Δευτέρα 16 Νοεμβρίου 2020

Essentials of a Robust Deep Learning System for Diabetic Retinopathy Screening: A Systematic Literature Review

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This systematic review was performed to identify the specifics of an optimal diabetic retinopathy deep learning algorithm, by identifying the best exemplar research studies of the field, whilst highlighting potential barriers to clinical implementation of such an algorithm. Searching five electronic databases (Embase, MEDLINE, Scopus, PubMed, and the Cochrane Library) returned 747 unique records on 20 December 2019. Predetermined inclusion and exclusion criteria were applied to the search results, resulting in 15 highest-quality publications. A manual search through the reference lists of relevant review articles found from the database search was conducted, yielding no additional records. A validation dataset of the trained deep learning algorithms was used for creating a set of optimal properties for an ideal diabetic retinopathy classification algorithm. Potential limitations to the clinical implementation of such systems were identified as lack of generalizability, limited screening scope, and data sovereignty issues. It is concluded that deep learning algorithms in the context of diabetic retinopathy screening have reported impressive results. Despite this, the potential sources of limitations in such systems must be evaluated carefully. An ideal deep learning algorithm should be clinic-, clinician-, and camera-agnostic; complying with the local regulation for data sovereignty, storage, privacy, and reporting; whilst requiring minimum human input.
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Risk Factors of Cerebral Infarction and Myocardial Infarction after Carotid Endarterectomy Analyzed by Machine Learning

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Objective. The incidence of cerebral infarction and myocardial infarction is higher in patients with carotid endarterectomy (CEA). Based on the concept of coprotection of heart and brain, this study attempts to screen the related factors of early cerebral infarction and myocardial infarction after CEA with the method of machine learning to provide clinical data for the prevention of postoperative cerebral infarction and myocardial infarction. Methods. 443 patients who received CEA operation under general anesthesia within 2 years were collected as the research objects. The demographic data, previous medical history, degree of neck vascular stenosis, blood pressure at all time points during the perioperative period, the time of occlusion, whether to place the shunt, and the time of hospital stay, whether to have cerebral infarction and myocardial infarction were collected. The machine learning model was established, and stable variables were selected based on single-factor analysis. Results. The incidence of cerebral infarction was 1.4% (6/443) and that of myocardial infarction was 2.3% (10/443). The hospitalization time of patients with cerebral infarction and myocardial infarction was longer than that of the control group (8 (7, 15) days vs. 7 (5, 8) days, ). The stable related factors were screened out by the xgboost model. The importance score ( score) was as follows: average arterial pressure during occlusion was 222 points, body mass index was 159 points, average arterial pressure postoperation was 156 points, the standard deviation of systolic pressure during occlusion was 153 points, diastolic pressure during occlusion was 146 points, mean arterial pressure after entry was 143 points, systolic pressure during occlusion was 121 points, and age was 117 points. Conclusion. Eight factors, such as blood pressure, body mass index, and age, may be related to the postoperative cerebral infarction and myocardial infarction in patients with CEA. The machine learning method deserves further study.
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Separability of Acute Cerebral Infarction Lesions in CT Based Radiomics: Toward Artificial Intelligence-Assisted Diagnosis

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This study aims at analyzing the separability of acute cerebral infarction lesions which were invisible in CT. 38 patients, who were diagnosed with acute cerebral infarction and performed both CT and MRI, and 18 patients, who had no positive finding in either CT or MRI, were enrolled. Comparative studies were performed on lesion and symmetrical regions, normal brain and symmetrical regions, lesion, and normal brain regions. MRI was reconstructed and affine transformed to obtain accurate lesion position of CT. Radiomic features and information gain were introduced to capture efficient features. Finally, 10 classifiers were established with selected features to evaluate the effectiveness of analysis. 1301 radiomic features were extracted from candidate regions after registration. For lesion and their symmetr ical regions, there were 280 features with information gain greater than 0.1 and 2 features with information gain greater than 0.3. The average classification accuracy was 0.6467, and the best classification accuracy was 0.7748. For normal brain and their symmetrical regions, there were 176 features with information gain greater than 0.1, 1 feature with information gain greater than 0.2. The average classification accuracy was 0.5414, and the best classification accuracy was 0.6782. For normal brain and lesions, there were 501 features with information gain greater than 0.1 and 1 feature with information gain greater than 0.5. The average classification accuracy was 0.7480, and the best classification accuracy was 0.8694. In conclusion, the study captured significant features correlated with acute cerebral infarction and confirmed the separability of acute lesions in CT, which established foundation for further artificial intelligence-assisted CT diagnosis.
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NAC Supplementation of Hyperglycemic Rats Prevents the Development of Insulin Resistance and Improves Antioxidant Status but Only Alleviates General and Salivary Gland Oxidative Stress

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Previous studies based on animal models demonstrated that N-acetylcysteine (NAC) prevents oxidative stress and improves salivary gland function when the NAC supplementation starts simultaneously with insulin resistance (IR) induction. This study is the first to evaluate the effect of a 4-week NAC supply on the antioxidant barrier and oxidative stress in Wistar rats after six weeks of high-fat diet (HFD) intake. Redox biomarkers were evaluated in the parotid (PG) and submandibular (SMG) salivary glands and stimulated whole saliva (SWS), as well as in the plasma and serum. We demonstrated that the activity of salivary peroxidase and superoxide dismutase and total antioxidant capacity were significantly higher in PG, SMG, and SWS of IR rats treated with NAC. It appears that in PG and SMG of rats fed an HFD, N -acetylcysteine supplementation abolishes oxidative modifications to proteins (evidenced by decreased content of advanced oxidation protein products (AOPP) and advanced glycation end products (AGE)). Simultaneously, it does not reverse oxidative modifications of lipids (as seen in increased concentration of 8-isoprostanes and 4-hydroxynonenal vs. the control), although it reduces the peroxidation of salivary lipids in relation to the group fed a high-fat diet alone. NAC administration increased protein levels in PG and SMG but did not affect saliva secretion, which was significantly lower compared to the controls. To sum up, the inclusion of NAC supplementation after six weeks of HFD feeding was effective in improving the general and salivary gland antioxidant status. Nevertheless, NAC did not eliminate salivary oxidative stress and only partially prevented salivary gland dysfunction.
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Invalid Self-Assessment of Olfactory Functioning in Parkinson’s Disease Patients May Mislead the Neurologist

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Olfactory dysfunction (OD) is a prominent nonmotor symptom in Parkinson's disease (PD), and OD is a supportive diagnostic criterion for PD. Physicians often ask their patients if they have noticed a smell disorder. This study evaluates the diagnostic validity of OD self-assessment in PD. To this end, 64 PD patients and 33 age-matched healthy controls were enrolled in a study assessing subjective and objective olfactory functioning. To examine subjective olfactory abilities, first, patients and controls had to classify their olfactory sense as "impaired" or "unimpaired," comparable to a realistic situation in an outpatient setting. Second, to evaluate subjective olfactory acuity, a visual analogue scale (VAS) was used. Third, the Sniffin' Sticks test battery was used as an objective instrument to diag nose OD. Categorical olfactory self-assessment predicts the classification normosmic versus hyposmic based on the global Sniffin' Sticks score (TDI) with a sensitivity of 0.79 and a specificity of 0.45. TDI correlated significantly with the VAS (r = 0.297, ). The ROC curve analysis, using the VAS rating as a predictor for objective olfaction, revealed 42 as the best possible cutoff score with an area under the curve of 0.63. These results demonstrate that olfactory self-assessments show a low accuracy and are not suitable for the diagnosis of a smell disorder in PD. Objective measures are necessary to evaluate olfactory sense in clinical and research settings.
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Comparison of the Stability of Two Intraocular Lenses in Primary Angle-Closure Glaucoma after Phacoemulsification

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Objective. To observe the stability of intraocular lenses (IOLs) in primary angle-closure glaucoma by ultralong scan depth spectral-domain optical coherence tomography (UL-OCT) after phacoemulsification. Methods. A prospective, randomized study. 73 patients (82 eyes) with primary closed-angle glaucoma and age-related cataract were included in the study. 42 eyes were implanted with ZCB00, while 40 eyes were implanted with Softec HD after phacoemulsification. The tilt, decentration, and space between IOL and posterior capsule (IOL-PC space) were analyzed using UL-OCT at 1 week, 1 month, and 3 months after surgery. The intergroup difference was compared with the paired t-test. Result. The difference of decentration and tilt was not statistically significant (both ) both in the horizontal and vertical position s at 1 week, 1 month, and 3 months postoperatively. The horizontal IOL-PC space is 0.111 ± 0.091 mm2, 0.044 ± 0.066 mm2, and 0.055 ± 0.055 mm2 in the Softec HD group and 0.458 ± 0.488 mm2, 0.497 ± 0.363 mm2, and 0.492 ± 0.441 mm2 in the ZCB00 group. The vertical IOL-PC space is 0.102 ± 0.061 mm2, 0.037 ± 0.052 mm2, and 0.053 ± 0.079 mm2 in the Softec HD group and 0.692 ± 0.815 mm2, 0.510 ± 0.415 mm2, and 0.691 ± 0.635 mm2 in the ZCB00 group. The difference was statistically significant () both in the horizontal and vertical positions except for the first week on the horizon. The Softec HD group is smaller than the ZCB00 group. Conclusion. There is no difference in the stability of the IOL although the IOL-PC space is different. The thickness of IOL may affect the IOL-PC space.
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Systemic Inflammation Response Index Predicts Survival Outcomes in Glioblastoma Multiforme Patients Treated with Standard Stupp Protocol

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Objectives. We endeavored to retrospectively assess the prognostic merit of pretreatment systemic immune response index (SIRI) in glioblastoma multiforme (GBM) patients who underwent postoperative partial brain radiotherapy (RT) and concurrent plus adjuvant temozolomide (TMZ), namely, the Stupp protocol. Methods. The records of 181 newly diagnosed GBM patients who received the postoperative Stupp protocol were retrospectively analyzed. The SIRI value for each eligible patient was calculated by utilizing the platelet, neutrophil, and lymphocyte measures obtained on the first day of treatment: . The ideal cutoff values for SIRI connected with the progression-free- (PFS) and overall survival (OS) results were methodically searched through using the receiver operating characteristic (ROC) curve analysis. Primary and secondary end-points constituted the potential OS and PFS distinctions among the SIRI groups, respectively. Results. The ROC curve analysis labeled the ideal SIRI cutoffs at 1.74 (Area under the curve (AUC): 74.9%; sensitivity: 74.2%; specificity: 71.4%) and 1.78 (AUC: 73.6%; sensitivity: 73.1%; specificity: 70.8%) for PFS and OS status, individually. The SIRI cutoff of 1.78 of the OS status was chosen as the common cutoff for the stratification of the study population (Group 1: () and ()) and further comparative PFS and OS analyses. Comparisons between the two SIRI cohorts manifested that the cohort had altogether significantly superior median PFS (16.2 versus 6.6 months; ) and OS (22.9 versus 12.2 months; ) than its counterparts. The results of multivariate Cox regression analyses ratified the independent and significant alliance between a low SIRI and longer PFS () and OS () durations, respectively. Conclusions. Present results firmly counseled the pretreatment SIRI as a novel, sound, and independent predictor of survival outcomes in newly diagnosed GBM patients intended to undergo postoperative Stupp protocol.
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Modulated Electrohyperthermia: A New Hope for Cancer Patients

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According to the World Health Organization, the prevalence of cancer has increased worldwide. Oncological hyperthermia is a group of methods that overheat the malignant tissues locally or systematically. Nevertheless, hyperthermia is not widely accepted, primarily because of the lack of selectivity for cancer cells and because the temperature-triggered higher blood flow increases the nutrient supply to the tumor, raising the risk of metastases. These problems with classical hyperthermia led to the development of modulated electrohyperthermia (mEHT). The biophysical differences of the cancer cells and their healthy hosts allow for selective energy absorption on the membrane rafts of the plasma membrane of the tumor cells, triggering immunogenic cell death. Currently, this method is used in only 34 countries . The effectiveness of conventional oncotherapies increases when it is applied in combination with mEHT. In silico, in vitro, and in vivo preclinical research studies have all shown the extraordinary ability of mEHT to kill malignant cells. Clinical applications have improved the quality of life and the survival of patients. For these reasons, many other research studies are presently in progress worldwide. Thus, the objective of this review is to highlight the capabilities and advantages of mEHT and provide new hopes for cancer patients worldwide.
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Reducing Sugar, Total Phenolic Content, and Antioxidant Potential of Nepalese Plants

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The aim of the present study was to investigate the reducing sugar, total phenolic content, and in vitro antioxidant activity of 70% () ethanolic extract of seven medicinal plants grown in Nepal. The reducing sugar content and total phenolic content were determined by 3,5-dinitrosalicylic acid (DNSA) and the Folin–Ciocalteu method, respectively. The in vitro antioxidant activity was evaluated using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. The reducing sugar content of the studied plant samples ranged from to  mg GE/g dry extract weight and the total phenolic content ranged from to  mg GAE/g dry extract weight. The reducing sugar and total phenolic content were found highest in Ficus glaberrima. Antioxidant activity was found highest in Melastoma malabathricum (IC50 μg/mL), followed by F. glaberrima (IC50 μg/mL). A positive and significant correlation was found between (i) total phenolic content and reducing sugar content and (ii) total phenolic content and antioxidant activity. The present study is the first study for the analysis of reducing sugar content of selected plants and for the scientific exploration of F. glaberrima. The present result suggests that the various parts of these studied plants could be assumed as a rich source of biologically active compounds and considered beneficial for the food and pharmaceutical industries.
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Research Status of Differentially Expressed Noncoding RNAs in Type 2 Diabetes Patients

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Aims. Noncoding RNAs (ncRNAs) play an important role in the occurrence and development of type 2 diabetes mellitus (T2DM). This paper summarized the current evidences of the involvement microRNAs, long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) in the differential expressions and their interaction with each other in T2DM. Methods. The differentially expressed miRNAs, lncRNAs, and circRNAs in the blood circulation (plasma, serum, whole blood, and peripheral blood mononuclear cells) of patients with T2DM were found in PubMed, GCBI, and other databases. The interactions between ncRNAs were predicted based on the MiRWalk and the DIANA Tools databases. The indirect and direct target genes of lncRNAs and circRNAs were predicted based on the starBase V2.0, DIANA Tools, and LncRNA-Target databases. The n, GO and KEGG analysis on all miRNA, lncRNA, and circRNA target genes was performed using the mirPath and Cluster Profile software package in R language. The lncRNA–miRNA and circRNA–miRNA interaction diagram was constructed with Cytoscape. The aim of this investigation was to construct a mechanism diagram of lncRNA involved in the regulation of target genes on insulin signaling pathways and AGE–RAGE signaling pathways of diabetic complications. Results. A total of 317 RNAs, 283 miRNAs, and 20 lncRNAs and circRNAs were found in the circulation of T2DM. Dysregulated microRNAs and lncRNAs were found to be involved in signals related to metabolic disturbances, insulin signaling, and AGE–RAGE signaling in T2DM. In addition, lncRNAs participate in the regulation of key genes in the insulin signaling and AGE–RAGE signaling pathways through microRNAs, which leads to insulin resistance and diabetic vascular complications. Conclusion. Noncoding RNAs participate in the occurrence a nd development of type 2 diabetes and lead to its vascular complications by regulating different signaling pathways.
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A Novel STAT3-Mediated GATA6 Pathway Contributes to tert-Butylhydroquinone- (tBHQ-) Protected TNFα-Activated Vascular Cell Adhesion Molecule 1 (VCAM-1) in Vascular Endothelium

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The activation of vascular cell adhesion molecule 1 (VCAM-1) in vascular endothelial cells has been well considered implicating in the initiation and processing of atherosclerosis. Oxidative stress is mechanistically involved in proatherosclerotic cytokine-induced VCAM-1 activation. tert-Butylhydroquinone (tBHQ), a synthetic phenolic antioxidant used for preventing lipid peroxidation of food, possesses strongly antioxidant capacity against oxidative stress-induced dysfunction in various pathological process. Here, we investigated the protective role of tBHQ on tumor necrosis factor alpha- (TNFα-) induced VCAM-1 activation in both aortic endothelium of mice and cultured human vascular endothelial cells and uncovered its potential mechanisms. Our data showed that tBHQ treatment significantly reversed TNFα- induced activation of VCAM-1 at both transcriptional and protein levels. The mechanistic study revealed that inhibiting neither nuclear factor (erythroid-derived 2)-like 2 (Nrf2) nor autophagy blocked the beneficial role of tBHQ. Alternatively, tBHQ intervention markedly alleviated TNFα-increased GATA-binding protein 6 (GATA6) mRNA and protein expressions and its translocation into nucleus. Further investigation indicated that tBHQ-inhibited signal transducer and activator of transcription 3 (STAT3) but not mitogen-activated protein kinase (MAPK) pathway contributed to its protective role against VCAM-1 activation via regulating GATA6. Collectively, our data demonstrated that tBHQ prevented TNFα-activated VCAM-1 via a novel STAT3/GATA6-involved pathway. tBHQ could be a potential candidate for the prevention of proatherosclerotic cytokine-caused inflammatory response and further dysfunctions in vascular endothelium.
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Structural Brain Imaging Phenotypes of Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) Found by Hierarchical Clustering

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A hierarchical clustering algorithm was applied to magnetic resonance images (MRI) of a cohort of 751 subjects having a mild cognitive impairment (MCI), 282 subjects having received Alzheimer's disease (AD) diagnosis, and 428 normal controls (NC). MRIs were preprocessed to gray matter density maps and registered to a stereotactic space. By first rendering the gray matter density maps comparable by regressing out age, gender, and years of education, and then performing the hierarchical clustering, we found clusters displaying structural features of typical AD, cortically-driven atypical AD, limbic-predominant AD, and early-onset AD (EOAD). Among these clusters, EOAD subjects displayed marked cortical gray matter atrophy and atrophy of the precuneus. Furthermore, EOAD subjects had the highest progression r ates as measured with ADAS slopes during the longitudinal follow-up of 36 months. Striking heterogeneities in brain atrophy patterns were observed with MCI subjects. We found clusters of stable MCI, clusters of diffuse brain atrophy with fast progression, and MCI subjects displaying similar atrophy patterns as the typical or atypical AD subjects. Bidirectional differences in structural phenotypes were found with MCI subjects involving the anterior cerebellum and the frontal cortex. The diversity of the MCI subjects suggests that the structural phenotypes of MCI subjects would deserve a more detailed investigation with a significantly larger cohort. Our results demonstrate that the hierarchical agglomerative clustering method is an efficient tool in dividing a cohort of subjects with gray matter atrophy into coherent clusters manifesting different structural phenotypes.
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