Stop codon variant in EFEMP1 is associated with primary open-angle glaucoma due to impaired regulation of aqueous humor outflow.

It is known that the actin cytoskeleton and its associated cellular interactions in the trabecular meshwork (TM) and juxtacanalicular tissues mainly contribute to the formation of resistance to aqueous outflow of the eye. Fibulin-3, encoded by EFEMP1 gene, has a role in extracellular matrix (ECM) modulation, and interacts with enzymatic ECM regulators, but the effects of fibulin-3 on TM cells has not been explored. Here, we report a stop codon variant (c.T1480C, p.X494Q) of EFEMP1 that co-segregates with primary open angle glaucoma (POAG) in a Chinese pedigree. In the human TM cells, overexpression of wild-type fibulin-3 reduced intracellular actin stress fibers formation and the extracellular fibronectin levels by inhibiting Rho/ROCK signaling. TGFß1 up-regulated fibulin-3 protein levels in human TM cells by activating Rho/ROCK signaling. In rat eyes, overexpression of wild-type fibulin-3 decreased the intraocular pressure and the fibronectin expression of TM, however, overexpression of mutant fibulin-3 (c.T1480C, p.X494Q) showed opposite effects in cells and rat eyes. Taken together, the EFEMP1 variant may impair the regulatory capacity of fibulin-3 which has a role for modulating the cell contractile activity and ECM synthesis in TM cells, and in turn may maintain normal resistance of aqueous humor outflow. This study contributes to the understanding of the important role of fibulin-3 in TM pathophysiology and provides a new possible POAG therapeutic approach.

γ-Gammaglutamyl transferase predicts all-cause mortality within three-year intervals in patients undergoing peritoneal dialysis.

OBJECTIVES: Peritoneal dialysis (PD) serves as a vital renal replacement therapy for patients with end-stage kidney disease (ESKD). γ-Gamma-glutamyl transferase (γ-GGT) is a recognized predictor of oxidative stress and mortality. This study aimed to assess the prognostic significance of γ-GGT in predicting all-cause and cardiovascular mortality among PD patients. METHODS: A retrospective study was conducted, enrolling 640 PD patients from a single center. The one-year, three-year, and five-year mortality rates for all causes and cardiovascular causes were evaluated. Kaplan-Meier survival analysis and multivariate Cox regression analysis were performed. RESULTS: Within five years of initiating PD, the observed all-cause mortality rates at one, three, and five years were 11.72%, 16.09%, and 23.44%, while cardiovascular mortality rates were 2.97%, 7.34%, and 11.09%, respectively. Lower γ-GGT levels were associated with decreased all-cause mortality during one-, three-, and five-year follow-ups, along with reduced cardiovascular mortality in the first and third years, as indicated by Kaplan-Meier analysis on median γ-GGT groupings. Multivariate Cox regression analysis showed significantly decreased hazard ratios (HRs) for one- to five-year all-cause mortality and cardiovascular mortality in the lower γ-GGT group compared to higher groups. However, when sex differences were eliminated using separate tertile groupings for males and females, only the one- and three-year all-cause mortality rates demonstrated significantly reduced hazard ratios (HRs) in the lower γ-GGT groups. CONCLUSION: This retrospective study suggests that γ-GGT levels have prognostic significance in predicting one- and three-year all-cause mortality among PD patients when accounting for sex differences.

OD-YOLO: Robust Small Object Detection Model in Remote Sensing Image with a Novel Multi-Scale Feature Fusion.

As remote sensing technology has advanced, the use of satellites and similar technologies has become increasingly prevalent in daily life. Now, it plays a crucial role in hydrology, agriculture, and geography. Nevertheless, because of the distinct qualities of remote sensing, including expansive scenes and small, densely packed targets, there are many challenges in detecting remote sensing objects. Those challenges lead to insufficient accuracy in remote sensing object detection. Consequently, developing a new model is essential to enhance the identification capabilities for objects in remote sensing imagery. To solve these constraints, we have designed the OD-YOLO approach that uses multi-scale feature fusion to improve the performance of the YOLOv8n model in small target detection. Firstly, traditional convolutions have poor recognition capabilities for certain geometric shapes. Therefore, in this paper, we introduce the Detection Refinement Module (DRmodule) into the backbone architecture. This module utilizes Deformable Convolutional Networks and the Hybrid Attention Transformer to strengthen the model's capability for feature extraction from geometric shapes and blurred objects effectively. Meanwhile, based on the Feature Pyramid Network of YOLO, at the head of the model framework, this paper enhances the detection capability by introducing a Dynamic Head to strengthen the fusion of different scales features in the feature pyramid. Additionally, to address the issue of detecting small objects in remote sensing images, this paper specifically designs the OIoU loss function to finely describe the difference between the detection box and the true box, further enhancing model performance. Experiments on the VisDrone dataset show that OD-YOLO surpasses the compared models by at least 5.2% in mAP50 and 4.4% in mAP75, and experiments on the Foggy Cityscapes dataset demonstrated that OD-YOLO improved mAP by 6.5%, demonstrating outstanding results in tasks related to remote sensing images and adverse weather object detection. This work not only advances the research in remote sensing image analysis, but also provides effective technical support for the practical deployment of future remote sensing applications.

Synthesis of environmentally friendly neonicotinoid insecticide with proper functional properties by theoretical methodologies.

Modern insecticide substitutes using acetylcholine receptors (nAChR) as biochemical targets, such as neonicotinoid insecticides (NNIs), have been extensively researched. Only 12 compounds have been experimentally realized since the initial discovery of imidacloprid. Increasingly, the bottleneck in this field is to rapidly determine the synthesizability of NNI substitutes. Here, we designed a coupled evaluation system for synthesis prediction and validation, including the synthesis probability, reaction path difficulty, and electron transfer characteristics of NNIs and their substitutes. Firstly, a total of 1475 eigenvalues were generated and 52 critical eigenvalues were screened out through the Pearson's correlation coefficient. The positive and unlabeled (PU) machine learning was constructed using the critical eigenvalues NNIs, including 12 experimentally synthesized NNIs (positive samples) and 73 unsynthesized NNI substitutes (unlabeled samples). Results identified 3 NNI substitutes that were highly promising candidates for synthesis (synthesis probability > 0.5). The results of density functional theory demonstrated the ranking of their reaction ease was UN-1 (31.4 kcal/mol) > UN-2 (81.6 kcal/mol) > UN-3 (3.35 ×103 kcal/mol). Time-dependent density functional theory revealed that changes in the electron distribution and electron excitation type were critical factors affecting their synthesizability, and the local excitation type was more favorable for the synthesizability of NNI substituents. The findings provide significant guidance for NNIs synthesis, reducing the possible space of unlabeled samples to 95.89% of their original size, while also minimizing the cost of research on subsequent NNI substitutes.

Mean platelet volume may predict all-cause and cardiovascular mortality among incident peritoneal dialysis patients.

BACKGROUND: The association between mean platelet volume (MPV) and mortality in patients with cardiovascular disease has been demonstrated. However, the association between MPV and mortality in peritoneal dialysis (PD) patients remains unclear. METHODS: Patients catheterized at the First Affiliated Hospital, Nanchang University, between November 1, 2005, and August 31, 2019, were enrolled. The primary endpoints were all-cause and cardiovascular mortality. Patients were divided into two groups according to the cutoff value, which was determined using maximally selected rank statistics. The mortality hazard ratio was evaluated using Cox regression models. RESULTS: Among the 1322 PD patients enrolled, the mean age was 49.3 ± 14.5 years, 57.6% were men, and 18.8% had diabetes. During a median follow-up of 50 months (IQR: 30-80), 360 patients died; among these, 167 deaths were attributed to cardiovascular diseases. Survival analysis revealed that all-cause and cardiovascular mortality rates were lower in the higher-MPV group than in the lower-MPV group (p < .001 and p < .001, respectively). After full adjustment, a higher MPV was significantly associated with a hazard ratio of 0.77 for all-cause mortality (95% CI: 0.60-0.98, p = .036) and 0.75 for cardiovascular mortality (95% CI: 0.51-0.97, p = .041). Subgroup analysis showed that a significant interaction existed between age and MPV (p < .001). Decreased MPV was associated with higher mortality risk only in patients < 60 years old. CONCLUSIONS: Our results showed that lower MPV can be associated with a higher risk of all-cause and cardiovascular mortality in patients with PD.

Visible light-induced catalytic performance of composite photocatalyst synthesized with nanomaterials WO3 and two-dimensional ultrathin g-C3N4.

To improve the visible light-induced catalytic activities of Ultrathin g-C3N4 (UCN), a promising photocatalyst WO3/UCN (WU) was synthesized. Its visible light-driven photocatalysis performance was controllable by adjusting the theoretical mass ratio of WO3/UCN. We have calibrated the optimal preparation conditions to be: WO3/UCN ratio as 1:1, the stirring time of the UCN and sodium tungstate mixture as 9 h and the volume of concentrated hydrochloric acid as 6 mL which was poured into the mixture solution with an extra stirring time of 1.5 h. The optimal photocatalyst WUopt had porous and wrinkled configurations. Its light absorption edge was 524 nm while that of UCN was 465 nm. The band gap of WUopt was 2.13 eV, 0.3 eV less than that of UCN. Therefore, the recombination rate of photo-generated electron-hole pairs of WUopt reduced significantly. The removal rate of WUopt on RhB was 97.3%. By contrast, the removal rate of UCN was much lower (53.4%). WUopt retained a high RhB removal rate, it was 5.5% lower than the initial one after being reused for five cycles. The photodegradation mechanism was facilitated through the strong oxidation behaviors from the active free radicals ·O2-, ·OH and h+ generated by WUopt under the visible light irradiation.

Development and validation of a multi-lingual online questionnaire for surveying the COVID-19 prevention and control measures used in global workplaces.

BACKGROUND: Despite widespread COVID-19 vaccination programs, there is an ongoing need for targeted disease prevention and control efforts in high-risk occupational settings. This study aimed to develop, pilot, and validate an instrument for surveying occupational COVID-19 infection prevention and control (IPC) measures available to workers in diverse geographic and occupational settings. METHODS: A 44-item online survey was developed in English and validated for face and content validity according to literature review, expert consultation, and pre-testing. The survey was translated and piloted with 890 workers from diverse industries in Canada, Ireland, Argentina, Poland, Nigeria, China, the US, and the UK. Odds ratios generated from univariable, and multivariable logistic regression assessed differences in 'feeling protected at work' according to gender, age, occupation, country of residence, professional role, and vaccination status. Exploratory factor analysis (EFA) was conducted, and internal consistency reliability verified with Cronbach's alpha. Hypothesis testing using two-sample t-tests verified construct validity (i.e., discriminant validity, known-groups technique), and criterion validity. RESULTS: After adjustment for occupational sector, characteristics associated with feeling protected at work included being male (AOR = 1.88; 95% CI = 1.18,2.99), being over 55 (AOR = 2.17; 95% CI = 1.25,3.77) and working in a managerial position (AOR = 3.1; 95% CI = 1.99,4.83). EFA revealed nine key IPC domains relating to: environmental adjustments, testing and surveillance, education, costs incurred, restricted movements, physical distancing, masking, isolation strategies, and areas for improvement. Each domain showed sufficient internal consistency reliability (Cronbach's alpha ≥0.60). Hypothesis testing revealed differences in survey responses by country and occupational sector, confirming construct validity (p < 0.001), criterion validity (p = 0.04), and discriminant validity (p < 0.001). CONCLUSIONS: The online survey, developed in English to identify the COVID-19 protective measures used in diverse workplace settings, showed strong face validity, content validity, internal consistency, criterion validity, and construct validity. Translations in Chinese, Spanish, French, Polish, and Hindi demonstrated adaptability of the survey for use in international working environments. The multi-lingual tool can be used by decision makers in the distribution of IPC resources, and to guide occupational safety and health (OSH) recommendations for preventing COVID-19 and future infectious disease outbreaks.

Identification of Hub Genes Associated with Abnormal Endothelial Function in Early Coronary Atherosclerosis.

Abnormal coronary endothelial function is an important step in the development of atherosclerosis. Coronary atherosclerosis is one of the main causes of death worldwide. We constructed a co-expression network to identify hub genes associated with abnormal coronary endothelial function in early coronary atherosclerosis. In brief, we used the GSE132651 dataset from the gene expression omnibus database. The top 5000 genes with greatest variances were used for weighted gene co-expression network analysis, and the module most strongly correlated with abnormal coronary endothelial function was chosen as key module. Functional enrichment analysis was performed for genes in the key module, a protein-protein interaction network was constructed to find hub genes, and gene set enrichment analysis (GSEA) was also performed. Genes were classified into 7 modules, with the midnightblue module being the one that was most related to abnormal coronary endothelial function and containing genes enriched in DNA replication, cell cycle, nucleotide excision repair, and Human T-cell leukemia virus 1 infection. We identified nine hub genes (HOXC5, PRND, PADI3, RC3H1, DAPP1, SIT1, DRICH1, GPRIN2, and RHO), which differently expressed in abnormal and normal coronary endothelial function samples. GSEA suggested that samples associated with abnormal coronary endothelial function and highly expressed hub genes were linked with immune, coagulation, hypoxia, and angiogenesis processes. These hub genes, their expression pattern, and pathways may be involved in the development of abnormal coronary endothelial function and promotion of early coronary atherosclerosis.

Emotional and Physical Health Impact in Children and Adolescents and Their Caregivers Using Open-source Automated Insulin Delivery: Qualitative Analysis of Lived Experiences.

BACKGROUND: Given the limitations in the access and license status of commercially developed automated insulin delivery (AID) systems, open-source AID systems are becoming increasingly popular among people with diabetes, including children and adolescents. OBJECTIVE: This study aimed to investigate the lived experiences and physical and emotional health implications of children and their caregivers following the initiation of open-source AID, their perceived challenges, and sources of support, which have not been explored in the existing literature. METHODS: Data were collected through 2 sets of open-ended questions from a web-based multinational survey of 60 families from 16 countries. The narratives were thematically analyzed, and a coding framework was identified through iterative alignment. RESULTS: A range of emotions and improvements in quality of life and physical health were reported, as open-source AID enabled families to shift their focus away from diabetes therapy. Caregivers were less worried about hypoglycemia at night and outside their family homes, leading to increased autonomy for the child. Simultaneously, the glycemic outcomes and sleep quality of both the children and caregivers improved. Nonetheless, the acquisition of suitable hardware and technical setup could be challenging. The #WeAreNotWaiting community was the primary source of practical and emotional support. CONCLUSIONS: Our findings show the benefits and transformative impact of open-source AID and peer support on children with diabetes and their caregivers and families, where commercial AID systems are not available or suitable. Further efforts are required to improve the effectiveness and usability and facilitate access for children with diabetes, worldwide, to benefit from this innovative treatment. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/15368.

Learning for Data Synthesis: Joint Local Salient Projection and Adversarial Network Optimization for Vehicle Re-Identification.

The problem of vehicle re-identification in surveillance scenarios has grown in popularity as a research topic. Deep learning has been successfully applied in re-identification tasks in the last few years due to its superior performance. However, deep learning approaches require a large volume of training data, and it is particularly crucial in vehicle re-identification tasks to have a sufficient amount of varying image samples for each vehicle. To collect and construct such a large and diverse dataset from natural environments is labor intensive. We offer a novel image sample synthesis framework to automatically generate new variants of training data by augmentation. First, we use an attention module to locate a local salient projection region in an image sample. Then, a lightweight convolutional neural network, the parameter agent network, is responsible for generating further image transformation states. Finally, an adversarial module is employed to ensure that the images in the dataset are distorted, while retaining their structural identities. This adversarial module helps to generate more appropriate and difficult training samples for vehicle re-identification. Moreover, we select the most difficult sample and update the parameter agent network accordingly to improve the performance. Our method draws on the adversarial networks strategy and the self-attention mechanism, which can dynamically decide the region selection and transformation degree of the synthesis images. Extensive experiments on the VeRi-776, VehicleID, and VERI-Wild datasets achieve good performance. Specifically, our method outperforms the state-of-the-art in MAP accuracy on VeRi-776 by 2.15%. Moreover, on VERI-Wil, a significant improvement of 7.15% is achieved.

High-density lipoprotein cholesterol to apolipoprotein A1 ratio and all-cause mortality among incident peritoneal dialysis patients.

BACKGROUND AND AIMS: The ratio of high-density lipoprotein cholesterol to apolipoprotein A1 (HAR) is associated with all-cause mortality in nonchronic kidney disease patients, but its role in predicting all-cause mortality in patients undergoing peritoneal dialysis (PD) is still unclear. The purpose of this study was to investigate the relationship between HAR and all-cause mortality in patients with PD. METHODS AND RESULTS: The medical records of 1199 patients with PD from November 1, 2005, to August 31, 2019, were collected retrospectively. The main outcome was defined as all-cause mortality. The HAR was divided into three groups by X-tile software. The association between HAR and all-cause mortality was evaluated by Cox models. The Kaplan-Meier method was used for the survival curve. The median follow-up period was 35 months (interquartile range: 20-57 months), with a total of 326 deaths recorded. After multiple adjustments, the risk of all-cause mortality in the high HAR group was 1.96-fold higher than that in the low HAR group (hazard ratio: 1.96; 95% CI, 1.22 to 3.15; P = 0.005). The restricted cubic splines showed that the risk of all-cause mortality increased gradually when HAR was >0.37. In the stratified analysis, a high HAR was linked to a high risk of all-cause mortality in males, patients under 55 years old, and patients without diabetes or cardiovascular disease (CVD). CONCLUSION: This study suggests that HAR is independently related to all-cause mortality in PD patients, especially in males, patients under 55 years old, and patients without diabetes or CVD.

SIRT1 downregulated FGB expression to inhibit RCC tumorigenesis by destabilizing STAT3.

Renal cell carcinoma (RCC) is one of the common lethal urologic tumors. Recent studies revealed that SIRT1 might function as a tumor suppressor during the progression of RCC. In addition, studies showed that FGB expression was abnormally upregulated in RCC and related to the progress of RCC. This study aimed to define the function of SIRT1 and underlying mechanism in the RCC progression. The expression of SIRT1 and FGB in RCC specimens and cells were detected by immunoblotting and immunostaining. Luciferase reporter assay was performed to confirm FGB as the target gene of STAT3. Other methods including stable transfection, co-immunoprecipitation, Western blot, and in vitro and in vivo proliferation assays were also performed. Our results showed that SIRT1 expression was downregulated in RCC tissues compared to adjacent normal tissues and relatively high expression of SIRT1 conferred a better prognosis for patients. Next, we showed that SIRT1 overexpression inhibited RCC tumorigenesis both in vitro and in vivo. In addition, FGB expression was upregulated in RCC tissues and overexpressing SIRT1 reduced FGB expression levels. Furthermore, inhibition of RCC proliferation by SIRT1 overexpression was rescued by FGB overexpression, indicating that SIRT1 inhibited RCC proliferation by repressing FGB expression. Mechanistically, we confirmed that FGB was the target gene of STAT3, and SIRT1 repressed the expression of FGB by deacetylation of STAT3, leading to STAT3 destabilization and degradation. SIRT1 inhibited RCC tumorigenesis by downregulating FGB expression, and this novel SIRT1-STAT3-FGB axis provided a potential target for RCC therapy.

Serum C-reactive protein to albumin ratio and mortality associated with peritoneal dialysis.

Background: Serum C-reactive protein to albumin ratio (CAR) was recently identified as a poor marker of prognosis among various populations. The current study aimed to examine the association between CAR and all-cause mortality among patients undergoing peritoneal dialysis (PD).Methods: A total of 758 patients with PD were included in this study during the period from 1 November 2005 to 28 February 2017 and followed up until 31 May 2017. The primary outcome was all-cause mortality. We used multivariate Cox proportional hazard models and Kaplan-Meier survival curves to assess the relationship between CAR and all-cause mortality in these patients.Results: Among 758 participants, mean age was 49.1 ± 14.2 years, with 56% males and 18.6% prevalence of diabetes. Median CAR was 0.13 (interquartile range [IQR], 0.07-0.34). After 27 months (IQR, 14-40 months) of follow-up, 157 deaths had been reported. After adjusting for confounding factors, we found a significant association between serum CAR and all-cause mortality among those in the highest CAR group (hazard ratio 1.91, 95% confidence interval 1.05- 3.47, p = 0.034).Conclusions: In patients undergoing PD, an increase in serum CAR is independently associated with increased risk for all-cause mortality.

Electronic Tongue Recognition with Feature Specificity Enhancement.

As a kind of intelligent instrument, an electronic tongue (E-tongue) realizes liquid analysis with an electrode-sensor array and certain machine learning methods. The large amplitude pulse voltammetry (LAPV) is a regular E-tongue type that prefers to collect a large amount of response data at a high sampling frequency within a short time. Therefore, a fast and effective feature extraction method is necessary for machine learning methods. Considering the fact that massive common-mode components (high correlated signals) in the sensor-array responses would depress the recognition performance of the machine learning models, we have proposed an alternative feature extraction method named feature specificity enhancement (FSE) for feature specificity enhancement and feature dimension reduction. The proposed FSE method highlights the specificity signals by eliminating the common mode signals on paired sensor responses. Meanwhile, the radial basis function is utilized to project the original features into a nonlinear space. Furthermore, we selected the kernel extreme learning machine (KELM) as the recognition part owing to its fast speed and excellent flexibility. Two datasets from LAPV E-tongues have been adopted for the evaluation of the machine-learning models. One is collected by a designed E-tongue for beverage identification and the other one is a public benchmark. For performance comparison, we introduced several machine-learning models consisting of different combinations of feature extraction and recognition methods. The experimental results show that the proposed FSE coupled with KELM demonstrates obvious superiority to other models in accuracy, time consumption and memory cost. Additionally, low parameter sensitivity of the proposed model has been demonstrated as well.

Triglyceride to high-density lipoprotein cholesterol ratio is associated with increased mortality in older patients on peritoneal dialysis.

BACKGROUND: The triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio (TG/HDL-C) has been suggested as a simple method to identify unfavorable cardiovascular (CV) outcomes in the general population. The aim of this study was to investigate the association between the TG/HDL-C ratio and all-cause and CV mortality in peritoneal dialysis (PD) patients. METHODS: We retrospectively analyzed patients on PD from November 1, 2005, to February 28, 2017, with a follow-up period lasting until May 31, 2017. The main outcomes were all-cause and CV mortality. RESULTS: Among the 973 PD patients, the mean age was 49.67 ± 14.58 (y). During a median follow-up period of 27.2 months (IQR = 13.4-41.5 months), 229 (23.5%) patients died, with 120 (12.3%) dying as a result of CV diseases. The median serum TG/HDL-C ratio was 1.11 (IQR = 0.71-1.80). In a multivariate Cox regression analysis, patients with higher TG/HDL-C ratio levels (tertile 3) had a higher incidence of CV mortality (adjusted HR = 2.12; 95% CI: 1.21-3.72; P = 0.009) and all-cause mortality (adjusted HR = 2.08; 95% CI: 1.37-3.14; P = 0.001) compared to patients in tertile 1. These associations persisted after excluding the patients who have already taken lipid-lowering medications. For older patients (> 60 years), each 1-unit higher baseline TG/HDL-C level was associated with a 48% (95% CI: 1.06-2.07; P = 0.021) increased risk of all-cause mortality and a 59% (95% CI: 1.03-2.45; P = 0.038) increased risk of CV mortality; however, this association was not observed in patients ≤60 years of age. CONCLUSIONS: A higher serum TG/HDL-C ratio was an independent predictor of all-cause and CV mortality in PD patients. Furthermore, an elevated TG/HDL-C ratio was significantly associated with higher all-cause and CV mortality in older PD patients.

Serum lipoprotein(a) and risk of hemorrhagic stroke among incident peritoneal dialysis patients: a large study from a single center in China.

Background: This retrospective study investigated whether baseline serum lipoprotein(a) (Lp(a)) may predict subsequent stroke in patients under chronic peritoneal dialysis (PD). Methods: Eight hundred and sixty incident PD patients, treated from 1 November 2005 to 28 February 2017, were enrolled, and followed until discontinuation of PD, death, or 31 May 2017. Hemorrhagic or ischemic stroke was the primary outcome. The population was stratified by baseline serum Lp(a) tertile. The risk of each stroke subtype was analyzed using the Cox proportional hazard models. Adjustments were made for: age; gender; history of stroke and hypertension; systolic blood pressure; lipid-lowering, antiplatelet and antihypertensive medications; laboratory profiles including hemoglobin, serum albumin, calcium, triglyceride, total and low-density lipoprotein cholesterol; and apolipoprotein A1. Results: Among the 860 participants, 19.3% and 4.1% had diabetes mellitus and a history of stroke, respectively. The median baseline serum Lp(a) was 328 (172-585) mg/L. After 28 (14-41) months of follow-up, 33 (3.84%) and 12 (1.40%) patients developed hemorrhagic and ischemic stroke, respectively. Participants in the highest Lp(a) tertile had a significantly lower risk of hemorrhagic stroke compared with those in the lowest tertile (hazard ratio (HR) 0.3, 95% confidence interval (CI) 0.1-0.86; p = .026); the rates of ischemic stroke were comparable among the tertiles. Each 10 mg/L rise in serum Lp(a) was associated with a 2% (95% CI 0.96-1; p = .033) lower risk of hemorrhagic stroke. Conclusions: Among patients with incident PD, a higher serum Lp(a) level may predict a lower risk of hemorrhagic stroke.

Comparison of risk of stroke in patients treated with peritoneal dialysis and hemodialysis: a systematic review and meta-analysis.

Objective: Accumulating evidence has demonstrated that dialysis patients are at increased risk for stroke. However, the impact of dialysis modalities on stroke risk remains controversial. We conducted a systematic review and meta-analysis to determine the effect of peritoneal dialysis (PD) and hemodialysis (HD) on stroke risk. Methods: A systematic search of PubMed, EMBASE, and Web of Science was performed to identify articles comparing the stroke outcomes of dialysis patients. Hazard ratios (HRs) with 95% confidence intervals (95% CIs) were extracted and synthesized to examine stroke outcomes, including ischemic stroke, hemorrhagic stroke, and overall stroke. Results: The search yielded five studies composed of 1,219,245 patients that were evaluated in the final analysis. The results showed that PD was associated with a lower risk for hemorrhagic stroke compared with HD (HR = 0.78; 95% CI: 0.69-0.88; p < 0.001). For ischemic stroke, the results showed that PD was associated with a higher risk compared with HD among the non-Asian patients (HR = 1.13; 95% CI: 1.05-1.23; p = 0.002), but there were no significant differences between PD and HD for the Asian patients. Similarly, there were no significant differences between the effects of the PD and HD approaches on overall stroke risk. Conclusions: We observed that PD patients were less likely to develop hemorrhagic stroke than HD patients, and the risk for ischemic stroke was significantly higher for PD patients than for HD patients among the non-Asian patients. However, our findings could be biased due to the heterogeneity of the included studies.

Relationship between serum bilirubin levels and mortality in patients on peritoneal dialysis.

Background: Studies have shown that the serum total bilirubin (TBil) is associated with the mortality of the general population and of hemodialysis patients. However, few studies have examined the associations of the direct bilirubin (DBil) and indirect bilirubin (IBil) with the mortality of peritoneal dialysis (PD) patients. Methods: This was a retrospective cohort study. Clinical and laboratory data were collected from 740 PD patients. The primary endpoint was 5-year all-cause mortality. Survival analysis was performed using the Kaplan-Meier method with the log-rank test. The mortality hazard ratio was evaluated using Cox regression models. Results: Among the 740 PD patients, the mean age was 49.9 ± 15.0 years, 54.9% were men, and 20.3% had diabetes. During the median follow-up period of 28 months (interquartile range, 14-41 months), 178 patients died. Kaplan-Meier analysis revealed that all-cause mortality was higher in the patients in the higher TBil group than in the lower TBil group (25.6% vs. 18.3%, p = .017) and in patients in the higher IBil group than in the lower IBil group (24.3% vs. 19%, p = .026). Multivariate analysis showed that compared with the lower TBil group, the 5-year mortality risk was higher in the higher TBil group (HR = 1.69, 95% CI: 1.11-2.56, p = .014). Similarly, there was a 56% higher risk of 5-year mortality in the higher IBil group than in the lower IBil group (HR = 1.56, 95% CI: 1.04-2.34, p = .032). However, no such associations were observed between the DBil and the mortality risk. Conclusions: The baseline serum TBil and IBil levels were significantly associated with 5-year all-cause mortality among PD patients.

Serum alkaline phosphatase levels correlate with long-term mortality solely in peritoneal dialysis patients with residual renal function.

Introduction: Increased serum alkaline phosphatase (ALP) is predictive of a higher mortality in patients with end-stage renal disease. However, it remains unknown whether residual renal function (RRF) influences the outcome-association of serum ALP among peritoneal dialysis (PD) patients. Methods: A total of 650 incident PD patients receiving PD catheter implantation in an institute between 1 November 2005 and 28 February 2017 were retrospectively enrolled. These patients were divided into groups with and without RRF (RRF and non-RRF groups) and those with serum ALP levels in tertiles. The Kaplan-Meier method and multivariate Cox proportional hazard models were used to analyze their outcomes based on RRF and serum ALP levels. Results: These 650 patients had a mean age of 49.4 ± 14.0 years old, their median ALP level was 74 U/L (interquartile range (IQR): 59-98). After 28-month (IQR: 14-41) follow-up, 80 patients in RRF group and 40 patients in non-RRF group died. PD patients with the highest serum ALP tertile had significant lower survival (p = .014), when compared to other patients in the RRF group. However, this relationship was not observed in patients in the non-RRF group. After multivariate adjustment, in the RRF group, patients with the highest ALP tertile had a significantly higher risk of mortality (hazard ratio (HR): 2.26, 95% confidence interval (CI): 1.06-4.82, p = .034). Each 10-U/L increase in ALP level was associated with a 4% (HR: 1.04, 95% CI: 1.00-1.08, p = .045) higher mortality risk. Conclusions: Higher serum ALP level is associated with increased mortality solely in PD patients with RRF.

Active Learning on Dynamic Clustering for Drift Compensation in an Electronic Nose System.

Drift correction is an important concern in Electronic noses (E-nose) for maintaining stable performance during continuous work. A large number of reports have been presented for dealing with E-nose drift through machine-learning approaches in the laboratory. In this study, we aim to counter the drift effect in more challenging situations in which the category information (labels) of the drifted samples is difficult or expensive to obtain. Thus, only a few of the drifted samples can be used for label querying. To solve this problem, we propose an innovative methodology based on Active Learning (AL) that selectively provides sample labels for drift correction. Moreover, we utilize a dynamic clustering process to balance the sample category for label querying. In the experimental section, we set up two E-nose drift scenarios-a long-term and a short-term scenario-to evaluate the performance of the proposed methodology. The results indicate that the proposed methodology is superior to the other state-of-art methods presented. Furthermore, the increasing tendencies of parameter sensitivity and accuracy are analyzed. In addition, the Label Efficiency Index (LEI) is adopted to measure the efficiency and labelling cost of the AL methods. The LEI values indicate that our proposed methodology exhibited better performance than the other presented AL methods in the online drift correction of E-noses.