Miracle-dz/UniFAR-FTUs huggingface dataset:
Plasma membrane damage caused by listeriolysin O is not repaired through endocytosis of the membrane pore

ABSTRACT Endocytic mechanisms have been suggested to be important for plasma membrane repair in response to pore-forming toxins such as listeriolysin O (LLO), which form membrane pores that disrupt cellular homeostasis. Yet, little is known about the specific role of distinct endocytic machineries in this process. Here, we have addressed the importance of key endocytic pathways and developed reporter systems for real-time imaging of the endocytic response to LLO pore formation. We found that loss of clathrin-independent endocytic pathways negatively influenced the efficiency of membrane repair. However, we did not detect any increased activity of these pathways, or co-localisation with the toxin or markers of membrane repair, suggesting that they were not directly involved in removal of LLO pores from the plasma membrane. In fact, markers of clathrin-independent carriers (CLICs) were rapidly disassembled in the acute phase of membrane damage due to Ca2+ influx, followed by a reassembly about 2 min after pore formation. We propose that these endocytic mechanisms might influence membrane repair by regulating the plasma membrane composition and tension, but not via direct internalisation of LLO pores. Summary: Using reporter systems and real-time imaging, we show that endocytic pathways are not directly involved in removal of LLO pores from the plasma membrane.
New Biocide Foam Containing Hydrogen Peroxide for the Decontamination of Vertical Surface Contaminated With Bacillus thuringiensis Spores

Despite scientific advances, bacterial spores remain a major preoccupation in many different fields, such as the hospital, food, and CBRN-E Defense sector. Although many disinfectant technologies exist, there is a lack for the decontamination of difficult to access areas, outdoor sites, or large interior volumes. This study evaluates the decontamination efficiency of an aqueous foam containing hydrogen peroxide, with the efficiency of disinfectant in the liquid form on vertical surfaces contaminated by Bacillus thurengiensis spores. The decontamination efficiency impact of the surfactant and stabilizer agents in the foam and liquid forms was evaluated. No interferences were observed with these two chemical additives. Our results indicate that the decontamination kinetics of both foam and liquid forms are similar. In addition, while the foam form was as efficient as the liquid solution at 4°C, it was even more so at 30°C. The foam decontamination reaction follows the Arrhenius law, which enables the decontamination kinetic to be predicted with the temperature. Moreover, the foam process used via spraying or filling is more attractive due to the generation of lower quantity of liquid effluents. Our findings highlight the greater suitability of foam to decontaminate difficult to access and high volume facilities compared to liquid solutions.
Learning and Anticipating Future Actions During Exploratory Data Analysis

The goal of visual analytics is to create a symbiosis between human and computer by leveraging their unique strengths. While this model has demonstrated immense success, we are yet to realize the full potential of such a human-computer partnership. In a perfect collaborative mixed-initiative system, the computer must possess skills for learning and anticipating the users' needs. Addressing this gap, we propose a framework for inferring focus areas from passive observations of the user's actions, thereby allowing accurate predictions of future events. We evaluate this technique with a crime map and demonstrate that users' clicks appear in our prediction set 95% - 97% of the time. Further analysis shows that we can achieve high prediction accuracy typically after three clicks. Altogether, we show that passive observations of interaction data can reveal valuable information that will allow the system to learn and anticipate future events, laying the foundation for next-generation tools.
Epidemiology and Immune Pathogenesis of Viral Sepsis

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis can be caused by a broad range of pathogens; however, bacterial infections represent the majority of sepsis cases. Up to 42% of sepsis presentations are culture negative, suggesting a non-bacterial cause. Despite this, diagnosis of viral sepsis remains very rare. Almost any virus can cause sepsis in vulnerable patients (e.g., neonates, infants, and other immunosuppressed groups). The prevalence of viral sepsis is not known, nor is there enough information to make an accurate estimate. The initial standard of care for all cases of sepsis, even those that are subsequently proven to be culture negative, is the immediate use of broad-spectrum antibiotics. In the absence of definite diagnostic criteria for viral sepsis, or at least to exclude bacterial sepsis, this inevitably leads to unnecessary antimicrobial use, with associated consequences for antimicrobial resistance, effects on the host microbiome and excess healthcare costs. It is important to understand non-bacterial causes of sepsis so that inappropriate treatment can be minimised, and appropriate treatments can be developed to improve outcomes. In this review, we summarise what is known about viral sepsis, its most common causes, and how the immune responses to severe viral infections can contribute to sepsis. We also discuss strategies to improve our understanding of viral sepsis, and ways we can integrate this new information into effective treatment.
CA19‐9 and apolipoprotein‐A2 isoforms as detection markers for pancreatic cancer: a prospective evaluation

Recently, we identified unique processing patterns of apolipoprotein A2 (ApoA2) in patients with pancreatic cancer. Our study provides a first prospective evaluation of an ApoA2 isoform (“ApoA2‐ATQ/AT”), alone and in combination with carbohydrate antigen 19–9 (CA19‐9), as an early detection biomarker for pancreatic cancer. We performed ELISA measurements of CA19‐9 and ApoA2‐ATQ/AT in 156 patients with pancreatic cancer and 217 matched controls within the European EPIC cohort, using plasma samples collected up to 60 months prior to diagnosis. The detection discrimination statistics were calculated for risk scores by strata of lag‐time. For CA19‐9, in univariate marker analyses, C‐statistics to distinguish future pancreatic cancer patients from cancer‐free individuals were 0.80 for plasma taken ≤6 months before diagnosis, and 0.71 for >6–18 months; for ApoA2‐ATQ/AT, C‐statistics were 0.62, and 0.65, respectively. Joint models based on ApoA2‐ATQ/AT plus CA19‐9 significantly improved discrimination within >6–18 months (C = 0.74 vs. 0.71 for CA19‐9 alone, p = 0.022) and ≤ 18 months (C = 0.75 vs. 0.74, p = 0.022). At 98% specificity, and for lag times of ≤6, >6–18 or ≤ 18 months, sensitivities were 57%, 36% and 43% for CA19‐9 combined with ApoA2‐ATQ/AT, respectively, vs. 50%, 29% and 36% for CA19‐9 alone. Compared to CA19‐9 alone, the combination of CA19‐9 and ApoA2‐ATQ/AT may improve detection of pancreatic cancer up to 18 months prior to diagnosis under usual care, and may provide a useful first measure for pancreatic cancer detection prior to imaging.
CXCR7 is not obligatory for CXCL12‐CXCR4‐induced epithelial‐mesenchymal transition in human ovarian cancer

Although the CXCL12‐CXCR4/CXCR7 chemokine axis is demonstrated to play an integral role in tumor progression, the controversy exists and the role of CXCL12‐CXCR4/CXCR7 signaling axis in epithelial‐mesenchymal transition (EMT) of human ovarian cancer has not been explored. Here, we showed that in ovarian cancer CXCL12 induced EMT phenotypes including the spindle‐like cell morphology, podia and stress fiber formation, a decrease in E‐cadherin expression, and increases in mesenchymal N‐cadherin and vimentin expressions. These effects of CXCL12 could be antagonized by the CXCR4 antagonist AMD3100, but not by the anti‐CXCR7 antibody. The expressions of the EMT markers were significantly down‐regulated by the CXCR4 siRNA, and up‐regulated by the pcDNA3.1/CXCR4 plasmid, whereas not affected by the CXCR7 siRNA. Furthermore, intraperitoneal administration of AMD3100 inhibited tumor dissemination and growth in the nude mice inoculated with ovarian IGROV‐1 cells with a concomitant reduction in EMT marker expressions. Collectively, these data suggest that CXCR4, rather than CXCR7, plays a key role in CXCL12‐activated EMT phenotypes, and targeting the CXCL12‐CXCR4 chemokine axis represents a potential therapeutic strategy to prevent ovarian cancer progression.
Predicting Outcome of Indian Premier League (IPL) Matches Using Classification Based Machine Learning Algorithm

Cricket, especially the twenty20 format, has maximum uncertainty, where a single over can completely change the momentum of the game. With millions of people following the Indian Premier League, therefore developing a model for predicting the outcome of its matches beforehand is a real-world problem. A cricket match depends upon various factors, and in this work various feature selection methods were used to reduce the number of features to 5 from 15. Player’s performance in the field is considered to find out the overall weightage (relative strength) of the team. A Linear Regression based solution is proposed to calculate the weightage of a team based on the past performance of its players who have appeared most for the team. Finally, a dataset with the features: home team, away team, stadium, toss winner, toss decision, home-team-weightage and away-team-weightage, is fed to a Random Forest Classifier to train the model and make prediction on unseen matches. Classification results are satisfactory. Problem in the dataset and how the accuracy of the classifier can be improved is discussed. Keywords—Machine Learning, Indian Premier League, Multiple Linear Regression, Random Forest Classifier
The changes in chemical composition of Holothuria tubulosa (Gmelin, 1788) with ambient‐drying and oven‐drying methods

Abstract In this study, the nutritional properties of fresh (F), boiled (B), ambient‐dried (Holothuria tubulosa) (DA, 23 ± 2°C) and oven‐dried sea cucumber (DO, 45 ± 1°C) were compared in terms of proximate composition and fatty acid profiles. The results of the proximate analyses showed that the highest moisture content (86.76%) was determined in fresh samples, whereas the lowest moisture content (9.35%) was obtained in the oven‐dried group (DO). The crude fat and protein contents were in the range of 0.19% (B) to 0.87% (DA) and 12.30% (F) to 62.13% (DA), respectively. The highest ash content (30.30%) was obtained in group DO, while the lowest ash content (0.61%) was observed in the boiled samples (B). According to fatty acid analyses, there were no significant differences (p > 0.05) between the two drying methods. The monounsaturated fatty acid (MUFA) (21.405%) and polyunsaturated fatty acid (PUFA) (36.018%) contents of H. tubulosa were high. Holothuria tubulosa can be used as protein and PUFA sources. Comparing the two methods, oven‐drying is better in terms of preservation, whereas drying at the ambient temperature is better in terms of nutrient value.
Spatial parcellations, spectral filtering, and connectivity measures in fMRI: Optimizing for discrimination

The analysis of Functional Connectivity (FC) is a key technique of fMRI, having been used to distinguish brain states and conditions. While many approaches to calculating FC are available, there have been few assessments of their differences, making it difficult to choose approaches, and compare results. Here, we assess the impact of methodological choices on discriminability, using a fully controlled data set of continuous active states involving basic visual and motor tasks, providing robust localized FC changes. We tested a range of anatomical and functional parcellations, including the AAL atlas, parcellations derived from the Human Connectome Project and Independent Component Analysis (ICA) of many dimensionalities. We measure amplitude, covariance, correlation, and regularized partial correlation under different temporal filtering choices. We evaluate features derived from these methods for discriminating states using MVPA. We find that multidimensional parcellations derived from functional data performed similarly, outperforming an anatomical atlas, with correlation and partial correlation (p < .05, FDR). Partial correlation, with appropriate regularization, outperformed correlation. Amplitude and covariance generally discriminated less well, although gave good results with high‐dimensionality ICA. We found that discriminative FC properties are frequency specific; higher frequencies performed surprisingly well under certain configurations of atlas choices and dependency measures, with ICA‐based parcellations revealing greater discriminability at high frequencies compared to other parcellations. Methodological choices in FC analyses can have a profound impact on results and can be selected to optimize accuracy, interpretability, and sharing of results. This work contributes to a basis for consistent selection of approaches to estimating and analyzing FC.
Pain relief provided by an outgroup member enhances analgesia

Pain feels different in different social contexts, yet the mechanisms behind social pain modulation remain poorly understood. To elucidate the impact of social context on pain processing, we investigated how group membership, one of the most important social context factors, shapes pain relief behaviourally and neurally in humans undergoing functional neuroimaging. Participants repeatedly received pain relief from a member of their own group (ingroup treatment) or a member of a disliked outgroup (outgroup treatment). We observed a decrease in pain ratings and anterior insula (AI) pain responses after outgroup treatment, but not after ingroup treatment. Moreover, path analyses revealed that the outgroup treatment induced a stronger relief learning in the AI, which in turn altered pain processing, in particular if the participant entered the treatment with a negative impression toward the outgroup individual. The finding of enhanced analgesia after outgroup treatment is relevant for intergroup clinical settings. More generally, we found that group membership affects pain responses through neural learning and we thus elucidate one possible mechanism through which social context impacts pain processing.
Geographical veracity of indicators derived from mobile phone data

In this contribution we summarize insights on the geographical veracity of using mobile phone data to create (statistical) indicators. We focus on problems that persist with spatial allocation, spatial delineation and spatial aggregation of information obtained from mobile phone data. For each of the cases, we offer insights from our works on a French CDR dataset and propose both short and long term solutions. As such, we aim at offering a list of challenges, and a roadmap for future work on the topic.
Generalization Properties of hyper-RKHS and its Application to Out-of-Sample Extensions

Hyper-kernels endowed by hyper-Reproducing Kernel Hilbert Space (hyper-RKHS) formulate the kernel learning task as learning on the space of kernels itself, which provides significant model flexibility for kernel learning with outstanding performance in real-world applications. However, the convergence behavior of these learning algorithms in hyper-RKHS has not been investigated in learning theory. In this paper, we conduct approximation analysis of kernel ridge regression (KRR) and support vector regression (SVR) in this space. To the best of our knowledge, this is the first work to study the approximation performance of regression in hyper-RKHS. For applications, we propose a general kernel learning framework conducted by the introduced two regression models to deal with the out-of-sample extensions problem, i.e., to learn a underlying general kernel from the pre-given kernel/similarity matrix in hyper-RKHS. Experimental results on several benchmark datasets suggest that our methods are able to learn a general kernel function from an arbitrary given kernel matrix.
The Multifarious Functions of Pyruvate Kinase M2 in Oral Cancer Cells

Head and neck cancers, including oral squamous cell carcinoma (OSCC), are the sixth most common malignancies worldwide. OSCC frequently leads to oral dysfunction, which worsens a patient’s quality of life. Moreover, its prognosis remains poor. Unlike normal cells, tumor cells preferentially metabolize glucose by aerobic glycolysis. Pyruvate kinase (PK) catalyzes the final step in glycolysis, and the transition from PKM1 to PKM2 is observed in many cancer cells. However, little is known about PKM expression and function in OSCC. In this study, we investigated the expression of PKM in OSCC specimens and performed a functional analysis of human OSCC cells. We found that the PKM2/PKM1 ratio was higher in OSCC cells than in adjacent normal mucosal cells and in samples obtained from dysplasia patients. Furthermore, PKM2 expression was strongly correlated with OSCC tumor progression on immunohistochemistry. PKM2 expression was higher during cell growth, invasion, and apoptosis in HSC3 cells, which show a high energy flow and whose metabolism depends on aerobic glycolysis and oxidative phosphorylation. PKM2 expression was also associated with the production of reactive oxygen species (ROS) and integration of glutamine into lactate. Our results suggested that PKM2 has a variety of tumor progressive functions in OSCC cells.
Explaining the Impact of Perceived Career Growth and Organisational Justice on Intention to Stay

This study aimed to investigate intention to stay among officers in the City Traffic Police Lahore in relation to their perceptions of organisational justice and career growth. Using a quantitative research approach, a sample of 224 traffic wardens working in 30 sectors in the city of Lahore were selected through stratified random sampling. Data were gathered using a questionnaire containing Likert-type scales relating to all variable of interest. Apart from procedural justice and professional ability development, all dimensions of organisational justice and perceived career growth were found to significantly influence traffic officers’ intention to stay. Moreover, promotional speed emerged as the strongest predictor of the intent to stay. The findings of this study may guide police authorities in dealing with issues on turnover by initiating policies which can strengthen employee retention intention. Additionally, it provides empirical insights on the contributing factors of high turnover in the City Traffic Police Lahore. This paper enhances understanding of turnover issues by investigating retention intention of traffic police officers in an Eastern culture. Specifically, this research contributes to literature by examining the predictive role of organisational inducement factors (organisational justice and career growth) on attitude (intention to stay). Additionally, both the exogenous constructs of interest are used at the dimensional levels.
Intracardiac echocardiography with ultrasound probe placed in the upper left pulmonary vein to guide left atrial appendage closure: First description

Intracardiac echocardiography (ICE) has become an effective alternative to trans‐esophageal echocardiography (TEE) as a guidance during interventional procedures for structural heart diseases, allowing to proceed under conscious sedation. To guide percutaneous left atrial appendage (LAA) closure, the ICE probe is usually placed in the right atrium, in the pulmonary artery or in the left atrium (LA); however, the views from the right atrium or the pulmonary artery are often suboptimal, debarring a complete visualization of the LAA and the surrounding structures, whereas the LA location requires trans‐septal puncture, may provoke LA wall mechanical stimulation and is often associated with unstable position of the ICE probe. In our case, after a second trans‐septal puncture, the ICE probe was placed in the upper left pulmonary vein; this was safely performed and provided an optimal imaging of the LAA, comparable to that obtained by TEE, thus warranting an adequate guide during all procedural steps.
Optimized Expression and Characterization of a Novel Fully Human Bispecific Single-Chain Diabody Targeting Vascular Endothelial Growth Factor165 and Programmed Death-1 in Pichia pastoris and Evaluation of Antitumor Activity In Vivo

Bispecific antibodies, which can bind to two different epitopes on the same or different antigens simultaneously, have recently emerged as attractive candidates for study in various diseases. Our present study successfully constructs and expresses a fully human, bispecific, single-chain diabody (BsDb) that can bind to vascular endothelial growth factor 165 (VEGF165) and programmed death-1 (PD-1) in Pichia pastoris. Under the optimal expression conditions (methanol concentration, 1%; pH, 4.0; inoculum density, OD600 = 4, and the induction time, 96 h), the maximum production level of this BsDb is achieved at approximately 20 mg/L. The recombinant BsDb is purified in one step using nickel-nitrilotriacetic acid (Ni-NTA) column chromatography with a purity of more than 95%. Indirect enzyme-linked immune sorbent assay (ELISA) and sandwich ELISA analyses show that purified BsDb can bind specifically to VEGF165 and PD-1 simultaneously with affinities of 124.78 nM and 25.07 nM, respectively. Additionally, the BsDb not only effectively inhibits VEGF165-stimulated proliferation, migration, and tube formation in primary human umbilical vein endothelial cells (HUVECs), but also significantly improves proliferation and INF-γ production of activated T cells by blocking PD-1/PD-L1 co-stimulation. Furthermore, the BsDb displays potent antitumor activity in mice bearing HT29 xenograft tumors by inhibiting tumor angiogenesis and activating immune responses in the tumor microenvironment. Based on these results, we have prepared a potential bispecific antibody drug that can co-target both VEGF165 and PD-1 for the first time. This work provides a stable foundation for the development of new strategies by the combination of an angiogenesis inhibition and immune checkpoint blockade for cancer therapy.
Adaptive consensus control of nonlinear systems with unknown control directions

Abstract In this paper, we investigate the adaptive consensus control for a class of nonlinear systems with different unknown control directions where communications among the agents are represented by a directed graph. Based on the backstepping technique, a fully distributed adaptive control approach is proposed without using global information of the topology. Meanwhile, a novel Nussbaum-type function is proposed to address the consensus control with unknown control directions. It is proved that boundedness of all closed-loop signals and asymptotic consensus tracking for all the agents' outputs are ensured. In simulation studies, a numerical example is illustrated to show the effectiveness of the control scheme.