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Abstract Aim Comprehensive genomic profiling (CGP) test for solid tumors is now increasingly utilized in clinical practice, especially in pancreatobiliary cancer, and specimens obtained by endoscopic ultrasound‐guided tissue acquisition (EUS‐TA) are often submitted for tissue‐based CGP test. In this study, we evaluated the feasibility of EUS‐TA using a 22‐gauge Franseen needle for the CGP test. Methods Consecutive patients with solid tumors who underwent EUS‐TA using a 22‐gauge Franseen needle, and whose tissue samples were pre‐checked for suitability for CGP test, were included in this single‐center, retrospective analysis. The success rates of appropriate sample collection for CGP evaluated by pathologists (1st quality control) and CGP test (2nd quality control) were evaluated. In addition, The EUS‐TA slides were evaluated for the tissue area and tumor area content, using the image software. Results A total of 50 cases, with 78% of pancreatic cancer, were included in the analysis. A median of 3 passes of EUS‐TA were performed with an adverse event rate of 4%. The success rates for 1st and 2nd quality control for CGP tests were 86% and 76%, respectively. The image analyses suggested EUS‐TA specimen did not always fulfill CGP test criteria, with 18% of tissue area ≥16 mm2 and 38% of tumor area content ≥20%, even in cases with successful CGP tests. The suction method yielded a significantly larger amount of DNA but without a significant difference in the multivariate analysis. Conclusions The present study demonstrated the feasibility of EUS‐TA using a 22‐gauge Franseen needle for CGP test.

Abstract Background Endoscopic ultrasound‐guided fine needle aspiration (EUS‐FNA) is widely used for the pathological diagnosis of solid pancreatic lesions but in cases with obstructive jaundice, transpapillary sampling can be performed during endoscopic retrograde cholangiopancreatography with transpapillary biliary stent placement. Thus, it is still controversial whether EUS‐FNA should be performed prior to endoscopic retrograde cholangiopancreatography with biliary stent placement or only after negative transpapillary sampling. Methods The accuracy, sensitivity, and specificity of EUS‐FNA for solid pancreatic lesions with or without indwelling biliary stents were retrospectively studied in patients undergoing EUS‐FNA between January 2017 and December 2021. We also conducted a meta‐analysis including our data to compare the accuracy and sensitivity of EUS‐FNA with or without biliary stents. Results A total of 509 patients (40 with biliary stents and 469 without biliary stents) were included. The accuracy (77.5% vs. 94.5%, p < 0.001) and sensitivity (71.0% vs. 91.7%, p < 0.001) were lower in EUS‐FNA with biliary stents. A meta‐analysis confirmed that accuracy (odds ratio [OR] of 0.43, 95% confidence interval [CI] 0.29–0.62, p < 0.001) and sensitivity (OR of 0.46, 95% CI 0.33–0.64, p < 0.001) were lower in EUS‐FNA with biliary stents. There were no statistically significant differences between plastic stents and self‐expandable metallic stents for accuracy or sensitivity. Conclusions The presence of biliary stents had a negative impact on the diagnostic performance of EUS‐FNA, and EUS‐FNA prior to endoscopic retrograde cholangiopancreatography with biliary stent placement should be considered in cases with obstructive jaundice.

While the past 50 years have been categorized as the Information or Digital Age, the mass amounts of digitized data has been sorely underutilized. It was only recently through the COVID-19 pandemic that accelerated efforts were sought to harness this data with the use of blockchain technology in healthcare. Through the infrastructure and its tokenization applications, we can now effectively leverage healthcare data into more efficient business processes, secure better patient engagement and outcomes all while generating new revenue streams for an array of healthcare stakeholders. It is in compiling this stockpiled data into new, compliant business models and utilizing blockchain technology that we can reap the full potential of this era. Here are some predictions as to how we might set about these efforts in 2023.

Background: Motor estimation error is an index of how accurately one’s body movement is recognized. This study determines whether motor estimation error distance is a Parkinson’s disease (PD)- or age-related disability using a two-step task. Methods: The participants were 19 PD patients and 58 elderly people with disabilities. A two-step prediction test and an actual two-step test were performed. The motor estimation error distance (prediction of two-step distance minus actual two-step distance) and error rate between the two groups were compared. We conducted a correlation analysis between the motor estimation error and clinical factor (e.g., Hoehn and Yahr stage (H & Y), Unified Parkinson’s Disease Rating Scale (UPDRS)) related to PD. Results: The motor estimation error distance was not significantly different between the PD patient group and the elderly group with disabilities. However, significant correlations between motor estimation error and H & Y, and between motor estimation error and UPDRS part II, were observed. The error rate was significantly correlated with the Fall Efficacy Scale. Conclusions: The motor estimation error distance is influenced by both aging and PD.

Visual stimuli without sharp edges fade gradually under visual fixation. This phenomenon is known as Troxler fading or fading illusion. Traditionally, this fading is explained by a hypothesis that physical stimulus is cancelled by a negative image generated in the visual pathway, because the negative image is perceived momentarily when the physical stimulus is removed suddenly. One prediction that may be tested neurophysiologically is that, in the faded or adapted state, visual neurons actually respond to a blank screen, as if they actually ‘see’ the negative image. To examine this prediction in cat V1, we measured the contrast response function of single neurons by presenting flashed grating stimuli of various contrasts (7 contrasts in straddle, ±25%, range and pedestal, within 0–50%, range; negative values for phase reversal) in a rapid succession. Data were analyzed using reverse correlation. The orientation and spatial frequency of gratings were fixed at the optimal value of each cell. We found that V1 neurons showed a shift of contrast response function during pedestal conditions to respond to a blank screen (i.e., 0% contrast stimulus). The amount of shift was consistent with the arithmetic mean of contrasts in each experimental condition. These results support the hypothesis that a negative image is generated during visual fading, and it behaves as if it were a real stimulus. Additionally, we examined phase retardation using periodic stimuli to investigate the temporal transition of contrast response functions. The time constant of phase retardation was comparable to that we observed perceptually.

Over the past 50 years, although categorized as the "Information Age" or "Digital Age," the vast amounts of digitized data have been sorely underutilized. Only recently, in response to the COVID-19 pandemic, efforts have accelerated to harness these data using blockchain technology as it pertains to healthcare. Today, through the blockchain infrastructure and its tokenization applications, we are able to leverage healthcare data effectively into more efficient business processes. In addition, we can secure better patient engagement and outcomes, while generating new revenue streams for an array of healthcare stakeholders. It is in the application of blockchain technology to compile these stockpiled data into new, compliant business models that we can reap the full potential of the blockchain. Here are predictions by members of the BHTY editorial board members on how we might further advance the role of blockchain in healthcare in 2023. [ABSTRACT FROM AUTHOR]