Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning.

OBJECTIVE: Use heuristic, deep learning (DL), and hybrid AI methods to predict semantic group (SG) assignments for new UMLS Metathesaurus atoms, with target accuracy ≥95%. MATERIALS AND METHODS: We used train-test datasets from successive 2020AA-2022AB UMLS Metathesaurus releases. Our heuristic "waterfall" approach employed a sequence of 7 different SG prediction methods. Atoms not qualifying for a method were passed on to the next method. The DL approach generated BioWordVec and SapBERT embeddings for atom names, BioWordVec embeddings for source vocabulary names, and BioWordVec embeddings for atom names of the second-to-top nodes of an atom's source hierarchy. We fed a concatenation of the 4 embeddings into a fully connected multilayer neural network with an output layer of 15 nodes (one for each SG). For both approaches, we developed methods to estimate the probability that their predicted SG for an atom would be correct. Based on these estimations, we developed 2 hybrid SG prediction methods combining the strengths of heuristic and DL methods. RESULTS: The heuristic waterfall approach accurately predicted 94.3% of SGs for 1 563 692 new unseen atoms. The DL accuracy on the same dataset was also 94.3%. The hybrid approaches achieved an average accuracy of 96.5%. CONCLUSION: Our study demonstrated that AI methods can predict SG assignments for new UMLS atoms with sufficient accuracy to be potentially useful as an intermediate step in the time-consuming task of assigning new atoms to UMLS concepts. We showed that for SG prediction, combining heuristic methods and DL methods can produce better results than either alone.

Industrial freezing and tempering for optimal functional properties in thawed Mozzarella cheese.

Mozzarella cheese was industrially frozen (-18 °C), stored for up to six months, tempered at 4 °C for one or three weeks and the structure and functionality compared to cheese stored at 4 °C and cheese aged at 4 °C for four weeks prior to freezing. When combined with ageing or tempering, the slow industrial freezing minimised changes to the protein network as detected by confocal microscopy and arrested proteolysis. Cheese functionality improved with three weeks of tempering, with properties similar to cheese refrigerated for one month, potentially due to increased proteolysis and protein rehydration. Frozen storage induced ß-sheet and ß-turn structures, as detected by S-FTIR microspectroscopy, with longer tempering leading to structural recovery in the cheese. This study indicates the proteolysis and functionality of frozen cheese can be optimised with tempering time. It also provides new insights into heat transfer during the industrial freezing and tempering of cheese.

Expression Changes in Mitochondrial Genes Affecting Mitochondrial Morphology, Transmembrane Potential, Fragmentation, Amyloidosis, and Neuronal Cell Death Found in Brains of Alzheimer's Disease Patients.

BACKGROUND: Alzheimer's disease (AD) is a neurological disease that has both a genetic and non-genetic origin. Mitochondrial dysfunction is a critical component in the pathogenesis of AD as deficits in oxidative capacity and energy production have been reported. OBJECTIVE: Nuclear-encoded mitochondrial genes were studied in order to understand the effects of mitochondrial expression changes on mitochondrial function in AD brains. These expression data were to be incorporated into a testable mathematical model for AD used to further assess the genes of interest as therapeutic targets for AD. METHODS: RT2-PCR arrays were used to assess expression of 84 genes involved in mitochondrial biogenesis in AD brains. A subset of mitochondrial genes of interest was identified after extensive Ingenuity Pathway Analysis (IPA) (Qiagen). Further filtering of this subset of genes of interest was achieved by individual qPCR analyses. Expression values from this group of genes were included in a mathematical model being developed to identify potential therapeutic targets. RESULTS: Nine genes involved in trafficking proteins to mitochondria, morphology of mitochondria, maintenance of mitochondrial transmembrane potential, fragmentation of mitochondria and mitochondrial dysfunction, amyloidosis, and neuronal cell death were identified as significant to the changes seen. These genes include TP53, SOD2, CDKN2A, MFN2, DNM1L, OPA1, FIS1, BNIP3, and GAPDH. CONCLUSION: Altered mitochondrial gene expression indicates that a subset of nuclear-encoded mitochondrial genes compromise multiple aspects of mitochondrial function in AD brains. A new mathematical modeling system may provide further insights into potential therapeutic targets.

Incorporating Mitochondrial Gene Expression Changes Within a Testable Mathematical Model for Alzheimer's Disease: Stress Response Modulation Predicts Potential Therapeutic Targets.

BACKGROUND: Alzheimer's disease is a specific form of dementia characterized by the aggregation of amyloid-ß plaques and tau tangles. New research has found that the formation of these aggregates occurs after dysregulation of cellular respiration and the production of radical oxygen species. Proteomic data shows that these changes are also related to unique gene expression patterns. OBJECTIVE: This study is designed to incorporate both proteomic and gene expression data into a testable mathematical model for AD. Manipulation of this new model allows the identification of potential therapeutic targets for AD. METHODS: We investigate the impact of these findings on new therapeutic targets via metabolic flux analysis of sirtuin stress response pathways while also highlighting the importance of metabolic enzyme activity in maintaining proper respiratory activity. RESULTS: Our results indicate that protective changes in SIRT1 and AMPK expression are potential avenues for therapeutics. CONCLUSION: Combining our mitochondrial gene expression analyses with available protein data allowed the construction of a new mathematical model for AD that provides a useful approach to test the efficacy of potential AD therapeutic targets.

Do electronic health record systems "dumb down" clinicians?

A panel sponsored by the American College of Medical Informatics (ACMI) at the 2021 AMIA Symposium addressed the provocative question: "Are Electronic Health Records dumbing down clinicians?" After reviewing electronic health record (EHR) development and evolution, the panel discussed how EHR use can impair care delivery. Both suboptimal functionality during EHR use and longer-term effects outside of EHR use can reduce clinicians' efficiencies, reasoning abilities, and knowledge. Panel members explored potential solutions to problems discussed. Progress will require significant engagement from clinician-users, educators, health systems, commercial vendors, regulators, and policy makers. Future EHR systems must become more user-focused and scalable and enable providers to work smarter to deliver improved care.

Don Lindberg's influence on future generations: The U.S. National Library of Medicine's biomedical informatics research training programs.

Through his visionary leadership as Director of the U.S. National Library of Medicine (NLM), Donald A. B. Lindberg M.D. influenced future generations of informatics professionals and the field of biomedical informatics itself. This chapter describes Dr. Lindberg's role in sponsoring and shaping the NLM's Institutional T15 training programs.

Donald A.B. Lindberg and the U.S. National Library of Medicine transformed biomedical and health informatics.

This overview summary of the Informatics Section of the book Transforming biomedical informatics and health information access: Don Lindberg and the U.S. National Library of Medicine illustrates how the NLM revolutionized the field of biomedical and health informatics during Lindberg's term as NLM Director. Authors present a before-and-after perspective of what changed, how it changed, and the impact of those changes.

Donald A.B. Lindberg and the U.S. National Library of Medicine Transformed Biomedical and Health Informatics.

This overview summary of the Informatics Section of the book Transforming biomedical informatics and health information access: Don Lindberg and the U.S. National Library of Medicine illustrates how the NLM revolutionized the field of biomedical and health informatics during Lindberg's term as NLM Director. Authors present a before-and-after perspective of what changed, how it changed, and the impact of those changes.

Don Lindberg's Influence on Future Generations: The U.S. National Library of Medicine's Biomedical Informatics Research Training Programs.

Through his visionary leadership as Director of the U.S. National Library of Medicine (NLM), Donald A.B. Lindberg M.D. influenced future generations of informatics professionals and the field of biomedical informatics itself. This chapter describes Dr. Lindberg's role in sponsoring and shaping the NLM's Institutional T15 training programs.

The roles of the US National Library of Medicine and Donald A.B. Lindberg in revolutionizing biomedical and health informatics.

Over a 31-year span as Director of the US National Library of Medicine (NLM), Donald A.B. Lindberg, MD, and his extraordinary NLM colleagues fundamentally changed the field of biomedical and health informatics-with a resulting impact on biomedicine that is much broader than its influence on any single subfield. This article provides substance to bolster that claim. The review is based in part on the informatics section of a new book, "Transforming biomedical informatics and health information access: Don Lindberg and the US National Library of Medicine" (IOS Press, forthcoming 2021). After providing insights into selected aspects of the book's informatics-related contents, the authors discuss the broader context in which Dr. Lindberg and the NLM accomplished their transformative work.

Reductive Radical Conjugate Addition of Alkyl Electrophiles Catalyzed by a Cobalt/Iridium Photoredox System.

Alkyl and aryl halides have been studied extensively as radical precursors; however, mild and less toxic conditions for the activation of alkyl bromides toward alkyl radicals are still desirable. Reported here is a reductive radical conjugate addition that allows for the formation of alkyl radicals via activation of alkyl bromides through cobalt/iridium catalysis. The developed conditions are emphasized in the broad substrate scope presented, including benzylic halides and halides containing free alcohols, silanes, and chlorides.

A Unified and Practical Method for Carbon-Heteroatom Cross-Coupling using Nickel/Photo Dual Catalysis.

While carbon-heteroatom cross-coupling reactions have been extensively studied, many methods are specific and limited to a particular set of substrates or functional groups. Reported here is a general method that allows for C-O, C-N and C-S cross-coupling reactions under one general set of conditions. We propose that an energy transfer pathway, in which an iridium photosensitizer produces an excited nickel(II) complex, is responsible for the key reductive elimination step that couples aryl bromides, iodides, and chlorides to 1° and 2° alcohols, amines, thiols, carbamates, and sulfonamides, and is amenable to scale up via a flow apparatus.

Post-Streptococcal Glomerulonephritis in Two Patients Following Deceased Donor Kidney Transplant.

BACKGROUND Post-streptococcal glomerulonephritis (PSGN) is a well-known cause of renal injury. This disease is caused by a prior infection with specific nephritogenic strains of group A beta-hemolytic streptococcus resulting in formation of immune complexes in the glomeruli. Clinical presentation can range from asymptomatic, microscopic hematuria to the nephritic syndrome which is defined by red to brown urine, nephrotic range proteinuria, edema, hypertension, and acute kidney injury. A few reports have described PSGN in kidney transplant recipients in the post-transplantation period. However, biopsy-proven, donor-derived, PSGN in kidney transplant recipients has not been described. CASE REPORT Kidneys were donated from a 25-year-old Caucasian female with no history of hypertension or diabetes who had anoxic brain death in the setting of sepsis due to group A Streptococcus pyogenes bacteremia. The recipients were a 55-year-old male and a 68-year-old female, both of whom had end stage renal disease (ESRD) secondary to hypertensive nephrosclerosis. The recipients had kidney biopsies, one at the time of implantation and the other on post-operative day (POD) 2. Both biopsies showed streptococcal-associated glomerulonephritis. The prompt recognition and treatment of this disease in the immediate post-operative period resulted in histological resolution of the disease as well as good graft outcomes. CONCLUSIONS Utilizing kidneys from donors with streptococcal bacteremia is possible while maintaining a high degree of suspicion for possible streptococcal-associated glomerulonephritis.

Assessment of Cardiovascular Disease Risk and Therapeutic Patterns among Urban Black Rheumatoid Arthritis Patients.

Rheumatoid arthritis (RA) patients have nearly twice the risk of cardiovascular disease (CVD) compared to the general population. We aimed to assess, in a predominantly Black population, the prevalence of traditional and RA-specific CVD risk factors and therapeutic patterns. Utilizing ICD codes, we identified 503 RA patients ≥18 years old who were seen from 2010 to 2017. Of them, 88.5% were Black, 87.9% were women and 29.4% were smokers. CVD risk factors (obesity, diabetes, hypertension, dyslipidemia) were higher than in previously reported White RA cohorts. Eighty-seven percent of the patients had at least one traditional CVD risk factor, 37% had three or more traditional CVD risk factors and 58% had RA-specific risk factors (seropositive RA, >10 years of disease, joint erosions, elevated inflammatory markers, extra-articular disease, body mass index (BMI) < 20). CV outcomes (coronary artery disease/myocardial infarction, heart failure, atrial fibrillation and stroke) were comparable to published reports. Higher steroid use, which increases CVD risk, and lesser utilization of biologics (decrease CV risk) were also observed. Our Black RA cohort had higher rates of traditional CVD risk factors, in addition to chronic inflammation from aggressive RA, which places our patients at a higher risk for CVD outcomes, calling for revised risk stratification strategies and effective interventions to address comorbidities in this vulnerable population.

A method for analyzing inpatient care variability through physicians' orders.

OBJECTIVE: Administrators assess care variability through chart review or cost variability to inform care standardization efforts. Chart review is costly and cost variability is imprecise. This study explores the potential of physician orders as an alternative measure of care variability. MATERIALS & METHODS: The authors constructed an order variability metric from adult Vanderbilt University Hospital patients treated between 2013 and 2016. The study compared how well a cost variability model predicts variability in the length of stay compared to an order variability model. Both models adjusted for covariates such as severity of illness, comorbidities, and hospital transfers. RESULTS: The order variability model significantly minimized the Akaike information criterion (superior outcome) compared to the cost variability model. This result also held when excluding patients who received intensive care. CONCLUSION: Order variability can potentially typify care variability better than cost variability. Order variability is a scalable metric, calculable during the course of care.

Asymmetric Synthesis of Griffipavixanthone Employing a Chiral Phosphoric Acid-Catalyzed Cycloaddition.

Asymmetric synthesis of the biologically active xanthone dimer griffipavixanthone is reported along with its absolute stereochemistry determination. Synthesis of the natural product is accomplished via dimerization of a p-quinone methide using a chiral phosphoric acid catalyst to afford a protected precursor in excellent diastereo- and enantioselectivity. Mechanistic studies, including an unbiased computational investigation of chiral ion-pairs using parallel tempering, were performed in order to probe the mode of asymmetric induction.

Discovering hidden knowledge through auditing clinical diagnostic knowledge bases.

OBJECTIVE: Evaluate potential for data mining auditing techniques to identify hidden concepts in diagnostic knowledge bases (KB). Improving completeness enhances KB applications such as differential diagnosis and patient case simulation. MATERIALS AND METHODS: Authors used unsupervised (Pearson's correlation - PC, Kendall's correlation - KC, and a heuristic algorithm - HA) methods to identify existing and discover new finding-finding interrelationships ("properties") in the INTERNIST-1/QMR KB. Authors estimated KB maintenance efficiency gains (effort reduction) of the approaches. RESULTS: The methods discovered new properties at 95% CI rates of [0.1%, 5.4%] (PC), [2.8%, 12.5%] (KC), and [5.6%, 18.8%] (HA). Estimated manual effort reduction for HA-assisted determination of new properties was approximately 50-fold. CONCLUSION: Data mining can provide an efficient supplement to ensuring the completeness of finding-finding interdependencies in diagnostic knowledge bases. Authors' findings should be applicable to other diagnostic systems that record finding frequencies within diseases (e.g., DXplain, ISABEL).