Miracle-dz/UniFAR-FTUs huggingface dataset:
Robotic Emulation of Candidate Prosthetic Foot Designs May Enable Efficient, Evidence-Based, and Individualized Prescriptions

ABSTRACT Introduction The design and selection of lower-limb prosthetic devices is currently hampered by a shortage of evidence to drive the choice of prosthetic foot parameters. We propose a new approach wherein prostheses could be designed, specified, and provided based on individualized measurements of the benefits provided by candidate feet. In this manuscript, we present a pilot test of this evidence-based and personalized process. Methods We previously developed a “prosthetic foot emulator,” a wearable robotic system that provides users with the physical sensation of trying on different prosthetic feet before definitive fitting. Here we detail preliminary demonstrations of two possible approaches to personalizing foot design: 1) an emulation and test-drive strategy of representative commercial foot models, and 2) a prosthetist-driven tuning procedure to optimize foot parameters. Results The first experiment demonstrated large and sometimes surprising differences in optimal prosthetic foot parameters across a variety of subjects, walking conditions, and outcome measures. The second experiment demonstrated a quick and effective simple manual tuning procedure for identifying preferred prosthetic foot parameters. Conclusions Emulator-based approaches could improve individualization of prosthetic foot prescription. The present results motivate future clinical studies of the validity, efficacy, and economics of the approach across larger and more diverse subject populations. Clinical Relevance Today, emulator technology is being used to accelerate research and development of novel prosthetic and orthotic devices. In the future, after further refinement and validation, this technology could benefit clinical practice by providing a means for rapid test-driving and optimal selection of clinically available prosthetic feet.
A Secure Multilayer Architecture for Software-Defined Space Information Networks

Both space information networks (SINs) and software-defined networking (SDN) have gained considerable attention from industry and academia in recent years. Due to the unique characteristics of SDN and SINs, a hybrid version of them, e.g., software-defined SINs, can handle many complicated tasks. Some technological advances based on SDN are increasingly being deployed to satellite networks. In this context, the multilayer architecture makes it difficult to control the different physical devices with maximum network performance for vast volumes of traffic transmission. The multilayer architecture is considered to be a versatile framework to include different applications and facilities efficiently, while it enjoys the support of SDN as well. In this context, this article proposes a secure multilayer SDN architecture that separates the paradigm into terrestrial, aerial, and ground domains and facilitates security solutions. We explore the specifics of this architecture's development and implementation, hence finding out some problems and unanswered questions. In addition, our descriptive results demonstrate that the proposed architecture will significantly improve the multilayer efficiency gains of configuration upgrading and decision-making.
The interplay between cerebellum and basal ganglia in motor adaptation: A modeling study

Motor adaptation to perturbations is provided by learning mechanisms operating in the cerebellum and basal ganglia. The cerebellum normally performs motor adaptation through supervised learning using information about movement error provided by visual feedback. However, if visual feedback is critically distorted, the system may disengage cerebellar error-based learning and switch to reinforcement learning mechanisms mediated by basal ganglia. Yet, the exact conditions and mechanisms of cerebellum and basal ganglia involvement in motor adaptation remain unknown. We use mathematical modeling to simulate control of planar reaching movements that relies on both error-based and non-error-based learning mechanisms. We show that for learning to be efficient only one of these mechanisms should be active at a time. We suggest that switching between the mechanisms is provided by a special circuit that effectively suppresses the learning process in one structure and enables it in the other. To do so, this circuit modulates learning rate in the cerebellum and dopamine release in basal ganglia depending on error-based learning efficiency. We use the model to explain and interpret experimental data on error- and non-error-based motor adaptation under different conditions.
Complementary Transcriptomic and Proteomic Analysis Reveals a Complex Network Regulating Pollen Abortion in GMS (msc-1) Pepper (Capsicum annuum L.)

Pepper (Capsicum annuum L.) is a globally important horticultural crop. Use of the genic male-sterile (GMS) line enables efficient commercial hybrid pepper seed production. However, the mechanisms of pepper GMS functioning remain unclear. In this study, we used proteomic and transcriptomic analysis to identify proteins and genes related to genic male sterility. A total of 764 differentially expressed proteins (DEPs) and 1069 differentially expressed genes (DEGs) were identified in the proteomic and transcriptomic level respectively, and 52 genes (hereafter “cor-DEGs-DEPs” genes) were detected at both levels. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis identified 13 DEPs and 14 DEGs involved in tapetum and pollen development. Among the 13 DEPs identified, eight were involved in pollen exine formation, and they were all up-regulated in the fertile line 16C1369B. For the 14 DEGs identified, ABORTED MICROSPORES (AMS) and DEFECTIVE IN TAPETAL DEVELOPMENT AND FUNCTION1 (TDF1) were involved in tapetum development, and both are possibly regulated by Msc-1. All of these genes were detected and confirmed by qRT-PCR. The presence of these genes suggests their possible role in tapetum and pollen exine formation in GMS pepper. Most key genes and transcription factors involved in these processes were down-regulated in the sterile line 16C1369A. This study provides a better understanding of GMS (msc-1) molecular functioning in pepper.
Antimicrobial Activity of Lignin and Lignin-Derived Cellulose and Chitosan Composites against Selected Pathogenic and Spoilage Microorganisms

The antiradical and antimicrobial activity of lignin and lignin-based films are both of great interest for applications such as food packaging additives. The polyphenolic structure of lignin in addition to the presence of O-containing functional groups is potentially responsible for these activities. This study used DPPH assays to discuss the antiradical activity of HPMC/lignin and HPMC/lignin/chitosan films. The scavenging activity (SA) of both binary (HPMC/lignin) and ternary (HPMC/lignin/chitosan) systems was affected by the percentage of the added lignin: the 5% addition showed the highest activity and the 30% addition had the lowest. Both scavenging activity and antimicrobial activity are dependent on the biomass source showing the following trend: organosolv of softwood > kraft of softwood > organosolv of grass. Testing the antimicrobial activities of lignins and lignin-containing films showed high antimicrobial activities against Gram-positive and Gram-negative bacteria at 35 °C and at low temperatures (0–7 °C). Purification of kraft lignin has a negative effect on the antimicrobial activity while storage has positive effect. The lignin release in the produced films affected the activity positively and the chitosan addition enhances the activity even more for both Gram-positive and Gram-negative bacteria. Testing the films against spoilage bacteria that grow at low temperatures revealed the activity of the 30% addition on HPMC/L1 film against both B. thermosphacta and P. fluorescens while L5 was active only against B. thermosphacta. In HPMC/lignin/chitosan films, the 5% addition exhibited activity against both B. thermosphacta and P. fluorescens.
Application of Artificial Neural Networks to Identify Alzheimer’s Disease Using Cerebral Perfusion SPECT Data

The aim of this study was to demonstrate the usefulness of artificial neural networks in Alzheimer disease diagnosis (AD) using data of brain single photon emission computed tomography (SPECT). The results were compared with discriminant analysis. The study population consisted of 132 clinically diagnosed patients. There were 72 subjects with AD and 60 belonging to the normal control group. The artificial neural network used 36 numerical values being the count numbers obtained for each area of brain SPECT. These numbers determined the set of input data for the artificial neural network. The sensitivity of Alzheimer disease diagnosis detection by artificial neural network and discriminant analysis were 93.8% and 86.1%, respectively, and the corresponding specificity was 100% and 95%. We also used receiver operating characteristic curve (ROC) analysis and areas under receiver operating characteristics curves were correspondingly 0.97 (p < 0.0001) for the artificial neural networks (ANN) and 0.96 (p < 0.0001) for discriminant analysis. In conclusion, artificial neural networks and conventional statistics methods (discriminant analysis) are a useful tool in Alzheimer disease diagnosis.
Noncanonical TGFβ Pathway Relieves the Blockade of IL1β/TGFβ-Mediated Crosstalk between Tumor and Stroma: TGFBR1 and TAK1 Inhibition in Colorectal Cancer

Purpose: The aim of the study is blocking the recruitment of a protective stroma by altering the crosstalk between normal stromal cells and tumor cells for stripping tumors of the protection conferred by the microenvironment. Experimental Design: A transcriptomic analysis of cocultured normal colonic fibroblasts and colorectal tumor cells was performed. We focused on the study of molecules that mediate the communication between both compartments and that entail fibroblasts’ activation and the alteration of the sensitivity to chemotherapy. We identified targets for the blocking of the tumor–stroma interaction. Finally, we tested, in vivo, the blockade of the tumor–stroma interaction in orthotopic models derived from patients and in models of acquired resistance to oxaliplatin. Results: IL1β/TGFβ1 are the triggers for fibroblasts’ recruitment and conversion into carcinoma-associated fibroblasts (CAF) in colorectal cancer. CAFs then secrete proinflammatory factors that alter sensitivity in tumor cells, activating JAK/STAT and PI3KCA/AKT pathways. Blocking such crosstalk with a neutralizing IL1β antibody and a TGFBR1 inhibitor is relieved by the TAK1-mediated activation of the noncanonical TGFβ pathway, which induces a change in the cytokine/chemokine repertoire that maintains a sustained activation of AKT in tumor cells. TAK1 plus TGFBR1 inhibition blocks IL1β/TGFβ1-mediated fibroblast activation, decreasing the secretion of proinflammatory cytokines. In turn, tumor cells became more sensitive to chemotherapy. In vivo, the combination of a TAK1 inhibitor plus TGFBR1 inhibitor reduced the metastatic capacity of tumor cells and the recruitment of fibroblasts. Conclusions: Our findings provide a translational rationale for the inhibition of TAK1 and TGFBR1 to remove the chemoprotection conferred by CAFs.
Antioxidative and Potentially Anti-inflammatory Activity of Phenolics from Lovage Leaves Levisticum officinale Koch Elicited with Jasmonic Acid and Yeast Extract

The effect of elicitation with jasmonic acids (JA) and yeast extract (YE) on the production of phenolic compounds as well as the antioxidant and anti-inflammatory properties of phenolic extracts of lovage was evaluated. The analysis of phenolic compounds carried out with the UPLC-MS technique indicated that rutin was the dominant flavonoid, while 5-caffeoylquinic acid was the main component in the phenolic acid fraction in the lovage leaves. The application of 10 µM JA increased the content of most of the identified phenolic compounds. The highest antioxidant activities estimated as free radical scavenging activity against ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) and reducing power were determined for the sample elicited with 10 µM JA, while this value determined as iron chelating ability was the highest for the 0.1% YE-elicited lovage. The 0.1% and 1% YE elicitation also caused significant elevation of the lipoxygenase (LOX) inhibition ability, while all the concentrations of the tested elicitors significantly improved the ability to inhibit cyclooxygenase 2 (COX2) (best results were detected for the 10 µM JA and 0.1% YE2 sample). Thus, 0.1% yeast extract and 10 µM jasmonic acid proved to be most effective in elevation of the biological activity of lovage.
In Vitro and In Vivo Studies of Hydrophilic Electrospun PLA95/β-TCP Membranes for Guided Tissue Regeneration (GTR) Applications

The guided tissue regeneration (GTR) membrane is a barrier intended to maintain a space for alveolar bone and periodontal ligament tissue regeneration but prevent the migration of fast-growing soft tissue into the defect sites. This study evaluated the physical properties, in vivo animal study, and clinical efficacy of hydrophilic PLA95/β-TCP GTR membranes prepared by electrospinning (ES). The morphology and cytotoxicity of ES PLA95/β-TCP membranes were evaluated by SEM and 3-(4,5-cimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) respectively. The cementum and bone height were measured by an animal study at 8 and 16 weeks after surgery. Fifteen periodontal patients were selected for the clinical trial by using a commercial product and the ES PLA95/β-TCP membrane. Radiographs and various indexes were measured six months before and after surgery. The average fiber diameter for this ES PLA95/β-TCP membrane was 2.37 ± 0.86 µm. The MTT result for the ES PLA95/β-TCP membrane showed negative for cytotoxicity. The significant differences in the cementum and bone height were observed between empty control and the ES PLA95/β-TCP membrane in the animal model (p < 0.05). Clinical trial results showed clinical attachment level (CAL) of both control and ES PLA95/β-TCP groups, with a significant difference from the pre-surgery results after six months. This study demonstrated that the ES PLA95/β-TCP membrane can be used as an alternative GTR membrane for clinical applications.
CONDITIONS OF CLINICAL SYMPTOMS AND LIFE OF VANAME SHRIMP IN PREVENTION OF Vibrio alginolyticus INFECTION USING MIANA LEAF EXTRACT

This study aims to determine the clinical symptoms and survival of white vaname shrimp in the prevention of Vibrio alginolyticus infection using miana leaf extract. The study consisted of 4 treatments and 3 replications. The treatments in this study were 1 treatment and 3 treatments using different concentrations of bacteria, namely 103 CFU/ml, 105 CFU/ml, and 107 CFU/ml. The research was carried out in June-July 2020 at the Hatchery Laboratory of the Faculty of Marine and Fisheries Sciences, Hasanuddin University. Data analysis used descriptive analysis and analysis of variance (ANOVA). The results showed that A (control) shrimp was under normal conditions, treatment B (103 CFU/ml) was red, treated C (105 CFU/ml) was red and had necrosis of the body, and treatment D (107 CFU/ml) was shrimp. reddening, necrosis of tail and body segments. The results of data analysis showed that the use of miana leaf extract had a significant effect (p<0.05) on the use of live vaname shrimp. The highest vaname shrimp survival was treatment A (control) at 100%, treatment B (103 CFU/ml) at 90%, treatment C (105 CFU/ml) at 63.33% and treatment D (107 CFU/ml) by 40%.
Effectiveness of Counseling on Chronic Pain Management in Patients with Temporomandibular Disorders.

AIMS To evaluate the effectiveness of counseling on pain intensity and oral health-related quality of life (OHRQoL) in temporomandibular disorders (TMD) patients. METHODS Fifty female patients diagnosed with TMD were divided into two groups: a group of waiting list patients (control group) and a group of patients who received counseling therapy (experimental group) involving education about etiologic factors, avoidance of parafunctional habits, and sleep, as well as dietary advice. All patients were evaluated at baseline and 7, 15, 30, and 60 days later. Patients reported pain intensity using a visual analog scale (VAS), and the Oral Health Impact Profile (OHIP-14) was used to assess the impact of pain on OHRQoL. Statistical analyses were performed using the split-plot analysis of variance (SPANOVA) design, with post hoc Student t tests for independent samples and for dependent samples, adopting a significance level of P < . 05. RESULTS The control group consisted of 24 female patients with a mean age of 39.96 ± 13.93 years, and the experimental group consisted of 26 female patients with a mean age of 35.15 ± 10.78 years. Counseling was considered effective for reducing pain intensity, with a significant improvement observed at 7 days (P < .001). Counseling was also responsible for a significant improvement in the impact of TMD on OHRQoL at all follow-up time points analyzed (P < .001). When comparing the groups, a significant difference was observed for both pain intensity and TMD impact on OHRQoL during follow-up (P < .05). CONCLUSION Counseling seems to significantly improve pain and OHRQoL in patients.
Signatures of Divergence, Invasiveness, and Terrestrialization Revealed by Four Apple Snail Genomes

Abstract The family Ampullariidae includes both aquatic and amphibious apple snails. They are an emerging model for evolutionary studies due to the high diversity, ancient history, and wide geographical distribution. Insight into drivers of ampullariid evolution is hampered, however, by the lack of genomic resources. Here, we report the genomes of four ampullariids spanning the Old World (Lanistes nyassanus) and New World (Pomacea canaliculata, P. maculata, and Marisa cornuarietis) clades. The ampullariid genomes have conserved ancient bilaterial karyotype features and a novel Hox gene cluster rearrangement, making them valuable in comparative genomic studies. They have expanded gene families related to environmental sensing and cellulose digestion, which may have facilitated some ampullarids to become notorious invasive pests. In the amphibious Pomacea, novel acquisition of an egg neurotoxin and a protein for making the calcareous eggshell may have been key adaptations enabling their transition from underwater to terrestrial egg deposition.
Human CST suppresses origin licensing and promotes AND-1/Ctf4 chromatin association

This study suggests a novel role of the telomere-associated human CST complex in suppressing origin licensing, through interactions with MCM, while promoting the recruitment of AND-1 and DNA polymerase alpha for replisome formation. Human CTC1-STN1-TEN1 (CST) is an RPA-like single-stranded DNA-binding protein that interacts with DNA polymerase α-primase (pol α) and functions in telomere replication. Previous studies suggest that CST also promotes replication restart after fork stalling. However, the precise role of CST in genome-wide replication remains unclear. In this study, we sought to understand whether CST alters origin licensing and activation. Replication origins are licensed by loading of the minichromosome maintenance 2–7 (MCM) complex in G1 followed by replisome assembly and origin firing in S-phase. We find that CST directly interacts with the MCM complex and disrupts binding of CDT1 to MCM, leading to decreased origin licensing. We also show that CST enhances replisome assembly by promoting AND-1/pol α chromatin association. Moreover, these interactions are not dependent on exogenous replication stress, suggesting that CST acts as a specialized replication factor during normal replication. Overall, our findings implicate CST as a novel regulator of origin licensing and replisome assembly/fork progression through interactions with MCM, AND-1, and pol α.
Mathematical Approach to N-Centered DFT and Associated Methods for the Study of Open Systems

A fundamental aspect of the study of N−electronic systems (systems containing N electrons) is to obtain information on the states in which these systems have minimal energy. In practice a numerical search of such states is impossible to carry out, so that alternative approaches have been developped, the one around which this work revolves being to consider electronic systems through their electronic density rather than their state. This approach, known today as Density Functional Theory (DFT), was formalised in Kohn and Sham’s seminal article [1] and its mathematical aspects were studied a few years later by Lieb [2]. Since then, the ideas leading to the construction of DFT have been adapted to the context of electronic systems with a fractionnal number of electrons (open systems), first through PPLB DFT[3] and more recently through the definition of N−centered DFT[4, 5]. In both cases it is unclear wherether the mathematical properties established for classical DFT can be expected to hold true. This question is the main problematic of our work, in which we shall study the analogy between N−centered and classical DFT, from their construction to the methods that are derived from them. This will lead us to construct a Kohn-Sham scheme for N−centered DFT, investigate the links between this theory and optimal transport and present the Hubbard Dimer in this particular situation.
Efficient Classification of Motor Imagery Electroencephalography Signals Using Deep Learning Methods

Single-trial motor imagery classification is a crucial aspect of brain–computer applications. Therefore, it is necessary to extract and discriminate signal features involving motor imagery movements. Riemannian geometry-based feature extraction methods are effective when designing these types of motor-imagery-based brain–computer interface applications. In the field of information theory, Riemannian geometry is mainly used with covariance matrices. Accordingly, investigations showed that if the method is used after the execution of the filterbank approach, the covariance matrix preserves the frequency and spatial information of the signal. Deep-learning methods are superior when the data availability is abundant and while there is a large number of features. The purpose of this study is to a) show how to use a single deep-learning-based classifier in conjunction with BCI (brain–computer interface) applications with the CSP (common spatial features) and the Riemannian geometry feature extraction methods in BCI applications and to b) describe one of the wrapper feature-selection algorithms, referred to as the particle swarm optimization, in combination with a decision tree algorithm. In this work, the CSP method was used for a multiclass case by using only one classifier. Additionally, a combination of power spectrum density features with covariance matrices mapped onto the tangent space of a Riemannian manifold was used. Furthermore, the particle swarm optimization method was implied to ease the training by penalizing bad features, and the moving windows method was used for augmentation. After empirical study, the convolutional neural network was adopted to classify the pre-processed data. Our proposed method improved the classification accuracy for several subjects that comprised the well-known BCI competition IV 2a dataset.
Effects of reallocating sedentary time with physical activity on quality of life indicators in breast cancer survivors

Physical activity is associated with better quality of life (QOL) among breast cancer survivors. However, it is unknown the extent to which time spent sedentary or replacing this time with active behaviors may affect QOL. Our aim was to determine the effect of substituting time between sedentary and active behaviors on QOL indicators in breast cancer survivors.