Academic literature on the topic 'Pitchbook'

Background Advancements in technology offer new opportunities for the prevention and management of type 2 diabetes. Venture capital companies have been investing in digital diabetes companies that offer digital behavior change interventions (DBCIs). However, little is known about the scientific evidence underpinning such interventions or the degree to which these interventions leverage novel technology-driven automated developments such as conversational agents (CAs) or just-in-time adaptive intervention (JITAI) approaches. Objective Our objectives were to identify the top-funded companies offering DBCIs for type 2 diabetes management and prevention, review the level of scientific evidence underpinning the DBCIs, identify which DBCIs are recognized as evidence-based programs by quality assurance authorities, and examine the degree to which these DBCIs include novel automated approaches such as CAs and JITAI mechanisms. Methods A systematic search was conducted using 2 venture capital databases (Crunchbase Pro and Pitchbook) to identify the top-funded companies offering interventions for type 2 diabetes prevention and management. Scientific publications relating to the identified DBCIs were identified via PubMed, Google Scholar, and the DBCIs’ websites, and data regarding intervention effectiveness were extracted. The Diabetes Prevention Recognition Program (DPRP) of the Center for Disease Control and Prevention in the United States was used to identify the recognition status. The DBCIs’ publications, websites, and mobile apps were reviewed with regard to the intervention characteristics. Results The 16 top-funded companies offering DBCIs for type 2 diabetes received a total funding of US $2.4 billion as of June 15, 2021. Only 4 out of the 50 identified publications associated with these DBCIs were fully powered randomized controlled trials (RCTs). Further, 1 of those 4 RCTs showed a significant difference in glycated hemoglobin A1c (HbA1c) outcomes between the intervention and control groups. However, all the studies reported HbA1c improvements ranging from 0.2% to 1.9% over the course of 12 months. In addition, 6 interventions were fully recognized by the DPRP to deliver evidence-based programs, and 2 interventions had a pending recognition status. Health professionals were included in the majority of DBCIs (13/16, 81%,), whereas only 10% (1/10) of accessible apps involved a CA as part of the intervention delivery. Self-reports represented most of the data sources (74/119, 62%) that could be used to tailor JITAIs. Conclusions Our findings suggest that the level of funding received by companies offering DBCIs for type 2 diabetes prevention and management does not coincide with the level of evidence on the intervention effectiveness. There is considerable variation in the level of evidence underpinning the different DBCIs and an overall need for more rigorous effectiveness trials and transparent reporting by quality assurance authorities. Currently, very few DBCIs use automated approaches such as CAs and JITAIs, limiting the scalability and reach of these solutions.

Context:There are contradictory data on optimal muscle-activation strategies for restoring shoulder stability. Further investigation of neuromuscular-control strategies for glenohumeral-joint stability will guide clinicians in decisions regarding appropriate rehabilitation exercises.Objectives:To determine whether subscapularis, infraspinatus, and teres minor (anteroposterior force couple) muscle activation differ between 4 shoulder exercises and describe coactivation ratios and individual muscle-recruitment characteristics of rotator-cuff muscles throughout each shoulder exercise.Design:Crossover.Setting:Laboratory.Participants:healthy, physically active men, age 20.55 ± 2.0 y.Interventions:4 rehabilitation exercises: pitchback, PNF D2 pattern with tubing, push-up plus, and slide board.Main Outcomes Measures:Mean coactivation level, coactivation-ratio patterns, and level (area) of muscle-activation patterns of the subscapularis, infraspinatus, and teres minor throughout each exercise.Results:Coactivation levels varied throughout each exercise. Subscapularis activity was consistently higher than that of the infraspinatus and teres minor combined at the start of each exercise and in end ranges of motion. Individual muscle-recruitment levels in the subscapularis were also different between exercises.Conclusion:Results provide descriptive data for determining normative coactivation-ratio values for muscle recruitment for the functional exercises studied. Differences in subscapularis activation suggest a reliance to resist anteriorly directed forces.

AbstractAnimals use diverse solutions to land on vertical surfaces. Here we show the unique landing of the gliding gecko, Hemidactylus platyurus. Our high-speed video footage in the Southeast Asian rainforest capturing the first recorded, subcritical, short-range glides revealed that geckos did not markedly decrease velocity prior to impact. Unlike specialized gliders, geckos crashed head-first with the tree trunk at 6.0 ± 0.9 m/s (~140 body lengths per second) followed by an enormous pitchback of their head and torso 103 ± 34° away from the tree trunk anchored by only their hind limbs and tail. A dynamic mathematical model pointed to the utility of tails for the fall arresting response (FAR) upon landing. We tested predictions by measuring foot forces during landing of a soft, robotic physical model with an active tail reflex triggered by forefoot contact. As in wild animals, greater landing success was found for tailed robots. Experiments showed that longer tails with an active tail reflex resulted in the lower adhesive foot forces necessary for stabilizing successful landings, with a tail shortened to 25% requiring over twice the adhesive foot force.

Сьогодні стартапи вважають одним з індикаторів розвитку економіки. Бізнес-простір кожної країни оцінюють з точки зору успішності проектів, створених з нуля. Саме тому на особливу увагу заслуговує питання дослідження найбільш популярних напрямів реалізації стартапів та їх особливості формування та розвитку в Україні та за кордоном.

Historical analyses surrounding the size effect on private equity buyout fund performance have arrived at controversial conclusions in regard to both the certainty of significance and, given significance, the outperformance of one size group over another. The paper uses performance data of 1,914buyout funds spanning vintages 1995 to 2015, retrieved from Pitchbook, and summarizes a survey on investors’ beliefs, conducted in Autumn 2019.No significance for fund size in absolute dollar terms can be found. However, when size is classified in to quartiles and groups, ‘Small’ performs the best. This is robust for IRRs. Finally, investors tend to invest into smaller funds when the time horizon is longer, however, do not generally favor one specific size group.