Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of expression patterns of six canonical clock genes of follicular phase and luteal phase in Small-tailed Han sheep

Abstract The circadian rhythm is a biological rhythm that is closely related to the rhythmic expression of a series of clock genes. Results from several studies have indicated that clock genes are associated with the estrous cycle in female animals. Until now, the relationship between estrus cycle transition and clock gene expression in reproductive-axis-related tissues has remained unknown in Small-tailed Han (STH) sheep. This study was conducted to analyze the expression patterns of six canonical clock genes (Clock, BMAL1, Per1, Per2, Cry1, and Cry2) in the follicle phase and luteal phase of STH sheep. We found that all six genes were expressed in the brain, cerebellum, hypothalamus, pituitary, ovary, uterus, and oviduct in follicle and luteal phases. The results indicated that Clock expression was significantly higher in the cerebellum, hypothalamus, and uterus of the luteal phase than that of the follicle phase, whereas BMAL1 expression was significantly higher in the hypothalamus of the luteal phase than that of the follicle phase. Per1 expression was significantly higher in the brain, cerebellum, hypothalamus, and pituitary of the luteal phase than that of the follicle phase, and Per2 expression was significantly higher in the hypothalamus, pituitary, and uterus of the luteal phase than that of the follicle phase. Cry1 expression was significantly higher in the brain, cerebellum, and hypothalamus of the luteal phase than that of the follicle phase, whereas Cry2 expression was significantly higher in the pituitary of the luteal phase than that of the follicle phase. The clock gene expression in all tissues was different between follicle and luteal phases, but all clock gene mRNA levels were found to exhibit higher expression among seven tissues in the luteal phase. Our results suggest that estrous cycles may be associated with clock gene expression in the STH sheep. This is the first study to systematically analyze the expression patterns of clock genes of different estrous cycle in ewes, which could form a basis for further studies to develop the relationship between clock genes and the estrous cycle.
GIS-Based Three-Dimensional SPH Simulation for the 11 April 2018 Yabakei Landslide at Oita Nakatsu, Japan

Landslides are usually triggered by strong earthquakes, heavy rainfalls, or intensive human activities in common wisdom. However, an unexpected landslide occurred in the Yabakei area, Nakatsu, Oita, Japan, at the pre-dawn hour 3:50 a.m. on 11 April 2018, without any accompanying rainfall and earthquake records during the event. This catastrophic landslide was 200 m in width, 110 m in height, and 60,000 m3 in mass volume, damaging four residential buildings with fatalities of six residents at the landslide toe. Field investigation was conducted immediately to identify geological setting, hydrological condition, and landslide geomorphological characteristics. Key findings speculate that infiltration of groundwater stored in the internal fractures led to the swelling and breaking of illite and askanite in the weathered sediment rocks, resulting in the failure of the Yabakei landslide. To reproduce and explore the dynamic process of this landslide event, based on spatial GIS data, we applied the proposed three-dimensional, Herschel-Bulkley-Papanastasiou rheology model-based smooth particle hydrodynamics (HBP-SPH) method to simulate the landslide dynamic process. Buildings in the landslide area are covered by a set of surfaced cells (SC) to analyze the mass impact on the residential buildings. Results showed good accordance between observation and simulation by the proposed SC-HBP-SPH method. The landslide impact force to the residential buildings could be up to 4224.89 kN, as indicated by the simulation.
An Overview of Noise-Shaping SAR ADC: From Fundamentals to the Frontier

The Noise-Shaping (NS) SAR is an attractive new ADC architecture that emerged in the last decade. It combines the advantages of the SAR and the DSM architectures. NS SAR shows excellent potential for high efficiency and low cost, and is highly suited to process scaling. This paper gives an overview of the history of NS-SAR, reviews the fundamentals challenges, and summarizes the latest developments, including advanced loop filtering techniques, DAC mismatch mitigation, kT/C mitigation, and bandwidth boosting. A comprehensive comparison of the state-of-the-art NS-SAR ADCs is provided, and conclusions are derived.
Stimulated Expression of CXCL12 in Adrenocortical Carcinoma by the PPARgamma Ligand Rosiglitazone Impairs Cancer Progression

Adrenocortical carcinoma (ACC) is a rare malignancy with poor prognosis when metastatic and scarce treatment options in the advanced stages. In solid tumors, the chemokine CXCL12/CXCR4 axis is involved in the metastatic process. We demonstrated that the human adrenocortex expressed CXCL12 and its cognate receptors CXCR4 and CXCR7, not only in physiological conditions, but also in ACC, where the receptors’ expression was higher and the CXCL12 expression was lower than in the physiological conditions. In a small pilot cohort of 22 ACC patients, CXCL12 negatively correlated with tumor size, stage, Weiss score, necrosis, and mitotic activity. In a Kaplan–Meier analysis, the CXCL12 tumor expression significantly predicted disease-free, progression-free, and overall survival. In vitro treatment of the primary ACC H295R and of the metastatic MUC-1 cell line with the PPARγ-ligand rosiglitazone (RGZ) dose-dependently reduced proliferation, resulting in a significant increase in CXCL12 and a decrease in its receptors in the H295R cells only, with no effect on the MUC-1 levels. In ACC mouse xenografts, tumor growth was inhibited by the RGZ treatment before tumor development (prevention-setting) and once the tumor had grown (therapeutic-setting), similarly to mitotane (MTT). This inhibition was associated with a significant suppression of the tumor CXCR4/CXCR7 and the stimulation of human CXCL12 expression. Tumor growth correlated inversely with CXCL12 and positively with CXCR4 expression, suggesting that local CXCL12 may impair the primary tumor cell response to the ligand gradient that may contribute to driving the tumor progression. These findings indicate that CXCL12/CXCR4 may constitute a potential target for anti-cancer agents such as rosiglitazone in the treatment of ACC.
Classical and Quantum Gases on a Semiregular Mesh

The main objective of a statistical mechanical calculation is drawing the phase diagram of a many-body system. In this respect, discrete systems offer the clear advantage over continuum systems of an easier enumeration of microstates, though at the cost of added abstraction. With this in mind, we examine a system of particles living on the vertices of the (biscribed) pentakis dodecahedron, using different couplings for first and second neighbor particles to induce a competition between icosahedral and dodecahedral orders. After working out the phases of the model at zero temperature, we carry out Metropolis Monte Carlo simulations at finite temperature, highlighting the existence of smooth transitions between distinct “phases”. The sharpest of these crossovers are characterized by hysteretic behavior near zero temperature, which reveals a bottleneck issue for Metropolis dynamics in state space. Next, we introduce the quantum (Bose-Hubbard) counterpart of the previous model and calculate its phase diagram at zero and finite temperatures using the decoupling approximation. We thus uncover, in addition to Mott insulating “solids”, also the existence of supersolid “phases” which progressively shrink as the system is heated up. We argue that a quantum system of the kind described here can be realized with programmable holographic optical tweezers.
Epstein–Barr Virus in Salivary Samples from Systemic Lupus Erythematosus Patients with Oral Lesions

In order to investigate the possible role of Epstein–Barr virus (EBV) in systemic lupus erythematosus (SLE) and its associated oral lesions, a pilot case–control study was performed. A total of 31 patients (18 females and 13 males) were enrolled in the study and divided into two groups: group A included 16 patients with diagnosis of SLE and group B included 15 healthy individuals. Salivary swab samples were collected and subjected to molecular screening by real-time quantitative PCR (qPCR) for the detection of EBV DNA. EBV DNA was significantly detected in 8/16 (50%) SLE patients and in 5/7 (71.4%) subjects with SLE-associated oral lesions. Since EBV is one of the most common viruses in the human population, it is difficult to understand if it is the causative agent of SLE or, vice versa, if SLE is able to trigger the reactivation of EBV. This study highlights a significant association between the presence of EBV and both SLE and SLE-related oral lesions and provides rationale for further investigation into the role of EBV in SLE pathogenesis.
Disease Management Options in Captive Reared Clownfish, Amphiprion sebae Bleeker 1853: Application of Chemotherapy, Marine Natural Products and Autogenous Vaccines

Disease conditions in aquarium captive-reared clownfish, Amphiprion sebae Bleeker 1853, were caused by bacterial pathogens belonging to Vibrio sp. , Alacaligenes sp. , Serratia marcescens and Flavobacterium sp. An emerging pathogen, Serratia marcescens was noted to cause severe ulcerations in the aquarium fish in a repetitive manner. Disease management studies conducted with antibiotics, extracts from marine macroalgae and sponges and immunoprophylaxis using formalin-killed S. marcescens cells gave promising results. Among the antibiotics, ciprofloxacin had a high inhibitory zone of 32 mm followed by oxytetracycline, trimethoprim and co-trimoxazole with 24 mm zones each. The methanol extract of the macroalga, Gracilaria corticata produced 36 mm inhibition zone, while the extracts of two sponge species, Callyspongia diffusa and Sigmadocia carnosa produced 26 mm and 24 mm zones respectively; suggesting scope for the use of extracts from maroalgae and sponges (marine natural products) for disease management in marine aquaria. The autogenous vaccine when administered in fish at 1 × 10 5 cells.g -1 resulted in increased relative percentage survival after the 15 th day and continued with 100 % protection at 35 and 50 days, on challenge with S. marcescens . These studies suggest that proactive management strategies can be successfully adopted for managing S. marcescens infection in clownfish.
Tart Cherry Extract and Omega Fatty Acids Reduce Behavioral Deficits, Gliosis, and Amyloid-Beta Deposition in the 5xFAD Mouse Model of Alzheimer’s Disease

Combined treatments using polyphenols and omega fatty acids provide several therapeutic benefits for a variety of age-related disorders, including Alzheimer’s disease (AD). Previously, we found a commercial product, Total Body Rhythm (TBR), consisting of tart cherry extract, a potent polyphenol, and omega fatty acids, significantly reduced memory, and neuropathological deficits in the 192 IgG-saporin mouse model of AD. The present study assessed the efficacy of TBR for treating behavioral and neuropathological deficits in the 5xFAD model of AD. Both 6- and 12-month-old 5xFAD mice and age-matched wild-type controls received TBR (60 mg/kg) or the equivalent dose of vehicle (0.5% methylcellulose) via oral administration, every other day for two months. All mice were tested in the open field (OF), novel object recognition (NOR), and the Morris water maze (MWM) tasks. In addition, neuronal morphology, neurodegeneration, Aβ plaque load, and glial activation were assessed. TBR treatment reduced memory deficits in the MWM and NOR tests and lessened anxiety levels in the OF task, mostly in the 6-month-old male mice. TBR also protected against neuron loss, reduced activation of astrocytes and microglia, primarily in 6-month-old mice, and attenuated Aβ deposition. These results suggest that the combination of tart cherry extract and omega fatty acids in TBR can reduce AD-like deficits in 5xFAD mice.
The correlation between fractional amplitude of low-frequency fluctuation-based resting-state functional magnetic resonance imaging and facial emotion recognition ability in patients with first-episode schizophrenia

Our aim was to analyse the correlation between the fractional amplitude of low-frequency fluctuation (fALFF) and facial emotion recognition (FER) ability in patients with first-episode schizophrenia (FSZ). A total of 28 patients with FSZ and 33 healthy controls (HCs) completed visual search tasks for FER ability. Regions of interest (ROIs) related to facial emotion were obtained from a previous meta-analysis. Pearson correlation analysis was performed to understand the correlation between fALFF and FER ability. Our results indicated that the patients performed worse than the HCs in the accuracy performances of happy FER and fearful FER. The previous meta-analysis results showed that the brain regions related to FER included the bilateral amygdala (AMY)/hippocampus (HIP), right fusiform gyrus (FFG), and right supplementary motor area (SMA). Pearson correlation showed that the fALFF of the right FFG was associated with high-load fearful FER accuracy (r = -0.43, p = 0.022). Multiple regression analysis showed that the fALFF of the right FFG was an independent contributor to fearful FER accuracy. Our study indicates that FER ability is correlated with resting-state intrinsic activity in brain regions related to facial emotion, which may provide a reference for the study of FER in schizophrenia.
Entanglement in bipartite quantum systems: Euclidean volume ratios and detectability by Bell inequalities

Euclidean volume ratios between quantum states with positive partial transpose and all quantum states in bipartite systems are investigated. These ratios allow a quantitative exploration of the typicality of entanglement and of its detectability by Bell inequalities. For this purpose a new numerical approach is developed. It is based on the Peres–Horodecki criterion, on a characterization of the convex set of quantum states by inequalities resulting from Newton identities and from Descartes’ rule of signs, and on a numerical approach involving the multiphase Monte Carlo method and the hit-and-run algorithm. This approach confirms not only recent analytical and numerical results on two-qubit, qubit-qutrit, and qubit-four-level qudit states but also allows for a numerically reliable numerical treatment of so far unexplored qutrit–qutrit states. Based on this numerical approach with the help of the Clauser–Horne–Shimony–Holt inequality and the Collins–Gisin inequality the degree of detectability of entanglement is investigated for two-qubit quantum states. It is investigated quantitatively to which extent a combined test of both Bell inequalities can increase the detectability of entanglement beyond what is achievable by each of these inequalities separately.
High-Resolution Mass Spectrometry and Chemometrics for the Detailed Characterization of Short Endogenous Peptides in Milk By-Products

The process of cheese-making has long been part of human food culture and nowadays dairy represents a large sector of the food industry. Being the main byproduct of cheese-making, the revalorization of milk whey is nowadays one of the primary goals in alignment with the principles of the circular economy. In the present paper, a deep and detailed investigation of short endogenous peptides in milk and its byproducts (whole whey, skimmed whey, and whey permeate) was carried out by high-resolution mass spectrometry, with a dedicated suspect screening data acquisition and data analysis approach. A total of 79 short peptides was tentatively identified, including several sequences already known for their exerted biological activities. An unsupervised chemometric approach was then employed for highlighting the differences in the short peptide content among the four sets of samples. Whole and skimmed whey showed not merely a higher content of short bioactive peptides compared to whole milk, but also a peculiar composition of peptides that are likely generated during the process of cheese-making. The results clearly demonstrate that whey represents a valuable source of bioactive compounds and that the set-up of processes of revalorization of milk byproducts is a promising path in the obtention of high revenue-generating products from dairy industrial waste.
Performance evaluation of IEEE 802.11p, LTE and 5G in connected vehicles for cooperative awareness

In recent years, researchers and scientists are continuously striving to design and develop advance wireless technologies for vehicular communication. Advanced short‐range (IEEE‐802.11p/ITS‐G5) and long‐range (LTE, LTE‐A, and 5G) technologies are indispensable for Vehicular Ad hoc networking (VANETs). Meanwhile, exploiting technologies for cooperative awareness of connected vehicles is important for seamless network connectivity in hazardous situations. For seamless network availability, there is a need to integrate short‐range and long‐range technologies together. In this article, we design a pilot platform based on IEEE‐802.11p, LTE and 5G test network (5GTN) utilizing road traffic and weather information. The use of real‐time and accurate road traffic and weather information together with road condition information is crucial to enhance road safety. To deliver updated road weather and traffic information, we have used a combination of networks. In this article, a comparison of vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) pilot scenarios was carried out considering the mentioned networks. The used IEEE 802.11p acts as a primary vehicular communication channel, assisted by other cellular‐based LTE and 5G networks. Network performance was analyzed by considering latency, packet loss, and throughput in V2V and V2I scenarios. These pilot measurements revealed that the state‐of‐the‐art 5G test network performs better in contrast of IEEE‐802.11p and LTE network by delivering real‐time road weather and road traffic observation data. These pilots filed measurements show the potential of combining short‐ and long‐range technologies for enhanced road safety.
Exploring the connection between work–family conflict and job burnout among Nigerian correctional staff

Only one study among U.S. prison staff has explored the effects of work–family conflict and job burnout. To replicate the research to determine whether the results vary by nation, this study examined the effects of four types of work–family conflict (strain-based, time-based, behavior-based and family-based conflict) on three dimensions of job burnout (emotional exhaustion, depersonalization and feeling ineffective at work) among Nigerian correctional staff. Strain- and behavior-based conflict had significant positive effects on emotional exhaustion, but time- and family-based conflict did not. Family-based conflict was the only type of domain spillover with significant positive effects on depersonalization. Behavior-based conflict was the only type of work–family conflict with significant positive effects on feeling ineffective at work. Time-based and strain-based conflict were highly related to one another, which was attributed to time-based conflict being a contributor to strain-based conflict for Nigerian prison staff.
Superiority of Multiple-Joint Space Width over Minimum-Joint Space Width Approach in the Machine Learning for Radiographic Severity and Knee Osteoarthritis Progression

Simple Summary Minimum-joint space width (JSW) is a prevalent clinical parameter in quantifying the joint space narrowing condition in knee osteoarthritis (KOA). In this study, we propose a novel multiple-JSW measurement, which is estimated by a deep learning-based model in an automated manner. The performance of the proposed automated measurement is found to be superior to the conventionally used minimum-JSW in the severity classification and progression prediction of KOA owing to the additional information of the joint space morphology encoded in the new approach. It is further demonstrated that the deep learning-based approach yields comparable performance as the measurement by radiologists. The approach presented in this work may lead to the development of a computer-aided tool for clinical practitioners that could facilitate the KOA diagnosis and prognosis with the fully automated, accurate, and efficient computation of the joint-space parameters. Abstract We compared the prediction efficiency of the multiple-joint space width (JSW) and the minimum-JSW on knee osteoarthritis (KOA) severity and progression by using a deep learning approach. A convolutional neural network (CNN) with ResU-Net architecture was developed for knee X-ray imaging segmentation and has attained a segmentation efficiency of 98.9% intersection over union (IoU) on the distal femur and proximal tibia. Later, by leveraging the image segmentation, the minimum and multiple-JSWs in the tibiofemoral joint were estimated and then validated by radiologist measurements in the Osteoarthritis Initiative (OAI) dataset using Pearson correlation and Bland–Altman plots. The agreement between the CNN-based estimation and radiologist’s measurement of minimum-JSWs reached 0.7801 (p < 0.0001). The estimated JSWs were deployed to predict the radiographic severity and progression of KOA defined by Kellgren-Lawrence (KL) grades using the XGBoost model. The 64-point multiple-JSWs achieved the best performance in predicting KOA progression within 48 months, with the area-under-receiver operating characteristic curve (AUC) of 0.621, outperforming the commonly used minimum-JSW with 0.554 AUC. We provided a fully automated radiographic assessment tool for KOA with comparable performance to the radiologists and showed that the fine-grained measurement of multiple-JSWs yields superior prediction performance for KOA over the minimum-JSW.
Membrane stability and antioxidant enzyme activity of rice seedlings in response to short-term high temperature treatments

The impact of temperature on plants varies depending on the temperature level and the time of exposure. The aim of this study was evaluating different short-term temperatures to stimulate rice (Oryza sativa L.) seedling growth indicated by some physiological functions. Thus, oxidative stress, membrane stability and antioxidant activity in ‘Dular’, ‘IR64’ and ‘KDML105’ rice seedlings were evaluated in response to 25, 35 and 45 °C for 30 min. At 25 °C, ‘IR64’ showed higher electrolyte leakage (EL) percentages, protein contents and peroxidase (POX) activity but lower hydrogen peroxide (H2O2) content. At 35 °C, the highest H2O2 content was found in ‘KDML105’ followed by ‘IR64’ and ‘Dular’. In all rice seedlings the lowest EL was after 35 °C exposure and activities of catalase (CAT) in ‘IR64’ and ‘KDML105’, ascorbate peroxidase (APX) in ‘Dular’, ‘IR64’ and ‘KDML105’ and glutathione reductase (GR) in ‘Dular’, ‘IR64’ and ‘KDML105’, and superoxide dismutase (SOD) in ‘Dular’ and ‘KDML105’ were stimulated by higher H2O2 production. At 45 °C, all rice seedlings showed pronounced EL increase but reduced H2O2 production, protein content and all antioxidant enzyme activities. These results suggested that short-term temperature at 35 °C was an optimum condition for all rice seedlings as indicated by the least membrane damage (EL ≈ 45.04%) and induction of most antioxidant enzymes (CAT, APX, GR and SOD ≈ 48.29 nmol min-1 μg-1 protein, 247.49 ng ascorbic acid min-1 μg-1 protein, 0.16 μM min-1 μg-1 protein and 0.078 unit min-1 μg-1 protein, respectively). This temperature induced higher H2O2 production which plays a significant role in signaling molecules to stimulate protein function and antioxidant enzyme activities. While short-term 45 °C proved to be damaging temperature for all rice seedlings because of membrane damage and decreased reactive oxygen species defense mechanism.