northwestern of China, including (1) analyzing the relationship between landscape pattern and ecosystem service values through mathematical statistics; (2) predicting landscape pattern and ecosystem services change under different scenarios based on cellular automaton model (SLEUTH-3r model); and (3) designing and validating optimized scenario through integrating historical analysis experiments and future multi-comparison suggestions. Results have suggested that landscape composition and configuration can significantly affect regional ecosystem service values, especially the connectivity and shape of landscape. Compact urban growth policy and medium environment protection policy are the appropriate setting for urban expansion plan. Optimization validation of the combined designed scenario implied the reliability of this method. Our results highlighted the significance of integrating application of landscape pattern analysis, ecosystem service value evaluation, model simulation and multi-scenario prediction in urban planning.
Evidence of Subduction‐Related Thermal and Compositional Heterogeneity Below the United States From Transition Zone Receiver Functions

The subduction of the Farallon Plate has altered the temperature and composition of the mantle transition zone (MTZ) beneath the United States. We investigate MTZ structure by mapping P‐to‐S conversions at mineralogical phase changes using USArray waveform data and theoretical seismic profiles based on experimental constraints of phase transition properties as a function of temperature and composition. The width of the MTZ varies by about 35 km over the study region, corresponding to a temperature variation of more than 300 K. The MTZ is coldest and thickest beneath the eastern United States where high shear velocity anomalies are tomographically resolved. We detect intermittent P‐to‐S conversions at depths of 520 km and 730 km. The conversions at 730‐km depth are coherent beneath the southeastern United States and are consistent with basalt enrichment of about 50%, possibly due to the emplacement of a fragment of an oceanic plateau (i.e., the Hess conjugate).
Comparison of Health Behaviors of Healthcare Workers and the General Public in Israel: A Cross-Sectional Survey

Healthcare workers (HCWs) are role models and advisors for promoting health behaviors among their patients. We conducted a cross-sectional survey to identify and compare the health behaviors of 105 HCWs and 82 members of the Israeli public. Of 13 health behaviors examined, undergoing screening tests, getting influenza vaccines and smoking were significantly different between the HCWs and the public. Further comparison between physicians and other HCWs (e.g., nurses, physiotherapists, dieticians) showed that the physicians reported the least favorable health behaviors: having less than 7 h of sleep, being less likely to eat breakfast, having greater alcohol consumption and being least likely to undergo regular screening tests. Analysis of a composite healthy lifestyle score (which included 11 health behaviors) showed statistically significant differences among the three groups (p = 0.034): only 10.6% of the physicians had a high healthy lifestyle score compared to the other HCWs (34.5%). In conclusion, the HCWs and the public report suboptimal health behaviors. Beyond the concern for HCWs’ personal health, their health behaviors have implications for the health of patients and the general public, as they play an important role in health promotion and counseling. HCWs’ suboptimal “health profile” mandates implementing policies to improve their knowledge of recommended health behaviors, primarily targeting physicians, even at an early phase of their professional journey.
The National Carbon Capture Center at the Power Systems Development Facility

The National Carbon Capture Center (NCCC) at the Power Systems Development Facility supports the Department of Energy (DOE) goal of promoting the United States’ energy security through reliable, clean, and affordable energy produced from coal. Work at the NCCC supports the development of new power technologies and the continued operation of conventional power plants under CO2 emission constraints. The NCCC includes adaptable slipstreams that allow technology development of CO2 capture concepts using coal-derived syngas and flue gas in industrial settings. Because of the ability to operate under a wide range of flow rates and process conditions, research at the NCCC can effectively evaluate technologies at various levels of maturity and accelerate their development path to commercialization. During its first contract period, from October 1, 2008, through December 30, 2014, the NCCC designed, constructed, and began operation of the Post-Combustion Carbon Capture Center (PC4). Testing of CO2 capture technologies commenced in 2011, and through the end of the contract period, more than 25,000 hours of testing had been achieved, supporting a variety of technology developers. Technologies tested included advanced solvents, enzymes, membranes, sorbents, and associated systems. The NCCC continued operation of the existing gasification facilities, which have been in operation since 1996, to support the advancement of technologies for next-generation gasification processes and pre-combustion CO2 capture. The gasification process operated for 13 test runs, supporting over 30,000 hours combined of both gasification and pre-combustion technology developer testing. Throughout the contract period, the NCCC incorporated numerous modifications to the facilities to accommodate technology developers and increase test capabilities. Preparations for further testing were ongoing to continue advancement of the most promising technologies for future power generation processes.
Land Cover Mapping From Multiple Complementary Experts Under Heavy Class Imbalance

Deep learning has emerged as a promising avenue for automatic mapping, demonstrating high efficacy in land cover categorization through various semantic segmentation models. Nonetheless, the practical deployment of these models encounters important challenges from the imbalanced distribution of samples between the classes, a problem inherent to real-world datasets. This results in models biased towards frequent classes that perform poorly on rare classes. While existing approaches to fight class imbalance mainly focus on image classification, here we propose to address this issue for semantic segmentation with a multiple complementary experts (MCE) structure. Taking inspiration from ensemble models, each expert in our MCE specializes in certain classes and works with other experts in a complementary manner to generate robust predictions for rare classes. We compare our approach to other existing methods and also explore different logit aggregation methods, to identify the performance upper bounds and improvement directions. Our model is evaluated on a large-scale and challenging alpine land cover dataset that we make openly available. In addition, we evaluated our model on an imbalanced land cover mapping dataset, FLAIR, to highlight its adaptability. Overall, our MCE model yields notable improvement in performances on the medium and rare classes compared to baseline methods, while only slightly compromising on the overall accuracy. Despite its simplicity, the MCE approach stands as a practical solution for more operational semantic segmentation models, not trading off performances on rare but important classes.
The ATPase Inhibitory Factor 1 (IF1) Contributes to the Warburg Effect and Is Regulated by Its Phosphorylation in S39 by a Protein Kinase A-like Activity

Simple Summary The ATPase Inhibitory Factor 1 (IF1) plays a prominent role as an inhibitor of mitochondrial ATP synthase. Herein we review the role of IF1 in promoting the Warburg effect and the relevance of its phosphorylation by protein kinase A (PKA) to block its activity as inhibitor of ATP synthase. Our results are supported by other independent studies and highlight the involvement of IF1 in metabolic reprogramming to promote an augmented glycolytic phenotype under aerobic conditions by exerting its inhibitory action on a fraction of ATP synthase present in the mitochondrion. The phosphorylation in vivo of IF1 at S39 by a mitochondrial c-AMP-dependent PKA activity prevents its interaction with ATP synthase. Finally, we stress that IF1 not only can play a cancer-promoting role but also can prevent metastatic disease in some carcinomas. Abstract The relevant role played by the ATPase Inhibitory Factor 1 (IF1) as a physiological in vivo inhibitor of mitochondrial ATP synthase in cancer and non-cancer cells, and in the mitochondria of different mouse tissues, as assessed in different genetic loss- and gain-of-function models of IF1 has been extensively documented. In this review we summarize our findings and those of others that favor the implication of IF1 in metabolic reprogramming to an enhanced glycolytic phenotype, which is mediated by its binding and inhibition of the ATP synthase. Moreover, we emphasize that IF1 is phosphorylated in vivo in its S39 by the c-AMP-dependent PKA activity of mitochondria to render an inactive inhibitor that is unable to interact with the enzyme, thus triggering the activation of ATP synthase. Overall, we discuss and challenge the results that argue against the role of IF1 as in vivo inhibitor of mitochondrial ATP synthase and stress that IF1 cannot be regarded solely as a pro-oncogenic protein because in some prevalent carcinomas, it prevents metastatic disease.
Identification of New Modulators and Inhibitors of Palmitoyl-Protein Thioesterase 1 for CLN1 Batten Disease and Cancer

Palmitoyl-protein thioesterase 1 (PPT1) is an understudied enzyme that is gaining attention due to its role in the depalmitoylation of several proteins involved in neurodegenerative diseases and cancer. PPT1 is overexpressed in several cancers, specifically cholangiocarcinoma and esophageal cancers. Inhibitors of PPT1 lead to cell death and have been shown to enhance the killing of tumor cells alongside known chemotherapeutics. PPT1 is hence a viable target for anticancer drug development. Furthermore, mutations in PPT1 cause a lysosomal storage disorder called infantile neuronal ceroid lipofuscinosis (CLN1 disease). Molecules that can inhibit, stabilize, or modulate the activity of this target are needed to address these diseases. We used PPT1 enzymatic assays to identify molecules that were subsequently tested by using differential scanning fluorimetry and microscale thermophoresis. Selected compounds were also tested in neuroblastoma cell lines. The resulting PPT1 screening data was used for building machine learning models to help select additional compounds for testing. We discovered two of the most potent PPT1 inhibitors reported to date, orlistat (IC50 178.8 nM) and palmostatin B (IC50 11.8 nM). When tested in HepG2 cells, it was found that these molecules had decreased activity, indicating that they were likely not penetrating the cells. The combination of in vitro enzymatic and biophysical assays enabled the identification of several molecules that can bind or inhibit PPT1 and may aid in the discovery of modulators or chaperones. The molecules identified could be used as a starting point for further optimization as treatments for other potential therapeutic applications outside CLN1 disease, such as cancer and neurological diseases.
Food Waste and Lunar Phases: Evidence from a Randomized Controlled Trial

To examine a potential correlation between food waste and lunar phases, we have devised a randomized controlled trial. The experiment spanned from 31 March to 10 July 2022, during which we employed the direct weighing method to collect 1903 valid data points on food waste. Utilizing propensity score matching, we meticulously controlled for various factors, including dining dates, the number of diners, dining times, spending levels, and store activities. The study revealed a close relationship between lunar phases and food waste. During the new moon phase, there was an increase in both orders and waste generated by consumers. Specifically, individuals, on average, squandered an additional 6.27% of animal protein (0.79 g), 24.5% of plant protein (1.26 g), 60.95% of starchy foods (3.86 g), and 61.09% of vegetables (5.12 g), resulting in an aggregate food waste of 32.14% (10.79 g). Conversely, during the full moon phase, consumers decreased their orders and subsequently decreased food waste. On average, individuals wasted 44.65% less animal protein (5.76 g), 43.36% less plant protein (2.5 g), 85.39% less seafood (0.73 g), and 8.43% less vegetables (0.93 g), resulting in a 20.52% (7.81 g) reduction in food waste. Furthermore, we validated our conclusions through various validation methods, including model replacement, to ensure robustness and reliability.
Inspecting mother-to-infant microbiota transmission: disturbance of strain inheritance by cesarian section

Introduction The initial acquisition and subsequent development of the microbiota in early life is crucial to future health. Cesarean-section (CS) birth is considered to affect early microbial transmission from mother to infant. Methods In this study, we collected fecal samples from 34 CS infants and their mothers from West China Second Hospital, Sichuan University to assess the microbiota developmental trajectory of mothers and infants. We explored mother-infant gut microbiome transmission via comparison with corresponding Finnish data. Results Metagenomic analysis of gut microbiota profiles indicated that the communities of mothers and infants were distinct. The composition of the infant gut microbiome was highly variable but also followed predictable patterns in the early stages of life. Maternal communities were stable and mainly dominated by species from Bacteroidacea spp. We used PStrain to analyze and visualize strain transmission in each mother-infant pair. Excluding missing data, we included 32 mother-infant pairs for analysis of strain transmission. Most CS deliveries (65.6%, 21/32) did not demonstrate transmission of strains from mother to infant. To further explore the mother-infant strain transmission, we analyzed metagenomics data from Finnish mother-infant pairs. A total of 32 mother-infant pairs were included in the analysis, including 28 vaginal delivery (VD) infants and four CS infants. Strain transmission was observed in 30 infants, including 28 VD infants and two CS infants. All VD infants received transmitted stains from their mothers. Finally, a total of 193 strain transmission events were observed, comprising 131 strains and 45 species. Discussion Taken together, our data suggested that delivery mode was an important factor influencing the mother-infant strain transmission.
We can help us: Does Community Resilience Buffer Against the Negative Impact of
Flooding on Mental Health?

Abstract. Empirical evidence on the relationship between social support and post-disaster mental health provides support for a general beneficial effect of social support (main-effect model; Wheaton, 1985). From a theoretical perspective, a buffering effect of social support on the relationship between disaster-related stress and mental health also seems plausible (stress-buffering-model; ibid.). Previous studies however a) have paid less attention to the buffering effect of social support and b) they have mainly relied on interpersonal support (but not collective-level support such as community resilience) when investigating this issue. This work might has underestimated the effect of support on post-disaster mental health. Building on a sample of residents in Germany recently affected by flooding (N = 118), we show that community resilience to flooding (but not general interpersonal social support) buffered against the negative effects of flooding on post-disaster mental health. The results support the stress-buffering model and call for a more detailed look at the relationship between support/resilience and post-disaster adjustment, including collective-level variables.