Microbials for the production of monoclonal antibodies and antibody fragments

Monoclonal antibodies (mAbs) and antibody fragments represent the most important biopharmaceutical products today. Because full length antibodies are glycosylated, mammalian cells, which allow human-like N-glycosylation, are currently used for their production. However, mammalian cells have several drawbacks when it comes to bioprocessing and scale-up, resulting in long processing times and elevated costs. By contrast, antibody fragments, that are not glycosylated but still exhibit antigen binding properties, can be produced in microbial organisms, which are easy to manipulate and cultivate. In this review, we summarize recent advances in the expression systems, strain engineering, and production processes for the three main microbials used in antibody and antibody fragment production, namely Saccharomyces cerevisiae, Pichia pastoris, and Escherichia coli

The impact of the SARS-CoV-2 pandemic on the workloads of UPMC advanced radiotherapy centers in Italy

GOALS The Advanced Radiotherapy Centers of UPMC San Pietro FBF of Rome (CC#1) and UPMC Villa Maria of Mirabella Eclano (CC#2) conducted a study to review variations in department workloads and workflows experienced during the pandemic. The potential relation between these variations and the new procedures introduced to prevent and contain the COVID-19 infection was also studied. MATERIALS AND METHODS The data used were obtained from reports present in the ARIA® system (v. 15.1 Varian Medical Systems, Palo Alto, CA, U.S.A.). To examine the workloads was used the Downtime, an indicator that directly quantifies the inactivity of the department, derived from the ratio between the daily stand-by time of the LINACs (TrueBeam STx®, Varian Medical Systems, Palo Alto, CA, U.S.A.) and the mean number of treatments performed every day. In order to examine the workflows and possible delays, we measured the time between the treatments ("Therapy intervals"). RESULTS The Downtime average at CC#1 slightly increased from 3.1% in 2019 to 3.8% in 2020. However, the monthly analysis shows significant reduction (March-April-May) and increase (November-December) peaks. At CC#2, the 2020 Downtime trend was fairly consistent (average value: 3.3%), with an increase during the first wave of the pandemic. The "5-10 min" Therapy intervals at CC#1, reviewed comparing the March-April-May 2020 quarter with 2019, were higher in the first months and lower in May; the "10-15 min" intervals were stable; the ">20 min" intervals slightly increased in March 2020. At CC#2, the trend in 2020 decreased during the months of higher health care emergency and increased during the summer months. CONCLUSIONS The fact that the trends of the indicators show peaks only during the periods of major health care emergency indicates an impact of the pandemic, both on the workload and on the workflow. However, they also highlight the staff's ability to rapidly adapt to the new procedures, without affecting the overall performance of the both centers

GEN-O-MA project: an Italian network studying clinical course and pathogenic pathways of moyamoya disease—study protocol and preliminary results

Background: GENetics of mOyaMoyA (GEN-O-MA) project is a multicenter observational study implemented in Italy aimed at creating a network of centers involved in moyamoya angiopathy (MA) care and research and at collecting a large series and bio-repository of MA patients, finally aimed at describing the disease phenotype and clinical course as well as at identifying biological or cellular markers for disease progression. The present paper resumes the most important study methodological issues and preliminary results. Methods: Nineteen centers are participating to the study. Patients with both bilateral and unilateral radiologically defined MA are included in the study. For each patient, detailed demographic and clinical as well as neuroimaging data are being collected. When available, biological samples (blood, DNA, CSF, middle cerebral artery samples) are being also collected for biological and cellular studies. Results: Ninety-eight patients (age of onset mean ± SD 35.5 ± 19.6 years; 68.4% females) have been collected so far. 65.3% of patients presented ischemic (50%) and haemorrhagic (15.3%) stroke. A higher female predominance concomitantly with a similar age of onset and clinical features to what was reported in previous studies on Western patients has been confirmed. Conclusion: An accurate and detailed clinical and neuroimaging classification represents the best strategy to provide the characterization of the disease phenotype and clinical course. The collection of a large number of biological samples will permit the identification of biological markers and genetic factors associated with the disease susceptibility in Italy

Impatto della pandemia da SARS-CoV-2 sui workload di due centri UPMC di radioterapia ad alta specializzazione in Italia

OBIETTIVI I Centri di Radioterapia UPMC San Pietro FBF di Roma (CC#1) e UPMC Villa Maria di Mirabella Eclano (CC#2) hanno condotto uno studio con l’obiettivo di analizzare le variazioni avvenute durante la pandemia sui workload e i workflow di reparto. È stato, inoltre, ricercato l’eventuale nesso tra queste e l’introduzione di nuove procedure per la prevenzione e il contenimento del contagio da Covid-19. MATERIALI E METODI I dati utilizzati sono stati ricavati da reports presenti nel sistema ARIA (V.15.1 Varian Medical System, CA, Palo Alto, USA). Per esaminare i workload è stato utilizzato il Downtime, un indicatore che quantifica direttamente l'inattività del reparto, ricavato dal rapporto tra il tempo di standby giornaliero dei LINAC (TrueBeam STx®, Varian Medical System, CA, Palo Alto, USA) e la media di trattamenti giornalieri effettuati. Per esaminare workflow ed eventuali ritardi tra le attività, sono stati valutati gli intervalli di tempo tra una terapia e la successiva (Intervalli di terapia). RISULTATI Il Downtime nel CC#1 ha subìto un leggero aumento del valore medio dal 3.1% del 2019 al 3.8% del 2020, tuttavia l’analisi mensile mostra consistenti picchi di riduzione (marzo-aprile-maggio) e di incremento (novembre-dicembre). Per il CC#2 il trend del Downtime nel 2020 è abbastanza regolare (valore medio del 3,3%), con un incremento durante la prima ondata della pandemia. Gli Intervalli di terapia di “5-10 min” nel CC#1, analizzati confrontando il trimestre marzo-aprile-maggio 2020 col 2019, risultano maggiori per i primi mesi e ridotti a maggio; quelli di “10-15” min risultano stabili; quelli “>20 min” sono leggermente aumentati a marzo 2020. Per il CC#2 il trend nel 2020 decresce nei mesi di maggiore emergenza sanitaria e incrementa nei mesi estivi. CONCLUSIONI Il fatto che i trend degli indicatori utilizzati abbiano dei picchi esclusivamente in corrispondenza dei periodi di maggiore emergenza sanitaria, è indice di un certo impatto – sia in termini di workload che di workflow – della pandemia, ma anche della capacità del personale di adattarsi in breve tempo alle nuove procedure da eseguire, senza inficiare sul rendimento generale dei Centri

Neurosphere-Derived Cells Exert a Neuroprotective Action by Changing the Ischemic Microenvironment

BACKGROUND: Neurosphere-derived cells (NC), containing neural stem cells, various progenitors and more differentiated cells, were obtained from newborn C57/BL6 mice and infused in a murine model of focal ischemia with reperfusion to investigate if: 1) they decreased ischemic injury and restored brain function; 2) they induced changes in the environment in which they are infused; 3) changes in brain environment consequent to transient ischemia were relevant for NC action. METHODOLOGY/PRINCIPAL FINDINGS: NC were infused intracerebroventricularly 4 h or 7 d after 30 min middle cerebral artery occlusion. In ischemic mice receiving cells at 4 h, impairment of open field performance was significantly improved and neuronal loss significantly reduced 7–14 d after ischemia compared to controls and to ischemic mice receiving cells at 7 d. Infusion of murine foetal fibroblast in the same experimental conditions was not effective. Assessment of infused cell distribution revealed that they migrated from the ventricle to the parenchyma, progressively decreased in number but they were observable up to 14 d. In mice receiving NC at 7 d and in sham-operated mice, few cells could be observed only at 24 h, indicating that the survival of these cells in brain tissue relates to the ischemic environment. The mRNA expression of trophic factors such as Insulin Growth Factor-1, Vascular Endothelial Growth Factor-A, Transforming Growth Factor-β1, Brain Derived Neurotrophic Factor and Stromal Derived Factor−1α, as well as microglia/macrophage activation, increased 24 h after NC infusion in ischemic mice treated at 4 h compared to sham-operated and to mice receiving cells at 7 d. CONCLUSIONS/SIGNIFICANCE: NC reduce functional impairment and neuronal damage after ischemia/reperfusion injury. Several lines of evidence indicate that the reciprocal interaction between NC and the ischemic environment is crucial for NC protective actions. Based on these results we propose that a bystander control of the ischemic environment may be the mechanism used by NC to rapidly restore acutely injured brain function

Arterially Perfused Neurosphere-Derived Cells Distribute Outside the Ischemic Core in a Model of Transient Focal Ischemia and Reperfusion In Vitro

BACKGROUND: Treatment with neural stem cells represents a potential strategy to improve functional recovery of post-ischemic cerebral injury. The potential benefit of such treatment in acute phases of human ischemic stroke depends on the therapeutic viability of a systemic vascular delivery route. In spite of the large number of reports on the beneficial effects of intracerebral stem cells injection in experimental stroke, very few studies demonstrated the effectiveness of the systemic intravenous delivery approach. METODOLOGY/PRINCIPAL FINDINGS: We utilized a novel in vitro model of transient focal ischemia to analyze the brain distribution of neurosphere-derived cells (NCs) in the early 3 hours that follow transient occlusion of the medial cerebral artery (MCA). NCs obtained from newborn C57/BL6 mice are immature cells with self-renewal properties that could differentiate into neurons, astrocytes and oligodendrocytes. MCA occlusion for 30 minutes in the in vitro isolated guinea pig brain preparation was followed by arterial perfusion with 1x10(6) NCs charged with a green fluorescent dye, either immediately or 60 minutes after reperfusion onset. Changes in extracellular pH and K(+) concentration during and after MCAO were measured through ion-sensitive electrodes. CONCLUSION/SIGNIFICANCE: It is demonstrated that NCs injected through the vascular system do not accumulate in the ischemic core and preferentially distribute in non-ischemic areas, identified by combined electrophysiological and morphological techniques. Direct measurements of extracellular brain ions during and after MCA occlusion suggest that anoxia-induced tissue changes, such as extracellular acidosis, may prevent NCs from entering the ischemic area in our in vitro model of transitory focal ischemia and reperfusion suggesting a role played by the surrounding microenviroment in driving NCs outside the ischemic core. These findings strongly suggest that the potential beneficial effect of NCs in experimental focal brain ischemia is not strictly dependent on their homing into the ischemic region, but rather through a bystander mechanism possibly mediated by the release of neuroprotective factors in the peri-infarct region

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification