Boundary-Repairing Dual-Path Network for Retinal Layer Segmentation in OCT Image with Pigment Epithelial Detachment.

Automatic retinal layer segmentation in optical coherence tomography (OCT) images is crucial for the diagnosis of ocular diseases. Currently, automatic retinal layer segmentation works well with normal OCT images. However, pigment epithelial detachment (PED) dramatically alters the retinal structure, causing blurred boundaries and partial disappearance of the Bruch's Membrane (BM), thus posing challenges to the segmentation. To tackle these problems, we propose a novel dual-path U-shaped network for simultaneous layer segmentation and boundary regression. This network first designs a feature interaction fusion (FIF) module to strengthen the boundary shape constraints in the layer path. To address the challenge posed by partial BM disappearance and boundary-blurring, we propose a layer boundary repair (LBR) module. This module aims to use contrastive loss to enhance the confidence of blurred boundary regions and refine the segmentation of layer boundaries through the re-prediction head. In addition, we introduce a novel bilateral threshold distance map (BTDM) designed for the boundary path. The BTDM serves to emphasize information within boundary regions. This map, combined with the updated probability map, culminates in topology-guaranteed segmentation results achieved through a topology correction (TC) module. We investigated the proposed network on two severely deformed datasets (i.e., OCTA-500 and Aier-PED) and one slightly deformed dataset (i.e., DUKE). The proposed method achieves an average Dice score of 94.26% on the OCTA-500 dataset, which was 1.5% higher than BAU-Net and outperformed other methods. In the DUKE and Aier-PED datasets, the proposed method achieved average Dice scores of 91.65% and 95.75%, respectively.

Combined scRNAseq and Bulk RNAseq Analysis to Reveal the Dual Roles of Oxidative Stress-Related Genes in Acute Myeloid Leukemia.

Background: Oxidative stress (OS) can either lead to leukemogenesis or induce tumor cell death by inflammation and immune response accompanying the process of OS through chemotherapy. However, previous studies mainly focus on the level of OS state and the salient factors leading to tumorigenesis and progression of acute myeloid leukemia (AML), and nothing has been done to distinguish the OS-related genes with different functions. Method: First, we downloaded single-cell RNA sequencing (scRNAseq) and bulk RNA sequencing (RNAseq) data from public databases and evaluated the oxidative stress functions between leukemia cells and normal cells by the ssGSEA algorithm. Then, we used machine learning methods to screen out OS gene set A related to the occurrence and prognosis of AML and OS gene set B related to treatment in leukemia stem cells (LSCs) like population (HSC-like). Furthermore, we screened out the hub genes in the above two gene sets and used them to identify molecular subclasses and construct a model for predicting therapy response. Results: Leukemia cells have different OS functions compared to normal cells and significant OS functional changes before and after chemotherapy. Two different clusters in gene set A were identified, which showed different biological properties and clinical relevance. The sensitive model for predicting therapy response based on gene set B demonstrated predictive accuracy by ROC and internal validation. Conclusion: We combined scRNAseq and bulk RNAseq data to construct two different transcriptomic profiles to reveal the different roles of OS-related genes involved in AML oncogenesis and chemotherapy resistance, which might provide important insights into the mechanism of OS-related genes in the pathogenesis and drug resistance of AML.

Beyond top-k: knowledge reasoning for multi-answer temporal questions based on revalidation framework.

Answer sorting and filtering are two closely related steps for determining the answer to a question. Answer sorting is designed to produce an ordered list of scores based on Top-k and contextual criteria. Answer filtering optimizes the selection according to other criteria, such as the range of time constraints the user expects. However, the unclear number of answers and time constraints, as well as the high score of false positive results, indicate that the traditional sorting and selection methods cannot guarantee the quality of answers to multi-answer questions. Therefore, this study proposes MATQA, a component based on multi-answer temporal question reasoning, using a re-validation framework to convert the Top-k answer list output by the QA system into a clear number of answer combinations, and a new multi-answer based evaluation index is proposed for this output form. First, the highly correlated subgraph is selected by calculating the scores of the boot node and the related fact node. Second, the subgraph attention inference module is introduced to determine the initial answer with the highest probability. Finally, the alternative answers are clustered at the semantic level and the time constraint level. Meanwhile, the candidate answers with similar types and high scores but do not satisfy the semantic constraints or the time constraints are eliminated to ensure the number and accuracy of final answers. Experiments on the multi-answer TimeQuestions dataset demonstrate the effectiveness of the answer combinations output by MATQA.

Contrastive uncertainty based biomarkers detection in retinal optical coherence tomography images.

Objective.Retinal biomarker in optical coherence tomography (OCT) images plays a key guiding role in the follow-up diagnosis and clinical treatment of eye diseases. Although there have been many deep learning methods to automatically process retinal biomarker, the detection of retinal biomarkers is still a great challenge due to the similar characteristics to normal tissue, large changes in size and shape and fuzzy boundary of different types of biomarkers. To overcome these challenges, a novel contrastive uncertainty network (CUNet) is proposed for retinal biomarkers detection in OCT images.Approach.In CUNet, proposal contrastive learning is designed to enhance the feature representation of retinal biomarkers, aiming at boosting the discrimination ability of network between different types of retinal biomarkers. Furthermore, we proposed bounding box uncertainty and combined it with the traditional bounding box regression, thereby improving the sensitivity of the network to the fuzzy boundaries of retinal biomarkers, and to obtain a better localization result.Main results.Comprehensive experiments are conducted to evaluate the performance of the proposed CUNet. The experimental results on two datasets show that our proposed method achieves good detection performance compared with other detection methods.Significance.We propose a method for retinal biomarker detection trained by bounding box labels. The proposal contrastive learning and bounding box uncertainty are used to improve the detection of retinal biomarkers. The method is designed to help reduce the amount of work doctors have to do to detect retinal diseases.

Spammer detection using multi-classifier information fusion based on evidential reasoning rule.

Spammer detection is essentially a process of judging the authenticity of users, and thus can be regarded as a classification problem. In order to improve the classification performance, multi-classifier information fusion is usually used to realize the automatic detection of spammers by utilizing the information from multiple classifiers. However, the existing fusion strategies do not reasonably take the uncertainty from the results of different classifiers (views) into account, and the relative importance and reliability of each classifier are not strictly distinguished. Therefore, in order to detect spammers effectively, this paper develops a novel multi-classifier information fusion model based on the evidential reasoning (ER) rule. Firstly, according to the user's characterization strategy, the base classifiers are constructed through the profile-based, content-based and behavior-based. Then, the idea of multi-classifier fusion is combined with the ER rule, and the results of base classifiers are aggregated by considering their weights and reliabilities. Extensive experimental results on the real-world dataset verify the effectiveness of the proposed model.

A CNN-based misleading video detection model.

Videos, especially short videos, have become an increasingly important source of information in these years. However, many videos spread on video sharing platforms are misleading, which have negative social impacts. Therefore, it is necessary to find methods to automatically identify misleading videos. In this paper, three categories of features (content features, uploader features and environment features) are proposed to construct a convolutional neural network (CNN) for misleading video detection. The experiment showed that all the three proposed categories of features play a vital role in detecting misleading videos. Our proposed approach that combines three categories of features achieved the best performance with the accuracy of 0.90 and the F1 score of 0.89. It also outperformed other baselines such as SVM, k-NN, decision tree and random forest models by more than 22%.

Defining Diffuse Large B-Cell Lymphoma Immunotypes by CD8+ T Cells and Natural Killer Cells.

BACKGROUND: There is a poor prognosis for diffuse large B-cell lymphoma (DLBCL), one of the most common types of non-Hodgkin lymphoma (NHL). Through gene expression profiles, this study intends to reveal potential subtypes among patients with DLBCL by evaluating their prognostic impact on immune cells. METHODS: Immune subtypes were developed based on CD8+ T cells and natural killer cells calculated from gene expression profiles. The comparison of prognoses and enriched pathways was made between immune subtypes. Following this validation step, samples from the independent data set were analyzed to determine the correlation between immune subtype and prognosis and immune checkpoint blockade (ICB) response. To provide a model to predict the DLBCL immune subtypes, machine learning methods were used. The virtual screening and molecular docking were adopted to identify small molecules to target the immune subtype biomarkers. RESULTS: A training data set containing 432 DLBCL samples from five data sets and a testing dataset containing 420 DLBCL samples from GSE10846 were used to develop and validate immune subtypes. There were two novel immune subtypes identified in this study: an inflamed subtype (IS) and a noninflamed subtype (NIS). When compared with NIS, IS was associated with higher levels of immune cells and a better prognosis for immunotherapy. Based on the random forest algorithm, a robust machine learning model has been established by 12 hub genes, and the area under the curve (AUC) value is 0.948. Three small molecules were selected to target NIS biomarkers, including VGF, RAD54L, and FKBP8. CONCLUSION: This study assessed immune cells as prognostic factors in DLBCL, constructed an immune subtype that could be used to identify patients who would benefit from ICB, and constructed a model to predict the immune subtype.

Detection of fake-video uploaders on social media using Naive Bayesian model with social cues.

With the rapid development of the Internet, the wide circulation of disinformation has considerably disrupted the search and recognition of information. Despite intensive research devoted to fake text detection, studies on fake short videos that inundate the Internet are rare. Fake videos, because of their quick transmission and broad reach, can increase misunderstanding, impact decision-making, and lead to irrevocable losses. Therefore, it is important to detect fake videos that mislead users on the Internet. Since it is difficult to detect fake videos directly, we probed the detection of fake video uploaders in this study with a vision to provide a basis for the detection of fake videos. Specifically, a dataset consisting of 450 uploaders of videos on diabetes and traditional Chinese medicine was constructed, five features of the fake video uploaders were proposed, and a Naive Bayesian model was built. Through experiments, the optimal feature combination was identified, and the proposed model reached a maximum accuracy of 70.7%.

Patterns of eHealth Website User Engagement Based on Cross-site Clickstream Data: Correlational Study.

BACKGROUND: User engagement is a key performance variable for eHealth websites. However, most existing studies on user engagement either focus on a single website or depend on survey data. To date, we still lack an overview of user engagement on multiple eHealth websites derived from objective data. Therefore, it is relevant to provide a holistic view of user engagement on multiple eHealth websites based on cross-site clickstream data. OBJECTIVE: This study aims to describe the patterns of user engagement on eHealth websites and investigate how platforms, channels, sex, and income influence user engagement on eHealth websites. METHODS: The data used in this study were the clickstream data of 1095 mobile users, which were obtained from a large telecom company in Shanghai, China. The observation period covered 8 months (January 2017 to August 2017). Descriptive statistics, two-tailed t tests, and an analysis of variance were used for data analysis. RESULTS: The medical category accounted for most of the market share of eHealth website visits (134,009/184,826, 72.51%), followed by the lifestyle category (46,870/184,826, 25.36%). The e-pharmacy category had the smallest market share, accounting for only 2.14% (3947/184,826) of the total visits. eHealth websites were characterized by very low visit penetration and relatively high user penetration. The distribution of engagement intensity followed a power law distribution. Visits to eHealth websites were highly concentrated. User engagement was generally high on weekdays but low on weekends. Furthermore, user engagement gradually increased from morning to noon. After noon, user engagement declined until it reached its lowest level at midnight. Lifestyle websites, followed by medical websites, had the highest customer loyalty. e-Pharmacy websites had the lowest customer loyalty. Popular eHealth websites, such as medical websites, can effectively provide referral traffic for lifestyle and e-pharmacy websites. However, the opposite is also true. Android users were more engaged in eHealth websites than iOS users. The engagement volume of app users was 4.85 times that of browser users, and the engagement intensity of app users was 4.22 times that of browser users. Male users had a higher engagement intensity than female users. Income negatively moderated the influence that platforms (Android vs iOS) had on user engagement. Low-income Android users were the most engaged in eHealth websites. Conversely, low-income iOS users were the least engaged in eHealth websites. CONCLUSIONS: Clickstream data provide a new way to derive an overview of user engagement patterns on eHealth websites and investigate the influence that various factors (eg, platform, channel, sex, and income) have on engagement behavior. Compared with self-reported data from a questionnaire, cross-site clickstream data are more objective, accurate, and appropriate for pattern discovery. Many user engagement patterns and findings regarding the influential factors revealed by cross-site clickstream data have not been previously reported.

An empirical investigation of trust in AI in a Chinese petrochemical enterprise based on institutional theory.

Despite its considerable potential in the manufacturing industry, the application of artificial intelligence (AI) in the industry still faces the challenge of insufficient trust. Since AI is a black box with operations that ordinary users have difficulty understanding, users in organizations rely on institutional cues to make decisions about their trust in AI. Therefore, this study investigates trust in AI in the manufacturing industry from an institutional perspective. We identify three institutional dimensions from institutional theory and conceptualize them as management commitment (regulative dimension at the organizational level), authoritarian leadership (normative dimension at the group level), and trust in the AI promoter (cognitive dimension at the individual level). We hypothesize that all three institutional dimensions have positive effects on trust in AI. In addition, we propose hypotheses regarding the moderating effects of AI self-efficacy on these three institutional dimensions. A survey was conducted in a large petrochemical enterprise in eastern China just after the company had launched an AI-based diagnostics system for fault detection and isolation in process equipment service. The results indicate that management commitment, authoritarian leadership, and trust in the AI promoter are all positively related to trust in AI. Moreover, the effect of management commitment and trust in the AI promoter are strengthened when users have high AI self-efficacy. The findings of this study provide suggestions for academics and managers with respect to promoting users' trust in AI in the manufacturing industry.

Extramedullary Blast Crisis of Chronic Myelogenous Leukemia With a Skin Lesion: A Case Report and Literature Review.

ABSTRACT: Extramedullary blast crisis of chronic myeloid leukemia (CML) is defined as extramedullary disease composed of blasts regardless of the proliferation of blasts in the bone marrow. The commonly affected sites are the lymph node, central nervous system, bone, skin, and soft tissue. However, skin infiltration of CML patients as the initial presentation while their bone marrow is still in the chronic phase is extremely rare. In this article, we present a case of a 51-year-old woman who was admitted to our hospital complaining about a skin nodule in her right calf and easy fatigability for 1 week. The peripheral blood and bone marrow analysis both supported the diagnosis of CML in the chronic phase, whereas the excisional biopsy specimen obtained from her right calf showed immature cells infiltration, and fluorescence in situ hybridization test was positive for p210 BCR/ABL1 gene rearrangement. Based on the presence of extramedullary myeloid sarcoma, the patient was diagnosed with extramedullary myeloid blast crisis of CML despite the chronic phase in the bone marrow.

[Clinical Characteristics of Patients with Myeloid Sarcoma].

OBJECTIVE: To investigate the clinical characteristics, diagnosis and treatment methods of patients with myeloid sarcoma(MS)． Methods: The clinical data, laboratory examination, clinical pathology and treatment methods of 15 patients with MS treated in the First Affiliated Hospital of Wannan Medical College from June 2012 to January 2020 were retrospectively analyzed. RESULTS: Among the 15 cases of MS, including eight males and seven females, the middle age of patients were 53（19 to 72）. Among the 15 patients with MS, 4 showed solitary MS, while 11 showed secondary MS. Immunohistochemical results showed that MPO+（12/15）、CD68+（3/6）、Lys+（3/3）、CD34+（6/14）、TdT+（0/9）、CD43+（13/13）、CD117+（6/10）、CD15+（7/10）、CD3+（1/15）、CD20+（0/15）. 6 of 13 patients were survival till follow-up date．The median overall survival (OS) time was 16 months (1-88 months)．Conclusion: Myeloid sarcoma is rare and often secondary from acute myeloid leukemia(AML) and chronic myeogenous leukemia(CML). Isolated MS can easily be misdiagnosed as lymphoma. Treatment response should be evaluated in combination with bone marrow examination, PET/CT and other imagines．Systematic chemotherapy and hematopoietic stem cell transplantation are the main method to treat MS.

Impact of timing on in-patient outcomes of complete repair of tetralogy of Fallot in infancy: an analysis of the United States National Inpatient 2005-2011 database.

BACKGROUND: This study aimed to investigate whether age at complete repair of tetralogy of Fallot (TOF) impacts postoperative morbidity and length of hospital stay in infants less than 365 days of age. METHODS: The United States Nationwide Inpatient Sample was searched for infants 0-365 days of age that underwent complete repair of TOF between 2005 and 2011. Patients were categorized based on age at time of repair: 0-30 days; 31-90 days; 91-180 days; > 180 days. RESULTS: A total of 1112 infants were included in the study. Multivariate analysis showed the risk of postoperative complications was 40% lower in infants ≥91 days old at the time of repair as compared to those ≤30 days old. In addition, children > 30 days old at the time of repair had a significantly shorter length of hospital stay than those aged ≤30 days. In the subgroup with elective repair, older age was associated with a shorter length of hospital stay as compared to those ≤30 days old at repair, while association between age at complete repair of TOF and postoperative complication was not significant among the groups after adjusting for confounders. CONCLUSIONS: In children < 1 year old, postoperative complications and length of hospital stay are affected by the timing of complete repair of TOF.

Comparison of two methods for hemodynamic assessment in children with tetralogy of Fallot after radical surgery / 中国胸心血管外科临床杂志

@#Objective To explore the hemodynamic assessment after radical surgery in children with tetralogy of Fallot (TOF) by both echocardiography and Mostcare monitor. Methods Clinical data of 63 children with TOF who underwent radical surgery in our hospital from February 2016 to June 2018 were retrospectively analyzed, including 34 males and 29 females, aged 6-24 (9.82±5.77) months. There were 19 patients undergoing transannular patch reconstruction of the right ventricular outflow tract (a transannular patch group) while 44 patients retained the pulmonary valve annulus (a non-transannular patch group) . The echocardiography and Mostcare monitor parameters were recorded and brain natriuretic peptide was tested at the time points of 0, 8, 12, 24 and 48 hours after operation (T 0, T 1, T 2, T 4) to analyze their correlations and the change trend at different time points after radical surgery. Results The left ventricular ejection fraction at T 1 (43.49%±3.82%) was lower than that at T 0 (48.29%±4.55%), T 2 (45.83%±3.69%), T 3 (53.76%±4.43%) and T 4 (60.54%±3.23%, P<0.05). The cardiac index at T 1 (1.85±0.35 L·min−1·m−2) was lower than that at T 0 (2.11±0.38 L·min−1·m−2), T 2 (2.07±0.36 L·min−1·m−2), T 3 (2.42±0.37 L·min−1·m−2) and T 4 (2.82±0.42 L·min−1·m−2, P<0.05). The cardiac circulation efficiency at T1 (0.19±0.05) was lower than that at T 0 (0.22±0.06), T 2 (0.22±0.05), T 3 (0.28±0.06) and T 4 (0.34±0.06, P<0.05). The right ventricular two-chambers view fraction area change at T 1 (23.17%±3.11%) was lower than that at T 0 (25.81%±3.74%), T 2 (25.38%±3.43%), T 3 (30.60%±4.50%) and T 4 (36.94%±5.85%, P<0.05). The pulse pressure variability was the highest at T 0 (18.76%±3.58%), followed by T 1 (14.81%±3.32%), T 2 (12.44%±2.94%), T 3 (10.39%±2.96%) and T 4 (9.18%±1.92%, P<0.05). The blood brain natriuretic peptide was higher at T 1 (846.67±362.95 pg/ml) than that at T 0 (42.60±18.06 pg/ml), T 2 (730.95±351.09 pg/ml), T 3 (510.98±290.39 pg/ml) and T 4 (364.41±243.56 pg/ml, P<0.05). There was no significant difference in left ventricular ejection fraction, cardiac circulation efficiency and heart index between the two groups (P>0.05). The right ventricular two-chambers view fraction area change of the transannular patch group was significantly lower than that of the nontransannular patch group at each time point (P<0.05). The blood brain natriuretic peptide and pulse pressure variability of the transannular patch group were significantly higher than those of the non-transannular patch group (P<0.05). Left ventricular ejection fraction was positively correlated with cardiac index (r=0.637, P=0.001) and cardiac circulation efficiency (r=0.462, P=0.001) while was significantly negatively correlated with blood brain natriuretic peptide (r=–0.419, P=0.001). Conclusion Both methods can accurately reflect the state of cardiac function. Mostcare monitor has a good consistency with echocardiography. Using transannular patch to recontribute right ventricular outflow tract in operation has more influence on right ventricular systolic function. The Mostcare monitor can guide the hemodynamic management after surgery in real time, continuously and accurately.

Next generation sequencing identified novel heterozygous nonsense mutation in CNGB1 gene associated with retinitis pigmentosa in a Chinese patient.

Retinitis pigmentosa (RP) is a severe hereditary eye disease characterized by progressive degeneration of photoreceptors and subsequent loss of vision. Retinitis pigmentosa (RP) is a clinically and genetically heterogeneous group of retinal diseases. Germline mutations of CNGB1 is associated with retinitis pigmentosa. We have identified and investigated a 34-year-old Chinese man with markedly have night vision blindness and loss of midperipheral visual field. The proband also lose his far peripheral visual field and also central vision. Proband's retinal pigment deposits visible on fundus examination and primary loss of rod photoreceptor cells followed by secondary loss of cone photoreceptors. Target exome capture based next generation sequencing and Sanger sequencing identified novel nonsense mutation, c.1917G>A and a reported mutation, c.2361C>A, in the CNGB1 gene. Both the nonsense mutations are predicted to lead to the formation of a premature stop codon which finally results into formation of truncated CNGB1 protein product which finally predicted to be disease causing. According to the variant classification guidelines of ACMG, these two variants are categorized as "likely pathogenic" variants. Our findings expand the mutational spectra of CNGB1 and are valuable in the mutation-based pre- and post-natal screening and genetic diagnosis for retinitis pigmentosa.

[Quantitative assess the efficacy of congenital idiopathic nystagmus surgery by digital eye tracker].

OBJECTIVE: To evaluate the feasibility of independently developed digital eye tracker in determining the efficacy of congenital idiopathic nystagmus (CIN) surgery. METHODS: Aprospective selfpairing study. The surgical efficacy was evaluated by independently developed eye tracker in 16 CIN patients. The null zone and the frequency, amplitude, intensity of nystagmus in various gazing position were recorded with eye tracker pre and post operatively. The consistency of null zone determined by digital eye tracker and clinical investigation were evaluated. The preoperative and postoperative rectification of horizontal and vertical nystagmus in the horizontal direction of individual patient were compared by paired samples t-test. The improvement or aggravation quantity were recorded by comparing preoperative and postoperative intensity of nystagmus every 5° within 25°. RESULT: The null zone got from digital eye tracker and clinical investigation were highly consistent (r = 0.952, P < 0.01). The horizontal and vertical intensity improved in 9 patients (t = 2.335-6.609, P < 0.05) and 5 patients (t = 2.176-5.471, P < 0.05) respectively after surgery. There were 67.63% (117/173) horizontal intensity and 69.94% (121/173) vertical intensity improvement. CONCLUSION: The independently developed digital eye tracker can quantitatively evaluate the pre and post-operative nystagmus and analyze the surgical efficacy for CIN patients.

Microbiological toxicity of tilmicosin on human colonic microflora in chemostats.

To evaluate the microbiological safety of tilmicosin on human intestinal microflora, four chemostat models of healthy human colonic ecosystems were exposed to tilmicosin (0, 0.436, 4.36, and 43.6 µg/mL) for 7 days. Prior to and during drug exposure, three microbiological endpoints were monitored daily including short-chain fatty acids, bacterial counts and macrolide susceptibility. Colonization resistance of each community was determined by 3 successive daily challenges of Salmonella typhimurium. Genes associated with virulence and macrolide resistance in Enterococcus faecalis were determined by PCR. Transcriptional expression of the virulence gene (gelE) in E. faecalis was determined by real-time RT-PCR. Our results showed that different concentrations of tilmicosin did not disrupt the colonization resistance in each chemostat. During exposure to 4.36 and 43.6 µg/mL tilmicosin, the Bacteroides fragilis population was significantly decreased while the proportion of resistant Enterococci increased. After long-term exposure to the highest concentration (43.6 µg/mL) of tilmicosin, the gelE gene was significantly up-regulated in the high-level macrolide resistant strains that also contained the ermB resistance gene. This study was the first of its kind to evaluate the microbiological toxicity of tilmicosin using a chemostat model. These findings also provide new insight into the co-occurrence of macrolide resistance and virulence in E. faecalis under tilmicosin selective pressure.

A new measure of nystagmus acuity.

AIM: To construct a new visual acuity measuring function for congenital nystagmus (CN) patients by studying the relationships between acuity, velocities and positions of the eye. METHODS: After assessing the relationship between acuity, movement velocities and positions of the eye separately, a new function, which we call the automated nystagmus acuity function (ANAF), was constructed to measure the visual acuity of CN patients. Using a high-speed digital video system working at 500 frames per second, each eye was calibrated during monocular fixation. Twenty-six recorded nystagmus data were selected randomly. Using nystagmus waveforms, the best vision position (foveation period) and visual acuity were analyzed in three groups of subjects, and then all outputs were compared with the well-known expanded nystagmus acuity function (NAFX) and ANAF. Standard descriptive statistics were used to summarize the outputs of the two programs. RESULTS: Foveation periods were brief intervals in the CN waveform when the image was on or near the fovea and eye velocity was relatively slow. Results showed good visual acuity happened during the period when velocity was low and the eye position was near the zero position, which fitted the foveation periods. The data analyzed with NAFX and ANAF had a correlation coefficient of 0.934276, with an average error of -0.00973. CONCLUSION: The results from ANAF and NAFX analyses showed no significant difference. The NAFX manually identifies foveation eye positions and produces accurate measurements. The ANAF, however, can be calculated simply using the factors eye position and velocity, and it automatically calculates the ANAF without the need to manually identify foveation eye positions.

Alterations of sodium and potassium channels of RGCs in RCS rat with the development of retinal degeneration.

All know that retinitis pigmentosa (RP) is a group of hereditary retinal degenerative diseases characterized by progressive dysfunction of photoreceptors and associated with progressive cells loss; nevertheless, little is known about how rods and cones loss affects the surviving inner retinal neurons and networks. Retinal ganglion cells (RGCs) process and convey visual information from retina to visual centers in the brain. The healthy various ion channels determine the normal reception and projection of visual signals from RGCs. Previous work on the Royal College of Surgeons (RCS) rat, as a kind of classical RP animal model, indicated that, at late stages of retinal degeneration in RCS rat, RGCs were also morphologically and functionally affected. Here, retrograde labeling for RGCs with Fluorogold was performed to investigate the distribution, density, and morphological changes of RGCs during retinal degeneration. Then, patch clamp recording, western blot, and immunofluorescence staining were performed to study the channels of sodium and potassium properties of RGCs, so as to explore the molecular and proteinic basis for understanding the alterations of RGCs membrane properties and firing functions. We found that the resting membrane potential, input resistance, and capacitance of RGCs changed significantly at the late stage of retinal degeneration. Action potential could not be evoked in a part of RGCs. Inward sodium current and outward potassium current recording showed that sodium current was impaired severely but only slightly in potassium current. Expressions of sodium channel protein were impaired dramatically at the late stage of retinal degeneration. The results suggested that the density of RGCs decreased, process ramification impaired, and sodium ion channel proteins destructed, which led to the impairment of electrophysiological functions of RGCs and eventually resulted in the loss of visual function.