Use of Artificial Intelligence in Drug Development.

This cross-sectional study investigates the scope and breadth of artificial intelligence use in drug development.

Systematic enhancement of protein crystallization efficiency by bulk lysine-to-arginine (KR) substitution.

Structural genomics consortia established that protein crystallization is the primary obstacle to structure determination using x-ray crystallography. We previously demonstrated that crystallization propensity is systematically related to primary sequence, and we subsequently performed computational analyses showing that arginine is the most overrepresented amino acid in crystal-packing interfaces in the Protein Data Bank. Given the similar physicochemical characteristics of arginine and lysine, we hypothesized that multiple lysine-to-arginine (KR) substitutions should improve crystallization. To test this hypothesis, we developed software that ranks lysine sites in a target protein based on the redundancy-corrected KR substitution frequency in homologs. This software can be run interactively on the worldwide web at https://www.pxengineering.org/. We demonstrate that three unrelated single-domain proteins can tolerate 5-11 KR substitutions with at most minor destabilization, and, for two of these three proteins, the construct with the largest number of KR substitutions exhibits significantly enhanced crystallization propensity. This approach rapidly produced a 1.9 Å crystal structure of a human protein domain refractory to crystallization with its native sequence. Structures from Bulk KR-substituted domains show the engineered arginine residues frequently make hydrogen-bonds across crystal-packing interfaces. We thus demonstrate that Bulk KR substitution represents a rational and efficient method for probabilistic engineering of protein surface properties to improve crystallization.

Mysidopsis jenseni n. sp. from the Pacific coast of Washington, with first description of female M. intii Holmquist, 1957 (Crustacea: Mysida: Mysidae).

Mysidopsis jenseni n. sp. is described from the Puget Sound area, Washington, USA from sand/rocky bottoms in depths of 8 to 15 m. This new species increases the number of American Pacific species of Mysidopsis to eight. Based on a collection of M. intii Holmquist, 1957 from coastal waters of Chile, a supplementary description of the male is presented and the female is described for the first time. The presence of a mid-dorsal lappet near the posterior margin of the carapace of females only distinguishes the new species from all other Mysidopsis species except M. velifera Brattegard, 1973 from the Caribbean. M. jenseni is further separated from its American Pacific congeners by the following combination of characters: antennal scale 34 times as long as wide with a rounded apex and distal suture; uropodal endopod with 89 spiniform setae along ventromedial margin; telson with 4654 spiniform setae along all margins. The presence of lobe-like protuberances on the basis and dactylus of thoracic endopods 38 was documented for the new species, M. intii and other species of Mysidopsis as well as species belonging to the other four genera within the Tribe Mysidopsini. A key to the species of Mysidopsis of the Pacific coasts of the Americas is given.

Principles for Health Information Collection, Sharing, and Use: A Policy Statement From the American Heart Association.

The evolution of the electronic health record, combined with advances in data curation and analytic technologies, increasingly enables data sharing and harmonization. Advances in the analysis of health-related and health-proxy information have already accelerated research discoveries and improved patient care. This American Heart Association policy statement discusses how broad data sharing can be an enabling driver of progress by providing data to develop, test, and benchmark innovative methods, scalable insights, and potential new paradigms for data storage and workflow. Along with these advances come concerns about the sensitive nature of some health data, equity considerations about the involvement of historically excluded communities, and the complex intersection of laws attempting to govern behavior. Data-sharing principles are therefore necessary across a wide swath of entities, including parties who collect health information, funders, researchers, patients, legislatures, commercial companies, and regulatory departments and agencies. This policy statement outlines some of the key equity and legal background relevant to health data sharing and responsible management. It then articulates principles that will guide the American Heart Association's engagement in public policy related to data collection, sharing, and use to continue to inform its work across the research enterprise, as well as specific examples of how these principles might be applied in the policy landscape. The goal of these principles is to improve policy to support the use or reuse of health information in ways that are respectful of patients and research participants, equitable in impact in terms of both risks and potential benefits, and beneficial across broad and demographically diverse communities in the United States.

Lactational performance effects of supplemental histidine in dairy cows: A meta-analysis.

The objective of this meta-analysis was to examine the effects of supplemental His on lactational performance, plasma His concentration and efficiency of utilization of digestible His (EffHis) in dairy cows. The meta-analysis was performed on data from 17 studies published in peer-reviewed journals between 1999 and 2022. Five publications reported data from 2 separate experiments, which were included in the analyses as separate studies, therefore resulting in a total of 22 studies. In 10 studies, His was supplemented as rumen-protected (RP) His; in 1 study, 2 basal diets with different dHis levels were fed; and in the remaining experiments, free His was infused into the abomasum (4 studies), the jugular vein (3 studies) or deleted from a mixture of postruminally infused AA (4 studies). The main forages in the diets were corn silage in 14 and grass silage in 8 studies. If not reported in the publications, the supplies of dietary CP, metabolizable protein (MP), net energy of lactation, and digestible His (dHis) were estimated using NRC (2001). An initial meta-analysis was performed to test the standard mean difference (SMD; raw mean difference of treatment and control means divided by the pooled standard deviation of the means), that is, effect size, and the corresponding 95% confidence interval (CI) in production parameters between His-supplemented groups versus control. Further, regression analyses were also conducted to examine and compare the relationships between several response variables and dHis supply. Across studies, His supplementation increased plasma His concentration (SMD = 1.39; 95% CI: 1.17-1.61), as well as DMI (SMD = 0.240; 95% CI: 0.051-0.429) and milk yield (MY; SMD = 0.667; 95% CI: 0.468-0.866), respectively. Further, milk true protein concentration (MTP; SMD = 0.236; 95% CI: 0.046-0.425) and milk true protein yield (MTPY; SMD = 0.581; 95% CI: 0.387-0.776) were increased by His supplementation. Notably, the increase in MTP concentration and MTPY were 3.9 and 1.3 times greater for studies with MP-deficient (according to NRC 2001) diets compared with studies with MP-adequate diets. The regression analyses revealed that production parameters (DMI, MY, and MTPY) responded in a nonlinear manner to increasing His supply. Further, we detected a difference in the magnitude of change in MTPY and plasma His concentration with the level of His supply and between His supplementation methods, being greater for infused His compared with RPHis. Lastly, a linear and negative relationship between EffHis and the ratio of total digestible His to net energy for lactation supply was observed, indicating an important interaction between dHis and energy supply and EffHis (i.e., utilization of dHis to support protein export). Overall, these analyses confirm His as an important AA in dairy cattle nutrition.

The lophogastrids (Crustacea: Peracarida: Lophogastrida) of Indonesia and its adjacent waters. An updated checklist.

The zoogeographic distribution of lophogastrid species (Crustacea: Peracarida: Lophogastrida) occurring in the Indonesian waters is presented. For each species, data on general distribution, bathymetric ranges, habitat and localities reported on published data are provided. A total of 20 lophogastrid species belonging to three families and seven genera occur in Indonesian waters (about 38% of all known lophogastrids species worldwide), a number greater than other areas of Southeast Asia. Also, based on current information, the number of species or species richness is greater than other regions, such as Madagascar, North Pacific off Japan, Mediterranean, Canary Island, northern mid-Atlantic ridge, Iberian Peninsula, Mexico, and Angola Basin (SE Atlantic). Most of the Indonesian species are distributed worldwide, but one species, Lophogaster inermis appears to be endemic to Indonesia. Previous listings of Paralophogaster intermedius occurring in Southeast Asian waters is not verified in any collections, and has therefore been removed from our updated list.

Exclusion cycles: Reinforcing disparities in medicine.

Clinical practice, data collection, and medical AI constitute self-reinforcing and interacting cycles of exclusion.

Open-Source Clinical Machine Learning Models: Critical Appraisal of Feasibility, Advantages, and Challenges.

Machine learning applications promise to augment clinical capabilities and at least 64 models have already been approved by the US Food and Drug Administration. These tools are developed, shared, and used in an environment in which regulations and market forces remain immature. An important consideration when evaluating this environment is the introduction of open-source solutions in which innovations are freely shared; such solutions have long been a facet of digital culture. We discuss the feasibility and implications of open-source machine learning in a health care infrastructure built upon proprietary information. The decreased cost of development as compared to drugs and devices, a longstanding culture of open-source products in other industries, and the beginnings of machine learning-friendly regulatory pathways together allow for the development and deployment of open-source machine learning models. Such tools have distinct advantages including enhanced product integrity, customizability, and lower cost, leading to increased access. However, significant questions regarding engineering concerns about implementation infrastructure and model safety, a lack of incentives from intellectual property protection, and nebulous liability rules significantly complicate the ability to develop such open-source models. Ultimately, the reconciliation of open-source machine learning and the proprietary information-driven health care environment requires that policymakers, regulators, and health care organizations actively craft a conducive market in which innovative developers will continue to both work and collaborate.

Respecting Autonomy And Enabling Diversity: The Effect Of Eligibility And Enrollment On Research Data Demographics.

Many promising advances in precision health and other Big Data research rely on large data sets to analyze correlations among genetic variants, behavior, environment, and outcomes to improve population health. But these data sets are generally populated with demographically homogeneous cohorts. We conducted a retrospective cohort study of patients at a major academic medical center during 2012-19 to explore how recruitment and enrollment approaches affected the demographic diversity of participants in its research biospecimen and data bank. We found that compared with the overall clinical population, patients who consented to enroll in the research data bank were significantly less diverse in terms of age, sex, race, ethnicity, and socioeconomic status. Compared with patients who were recruited for the data bank, patients who enrolled were younger and less likely to be Black or African American, Asian, or Hispanic. The overall demographic diversity of the data bank was affected as much (and in some cases more) by which patients were considered eligible for recruitment as by which patients consented to enroll. Our work underscores the need for systemic commitment to diversify data banks so that different communities can benefit from research.

Collaboration in times of crisis: A study on COVID-19 vaccine R&D partnerships.

Collaboration is central for initiatives and efforts in the race to fight COVID-19, with particular focus on fostering rapid development of safe and effective COVID-19 vaccines. We investigated the types of partnerships that have emerged during the pandemic to develop these products. Using the World Health Organization's list of COVID-19 vaccine developments, we found nearly one third of all vaccine candidates were developed by partnerships, which tended to use next-gen vaccine platforms more than solo efforts. These partnerships vary substantially between materials-transfer partnerships and knowledge-sharing partnerships. The difference is important: The type of sharing between partners not only shapes the collaboration, but also bears implications for knowledge and technology development in the field and more broadly. Policies promoting fair and effective collaboration and knowledge-sharing are key for public health to avoid stumbling blocks for vaccine development, deployment, and equitable access, both for COVID-19 and expected future pandemics.

Emergent postpartum pelvic sonography.

This article describes the variable appearance of the normal postpartum uterus and reviews complications which can occur in the postpartum period, with particular emphasis on the sonographic findings. Postpartum complications are a common presentation to the emergency department. The majority of these patients present with secondary postpartum hemorrhage. Additional symptoms of pain or clinical findings of pyrexia and leukocytosis confound the clinical scenario and necessitate further evaluation with imaging. Ultrasonography is the mainstay in the initial imaging evaluation of the postpartum patient, with occasional progression to CT, MR, or angiography. We sought to provide a brief review of the literature, with pictorial review of key imaging findings, with a focus on ultrasonography. We provide a pictorial and brief literature review, with case examples from our institution, of key postpartum complications. Ultrasonography is an important component of evaluation in postpartum patients, particularly those with hemorrhage or other complication.

Artificial insemination of cattle: Description and assessment of a training program for veterinary students.

The objective was to assess the effectiveness of a comprehensive artificial insemination (AI) training program designed to facilitate an understanding of the breadth of the AI process, including AI skill acquisition, for preclinical veterinary students. Participants (n = 303) were enrolled at the Ross University School of Veterinary Medicine (Basseterre, St. Kitts, West Indies). The 2-d AI training program (n = 20) consisted of ∼8 h of instruction and ∼8 h of demonstration and hands-on activity. Oral presentations were used to deliver educational content, followed by video clips, discussion, demonstrations, and hands-on activity. Reproductive anatomy and physiology of the estrous cycle, AI sire acquisition, collection, evaluation, cryopreservation and distribution of conventional and sexed semen, storage and handling of frozen semen, use of synchronization protocols, accurate and efficient detection of estrus, and correct AI technique were discussed. True or false pre- and posttests were used to determine the level of knowledge gained by participants during the AI training program. Preclinical veterinary students were required to complete a semen handling and AI technique practical exam to achieve a certificate of completion. Participant program evaluations conducted at the conclusion of the program indicated that veterinary students found the content, structure, discussion, demonstrations, and hands-on activities to be appropriate and useful. No negative comments were offered about the training program, instructor, or activity coinstructors. The AI training program increased the posttest knowledge scores of veterinary students by 22 percentage points. Only 1 participant was unable to achieve a certificate of completion due to failure of the semen handling and AI technique practical exam. These results provide evidence that the AI training program was relevant and effective and that it offered information and skill acquisition with immediate field application.

Body MRI Subspecialty Reinterpretations at a Tertiary Care Center: Discrepancy Rates and Error Types.

OBJECTIVE. Radiology departments in tertiary care centers are frequently asked to perform secondary interpretations of imaging studies, particularly when a patient is transferred from a community hospital. Discrepancy rates in radiology vary widely, with low rates reported for preliminary resident reports that are overread by attending radiologists (2-6%) and higher rates (up to 56%) for secondary interpretations. Abdominal and pelvic imaging and cross-sectional imaging have the highest discrepancy rates. The purpose of our study was to determine the discrepancy rate and the most common reasons for discrepancies between abdominal and pelvic MRI reports obtained from outside institutions and secondary interpretations of these reports by a fellowship-trained radiologist at a tertiary care center. MATERIALS AND METHODS. We retrospectively identified 395 secondary MRI reports from January 2015 to December 2018 that were labeled as body MRI examinations at a tertiary care center. Thirty-eight cases were excluded for various reasons, including incorrect categorization or lack of outside report. We reviewed the outside reports, compared them with the secondary interpretations, and categorized the cases as discrepancy or no discrepancy. The discrepancies were subdivided into the most likely reason for the error using previously published categories; these categories were also divided into perceptive and cognitive errors. RESULTS. Of the 357 included cases, 246 (68.9%) had at least one discrepancy. The most common reason for error was faulty reasoning (34.3%), which is a cognitive error characterized by misidentifying an abnormality. Satisfaction of search, which is a perceptive error, was the most common reason for second discrepancies (15.0%). CONCLUSION. Secondary interpretations of body MR images at a tertiary care center identify a high rate of discrepancies, with cognitive error types predominating.