Relationship of Retinal Nerve Fiber Layer Thickness and Retinal Vessel Calibers with Cognitive Impairment in the Asymptomatic Polyvascular Abnormalities Population

Objective Cognitive impairment(CI)in older individuals has a high morbidity rate worldwide,with poor diagnostic methods and susceptible population identification.This study aimed to investigate the relationship between different retinal metrics and CI in a particular population,emphasizing polyvascular status.Methods We collected information from the Asymptomatic Polyvascular Abnormalities Community Study on retinal vessel calibers,retinal nerve fiber layer(RNFL)thickness,and cognitive function of 3,785participants,aged 40 years or older.Logistic regression was used to analyze the relationship between retinal metrics and cognitive function.Subgroups stratified by different vascular statuses were also analyzed.Results RNFL thickness was significantly thinner in the CI group(odds ratio:0.973,95%confidence interval:0.953–0.994).In the subgroup analysis,the difference still existed in the non-intracranial arterial stenosis,non-extracranial carotid arterial stenosis,and peripheral arterial disease subgroups(P<0.05).Conclusion A thin RNFL is associated with CI,especially in people with non-large vessel stenosis.The underlying small vessel change in RNFL and CI should be investigated in the future.

Analysis of the Efficacy of Prenatal B-Ultrasound in Diagnosing Fetal Abnormalities

Objective:To explore the positive significance of using prenatal B-ultrasound in diagnosing fetal abnormalities.Methods:A total of 200 pregnant women who visited Shaanxi Provincial People’s Hospital between January 2023 and January 2024 were recruited as the research subjects.All pregnant women received prenatal examinations.A retrospective analysis was carried out to analyze the positive significance of prenatal B-ultrasound examination in the diagnosis of fetal abnormalities.Results:Prenatal B-ultrasound examination detected 10 cases of fetal abnormalities,with a detection rate of 5.00%.When compared with the postnatal examination results of 5.50%,the difference was insignificant(P>0.05).Moreover,comparing the fetal limb abnormalities and cardiovascular abnormalities in prenatal B-ultrasound examination and postnatal examination,one case of congenital heart disease was missed in the prenatal B-ultrasound examination,and the others were consistent with the postnatal examination results,with a coincidence rate of 90.91%,indicating a high compliance rate.Conclusion:Fetal abnormalities have a great impact on mothers,babies,and families,and it is particularly important to strengthen diagnosis during this process.Prenatal B-ultrasound examination can improve the accuracy of diagnosis of fetal abnormalities and can be promoted in clinical practice as a basis for screening fetal abnormalities.

Coagulation abnormalities and their relationship with bleeding manifestations in patients with dengue-A single center observational study

Objective:To evaluate coagulation abnormalities and their relationship with bleeding manifestations among patients with dengue.Methods:This observational study was conducted on 292 adult dengue patients who were admitted to a tertiary care hospital of Western India from July 2021 to June 2022.Coagulation tests including prothrombin time(PT),international normalized ratio(INR),activated partial thromboplastin time(aPTT),fibrinogen,and D-dimer were performed.Patients were monitored for bleeding manifestations.Results:Coagulation abnormalities were reported in 42.8%of the patients.Overall,prolonged aPTT was the most common coagulation abnormality(40.8%),followed by low fibrinogen(38.7%),raised D-dimer(31.2%),raised INR(26.0%)and prolonged PT(19.2%).Bleeding manifestations were present in 19.9%patients.PT,INR,aPTT and D-dimer levels were significantly higher(P<0.01)and fibrinogen level was significantly lower(P<0.001)in patients with bleeding compared to patients without bleeding.Patients with bleeding had a significantly higher rate of all coagulation abnormalities than patients without bleeding(P<0.01).Conclusions:Patients with bleeding showed a significantly higher frequency of coagulation abnormalities compared to patients without bleeding.Patients with dengue should be assessed for coagulation abnormalities.

Prevalence of Ventilatory Function Abnormalities in Residents of Attecoube Lagune, Abidjan (Côte d’Ivoire)

Introduction: Studies of abnormal ventilatory function in Côte d’Ivoire have been carried out in the workplace and in schools. The objective of this study was to determine the prevalence of respiratory symptoms and ventilatory function abnormalities in the population of the lagoon district of Attécoubé in Abidjan. Material and Methods: A cross-sectional study was carried out on 170 people in the municipality of Attécoubé Lagune. A questionnaire was used to collect information on sociodemographic, clinical, and environmental characteristics. A basic spirometry and a beta mimetic test were carried out on all the subjects surveyed. Data analysis was done with the stata 15.1 software. Results: The study population was composed of 103 women and 67 men with a sex ratio (M/F) of 0.65. The average age was 35.92 ± 15.28 years. The most frequent respiratory symptoms were chest tightness (29.41%), dyspnea (28.82%), sneezing (22.94%) and cough (22.35%). The prevalence of ventilatory function abnormalities was 43.24% among residents of Attécoubé Lagune and the most frequent abnormality was ventilatory restriction (35.15%) followed by obstruction (4.85%). The risk factor for ventilatory function abnormalities was heavy pollution [OR = 2.66;IC: 1.053 - 6.743;P = 0.038]. Conclusion: Residents of the Attécoubé Lagune district had many respiratory symptoms and a high prevalence of ventilatory function abnormalities. Improving air quality is urgently needed in this municipality.

Correlation between Reasons for Prescription and Karyotype Results in Patients Referred for Suspected Chromosomal Abnormalities

Karyotype prescription is based on clinical signs (or reasons for karyotype prescription) which are phenotypic manifestations associated with chromosomal abnormalities. The aim of this study was to establish a correspondence between karyotype indications and their results in patients. This was a retrospective study that was carried out in the Histology-Embryology-Cytogenetics laboratory of the University Hospital of Cocody-Abidjan from 2014 to 2019. 58 patient files were identified and included the indication or reason for prescribing a constitutional karyotype and the biological result obtained. An individual data sheet was used to collect the data. 17 reasons for prescription were identified and divided into 2 groups. Sexual ambiguity was the most frequent reason (29.3%). The first group (G1) represented the 10 reasons for which the karyotype results were normal. The second group (G2) corresponded of the 7 motives with normal or abnormal karyotype results. Several anomalies were listed according to these reasons: inversions, mosaics (anomalies of number and structure) and trisomy 21. The last was the most frequent chromosomal anomaly (69.24%). It was found in several reasons for karyotype prescription: malformations, neurological disorders, suspected trisomy and cardiac pathology. Several factors could explain these results, among which are the limits of the karyotype and the non-genetic causes that can induce these abnormal phenotypes. Complementary examinations to the karyotype are molecular cytogenetic techniques, notably fluorescence in situ hybridization (FISH) and array comparative genomic hybridization (Array-CGH).

改进Wav2Lip的文本音频驱动人脸动画生成

为了提高中文唇音同步人脸动画视频的真实性,本文提出一种基于改进Wav2Lip模型的文本音频驱动人脸动画生成技术.首先,构建了一个中文唇音同步数据集,使用该数据集来预训练唇部判别器,使其判别中文唇音同步人脸动画更加准确.然后,在Wav2Lip模型中,引入文本特征,提升唇音时间同步性从而提高人脸动画视频的真实性.本文模型综合提取到的文本信息、音频信息和说话人面部信息,在预训练的唇部判别器和视频质量判别器的监督下,生成高真实感的唇音同步人脸动画视频.与ATVGnet模型和Wav2Lip模型的对比实验表明,本文模型生成的唇音同步人脸动画视频提升了唇形和音频之间的同步性,提高了人脸动画视频整体的真实感.本文成果为当前人脸动画生成需求提供一种解决方案.

Blood Count Abnormalities Associated with Death in Patients Infected with SARS-COV-2 at the Ziguinchor EpidemicTreatment Center (ETC)

Introduction: SARS-COV-2 infection is a real public health challenge for the World Health Organization and for our country. It is responsible for numerous hematological abnormalities in infected patients. Objectives: To describe the haemogram abnormalities in patients infected with SARS-COV-2 and to determine which ones are associated with death. Material and Method: We conducted a retrospective, descriptive, analytical, cross-sectional study from March 2020 to September 2021. The study included all patients hospitalized with RT-PCR-confirmed COVID-19 who performed a blood count. We evaluated the blood count profile, the pathologies found and the associated blood count abnormalities. Results: A total of 263 patients were included. The mean age of the patients was 63.77 years (range 12 - 90 years). The male sex represented 54.75% (n = 144) while the female sex was 45.25% (n = 119) (sex ratio = 1.21). The most common pathologies were: diabetes: 30.03% (n = 79), high blood pressure: 41.04% (n = 108), and Chronic kidney disease: 7.98 (n = 21). The abnormalities of the haemogram found were essential: anaemia 28.13% (n = 121), hyperleukocytosis with neutrophilic predominance: 29.3% (126), lymphopenia: 34.41% (n = 148), thrombocytopenia: 8.16% (n = 35). The search for hematological factors associated with death in patients showed a significant difference between hyperleukocytosis (p = 0.000) and lymphopenia (p = 0.0001). Conclusion: SARS-COV-2 disease was a mortality factor when associated with lymphopenia and hyperleukocytosis in our series.

Improving Federated Learning through Abnormal Client Detection and Incentive

Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness.

Prevalence of Dyslipidemia among Patients Received at the Biochemistry Unit of the Charles de Gaulle Pediatric University Hospital in Ouagadougou

Introduction: Cardiovascular disease represents a major public health burden worldwide. Research and management of risk factors contribute to the prevention of these diseases. The aim of this study was to assess the prevalence of dyslipidemia in the biochemistry unit of the Charles De Gaulle Pediatric University Hospital (CHUP-CDG) in Ouagadougou. Material and Methods: This was a descriptive and analytical cross-sectional study, with retrospective data collection from January 1, 2020 to December 31, 2022. Patients of all ages who performed a lipid panel in the CHUP-CDG biochemistry unit during the study period have been included. Results: A total of 2872 patients have been included. The mean age of the study population was 27.72 ± 19.51 years and the M/F sex ratio was 0.81. Among the patients, 22.84% had at least one dyslipidemia. The prevalences of hypercholesterolemia, hypo-HDL cholesterolemia and hyper-LDL cholesterolemia were 11.57%, 49.19% and 57.50% respectively. Hypertriglyceridemia and mixed hyperlipidemia were present in 9.04% and 2.08% of patients. Hypercholesterolemia was significantly more frequent in the female sex (p = 0.0077);hyper-LDL cholesterolemia (p = 0.0255) and mixed hyperlipidemia (p Conclusion: The relatively high prevalence of dyslipidemia in the study indicates a worrying situation. It would therefore appear essential to extend the search for risk factors nationwide, particularly those that can be modified, in order to reduce morbidity and mortality linked to cardiovascular disease.

Abnormal State Detection in Lithium-ion Battery Using Dynamic Frequency Memory and Correlation Attention LSTM Autoencoder

This paper addresses the challenge of identifying abnormal states in Lithium-ion Battery(LiB)time series data.As the energy sector increasingly focuses on integrating distributed energy resources,Virtual Power Plants(VPP)have become a vital new framework for energy management.LiBs are key in this context,owing to their high-efficiency energy storage capabilities essential for VPP operations.However,LiBs are prone to various abnormal states like overcharging,over-discharging,and internal short circuits,which impede power transmission efficiency.Traditional methods for detecting such abnormalities in LiB are too broad and lack precision for the dynamic and irregular nature of LiB data.In response,we introduce an innovative method:a Long Short-Term Memory(LSTM)autoencoder based on Dynamic Frequency Memory and Correlation Attention(DFMCA-LSTM-AE).This unsupervised,end-to-end approach is specifically designed for dynamically monitoring abnormal states in LiB data.The method starts with a Dynamic Frequency Fourier Transform module,which dynamically captures the frequency characteristics of time series data across three scales,incorporating a memory mechanism to reduce overgeneralization of abnormal frequencies.This is followed by integrating LSTM into both the encoder and decoder,enabling the model to effectively encode and decode the temporal relationships in the time series.Empirical tests on a real-world LiB dataset demonstrate that DFMCA-LSTM-AE outperforms existing models,achieving an average Area Under the Curve(AUC)of 90.73%and an F1 score of 83.83%.These results mark significant improvements over existing models,ranging from 2.4%–45.3%for AUC and 1.6%–28.9%for F1 score,showcasing the model’s enhanced accuracy and reliability in detecting abnormal states in LiB data.

Management of Square Carcinoma of the Lower Lip Using Camille-Bernard Flap under Local Anesthesia: When Constraints Dictate Our Attitude

Introduction: Squamous cell carcinomas of the lip essentially pose a therapeutic management problem. In the West, their treatment is done under general anesthesia and follows the classic rules of oncology. In our context of exercise, we sometimes have a different attitude dictated by various constraints. Observation: 55-year-old patient with no notable history, seen in consultation for a very large ulcerative-budding lesion on the right 2/3 of the lower lip with mucocutaneous involvement without lymph node findings found on examination. Faced with this suspicious lesion and the patient’s financial difficulties, we decided to operate under local anesthesia to remove this tumor. The oncological excision was followed by immediate plasty using a Camille-Bernard flap with a good immediate aesthetic and functional result and postoperative day 7. The patient was unable to take his surgical specimen to anatomy-pathology and was lost to follow-up due to lack of financial resources. On anatomo-pathological analysis of the surgical specimen, the margins were healthy with confirmation of squamous cell carcinoma (anapathological reading made for scientific interest). Discussion: The particular mentality of certain patients and their difficult financial conditions push us to have an unconventional therapeutic attitude in oncology, but which nevertheless makes it possible to resolve certain problems that we often face. Local anesthesia is possible and realistic in cases like ours and the results can be acceptable and life-saving.

Abnormal Traffic Detection for Internet of Things Based on an Improved Residual Network

Along with the progression of Internet of Things(IoT)technology,network terminals are becoming continuously more intelligent.IoT has been widely applied in various scenarios,including urban infrastructure,transportation,industry,personal life,and other socio-economic fields.The introduction of deep learning has brought new security challenges,like an increment in abnormal traffic,which threatens network security.Insufficient feature extraction leads to less accurate classification results.In abnormal traffic detection,the data of network traffic is high-dimensional and complex.This data not only increases the computational burden of model training but also makes information extraction more difficult.To address these issues,this paper proposes an MD-MRD-ResNeXt model for abnormal network traffic detection.To fully utilize the multi-scale information in network traffic,a Multi-scale Dilated feature extraction(MD)block is introduced.This module can effectively understand and process information at various scales and uses dilated convolution technology to significantly broaden the model’s receptive field.The proposed Max-feature-map Residual with Dual-channel pooling(MRD)block integrates the maximum feature map with the residual block.This module ensures the model focuses on key information,thereby optimizing computational efficiency and reducing unnecessary information redundancy.Experimental results show that compared to the latest methods,the proposed abnormal traffic detection model improves accuracy by about 2%.

Vehicle Abnormal Behavior Detection Based on Dense Block and Soft Thresholding

With the rapid advancement of social economies,intelligent transportation systems are gaining increasing atten-tion.Central to these systems is the detection of abnormal vehicle behavior,which remains a critical challenge due to the complexity of urban roadways and the variability of external conditions.Current research on detecting abnormal traffic behaviors is still nascent,with significant room for improvement in recognition accuracy.To address this,this research has developed a new model for recognizing abnormal traffic behaviors.This model employs the R3D network as its core architecture,incorporating a dense block to facilitate feature reuse.This approach not only enhances performance with fewer parameters and reduced computational demands but also allows for the acquisition of new features while simplifying the overall network structure.Additionally,this research integrates a self-attentive method that dynamically adjusts to the prevailing traffic conditions,optimizing the relevance of features for the task at hand.For temporal analysis,a Bi-LSTM layer is utilized to extract and learn from time-based data nuances.This research conducted a series of comparative experiments using the UCF-Crime dataset,achieving a notable accuracy of 89.30%on our test set.Our results demonstrate that our model not only operates with fewer parameters but also achieves superior recognition accuracy compared to previous models.

Abnormal Action Recognition with Lightweight Pose Estimation Network in Electric Power Training Scene

Electric power training is essential for ensuring the safety and reliability of the system.In this study,we introduce a novel Abnormal Action Recognition(AAR)system that utilizes a Lightweight Pose Estimation Network(LPEN)to efficiently and effectively detect abnormal fall-down and trespass incidents in electric power training scenarios.The LPEN network,comprising three stages—MobileNet,Initial Stage,and Refinement Stage—is employed to swiftly extract image features,detect human key points,and refine them for accurate analysis.Subsequently,a Pose-aware Action Analysis Module(PAAM)captures the positional coordinates of human skeletal points in each frame.Finally,an Abnormal Action Inference Module(AAIM)evaluates whether abnormal fall-down or unauthorized trespass behavior is occurring.For fall-down recognition,three criteria—falling speed,main angles of skeletal points,and the person’s bounding box—are considered.To identify unauthorized trespass,emphasis is placed on the position of the ankles.Extensive experiments validate the effectiveness and efficiency of the proposed system in ensuring the safety and reliability of electric power training.

First record of abnormal body coloration in a rockfish Sebastes koreanus(Scorpaenoidei:Sebastidae)from coastal water of China based on morphological characteristics and DNA barcoding

The first record of abnormal body coloration in Sebastes koreanus Kim and Lee,1994,from the Yellow Sea of China,was documented based on morphological characteristics and DNA barcoding.The two rockfish specimens were collected from the coastal waters of Qingdao,China,and the whole body and all fins of them were red.Of the two red-colored rockfish,there were tiny deep red spots on each fin,2 red radial stripes behind and below the eyes and 1 large deep red blotch on the opercula,while the similar stripe and spot patterns are also present in the S.koreanus specimens with normal body coloration.The countable characteristics of the two specimens are in the range of the morphometry of S.koreanus.To further clarify the species identity and taxonomic status of the two specimens,DNA barcode analysis was carried out.The genetic distance between the red-colored rockfish and S.koreanus was 0,and the minimum net genetic distances between the red-colored rockfish and other Sebastes species except for S.koreanus were 3.0%,which exceeds the threshold of species delimitation.The phylogenetic analysis showed that the DNA barcoding sequences of the two red-colored rockfish clustered with the S.koreanus sequences.The above results of DNA barcode analysis also support that the two red-colored rockfish could be identified as the species of S.koreanus.The mechanism of color variation in S.koreanus is desirable for further research and the species could be an ideal model to study the color-driven speciation of the rockfishes.

A Clinical Study to Assess the Effectiveness of Oral Combination Kit Therapy in Syndromic Management of Abnormal Vaginal Discharge (FEMINE Study) in Kinshasa, Democratic Republic of Congo

Background: Vaginal discharge is one of most common and nagging problems that women face. About 20% - 25% of women who visit gynecology department complain of vaginal discharge and leucorrhoea. An orally administered combination kit, containing 2 g secnidazole, 1 g azithromycin and 150 mg fluconazole (Azimyn FS Kit), has been successfully evaluated in clinical trials and used in several countries for management syndromic vaginal discharge due to infections. Methods: This is a longitudinal study which aimed to verify the clinical efficacy of the combined oral kit containing secnidazole, azithromycin and fluconazole (Azimyn FS Kit®) in the syndromic treatment of abnormal vaginal discharge in patients received in outpatient consultations in Kinshasa/DR Congo from March to September 2023. Results: Majority of patients had whitish vaginal discharge (51.6%) of average abundance (56.2%), accompanied by pruritus in 72.1% of cases, and dyspareunia in 23.5% of cases and hypogastralgia in 40.2% of cases. One week after treatment with the Azimyn FS® combined kit, at the greatest majority of patients (97.3%), abnormal vaginal discharge had decreased by more than 50% (84.1%). Two weeks after treatment with the Azimyn FS® combined kit, almost all patients (97.3%) no longer had abnormal vaginal discharge which had completely disappeared. Conclusion: A single dose of secnidazole, azithromycin and fluconazole in the form of an oral combi-kit (Azimyn FS Kit) has shown excellent therapeutic effectiveness in the syndromic treatment of abnormal vaginal discharge wherein patients were treated without diagnostic confirmation.

Study on the Efficacy Claim and Evaluation Method of Lip Cosmetics

To study the efficacy of lip moisturizing cosmetics and explore the methods for evaluating their efficacy.The claimed efficacy and number of claimed efficacy of 44 lip moisturizing cosmetics were investigated,and a combination of in vitro and human testing was used to evaluate the efficacy of the lip moisturizing cosmetics.The efficacy claims of lip cosmetics mainly included 4 categories of moisturizing,repairing,soothing and anti-wrinkle,with 79.55%of the products claiming 3~4 categories of efficacy.In the in vitro test,the cell morphology of the skin damage model improved and the secretion of pro-inflammatory factors decreased significantly.In the human trial,the water content,skin softness and brightness L value of the cuticle of the lips increased significantly in 31 subjects,and the transepidermal water loss,redness a value,and the area and volume of lip wrinkles decreased significantly;the dryness of the lip skin and the uniformity of the skin texture improved significantly.The dryness of lip skin and the uniformity of skin texture were significantly improved.The results show that the moisture content of the stratum corneum can be used to evaluate the moisturizing efficacy of lip products.The transepidermal water loss,skin color,skin softness and expert assessment can be used to evaluate the repairing efficacy.The observation of cell morphology of skin damage models and the detection of pro-inflammatory factor content can be used to evaluate the soothing efficacy.The area and volume of lip wrinkles can be used to evaluate the anti-wrinkle efficacy of products.

LipSense:基于CSI相位差的自适应唇语识别方法

针对目前基于CSI幅度的行为识别方法对细粒度动作不敏感及传统的动作分割算法存在动作起止点判断不准确的问题,提出了一种基于相位差的自适应唇语识别方法。首先,利用MIMO系统的空间分集,构造出对细粒度动作更敏感的相位差信号,解决了细粒度动作感知不易的问题;然后利用OFDM子载波的频率分集来补偿小尺度衰落效应,以增强信号的空间感知能力;再次,通过研究唇语信号独特的变化模式,提出基于迭代方差曲线的自适应唇语分割模型;最后设计用于表示和匹配唇语特征的识别技术。在真实环境下的实验表明,所提方法在单人情况下平均识别精度达到94.3%,三人的综合识别准确率可达85.7%。在实验者佩戴金属饰品、网络被他人共享、以及周围有人移动等对比实验下,系统仍能实现较高的准确率。

Multi-modality imaging review of congenital abnormalities of kidney and upper urinary tract

Congenital abnormalities of the kidney and urinary tract(CAKUT) include a wide range of abnormalities ranging from asymptomatic ectopic kidneys to life threatening renal agenesis(bilateral). Many of them are detected in the antenatal or immediate postnatal with a significant proportion identified in the adult population with varying degree of severity. CAKUT can be classified on embryological basis in to abnormalities in the renal parenchymal development, aberrant embryonic migration and abnormalities of the collecting system. Renal parenchymal abnormalities include multi cystic dysplastic kidneys, renal hypoplasia, number(agenesis or supernumerary), shape and cystic renal diseases. Aberrant embryonic migration encompasses abnormal location and fusion anomalies. Collecting system abnormalities include duplex kidneys and Pelvi ureteric junction obstruction. Ultrasonography(US) is typically the first imaging performed as it is easily available, noninvasive and radiation free used both antenatally and postnatally. Computed tomography(CT) and magnetic resonance imaging(MRI) are useful to confirm the ultrasound detected abnormality, detection of complex malformations, demonstration of collecting system and vascular anatomy and more importantly for early detection of complications like renal calculi, infection and malignancies. As CAKUT are one of the leading causes of end stage renal disease, it is important for the radiologists to be familiar with the varying imaging appearances of CAKUT on US, CT and MRI, thereby helping in prompt diagnosis and optimal management.

Characteristics of ocular abnormalities in gout patients

·AIM: To characterize the clinical features of ocular surface in gout patients in coastal area of Shandong Province in China. ·METHODS: A total of 380 consecutive gout patients were examined from January 2011 to May 2011. According to the course of gout, patients were divided into group A (【5 years), B (5 -10 years) and C (】10 years). Group D (control group) was consist of 50 healthy subjects. Eyelids, lateral canthus, medial canthus, palpebral conjunctiva, sclera and cornea, anterior chamber, lens, anterior vitreous were examined by slit lamp to find whether there were deposition of uric acid crystals, ocular vascular tortuosity, redness and subconjunctival hemorrhage. The ophthalmic exams of visual acuity, intraocular pressure, fundus were used to assess any gout-related eye disease. ·RESULTS: Uric acid crystals were found in 3 patients and the positions of the deposite were in corneal stroma, corneal epithelium and superficial stroma, and sclera respectively. The incidence was 0.79% . Dilatated and tortuous blood vessels in conjunctiva and sclera surface were found in 38 (23.8% ), 40 (44.0% ), 58 (45.0% ), 9 (18.0% ) patients in groups A, B, C and D, respectively. The differences between group B and D, group C and D were statistically significant( 【0.01, 【0.01).Transparent vesicles with metal -like reflected light in subconjunctiva were seen in 26 (16.2%), 29 (31.9%), 41 (31.8%), 2 (4.00%) patients in groups A, B, C and D, respectively. The differences between A and D, B and D, C and D were statistically significant ( 【0.05, 【0.01, 【0.01). Subconjunctival hemorrhage was found in all groups, the difference among the four groups showed no statistically significance. · CONCLUSION: Gout can cause ocular surface abnormalities, such as tophi deposition, subconjunctival transparent vesicles and hemorrhage, and vascular changes. These features have important clinical significance in early detection of the gout and prevention of eye injury. ·