Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution of the Gut Microbiota to Intestinal Fibrosis in Crohn's Disease

In Crohn's disease (CD), intestinal fibrosis is a critical determinant of a patient's prognosis. Although inflammation may be a prerequisite for the initiation of intestinal fibrosis, research shows that the progression or continuation of intestinal fibrosis can occur independently of inflammation. Thus, once initiated, intestinal fibrosis may persist even if medical treatment controls inflammation. Clearly, an understanding of the pathophysiological mechanisms of intestinal fibrosis is required to diminish its occurrence. Accumulating evidence suggests that the gut microbiota contributes to the pathogenesis of intestinal fibrosis. For example, the presence of antibodies against gut microbes can predict which CD patients will have intestinal complications. In addition, microbial ligands can activate intestinal fibroblasts, thereby inducing the production of extracellular matrix. Moreover, in various animal models, bacterial infection can lead to the development of intestinal fibrosis. In this review, we summarize the current knowledge of the link between intestinal fibrosis in CD and the gut microbiota. We highlight basic science and clinical evidence that the gut microbiota can be causative for intestinal fibrosis in CD and provide valuable information about the animal models used to investigate intestinal fibrosis.
Cardiovascular Risk Prediction Parameters for Better Management in Rheumatic Diseases

The early detection of cardiovascular disease (CVD) serves as a key element in preventive cardiology. The risk of developing CVD in patients with rheumatic disease is higher than that of the general population. Thus, the objective of this narrative review was to assess and describe updated risk-prediction parameters for CVD in patients suffering from rheumatic diseases, and, additionally, to evaluate therapeutic and risk management possibilities. The processes of recognizing CVD risk factors in rheumatic diseases, establishing diagnoses, and discovering CV risk assessments are currently displeasing in clinical practice; they have a limited clinical impact. A large number of references were found while screening PUBMED, Scopus, and Google scholar databases; the 47 most relevant references were utilized to build up this study. The selection was limited to English language full text articles, RCTs, and reviews published between 2011 and 2021. Multiple imaging techniques, such as ECG, ultrasound, and cIMT, as well as biomarkers like osteoprotegerin cytokine receptor and angiopoietin-2, can be beneficial in both CV risk prediction and in early subclinical diagnosis. Physical exercise is an essential non-pharmacological intervention that can maintain the health of the cardiovascular system and, additionally, influence the underlying disease. Lipid-lowering drugs (methotrexate from the non-biologic DMARDs family as well as biologic DMARDs such as anti-TNF) were all associated with a lower CV risk; however, anti-TNF medication can decrease cardiac compliance and promote heart failure in patients with previously diagnosed chronic HF. Although they achieved success rates in reducing inflammation, glucocorticoids, NSAIDs, and COX-2 inhibitors were correlated with an increased risk of CVD. When taking all of the aforementioned points into consideration, there appears to be a dire need to establish and implement CVD risk stratification models in rheumatic patients.
Non-Invasive Monitoring of Human Health by Photoacoustic Spectroscopy

For certain diseases, the continuous long-term monitoring of the physiological condition is crucial. Therefore, non-invasive monitoring methods have attracted widespread attention in health care. This review aims to discuss the non-invasive monitoring technologies for human health based on photoacoustic spectroscopy. First, the theoretical basis of photoacoustic spectroscopy and related devices are reported. Furthermore, this article introduces the monitoring methods for blood glucose, blood oxygen, lipid, and tumors, including differential continuous-wave photoacoustic spectroscopy, microscopic photoacoustic spectroscopy, mid-infrared photoacoustic detection, wavelength-modulated differential photoacoustic spectroscopy, and others. Finally, we present the limitations and prospects of photoacoustic spectroscopy.
A Review on Antenna Technologies for Ambient RF Energy Harvesting and Wireless Power Transfer: Designs, Challenges and Applications

Radio frequency energy harvesting (RFEH) and wireless power transmission (WPT) are two emerging alternative energy technologies that have the potential to offer wireless energy delivery in the future. One of the key components of RFEH or WPT system is the receiving antenna. The receiving antenna’s performance has a considerable impact on the power delivery capability of an RFEH or WPT system. This paper provides a well-rounded review of recent advancements of receiving antennas for RFEH and WPT. Antennas discussed in this paper are categorized as low-profile antennas, multi-band antennas, circularly polarized antennas, and array antennas. A number of contemporary antennas from each category are presented, compared, and discussed with particular emphasis on design approach and performance. Current design and fabrication challenges, future development, open research issues of the antennas and visions for RFEH and WPT are also discussed in this review.
Research on quantitative multi-factor stock selection model based on machine learning

With the popularization of computer technology, the quantitative investment business in China has been developing rapidly, but it started late compared to the developed markets, and its related theories and applications have received very high attention in the investment field in China. In this paper, we focus on the effectiveness of multi-factor stock selection model applied to A-share market and use machine learning algorithms to improve the performance of the model. First, this paper selects 10 relatively independent valid factors from 44 candidate factors by validity testing and redundancy removal; second, builds a multifactor model and tests its validity, and introduces a hedging mechanism to further reduce the maximum retracement of the model; then changes the factor retracement period to select the model with the best effect for backtesting; finally, combines the AdaBoost algorithm with the multi-factor model and and the traditional Finally, the stock selection effect of combining AdaBoost algorithm with multi-factor model and and traditional multi-factor model is compared. The study finds that the machine learning AdaBoost [1] algorithm can enhance the stock selection effect of the traditional multi-factor model, and this study has a significant role in the future development of this field.
Enterprise Data Sharing with Privacy-Preserved Based on Hyperledger Fabric Blockchain in IIOT’s Application

Internet of Things (IoT) technology is now widely used in energy, healthcare, services, transportation, and other fields. With the increase in industrial equipment (e.g., smart mobile terminals, sensors, and other embedded devices) in the Internet of Things and the advent of Industry 4.0, there has been an explosion of data generated that is characterized by a high volume but small size. How to manage and protect sensitive private data in data sharing has become an urgent issue for enterprises. Traditional data sharing and storage relies on trusted third-party platforms or distributed cloud storage, but these approaches run the risk of single-node failure, and third parties and cloud storage providers can be vulnerable to attacks that can lead to data theft. To solve these problems, this paper proposes a Hyperledger Fabric blockchain-based secure data transfer scheme for enterprises in the Industrial Internet of Things (IIOT). We store raw data in the IIoT in the InterPlanetary File System (IPFS) network after encryption and store the Keyword-index table we designed in Hyperledger Fabric blockchain, and enterprises share the data by querying the Keyword-index table. We use Fabric’s channel mechanism combined with our designed Chaincode to achieve privacy protection and efficient data transmission while using the Elliptic Curve Digital Signature Algorithm (ECDSA) to ensure data integrity. Finally, we performed security analysis and experiments on the proposed scheme, and the results show that overall the data transfer performance in the IPFS network is generally better than the traditional network, In the case of transferring 5 MB file size data, the transmission speed and latency of IPFS are 19.23 mb/s and 0.26 s, respectively, and the IPFS network is almost 4 times faster than the TCP/IP network while taking only a quarter of the time, which is more advantageous when transferring small files, such as data in the IIOT. In addition, our scheme outperforms the blockchain systems mainly used today in terms of both throughput, latency, and system overhead. The average throughput of our solution can reach 110 tps (transactions are executed per second), and the minimum throughput in experimental tests can reach 101 tps.
Growth performance, carcass traits, muscle fiber characteristics and skeletal muscle mRNA abundance in hair lambs supplemented with ferulic acid

Abstract Ferulic acid (FA) is a phytochemical with various bioactive properties. It has recently been proposed that due to its phytogenic action it can be used as an alternative growth promoter additive to synthetic compounds. The objective of the present study was to evaluate the growth performance, carcass traits, fiber characterization and skeletal muscle gene expression on hair-lambs supplemented with two doses of FA. Thirty-two male lambs (n = 8 per treatment) were individually housed during a 32 d feeding trial to evaluate the effect of FA (300 and 600 mg d−1) or zilpaterol hydrochloride (ZH; 6 mg d−1) on growth performance, and then slaughtered to evaluate the effects on carcass traits, and muscle fibers morphometry from Longissimus thoracis (LT) and mRNA abundance of β2-adrenergic receptor (β2-AR), MHC-I, MHC-IIX and IGF-I genes. FA increased final weight and average daily gain with respect to non-supplemented animals (p < 0.05). The ZH supplementation increased LT muscle area, with respect to FA doses and control (p < 0.05). Cross-sectional area (CSA) of oxidative fibers was larger with FA doses and ZH (p < 0.05). Feeding ZH increased mRNA abundance for β2-AR compared to FA and control (p < 0.05), and expression of MHC-I was affected by FA doses and ZH (p < 0.05). Overall, FA supplementation of male hair lambs enhanced productive variables due to skeletal muscle hypertrophy caused by MHC-I up-regulation. Results suggest that FA has the potential like a growth promoter in lambs.
The AI Will See You Now: Feasibility and Acceptability of a Conversational AI Medical Interviewing System

Background Primary care physicians (PCPs) are often limited in their ability to collect detailed medical histories from patients, which can lead to errors or delays in diagnosis. Recent advances in artificial intelligence (AI) show promise in augmenting current human-driven methods of collecting personal and family histories; however, such tools are largely unproven. Objective The main aim of this pilot study was to evaluate the feasibility and acceptability of a conversational AI medical interviewing system among patients. Methods The study was conducted among adult patients empaneled at a family medicine clinic within a large academic medical center in Northern California. Participants were asked to test an AI medical interviewing system, which uses a conversational avatar and chatbot to capture medical histories and identify patients with risk factors. After completing an interview with the AI system, participants completed a web-based survey inquiring about the performance of the system, the ease of using the system, and attitudes toward the system. Responses on a 7-point Likert scale were collected and evaluated using descriptive statistics. Results A total of 20 patients with a mean age of 50 years completed an interview with the AI system, including 12 females (60%) and 8 males (40%); 11 were White (55%), 8 were Asian (40%), and 1 was Black (5%), and 19 had at least a bachelor’s degree (95%). Most participants agreed that using the system to collect histories could help their PCPs have a better understanding of their health (16/20, 80%) and help them stay healthy through identification of their health risks (14/20, 70%). Those who reported that the system was clear and understandable, and that they were able to learn it quickly, tended to be younger; those who reported that the tool could motivate them to share more comprehensive histories with their PCPs tended to be older. Conclusions In this feasibility and acceptability pilot of a conversational AI medical interviewing system, the majority of patients believed that it could help clinicians better understand their health and identify health risks; however, patients were split on the effort required to use the system, and whether AI should be used for medical interviewing. Our findings suggest areas for further research, such as understanding the user interface factors that influence ease of use and adoption, and the reasons behind patients’ attitudes toward AI-assisted history-taking.
Neutral and adaptive drivers of genomic change in introduced brook trout (Salvelinus fontinalis) populations revealed by pooled sequencing

Abstract Understanding the drivers of successful species invasions is important for conserving native biodiversity and for mitigating the economic impacts of introduced species. However, whole‐genome resolution investigations of the underlying contributions of neutral and adaptive genetic variation in successful introductions are rare. Increased propagule pressure should result in greater neutral genetic variation, while environmental differences should elicit selective pressures on introduced populations, leading to adaptive differentiation. We investigated neutral and adaptive variation among nine introduced brook trout (Salvelinus fontinalis) populations using whole‐genome pooled sequencing. The populations inhabit isolated alpine lakes in western Canada and descend from a common source, with an average of ~19 (range of 7–41) generations since introduction. We found some evidence of bottlenecks without recovery, no strong evidence of purifying selection, and little support that varying propagule pressure or differences in local environments shaped observed neutral genetic variation differences. Putative adaptive loci analysis revealed nonconvergent patterns of adaptive differentiation among lakes with minimal putatively adaptive loci (0.001%–0.15%) that did not correspond with tested environmental variables. Our results suggest that (i) introduction success is not always strongly influenced by genetic load; (ii) observed differentiation among introduced populations can be idiosyncratic, population‐specific, or stochastic; and (iii) conservatively, in some introduced species, colonization barriers may be overcome by support through one aspect of propagule pressure or benign environmental conditions.
Reactive, Proactive, and Inducible Proximal Crowd Robot Navigation Method based on Inducible Social Force Model

To smoothly and efficiently enable autonomous mobile robots to move in human crowd environments, path planning based on human movement-prediction, reactive movement toward human movement, and active motion-inducing physical interaction to avoid getting stuck are required. In this study, we developed a reactive, proactive, and inducible proximal crowd navigation (PCN) method that is based on a newly developed inducible social force model (i-SFM). The PCN first reactively generates multiple paths including avoidance, proximal, and inducible physical-touch paths based on the waypoint-i-SFM fused-path planning method, proactively predicts human movement based on i-SFM, selects an optimal path based on the movement cost including robot-movement efficiency and the crowd-invasion index (impulsive and touch forces applied to the humans), and finally reactively moves in the crowd based on the forces applied on it. The proposed PCN method works not only when the robot enters crowds but also when it is already in a crowd and avoids humans who enter the crowd, so we also applied our PCN method to both situations. Simulation and experimental results indicated that our PCN method can adequately predict the movement of human crowds and achieve higher movement efficiency without stuck, compared with a conventional non-proximal navigation method using the SFM.
In Vivo Evaluation of ECP Peptide Analogues for the Treatment of Acinetobacter baumannii Infection

Antimicrobial peptides (AMPs) are alternative therapeutics to traditional antibiotics against bacterial resistance. Our previous work identified an antimicrobial region at the N-terminus of the eosinophil cationic protein (ECP). Following structure-based analysis, a 30mer peptide (ECPep-L) was designed that combines antimicrobial action against Gram-negative species with lipopolysaccharides (LPS) binding and endotoxin-neutralization activities. Next, analogues that contain non-natural amino acids were designed to increase serum stability. Here, two analogues were selected for in vivo assays: the all-D version (ECPep-D) and the Arg to Orn version that incorporates a D-amino acid at position 2 (ECPep-2D-Orn). The peptide analogues retained high LPS-binding and anti-endotoxin activities. The peptides efficacy was tested in a murine acute infection model of Acinetobacter baumannii. Results highlighted a survival rate above 70% following a 3-day supervision with a single administration of ECPep-D. Moreover, in both ECPep-D and ECPep-2D-Orn peptide-treated groups, clinical symptoms improved significantly and the tissue infection was reduced to equivalent levels to mice treated with colistin, used as a last resort in the clinics. Moreover, treatment drastically reduced serum levels of TNF-α inflammation marker within the first 8 h. The present results support ECP-derived peptides as alternative candidates for the treatment of acute infections caused by Gram-negative bacteria.
Flowering Mechanisms and Environmental Stimuli for Flower Transition: Bases for Production Scheduling in Greenhouse Floriculture

The scheduling of plant production is a critical aspect in modern floriculture since nowadays, sales are not oriented toward the recurring holidays as in the past, but always more toward impulse buying, implying a more diverse and constant demand on the market. This requires continuous production, often regulated by precise commercial agreements between growers and buyers, and between buyers and dealers, particularly in large-scale retail trade. In this scenario, diverse techniques to modulate the duration of the growing cycle, by hastening or slowing down plant growth and development, have been developed to match plant flowering to the market demand. Among the numerous approaches, the manipulation of climatic parameters in the growth environment is one of the most common in greenhouse floriculture. In this review, we summarize the physiological and biochemical bases underlying the main mechanisms of flowering, depending on the plant reaction to endogenous signals or environmental stimuli. In addition, the strategies based on the control of temperature (before or after planting) and light environment (as light intensity and spectrum, and the photoperiod) in the scheduling of flower and ornamental crop production are briefly described.
Photosynthesis of an endolithic Chlorococcum alga (Chlorophyta, Chlorococcaceae) from travertine calcium carbonate rocks of a tropical limestone Spring

ABSTRACT A green alga, Chlorococcum sp. (Chlorococcales, Chlorophyceae), was grown from scrapings of the travertine rocks from the outlet stream of the Emerald Pool, Khlong Thom Nuea, Khlong Thom District Krabi province in Southern Thailand – a classic karstic stream habitat. It was a recalcitrant alga: organic solvents did not extract chlorophyll (Chl) from the algae very well but heated Dimethylsulphoxide (DMSO) was effective. Rapid light curve PAM experiments were used to quantify photosynthetic parameters: Eopt = 275 ± 9.7 µmol photons m–2 s–1, ETRmax = 277 ± 5.99 µmol e– g–1 Chl a s–1, photosynthetic efficiency (Alpha, α0) = 2.248 ± 0.112 e– g–1 Chl a. For Chlorococcum sp. deliberately grown in very low light, Eopt = 290 ± 4.89 µmol photons m–2 s–1 but ETRmax = 109 ± 0.97 µmol e– g–1 Chl a s–1, Alpha (α0) = 1.010 ± 0.192 e– g–1 Chl a. Overall, the amount of Chl b compared with Chl a was relatively low for most Chl a + b organisms (Chl b/a ≈ 0.21) but the ratio was not strongly affected by irradiance. The changes in ETRmax and α0 indicate that the Chlorococcum sp, responded to very low irradiance by increasing total Chl as Chl a, a marginal decrease in Chl b/a ratio but no substantial change in far-red absorption. The spectrum stripping technique confirmed Chlorococcum sp, is a Chl a + b organism albeit with a low Chl b content. Photosynthesis in this species was not very sensitive to pH in the range pH 5–9 but was inhibited at pH 10, indicating that it was very capable of using HCO3 – as an inorganic carbon source. Chlorococcum has a carbon concentrating mechanism (CCM), however based on its insensitivity to the depolarizing effects of high [K+], it is unlikely to be dependent on the membrane potential across the cell membrane. The alga is homiochlorophyllous and recovers rapidly from dessication without synthesis of new chlorophyll. Highlights The green unicellular alga Chlorococcum was found growing in travertine rock, Has Chl b/a ratio typical of green algae, contrasting with Ostreobium, Rapid light curves show optimum irradiance at about 300 µmol photons m–2 s–1, Chlorococcum has a carbon concentrating mechanism (CCM), Homiochlorophyllous alga quickly recovering from desiccation without synthesizing new chlorophyll.
Central Nervous System Stimulants Limit Caffeine Transport at the Blood–Cerebrospinal Fluid Barrier

Caffeine, a common ingredient in energy drinks, crosses the blood–brain barrier easily, but the kinetics of caffeine across the blood–cerebrospinal fluid barrier (BCSFB) has not been investigated. Therefore, 127 autopsy cases (Group A, 30 patients, stimulant-detected group; and Group B, 97 patients, no stimulant detected group) were examined. In addition, a BCSFB model was constructed using human vascular endothelial cells and human choroid plexus epithelial cells separated by a filter, and the kinetics of caffeine in the BCSFB and the effects of 4-aminopyridine (4-AP), a neuroexcitatory agent, were studied. Caffeine concentrations in right heart blood (Rs) and cerebrospinal fluid (CSF) were compared in the autopsy cases: caffeine concentrations were higher in Rs than CSF in Group A compared to Group B. In the BCSFB model, caffeine and 4-AP were added to the upper layer, and the concentration in the lower layer of choroid plexus epithelial cells was measured. The CSF caffeine concentration was suppressed, depending on the 4-AP concentration. Histomorphological examination suggested that choroid plexus epithelial cells were involved in inhibiting the efflux of caffeine to the CSF. Thus, the simultaneous presence of stimulants and caffeine inhibits caffeine transfer across the BCSFB.