Miracle-dz/UniFAR-FTUs huggingface dataset:
Manufacturability and functionality assessment of different formats of T-cell engaging bispecific antibodies

ABSTRACT T-cell-engaging bispecific antibodies (T-bsAbs) are promising immunotherapies for cancer treatment due to their capability of redirecting T-cells toward destroying tumor cells. Numerous T-bsAb formats have been developed, each with advantages and disadvantages in terms of developability, immunogenicity, effector functions, and pharmacokinetics. Here, we systematically compared T-bsAbs produced using eight different formats, evaluating the effect of molecular design of T-bsAbs on their manufacturability and functionality. These eight T-bsAb formats were constructed using antigen-binding fragments (Fabs) and single-chain variable fragments (scFvs) of antibodies linked to the crystallizable fragment (Fc) domain of immunoglobulin G. To ensure a fair comparison of growth and production data, we used recombinase-mediated cassette exchange technology to generate the T-bsAb-producing CHO cell lines. The produced T-bsAbs were assessed for their purification profile and recovery, binding capability, and biological activities. Our findings indicated that the manufacturability of bsAbs was adversely affected with increased number of scFv building blocks, while the functionality was affected by the combination of multiple factors, including the binding affinity and avidity of targeting moieties and the flexibility and geometry of formats. These results provide valuable insights into the impact of the format design on the optimal production and function of T-bsAbs.
Point-of-care ultrasound: The new district focus

Background Point-of-care ultrasound (POCUS) improves patient outcomes. The current POCUS curriculum of the Emergency Medicine Society of South Africa is based on guidelines from the United Kingdom with a different burden of disease (BoD) and available resources than encountered locally. Aim To determine which modules of the POCUS curriculum should be implemented to better equip doctors working at a district hospital in the West Coast District (WCD), South Africa. Setting Six district hospitals within the WCD. Methods A descriptive cross-sectional survey with questionnaires for medical managers (MMs) and medical practitioners (MPs). Results A response rate of 78.9% for MPs and 100% for MMs was obtained. MPs rated the following modules of POCUS most relevant to their daily practice: (1) first trimester pregnancy; (2) deep vein thrombosis; (3) extended focused assessment with sonography in trauma; (4) central vascular access; and (5) focused assessment with sonography for human immunodeficiency virus (HIV) and tuberculosis (TB) (FASH). Conclusion There is a need for a POCUS curriculum informed by the local pattern of disease. Priority modules were identified based on the local BoD and reported relevance to practice. Despite the availability of ultrasound machines within the WCD, few MPs were accredited and able to perform POCUS independently. There is a need to implement training programmes for medical interns, MPs, family medicine registrars and family physicians working in district hospitals. A relevant curriculum for POCUS training based on the local needs within communities has to be developed. Contribution This study emphasises the need for a locally informed POCUS curriculum and training programmes.
Operational manager’s knowledge and attitudes toward data and universal health coverage indicators in primary health clinics in Ugu, South Africa

ABSTRACT Universal health coverage (UHC) aims to ensure people have access to the health services they need. Sixteen tracer indicators were developed for implementation by countries to measure UHC in the health system. South Africa uses 15 of the proposed 16 indicators. Operational managers in the public health care sector collect data and report on these indicators at a primary health clinic level. This qualitative study explored the knowledge and attitudes of managers toward data and UHC service indicators in a sub-district in Ugu, KwaZulu-Natal, South Africa. Operational managers saw data collection as information gathering, measuring performance and driving action. They understood UHC indicators as ‘health for all’ linking them to National Department of Health Strategic plans and saw the value of indicators for health promotion. They found the lack of training, inadequate numeracy skills, requests for data from multiple spheres of government and the indicator targets that they had to reach as challenging and untenable. While operational managers made the link between data, measuring performance and action, the limited training, skills gaps and pressures from higher levels of government may impede their ability to use data for local level planning and decision making.
The Exo-Life Finder Telescope (ELF): design and beam synthesis concepts

Currently planned massively segmented telescopes like the European Extremely Large Telescope (EELT)1 or the Thirty Meter Telescope (TMT)2, use “Keck-era” optics. Their mirror subapertures create a dynamically rigid primary optical surface from 100’s of 1m-scale few-cm thick mirrors. We suggest that a dedicated telescope for distinguishing reflected exoplanet light from its host star may not follow these design principles. To reduce moving mass and telescope-scattered light, a post-Keck era large telescope could use new technologies that replace this opto-mechanical stiffness with massively parallel active electro-optics and interferometric concepts. This opens the intriguing possibility of building a dedicated ground-based exoplanet telescope with an aperture of 20m at a cost-scale of $100M. This is a compelling reason for exploring what we call “synthetic aperture” or “hybrid optical telescopes. ” Even larger apertures that could be an order of magnitude less costly per square meter than comparable Keck-like optics are possible. Here we consider an optical system built from a relatively “floppy” optical structure and scalable interferometrically phased, moderate size (5m diameter), subapertures. This ExoLife Finder (ELF) telescope is sensitive to optical biomarker signals and has the power to map the surfaces of nearby M-dwarf exoplanets on subcontinental scales.
The Mediating Role of Social Participation in Motoric Cognitive Risk and its Relation to Depression and Loneliness in Older Adults

Background Motoric cognitive risk syndrome (MCR) reduces the quality of life, independence, and social interaction in older adults. Social participation is a potentially modifiable factor that benefits cognitive and mental health. This study explored the mediating roles of social participation between MCR and depression and between MCR and loneliness. Methods We performed a secondary analysis of data from the 2015–2016 National Social Life, Health, and Aging Project. Slow gait speed and cognitive decline were used to assess MCR. Mediation analysis was applied to two models, both of which used MCR as an exposure and social participation as a mediator. The outcomes were depression and loneliness for each model, respectively. Results Among 1,697 older adults, 196 (11.6%) had MCR. The mediating role of social participation was statistically significant in both models. The indirect effect (β=0.267, p=0.001) of MCR on depression through social participation comprised 11.97% of the total effect (β=2.231, p<0.001). The indirect effect (β=0.098, p=0.001) of MCR on loneliness through social participation was 19.48% of the total effect (β=0.503, p<0.001). Conclusion Interventions to increase social participation may reduce depression and loneliness of older adults with MCR.
Pinning Consensus Analysis for Nonlinear Second‐Order Multi‐Agent Systems with Time‐Varying Delays

This paper considers the second‐order leader‐following consensus problem for adelayed multi‐agent systems under general network topologies, in which each agent is a time‐delayed second‐order system with inherent nonlinear dynamics. Based on the pinning control strategy, a distributed control algorithm is proposed to achieve the second‐order leader‐following consensus of multi‐agent systems. Using matrix theory, algebraic graph theory and the free‐weighting‐matrix approach, some sufficient conditions are established in terms of linear matrix inequalities to ensure that all the agents can asymptotically follow the virtual leader. Finally, the effectiveness and the advantages of the developed approach are illustrated by means of simulations.
Describing the patient journey through healthcare pathways following mild traumatic brain injury in New Zealand using novel Graph analysis

ABSTRACT Aim To identify treatment provider sequences and healthcare pathway characteristics and outcomes for people with mild traumatic brain injury (mTBI) in New Zealand. Methods Total mTBI costs and key pathway characteristics were analysed using national healthcare data (patient’s injury and services provided). Graph analysis produced sequences of treatment provider types for claims with more than one appointment and healthcare outcomes (costs and time to exit pathway) were compared. Key pathway characteristics’ effect on healthcare outcomes were evaluated. Results In two years, 55,494 accepted mTBI claims cost ACC USD$93,647,261 over four years. For claims with more than one appointment (36%), healthcare pathways had a median 49 days (IQR, 12–185). The 89 treatment provider types resulted in 3,396 different provider sequences of which 25% were General Practitioners only (GP), 13% Emergency Department to GP (ED-GP) and 5% GP to Concussion Service (GP-CS). Pathways with shorter time to exit and lower costs had correct mTBI diagnosis at initial appointment. Income maintenance comprised 52% of costs but only occurred for 20% claims. Conclusions Improving healthcare pathways for people with mTBI by investing in training of providers to enable correct mTBI diagnosis could yield longer term cost savings. Interventions to reduce income maintenance costs are recommended.
Plasma Calcium Level and C-Reactive Protein Albumin Ratio Affect Severe Bleeding After Coronary Artery Bypass Grafting

Objective In this study, we aimed to determine whether plasma calcium level and C-reactive protein albumin ratio (CAR) as well as other demographic and hematological markers are related in predicting severe bleeding after coronary artery bypass grafting (CABG). Methods A total of 227 adult patients who underwent CABG at our hospital between December 2021 and June 2022 were prospectively studied. Total amount of chest tube drainage was evaluated within the first 24 hours postoperatively or until the patient was re-explored for bleeding. The patients were divided into two groups - Group 1, patients with low amount of bleeding (n=174), and Group 2, patients with severe bleeding (n=53). Univariate and multivariate regression analyzes were performed to determine independent parameters related to severe bleeding within the first 24 hours after surgery. Results When the groups were compared in terms of demographic, clinical, and preoperative blood parameters; cardiopulmonary bypass time and serum C-reactive protein (CRP) levels were found to be significantly higher in Group 2 compared to the low bleeding group. In addition, lymphocytes, hemoglobin, calcium, albumin, and CAR were found to be significantly lower in Group 2. In multivariate analysis, calcium, albumin, CRP, and CAR were found to be independent predictors of significant association with excessive bleeding. A cut-off value of 8.7 (94.3% sensitivity and 94.8% specificity) for calcium and 0.155 (75.4% sensitivity and 80.4% specificity) for CAR predicted excessive bleeding. Conclusion Plasma calcium level, CRP, albumin, and CAR can be used to predict severe bleeding after CABG.
Estimation of a non-linear reward function using score-based inverse reinforcement learning

This paper presents a novel inverse reinforcement learning method, which estimates a reward function from arbitrary trajectories and their scores. Whereas standard inverse reinforcement learning methods query (near-) optimal demonstrations to an expert and estimate a linear reward function, our method 1) queries scores of arbitrary trajectories, and 2) estimates a non-linear reward function. Our method inherits a benefit of score-based inverse reinforcement learning enabling the expert to free him/herself from a burden to generate demonstration trajectories. The method also can estimate a non-linear reward function by introducing kernel function to score-based inverse reinforcement learning. We tested our method by a control task of a simulated robotic manipulator. The results demonstrate that our method estimates a non-linear reward function, from which reinforcement learner generate trajectories with a high score.
Time-varying Network Modeling and its Optimal Routing Strategy

Since all the existing real world networks are evolving, the study of traffic dynamics is a challenging task. Avoidance of traffic congestion, system utility maximization and enhancement of network capacity are prominent issues. Network capacity may be improved either by optimizing network topology or enhancing in routing approach. In this context, we propose and design a model of the time-varying data communication networks (TVCN) based on the dynamics of inflowing links. Traffic congestion can be avoided by using a suitable centrality measure, especially betweenness and Eigen vector centralities. If the nodes coming in user’s route are most betweenness central, then that route will be highly congested. Eigen vector centrality is used to find the influence of a node on others. If a node is most influential, then it will be highly congested and considered as least reputed. For that reason, routes are chosen such that the sum of the centralities of the nodes coming in user’s route should be minimum. Furthermore, Kelly’s optimization formulation for a rate allocation problem is used for obtaining optimal rates of distinct users at different time instants and it is found that the user’s path with lowest betweenness centrality and highest reputation will always give maximum rate at the stable point.
Data Compression Versus Signal Fidelity Tradeoff in Wired-OR Analog-to-Digital Compressive Arrays for Neural Recording

Future high-density and high channel count neural interfaces that enable simultaneous recording of tens of thousands of neurons will provide a gateway to study, restore and augment neural functions. However, building such technology within the bit-rate limit and power budget of a fully implantable device is challenging. The wired-OR compressive readout architecture addresses the data deluge challenge of a high channel count neural interface using lossy compression at the analog-to-digital interface. In this article, we assess the suitability of wired-OR for several steps that are important for neuroengineering, including spike detection, spike assignment and waveform estimation. For various wiring configurations of wired-OR and assumptions about the quality of the underlying signal, we characterize the trade-off between compression ratio and task-specific signal fidelity metrics. Using data from 18 large-scale microelectrode array recordings in macaque retina ex vivo, we find that for an event SNR of 7–10, wired-OR correctly detects and assigns at least 80% of the spikes with at least 50× compression. The wired-OR approach also robustly encodes action potential waveform information, enabling downstream processing such as cell-type classification. Finally, we show that by applying an LZ77-based lossless compressor (gzip) to the output of the wired-OR architecture, 1000× compression can be achieved over the baseline recordings.
A study of simple and multiple relations between mathematics attitude, academic motivation and intelligence quotient with mathematics achievement

Purpose of current study was to investigate simple and multiple relations between mathematics' attitude, academic motivation and intelligence quotient with mathematics achievement. The Statistical population involved the entire Ardabil province' high schools students in 2008 (N = 33982). From these, 1670 students are selected as sample by using Cochran's formula and multiple cluster sampling. For gathering data, the following instrument is used. Raven IQ test (=0.86), Hermense Academic Achievement Test (=0.83), Moenikia mathematics attitude questionnaire (=0.79), and students' mathematics score in final exam. Correlation method was the research method. For data analysis, Pearson coefficient correlation and multiple regression in enter model were used. The Results showed that all of the variables correlate with together significantly. Mathematics' attitude, academic motivation, and intelligence quotient were predicator of mathematics achievement statistically significant. © 2010 Elsevier Ltd. All rights reserved.
The Impact of Culture Variables on a 3D Human In Vitro Bone Remodeling Model: A Design of Experiments Approach

Human in vitro bone remodeling models, using osteoclast–osteoblast cocultures, can facilitate the investigation of human bone remodeling while reducing the need for animal experiments. Although current in vitro osteoclast–osteoblast cocultures have improved the understanding of bone remodeling, it is still unknown which culture conditions support both cell types. Therefore, in vitro bone remodeling models can benefit from a thorough evaluation of the impact of culture variables on bone turnover outcomes, with the aim to reach balanced osteoclast and osteoblast activity, mimicking healthy bone remodeling. Using a resolution III fractional factorial design, the main effects of commonly used culture variables on bone turnover markers in an in vitro human bone remodeling model are identified. This model is able to capture physiological quantitative resorption–formation coupling along all conditions. Culture conditions of two runs show promising results: conditions of one run can be used as a high bone turnover system and conditions of another run as a self‐regulating system as the addition of osteoclastic and osteogenic differentiation factors is not required for remodeling. The results generated with this in vitro model allow for better translation between in vitro studies and in vivo studies, toward improved preclinical bone remodeling drug development.
Morphological and molecular characterization of Contracaecum australe (Nematoda: Anisakidae) parasitizing Phalacrocorax brasilianus (Aves: Phalacrocoracidae) on the north coast of Brazil

Abstract For the first time in Brazil, Contracaecum australe is recorded parasitizing Phalacrocorax brasilianus (Aves, Suliformes, Phalacrocoracidae) from the Marine Extractive Reserve of Soure on Marajó Island, Brazilian Amazon. Its morphology revealed a body with a transversally striated cuticle, smooth or slightly cleft interlabia, lips with auricles, labial papillae, and conspicuous amphids. In males, the presence of the median papilla on the upper lip of the cloaca and spicules that reach almost half of the body of the parasite. These morphological characters, added to the number and distribution of the pre- and postcloacal papillae of the male specimens, and supported by the molecular phylogeny from the analysis of the ITS-1, 5.8S and ITS-2 genes, allowed the identification of these parasites.
Flask and reactor scale production of plant growth regulators by Inonotus hispidus: optimization, immobilization and kinetic parameters

Abstract The aims of the presented study are to compare submerged, static, and solid-state fermentation in the production of gibberellic acid (GA3), indole acetic acid (IAA), and abscisic acid (ABA) by Inonotus hispidus, to optimize with a statistical approach, and to determine the kinetic parameters under flask and reactor conditions. The maximum concentrations of GA3, (2478.85 ± 68.53 mg/L), ABA, (273.26 ± 6.17 mg/L) and IAA (30.67 ± 0.19 mg/L) were obtained in submerged conditions. After optimization, these values reached 2998.85 ± 28.85, 339.47 ± 5.50, and 34.56 ± 0.25 mg/L, respectively. Immobilization of fungal cells on synthetic fiber, polyurethane foam, and alginate beads resulted in an increase in plant growth regulators (PGR) production by 5.53%− 5.79% under optimized conditions. At the reactor scale, a significant increase was observed for GA3 concentration, 5441.54 mg/L, which was 2.14 and 1.45 times higher than non-optimized and optimized conditions in the flask scale, respectively. The maximum values for ABA and IAA were 390.39 and 44.79 mg/L, respectively. Although the specific growth rate (µ) decreases relatively from non-optimized flask conditions to optimized reactor conditions, it was observed that the PGR amounts produced per liter medium (rp) and per gram biomass (Qp) increased significantly. This is the first report on the synthesis of PGR by Inonotus hispidus which could be crucial for sustainable agriculture.
Assessing cognitive changes in multiple sclerosis: criteria for a reliable decision

ABSTRACT Introduction Quantifying a significant cognitive change on a neuropsychological battery is essential to assess patients’ decline or recovery and offer appropriate care. The reliability of change indices is particularly important in multiple sclerosis (MS), as the course of cognitive impairment is quite unpredictable, due at least in part to substantial interindividual variability. The main objective of this study was to compare six different methods for assessing cognitive change in an MS sample: the SD method, two reliable change indices, two standardized regression-based methods (SRB), and the generalized regression-based method (GSRB). Method One hundred and twenty-three patients with clinically definite MS and 89 healthy controls underwent a battery of standardized neuropsychological tests assessing cognitive functions that are frequently affected in this disease (i.e., verbal episodic memory, working memory, processing speed and verbal fluency). Results We observed fairly similar proportions of improvement, decline or stability in the control group whatever the method. By contrast, in the MS sample, regression-based methods with one predictor (i.e., score at T1) and four predictors (i.e., score at T1 and demographic factors: age, sex, education level) detected a significant worsening more often than the reliable change indices while the GSRB method was more consistent with the RCI methods in tasks associated with ceiling effects. Conclusions The interpretation of a patient’s cognitive changes depends on which method is used. The (G)SRB methods appear to be relevant indicators for assessing cognitive change in MS. The addition of demographic factors does not seem to play an important role in the prediction of significant worsening in the MS sample, regardless of cognitive domain. For clinicians, an easy-to-use free shiny app is provided.