Exome sequencing links the SUMO protease SENP7 with fatal arthrogryposis multiplex congenita, early respiratory failure and neutropenia.

BACKGROUND: SUMOylation involves the attachment of small ubiquitin-like modifier (SUMO) proteins to specific lysine residues on thousands of substrates with target-specific effects on protein function. Sentrin-specific proteases (SENPs) are proteins involved in the maturation and deconjugation of SUMO. Specifically, SENP7 is responsible for processing polySUMO chains on targeted substrates including the heterochromatin protein 1α (HP1α). METHODS: We performed exome sequencing and segregation studies in a family with several infants presenting with an unidentified syndrome. RNA and protein expression studies were performed in fibroblasts available from one subject. RESULTS: We identified a kindred with four affected subjects presenting with a spectrum of findings including congenital arthrogryposis, no achievement of developmental milestones, early respiratory failure, neutropenia and recurrent infections. All died within four months after birth. Exome sequencing identified a homozygous stop gain variant in SENP7 c.1474C>T; p.(Gln492*) as the probable aetiology. The proband's fibroblasts demonstrated decreased mRNA expression. Protein expression studies showed significant protein dysregulation in total cell lysates and in the chromatin fraction. We found that HP1α levels as well as different histones and H3K9me3 were reduced in patient fibroblasts. These results support previous studies showing interaction between SENP7 and HP1α, and suggest loss of SENP7 leads to reduced heterochromatin condensation and subsequent aberrant gene expression. CONCLUSION: Our results suggest a critical role for SENP7 in nervous system development, haematopoiesis and immune function in humans.

SipNose-topiramate: a potential novel approach to binge eating management.

BACKGROUND: Binge-eating disorder) BED) is the most common eating disorder in the United-States. Daily, orally administered topiramate has shown BED treatment efficacy, with two major limitations: frequent and severe side effects and slow time-to-effect. SipNose is a novel non-invasive intranasal direct nose-to-brain drug delivery platform that delivers drugs to the central nervous system consistently and rapidly. Herein, we study a SipNose-topiramate combination product, as an acute "as needed" (PRN) solution for BED management. METHODS: First, SipNose-topiramate's pharmacokinetics (PK) and safety was evaluated. The second part aimed to demonstrate its PRN-treatment feasibility in terms of usability and potential efficacy in reducing the number of binge-eating events. Twelve BED patients were studied over three time periods; 2-weeks of baseline monitoring [BL], 8-weeks of treatment [TX], and 2-weeks of follow up [FU]. RESULTS: The PK profile showed peak plasma levels at 90 min post-administration, a t1/2 > 24 h and consistent topiramate delivery with no adverse events. In the second part, 251 treatments were self-administered by the patient participants. There was a significant reduction from baseline to treatment periods in mean weekly binge-eating events and binge-eating event days per week. This was maintained during the follow up period. Efficacy was corroborated by improved patient illness severity scales. There were no adverse events associated with any administered treatments. Patients were exposed to less drug when compared with accepted oral dosing. CONCLUSIONS: This study introduces a SipNose-topiramate drug-device combination as a potentially safe, effective, and controlled method for BED management. Its findings introduce a potential approach to BED management both as an intranasal and as a PRN therapy for reducing binge-eating events, with a large-scale reduction in patient drug exposure and side effects and with improved patient quality of life. Further studies are needed with larger patient populations to establish SipNose-topiramate as a mainstream treatment for BED. TRIAL REGISTRATION: Registration number and date of registration of the clinical studies reported in this article are as follows: 0157-18-HMO, August 15th 2018 and 6814-20-SMC, December 2nd 2020.

Binge eating disorder (BED) is a common eating disorder. Daily oral topiramate treatment has shown efficacy in clinical studies and off-label use, with frequent and severe side effects. SipNose is a novel, rapid and consistent direct nose-to-brain drug delivery platform. This study evaluates a SipNose-topiramate combination product, as an innovative acute "as needed" (PRN) BED treatment solution. SipNose-topiramate's pharmacokinetics (PK) and safety demonstrated consistent, dose-dependent topiramate delivery with no adverse events. SipNose-topiramate was studied vis-à-vis its safety and feasibility as a PRN-treatment for reducing the number of binge-eating events. 12 BED patients were studied (2-weeks baseline monitoring, 8-weeks treatment, 2-weeks follow-up). Patients were instructed to self-administer the drug when they feel an urge to binge-eat. Two hundred fifty-one treatments were administered. When compared with daily oral dosing, lower doses were used with no adverse events and minimal side effects. Baseline to treatment periods showed significant reduction in mean weekly binge-eating events and binge-eating event days-per-week. This was maintained during follow-up. Improved illness severity scales corroborated the improved feasibility outcomes. In conclusion, this study introduces SipNose-topiramate as a potential "as needed" intranasal treatment for BED that is safe, effective, and reduces drug exposure and side effects. Additional studies are needed to validate SipNose-topiramate as a BED management therapy.

Validation of the Algorithmic Prediction of Failure Modes in Health Care Methodology: Applied to the Department of Sterile Supply and Equipment.

Failure mode and effect analysis (FMEA) is a leading tool for risk management in health care. The term "blanket" approach FMEA describes a comprehensive simultaneous look at the variety of interrelated factors that may directly and indirectly affect patient safety. Applying FMEA with the "blanket" approach is not common, due to FMEA's limitations. Algorithmic prediction of failure modes in health care (APFMH) is leaner and enables the application of the "blanket" approach, but, like FMEA, it lacks formal validation. The authors set out to validate the APFMH method while applying a "blanket" approach. They analyzed the sterile supply handling at a 1900-bed academic medical center. The study's first step took place in the operating room (OR) aspect of the process. An APFMH analysis was performed using the "blanket" approach, to identify the hazards and define the common root causes for predicted hazards. The second step took place a year later at the sterile supply and equipment department (SSED) and aimed to validate these root causes, thus validating the reliability of APFMH. The "blanket" approach analysis with the APFMH method consisted of categorization into 3 risk-dimensions: patient safety, equipment damage, and time management. Root causes were defined for 8 high-ranking hazards. All the root causes for failures, identified by APFMH at the OR department, were revealed as actual hazards in the processes of the SSED. The independent findings at the SSED level validated the list of identified hazards that was formed at the target department (ie, the OR). APFMH methodology is a lean in time and human resources process that ensures comprehensive hazard analysis, which can include the "blanket" approach, and which was validated in this study. The authors suggest using the APFMH methodology for any organizational analysis method that requires the inclusion of "blanket" approaches.

A non-invasive direct nose to brain drug delivery platform vs. invasive brain delivery approach: patient-centered care impact analysis.

Current literature lacks structured methodologies for analyzing medical technologies' impact from the patient-centered care perspective. This study introduces, applies and validates 'Patient-Centered Care Impact Analysis' (PCIA) as a method for identifying patient-centered care associated demands and expectations for a particular technology and assessing its compliance with these demands. PCIA involves five stages: (1) demand identification, (2) ranking demands' impact magnitude, (3) scoring demand compliance (DC), (4) demand priority (DP) assignment based on impact magnitude and compliance, (5) generating a summative impact priority number (IPN). PCIA was performed as a comparative assessment of two central nervous system (CNS) drug-delivery platforms; SipNose, a novel noninvasive Direct-Nose-to-Brain (DNTB), vs. the standard-of-care invasive intrathecal/intracerebroventricular injection (Invasive I/I). Study participants included a ranking team (RT) without experience with the SipNose technology that based their scoring on experimental data; and a validation team (VT) experienced with the SipNose platform. All had experience with, or knowledge of, InvasiveI/I. Demand identification and impact magnitude were performed by one content and one assessment expert. Each participant assessed each technology's DC. DP scores, IPN's and IPN DNTB:InvasiveI/I ratios were generated for each technology, for each team, based on DC and summative DP scores, respectively. Both teams assigned DNTB higher DC scores, resulting in higher DNTB DP, IPN scores and DNTB:InvasiveI/I IPN ratios. Lack of difference between team assessments of DP and IPN ratio validate PCIA as an assessment tool capable of predicting patient-centered clinical care quality for a new technology. The significant differences between the platforms highlight SipNose's patient-care centered advantages as an effective CNS drug-delivery platform.

Detection of SARS-CoV-2 infection by exhaled breath spectral analysis: Introducing a ready-to-use point-of-care mass screening method.

BACKGROUND: The current SARS-CoV-2 pandemic created an urgent need for rapid, infection screening applied to large numbers of asymptomatic individuals. To date, nasal/throat swab polymerase chain reaction (PCR) is considered the "gold standard". However, this is inconducive to mass, point-of-care (POC) testing due to person discomfort during sampling and a prolonged result turnaround. Breath testing for disease specific organic compounds potentially offers a practical, rapid, non-invasive, POC solution. The study compares the Breath of Health, Ltd. (BOH) breath analysis system to PCR's ability to screen asymptomatic individuals for SARS-CoV-2 infection. The BOH system is mobile and combines Fourier-transform infrared (FTIR) spectroscopy with artificial intelligence (AI) to generate results within 2 min and 15 s. In contrast to prior SARS-CoV-2 breath analysis research, this study focuses on diagnosing SARS-CoV-2 via disease specific spectrometric profiles rather than through identifying the disease specific molecules. METHODS: Asymptomatic emergency room patients with suspected SARS-CoV-2 exposure in two leading Israeli hospitals were selected between February through April 2021. All were tested via nasal/throat-swab PCR and BOH breath analysis. In total, 297 patients were sampled (mean age 57·08 ± SD 18·86, 156 males, 139 females, 2 unknowns). Of these, 96 were PCR-positive (44 males, 50 females, 2 unknowns), 201 were PCR-negative (112 males, 89 females). One hundred samples were used for AI identification of SARS-CoV-2 distinguishing spectroscopic wave-number patterns and diagnostic algorithm creation. Algorithm validation was tested in 100 proof-of-concept samples (34 PCR-positive, 66 PCR-negative) by comparing PCR with AI algorithm-based breath-test results determined by a blinded medical expert. One hundred additional samples (12 true PCR-positive, 85 true PCR-negative, 3 confounder false PCR-positive [not included in the 297 total samples]) were evaluated by two blinded medical experts for further algorithm validation and inter-expert correlation. FINDINGS: The BOH system identified three distinguishing wave numbers for SARS-CoV-2 infection. In the first phase, the single expert identified the first 100 samples correctly, yielding a 1:1 FTIR/AI:PCR correlation. The two-expert second-phase also yielded 1:1 FTIR/AI:PCR correlation for 97 non-confounders and null correlation for the 3 confounders. Inter-expert correlation was 1:1 for all results. In total, the FTIR/AI algorithm demonstrated 100% sensitivity and specificity for SARS-CoV-2 detection when compared with PCR. INTERPRETATION: The SARS-CoV-2 method of breath analysis via FTIR with AI-based algorithm demonstrated high PCR correlation in screening for asymptomatic individuals. This is the first practical, rapid, POC breath analysis solution with such high PCR correlation in asymptomatic individuals. Further validation is required with a larger sample size. FUNDING: Breath of Health Ltd, Rehovot, Israel provided study funding.

Perceived reliability of medical device alarms-a major determinant of medical errors driven by frozen medical thinking.

This concept paper introduces the phenomenon of self-assigning a 'perceived reliability' value to medical device readings as a potential source of cognitive bias in medical decision-making. Medical errors can result from clinical decisions based on partial clinical data despite medical device readings providing data to the contrary. At times, this results from clinician distrust of medical device output. Consequentially, clinicians engage in a form of 'frozen thinking', a fixation on a particular thought process despite data to the contrary. Many medical devices, such as intensive care unit (ICU) monitors and alarms, lack validated statistics of device output reliability and validity. In its absence, clinicians assign a self-perceived reliability value to device output data and base clinical decisions therefrom. When the perceived reliability value is low, clinicians distrust the device and ignore device readings, especially when other clinical data are contrary. We explore the cognitive and theoretical underpinnings of this 'perceived reliability' phenomenon. The mental assignment of a perceived reliability value stems from principles of 'script theory' of medical decision-making. In this conceptual framework, clinicians make decisions by comparing current situations to mental 'scripts' of prior clinical decisions and their outcomes. As such, the clinician utilizes scripts of prior experiences to create the perceived reliability value. Self-assigned perceived reliability is subject to multiple dangers of reliability and cognitive biases. Some of these biases are presented. Among these is the danger of dismissing device readings as 'noise'. This is particularly true of ICU alarms that can emit frequent false alarms and contribute to clinician sensory overload. The cognitive dangers of this 'noise dismissal' are elaborated via its similarity to the phenomenon of 'spatial disorientation' among aviation pilots. We conclude with suggestions for reducing the potential bias of 'perceived reliability'. First presented are regulatory/legislative and industry-based interventions for increasing the study of, and end-user access to, validated device output reliability statistics. Subsequently, we propose strategies for overcoming and preventing this phenomenon. We close with suggestions for future research and development of this 'perceived reliability' phenomenon.

Impact of the final adjective in the Medical Student Performance Evaluation on determination of applicant desirability.

BACKGROUND: The Medical Student Performance Evaluation (MSPE) is a primary source of information used by residency programs in their selection of trainees. The MSPE contains a narrative description of the applicant's performance during medical school. In 2002, the Association of American Medical Colleges' guideline for preparation of the MSPE recommended inclusion of a comparative summative assessment of the student's overall performance relative to his/her peers (final adjective). OBJECTIVE: We hypothesize that the inclusion of a final adjective in the MSPE affects a reviewer's assessment of the applicant's desirability more than the narrative description of performance and designed a study to evaluate this hypothesis. DESIGN: Fifty-six faculty members from the Departments of Pediatrics and Medicine with experience reviewing MSPEs as part of the intern selection process reviewed two pairs of mock MSPE letters. In each pair, the narrative in one letter was superior to that in the other. Two final adjectives describing relative class ranks were created. Each subject was first presented with a pair of letters with mismatched final adjective (study), i.e., the letter with the stronger narrative was presented with the weaker final adjective and vice versa. The subject was then presented with a second pair of letters without final adjectives (control). Subjects ranked the relative desirability of the two applicants in each pair. RESULTS: The proportion of rankings congruent with the strength of the narratives under study and control conditions were compared. Subjects were significantly less likely to rank the applicants congruent with the strength of the narratives when the strength of the final adjectives conflicted with the strength of the narrative; 42.9% of study letters were ranked congruent with the narrative versus 82.1% of controls (p = 0.0001). CONCLUSION: The MSPE final adjective had a greater impact than the narrative description of performance on the determination of applicant desirability. ABBREVIATIONS: MSPE: Medical Student Performance Evaluation; AAMC: Association of American Medical Colleges; BCM: Baylor College of Medicine.