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All people have culture. When white educators in multicultural communities acknowledge their culture, they are not denying their white privilege, but rather making room for the realization that their teaching practices and learning environments are imbedded with their own cultural codes and traditions. When these educators claim that they do not have a culture, it hurts everyone and hurts those in their classes who presumably do. In this article, the author explores her own culture and discusses how denying or ignoring her cultural roots would hurt her and those around her who have a different culture.

Background: The anti-CD38 antibody daratumumab is a common multiple myeloma treatment. As the erythrocyte's membrane expresses CD38, Daratumumab-treated samples show agglutination in serological pre-transfusion tests, hindering detection of erythrocyte alloantibodies. Dithiothreitol interferes with erythrocyte antigens, affecting investigation of unexpected antibodies. DARAEx®, an anti-CD38 neutralizing agent, overcomes daratumumab- induced effects, without dithiothreitol's interferences. DARAEx® is applied only in Biorad columns. This study aimed to provide a DARAEx® protocol for application with the Grifols platform. Methods: We introduced a modified DARAEx® protocol (AssutaBB protocol) and performed antibody screenings on samples from nineteen daratumumab-treated patients. Results: The AssutaBB protocol provided antibody screen results for all patients, exactly as established in the default manufacturing protocol. Eleven patients presented natural negative antibody screens; eight presented positive K/E antibodies. Conclusions: AssutaBB allows the use of the more widespread Grifols platform in daratumumab-treated patients. [ABSTRACT FROM AUTHOR]

When Billy boy was one, he learned to suck his thumb. Tapioca, tapioca, half past one, cross down When Billy boy was two, he learned to tie his shoe, Tapioca, […]

An understanding of the mechanisms underlying acquired resistance to cetuximab is urgently needed to improve cetuximab efficacy in patients with head and neck squamous cell carcinoma (HNSCC). Here, we present a clinical observation that MET pathway activation constitutes the mechanism of acquired resistance to cetuximab in a patient with HNSCC. Specifically, RNA sequencing and mass spectrometry analysis of cetuximab‐sensitive (CetuxSen) and cetuximab‐resistant (CetuxRes) tumors indicated MET amplification and overexpression in the CetuxRes tumor compared to the CetuxSen lesion. Stimulation of MET in HNSCC cell lines was sufficient to reactivate the MAPK pathway and to confer resistance to cetuximab in vitro and in vivo. In addition to the direct role of MET in reactivation of the MAPK pathway, MET stimulation abrogates the well‐known cetuximab‐induced compensatory feedback loop of HER2/HER3 expression. Mechanistically, we showed that the overexpression of HER2 and HER3 following cetuximab treatment is mediated by the ETS homologous transcription factor (EHF), and is suppressed by MET/MAPK pathway activation. Collectively, our findings indicate that evaluation of MET and HER2/HER3 in response to cetuximab in HNSCC patients can provide the rationale of successive line of treatment. What's new? Resistance to cetuximab is a major obstacle in the treatment of patients with head and neck squamous cell carcinoma (HNSCC), though the underlying mechanisms of resistance remain unclear. In the present study, analyses of tumor samples from an HNSCC patient with exceptional clinical response to cetuximab monotherapy implicate MET pathway activation as a causative factor in acquired cetuximab resistance. Experiments in vitro and in vivo show that MET confers resistance to cetuximab via activation of the MAPK pathway. MET stimulation further limits cetuximab‐induced HER2/HER3 overexpression, highlighting the importance of HER2/HER3 and MET evaluation when monitoring patient reponse to cetuximab. [ABSTRACT FROM AUTHOR]

Liz Cohen is a partner at London law firm Bristows LLP, where she specialises in intellectual property matters with a particular focus on patent litigation. Her expertise lies in advising and representing businesses operating in the life sciences sector. Laura Peirson is a trainee in the IP Litigation practice of Bristows LLP.Patent laws in most European countries include an ‘experimental use’ exemption which permits the use of a patented invention for experimental purposes without infringing the rights of the patent holder. However, the legislation in this area varies throughout the EU according to how it has been implemented and subsequently interpreted by the national courts. This has led to uncertainty for companies operating in the pharmaceutical and biotech industries across Europe, due to the varying extent to which their activities can fall within the exemption in different Member States.More recently, experimental use in the life sciences sector has also been exempt from infringement if it is carried out to gain regulatory authorisation for generic products (the ‘EU Bolar‘ exemption). Since its introduction into UK law, the EU Bolar exemption has been the subject of a series of consultations, largely due to the UK’s relatively narrow implementation of the exemption and, in particular, the exclusion of innovative drugs from its protection. Consequently, the UK IPO is now proposing to amend the legislation to broaden the scope of the exemption.This article considers the issues surrounding the consultations and the plans to amend the Patents Act 1977 to expand the existing EU Bolar exemption. [ABSTRACT FROM PUBLISHER]

O-Linked β-N-acetylglucosamine (O-GlcNAc) glycosylation is a regulatory post-translational modification occurring on the serine or threonine residues of nucleocytoplasmic proteins. O-GlcNAcylation is dynamically regulated by O-GlcNAc transferase and O-GlcNAcase (OGA), which are responsible for O-GlcNAc addition and removal, respectively. Although O-GlcNAcylation was found to play a significant role in several pathologies such as type II diabetes and neurodegenerative diseases, the role of O-GlcNAcylation in the etiology and progression of cancer remains vague. Here, we followed O-GlcNAcylation and its catalytic machinery in metastatic clones of human colorectal cancer and the effect of OGA knockdown on cellular phenotype and on the transcriptome. The colorectal cancer SW620 metastatic clone exhibited increased O-GlcNAcylation and decreased OGA expression compared with its primary clone, SW480. O-GlcNAcylation elevation in SW620 cells, through RNA interference of OGA, resulted in phenotypic alterations that included acquisition of a fibroblastlike morphology, which coincides with epithelial metastatic progression and growth retardation. Microarray analysis revealed that OGA silencing altered the expression of about 1300 genes, mostly involved in cell movement and growth, and specifically affected metabolic pathways of lipids and carbohydrates. These findings support the involvement of O-GlcNAcylation in various aspects of tumor cell physiology and suggest that this modification may serve as a link between metabolic changes and cancer. [ABSTRACT FROM AUTHOR]

Background: Medical image segmentation is a well-studied subject within the field of image processing. The goal of this research is to create an AI retinal screening grading system that is both accurate and fast. We introduce a new segmentation network which achieves state-of-the-art results on semantic segmentation of colour fundus photographs. By applying the network to identify anatomical markers of diabetic retinopathy (DR) and diabetic macular edema (DME) including: micro-aneurysms, haemorrhages, etc., we collect sufficient information to classify patients into R0 (no DR) and R1 or above (DR), as well as M0 (no DME) and M1 (DME). Methods: The AI grading system was trained on public and private screening data to evaluate the presence of DR and DME. The system's core algorithm is a novel deep learning segmentation network (W-net) that locates and segments relevant anatomical features in a retinal image. Both eyes of the patients are graded individually, based on the detected features and classified according to the standard feature-based grading protocol used in the NHS Diabetic Eye Screening Programme. Results: The algorithm performance was evaluated with a series of patient retinal images from routine diabetic eye screenings and achieved state-of-the-art results. It correctly predicted 98% of retinopathy events (95% confidence interval [CI], 97.1-98.8) and 68.9% of maculopathy events (95% CI, 58.1-79.7). Non-disease events prediction rate was 68.6% for retinopathy and 81.3% for maculopathy. Conclusion: This novel deep learning segmentation model trained on a colour fundus photograph data set and tested on patient data from annual diabetic retinopathy screenings can detect and classify with high accuracy the DR and DME status of a person with diabetes. The system can be easily reconfigured according to any grading protocol, without starting a long AI training procedure. The incorporation of the AI grading system can increase the graders' productivity and improve the final outcome of the screening process. Disclosure: O. Katz: Employee; Self; NECAM, Research Support; Self; Northgate Public Services. D. Presil: Employee; Self; NECAM, Research Support; Self; Northgate Public Services. L. Cohen: Employee; Self; NECAM, Research Support; Self; Northgate Public Services. R. Nachmani: Employee; Self; NECAM, Research Support; Self; Northgate Public Services. N. Kirshner: Employee; Self; NEC, Research Support; Self; Northgate Public Service. D. R. Owens: Advisory Panel; Self; 360 Consulting. T. H. Lev: Employee; Self; NECAM (NEC Corporation of America), Research Support; Self; Northgate Public Services. A. Hadad: Consultant; Self; Necam. [ABSTRACT FROM AUTHOR]

Background: Medical image segmentation is a well-studied subject within the field of image processing. The goal of this research is to create an AI retinal screening grading system that is both accurate and fast. We introduce a new segmentation network which achieves state-of-the-art results on semantic segmentation of color fundus photographs. By applying the net-work to identify anatomical markers of diabetic retinopathy (DR) and diabetic macular edema (DME), we collect sufficient information to classify patients by grades R0 and R1 or above, M0 and M1., Methods: The AI grading system was trained on screening data to evaluate the presence of DR and DME. The core algorithm of the system is a deep learning network that segments relevant anatomical features in a retinal image. Patients were graded according to the standard NHS Diabetic Eye Screening Program feature-based grading protocol., Results: The algorithm performance was evaluated with a series of 6,981 patient retinal images from routine diabetic eye screenings. It correctly predicted 98.9% of retinopathy events and 95.5% of maculopathy events. Non-disease events prediction rate was 68.6% for retinopathy and 81.2% for maculopathy., Conclusion: This novel deep learning model was trained and tested on patient data from annual diabetic retinopathy screenings can classify with high accuracy the DR and DME status of a person with diabetes. The system can be easily reconfigured according to any grading protocol, without running a long AI training procedure. The incorporation of the AI grading system can increase the graders' productivity and improve the final outcome accuracy of the screening process.

A form of unified patent protection has been available in Europe since the 1970s, but enforcement remains purely a national matter. After many years' negotiation, an agreement was signed in February 2013 to create a pan-European court (the UPC), potentially affecting global litigation strategies. A constitutional complaint brought in Germany in 2017 has delayed the project and potentially presents an existential challenge, but more likely the issue is how much further delay it will cause. It remains entirely possible the UPC will start in Q1 2019 (before Brexit). In addition, for patentees such as pharmaceutical companies requiring broad geographic protection, another part of the new system, the unitary patent, would also mean a dramatic reduction in patent maintenance costs.

The skilled person is a concept central to patent law, underpinning the analysis of obviousness, sufficiency, claim construction, novelty, added matter and priority. Identifying such a person correctly, particularly the level of skill and the common general knowledge that they should possess, is critical to determining whether a patent is valid and/or infringed and has significant implications for the pharmaceutical industry. However, the concept can be difficult to define. Once referred to as 'The man on the Clapham omnibus' of patent law, the skilled person is a technician who is skilled in the art yet wholly devoid of imagination. Nevertheless, his attributes and knowledge, which are context-dependent and vary from art to art, are continually evolving. This article will look at the evolution of the skilled person, focusing on the implications for the future of pharmaceutical patents and patent litigation.