Miracle-dz/UniFAR-FTUs huggingface dataset:
HLA Class I Knockout Converts Allogeneic Primary NK Cells Into Suitable Effectors for “Off-the-Shelf” Immunotherapy

Cellular immunotherapy using chimeric antigen receptors (CARs) so far has almost exclusively used autologous peripheral blood-derived T cells as immune effector cells. However, harvesting sufficient numbers of T cells is often challenging in heavily pre-treated patients with malignancies and perturbed hematopoiesis and perturbed hematopoiesis. Also, such a CAR product will always be specific for the individual patient. In contrast, NK cell infusions can be performed in non-HLA-matched settings due to the absence of alloreactivity of these innate immune cells. Still, the infused NK cells are subject to recognition and rejection by the patient’s immune system, thereby limiting their life-span in vivo and undermining the possibility for multiple infusions. Here, we designed genome editing and advanced lentiviral transduction protocols to render primary human NK cells unsusceptible/resistant to an allogeneic response by the recipient’s CD8+ T cells. After knocking-out surface expression of HLA class I molecules by targeting the B2M gene via CRISPR/Cas9, we also co-expressed a single-chain HLA-E molecule, thereby preventing NK cell fratricide of B2M-knockout (KO) cells via “missing self”-induced lysis. Importantly, these genetically engineered NK cells were functionally indistinguishable from their unmodified counterparts with regard to their phenotype and their natural cytotoxicity towards different AML cell lines. In co-culture assays, B2M-KO NK cells neither induced immune responses of allogeneic T cells nor re-activated allogeneic T cells which had been expanded/primed using irradiated PBMNCs of the respective NK cell donor. Our study demonstrates the feasibility of genome editing in primary allogeneic NK cells to diminish their recognition and killing by mismatched T cells and is an important prerequisite for using non-HLA-matched primary human NK cells as readily available, “off-the-shelf” immune effectors for a variety of immunotherapy indications in human cancer.
Correlations in Somatic Hypermutation Between Sites in IGHV Genes Can Be Explained by Interactions Between AID and/or Polη Hotspots

The somatic hypermutation (SHM) of Immunoglobulin (Ig) genes is a key process during antibody affinity maturation in B cells. The mutagenic enzyme activation induced deaminase (AID) is required for SHM and has a preference for WRC hotspots in DNA. Error-prone repair mechanisms acting downstream of AID introduce further mutations, including DNA polymerase eta (Polη), part of the non-canonical mismatch repair pathway (ncMMR), which preferentially generates mutations at WA hotspots. Previously proposed mechanistic models lead to a variety of predictions concerning interactions between hotspots, for example, how mutations in one hotspot will affect another hotspot. Using a large, high-quality, Ig repertoire sequencing dataset, we evaluated pairwise correlations between mutations site-by-site using an unbiased measure similar to mutual information which we termed “mutational association” (MA). Interactions are dominated by relatively strong correlations between nearby sites (short-range MAs), which can be almost entirely explained by interactions between overlapping hotspots for AID and/or Polη. We also found relatively weak dependencies between almost all sites throughout each gene (longer-range MAs), although these arise mostly as a statistical consequence of high pairwise mutation frequencies. The dominant short-range interactions are also highest within the most highly mutating IGHV sub-regions, such as the complementarity determining regions (CDRs), where there is a high hotspot density. Our results suggest that the hotspot preferences for AID and Polη have themselves evolved to allow for greater interactions between AID and/or Polη induced mutations.
Propranolol Sensitizes Vascular Sarcoma Cells to Doxorubicin by Altering Lysosomal Drug Sequestration and Drug Efflux

Angiosarcoma is a rare cancer of blood vessel–forming cells with a high patient mortality and few treatment options. Although chemotherapy often produces initial clinical responses, outcomes remain poor, largely due to the development of drug resistance. We previously identified a subset of doxorubicin-resistant cells in human angiosarcoma and canine hemangiosarcoma cell lines that exhibit high lysosomal accumulation of doxorubicin. Hydrophobic, weak base chemotherapeutics, like doxorubicin, are known to sequester within lysosomes, promoting resistance by limiting drug accessibility to cellular targets. Drug synergy between the beta adrenergic receptor (β-AR) antagonist, propranolol, and multiple chemotherapeutics has been documented in vitro, and clinical data have corroborated the increased therapeutic potential of propranolol with chemotherapy in angiosarcoma patients. Because propranolol is also a weak base and accumulates in lysosomes, we sought to determine whether propranolol enhanced doxorubicin cytotoxicity via antagonism of β-ARs or by preventing the lysosomal accumulation of doxorubicin. β-AR-like immunoreactivities were confirmed in primary tumor tissues and cell lines; receptor function was verified by monitoring downstream signaling pathways of β-ARs in response to receptor agonists and antagonists. Mechanistically, propranolol increased cytoplasmic doxorubicin concentrations in sarcoma cells by decreasing the lysosomal accumulation and cellular efflux of this chemotherapeutic agent. Equivalent concentrations of the receptor-active S-(−) and -inactive R-(+) enantiomers of propranolol produced similar effects, supporting a β-AR-independent mechanism. Long-term exposure of hemangiosarcoma cells to propranolol expanded both lysosomal size and number, yet cells remained sensitive to doxorubicin in the presence of propranolol. In contrast, removal of propranolol increased cellular resistance to doxorubicin, underscoring lysosomal doxorubicin sequestration as a key mechanism of resistance. Our results support the repurposing of the R-(+) enantiomer of propranolol with weak base chemotherapeutics to increase cytotoxicity and reduce the development of drug-resistant cell populations without the cardiovascular and other side effects associated with antagonism of β-ARs.
Advances in Engineering Human Tissue Models

Research in cell biology greatly relies on cell-based in vitro assays and models that facilitate the investigation and understanding of specific biological events and processes under different conditions. The quality of such experimental models and particularly the level at which they represent cell behavior in the native tissue, is of critical importance for our understanding of cell interactions within tissues and organs. Conventionally, in vitro models are based on experimental manipulation of mammalian cells, grown as monolayers on flat, two-dimensional (2D) substrates. Despite the amazing progress and discoveries achieved with flat biology models, our ability to translate biological insights has been limited, since the 2D environment does not reflect the physiological behavior of cells in real tissues. Advances in 3D cell biology and engineering have led to the development of a new generation of cell culture formats that can better recapitulate the in vivo microenvironment, allowing us to examine cells and their interactions in a more biomimetic context. Modern biomedical research has at its disposal novel technological approaches that promote development of more sophisticated and robust tissue engineering in vitro models, including scaffold- or hydrogel-based formats, organotypic cultures, and organs-on-chips. Even though such systems are necessarily simplified to capture a particular range of physiology, their ability to model specific processes of human biology is greatly valued for their potential to close the gap between conventional animal studies and human (patho-) physiology. Here, we review recent advances in 3D biomimetic cultures, focusing on the technological bricks available to develop more physiologically relevant in vitro models of human tissues. By highlighting applications and examples of several physiological and disease models, we identify the limitations and challenges which the field needs to address in order to more effectively incorporate synthetic biomimetic culture platforms into biomedical research.
Investigation on the Efficiency of Chinese Herbal Injections for Treating Non-small Cell Lung Cancer With Vinorelbine and Cisplatin Based on Multidimensional Bayesian Network Meta-Analysis

Background: As non-small cell lung cancer (NSCLC) seriously threatens human health, several clinical studies have reported that Chinese herbal injections (CHIs) combined with vinorelbine and cisplatin (NP) are beneficial. This multidimensional network meta-analysis was performed to explore the preferable options among different CHIs for treating NSCLC. Methods: A literature search was performed in several databases to identify randomized controlled trials (RCTs) of CHIs in the treatment of NSCLC from inception to January 31, 2019. Final included studies met the eligibility criteria and methodological quality recommendations. Data analysis was performed using Stata 13.0 and WinBUGS 14.0 software. Each outcome was presented as an odds ratio and the surface under the cumulative ranking curve value (SCURA). The “scatterplot3d” package in R 3.6. 1 software was used to perform multidimensional cluster analysis. Results: Ultimately, 97 eligible RCTs involving 7,440 patients and 14 CHIs were included in this network meta-analysis. Combined with NP chemotherapy, Kanglaite injection plus NP exhibited a better impact on the clinical effectiveness rate (SCURA probability: 78.34%), and Javanica oil emulsion injection plus NP was better in the performance status (95.44%). Huachansu injection plus NP was dominant in reducing thrombocytopenia (92.67%) and gastrointestinal reactions (92.52%). As to multidimensional cluster analysis, Shenmai injection plus NP was superior considering improving the clinical effectiveness rate, performance status and relieving leukopenia. Conclusions: The combination of CHIs and NP has a better impact on patients with NSCLC than NP alone. Among them, Shenmai injection plus NP, Kanglaite injection plus NP and Javanica oil emulsion injection plus NP were notable. Nevertheless, more multicenter and better designed RCTs are needed to validate our findings.
Comprehensive Succinylome Profiling Reveals the Pivotal Role of Lysine Succinylation in Energy Metabolism and Quorum Sensing of Staphylococcus epidermidis

Background Lysine succinylation is a newly identified posttranslational modification (PTM), which exists widely from prokaryotes to eukaryotes and participates in various cellular processes, especially in the metabolic processes. Staphylococcus epidermidis is a commensal bacterium in the skin, which attracts more attention as a pathogen, especially in immunocompromised patients and neonates by attaching to medical devices and forming biofilms. However, the significance of lysine succinylation in S. epidermidis proteins has not been investigated. Objectives The purpose of this study was to investigate the physiological and pathological processes of S. epidermidis at the level of PTM. Moreover, by analyzing previous succinylome datasets in various organisms, we tried to provide an in-depth understanding of lysine succinylation. Methods Using antibody affinity enrichment followed by LC-MS/MS analysis, we examined the succinylome of S. epidermidis (ATCC 12228). Then, bioinformatics analysis was performed, including Gene Ontology (GO), KEGG enrichment, motif characterization, secondary structure, protein–protein interaction, and BLAST analysis. Results A total of 1557 succinylated lysine sites in 649 proteins were identified in S. epidermidis (ATCC 12228). Among these succinylation proteins, GO annotation showed that proteins related to metabolic processes accounted for the most. KEGG pathway characterization indicated that proteins associated with the glycolysis/gluconeogenesis and citrate cycle (TCA cycle) pathway were more likely to be succinylated. Moreover, 13 conserved motifs were identified. The specific motif KsuD was conserved in model prokaryotes and eukaryotes. Succinylated proteins with this motif were highly enriched in the glycolysis/gluconeogenesis pathway. One succinylation site (K144) was identified in S-ribosylhomocysteine lyase, a key enzyme in the quorum sensing system, indicating the regulatory role succinylation may play in bacterial processes. Furthermore, 15 succinyltransferases and 18 desuccinylases (erasers) were predicted in S. epidermidis by BLAST analysis. Conclusion We performed the first comprehensive profile of succinylation in S. epidermidis and illustrated the significant role succinylation may play in energy metabolism, QS system, and other bacterial behaviors. This study may be a fundamental basis to investigate the underlying mechanisms of colonization, virulence, and infection of S. epidermidis, as well as provide a new insight into regulatory effects succinylation may lay on metabolic processes (Data are available via ProteomeXchange with identifier PXD022866).
The Relationship Between Salivary Redox, Diet, and Food Flavor Perception

The mouth is the gateway for entrance of food and microorganisms into the organism. The oral cavity is bathed by saliva, which is thus the first fluid that food and microorganisms will face after their entrance. As a result, saliva plays different functions, including lubrication, predigestion, protection, detoxification, and even transport of taste compounds to chemoreceptors located in the taste buds. To ensure its function of protection, saliva contains reactive harmful compounds such as reactive oxygen species that are controlled and neutralized by the antioxidant activity of saliva. Several antioxidant molecules control the production of molecules such as reactive oxygen compounds, neutralize them and/or repair the damage they have caused. Therefore, a balance between reactive oxidant species and antioxidant compounds exists. At the same time, food can also contain antioxidant compounds, which can participate in the equilibrium of this balance. Numerous studies have investigated the effects of different food components on the antioxidant capacity of saliva that correspond to the ability of saliva to neutralize reactive oxygen species. Contradictory results have sometimes been obtained. Moreover, some antioxidant compounds are also cofactors of enzymatic reactions that affect flavor compounds. Recent studies have considered the salivary antioxidant capacity to explain the release of flavor compounds ex vivo or in vivo. This article aims to review the effect of food on the antioxidant capacity of saliva and the impact of salivary antioxidant capacity on flavor perception after a brief presentation of the different molecules involved.
The structure of developing semantic networks: Evidence from single and multiple nominal word associations in young monolingual and bilingual readers

ABSTRACT The present study focuses on the effect of an important methodological choice in word association studies in children: the elicitation of single versus multiple responses. This choice has been shown to affect the numbers and types of associations adults produce, however, little is known about how it affects children’s word associations. A total of 11,725 associations to 80 nouns from 207 monolingual and bilingual minority children were classified according to a detailed coding system, and differences between the semantic characteristics of first, second, and third responses were examined. We show that in children as well, the multiple association task elicits more and qualitatively different responses, resulting in more diversified semantic networks surrounding the stimulus nouns. On the speaker level, reading comprehension scores were related differently to initial and later responses, suggesting a more complex measure of semantic knowledge emerges from the multiple word association task. No differences were found between monolingual and bilingual children’s associative preferences. We argue that the multiple association task produces more detailed data on language users’ semantic networks than the single association task, and suggest a number of ways in which this task could be employed in future research.
Nutrients Bioaccessibility and Anti-inflammatory Features of Fermented Bee Pollen: A Comprehensive Investigation

We compared raw bee-collected pollen (Raw-BCP), spontaneously fermented BCP (Unstarted-BCP), and BCP fermented with selected microbial starters (Started-BCP) to deepen whether fermentation may favorably affect the nutrients bioaccessibility and functional features of BCP. Under in vitro gastrointestinal batches, the highest serum-availability of phenolic compounds was found in Started-BCP, highlighting the positive effect exerted by selected microbial starters. The same effect was not found in spontaneously fermented BCP. In colon adenocarcinoma cell line-2 (Caco-2) cells stressed by a pro-inflammatory stimulus, the treatment with Started-BCP halted the increase of pro-inflammatory mediator’s level. Started-BCP counteracted efficiently the deleterious effects of inflammatory stimuli on the integrity of the Caco-2 cells monolayer and its barrier function. Started-BCP successfully counteracted the H2O2-induced intracellular accumulation of reactive oxygen species (ROS) in Caco-2 cells. A protective role against lipopolysaccharide (LPS)-induced inflammation was exerted by Started-BCP in human keratinocytes. The same protective effects on Caco-2 and keratinocyte cell lines were negligible after treatments with Raw-BCP or Unstarted-BCP.
Estimating a Sleep Apnea Hypopnea Index Based on the ERB Correlation Dimension of Snore Sounds

This paper proposes a new perspective of analyzing non-linear acoustic characteristics of the snore sounds. According to the ERB (Equivalent Rectangular Bandwidth) scale used in psychoacoustics, the ERB correlation dimension (ECD) of the snore sound was computed to feature different severity levels of sleep apnea hypopnea syndrome (SAHS). For the training group of 93 subjects, snore episodes were manually segmented and the ECD parameters of the snores were extracted, which established the gaussian mixture models (GMM). The nocturnal snore sound of the testing group of another 120 subjects was tested to detect SAHS snores, thus estimating the apnea hypopnea index (AHI), which is called AHIECD. Compared to the AHIPSG value of the gold standard polysomnography (PSG) diagnosis, the estimated AHIECD achieved an accuracy of 87.5% in diagnosis the SAHS severity levels. The results suggest that the ECD vectors can be effective parameters for screening SAHS.
Commentary: A Computational Theory of Mindfulness Based Cognitive Therapy from the “Bayesian Brain” Perspective

Manjaly and Iglesias (2020) introduce a neurocomputational model of mechanisms through which Mindfulness Based Cognitive Therapy may work, based on a Bayesian perspective. They claim that mindfulness increases the precision of likelihood, but decreases the precision of prior. In this commentary, we argue that these two mechanisms conflict when describing mindful functioning. We suggest an alternative mechanism – namely the dynamic updating of prior beliefs as a function of context, which contributes to active inference. The moment-to-moment attentional pattern of mindfulness could promote the optimal adjustment of prior beliefs to the context of each present experience.
Impulsivity Mediates Associations Between Problematic Internet Use, Anxiety, and Depressive Symptoms in Students: A Cross-Sectional COVID-19 Study

Background: Problematic internet use (PIU) is a serious global mental health issue that especially manifested during the Coronavirus disease (COVID-19) pandemic. Engagement in PIU as an impulsive coping with mental distress may pose a long-lasting threat to develop anxiety and depressive disorders. The first aim of our study was to investigate the prevalence of PIU and mental distress symptoms during the COVID-19 pandemic among university students in Lithuania. The second aim was to test the hypothesis that PIU affects anxiety and depressive symptoms through the mediating role of impulsivity. Methods: The cross-sectional study was comprised of 619 university students (92.9% females and 7.1% males) with a mean age of 22 ± 3 years who participated in an online survey from May to November, 2020. Participants completed the following scales: the Problematic Internet Use Questionnaire-9, the Generalized Anxiety Disorder Questionnaire-7, the Patient Health Questionnaire-9, and the Barratt Impulsiveness Scale-11. K-means cluster analysis and one-way multivariate analysis of variance were used for group comparison in terms of internet use time and habit change during COVID-19 pandemic. Structural equation modeling was applied to examine the mediating effect of impulsivity in association between PIU and mental distress, while controlling for age. Results: In sum, 45.1% of the participants reported PIU and 38.1% had markedly expressed symptoms of anxiety while 43.6% of the students reported moderate to severe depressive symptoms. During the COVID-19 pandemic 76% of the students reported at least moderate increase in their internet use time. Anxiety and depressive symptoms were significantly higher in the group of frequent internet users. The results of the structural equational modeling analysis showed a statistically significant effect of PIU on subjective anxiety symptoms and the statistically significant effect of PIU on subjective depression symptoms, both mediated via impulsivity. Conclusions: During COVID-19 pandemic, PIU, anxiety and depression symptoms are highly prevalent among students. Findings also suggest that relationships between PIU, anxiety and depressive symptoms are mediated via impulsivity. These results underscore the importance of the inclusion of impulsivity factor in the studies analyzing longitudinal effects of PIU on mental distress during COVID-19 pandemic.
On the Use of Artificial Neural Networks to Monitor a Pharmaceutical Freeze-Drying Process

This paper is focused on the use of artificial neural networks to monitor a pharmaceutical freeze-drying process. A detailed phenomenological model of the process is used to provide the dataset for the learning phase of the neural network development. Then, a methodology based on a self-adaptive differential evolution scheme is combined with a back-propagation algorithm, as local search method, for the simultaneous structural and parametric optimization of the neural network which models the freeze-drying process. Using some experimentally available measurements at a generic time t, the neural network is able to estimate the temperature of the product and the thickness of the dried cake (the amount of residual ice, as well as the sublimation flux, can be easily calculated from the cake thickness) at a future time t + Δt, for the given operating conditions (the temperature of the heating shelf and the pressure in the drying chamber). Also, the duration of the primary drying phase and the maximum product temperature in the future are predicted, in case the operating conditions are not modified. In this way it is possible to understand if it is necessary to modify the operating conditions, in case the product temperature should trespass the limit value before the ending point of the primary drying. Despite the fact that the artificial neural network is obtained using a learning set determined for specific values of heat transfer coefficient (between the heating shelf and the product at the bottom of the container) and of mass transfer resistance (of the dried cake to vapor flow), reliable and accurate estimations are also obtained in case the sensor is used to monitor a process characterized by different values of heat and mass transfer coefficients.