Colorectal cancer remains a leading source of cancer mortality worldwide. Initial response is often followed by emergent resistance that is poorly responsive to targeted therapies, reflecting currently undruggable cancer drivers such as KRAS and overall genomic complexity. Here, we report a novel approach to developing a personalized therapy for a patient with treatment-resistant metastatic KRAS-mutant colorectal cancer. An extensive genomic analysis of the tumor’s genomic landscape identified nine key drivers. A transgenic model that altered orthologs of these nine genes in the Drosophila hindgut was developed; a robotics-based screen using this platform identified trametinib plus zoledronate as a candidate treatment combination. Treating the patient led to a significant response: Target and nontarget lesions displayed a strong partial response and remained stable for 11 months. By addressing a disease’s genomic complexity, this personalized approach may provide an alternative treatment option for recalcitrant disease such as KRAS-mutant colorectal cancer.

The grape is one of the most valued conventional fruits, worldwide. Although most of the parts of the grapevine are useful, primarily, the grape is considered as a source of unique natural products not only for the development of valuable medicines against a number of diseases, but also for manufacturing various industrial products. Over the last few decades, apart from the chemistry of grape compounds, considerable progress has been made towards exploring the biological activities of various grape-derived constituents. Today, it is well established that in addition to serving as food, the grape is a major source of several phytochemicals. The main biologically active and well-characterized constituent from the grape is resveratrol, which is known for various medicinal properties in human diseases. This review discusses the roles of various grape-derived phytochemicals in relation to various diseases.

The last few years have produced a revolution in the development of very sensitive, rapid, automated, molecular detection methods for a variety of various species of lactic acid bacteria (LAB) associated with food and dairy products. Nowadays many such strains of LAB are considered probiotics. The genome-based methods are useful in identifying bacteria as a complementary or alternative tool to phenotypical methods. Over the years, identification methodologies using primers that target different sequences, such as the 16S ribosomal RNA (rRNA)-encoding gene, the 16S-23S rRNA intergenic spacer region, the 23S rRNA-encoding, recA and ldhD genes; randomly amplified polymorphic DNA, restriction fragment length polymorphism, denaturing gradient gel electrophoresis, temperature gradient gel electrophoresis, amplification rDNA restriction analysis, restriction enzyme analysis, rRNA, pulse field gel electrophoresis and amplification fragment length polymorphism have played a significant role in probiotic bacteriology. Hence, the aim of this review is to provide an overview of some rapid and reliable polymerase chain reaction-based molecular methods used for identifying and differentiating closely related species and strains of LAB associated with food and industry.

To the Editor: Although Yuki and Hartung mention that toxic neuropathy should be included in the differential diagnosis of the Guillain-Barré syndrome, they do not discuss the particular toxicities that should be considered. Specifically, arsenic neurotoxicity, often characterized by an ascending, symmetrical, sensorimotor neuropathy, strongly resembles the Guillain-Barré syndrome and should be specifically ruled out in all applicable cases. 1 The best specimen to test for recent arsenic exposure is a 24-hour urine collection (in a metal-free container) for arsenic and creatinine. Measuring both arsenic and creatinine allows for more accurate determination of arsenic excretion. It is important to remember that arsenic testing can be confounded by certain dietary sources (especially seafood eaten within a week of testing). When test results are in doubt, clinicians should request speciation of arsenic (i.e., analysis of organoarsenicals and inorganic species, rather than total arsenic). 2

87 Background: New York City was the epicenter of the COVID-19 pandemic. Public concern about exposure and policies to “flatten the curve” led to abrupt curtailment of health care service use, including cancer. Innovative strategies to mitigate the disruption, including telemedicine, was utilized. However, this may be less accessible to minority populations. We evaluated the differences in telehealth use among minorities and non-minorities with cancer. Methods: Our health system includes an NCI designated cancer center and 8 ambulatory sites across New York City. Utilizing the electronic medical record (EMR) we collected data on all cancer patients with an in-person or telehealth visit during the peak of the pandemic from March 1, 2020 to June 1, 2020. Race/ethnicity and visit type data was collected from the EMR. Telehealth includes video visits and telephone encounters. We used ANOVA and-chi square where appropriate to identify differences between the racial and ethnic groups in terms of use and type of telehealth and compared any differences to baseline cancer center demographics. Results: There were a total of 7,681 telehealth visits during 3/1/2020-6/1/2020; 76% were video visits. At baseline in 2019, < 1% of all patient visits were conducted via telehealth. Within our cancer center our demographic breakdown for patients seen in 2019 includes 42% patients were white, 23% Black, 14% Hispanic and 7% Asian. Among those patients utilizing video visits, 50% patients were white, 17% Black, 8% Asian, and 5% Hispanic. Among those patients utilizing phone encounters, 43% patients were white, 23% Black, 7% Hispanic and 6% Asian. Conclusions: During the COVID-19 pandemic our utilization of telehealth increased exponentially. There were significant disparities observed in the use of telehealth with Black, Hispanic and Asian patients having less utilization. These findings are important as telehealth use will now become more integrated into standard oncologic care, and it is likely that we will have a second or third wave of COVID-19 infections. Future work to understand the determinants of these disparities and interventions are needed. [Table: see text]