Miracle-dz/UniFAR-FTUs huggingface dataset:
Infections, Reactions of Natural Killer T Cells and Natural Killer Cells, and Kidney Injury

Natural killer T (NKT) cells and NK cells are representative innate immune cells that perform antitumor and antimicrobial functions. The involvement of these cells in various renal diseases, including acute kidney injury (AKI), has recently become evident. Murine NKT cells are activated and cause AKI in response to various stimuli, such as their specific ligand, cytokines, and bacterial components. Both renal vascular endothelial cell injury (via the perforin-mediated pathway) and tubular epithelial cell injury (via the tumor necrosis factor-alpha/Fas ligand pathway) are independently involved in the pathogenesis of AKI. NK cells complement the functions of NKT cells, thereby contributing to the development of infection-associated AKI. Human CD56+ T cells, which are a functional counterpart of murine NKT cells, as well as a subpopulation of CD56+ NK cells, strongly damage intrinsic renal cells in vitro upon their activation, possibly through mechanisms similar to those in mice. These cells are also thought to be involved in the acute exacerbation of pre-existing glomerulonephritis triggered by infection in humans, and their roles in sepsis-associated AKI are currently under investigation. In this review, we will provide an overview of the recent advances in the understanding of the association among infections, NKT and NK cells, and kidney injury, which is much more profound than previously considered. The important role of liver macrophages in the activation of NKT cells will also be introduced.
Traceable Micro-Force Sensor for Instrumented Indentation Calibration

Instrumented indentation testing (IIT), commonly referred to as nanoindentation when small forces are used, is a popular technique for determining the mechanical properties of small volumes of material. Sample preparation is relatively easy, usually requiring only that a smooth surface of the material to be tested be accessible to a contact probe, and instruments that combine sophisticated automation with straightforward user interfaces are available commercially from several manufacturers. In addition, documentary standards are now becoming available from both the International Standards Organization (ISO 14577) and ASTM International (E28 WK382) that define test methods and standard practices for IIT, and will allow the technique to be used to produce material property data that can be used in product specifications. These standards also define the required level of accuracy of the force data produced by IIT instruments, as well as methods to verify that accuracy. For forces below 10 mN, these requirements can be difficult to meet, particularly for instrument owners who need to verify the performance of their instrument as it is installed at their site. In this paper, we describe the development, performance and application of an SI-traceable force sensor system for potential use in the field calibration of commercialmore » IIT instruments. The force sensor itself, based on an elastically deforming capacitance gauge, is small enough to mount in a commercial instrument as if it were a test specimen, and is used in conjunction with an ultra-high accuracy capacitance bridge. The sensor system is calibrated with NIST-traceable masses over the range 5.0 {micro}N through 5.0 mN. We will present data on its accuracy and precision, as well its potential application to the verification of force in commercial instrumented indentation instruments. « less
A Large-Scale k -Nearest Neighbor Classification Algorithm Based on Neighbor Relationship Preservation

Owing to the absence of hypotheses of the underlying distributions of the data and the strong generation ability, the k -nearest neighbor (kNN) classification algorithm is widely used to face recognition, text classification, emotional analysis, and other fields. However, kNN needs to compute the similarity between the unlabeled instance and all the training instances during the prediction process; it is difficult to deal with large-scale data. To overcome this difficulty, an increasing number of acceleration algorithms based on data partition are proposed. However, they lack theoretical analysis about the effect of data partition on classification performance. This paper has made a theoretical analysis of the effect using empirical risk minimization and proposed a large-scale k -nearest neighbor classification algorithm based on neighbor relationship preservation. The process of searching the nearest neighbors is converted to a constrained optimization problem. Then, it gives the estimation of the difference on the objective function value under the optimal solution with data partition and without data partition. According to the obtained estimation, minimizing the similarity of the instances in the different divided subsets can largely reduce the effect of data partition. The minibatch k -means clustering algorithm is chosen to perform data partition for its effectiveness and efficiency. Finally, the nearest neighbors of the test instance are continuously searched from the set generated by successively merging the candidate subsets until they do not change anymore, where the candidate subsets are selected based on the similarity between the test instance and cluster centers. Experiment results on public datasets show that the proposed algorithm can largely keep the same nearest neighbors and no significant difference in classification accuracy as the original kNN classification algorithm and better results than two state-of-the-art algorithms.
Cerebellar degeneration in primary lateral sclerosis: an under-recognized facet of PLS

Abstract While primary lateral sclerosis (PLS) has traditionally been regarded as a pure upper motor neuron disorder, recent clinical, neuroimaging and postmortem studies have confirmed significant extra-motor involvement. Sporadic reports have indicated that in addition to the motor cortex and corticospinal tracts, the cerebellum may also be affected in PLS. Cerebellar manifestations are difficult to ascertain in PLS as the clinical picture is dominated by widespread upper motor neuron signs. The likely contribution of cerebellar dysfunction to gait disturbance, falls, pseudobulbar affect and dysarthria may be overlooked in the context of progressive spasticity. The objective of this study is the comprehensive characterization of cerebellar gray and white matter degeneration in PLS using multiparametric quantitative neuroimaging methods to systematically evaluate each cerebellar lobule and peduncle. Forty-two patients with PLS and 117 demographically-matched healthy controls were enrolled in a prospective MRI study. Complementary volumetric and voxelwise analyses revealed focal cerebellar alterations instead of global cerebellar atrophy. Bilateral gray matter volume reductions were observed in lobules III, IV and VIIb. Significant diffusivity alterations within the superior cerebellar peduncle indicate disruption of the main cerebellar outflow tracts. These findings suggest that the considerable intra-cerebellar disease-burden is coupled with concomitant cerebro-cerebellar connectivity disruptions. While cerebellar dysfunction is challenging to demonstrate clinically, cerebellar pathology is likely to be a significant contributor to disability in PLS.
Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model

Background/aims This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms. The primary interest is in reducing opioid overdose fatalities, which will be collected as a count outcome at the community level. Communities range in size from thousands to over one million residents, and fatalities are expected to be rare. Traditional marginal modeling approaches in the cluster randomized trial literature include the use of generalized estimating equations with an exchangeable correlation structure when utilizing subject-level data, or analogously quasi-likelihood based on an over-dispersed binomial variance when utilizing community-level data. These approaches account for and estimate the intra-cluster correlation coefficient, which should be provided in the results from a cluster randomized trial. Alternatively, the coefficient of variation or R coefficient could be reported. In this article, we show that negative binomial regression can also be utilized when communities are large and events are rare. The objectives of this article are (1) to show that the negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model and to explain why the estimates may differ; (2) to derive formulas relating the negative binomial overdispersion parameter k with the intra-cluster correlation coefficient, coefficient of variation, and R coefficient; and (3) analyze pre-intervention data from the HEALing Communities Study to demonstrate and contrast models and to show how to report the intra-cluster correlation coefficient, coefficient of variation, and R coefficient when utilizing negative binomial regression. Methods Negative binomial and over-dispersed binomial regression modeling are contrasted in terms of model setup, regression parameter estimation, and formulation of the overdispersion parameter. Three specific models are used to illustrate concepts and address the third objective. Results The negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model, although estimates may differ. Practical differences arise in regard to how overdispersion, and hence the intra-cluster correlation coefficient is modeled. The negative binomial overdispersion parameter is approximately equal to the ratio of the intra-cluster correlation coefficient and marginal probability, the square of the coefficient of variation, and the R coefficient minus 1. As a result, estimates corresponding to all four of these different types of overdispersion parameterizations can be reported when utilizing negative binomial regression. Conclusion Negative binomial regression provides a valid, practical, alternative approach to the analysis of count data, and corresponding reporting of overdispersion parameters, from community randomized trials in which communities are large and events are rare.
PEG‐Like Brush Polymer Conjugate of RNA Aptamer That Shows Reversible Anticoagulant Activity and Minimal Immune Response

Ribonucleic acid (RNA) therapeutics are an emerging class of drugs. RNA aptamers are of significant therapeutic and clinical interest because their activity can be easily reversed in vivo—a useful feature that is difficult to achieve using other therapeutic modalities. Despite their therapeutic promise, RNA aptamers are limited by their poor blood circulation. The attachment of polyethylene glycol (PEG) to RNA aptamers addresses this limitation. However, an RNA aptamer‐PEG conjugate that is a reversible anticoagulant fails in a clinical trial due to the reactivity of the conjugate with pre‐existing PEG antibodies and has cast a pall over PEGylation of aptamers and other biologics, despite its long history of utility in drug delivery. Here, PEG antibody‐reactivity of this RNA aptamer is eliminated by conjugating it to a next‐generation PEG‐like brush polymer—poly[(oligoethylene glycol) methyl ether methacrylate)] (POEGMA). The conjugate retained the drug's therapeutic action and the ability to be easily reversed. Importantly, this conjugate does not bind pre‐existing PEG antibodies that are prevalent in humans and does not induce a humoral immune response against the polymer itself in mice. These findings suggest a path to rescuing the PEGylation of RNA therapeutics and vaccines from the deleterious side‐effects of PEG.
On Evolutionary Vaccination Game in Activity-Driven Networks

Since human face-to-face communications change over time, their perceived probabilities associated with uncertain outcomes usually present a nonlinear fashion in reality. This article incorporates both humans active characteristics and risk perception into epidemic spreading and explores a comprehensive evolutionary vaccination game in activity-driven networks. According to the weighting effect, the individuals’ activity rate thresholds are obtained in different cases under the framework of the pure Nash equilibrium. Furthermore, how the number of connected edges of activated individuals <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> and infection rate <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> affect individuals’ vaccination, decision-making is theoretically analyzed. It is proven that some unvaccinated individuals gradually become vaccinated individuals with the increase of <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>. Moreover, there is a unique pure Nash equilibrium social state (Pareto optimization), and the pure Nash equilibrium together with Pareto optimization has the same equilibrium for our proposed evolutionary vaccination game, which provides an alternative condition judging the stability of game system. In the case of complete information and individual complete rationality, the factors, including vaccination cost, individuals’ activity rate, the number of connected edges of activated individuals, and infection rate, have a significant influence on the final average social cost.
The Readiness of Australian Food Regulation for the Use of Nanotechnology in Food and Food Packaging

This paper first briefly introduces the reader to nanotechnology and the potential health risks it raises. It then reviews how nanotechnology is or may be used by the food industry so that challenges that must be addressed by food regulations can be better understood. The application of current Australian food regulations to nanofoods and their suitability for meeting those challenges is then examined. International responses to the problem are described before conclusions and suggested responses are provided.
Study on Probabilistic Demand Models of Tunnel Linings Subjected to Transverse Seismic Load

Since there have been cases of severe damage or even collapse of tunnel structures in recent major earthquakes, the seismic safety of tunnel structures has attracted widespread attention from scholars. In the performance-based seismic design, it is essential to establish a universal and practical demand model. In this paper, to facilitate the use in practice, the probabilistic demand models are developed by adding linear correction term and random term to the commonly used deterministic models. Two types of demand measures, the bending moment and the axial force of the lining to transverse seismic load are considered. The uniform design method is used to generate the samples to calibrate the model parameters, and the uncertainties of ground motions, site properties, and tunnel dimensions are considered. The parameters of the demand models are estimated by the least square method. The probabilistic demand models established in this paper can accurately and reliably evaluate the seismic demand of the tunnel and obtain the probabilistic distribution of the demand, which is of great significance for the seismic vulnerability analysis of tunnel structures. 
Efficient Editing of CSLD2 Orthologue by CRISPR/Cas9 Affects Cell Morphogenesis of Root Hair in Spinach

CRISPR/Cas9 is a valuable tool and has been extensively employed to perform gene editing in plants. However, CRISPR/Cas9 has not been successfully used in spinach, an important leafy vegetable crop. Here, we precisely edited Spo23361 and Spo10340, two cellulose synthase-like D (CSLD) genes involved in root hair formation of spinach hairy roots, using CRISPR/Cas9 system. Four mutation types (i.e., replacement, insertion, deletion, and combined mutations) were observed, among which the deletion accounted for the vast majority (about 64.1%). Mutation rate differed largely among different targets. Seven homozygous/bi-allelic and eight heterozygous/chimeric mutated lines of Spo23361 were obtained from 15 independent transgenic hairy root lines. All of the seven homozygous/bi-allelic lines displayed bulking and short root hairs, which exhibited the characteristics of Arabidopsis csld2 mutants. Thirteen heterozygous/chimeric mutated lines, but no homozygous/bi-allelic lines, of Spo10340 were obtained from 15 independent transgenic hairy root lines, all of which showed similar phenotype of root hair with normal hairy roots. The transcriptomic analysis further revealed that multiple gene expressions for cell wall modulation and membrane trafficking were disturbed, which might result in the inhibition of root hair growth in Spo23361 mutants. Our results indicate that Agrobacterium rhizogenes-mediated transformation using CRISPR/Cas9 is a simple and efficient genome editing tool in spinach. It lays a solid foundation for large-scale genome editing in spinach in future.
Design of a Remotely Operated Vehicle (ROV) for Biofoul Cleaning and Inspection of Variety of Underwater Structures

Biofouling is a thin layer of bacterial formation on surfaces in prolonged contact with water. Biofouling is the primary cause of decay in a lifetime in dams and reduces energy output from reservoirs and ship hulls.Our primary aim is to effectively remove biofouling of almost every underwater surface and construction mentioned above. The product will result in less human interference in such dangerous and less efficient aquatic cleaning activities, decreasing the cost and increasing the cleaning operations’ safety and efficiency.
Analysis of Movement Entropy during Community Dance Programs for People with Parkinson’s Disease and Older Adults: A Cohort Study

Dance therapy can improve motor skills, balance, posture, and gait in people diagnosed with Parkinson’s disease (PD) and healthy older adults (OA). It is not clear how specific movement patterns during dance promote these benefits. The purpose of this cohort study was to identify differences and complexity in dance movement patterns among different dance styles for PD and OA participants in community dance programs using approximate entropy (ApEn) analysis. The hypothesis was that PD participants will show greater ApEn during dance than OA participants and that the unique dance style of tango with more pronounced foot technique and sharp direction changes will show greater ApEn than smoother dance types such as foxtrot and waltz characterized by gradual changes in direction and gliding movement with rise and fall. Individuals participated in one-hour community dance classes. Movement data were captured using porTable 3D motion capture sensors attached to the arms, torso and legs. Classes were also video recorded to assist in analyzing the dance steps. Movement patterns were captured and ApEn was calculated to quantify the complexity of movements. Participants with PD had greater ApEn in right knee flexion during dance movements than left knee flexion (p = 0.02), greater ApEn of right than left hip flexion (p = 0.05), and greater left hip rotation than right (p = 0.03). There was no significant difference in ApEn of body movements (p > 0.4) or mean body movements (p > 0.3) at any body-segment in OA. ApEn analysis is valuable for quantifying the degree of control and predictability of dance movements and could be used as another tool to assess the movement control of dancers and aid in the development of dance therapies.
The impact of competitive integrated employment on economic, psychological, and physical health outcomes for individuals with intellectual and developmental disabilities.

BACKGROUND Although competitive integrated employment (CIE) has been established as a goal of employment research, policy, and practice for individuals with intellectual and developmental disabilities, the secondary benefits of CIE are rarely discussed. AIMS The purpose of this systematic review was to analyze and synthesise research related to the association between CIE and improved economic, psychological health, and physical health outcomes for individuals with intellectual and developmental disabilities. MATERIALS & METHODS Our review searched peer-reviewed literature from seven electronic databases and screened 1110 peer-reviewed articles based on inclusion criteria established following PRISMA guidelines. RESULTS Our search procedures produced a final sample of 17 studies. DISCUSSION Implications of these findings for future research, policy, and practice are provided. CONCLUSION Our findings showed strong evidence associated with economic outcomes of CIE, moderate associated with psychological health outcomes, and limited evidence related to physical health outcomes.
Evolutionary Game Analysis of Responding to the EU’s Carbon Border Adjustment Mechanism

The European Union (EU) views the carbon border adjustment mechanism (CBAM) as a measure to tackle carbon leakage, which will have a profound impact on non-EU countries’ exports. Policymakers are faced with the question of how to deal with the CBAM. In contrast to previous studies, we explore the effects of the CBAM on non-EU countries from a dynamic game perspective. This study analyzed the potential effects of the CBAM on China and found that the government and export companies are the two main stakeholders. We found that they can both choose whether to respond actively or passively. Based on their interactive relationship, we adopted an evolutionary game to model the nexus between the government and export companies. We analyzed the evolutionary stable state of each stakeholder and the whole game with the replicator dynamic equation system. To make the system evolve to the optimal state where the government reacts actively and export companies implement low-carbon production, we provide a policy mechanism for how to set key parameters’ values. We used numerical simulation to verify the policy design and to conduct sensitivity analyses of the key parameters. Our results show that, when two stakeholders positively react to the CBAM, it is necessary to increase their profits and to reduce their costs. Therefore, some suggestions are proposed, including optimizing the trade structure, strengthening cooperation with the EU, improving the current carbon market, and adopting carbon tax.
Analysis of the Changes in Occlusal Plane Inclination in a Class II Deep Bite “Teen” Patient Treated with Clear Aligners: A Case Report

Background: Optimal management of hypodivergent growing patients demands a strict control of vertical dimension and to exploit the growth potential. If a deep bite malocclusion causes a traumatic contact between the upper and lower incisors and affects the facial appearance, an early interceptive treatment is recommended. The aim of this case report is to outline the clinical management of the occlusal plane of a growing Class II division 1 deep bite patient treated with aligners and Class II elastics. Methods: The treatment lasted 11 months and was divided into two phases. Treatment goals included improvement of the soft tissue profile and basal bone relationships through an increase in the mandibular third of the face and a sagittal advancement of the mandible. The correction of the curve of Spee involved intrusion of the mandibular incisors and extrusion of the mandibular premolars. Results: The cephalometric analysis at the end of the treatment displayed significant differences in the skeletal and occlusal pattern along with aesthetic improvements. Conclusion: The final cephalogram showed a consistency between the planned tooth movement and the clinical results. Although definitive recommendations must be withheld until longer follow-up is available, the patient presented here shows that the treatment protocol yielded positive mandibular growth.