NK Cell-Based Immunotherapy in Colorectal Cancer.

Human Natural Killer (NK) cells are all round players in immunity thanks to their powerful and immediate response against transformed cells and the ability to modulate the subsequent adaptive immune response. The potential of immunotherapies based on NK cell involvement has been initially revealed in the hematological setting but has inspired the design of different immune tools to also be applied against solid tumors, including colorectal cancer (CRC). Indeed, despite cancer prevention screening plans, surgery, and chemotherapy strategies, CRC is one of the most widespread cancers and with the highest mortality rate. Therefore, further efficient and complementary immune-based therapies are in urgent need. In this review, we gathered the most recent advances in NK cell-based immunotherapies aimed at fighting CRC, in particular, the use of monoclonal antibodies targeting tumor-associated antigens (TAAs), immune checkpoint blockade, and adoptive NK cell therapy, including NK cells modified with chimeric antigen receptor (CAR-NK).

CD19-Targeted Immunotherapies for Diffuse Large B-Cell Lymphoma.

Surgical resection, chemotherapy and radiotherapy were, for many years, the only available cancer treatments. Recently, the use of immune checkpoint inhibitors and adoptive cell therapies has emerged as promising alternative. These cancer immunotherapies are aimed to support or harness the patient's immune system to recognize and destroy cancer cells. Preclinical and clinical studies, based on the use of T cells and more recently NK cells genetically modified with chimeric antigen receptors retargeting the adoptive cell therapy towards tumor cells, have already shown remarkable results. In this review, we outline the latest highlights and progress in immunotherapies for the treatment of Diffuse Large B-cell Lymphoma (DLBCL) patients, focusing on CD19-targeted immunotherapies. We also discuss current clinical trials and opportunities of using immunotherapies to treat DLBCL patients.

Treating Critically Ill Patients Experiencing SARS-CoV-2 Severe Infection with Ig-M and Ig-A Enriched Ig-G Infusion.

SARS-CoV-2 in patients who need intensive care unit (ICU) is associated with a mortality rate ranging from 10 to 40-45%, with an increase in morbidity and mortality in presence of sepsis. We hypothesized that IgM and IgA enriched immunoglobulin G may support the sepsis-related phase improving patient outcome. We conducted a retrospective case-control study on 47 consecutive patients admitted to our ICU. At the time of admission, patients received anticoagulants (heparin sodium) together with the standard supportive treatment. We decided to add IgM and IgA enriched immunoglobulin G to the standard therapy. Patients receiving IgM and IgA enriched immunoglobulin G were compared with patients with similar baseline characteristics and treatment, receiving only standard therapy. The mortality resulted significantly higher in patients treated with standard therapy only (56.5 vs. 37.5%, p < 0.01) and, at day 7, the probability of dying was 3 times higher in this group. Variable life adjustment display (VLAD) was 2.4 and -2.2 (in terms of lives saved in relation with those expected and derived from Simplified Acute Physiology Score II) in the treated and not treated group, respectively. The treatment based on IgM and IgA enriched immunoglobulin G infusion seems to give an advantage on survival in SARS-CoV-2 severe infection.

IL-27 Mediates PD-L1 Expression and Release by Human Mesothelioma Cells.

Malignant mesothelioma (MM) is a rare tumor with an unfavorable prognosis. MM genesis involves asbestos-mediated local inflammation, supported by several cytokines, including IL-6. Recent data showed that targeting PD-1/PD-L1 is an effective therapy in MM. Here, we investigated the effects of IL-6 trans-signaling and the IL-6-related cytokine IL-27 on human MM cells in vitro by Western blot analysis of STAT1/3 phosphorylation. The effects on PD-L1 expression were tested by qRT-PCR and flow-cytometry and the release of soluble (s)PD-L1 by ELISA. We also measured the concentrations of sPD-L1 and, by multiplexed immunoassay, IL-6 and IL-27 in pleural fluids obtained from 77 patients in relation to survival. IL-27 predominantly mediates STAT1 phosphorylation and increases PD-L1 gene and surface protein expression and sPD-L1 release by human MM cells in vitro. IL-6 has limited activity, whereas a sIL-6R/IL-6 chimeric protein mediates trans-signaling predominantly via STAT3 phosphorylation but has no effect on PD-L1 expression and release. IL-6, IL-27, and sPD-L1 are present in pleural fluids and show a negative correlation with overall survival, but only IL-27 shows a moderate albeit significant correlation with sPD-L1 levels. Altogether these data suggest a potential role of IL-27 in PD-L1-driven immune resistance in MM.

A new open-access platform for measuring and sharing mTBI data.

Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: (1) a centralized, open-access platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and (2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.

Feasibility and effectiveness of Dialectical-Behavior Therapy for patients with borderline personality disorder in Italian mental health services: a preliminary study.

Dialectical-Behavior Therapy (DBT) is an evidence-based effective psychotherapeutic intervention for patients with Borderline Personality Disorder (BPD). There is a paucity of empirical evidences on the feasibility and the effectiveness of DBT in real-world Italian mental health services. This study aimed at reporting preliminary data on the implementation of DBT for adult patients with BPD attending an Italian mental health service. 28 BPD patients attending a mental health service underwent a 16-session DBT program. Effects of DBT were measured with the Difficulties in Emotion Regulation Scale (DERS) and the Barratt Impulsiveness Scale (BIS-11). 17 patients completed the DBT program, reporting reduced levels of emotion dysregulation and impulsiveness at follow up in comparison with baseline. Higher emotional dysregulation was a risk factor for dropout. In conclusion, this preliminary pilot study suggests that DBT is feasible and effective for BPD patients in Italian adult mental health services.

Freedom or money? The dilemma of migrant live-in elderly carers in times of COVID-19.

As a consequence of the lockdown measures imposed by the Belgian government to fight against COVID-19, migrant live-in elderly carers had to choose between safeguarding their job - at the detriment of their personal freedom, their health and their working conditions - and safeguarding their freedom but losing their job - at the detriment of their economic survival and that of their families. This article explores this dilemma from an intersectionality perspective. In order to understand their experience in times of COVID-19 and their response to this dilemma, I analyse their position as women, as migrants, as elderly care workers, as family breadwinners and as 'quasi-family members' in the families of their employer - which correspond to five interlocking systems of oppression.

Multi-Directional Dynamic Model for Traumatic Brain Injury Detection.

Given the worldwide adverse impact of traumatic brain injury (TBI) on the human population, its diagnosis and prediction are of utmost importance. Historically, many studies have focused on associating head kinematics to brain injury risk. Recently, there has been a push toward using computationally expensive finite element (FE) models of the brain to create tissue deformation metrics of brain injury. Here, we develop a new brain injury metric, the brain angle metric (BAM), based on the dynamics of a 3 degree-of-freedom lumped parameter brain model. The brain model is built based on the measured natural frequencies of an FE brain model simulated with live human impact data. We show that it can be used to rapidly estimate peak brain strains experienced during head rotational accelerations that cause mild TBI. In our data set, the simplified model correlates with peak principal FE strain (R2 = 0.82). Further, coronal and axial brain model displacement correlated with fiber-oriented peak strain in the corpus callosum (R2 = 0.77). Our proposed injury metric BAM uses the maximum angle predicted by our brain model and is compared against a number of existing rotational and translational kinematic injury metrics on a data set of head kinematics from 27 clinically diagnosed injuries and 887 non-injuries. We found that BAM performed comparably to peak angular acceleration, translational acceleration, and angular velocity in classifying injury and non-injury events. Metrics that separated time traces into their directional components had improved model deviance compare with those that combined components into a single time trace magnitude. Our brain model can be used in future work to rapidly approximate the peak strain resulting from mild to moderate head impacts and to quickly assess brain injury risk.

Dynamic Blood-Brain Barrier Regulation in Mild Traumatic Brain Injury.

Whereas the diagnosis of moderate and severe traumatic brain injury (TBI) is readily visible on current medical imaging paradigms (magnetic resonance imaging [MRI] and computed tomography [CT] scanning), a far greater challenge is associated with the diagnosis and subsequent management of mild TBI (mTBI), especially concussion which, by definition, is characterized by a normal CT. To investigate whether the integrity of the blood-brain barrier (BBB) is altered in a high-risk population for concussions, we studied professional mixed martial arts (MMA) fighters and adolescent rugby players. Additionally, we performed the linear regression between the BBB disruption defined by increased gadolinium contrast extravasation on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) on MRI and multiple biomechanical parameters indicating the severity of impacts recorded using instrumented mouthguards in professional MMA fighters. MMA fighters were examined pre-fight for a baseline and again within 120 h post-competitive fight, whereas rugby players were examined pre-season and again post-season or post-match in a subset of cases. DCE-MRI, serological analysis of BBB biomarkers, and an analysis of instrumented mouthguard data, was performed. Here, we provide pilot data that demonstrate disruption of the BBB in both professional MMA fighters and rugby players, dependent on the level of exposure. Our data suggest that biomechanical forces in professional MMA and adolescent rugby can lead to BBB disruption. These changes on imaging may serve as a biomarker of exposure of the brain to repetitive subconcussive forces and mTBI.

Lateral impacts correlate with falx cerebri displacement and corpus callosum trauma in sports-related concussions.

Corpus callosum trauma has long been implicated in mild traumatic brain injury (mTBI), yet the mechanism by which forces penetrate this structure is unknown. We investigated the hypothesis that coronal and horizontal rotations produce motion of the falx cerebri that damages the corpus callosum. We analyzed previously published head kinematics of 115 sports impacts (2 diagnosed mTBI) measured with instrumented mouthguards and used finite element (FE) simulations to correlate falx displacement with corpus callosum deformation. Peak coronal accelerations were larger in impacts with mTBI (8592 rad/s2 avg.) than those without (1412 rad/s2 avg.). From FE simulations, coronal acceleration was strongly correlated with deep lateral motion of the falx center (r = 0.85), while horizontal acceleration was correlated with deep lateral motion of the falx periphery (r > 0.78). Larger lateral displacement at the falx center and periphery was correlated with higher tract-oriented strains in the corpus callosum body (r = 0.91) and genu/splenium (r > 0.72), respectively. The relationship between the corpus callosum and falx was unique: removing the falx from the FE model halved peak strains in the corpus callosum from 35% to 17%. Consistent with model results, we found indications of corpus callosum trauma in diffusion tensor imaging of the mTBI athletes. For a measured alteration of consciousness, depressed fractional anisotropy and increased mean diffusivity indicated possible damage to the mid-posterior corpus callosum. Our results suggest that the corpus callosum may be sensitive to coronal and horizontal rotations because they drive lateral motion of a relatively stiff membrane, the falx, in the direction of commissural fibers below.

Performances of the PIPER scalable child human body model in accident reconstruction.

Human body models (HBMs) have the potential to provide significant insights into the pediatric response to impact. This study describes a scalable/posable approach to perform child accident reconstructions using the Position and Personalize Advanced Human Body Models for Injury Prediction (PIPER) scalable child HBM of different ages and in different positions obtained by the PIPER tool. Overall, the PIPER scalable child HBM managed reasonably well to predict the injury severity and location of the children involved in real-life crash scenarios documented in the medical records. The developed methodology and workflow is essential for future work to determine child injury tolerances based on the full Child Advanced Safety Project for European Roads (CASPER) accident reconstruction database. With the workflow presented in this study, the open-source PIPER scalable HBM combined with the PIPER tool is also foreseen to have implications for improved safety designs for a better protection of children in traffic accidents.

IL-27 mediates HLA class I up-regulation, which can be inhibited by the IL-6 pathway, in HLA-deficient Small Cell Lung Cancer cells.

BACKGROUND: Recently, immunotherapy with anti-PD-1 antibodies has shown clinical benefit in recurrent Small Cell Lung Cancer (SCLC). Since anti-PD-1 re-activates anti-tumor Cytotoxic T Lymphocyte (CTL) responses, it is crucial to understand the mechanisms regulating HLA class I, and PD-L1 expression in HLA-negative SCLC. Here we addressed the role of IL-27, a cytokine related to both IL-6 and IL-12 families. METHODS: The human SCLC cell lines NCI-N592, -H69, -H146, -H446 and -H82 were treated in vitro with different cytokines (IL-27, IFN-γ, IL-6 or a soluble IL-6R/IL-6 chimera [sIL-6R/IL-6]) at different time points and analyzed for tyrosine-phosphorylated STAT proteins by Western blot, for surface molecule expression by immunofluorescence and FACS analyses or for specific mRNA expression by QRT-PCR. Relative quantification of mRNAs was calculated by the ΔΔCT method. The Student's T test was used for the statistical analysis of experimental replicates. RESULTS: IL-27 triggered STAT1/3 phosphorylation and up-regulated the expression of surface HLA class I antigen and of TAP1 and TAP2 mRNA in four out of five SCLC cell lines tested. The IL-27-resistant NCI-H146 cells showed up-regulation of HLA class I by IFN-γ. IFN-γ also induced expression of PD-L1 in SCLC cells, while IL-27 was less potent in this respect. IL-27 failed to activate STAT1/3 phosphorylation in NCI-H146 cells, which display a low expression of the IL-27RA and GP130 receptor chains. As GP130 is shared in IL-27R and IL-6R complexes, we assessed its functionality in response to sIL-6R/IL-6. sIL-6R/IL-6 failed to trigger STAT1/3 signaling in NCI-H146 cells, suggesting low GP130 expression or uncoupling from signal transduction. Although both sIL-6R/IL-6 and IL-27 triggered STAT1/3 phosphorylation, sIL-6R/IL-6 failed to up-regulate HLA class I expression, in relationship to the weak activation of STAT1. Finally sIL-6R/IL-6 limited IL-27-effects, particularly in NCI-H69 cells, in a SOCS3-independent manner, but did not modify IFN-γ induced HLA class I up-regulation. CONCLUSIONS: In conclusion, IL-27 is a potentially interesting cytokine for restoring HLA class I expression for SCLC combined immunotherapy purposes. However, the concomitant activation of the IL-6 pathway may limit the IL-27 effect on HLA class I induction but did not significantly alter the responsiveness to IFN-γ.

Gait abnormalities of COPD are not directly related to respiratory function.

STUDY OBJECTIVE: To assess whether gait abnormalities in COPD depend on mere impairment of respiratory function. METHODS: In 40 patients with COPD at different GOLD stages and 28 controls, we evaluated: forced expiratory volume in 1s (FEV1); partial pressure of oxygen; Mini-Mental State Examination (MMSE); dynamic balance through the Mini-BESTest (MBT); Timed Up and Go (TUG) test without and with dual task counting aloud back by three; 6-min walk test (6MWT); body sway during quiet stance (stabilometry); spatial-temporal variables of gait by a 4-m long sensorized walkway (baropodometry). Lower-limb muscle strength, tendon reflexes, and sensation were also clinically evaluated. RESULTS: Muscle strength of proximal but not distal muscles was slightly reduced in patients, whereas reflexes and sensation were unaffected. FEV1, partial pressure of oxygen, MMSE, MBT, stabilometry, as well as baropodometry, were abnormal and unrelated to muscle weakness. The time taken to perform the TUG test was increased, and to a larger extent with than without dual task. At baropodometry, variability of step length was increased; abnormalities of gait variables were associated with larger body sway but not with FEV1 or hypoxemia. Gait speed at 6MWT was correlated with MBT score and with FEV1 as well as hypoxemia. CONCLUSIONS: 6MWT findings give a measure of gait disability linked to endurance-related respiratory failure. Gait at baropodometry is associated with impairment of balance, cognitive status and abnormal dual task performance. We suggest that central nervous lesions, presumably of vascular origin, are detrimental to balance and gait in COPD.

Anisotropic finite element models for brain injury prediction: the sensitivity of axonal strain to white matter tract inter-subject variability.

Computational models incorporating anisotropic features of brain tissue have become a valuable tool for studying the occurrence of traumatic brain injury. The tissue deformation in the direction of white matter tracts (axonal strain) was repeatedly shown to be an appropriate mechanical parameter to predict injury. However, when assessing the reliability of axonal strain to predict injury in a population, it is important to consider the predictor sensitivity to the biological inter-subject variability of the human brain. The present study investigated the axonal strain response of 485 white matter subject-specific anisotropic finite element models of the head subjected to the same loading conditions. It was observed that the biological variability affected the orientation of the preferential directions (coefficient of variation of 39.41% for the elevation angle-coefficient of variation of 29.31% for the azimuth angle) and the determination of the mechanical fiber alignment parameter in the model (gray matter volume 55.55-70.75%). The magnitude of the maximum axonal strain showed coefficients of variation of 11.91%. On the contrary, the localization of the maximum axonal strain was consistent: the peak of strain was typically located in a 2 cm3 volume of the brain. For a sport concussive event, the predictor was capable of discerning between non-injurious and concussed populations in several areas of the brain. It was concluded that, despite its sensitivity to biological variability, axonal strain is an appropriate mechanical parameter to predict traumatic brain injury.

Development of an Unbiased Validation Protocol to Assess the Biofidelity of Finite Element Head Models used in Prediction of Traumatic Brain Injury.

This study describes a method to identify laboratory test procedures and impact response requirements suitable for assessing the biofidelity of finite element head models used in prediction of traumatic brain injury. The selection of the experimental data and the response requirements were result of a critical evaluation based on the accuracy, reproducibility and relevance of the available experimental data. A weighted averaging procedure was chosen in order to consider different contributions from the various test conditions and target measurements based on experimental error. According to the quality criteria, 40 experimental cases were selected to be a representative dataset for validation. Based on the evaluation of response curves from four head finite element models, CORA was chosen as a quantitative method to compare the predicted time history response to the measured data. Optimization of the CORA global settings led to the recommendation of performing curve comparison on a fixed time interval of 0-30 ms for intracranial pressure and at least 0-40 ms for brain motion and deformation. The allowable maximum time shift was adjusted depending on the shape of the experimental curves (DMAX = 0.12 for intracranial pressure, DMAX = 0.40 for brain motion and DMAX = 0.25 for brain deformation). Finally, bigger penalization of ratings was assigned to curves with fundamentally incorrect shape compared to those having inaccuracies in amplitude or time shift (cubic vs linear). This rigorous approach is necessary to ensure confidence in the model results and progress in the usage of finite element head models for traumatic brain injury prediction.

Connecting fractional anisotropy from medical images with mechanical anisotropy of a hyperviscoelastic fibre-reinforced constitutive model for brain tissue.

Brain tissue modelling has been an active area of research for years. Brain matter does not follow the constitutive relations for common materials and loads applied to the brain turn into stresses and strains depending on tissue local morphology. In this work, a hyperviscoelastic fibre-reinforced anisotropic law is used for computational brain injury prediction. Thanks to a fibre-reinforcement dispersion parameter, this formulation accounts for anisotropic features and heterogeneities of the tissue owing to different axon alignment. The novelty of the work is the correlation of the material mechanical anisotropy with fractional anisotropy (FA) from diffusion tensor images. Finite-element (FE) models are used to investigate the influence of the fibre distribution for different loading conditions. In the case of tensile-compressive loads, the comparison between experiments and simulations highlights the validity of the proposed FA-k correlation. Axon alignment affects the deformation predicted by FE models and, when the strain in the axonal direction is large with respect to the maximum principal strain, decreased maximum deformations are detected. It is concluded that the introduction of fibre dispersion information into the constitutive law of brain tissue affects the biofidelity of the simulations.

Evaluation of Axonal Strain as a Predictor for Mild Traumatic Brain Injuries Using Finite Element Modeling.

Finite element (FE) models are often used to study the biomechanical effects of traumatic brain injury (TBI). Measures based on mechanical responses, such as principal strain or invariants of the strain tensor, are used as a metric to predict the risk of injury. However, the reliability of inferences drawn from these models depends on the correspondence between the mechanical measures and injury data, as well as the establishment of accurate thresholds of tissue injury. In the current study, a validated anisotropic FE model of the human head is used to evaluate the hypothesis that strain in the direction of fibers (axonal strain) is a better predictor of TBI than maximum principal strain (MPS), anisotropic equivalent strain (AESM) and cumulative strain damage measure (CSDM). An analysis of head kinematics-based metrics, such as head injury criterion (HIC) and brain injury criterion (BrIC), is also provided. Logistic regression analysis is employed to compare binary injury data (concussion/no concussion) with continuous strain/kinematics data. The threshold corresponding to 50% of injury probability is determined for each parameter. The predictive power (area under the ROC curve, AUC) is calculated from receiver operating characteristic (ROC) curve analysis. The measure with the highest AUC is considered to be the best predictor of mTBI. Logistic regression shows a statistical correlation between all the mechanical predictors and injury data for different regions of the brain. Peaks of axonal strain have the highest AUC and determine a strain threshold of 0.07 for corpus callosum and 0.15 for the brainstem, in agreement with previously experimentally derived injury thresholds for reversible axonal injury. For a data set of mild TBI from the national football league, the strain in the axonal direction is found to be a better injury predictor than MPS, AESM, CSDM, BrIC and HIC.