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Competing Interests: Declaration of interests No funding was provided specifically for this Commission paper; however, most authors are involved in the International Initiative for Traumatic Brain Injury Research (InTBIR) as a scientific participant or an investigator. This Commission would not have been possible without the indirect facilitation provided by the InTBIR network. AIRM declares consulting fees from PresSura Neuro, Integra Life Sciences, and NeuroTrauma Sciences. DKM reports research support, and educational and consulting fees from Lantmannen AB, GlaxoSmithKline, Calico, PresSura Neuro, NeuroTrauma Sciences, and Integra Neurosciences. GTM declares grants from the US National Institutes of Health-National Institute of Neurological Disorders and Stroke (grant U01NS086090), the US Department of Defense (grant W81XWH-14-2-0176, grant W81XWH-18-2-0042, and contract W81XWH-15-9-0001). MC reports licensing fees for ICM+ software from Cambridge Enterprise and was an honorary (unpaid) director for Medicam. PS reports licensing fees for ICM+ software from Cambridge Enterprise. MBS has in the past 3 years received consulting income from Acadia Pharmaceuticals, Aptinyx, atai Life Sciences, Boehringer Ingelheim, Bionomics, BioXcel Therapeutics, Clexio, Eisai, EmpowerPharm, Engrail Therapeutics, Janssen, Jazz Pharmaceuticals, and Roche/Genentech. MBS also has stock options in Oxeia Biopharmaceuticals and EpiVario and is paid for editorial work on Depression and Anxiety (Editor-in-Chief), Biological Psychiatry (Deputy Editor), and UpToDate (Co-Editor-in-Chief for Psychiatry). KKWW holds stock options in Gryphon Bio. All other authors declare no competing interests.

The placebo response is a highly complex psychosocial-biological phenomenon that has challenged drug development for decades, particularly in neurological and psychiatric disease. While decades of research have aimed to understand clinical trial factors that contribute to the placebo response, a comprehensive solution to manage the placebo response in drug development has yet to emerge. Advanced data analytic techniques, such as artificial intelligence (AI), might be needed to take the next leap forward in mitigating the negative consequences of high placebo-response rates. The objective of this review was to explore the use of techniques such as AI and the sub-discipline of machine learning (ML) to address placebo response in practical ways that can positively impact drug development. This examination focused on the critical factors that should be considered in applying AI and ML to the placebo response issue, examples of how these techniques can be used, and the regulatory considerations for integrating these approaches into clinical trials., Competing Interests: DISCLOSURES: Drs. Smith and Demolle are employees of Cognivia, which develops commercial placebo prediction products. Dr. Horan is a full-time employee of VeraSci. Dr. Fu is an employee of Janssen Research and Development, LLC, and is a stockholder of Johnson & Johnson, Inc. Dr. Geraci is a significant shareholder of NetraMark Corp. and is an employee of Nurosene Health, Inc., which develops commercial placebo prediction products. Ms. Link is an employee of Boehringer Ingelheim International GmbH but did not receive any direct compensation relating to the development of this manuscript. Dr. Alphs is an employee of and has stock in Newron Pharmaceuticals and has stock in Johnson & Johnson, Inc., (Copyright © 2022. Matrix Medical Communications. All rights reserved.)

Single-molecule localization microscopy (SMLM) has revolutionized optical microscopy, extending resolution down to the level of individual molecules. However, the actual counting of molecules relies on preliminary knowledge of the blinking behavior of individual targets or on a calibration to a reference. In particular for biological applications, great care has to be taken because a plethora of factors influence the quality and applicability of calibration-dependent approaches to count targets in localization clusters particularly in SMLM data obtained from heterogeneous samples. Here, we present localization-based fluorescence correlation spectroscopy (lbFCS) as the first absolute molecular counting approach for DNA-points accumulation for imaging in nanoscale topography (PAINT) microscopy and, to our knowledge, for SMLM in general. We demonstrate that lbFCS overcomes the limitation of previous DNA-PAINT counting and allows the quantification of target molecules independent of the localization cluster density. In accordance with the promising results of our systematic proof-of-principle study on DNA origami structures as idealized targets, lbFCS could potentially also provide quantitative access to more challenging biological targets featuring heterogeneous cluster sizes in the future.

The increasing miniaturization and affordability of sensors and circuitry has led to the current level of innovation in the area of wearable and microsensor solutions for health monitoring. This facilitates the development of solutions that can be used to measure complex health outcomes in nonspecialist and remote settings. In this article, we review a number of innovations related to brain monitoring including portable and wearable solutions to directly measure brain electrical activity, and solutions measuring aspects related to brain function such as sleep patterns, gait, cognition, voice acoustics, and gaze analysis. Despite the need for more scientific validation work, we conclude that there is enough understanding of how to implement these approaches as exploratory tools that may provide additional valuable insights due to the rich and frequent data they produce, to justify their inclusion in clinical study protocols., (© 2018 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.)

The ability to detect individuals at high risk for developing schizophrenia before they express the disease will lead to targeted early intervention. It has been proposed that subjects at risk share a core deficit with people who already have schizophrenia. This includes cognitive impairment, affective symptoms, social isolation and decline in social functioning. In a sample of 104 help-seeking patients from a specialised outpatient clinic we investigated how well two different sets of criteria define the at-risk group and capture this core deficit. One set of criteria is the well-established ultra high-risk model of McGlashan et al. [McGlashan 2001 (SIPS) McGlashan, T. H., Miller, T. J., Woods, S. W., et al. (2001) Structured Interview for Prodromal Syndromes (Version 3.0, unpublished manuscript). New Haven, Connecticut: PRIME Research Clinic, Yale School of Medicine.]; the other criteria were those defined by Cornblatt et al. [Cornblatt, B., Lencz, T., Smith, C.W., Correll, C.U., Auther, A., Nakayama, E., 2003. The schizophrenia prodrome revisited: a neurodevelopmental perspective. Schizophr. Bull. 29, 633-651.]. There was considerable overlap in the two sets of criteria. However, when the basic symptoms of Klosterkötter [Klosterkötter, J., Hellmich, M., Steinmeyer, E.M., Schultze-Lutter, F., 2001a. Diagnosing schizophrenia in the initial prodromal phase. Arch. Gen. Psychiatry, 58, 158-164.] were included in the McGlashan et al. model, a more narrow and homogeneous group was defined.

The tetracyclic ergoline derivative cabergoline was investigated in three studies to test its efficacy in treating the motor symptoms of Parkinson's disease. In two studies, it was used as an add-on agent to the previous medication regimen that included other parkinsonian drugs, including levodopa. In the third study, cabergoline was switched from another dopamine agonist. All studies proved this drug's effectiveness in treating such motor symptoms as akinesia, dyskinesia, and nocturnal akinesia. Quality of life and disability in activities of daily living assessments were measured by PDQ 39 or UPDRS VI. Treatment with cabergoline showed higher efficacy and greater safety than other parkinsonian drugs., (Copyright 2001 S. Karger AG, Basel)