Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Transcriptome Profiling of mRNA and lncRNA of Mouse Spleens Inoculated with the Group ACYW135 Meningococcal Polysaccharide Vaccine

The Group ACYW135 meningococcal polysaccharide vaccine (MPV-ACYW135) is a classical common vaccine used to prevent Neisseria meningitidis serogroups A, C, Y, and W135, but studies on the vaccine at the transcriptional level are still limited. In the present study, mRNAs and lncRNAs related to immunity were screened from the spleens of mice inoculated with MPV-ACYW135 and compared with the control group to identify differentially expressed mRNAs and lncRNAs in the immune response. The result revealed 34375 lncRNAs and 41321 mRNAs, including 405 differentially expressed (DE) lncRNAs and 52 DE mRNAs between the MPV group and the control group. Results of GO and KEGG enrichment analysis turned out that the main pathways related to the immunity of target genes of those DE mRNAs and DE lncRNAs were largely associated with positive regulation of T cell activation, CD8-positive immunoglobulin production in mucosal tissue, alpha-beta T cell proliferation, negative regulation of CD4-positive, and negative regulation of interleukin-17 production, suggesting that the antigens of MPV-ACYW135 capsular polysaccharide might activate T cell related immune reaction in the vaccine inoculation. In addition, it was noted that Bach2 (BTB and CNC homolog 2), the target gene of lncRNA MSTRG.17645, was involved in the regulation of immune response in MPV-ACYW135 vaccination. This study provided a preliminary catalog of both mRNAs and lncRNAs associated with the proliferation and differentiation of body immune cells, which was worthy of further research to enhance the understanding of the biological immune process regulated by MPV-ACYW135.
Old Folks, Bad Boon: Antimicrobial Resistance in the Infant Gut Microbiome

The development of the intestinal microbiome in the neonate starts, mainly, at birth, when the infant receives its founding microbial inoculum from the mother. This microbiome contains genes conferring resistance to antibiotics since these are found in some of the microorganisms present in the intestine. Similarly to microbiota composition, the possession of antibiotic resistance genes is affected by different perinatal factors. Moreover, antibiotics are the most used drugs in early life, and the use of antibiotics in pediatrics covers a wide variety of possibilities and treatment options. The disruption in the early microbiota caused by antibiotics may be of great relevance, not just because it may limit colonization by beneficial microorganisms and increase that of potential pathogens, but also because it may increase the levels of antibiotic resistance genes. The increase in antibiotic-resistant microorganisms is one of the major public health threats that humanity has to face and, therefore, understanding the factors that determine the development of the resistome in early life is of relevance. Recent advancements in sequencing technologies have enabled the study of the microbiota and the resistome at unprecedent levels. These aspects are discussed in this review as well as some potential interventions aimed at reducing the possession of resistance genes.
Bi-directional controlled asymmetric teleportation protocol initiated by a mentor in noisy environments

In this paper we consider the problem of the bidirectional state transfer of a 2-qubit and a 3-qubit quantum state unknown to the parties, respectively, who intend to send the respective states in the site of the other party. These states are intended for transfer but are not possessed by the intender. The protocol has a Mentor whose role is in the fabrication of entangled channels, distribution of qubits through the noisy environment in order to create entanglement sharing and finally fixing one of the several courses of the protocol. The role of the Mentor is thereby completed. The protocol is overseen by a controller whose action signals the final steps to be taken in the protocol. Three types of noises are considered through three different Kraus operators. There is an analysis of the fidelity of the protocol corresponding to three types of noises.
On the precision of aero-thermal simulations for TMT

Environmental effects on the Image Quality (IQ) of the Thirty Meter Telescope (TMT) are estimated by aero-thermal numerical simulations. These simulations utilize Computational Fluid Dynamics (CFD) to estimate, among others, thermal (dome and mirror) seeing as well as wind jitter and blur. As the design matures, guidance obtained from these numerical experiments can influence significant cost-performance trade-offs and even component survivability. The stochastic nature of environmental conditions results in the generation of a large computational solution matrix in order to statistically predict Observatory Performance. Moreover, the relative contribution of selected key subcomponents to IQ increases the parameter space and thus computational cost, while dictating a reduced prediction error bar. The current study presents the strategy followed to minimize prediction time and computational resources, the subsequent physical and numerical limitations and finally the approach to mitigate the issues experienced. In particular, the paper describes a mesh-independence study, the effect of interpolation of CFD results on the TMT IQ metric, and an analysis of the sensitivity of IQ to certain important heat sources and geometric features.
Event-Triggered Adaptive Dynamic Programming for Zero-Sum Game of Partially Unknown Continuous-Time Nonlinear Systems

In this paper, the zero-sum game problem is considered for partially unknown continuous-time nonlinear systems, and an event-triggered adaptive dynamic programming (ADP) method is developed to solve the problem. First, an identifier neural network (NN) and a critic NN are applied to approximate the drift system dynamics and the optimal value function, respectively. Subsequently, an event-triggered approach is developed based on ADP, which samples the states and updates the weights of NNs at the same time when the event-triggering condition is violated, such that the computational complexity is reduced. It is proved that the states and the error of NN weights are uniformly ultimately bounded. Finally, the effectiveness of the developed ADP-based event-triggered method is verified through simulation studies.
Motor Current-Based Degradation Modeling for Tool Wear Hybrid Prognostics in Turning Process

For many machines with turning process systems, the application of economical indirect Tool Condition Monitoring (TCM) is enhanced by utilizing internal encoder spindle motor current signals. In this study, we proposed a novel approach to extract the total harmonic distortion (THD) feature associated with the metal cutting frequency of a specific working tool in the time domain. Our method entailed the application of filtered variational mode decomposition (VMD) combined with envelope analysis to demodulate the motor current signal and define TCM features based on the THD of odd harmonics, which are more related to the motor structure. These features serve as inputs for a hybrid prognostics technique, employing the Geometric Brownian Motion (GBM) to stochastically model the degradation process along with a deep learning transformer-based framework called the time series Transformer (TST) to improve the life prediction. Finally, to validate our approach, we conducted experiments based on 36 sets of tool run-to-wear data extracted from a CNC machine operating under turning process conditions using two different tools. Finally, we compared the degradation models based on the extracted odd-THD and even-THD features.
The impact of charge transfer inefficiency on Extreme Precision Doppler measurements

A new generation of ``Extreme Precision'' astronomical spectrometers is currently being designed to detect Earth-mass planets orbiting nearby stars using the Doppler method. Measuring the subtle shifts in stellar absorption features resulting from stellar radial velocity variations of tens of centimeters per second is a significant technological challenge. Currently, there are several instruments around the world capable of measuring stellar radial velocities at the 1 m s−1 level. Moving beyond this level of precision, CCD effects may become important and could limit the ultimate measurement precision in complex ways. Here, we simulate the impact of Charge Transfer Inefficiency (CTI) in CCDs on radial velocity measurements. We show that CTI can manifest as a significant source of systematic error in high precision Doppler measurements, though these effects can likely be mitigated using optimized observing strategies and empirical flux corrections.
A population-based study of caesarean section in women with juvenile idiopathic arthritis

Abstract Objectives The literature on delivery methods in women with JIA is limited. Active inflammation is a risk factor for caesarean section (CS) in other arthritic diseases. A CS entails a higher risk for complications than vaginal delivery and restricted physical activity in the first weeks after birth. Our objective was to explore a possible association of inflammatory active disease and the proportion of CS in women with JIA. Methods Data from the Norwegian nationwide observational register RevNatus were linked with data from the Medical Birth Registry of Norway (MBRN). Cases comprised singleton births in women with JIA (n = 196) included in RevNatus from 2010 to 2019. Singleton births registered in the MBRN during the same period of time, excluding births in mothers with rheumatic inflammatory diseases, served as population controls (n = 575 798). Results CS was more frequent in women with JIA (20.4%) and in the subgroup of women with inflammatory active JIA (30.0%) than in population controls (15.6%). Women with active JIA had a risk for elective CS similar to population controls [risk difference 2.3% (95% CI −2.5, 12.9)] and a higher risk for emergency CS [risk difference 14.0% (95% CI 4.3, 27.4)] compared with population controls. Conclusion Women with active JIA had a higher risk for emergency CS, but not elective CS, compared with population controls.
A stationary long-pulse ELM-absent H-mode regime in EAST

A stationary edge-localized mode (ELM)-absent H-mode regime, with an electrostatic edge coherent mode (ECM) which resides in the pedestal region, has been achieved in the EAST tokamak recently. This regime allows the operation of a nearly fully noninductive long pulse (>15 s), exhibiting a relatively high pedestal and good global energy confinement with H98,y2 near 1.2, and excellent impurity control. Furthermore, this regime is mostly obtained with a 4.6 GHz lower hybrid current drive (LHCD) or counter-current neutral beam injection (NBI), plus electron cyclotron resonance heating, and an extensive lithium wall coating. This stationary ELM-absent H-mode regime transits to a stationary small ELM H-mode regime, and upon additional heating power from the 2.45 GHz LHCD, an ion cyclotron resonant frequency or co-current NBI is applied (under 4.6 GHz LHCD heating background). A slight change of the plasma configuration also makes the small ELMs reappear. The experimental observations suggest that a long-pulse ELM-absent regime can be induced by the ECM, which exhibits strong electrostatic fluctuations and may provide a channel for continuous particle (especially impurities) and heat exhaust across the pedestal. The ECM exists in the collisionality of νe∗ = 2.5–4 and the pressure gradient |∇P| = |dP╱dρ| = 100–200 (kPa), which is in good agreement with the previous simulation of GYRO. This ELM-absent H-mode regime with ECM may offer a suitable candidate for high-performance, steady-state H-mode operation in future fusion reactors.
The Influence of Sildenafil–Metformin Combination on Hyperalgesia and Biochemical Markers in Diabetic Neuropathy in Mice

Background and objectives: Worldwide, approximately 500 million people suffer from diabetes and at least 50% of these people develop neuropathy. Currently, therapeutic strategies for reducing diabetic neuropathy (DN)-associated pain are limited and have several side effects. The purpose of the study was to evaluate the antihyperalgesic action of different sildenafil (phosphodiesterase-5 inhibitor) and metformin (antihyperglycemic agent) combinations in alloxan-induced DN. Methods: The study included 100 diabetic mice and 20 non-diabetic mice that were subjected to hot and cold stimulus tests. Furthermore, we determined the influence of this combination on TNF-α, IL-6 and nitrites levels in brain and liver tissues. Results: In both the hot-plate and tail withdrawal test, all sildenafil–metformin combinations administered in our study showed a significant increase in pain reaction latencies when compared to the diabetic control group. Furthermore, all combinations decreased blood glucose levels due to the hypoglycemic effect of metformin. Additionally, changes in nitrite levels and pro-inflammatory cytokines (TNF-α and IL-6) were observed after 14 days of treatment with different sildenafil–metformin combinations. Conclusions: The combination of these two substances increased the pain reaction latency of diabetic animals in a dose-dependent manner. Moreover, all sildenafil–metformin combinations significantly reduced the concentration of nitrites in the brain and liver, which are final products formed under the action of iNOS.
Thalassemia, biobanking infrastructures, and personalized stem cell therapies in Chennai

Thalassemia and leukemia and related blood disorders are approved for blood stem cell transplants in India, for a stem cell transplant to be successful, the human leukocyte antigen (HLA) complex located on the arm of chromosome six must be a match between the cord blood donor and the recipient. In the quest to find an exact blood stem cell match for an individual, the HLA becomes the node at the center of community genetics where the HLA match is sought (not necessarily successful) in the extended family, the same caste, language, and ethnic (both national and the diaspora) groups. By considering thalassemia as a case study, how do we understand personalized stem cell therapies within biobanking infrastructures in Chennai? How do social categories get entwined with biological materials like cord blood?
Towards deep learning based smart farming for intelligent weeds management in crops

Introduction Deep learning (DL) is a core constituent for building an object detection system and provides a variety of algorithms to be used in a variety of applications. In agriculture, weed management is one of the major concerns, weed detection systems could be of great help to improve production. In this work, we have proposed a DL-based weed detection model that can efficiently be used for effective weed management in crops. Methods Our proposed model uses Convolutional Neural Network based object detection system You Only Look Once (YOLO) for training and prediction. The collected dataset contains RGB images of four different weed species named Grass, Creeping Thistle, Bindweed, and California poppy. This dataset is manipulated by applying LAB (Lightness A and B) and HSV (Hue, Saturation, Value) image transformation techniques and then trained on four YOLO models (v3, v3-tiny, v4, v4-tiny). Results and discussion The effects of image transformation are analyzed, and it is deduced that the model performance is not much affected by this transformation. Inferencing results obtained by making a comparison of correctly predicted weeds are quite promising, among all models implemented in this work, the YOLOv4 model has achieved the highest accuracy. It has correctly predicted 98.88% weeds with an average loss of 1.8 and 73.1% mean average precision value. Future work In the future, we plan to integrate this model in a variable rate sprayer for precise weed management in real time.
Digital twin deployment for smart agriculture in Cloud-Fog-Edge infrastructure

The rapid adoption of Cloud, Fog, and Edge computing paradigms, along with Digital Twin (DT) technology, is being observed across numerous domains. Smart Agriculture is one such domain, where diverse requirements exist for applications that range from Augmented Reality, Satellite, and auto harvesters to a multitude of agricultural devices and sensors. While the integration of Cloud, Fog, and Edge computing can address various challenges, it can also pose some difficulties, including resource allocation, resource scheduling, and task scheduling. To address these challenges and enhance the productivity and sustainability of Smart Agriculture, this paper presents a novel architecture based on Cloud, Fog, Edge computing, and Multi-Agent Systems (MAS), incorporating the concept of Digital Twin. This proposed architecture is implemented in Smart Agricultural farms and fields, opening up new contemporary applications in the Agriculture domain.
Tropical cyclone strike and wind probability applications

Introduction de la notion de probabilite de frappe et de probabilite de vent, pour quantifier la menace d'un cyclone tropical. La frappe du cyclone est definie comme l'evenement se produisant en un point, lorsque la trajectoire passe a moins de 140 km a gauche, ou a moins de 95 km a droite du point de station
Testing the somatic marker hypothesis in decisions-from-experience with non-stationary outcome probabilities

Introduction The Somatic Marker Hypothesis (SMH) posits that in experience-based choice, people develop physiological reactions that mark options as either positive or negative. These somatic markers aid decision making because they differentiate between “good” and “bad” options during pre-choice deliberation. Methods We examined this proposed role for somatic states in two decision-from-experience tasks (each N = 36) in which participants selected repeatedly with full feedback (i.e., for obtained and forgone outcomes) between two unlabeled options that returned wins or losses, with half receiving an additional summary of past outcomes. The probabilities of good and bad outcomes changed at an unannounced point. Participants completed a 100-trial game with a switch in the optimal option after trial 40 (Study 1) or a 200-trial game with switch points after trial 40 and trial 120 (Study 2). Skin conductance (SC) was measured continuously as an index of emotional intensity, from which we extracted measures of anticipatory SC (pre-choice) and outcome SC (post-choice). Results Participants reliably selected the optimal option prior to any switches. They also altered their choices appropriately when the payoffs changed, though optimal play following payoff switches was reduced. Losses resulted in a greater outcome SC than wins, but only in Study 1, as did the finding that the outcome SC was greater when the forgone outcome was positive. Anticipatory SC did not reliably predict optimal play in either study. Discussion These results provide little support for the SMH. Our studies point to the importance of using diverse tasks and measures and very large sample sizes when testing the role of somatic states in decision making.
Induced Pluripotent Stem Cells for Modeling Physiological and Pathological Striated Muscle Complexity

Neuromuscular disorders (NMDs) are a large group of diseases associated with either alterations of skeletal muscle fibers, motor neurons or neuromuscular junctions. Most of these diseases is characterized with muscle weakness or wasting and greatly alter the life of patients. Animal models do not always recapitulate the phenotype of patients. The development of innovative and representative human preclinical models is thus strongly needed for modeling the wide diversity of NMDs, characterization of disease-associated variants, investigation of novel genes function, or the development of therapies. Over the last decade, the use of patient’s derived induced pluripotent stem cells (hiPSC) has resulted in tremendous progress in biomedical research, including for NMDs. Skeletal muscle is a complex tissue with multinucleated muscle fibers supported by a dense extracellular matrix and multiple cell types including motor neurons required for the contractile activity. Major challenges need now to be tackled by the scientific community to increase maturation of muscle fibers in vitro, in particular for modeling adult-onset diseases affecting this tissue (neuromuscular disorders, cachexia, sarcopenia) and the evaluation of therapeutic strategies. In the near future, rapidly evolving bioengineering approaches applied to hiPSC will undoubtedly become highly instrumental for investigating muscle pathophysiology and the development of therapeutic strategies.
Current trends of high-risk gene Cul3 in neurodevelopmental disorders

Cul3 encodes Cullin-3, a core component of the ubiquitin E3 ligase that is involved in protein ubiquitination. Recent studies have identified Cul3 as a high-confidence risk gene in neurodevelopmental disorders (NDDs), especially autism spectrum disorder (ASD). Different strategies have been used to generate animal models with Cul3 deficiency in the central nervous system, including whole-brain knockout (KO), cell-type specific conditional KO (cKO), and brain region-specific knockdown. In this review, we revisited the basic properties of CUL3 and its function under physiological and pathological conditions. Recent clinical studies including case reports and large cohort sequencing studies related to CUl3 in NDDs have been summarized. Moreover, we characterized the behavioral, electrophysiological, and molecular changes in newly developed Cul3 deficiency models. This would guide further studies related to Cul3 in CNS and provide potential therapeutic targets for Cul3-deficiency-induced NDDs, including ASD.
ECG-Gated CCTA in the Assessment of Post-Procedural Complications

Introduction: The aim of our study was to assess the role of ECG-gated coronary CT angiography (CCTA) in the diagnosis, imaging follow-up, and treatment guidance in post-procedural/surgical interventions in the heart and thoracic aorta (PTCA, TAVI, PMK/ICD placement, CABGs). Materials and Methods: We retrospectively evaluated 294 ECG-gated CCTA studies performed in our center from January 2020 to January 2023. CCTA studies were acquired to detect/exclude possible complications related to the endovascular or surgical procedure. Results: There were 27 cases (9.2%) of post-procedural complications. Patients enrolled in the study were 18 males and 9 females (male/female ratio: 2), with age ranging from 47 to 86 years (mean age, 68.3 years). Among percutaneous coronary intervention (PCI) complications, coronary intimal dissection with ascending aorta involvement was found to be the most frequent complication after PTCA (22.2%). Vascular wall pseudoaneurysm formation (11.1%) and coronary stent misalignment or displacement (14.8%) were complications less frequently encountered after PTCA. Right atrial or ventricular perforation with associated hemopericardium were the most common complications (18.5%) after pacemaker implantation. Complications encountered after aortic valve interventions were loosening and dislocation of the prosthesis associated with aortic root pseudoaneurysm (7.4%), para-valvular leak (11.1%), and hemopericardium (7.4%). In one patient who underwent transcatheter repair of patent foramen ovale (3.7%), CTTA detected the dislocation of the Amplatzer septal occluder. Conclusions: ECG-gated CCTA is a fundamental diagnostic tool for the detection of post-procedural endovascular/surgical complications to enable optimal patient management. Radiologists must be familiar with the use of cardiac synchronization in the course of CT and must be aware of all possible complications that can occur in the context of acute settings or routine follow-up studies.