Structured feedback and operative video debriefing with critical view of safety annotation in training of laparoscopic cholecystectomy: a randomized controlled study.

BACKGROUND: The learning curve in minimally invasive surgery (MIS) is lengthened compared to open surgery. It has been reported that structured feedback and training in teams of two trainees improves MIS training and MIS performance. Annotation of surgical images and videos may prove beneficial for surgical training. This study investigated whether structured feedback and video debriefing, including annotation of critical view of safety (CVS), have beneficial learning effects in a predefined, multi-modal MIS training curriculum in teams of two trainees. METHODS: This randomized-controlled single-center study included medical students without MIS experience (n = 80). The participants first completed a standardized and structured multi-modal MIS training curriculum. They were then randomly divided into two groups (n = 40 each), and four laparoscopic cholecystectomies (LCs) were performed on ex-vivo porcine livers each. Students in the intervention group received structured feedback after each LC, consisting of LC performance evaluations through tutor-trainee joint video debriefing and CVS video annotation. Performance was evaluated using global and LC-specific Objective Structured Assessments of Technical Skills (OSATS) and Global Operative Assessment of Laparoscopic Skills (GOALS) scores. RESULTS: The participants in the intervention group had higher global and LC-specific OSATS as well as global and LC-specific GOALS scores than the participants in the control group (25.5 ± 7.3 vs. 23.4 ± 5.1, p = 0.003; 47.6 ± 12.9 vs. 36 ± 12.8, p < 0.001; 17.5 ± 4.4 vs. 16 ± 3.8, p < 0.001; 6.6 ± 2.3 vs. 5.9 ± 2.1, p = 0.005). The intervention group achieved CVS more often than the control group (1. LC: 20 vs. 10 participants, p = 0.037, 2. LC: 24 vs. 8, p = 0.001, 3. LC: 31 vs. 8, p < 0.001, 4. LC: 31 vs. 10, p < 0.001). CONCLUSIONS: Structured feedback and video debriefing with CVS annotation improves CVS achievement and ex-vivo porcine LC training performance based on OSATS and GOALS scores.

RNA-Templated Peptide Bond Formation Promotes L-Homochirality.

The world in which we live is homochiral. The ribose units that form the backbone of DNA and RNA are all D-configured and the encoded amino acids that comprise the proteins of all living species feature an all-L-configuration at the α-carbon atoms. The homochirality of α-amino acids is essential for folding of the peptides into well-defined and functional 3D structures and the homochirality of D-ribose is crucial for helix formation and base-pairing. The question of why nature uses only encoded L-α-amino acids is not understood. Herein, we show that an RNA-peptide world, in which peptides grow on RNAs constructed from D-ribose, leads to the self-selection of homo-L-peptides, which provides a possible explanation for the homo-D-ribose and homo-L-amino acid combination seen in nature.

Autoantibodies against the chemokine receptor 3 predict cardiovascular risk.

BACKGROUND AND AIMS: Chronic inflammation and autoimmunity contribute to cardiovascular (CV) disease. Recently, autoantibodies (aAbs) against the CXC-motif-chemokine receptor 3 (CXCR3), a G protein-coupled receptor with a key role in atherosclerosis, have been identified. The role of anti-CXCR3 aAbs for CV risk and disease is unclear. METHODS: Anti-CXCR3 aAbs were quantified by a commercially available enzyme-linked immunosorbent assay in 5000 participants (availability: 97.1%) of the population-based Gutenberg Health Study with extensive clinical phenotyping. Regression analyses were carried out to identify determinants of anti-CXCR3 aAbs and relevance for clinical outcome (i.e. all-cause mortality, cardiac death, heart failure, and major adverse cardiac events comprising incident coronary artery disease, myocardial infarction, and cardiac death). Last, immunization with CXCR3 and passive transfer of aAbs were performed in ApoE(-/-) mice for preclinical validation. RESULTS: The analysis sample included 4195 individuals (48% female, mean age 55.5 ± 11 years) after exclusion of individuals with autoimmune disease, immunomodulatory medication, acute infection, and history of cancer. Independent of age, sex, renal function, and traditional CV risk factors, increasing concentrations of anti-CXCR3 aAbs translated into higher intima-media thickness, left ventricular mass, and N-terminal pro-B-type natriuretic peptide. Adjusted for age and sex, anti-CXCR3 aAbs above the 75th percentile predicted all-cause death [hazard ratio (HR) (95% confidence interval) 1.25 (1.02, 1.52), P = .029], driven by excess cardiac mortality [HR 2.51 (1.21, 5.22), P = .014]. A trend towards a higher risk for major adverse cardiac events [HR 1.42 (1.0, 2.0), P = .05] along with increased risk of incident heart failure [HR per standard deviation increase of anti-CXCR3 aAbs: 1.26 (1.02, 1.56), P = .03] may contribute to this observation. Targeted proteomics revealed a molecular signature of anti-CXCR3 aAbs reflecting immune cell activation and cytokine-cytokine receptor interactions associated with an ongoing T helper cell 1 response. Finally, ApoE(-/-) mice immunized against CXCR3 displayed increased anti-CXCR3 aAbs and exhibited a higher burden of atherosclerosis compared to non-immunized controls, correlating with concentrations of anti-CXCR3 aAbs in the passive transfer model. CONCLUSIONS: In individuals free of autoimmune disease, anti-CXCR3 aAbs were abundant, related to CV end-organ damage, and predicted all-cause death as well as cardiac morbidity and mortality in conjunction with the acceleration of experimental atherosclerosis.

Viral load of SARS-CoV-2 in surgical smoke in minimally invasive and open surgery: a single-center prospective clinical trial.

At the beginning of the COVID-19 pandemic, it was assumed that SARS-CoV-2 could be transmitted through surgical smoke generated by electrocauterization. Minimally invasive surgery (MIS) was targeted due to potentially higher concentrations of the SARS-CoV-2 particles in the pneumoperitoneum. Some surgical societies even recommended open surgery instead of MIS to prevent the potential spread of SARS-CoV-2 from the pneumoperitoneum. This study aimed to detect SARS-CoV-2 in surgical smoke during open and MIS. Patients with SARS-CoV-2 infection who underwent open surgery or MIS at Heidelberg University Hospital were included in the study. A control group of patients without SARS-CoV-2 infection undergoing MIS or open surgery was included for comparison. The trial was approved by the Ethics Committee of Heidelberg University Medical School (S-098/2021). The following samples were collected: nasopharyngeal and intraabdominal swabs, blood, urine, surgical smoke, and air samples from the operating room. An SKC BioSampler was used to sample the surgical smoke from the pneumoperitoneum during MIS and the approximate surgical field during open surgery in 15 ml of sterilized phosphate-buffered saline. An RT-PCR test was performed on all collected samples to detect SARS-CoV-2 viral particles. Twelve patients with proven SARS-CoV-2 infection underwent open abdominal surgery. Two SARS-CoV-2-positive patients underwent an MIS procedure. The control group included 24 patients: 12 underwent open surgery and 12 MIS. One intraabdominal swab in a patient with SARS-CoV-2 infection was positive for SARS-CoV-2. However, during both open surgery and MIS, none of the surgical smoke samples showed any detectable viral particles of SARS-CoV-2. The air samples collected at the end of the surgical procedure showed no viral particles of SARS-CoV-2. Major complications (CD ≥ IIIa) were more often observed in SARS-CoV-2 positive patients (10 vs. 4, p = 0.001). This study showed no detectable viral particles of SARS-CoV-2 in surgical smoke sampled during MIS and open surgery. Thus, the discussed risk of transmission of SARS-CoV-2 via surgical smoke could not be confirmed in the present study.

Diagnostic test accuracy study of a commercially available deep learning algorithm for ischemic lesion detection on brain MRIs in suspected stroke patients from a non-comprehensive stroke center.

PURPOSE: To estimate the ability of a commercially available artificial intelligence (AI) tool to detect acute brain ischemia on Magnetic Resonance Imaging (MRI), compared to an experienced neuroradiologist. METHODS: We retrospectively included 1030 patients with brain MRI, suspected of stroke from January 6th, 2020 to 1st of April 2022, based on these criteria: Age ≥ 18 years, symptoms within four weeks before the scan. The neuroradiologist reinterpreted the MRI scans and subclassified ischemic lesions for reference. We excluded scans with interpretation difficulties due to artifacts or missing sequences. Four MRI scanner models from the same vendor were used. The first 800 patients were included consecutively, remaining enriched for less frequent lesions. The index test was a CE-approved AI tool (Apollo version 2.1.1 by Cerebriu). RESULTS: The final analysis cohort comprised 995 patients (mean age 69 years, 53 % female). A case-based analysis for detecting acute ischemic lesions showed a sensitivity of 89 % (95 % CI: 85 %-91 %) and specificity of 90 % (95 % CI: 87 %-92 %). We found no significant difference in sensitivity or specificity based on sex, age, or comorbidities. Specificity was reduced in cases with DWI artifacts. Multivariate analysis showed that increasing ischemic lesion size and fragmented lesions were independently associated with higher sensitivity, while non-acute lesion ages lowered sensitivity. CONCLUSIONS: The AI tool exhibits high sensitivity and specificity in detecting acute ischemic lesions on MRI compared to an experienced neuroradiologist. While sensitivity depends on the ischemic lesions' characteristics, specificity depends on the image quality.

The Entropy of Entropy: Are We Talking about the Same Thing?

In the last few decades, the number of published papers that include search terms such as thermodynamics, entropy, ecology, and ecosystems has grown rapidly. Recently, background research carried out during the development of a paper on "thermodynamics in ecology" revealed huge variation in the understanding of the meaning and the use of some of the central terms in this field-in particular, entropy. This variation seems to be based primarily on the differing educational and scientific backgrounds of the researchers responsible for contributions to this field. Secondly, some ecological subdisciplines also seem to be better suited and applicable to certain interpretations of the concept than others. The most well-known seems to be the use of the Boltzmann-Gibbs equation in the guise of the Shannon-Weaver/Wiener index when applied to the estimation of biodiversity in ecology. Thirdly, this tendency also revealed that the use of entropy-like functions could be diverted into an area of statistical and distributional analyses as opposed to real thermodynamic approaches, which explicitly aim to describe and account for the energy fluxes and dissipations in the systems. Fourthly, these different ways of usage contribute to an increased confusion in discussions about efficiency and possible telos in nature, whether at the developmental level of the organism, a population, or an entire ecosystem. All the papers, in general, suffer from a lack of clear definitions of the thermodynamic functions used, and we, therefore, recommend that future publications in this area endeavor to achieve a more precise use of language. Only by increasing such efforts it is possible to understand and resolve some of the significant and possibly misleading discussions in this area.

Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion.

Background Commercially available artificial intelligence (AI) tools can assist radiologists in interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear. Purpose To evaluate the diagnostic accuracy of four commercially available AI tools for detection of airspace disease, pneumothorax, and pleural effusion on chest radiographs. Materials and Methods This retrospective study included consecutive adult patients who underwent chest radiography at one of four Danish hospitals in January 2020. Two thoracic radiologists (or three, in cases of disagreement) who had access to all previous and future imaging labeled chest radiographs independently for the reference standard. Area under the receiver operating characteristic curve, sensitivity, and specificity were calculated. Sensitivity and specificity were additionally stratified according to the severity of findings, number of findings on chest radiographs, and radiographic projection. The χ2 and McNemar tests were used for comparisons. Results The data set comprised 2040 patients (median age, 72 years [IQR, 58-81 years]; 1033 female), of whom 669 (32.8%) had target findings. The AI tools demonstrated areas under the receiver operating characteristic curve ranging 0.83-0.88 for airspace disease, 0.89-0.97 for pneumothorax, and 0.94-0.97 for pleural effusion. Sensitivities ranged 72%-91% for airspace disease, 63%-90% for pneumothorax, and 62%-95% for pleural effusion. Negative predictive values ranged 92%-100% for all target findings. In airspace disease, pneumothorax, and pleural effusion, specificity was high for chest radiographs with normal or single findings (range, 85%-96%, 99%-100%, and 95%-100%, respectively) and markedly lower for chest radiographs with four or more findings (range, 27%-69%, 96%-99%, 65%-92%, respectively) (P < .001). AI sensitivity was lower for vague airspace disease (range, 33%-61%) and small pneumothorax or pleural effusion (range, 9%-94%) compared with larger findings (range, 81%-100%; P value range, > .99 to < .001). Conclusion Current-generation AI tools showed moderate to high sensitivity for detecting airspace disease, pneumothorax, and pleural effusion on chest radiographs. However, they produced more false-positive findings than radiology reports, and their performance decreased for smaller-sized target findings and when multiple findings were present. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Yanagawa and Tomiyama in this issue.

AutoCore: A network-based definition of the core module of human autoimmunity and autoinflammation.

Although research on rare autoimmune and autoinflammatory diseases has enabled definition of nonredundant regulators of homeostasis in human immunity, because of the single gene-single disease nature of many of these diseases, contributing factors were mostly unveiled in sequential and noncoordinated individual studies. We used a network-based approach for integrating a set of 186 inborn errors of immunity with predominant autoimmunity/autoinflammation into a comprehensive map of human immune dysregulation, which we termed "AutoCore." The AutoCore is located centrally within the interactome of all protein-protein interactions, connecting and pinpointing multidisease markers for a range of common, polygenic autoimmune/autoinflammatory diseases. The AutoCore can be subdivided into 19 endotypes that correspond to molecularly and phenotypically cohesive disease subgroups, providing a molecular mechanism-based disease classification and rationale toward systematic targeting for therapeutic purposes. Our study provides a proof of concept for using network-based methods to systematically investigate the molecular relationships between individual rare diseases and address a range of conceptual, diagnostic, and therapeutic challenges.

Telestration with augmented reality improves the performance of the first ten ex vivo porcine laparoscopic cholecystectomies: a randomized controlled study.

INTRODUCTION: The learning curve in minimally invasive surgery (MIS) is steep compared to open surgery. One of the reasons is that training in the operating room in MIS is mainly limited to verbal instructions. The iSurgeon telestration device with augmented reality (AR) enables visual instructions, guidance, and feedback during MIS. This study aims to compare the effects of the iSurgeon on the training of novices performing repeated laparoscopic cholecystectomy (LC) on a porcine liver compared to traditional verbal instruction methods. METHODS: Forty medical students were randomized into the iSurgeon and the control group. The iSurgeon group performed 10 LCs receiving interactive visual guidance. The control group performed 10 LCs receiving conventional verbal guidance. The performance assessment using Objective Structured Assessments of Technical Skills (OSATS) and Global Operative Assessment of Laparoscopic Skills (GOALS) scores, the total operating time, and complications were compared between the two groups. RESULTS: The iSurgeon group performed LCs significantly better (global GOALS 17.3 ± 2.6 vs. 16 ± 2.6, p ≤ 0.001, LC specific GOALS 7 ± 2 vs. 5.9 ± 2.1, p ≤ 0.001, global OSATS 25.3 ± 4.3 vs. 23.5 ± 3.9, p ≤ 0.001, LC specific OSATS scores 50.8 ± 11.1 vs. 41.2 ± 9.4, p ≤ 0.001) compared to the control group. The iSurgeon group had significantly fewer intraoperative complications in total (2.7 ± 2.0 vs. 3.6 ± 2.0, p ≤ 0.001) than the control group. There was no difference in operating time (79.6 ± 25.7 vs. 84.5 ± 33.2 min, p = 0.087). CONCLUSION: Visual guidance using the telestration device with AR, iSurgeon, improves performance and lowers the complication rates in LCs in novices compared to conventional verbal expert guidance.

Effective Connectivity of Thalamocortical Interactions Following d-Amphetamine, LSD, and MDMA Administration.

BACKGROUND: While the exploration of serotonergic psychedelics as psychiatric medicines deepens, so does the pressure to better understand how these compounds act on the brain. METHODS: We used a double-blind, placebo-controlled, crossover design and administered lysergic acid diethylamide (LSD), 3,4-methylenedioxymethamphetamine (MDMA), and d-amphetamine in 25 healthy participants. By using spectral dynamic causal modeling, we mapped substance-induced changes in effective connectivity between the thalamus and different cortex types (unimodal vs. transmodal) derived from a previous study with resting-state functional magnetic resonance imaging data. Due to the distinct pharmacological modes of action of the 3 substances, we were able to investigate specific effects mainly driven by different neurotransmitter systems on thalamocortical and corticothalamic interactions. RESULTS: Compared with placebo, all 3 substances increased the effective connectivity from the thalamus to specific unimodal cortices, whereas the influence of these cortices on the thalamus was reduced. These results indicate increased bottom-up and decreased top-down information flow between the thalamus and some unimodal cortices. However, for the amphetamines, we found the opposite effects when examining the effective connectivity with transmodal cortices, including parts of the salience network. Intriguingly, LSD increased the effective connectivity from the thalamus to both unimodal and transmodal cortices, indicating a breach in the hierarchical organization of ongoing brain activity. CONCLUSIONS: The results advance our knowledge about the action of psychedelics on the brain and refine current models aiming to explain the underlying neurobiological processes.

Heart rate variability: reference values and role for clinical profile and mortality in individuals with heart failure.

AIMS: To establish reference values and clinically relevant determinants for measures of heart rate variability (HRV) and to assess their relevance for clinical outcome prediction in individuals with heart failure. METHODS: Data from the MyoVasc study (NCT04064450; N = 3289), a prospective cohort on chronic heart failure with a highly standardized, 5 h examination, and Holter ECG recording were investigated. HRV markers were selected using a systematic literature screen and a data-driven approach. Reference values were determined from a healthy subsample. Clinical determinants of HRV were investigated via multivariable linear regression analyses, while their relationship with mortality was investigated by multivariable Cox regression analyses. RESULTS: Holter ECG recordings were available for analysis in 1001 study participants (mean age 64.5 ± 10.5 years; female sex 35.4%). While the most frequently reported HRV markers in literature were from time and frequency domains, the data-driven approach revealed predominantly non-linear HRV measures. Age, sex, dyslipidemia, family history of myocardial infarction or stroke, peripheral artery disease, and heart failure were strongly related to HRV in multivariable models. In a follow-up period of 6.5 years, acceleration capacity [HRperSD 1.53 (95% CI 1.21/1.93), p = 0.0004], deceleration capacity [HRperSD: 0.70 (95% CI 0.55/0.88), p = 0.002], and time lag [HRperSD 1.22 (95% CI 1.03/1.44), p = 0.018] were the strongest predictors of all-cause mortality in individuals with heart failure independently of cardiovascular risk factors, comorbidities, and medication. CONCLUSION: HRV markers are associated with the cardiovascular clinical profile and are strong and independent predictors of survival in heart failure. This underscores clinical relevance and interventional potential for individuals with heart failure. GOV IDENTIFIER: NCT04064450.

Circulating Epithelial Cells in Patients with Intraductal Papillary Mucinous Neoplasm of the Pancreas.

Intraductal papillary mucinous neoplasm (IPMN) is the most common pancreatic cyst and a precursor of pancreatic cancer (PDAC). Since PDAC has a devastatingly high mortality rate, the early diagnosis and treatment of any precursor lesion are rational. The safety of the existing guidelines on the clinical management of IPMN has been criticized due to unsatisfactory sensitivity and specificity, showing the need for further markers. Blood obtained from patients with IPMN was therefore subjected to size-based isolation of circulating epithelial cells (CECs). We isolated CECs and evaluated their cytological characteristics. Additionally, we compared Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations in CECs and the primary IPMN tissue, since KRAS mutations are very typical for PDAC. Samples from 27 IPMN patients were analyzed. In 10 (37%) patients, CECs were isolated and showed a hybrid pattern of surface markers involving both epithelial and mesenchymal markers, suggesting a possible EMT process of the cells. Especially, patients with high-grade dysplasia in the main specimen were all CEC-positive. KRAS mutations were also present in CECs but less common than in IPMN tissue. The existence of CEC in IPMN patients offers additional blood-based research possibilities for IMPN biology.

The effect of lysergic acid diethylamide (LSD) on whole-brain functional and effective connectivity.

Psychedelics have emerged as promising candidate treatments for various psychiatric conditions, and given their clinical potential, there is a need to identify biomarkers that underlie their effects. Here, we investigate the neural mechanisms of lysergic acid diethylamide (LSD) using regression dynamic causal modelling (rDCM), a novel technique that assesses whole-brain effective connectivity (EC) during resting-state functional magnetic resonance imaging (fMRI). We modelled data from two randomised, placebo-controlled, double-blind, cross-over trials, in which 45 participants were administered 100 µg LSD and placebo in two resting-state fMRI sessions. We compared EC against whole-brain functional connectivity (FC) using classical statistics and machine learning methods. Multivariate analyses of EC parameters revealed predominantly stronger interregional connectivity and reduced self-inhibition under LSD compared to placebo, with the notable exception of weakened interregional connectivity and increased self-inhibition in occipital brain regions as well as subcortical regions. Together, these findings suggests that LSD perturbs the Excitation/Inhibition balance of the brain. Notably, whole-brain EC did not only provide additional mechanistic insight into the effects of LSD on the Excitation/Inhibition balance of the brain, but EC also correlated with global subjective effects of LSD and discriminated experimental conditions in a machine learning-based analysis with high accuracy (91.11%), highlighting the potential of using whole-brain EC to decode or predict subjective effects of LSD in the future.

Autonomous Chest Radiograph Reporting Using AI: Estimation of Clinical Impact.

Background Automated interpretation of normal chest radiographs could alleviate the workload of radiologists. However, the performance of such an artificial intelligence (AI) tool compared with clinical radiology reports has not been established. Purpose To perform an external evaluation of a commercially available AI tool for (a) the number of chest radiographs autonomously reported, (b) the sensitivity for AI detection of abnormal chest radiographs, and (c) the performance of AI compared with that of the clinical radiology reports. Materials and Methods In this retrospective study, consecutive posteroanterior chest radiographs from adult patients in four hospitals in the capital region of Denmark were obtained in January 2020, including images from emergency department patients, in-hospital patients, and outpatients. Three thoracic radiologists labeled chest radiographs in a reference standard based on chest radiograph findings into the following categories: critical, other remarkable, unremarkable, or normal (no abnormalities). AI classified chest radiographs as high confidence normal (normal) or not high confidence normal (abnormal). Results A total of 1529 patients were included for analysis (median age, 69 years [IQR, 55-69 years]; 776 women), with 1100 (72%) classified by the reference standard as having abnormal radiographs, 617 (40%) as having critical abnormal radiographs, and 429 (28%) as having normal radiographs. For comparison, clinical radiology reports were classified based on the text and insufficient reports excluded (n = 22). The sensitivity of AI was 99.1% (95% CI: 98.3, 99.6; 1090 of 1100 patients) for abnormal radiographs and 99.8% (95% CI: 99.1, 99.9; 616 of 617 patients) for critical radiographs. Corresponding sensitivities for radiologist reports were 72.3% (95% CI: 69.5, 74.9; 779 of 1078 patients) and 93.5% (95% CI: 91.2, 95.3; 558 of 597 patients), respectively. Specificity of AI, and hence the potential autonomous reporting rate, was 28.0% of all normal posteroanterior chest radiographs (95% CI: 23.8, 32.5; 120 of 429 patients), or 7.8% (120 of 1529 patients) of all posteroanterior chest radiographs. Conclusion Of all normal posteroanterior chest radiographs, 28% were autonomously reported by AI with a sensitivity for any abnormalities higher than 99%. This corresponded to 7.8% of the entire posteroanterior chest radiograph production. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Park in this issue.

Loading of Amino Acids onto RNA in a Putative RNA-Peptide World.

RNA is a molecule that can both store genetic information and perform catalytic reactions. This observed dualism places RNA into the limelight of concepts about the origin of life. The RNA world concept argues that life started from self-replicating RNA molecules, which evolved toward increasingly complex structures. Recently, we demonstrated that RNA, with the help of conserved non-canonical nucleosides, which are also putative relics of an early RNA world, had the ability to grow peptides covalently connected to RNA nucleobases, creating RNA-peptide chimeras. It is conceivable that such molecules, which combined the information-coding properties of RNA with the catalytic potential of amino acid side chains, were once the structures from which life emerged. Herein, we report prebiotic chemistry that enabled the loading of both nucleosides and RNAs with amino acids as the first step toward RNA-based peptide synthesis in a putative RNA-peptide world.

Effects of empagliflozin on left ventricular diastolic function in addition to usual care in individuals with type 2 diabetes mellitus-results from the randomized, double-blind, placebo-controlled EmDia trial.

BACKGROUND: The sodium-glucose co-transporter 2 inhibitor empagliflozin improves cardiovascular outcome in patients with type 2 diabetes mellitus (T2DM) and heart failure. Experimental studies suggest a direct cardiac effect of empagliflozin associated with an improvement in left ventricular diastolic function. METHODS: In the randomized, double-blind, two-armed, placebo-controlled, parallel group trial EmDia, patients with T2DM and elevated left ventricular E/E´ ratio were enrolled and randomized 1:1 to receive empagliflozin 10 mg/day versus placebo. The primary endpoint was the change of left ventricular E/E´ ratio after 12 weeks of intervention. RESULTS: A total of 144 patients with T2DM and an elevated left ventricular E/e´ ratio (age 68.9 ± 7.7 years; 14.1% women; E/e´ ratio 9.61[8.24/11.14], left ventricular ejection fraction 58.9% ± 5.6%). After 12 weeks of intervention, empagliflozin resulted in a significant higher decrease in the primary endpoint E/e´ ratio by - 1.18 ([95% confidence interval (CI) - 1.72/- 0.65]; P < 0.0001) compared with placebo. The beneficial effect of empagliflozin was consistent across all subgroups and also occurred in subjects with heart failure and preserved ejection fraction (n = 30). Additional effects of empagliflozin on body weight, HbA1c, uric acid, red blood cell count, hemoglobin, mean corpuscular hemoglobin, and hematocrit were detected (all P < 0.001). Approximately one-third of the reduction in E/e´ by empagliflozin could be explained by the variables examined. CONCLUSIONS: Empagliflozin improves diastolic function in patients with T2DM and elevated end-diastolic pressure. Since the positive effects were consistent in patients with and without heart failure with preserved ejection fraction, the data add a mechanistic insight for the beneficial cardiovascular effect of empagliflozin. TRIAL REGISTRATION: Clinicaltrials.gov, unique identifier: NCT02932436.

A Highly Active Cobalt Catalyst for the General and Selective Hydrogenation of Aromatic Heterocycles.

Nanostructured earth abundant metal catalysts that mediate important chemical reactions with high efficiency and selectivity are of great interest. This study introduces a synthesis protocol for nanostructured earth abundant metal catalysts. Three components, an inexpensive metal precursor, an easy to synthesize N/C precursor, and a porous support material undergo pyrolysis to give the catalyst material in a simple, single synthesis step. By applying this catalyst synthesis, a highly active cobalt catalyst for the general and selective hydrogenation of aromatic heterocycles could be generated. The reaction is important with regard to organic synthesis and hydrogen storage. The mild reaction conditions observed for quinolines permit the selective hydrogenation of numerous classes of N-, O- and S-heterocyclic compounds such as: quinoxalines, pyridines, pyrroles, indoles, isoquinoline, aciridine amine, phenanthroline, benzofuranes, and benzothiophenes.

Computer-Assisted Diagnosis of Lymph Node Metastases in Colorectal Cancers Using Transfer Learning With an Ensemble Model.

Screening of lymph node metastases in colorectal cancer (CRC) can be a cumbersome task, but it is amenable to artificial intelligence (AI)-assisted diagnostic solution. Here, we propose a deep learning-based workflow for the evaluation of CRC lymph node metastases from digitized hematoxylin and eosin-stained sections. A segmentation model was trained on 100 whole-slide images (WSIs). It achieved a Matthews correlation coefficient of 0.86 (±0.154) and an acceptable Hausdorff distance of 135.59 µm (±72.14 µm), indicating a high congruence with the ground truth. For metastasis detection, 2 models (Xception and Vision Transformer) were independently trained first on a patch-based breast cancer lymph node data set and were then fine-tuned using the CRC data set. After fine-tuning, the ensemble model showed significant improvements in the F1 score (0.797-0.949; P <.00001) and the area under the receiver operating characteristic curve (0.959-0.978; P <.00001). Four independent cohorts (3 internal and 1 external) of CRC lymph nodes were used for validation in cascading segmentation and metastasis detection models. Our approach showed excellent performance, with high sensitivity (0.995, 1.0) and specificity (0.967, 1.0) in 2 validation cohorts of adenocarcinoma cases (n = 3836 slides) when comparing slide-level labels with the ground truth (pathologist reports). Similarly, an acceptable performance was achieved in a validation cohort (n = 172 slides) with mucinous and signet-ring cell histology (sensitivity, 0.872; specificity, 0.936). The patch-based classification confidence was aggregated to overlay the potential metastatic regions within each lymph node slide for visualization. We also applied our method to a consecutive case series of lymph nodes obtained over the past 6 months at our institution (n = 217 slides). The overlays of prediction within lymph node regions matched 100% when compared with a microscope evaluation by an expert pathologist. Our results provide the basis for a computer-assisted diagnostic tool for easy and efficient lymph node screening in patients with CRC.