Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in Gut Microbiota and Multiple Sclerosis: A Systematic Review

Introduction: Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative disease mediated by autoimmune reactions against myelin proteins and gangliosides in the grey and white matter of the brain and spinal cord. It is considered one of the most common neurological diseases of non-traumatic origin in young people, especially in women. Recent studies point to a possible association between MS and gut microbiota. Intestinal dysbiosis has been observed, as well as an alteration of short-chain fatty acid-producing bacteria, although clinical data remain scarce and inconclusive. Objective: To conduct a systematic review on the relationship between gut microbiota and multiple sclerosis. Method: The systematic review was conducted in the first quarter of 2022. The articles included were selected and compiled from different electronic databases: PubMed, Scopus, ScienceDirect, Proquest, Cochrane, and CINAHL. The keywords used in the search were: “multiple sclerosis”, “gut microbiota”, and “microbiome”. Results: 12 articles were selected for the systematic review. Among the studies that analysed alpha and beta diversity, only three found significant differences with respect to the control. In terms of taxonomy, the data are contradictory, but confirm an alteration of the microbiota marked by a decrease in Firmicutes, Lachnospiraceae, Bifidobacterium, Roseburia, Coprococcus, Butyricicoccus, Lachnospira, Dorea, Faecalibacterium, and Prevotella and an increase in Bacteroidetes, Akkermansia, Blautia, and Ruminocococcus. As for short-chain fatty acids, in general, a decrease in short-chain fatty acids, in particular butyrate, was observed. Conclusions: Gut microbiota dysbiosis was found in multiple sclerosis patients compared to controls. Most of the altered bacteria are short-chain fatty acid (SCFA)-producing, which could explain the chronic inflammation that characterises this disease. Therefore, future studies should consider the characterisation and manipulation of the multiple sclerosis-associated microbiome as a focus of both diagnostic and therapeutic strategies.
Learning Analytics and the Abolitionist Imagination

This article advances an abolitionist reframing of learning analytics (LA) that explores the benefits of productive disorientation, considers potential harms and care made possible by LA, and suggests the abolitionist imagination as an important educational practice. By applying abolitionist concepts to LA, we propose it may be feasible to open new critiques and social futures that build toward equity-oriented LA design and implementation. We introduce speculative methods to advance three vignettes imagining how LA could be weaponized against students or transformed into a justice-directed learning tool. Our speculative methods aim to destabilize where power in LA has been routinely located and contested, thereby opening new lines of inquiry about more equitable educational prospects. Our concluding discussion addresses how speculative design and fiction are complementary methods to the abolitionist imagination and can be pragmatic tools to help build a world with fairer, more equitable, and responsible LA technologies.
Deep Learning Models for Single-Channel Speech Enhancement on Drones

Speech enhancement for drone audition is made challenging by the strong ego-noise from the rotating motors and propellers, which leads to extremely low signal-to-noise ratios (e.g. SNR $< -15$ dB) at onboard microphones. In this paper, we extensively assess the ability of single-channel deep learning approaches to ego-noise reduction on drones. We train twelve representative deep neural network (DNN) models, covering three operation domains (time-frequency magnitude domain, time-frequency complex domain and end-to-end time domain) and three distinct architectures (sequential, encoder-decoder and generative). We critically discuss and compare the performance of these models in extremely low-SNR scenarios, ranging from −30 to 0 dB. We show that time-frequency complex domain and UNet encoder-decoder architectures outperform other approaches on speech enhancement measures while providing a good trade-off with other criteria, such as model size, computation complexity and context length. The best-performing model is a UNet model operating in the time-frequency complex domain, which, at input SNR −15 dB, improves ESTOI from 0.1 to 0.4, PESQ from 1.0 to 1.9 and SI-SDR from −15 dB to 3.7 dB. Based on the insights drawn from these findings, we discuss future research in drone ego-noise reduction.
Tissue characterization of renal masses using Nakagami-modeling of ultrasound-based texture

In this Institutional Review Board (IRB) approved, Health Insurance Portability and Accountability Act (HIPAA) compliant, prospective study, uncompressed envelope data (RF data) were collected from 100 patients with focal renal masses using an RS80A ultrasound scanner with B-mode and CEUS. By summing and averaging the Nakagami images formed using sliding windows, we use the average ‘m’ to stratify manually segmented masses, using data from both the B-mode and CEUS scans. Wilcoxon rank sum test using an alpha value of 0.05 was used detect differences between the groups. Logistic regression was used for classification and the area under the receiver operator curve (AUC) was used to assess performance. Among the 100 masses, 40 were benign, 37 were malignant based on histopathology, and 23 were radiologically and clinically presumed malignant but with no pathological proof at the time of data analysis. Univariate analyses showed significant (p<0.01) differences between the benign and non-benign masses on both B-mode and CEUS, with non-benign masses having smaller ‘m’. Predictive models constructed using Nakagami parameters extracted from Bmode and CEUS-based RF scans showed an AUC of 0.67 95% CI: (0.56, 0.78) and 0.61 95% CI: (0.5, 0.73), respectively for discriminating benign from non-benign renal masses. The concordance between the two assessments was 95%. We present a framework for characterizing images using speckle textural properties, for example Nakagami analysis, to aid in objective tissue characterization using ultrasound.
Role of Angiotensin Converting Enzyme-2 and its modulation in disease: exploring new frontiers

Angiotensin Converting Enzyme-2 (ACE2), an important enzyme in the Renin Angiotensin Aldosterone System, degrades Angiotensin II (Ang II) into Angiotensin-(1-7) (Ang-(1-7)), whose actions are opposite to that of Ang II. Interestingly, SARS CoV-2 virus entry into human cells is mediated by ACE2. ACE2 receptors that are widely expressed in lungs and various other organs. Ang-(1-7) seems to have favorable effects on lungs, by preventing fibrosis in lung inflammation models, and exerts a similar action in cardiac and renal pathologies as well. Thus, modulation of Ang-(1-7) can be of potential benefit in chronic as well as acute inflammatory diseases affecting lungs and other organs. Upregulation of ACE2 by statins in different organs, and its consequent beneficial effects, have been demonstrated in many experimental studies, and also in a few clinical ones. This review aims at probing the role of ACE2 and its therapeutic modulation in pulmonary and extra pulmonary diseases, including COVID-19.
Make-to-order versus make-to-stock in a production-inventory system with general production times

We study the optimality of make-to-order (MTO) versus make-to-stock (MTS) policies for a company producing multiple heterogeneous products at a shared manufacturing facility. Manufacturing times are general i.i. d. random variables, and different products may have different manufacturing-time distributions. Demands for the products are independent Poisson processes with different arrival rates. The costs of managing the production-inventory system are stationary and include inventory holding and backordering costs. Backordering costs may be $ per unit or $ per unit per unit time. We derive optimality conditions for MTO and MTS policies. We also study the impact of several managerial considerations on the MTO versus MTS decision.
Non-steroidal anti-inflammatory drugs and biomarkers: A new paradigm in colorectal cancer

Colorectal cancer is a sporadic, hereditary, or familial based disease in its origin, caused due to diverse set of mutations in large intestinal epithelial cells. Colorectal cancer (CRC) is a common and deadly disease that accounts for the 4th worldwide highly variable malignancy. For the early detection of CRC, the most common predictive biomarker found endogenously are KRAS and ctDNA/cfDNA along with SEPT9 methylated DNA. Early detection and screening for CRC are necessary and multiple methods can be employed to screen and perform early diagnosis of CRC. Colonoscopy, an invasive method is most prevalent for diagnosing CRC or confirming the positive result as compared to other screening methods whereas several non-invasive techniques such as molecular analysis of breath, urine, blood, and stool can also be performed for early detection. Interestingly, widely used medicines known as non-steroidal anti-inflammatory drugs (NSAIDs) to reduce pain and inflammation have reported chemopreventive impact on gastrointestinal malignancies, especially CRC in several epidemiological and preclinical types of research. NSAID acts by inhibiting two cyclooxygenase enzymes, thereby preventing the synthesis of prostaglandins (PGs) and causing NSAID-induced apoptosis and growth inhibition in CRC cells. This review paper majorly focuses on the diversity of natural and synthetic biomarkers and various techniques for the early detection of CRC. An approach toward current advancement in CRC detection techniques and the role of NSAIDs in CRC chemoprevention has been explored systematically. Several prominent governing mechanisms of the anti-cancer effects of NSAIDs and their synergistic effect with statins for an effective chemopreventive measure have also been discussed in this review paper.
Compact and Efficient Dual-Band Rectifier Using Modified T-Section Matching Network

In this letter, a compact and efficient dual-band rectifier for radio frequency (RF) energy harvesting is presented. The proposed design utilizes a modified T-section comprising a parallel resonance circuit combination of LC in the shunt arm, which plays a key role in obtaining the resultant dual-band rectifier. The shunt arm provides a shift of the high-frequency point in the clockwise direction on the impedance trace (Smith chart) while maintaining an insignificant shift at the lower frequency. The proposed design is verified through theoretical and simulation studies for different Schottky diodes. The circuit is optimized and fabricated to compensate for undesired parasitic effects and achieve the required rectifier performance. For validation, a dual-band rectifier working at 1.4 and 2.45 GHz is fabricated. The measured results show that with a 3.02 $\text{k}\Omega $ load, the maximum efficiencies of the rectifier achieve 65.0% and 57.0% at 1.4 and 2.45 GHz, respectively with 0 dBm input power.
Associations between Plasma Essential Metals Levels and the Risks of All-Cause Mortality and Cardiovascular Disease Mortality among Individuals with Type 2 Diabetes

Epidemiological evidence regarding the possible link between multiple essential metals levels and all-cause mortality and cardiovascular disease (CVD) mortality among type 2 diabetes (T2D) patients is sparse. Here, we aimed to evaluate the longitudinal associations between 11 essential metals levels in plasma and all-cause mortality and CVD mortality among T2D patients. Our study included 5278 T2D patients from the Dongfeng–Tongji cohort. LASSO penalized regression analysis was used to select the all-cause and CVD mortality-associated metals from 11 essential metals (iron, copper, zinc, selenium, manganese, molybdenum, vanadium, cobalt, chromium, nickel, and tin) measured in plasma. Cox proportional hazard models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Results: With a median follow-up of 9.8 years, 890 deaths were documented, including 312 deaths of CVD. LASSO regression models and the multiple-metals model revealed that plasma iron and selenium were negatively associated with all-cause mortality (HR: 0.83; 95%CI: 0.70, 0.98; HR: 0.60; 95%CI: 0.46, 0.77), whereas copper was positively associated with all-cause mortality (HR: 1.60; 95%CI: 1.30, 1.97). Only plasma iron has been significantly associated with decreased risk of CVD mortality (HR: 0.61; 95%CI: 0.49, 0.78). The dose-response curves for the association between copper levels and all-cause mortality followed a J shape (Pfor nonlinear = 0.01). Our study highlights the close relationships between essential metals elements (iron, selenium, and copper) and all-cause and CVD mortality among diabetic patients.
Motion of miscible magnetic fluids in a dynamic magnetic field

Displacements of a miscible magnetic layer in a capillary tube under a moving ring‐shaped magnet are studied numerically. The magnet is adjusted dynamically to maintain a constant distance from the front mixing interface on the centerline. Control parameters, such as magnetic strength, effective viscosity variation due to magnetization, diffusion and the position of the magnet, are analyzed systematically. Motion of the magnetic layer is evaluated by two quantitative measurements, i.e. movement of center of gravity and spread of layer width. In general, the moving speed of the center of gravity depends only slightly on the magnetic strength, and is found slower at a higher viscosity ratio and a closer placement to the front interface as well if the magnet is placed amid the layer. A weaker spread occurs in situations of stronger magnetic strength, lower viscosity parameters and also placements near the rear interface. A multi‐front finger results if the magnet is positioned ahead of the front interface.
Flexible pulse-wave sensors from oriented aluminum nitride nanocolumns

Flexible pulse-wave sensors were fabricated from density-packed oriented aluminum nitride nanocolumns prepared on aluminum foils. The nanocolumns were prepared by the rf magnetron sputtering method and were perpendicularly oriented to the aluminum foil surfaces. The sensor structure is laminated, and the structure contributes to avoiding unexpected leakage of an electric charge. The resulting sensor thickness is 50 μm. The sensor is flexible like aluminum foil and can respond to frequencies from 0.1 to over 100 Hz. The sensitivity of the sensor to pressure is proportional to the surface area. The sensor sensitively causes reversible charge signals that correlate with the pulse wave form, which contains significant information on arteriosclerosis and cardiopathy of a man sitting on it.
PROVISIONAL ELEMENTS OF THE SPECTROSCOPIC BINARY Ν OCTANTIS

v Octantis (cxigoo.o = 21 30TM4; ôi900.o = —77° 50') was announced as a spectroscopic binary, by Dr. W. H. Wright, from observations obtained at the Lick Observatory Station, Santiago, Chile. The star is of visual magnitude 3.74 and of type K0, with one spectrum visible. The radial velocities derived from eleven plates taken in the years 1904-1920 are given in Lick Observatory Publications, Volume 16. Six of these spectrograms were measured more than once and for each of these the mean was taken. Another set of radial velocities was derived from ten plates taken in the years 1909-1924 at the Cape Observatory and published in Cape Annals, Vol. X, Part 8. To the Cape velocities a systematic correction of —0.15 kilometer per second has been applied. Dr. G. P. Kuiper, of the Lick Observatory, called my attention to the possibility of representing all these data with a period of about 1040 days. Since this star has a fairly large parallax and in view of the fact that further observations will probably not be available for some time, it appeared useful to derive a provisional set of elements. Since the observations are not well distributed for accurate determination of the orbit, the majority being grouped near one epoch, no high precision is claimed for the following set of elements : P = 1037 days = 2.839 years T= 2317506 J.D. (o = 90° e = 0.25 K,
Social Support: The Effect on Nocturnal Blood Pressure Dipping

Social support has long been associated with cardiovascular disease risk assessed with blood pressure (BP). BP exhibits a circadian rhythm in which BP should dip between 10 and 15% overnight. Blunted nocturnal dipping (non-dipping) is a predictor of cardiovascular morbidity and mortality independent of clinical BP and is a better predictor of cardiovascular disease risk than either daytime or nighttime BP. However, it is often examined in hypertensive individuals and less often in normotensive individuals. Those under age 50 are at increased risk for having lower social support. This study examined social support and nocturnal dipping in normotensive individuals under age 50 using ambulatory blood pressure monitoring (ABP). ABP was collected in 179 participants throughout a 24-h period. Participants completed the Interpersonal Support Evaluation List, which assesses perceived levels of social support in one’s network. Participants with low levels of social support demonstrated blunted dipping. This effect was moderated by sex, with women showing greater benefit from their social support. These findings demonstrate the impact social support can have on cardiovascular health, exhibited through blunted dipping, and are particularly important as the study was conducted in normotensive individuals who are less likely to have high levels of social support.
The ferroelectric-ferroelectric transition in rhombohedral lead zirconate-titanate

The rhombohedral-rhombohedral transition in PbZrxTi1-xO3 is found to be of first order. Calculations are given of the tilt angle of the oxygen octahedra about [111] together with the octahedron strain. Coupling between these two quantities is found to account for the nature of the phase transition. In addition, an explanation of the pyroelectric behaviour is given.
Phosphorylation of LKB1 by PDK1 Inhibits Cell Proliferation and Organ Growth by Decreased Activation of AMPK

The master kinase LKB1 is a key regulator of se veral cellular processes, including cell proliferation, cell polarity and cellular metabolism. It phosphorylates and activates several downstream kinases, including AMP-dependent kinase, AMPK. Activation of AMPK by low energy supply and phosphorylation of LKB1 results in an inhibition of mTOR, thus decreasing energy-consuming processes, in particular translation and, thus, cell growth. LKB1 itself is a constitutively active kinase, which is regulated by posttranslational modifications and direct binding to phospholipids of the plasma membrane. Here, we report that LKB1 binds to Phosphoinositide-dependent kinase (PDK1) by a conserved binding motif. Furthermore, a PDK1-consensus motif is located within the kinase domain of LKB1 and LKB1 gets phosphorylated by PDK1 in vitro. In Drosophila, knockin of phosphorylation-deficient LKB1 results in normal survival of the flies, but an increased activation of LKB1, whereas a phospho-mimetic LKB1 variant displays decreased AMPK activation. As a functional consequence, cell growth as well as organism size is decreased in phosphorylation-deficient LKB1. Molecular dynamics simulations of PDK1-mediated LKB1 phosphorylation revealed changes in the ATP binding pocket, suggesting a conformational change upon phosphorylation, which in turn can alter LKB1’s kinase activity. Thus, phosphorylation of LKB1 by PDK1 results in an inhibition of LKB1, decreased activation of AMPK and enhanced cell growth.
Assessment of shape-based features ability to predict the ascending aortic aneurysm growth

The current guidelines for the ascending aortic aneurysm (AsAA) treatment recommend surgery mainly according to the maximum diameter assessment. This criterion has already proven to be often inefficient in identifying patients at high risk of aneurysm growth and rupture. In this study, we propose a method to compute a set of local shape features that, in addition to the maximum diameter D, are intended to improve the classification performances for the ascending aortic aneurysm growth risk assessment. Apart from D, these are the ratio DCR between D and the length of the ascending aorta centerline, the ratio EILR between the length of the external and the internal lines and the tortuosity T. 50 patients with two 3D acquisitions at least 6 months apart were segmented and the growth rate (GR) with the shape features related to the first exam computed. The correlation between them has been investigated. After, the dataset was divided into two classes according to the growth rate value. We used six different classifiers with input data exclusively from the first exam to predict the class to which each patient belonged. A first classification was performed using only D and a second with all the shape features together. The performances have been evaluated by computing accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUROC) and positive (negative) likelihood ratio LHR+ (LHR−). A positive correlation was observed between growth rate and DCR (r = 0.511, p = 1.3e-4) and between GR and EILR (r = 0.472, p = 2.7e-4). Overall, the classifiers based on the four metrics outperformed the same ones based only on D. Among the diameter-based classifiers, k-nearest neighbours (KNN) reported the best accuracy (86%), sensitivity (55.6%), AUROC (0.74), LHR+ (7.62) and LHR− (0.48). Concerning the classifiers based on the four shape features, we obtained the best accuracy (94%), sensitivity (66.7%), specificity (100%), AUROC (0.94), LHR+ (+∞) and LHR− (0.33) with support vector machine (SVM). This demonstrates how automatic shape features detection combined with risk classification criteria could be crucial in planning the follow-up of patients with ascending aortic aneurysm and in predicting the possible dangerous progression of the disease.
Temporal dynamics of heatwaves are key drivers of sediment mixing by bioturbators

Heatwaves affect tidal flat ecosystems by altering the bioturbating behavior of benthic species, with potential consequences for sediment oxygenation, particle mixing, and erodibility. Although the frequency and duration of heatwaves are expected to increase under global warming scenarios, we lack insights into how heatwaves' temporal dynamics affect bioturbating behaviors. Using the widely distributed bioturbator Cerastoderma edule as model species, we quantified how heatwaves with identical heat‐sum but different temporal dynamics (i.e., 3‐ vs. 6‐d heating and normal temperature cycles) affect bioturbating behaviors and the sediment mixing processes in tidal mesocosms. Our results show that short but frequent 3‐d heatwave cycles increased the magnitude of bioturbating behaviors, thereby resulting in more bio‐mixed sediment than observed under infrequent prolonged 6‐d heatwave cycles. This unexpected result could be ascribed to the weakening health condition indicated by a high death rate (47.37%) under 6‐d heatwave cycles than in 3‐d and no‐heatwave control cycles. Present findings reveal that the impact of heatwaves on sediment bioturbation will strongly depend on the temporal dynamics of future heatwaves: bioturbation will be enhanced unless the heatwave duration exceeds species resistance and increases mortality.