Miracle-dz/UniFAR-FTUs huggingface dataset:
Using hydrogen peroxide to prevent antibody disulfide bond reduction during manufacturing process

ABSTRACT During large-scale monoclonal antibody manufacturing, disulfide bond reduction of antibodies, which results in generation of low molecule weight species, is occasionally observed. When this happens, the drug substance does not meet specifications. Many investigations have been conducted across the biopharmaceutical industry to identify the root causes, and multiple strategies have been proposed to mitigate the problem. The reduction is correlated with the release of cellular reducing components and depletion of dissolved oxygen before, during, and after harvest. Consequently, these factors can lead to disulfide reduction over long-duration storage at room temperature prior to Protein A chromatography. Several strategies have been developed to minimize antibody reduction, including chemical inhibition of reducing components, maintaining aeration before and after harvest, and chilling clarified harvest during holding. Here, we explore the use of hydrogen peroxide in clarified harvest bulk or cell culture fluid as a strategy to prevent disulfide reduction. A lab-scale study was performed to demonstrate the effectiveness of hydrogen peroxide in preventing antibody reduction using multiple IgG molecules. Studies were done to define the optimal concentration of hydrogen peroxide needed to avoid unnecessary oxidization of the antibody products. We show that adding a controlled amount of hydrogen peroxide does not change product quality attributes of the protein. Since hydrogen peroxide is soluble in aqueous solutions and decomposes into water and oxygen, there is no additional burden involved in removing it during the downstream purification steps. Due to its ease of use and minimal product impact, we demonstrate that hydrogen peroxide treatment is a powerful, simple tool to quench reducing potential by simply mixing it with harvested cell culture fluid.
Quantification of the Relative Importance of CTL, B Cell, NK Cell, and Target Cell Limitation in the Control of Primary SIV-Infection

CD8+ cytotoxic T lymphocytes (CTLs), natural killer (NK) cells, B cells and target cell limitation have all been suggested to play a role in the control of SIV and HIV-1 infection. However, previous research typically studied each population in isolation leaving the magnitude, relative importance and in vivo relevance of each effect unclear. Here we quantify the relative importance of CTLs, NK cells, B cells and target cell limitation in controlling acute SIV infection in rhesus macaques. Using three different methods, we find that the availability of target cells and CD8+ T cells are important predictors of viral load dynamics. If CTL are assumed to mediate this anti-viral effect via a lytic mechanism then we estimate that CTL killing is responsible for approximately 40% of productively infected cell death, the remaining cell death being attributable to intrinsic, immune (CD8+ T cell, NK cell, B cell) -independent mechanisms. Furthermore, we find that NK cells have little impact on the death rate of infected CD4+ cells and that their net impact is to increase viral load. We hypothesize that NK cells play a detrimental role in SIV infection, possibly by increasing T cell activation.
The Analytical Challenge in the Determination of Cathinones, Key-Players in the Worldwide Phenomenon of Novel Psychoactive Substances

ABSTRACT Since the turn of the century, the synthesis, availability, and use of new psychoactive substances (NPS) have been increasingly reported worldwide, being considered a complex global phenomenon. As most NPS are not detected in routine drug screening, extra efforts have been made to develop new analytical methods for the detection of these compounds, with several approaches being successfully applied and reported in the literature. The increased traffic of NPS is often related to the limited capacity for detecting and monitoring these compounds, which makes it essential to explore in detail both conventional and more recent approaches to prospect novel sensing strategies and develop in-the-field sensors that are able to detect NPS in a time-efficient manner, within a wide range of concentrations, and in a variety of sample matrices, such as biological samples, wastewater, powders, crystals, and post-mortem specimens. In this context, this review aims to provide an overview of the state of the art in the identification and analytical detection of cathinones, a considerable group within NPS, as well as a critical discussion of the most frequently described sample preparation techniques.
Repairing the corneal epithelium using limbal stem cells or alternative cell-based therapies

ABSTRACT Introduction: The corneal epithelium is maintained by limbal stem cells (LSCs) that reside in the basal epithelial layer of the tissue surrounding the cornea termed the limbus. Loss of LSCs results in limbal stem cell deficiency (LSCD) that can cause severe visual impairment. Patients with partial LSCD may respond to conservative therapies designed to rehabilitate the remaining LSCs. However, if these conservative approaches fail or, if complete loss of LSCs occurs, transplantation of LSCs or their alternatives is the only option. While a number of clinical studies utilizing diverse surgical and cell culture techniques have shown favorable results, a universal cure for LSCD is still not available. Knowledge of the potential risks and benefits of current approaches, and development of new technologies, is essential for further improvement of LSCD therapies. Areas covered: This review focuses on cell-based LSCD treatment approaches ranging from current available clinical therapies to preclinical studies of novel promising applications. Expert opinion: Improved understanding of LSC identity and development of LSC expansion methods will influence the evolution of successful LSCD therapies. Ultimately, future controlled clinical studies enabling direct comparison of the diverse employed approaches will help to identify the most effective treatment strategies.
Young's moduli of cellulose nanofibers measured by atomic force microscopy

Atomic force microscopy (AFM) is known for measuring the mechanical properties of nanomaterials. It has been used for measuring the mechanical properties of few kinds of fibers, such as carbon nanotubes, gold nanofibers, graphene. In this study, the effect of various sources on the elastic modulus of cellulose nanofibers (CNFs) was investigated by using AFM three-points bending test. The CNFs were extracted from hardwood, softwood, bamboo and cotton by using aqueous counter collision (ACC) system and the morphology of CNFs were studied by AFM. CNFs were successfully transferred to the AFM calibration chip and the three-points bending test was performed. CNFs were considered to be circular shape by taking into account the AFM tip radius and the Young’s modulus was calculated. The calculation results indicate that the range of Young’s modulus is between 102 and 131 GPa varying upon the cellulose resources.
Pore scale modeling of multiphase flow in heterogeneously wet media

Pore scale modeling of multiphase flow in heterogeneously wet media Rahul Verma, Ph.D. The University of Texas at Austin, 2018 Supervisor: Maša Prodanović Pore scale simulation has recently become an important tool for understanding multiphase flow behavior in porous materials. It enables detailed mechanistic studies of upscaled flow parameters such as capillary-pressure saturation curves, residual saturation of each phase, and relative permeability. However, direct modeling of multiphase flow given the complex solid surfaces in a porous medium is a non-trivial problem. In this work, we develop a new quasi-static, variational level set formulation capable of handling trapped phases as well as wettability. We extend our previous work [1, 2] for simple geometries, and develop a new parallelized code enabling application of the method in larger geometries. We compare our model results against several experimental and semi-analytical datasets. The model is first applied to both homogeneous and heterogeneously wet rhomboidal pores, and compared against semi-analytical solutions derived by Mason and Morrow [3]. Subsequently, we focus on a quasi-2D micromodel study of fluid-fluid displacement for different wettabilities, which is quantified using the displacement efficiency and fractal dimension of the displacement patterns [4]. We then study classic experiments by Haines [5] and Leverett [6] for measuring the capillary pressure and relative permeability curves in sphere packs and sandpacks, respectively. We match trends in trapping in sandpacks during drainage/imbibition experiments by Pentland et al. [7], and also compare it against predictions by several other pore-scale models. Finally, we confirm the pore-scale hypothesis suggested by DiCarlo et al. [8] for explaining experi-
Effects of different substrates/growth media on microbial community of saliva‐derived biofilm

Abstract The aims of this study were to investigate the effects of substrates (glass versus hydroxyapatite [HA]) and growth media (SHI medium versus a modified artificial saliva medium with cysteine) on the microbial community of saliva‐derived biofilm in vitro. 16S rRNA gene sequencing technology was used to analyze the microbial community of saliva‐derived biofilm cultured for 72 h anaerobically. The metagenomes of biofilms were predicted from the clusters of orthologous groups. No significant difference was found between the saliva‐derived biofilms grown on HA and glass in ACE, Chao, Shannon and Simpson indices. The abundances of only a few bacteria on HA were significantly different from those on glass with a low relative abundance (<0.5%). Compared with the biofilms developed in a modified artificial saliva medium with cysteine, biofilms in SHI medium were significantly higher (P < 0.05) in diversity. Linear discriminant analysis coupled with effect size measurement showed that some obligate anaerobic genera (Lactobacillus, Veillonella, Porphyromonas and Leptotrichia) were more abundant in SHI medium biofilms. The biofilms grown in different media were also significantly different in predicted gene categories. In conclusion, the growth media, not the substrates, have significant effects on the microbial community of saliva‐derived biofilm in vitro.
Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs

SUMMARY Biological and engineered networks have recently been shown to display network motifs: a small set of characteristic patterns that occur much more frequently than in randomized networks with the same degree sequence. Network motifs were demonstrated to play key information processing roles in biological regulation networks. Existing algorithms for detecting network motifs act by exhaustively enumerating all subgraphs with a given number of nodes in the network. The runtime of such algorithms increases strongly with network size. Here, we present a novel algorithm that allows estimation of subgraph concentrations and detection of network motifs at a runtime that is asymptotically independent of the network size. This algorithm is based on random sampling of subgraphs. Network motifs are detected with a surprisingly small number of samples in a wide variety of networks. Our method can be applied to estimate the concentrations of larger subgraphs in larger networks than was previously possible with exhaustive enumeration algorithms. We present results for high-order motifs in several biological networks and discuss their possible functions. AVAILABILITY A software tool for estimating subgraph concentrations and detecting network motifs (mfinder 1.1) and further information is available at http://www.weizmann. ac.il/mcb/UriAlon/
Glycated haemoglobin A1c as a risk factor of cardiovascular outcomes and all-cause mortality in diabetic and non-diabetic populations: a systematic review and meta-analysis

Objective To examine the relationship between glycated haemoglobin A1c (HbA1c) levels and the risk of cardiovascular outcomes and all-cause mortality based on data from observational studies and to determine the optimal levels of HbA1c for preventing cardiovascular events and/or mortality in diabetic and non-diabetic populations. Review methods We systematically searched Medline, Embase, the Cochrane Central Register of Controlled Trials, the Cochrane Database of Systematic Reviews and Web of Science databases, from inception to July 2016, for observational studies addressing the association of HbA1c levels with mortality and cardiovascular outcomes. Random effects models were used to compute pooled estimates of HR and respective 95% CI for all-cause mortality, cardiovascular mortality and risk of cardiovascular events, separately for people with and without diabetes. Results Seventy-four published studies were included in the systematic review, but only 46 studies could be incorporated in the meta-analysis. In both diabetic and non-diabetic populations, there was an increase in the risk of all-cause mortality when HbA1c levels were over 8.0% and 6.0%, respectively. The highest all-cause mortality in people with diabetes was HbA1c above 9.0% (HR=1.69; 95% CI 1.09 to 2.66) and in those without diabetes was HbA1c above 6.0% (HR=1.74; 95% CI 1.38 to 2.20). However, both diabetic and non-diabetic populations with lower HbA1c levels (below 6.0% HR=1.57; 95% CI 1.14 to 2.17 and below 5.0% HR=1.19; 95% CI 1.04 to 1.36, respectively) had higher all-cause mortality. Similar pooled estimates were found when cardiovascular mortality was the outcome variable. Conclusion HbA1c is a reliable risk factor of all-cause and cardiovascular mortality in both diabetics and non-diabetics. Our findings establish optimal HbA1c levels, for the lowest all-cause and cardiovascular mortality, ranging from 6.0% to 8.0% in people with diabetes and from 5.0% to 6.0% in those without diabetes.
Optimal tracking agent: a new framework of reinforcement learning for multiagent systems

The curse of dimensionality is a ubiquitous problem for multiagent reinforcement learning, which means the learning and storing space grows exponentially with the number of agents and hinders the application of multiagent reinforcement learning. To relieve this problem, we propose a new framework named as optimal tracking agent (OTA). The OTA views the other agents as part of the environment and uses a reduced form to learn the optimal decision. Although merging other agents into the environment may reduce the dimension of action space, the environment characterized by such form is dynamic and does not satisfy the convergence of reinforcement learning (RL). Thus, we develop an estimator to track the dynamics of the environment. The estimator obtains the dynamic model, and then the model‐based RL can be used to react to the dynamic environment optimally. Because the Q‐function in OTA is also a dynamic process because of other agents’ dynamics, different from traditional RL, in which the learning is a stationary process and the usual action selection mechanisms just suit to such stationary process, we improve the greedy action selection mechanism to adapt to such dynamics. Thus, the OTA will have convergence. An experiment illustrates the validity and efficiency of the OTA.Copyright © 2012 John Wiley & Sons, Ltd.
Leveraging Strategic Detection Techniques for Smart Home Pricing Cyberattacks

In this work, the vulnerability of the electricity pricing model in the smart home system is assessed. Two closely related pricing cyberattacks which manipulate the guideline electricity prices received at smart meters are considered and they aim at reducing the expense of the cyberattacker and increasing the peak energy usage in the local community. A single event detection technique which uses support vector regression and impact difference for detecting anomaly pricing is proposed. The detection capability of such a technique is still limited since it does not model the long term impact of pricing cyberattacks. This motivates us to develop a partially observable Markov decision process based detection algorithm, which has the ingredients such as reward expectation and policy transfer graph to account for the cumulative impact and the potential future impact due to pricing cyberattacks. Our simulation results demonstrate that the pricing cyberattack can reduce the cyberattacker's bill by 34.3 percent at cost of the increase of others' bill by 7.9 percent, and increase the peak to average ratio (PAR) by 35.7 percent. Furthermore, the proposed long term detection technique has the detection accuracy of more than 97 percent with significant reduction in PAR and bill compared to repeatedly using the single event detection technique.
Compression for quantum population coding

We study the compression of arbitrary parametric families of n identically prepared finite-dimensional quantum states, in a setting that can be regarded as a quantum analogue of population coding. For a family with f free parameters, we propose an asymptotically faithful protocol that requires a memory of overall size (f/2) logn. Our construction uses a quantum version of local asymptotic normality and, as an intermediate step, solves the problem of the optimal compression of n identically prepared displaced thermal states. Our protocol achieves the ultimate bound predicted by quantum Shannon theory. In addition, we explore the minimum requirement for quantum memory: On the one hand, the amount of quantum memory used by our protocol can be made arbitrarily small compared to the overall memory cost; on the other hand, any protocol using only classical memory cannot be faithful.
Schizophrenia and abnormal brain network hubs

Schizophrenia is a heterogeneous psychiatric disorder of unknown cause or characteristic pathology. Clinical neuroscientists increasingly postulate that schizophrenia is a disorder of brain network organization. In this article we discuss the conceptual framework of this dysconnection hypothesis, describe the predominant methodological paradigm for testing this hypothesis, and review recent evidence for disruption of central/hub brain regions, as a promising example of this hypothesis. We summarize studies of brain hubs in large-scale structural and functional brain networks and find strong evidence for network abnormalities of prefrontal hubs, and moderate evidence for network abnormalities of limbic, temporal, and parietal hubs. Future studies are needed to differentiate network dysfunction from previously observed gray- and white-matter abnormalities of these hubs, and to link endogenous network dysfunction phenotypes with perceptual, behavioral, and cognitive clinical phenotypes of schizophrenia.
Increasing Ketamine Use for Refractory Status Epilepticus in US Pediatric Hospitals

Ketamine is an emerging therapy for pediatric refractory status epilepticus. The circumstances of its use, however, are understudied. The authors described pediatric refractory status epilepticus treated with ketamine from 2010 to 2014 at 45 centers using the Pediatric Hospital Inpatient System database. For comparison, they described children treated with pentobarbital. The authors estimated that 48 children received ketamine and pentobarbital for refractory status epilepticus, and 630 pentobarbital without ketamine. Those receiving only pentobarbital were median age 3 [interquartile range 0-10], and spent 30 [18-52] days in-hospital, including 17 [9-28] intensive care unit (ICU) days; 17% died. Median cost was $148 000 [81 000-241 000]. The pentobarbital-ketamine group was older (7 [2-11]) with longer hospital stays (51 [30-93]) and more ICU days (29 [20-56]); 29% died. Median cost was $298 000 [176 000-607 000]. For 71%, ketamine was given ≥1 day after pentobarbital. Ketamine cases per half-year increased from 2 to 9 (P < .05). Ketamine is increasingly used for severe pediatric refractory status epilepticus, typically after pentobarbital. Research on its effectiveness is indicated.
Social Relationships, Inflammation, and Cancer Survival

Background: Social stressors, such as social relationship deficits, have been increasingly linked to chronic disease outcomes, including cancer. However, critical gaps exist in our understanding of the nature and strength of such links, as well as the underlying biological mechanisms relating social relationships to cancer progression and survival. Methods: Utilizing novel questionnaire and biomarker data from the UNC Health Registry/Cancer Survivorship Cohort, this study examines the associations between diverse measures of social support and mortality risk among individuals with cancer (N = 1,004). We further assess the role of multiple serum markers of inflammation, including high-sensitivity C-reactive protein (CRP), IL6, TNFα, and VEGF, as potential mediators in the social relationship–cancer link. Results: The findings revealed that one's appraisal of their social support was associated with cancer mortality, such that individuals reporting higher levels of social support satisfaction had lower mortality risk than individuals reporting lower levels of satisfaction. The amount of support received, on the other hand, was not predictive of cancer survival. We further found evidence that inflammatory processes may undergird the link between social support satisfaction and mortality among individuals with cancer, with individuals reporting higher levels of social support satisfaction having lower levels of CRP, IL6, and TNFα. Conclusions: These results provide new knowledge of the biosocial processes producing population disparities in cancer outcomes. Impact: Our study offers new insights for intervention efforts aimed at promoting social connectedness as a means for improving cancer survival. Cancer Epidemiol Biomarkers Prev; 27(5); 541–9. ©2018 AACR.
Cohort Profile Cohort Profile : The JS High School study ( JSHS ) : a cohort study of Korean adolescents

Major aetiologies of atherosclerotic cardiovascular diseases begin in childhood and atherosclerotic vascular abnormalities can be observed among children and adolescents. Adolescent cohort studies have important advantages because they can observe earlier changes in vascular structure and function. The purpose of the JS High School study (JSHS) is to identify biomarkers predicting or indicating early structural and functional vascular change in adolescents. The JSHS is a prospective cohort study of a Korean adolescent population. The target population of the JSHS was first-graders (aged 14 to17 years) at a high school of South Korea. Enrolment and baseline examinations were conducted in years 2007, 2010, 2011 and 2012. Among the total eligible population of 1115 students, 1071 (96.1%) participated in the study and completed all baseline examinations. Informed consent forms were obtained from each participant and his/her parent or guardian. Baseline examinations include: questionnaires on demographics, health behaviours, medical history, and depression symptoms; fasting blood analysis; anthropometric measurement; body impedance analysis; blood pressure measurement; radial artery tonometry; bone densitometry; pulmonary function tests; and carotid ultrasonography. Participants enrolled from 2007 through 2012 were re-examined after 30 months of follow-up, and those who enrolled in 2012 were re-examined after 24 months of follow-up. The corresponding author may be contacted for potential collaboration and data access.
Reirradiation in patients with diffuse intrinsic pontine gliomas: The Canadian experience

Clinical trials have failed to demonstrate a survival benefit of adjuvant chemotherapy in diffuse intrinsic pontine gliomas (DIPG). Radiation therapy (RT) is the only effective treatment thus far and reirradiation (rRT) has become an option at the time of progression. The aim of this study was to review the Canadian experience of DIPG rRT with a focus on the safety and possible efficacy of this approach.