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Lipid droplets and cholesterol crystals were detected using coherent anti-Stokes Raman scattering in the tissue from the ApoE-/- mice. Here, we demonstrated that OCT and MPM, which are fast and precise contactless imaging approaches, are suitable for defining early morphological and structural alterations of sclerotic murine aortic valves.Automatic representation learning of key entities in electronic health record (EHR) data is a critical step for healthcare data mining that turns heterogeneous medical records into structured and actionable information. Here we propose ME2Vec, an algorithmic framework for learning continuous low-dimensional embedding vectors of the most common entities in EHR medical services, doctors, and patients. ME2Vec features a hierarchical structure that encapsulates different node embedding schemes to cater for the unique characteristic of each medical entity. To embed medical services, we employ a biased-random-walk-based node embedding that leverages the irregular time intervals of medical services in EHR to embody their relative importance. To embed doctors and patients, we adhere to the principle "it's what you do that defines you" and derive their embeddings based on their interactions with other types of entities through graph neural network and proximity-preserving network embedding, respectively. Using real-world clinical data, we demonstrate the efficacy of ME2Vec over competitive baselines on diagnosis prediction, readmission prediction, as well as recommending doctors to patients based on their medical conditions. In addition, medical service embeddings pretrained using ME2Vec can substantially improve the performance of sequential models in predicting patients clinical outcomes. Overall, ME2Vec can serve as a general-purpose representation learning algorithm for EHR data and benefit various downstream tasks in terms of both performance and interpretability.Molecular evolution is an important step in the development of therapeutic antibodies. However, the current method of affinity maturation is overly costly and labor-intensive because of the repetitive mutation experiments needed to adequately explore sequence space. Here, we employed a long short term memory network (LSTM)-a widely used deep generative model-based sequence generation and prioritization procedure to efficiently discover antibody sequences with higher affinity. We applied our method to the affinity maturation of antibodies against kynurenine, which is a metabolite related to the niacin synthesis pathway. Kynurenine binding sequences were enriched through phage display panning using a kynurenine-binding oriented human synthetic Fab library. We defined binding antibodies using a sequence repertoire from the NGS data to train the LSTM model. We confirmed that likelihood of generated sequences from a trained LSTM correlated well with binding affinity. The affinity of generated sequences are over 1800-fold higher than that of the parental clone. Moreover, compared to frequency based screening using the same dataset, our machine learning approach generated sequences with greater affinity.Ambulatory blood pressure monitoring (ABPM) can produce many variables, of which the lowest nocturnal systolic blood pressure (LNSBP) currently used in calculating morning surge is occasionally overlooked in recent kidney studies compared with other ABPM parameters. We explored the clinical effects of LNSBP in elderly patients with chronic kidney disease (CKD) in a multicenter, observational cohort study. A total of 356 elderly patients with CKD from 19 clinics were included in this analysis. We used multiple logistic regression and survival analyses to assess the associations between the lowest nocturnal systolic blood pressure and heavy proteinuria and kidney disease outcomes, respectively. The median age was 66 years, and 66.6% were men. The median eGFR was 49.2 ml/min/1.73 m2. Multivariate logistic regression analysis demonstrated that LNSBP (OR 1.24; 95% CI 1.10-1.39; P  less then  0.001; per 10 mmHg) was associated with heavy proteinuria. During the median follow-up of 23 months, 70 patients (19.7%) had a composite outcome; of these, 25 initiated dialysis, 25 had 40% eGFR loss, and 20 died. Cox analysis showed that the renal risk of LNSBP for CKD outcomes remained significant even after adjusting for background factors, including age, sex, medical history of hypertension and diabetes, smoking status, eGFR, 24-h proteinuria, and etiology of CKD (HR 1.18; 95% CI 1.06-1.32; P = 0.002; per 10 mmHg). [https://www.selleckchem.com/products/PP242.html selleck chemicals] Concentrating on LNSBP could be valuable in guiding antihypertensive treatment to control heavy proteinuria and improve renal prognosis in elderly CKD patients.Stereotactic body radiotherapy (SBRT) applies high doses and requires advanced techniques to spare surrounding tissue in the presence of organ motion. In this work patient individual phase gating is investigated. We studied peripheral and central primary lung tumors. The internal target volume (ITV) was defined including different numbers of phases picked from a 4D Computed tomography (CT) defining the gating window (gw). Planning target volume (PTV) reductions depending on the gw were analyzed. A treatment plan was calculated on a reference phase CT (rCT) and the dose for each breathing phase was calculated and accumulated on the rCT. We compared the dosimetric results with the dose calculated when all breathing phases were included for ITV definition. GWs including 1 to 10 breathing phases were analyzed. We found PTV reductions up to 38.4%. The mean reduction of the lung volume receiving 20 Gy due to gating was found to be 25.7% for peripheral tumors and 16.7% for central tumors. Gating considerably reduced esophageal doses. However, we found that simple reduction of the gw does not necessarily influence the dose in a clinically relevant range. Thus, we suggest a patient individual definition of the breathing phases included within the gw.This report suggests a method of enhancing the sensitivity of chemifluorescence-based ELISA, using photooxidation-induced fluorescence amplification (PIFA). The PIFA utilized autocatalytic photooxidation of the chemifluorescent substrate, 10-acetyl 3,7-dihydroxyphenoxazine (ADHP, Amplex Red) to amplify the fluorescent product resorufin, initially oxidized by horse radish peroxidase (HRP). As the amplification rate is proportional to the initial level of resorufin, the level of antigen labeled by HRP is quantified by analyzing the profile of fluorescence intensity. The normalized profile was interpolated into an autocatalysis model, and the rate of increase at half-maximum time was quantified by the use of an amplification index (AI). The lower limit of detection, for resorufin or HRP, was less than one-tenth that of the plate reader. It requires only slight modification of the fluorescence reader and is fully compatible with conventional or commercial ELISA. When it is applied to a commercial ELISA kit for the detection of amyloid beta, it is verified that the PIFA assay enhanced the detection sensitivity by more than a factor of 10 and was compatible with a conventional 96-well ELISA assay kit.