Enhance Representation Learning of Clinical Narrative with Neural Networks for Clinical Predictive Modeling

Medicine is undergoing a technological revolution. Understanding human health from clinical data has major challenges from technical and practical perspectives, thus prompting methods that understand large, complex, and noisy data. These methods are particularly necessary for natural language data from clinical narratives/notes, which contain some of the richest information on a patient. Meanwhile, deep neural networks have achieved superior performance in a wide variety of natural language processing (NLP) tasks because of their capacity to encode meaningful but abstract representations and learn the entire task end-to-end. In this thesis, I investigate representation learning of clinical narratives with deep neural networks through a number of tasks ranging from clinical concept extraction, clinical note modeling, and patient-level language representation. I present methods utilizing representation learning with neural networks to support understanding of clinical text documents. I first introduce the notion of representation learning from natural language processing and patient data modeling. Then, I investigate word-level representation learning to improve clinical concept extraction from clinical notes. I present two works on learning word representations and evaluate them to extract important concepts from clinical notes. The first study focuses on cancer-related information, and the second study evaluates shared-task data. The aims of these two studies are to automatically extract important entities from clinical notes. Next, I present a series of deep neural networks to encode hierarchical, longitudinal, and contextual information for modeling a series of clinical notes. I also evaluate the models by predicting clinical outcomes of interest, including mortality, length of stay, and phenotype predictions. Finally, I propose a novel representation learning architecture to develop a generalized and transferable language representation at the patient level. I also identify pre-training tasks appropriate for constructing a generalizable language representation. The main focus is to improve predictive performance of phenotypes with limited data, a challenging task due to a lack of data. Overall, this dissertation addresses issues in natural language processing for medicine, including clinical text classification and modeling. These studies show major barriers to understanding large-scale clinical notes. It is believed that developing deep representation learning methods for distilling enormous amounts of heterogeneous data into patient-level language representations will improve evidence-based clinical understanding. The approach to solving these issues by learning representations could be used across clinical applications despite noisy data. I conclude that considering different linguistic components in natural language and sequential information between clinical events is important. Such results have implications beyond the immediate context of predictions and further suggest future directions for clinical machine learning research to improve clinical outcomes. This could be a starting point for future phenotyping methods based on natural language processing that construct patient-level language representations to improve clinical predictions. While significant progress has been made, many open questions remain, so I will highlight a few works to demonstrate promising directions

Identification of the chemical components of ethanol extract of Chenopodium ambrosioides and evaluation of their in vitro antioxidant and anti tumor activities

Purpose: To determine the characteristic chemical components of the ethanol extract of Chenopodium ambrosioides and evaluate their antioxidant and anti-tumor effects in vitro. Methods: The plant powder (5 g) was extracted with 1 L of 80 % ethanol at room temperature for 45 min, and then placed at 60 oC at varying microwave power and duration to obtain optimal extraction conditions. Characteristic chemical components were detected using ultra-high performance liquid chromatography quadrupole time of flight mass spectrometry (UPLC-Q-TOF-MS/MS). Kaempferitrin was isolated from the 80 % ethanol extract using a D101 macroporous resin column, and its content was assessed by high performance liquid chromatography (HPLC). The antioxidant effect of kaempferitrin was evaluated by its ability to scavenge 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-azinobis-(3-ethylbenzthiazoline-6-sulphonate) (ABTS) radicals, while its anti-proliferation activity in human liver cancer cells SMMC-7721 was determined using cell counting kit-8 (CCK-8) reagent. Results: Three characteristic components of ethanol extract of C. ambrosioides were obtained, namely, kaempferitrin, kaempferol-3-O-apigenin-7-O-rhamnoside and kaempferol-3-O-acetylapigenin-7-O-rhamnoside. Kaempferitrin was shown to possess strong DPPH radical and moderate ABTS radical scavenging activities. Kaempferitrin significantly inhibited the proliferation of SMMC-7721 cells at doses of 4 and 8 μg/mL, with half-maximal concentration (IC50) of 0.38 μM (p < 0.05). Conclusion: Kaempferitrin extracted from C. ambrosioides has antioxidant and anti-tumor activities. The results reported here indicate that C. ambrosioides may have potential use in herbal medicine practice

Concomitant valve surgery is associated with worse outcomes in surgical treatments of post-infarction ventricular aneurysm

ObjectiveTo evaluate the impact of concomitant valve surgery on the prognosis of patients who experienced coronary artery bypass graft (CABG) with/without ventricular reconstruction for the ventricular aneurysm.MethodsIn our department, 354 patients underwent CABG with/without ventricular reconstruction for a ventricular aneurysm from July 23rd, 2000 to December 23rd, 2022. A total of 77 patients received concomitant valve surgery, 37 of whom underwent replacement, and 40 of whom underwent repair. The baseline characteristics, prognostic, and follow-up information were statically analyzed. Univariate and multivariate Cox regression analyses were applied to identify the risk factors of long-term outcomes.ResultsCompared with patients who did not undergo valvular surgery, patients who experienced concomitant valve surgical treatments had a significantly lower survival rate (p = 0.00022) and a longer total mechanical ventilation time. Subgroup analysis indicated that the options of repair or replacement exhibited no statistically significant difference in postoperative mortality (p = 0.44) and prognosis. The multivariate Cox regression analysis suggested that the pre-operative cholesterol level (HR = 1.68), postoperative IABP (HR = 6.29), NYHA level (HR = 2.84), and pre-operative triglyceride level (HR = 1.09) were independent and significant predictors for overall all-cause mortality after surgery.ConclusionConcomitant valve surgery was considerably related to a higher risk of postoperative mortality in patients with post-infarction ventricle aneurysms who underwent surgical treatments. No significant difference in the prognosis outcomes was observed between the operating methods of repair or replacement valve surgery

Royal Jelly Alleviates Cognitive Deficits and β-Amyloid Accumulation in APP/PS1 Mouse Model Via Activation of the cAMP/PKA/CREB/BDNF Pathway and Inhibition of Neuronal Apoptosis

Alzheimer’s disease (AD) is characterized clinically by progressive cognitive decline and pathologically by the accumulation of amyloid-β (Aβ) in the brain. Royal jelly (RJ), a secretion of honeybee hypopharyngeal and mandibular glands, has previously been shown to have anti-aging and neuromodulatory activities. In this study, we discovered that 3 months of RJ treatment substantially ameliorated behavioral deficits of APP/PS1 mice in the Morris Water Maze (MWM) test and step-down passive avoidance test. Our data also showed that RJ significantly diminished amyloid plaque pathology in APP/PS1 mice. Furthermore, RJ alleviated c-Jun N-terminal kinase (JNK) phosphorylation-induced neuronal apoptosis by suppressing oxidative stress. Importantly, hippocampal cyclic adenosine monophosphate (cAMP), p-PKA, p-CREB and BDNF levels were significantly increased in the APP/PS1 mice after RJ treatment, indicating that the cAMP/PKA/CREB/BDNF pathway might be related to the ameliorative effect of RJ on cognitive decline. Collectively, these results provide a scientific basis for using RJ as a functional food for targeting AD pathology

Postoperative hypothalamic-pituitary dysfunction and long-term hormone replacement in patients with childhood-onset craniopharyngioma

ObjectiveHypothalamic-pituitary axis dysfunction is a common complication in post-operative craniopharyngioma(CP) patients, and it greatly impacts the long-term quality of life of such patients. To better understand the effects of postoperative hypothalamic-pituitary dysfunction and long-term hormone replacement therapy in patients with childhood CP, we assessed approximately 200 patients with childhood-onset CP postoperatively.MethodsClinical details of patients with childhood-onset CP who underwent sellar tumor resection in Beijing Children’s Hospital and Beijing Tiantan Hospital from 2018 to 2019 were retrieved retrospectively. The participants were followed up to assess the effects of post-operative long-term hormone replacement therapy and assess the tumor recurrence rate.ResultsThe median age of admission was 8.1 (1.8, 14.3) years. Headache (45.5%), visual impairment (39.5%), and nausea (33.0%) were the most common clinical manifestations. ACP accounted for 95% of all CP cases. The incidence of central adrenal insufficiency and central hypothyroidism within the first week after surgery was 56.2% and 70.3%, respectively. At the same time 85.5% of the patients required at least one dose of desmopressin to control urine output. Total survival and tumor recurrence rates were 98.6% and 26.1%, respectively, with a median follow-up time of 29.7 (19.0, 40.3) months. During the follow-up period, 28.1% patients met the diagnostic criteria for short stature, while 54.4% fit the criteria for obesity. In addition, 94.4% of the patients were taking at least one kind of hormone substitution, and 74.7% were taking three or more. The prevalence of levothyroxine, glucocorticoid, desmopressin, and growth hormone replacement therapy was 87.3%, 77.5%, 78.9% and 31.0%, respectively. The proportion of patients treated with the substitutive combination of levothyroxine, hydrocortisone, and desmopressin was 54.9%.ConclusionThis study is a large-sample systematic postoperative endocrine function evaluation of patients with childhood-onset CP. Due to the high prevalence of post-operative hypothalamic-pituitary dysfunction, patients with CP usually require long-term multiple hormone substitution therapy. Individualized management and accurate hormone replacement dosage for postoperative childhood-onset CP patients are of great importance