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Context.— Galectin-9 reduces tissue damage in certain immune-mediated glomerular diseases. However, its role in structural and functional renal changes in patients with varying types of chronic kidney disease (CKD) is less clear. Objective.— To investigate the association between plasma galectin-9 levels, proteinuria, tubulointerstitial lesions, and renal function in different CKD stages. Design.— We measured plasma galectin-9 levels in 243 patients undergoing renal biopsy for determining the CKD etiology. mRNA and protein expression levels of intrarenal galectin-9 were assessed by quantitative real-time polymerase chain reaction and immunostaining. Relationships between plasma galectin-9, clinical characteristics, and tubulointerstitial damage were analyzed with logistic regression. We investigated galectin-9 expression patterns in vitro in murine J774 macrophages treated with differing stimuli. Results.— To analyze the relationship between galectin-9 and clinical features, we divided the patients into 2 groups according to median plasma galectin-9 levels. The high galectin-9 group tended to be older and to have decreased renal function, higher proteinuria, and greater interstitial fibrosis. After multivariable adjustment, elevated plasma galectin-9 levels were independently associated with stage 3b or higher CKD. An analysis of gene expression in the tubulointerstitial compartment in the biopsy samples showed a significant positive correlation between intrarenal galectin-9 mRNA expression and plasma galectin-9 levels. Immunohistochemistry confirmed increased galectin-9 expression in the renal interstitium of patients with advanced CKD, and most galectin-9–positive cells were macrophages, as determined by double-immunofluorescence staining. In vitro experiments showed that galectin-9 expression in macrophages was significantly increased after interferon-γ stimulation. Conclusions.— Our findings suggest that plasma galectin-9 is a good biomarker for diagnosing advanced CKD.

Objectives Type 2 diabetes mellitus (T2DM) imposes a great burden on healthcare systems, and these patients experience higher long-term risks for developing end-stage renal disease (ESRD). Managing diabetic nephropathy becomes more challenging when kidney function starts declining. Therefore, developing predictive models for the risk of developing ESRD in newly diagnosed T2DM patients may be helpful in clinical settings. Methods We established machine learning models constructed from a subset of clinical features collected from 53,477 newly diagnosed T2DM patients from January 2008 to December 2018 and then selected the best model. The cohort was divided, with 70% and 30% of patients randomly assigned to the training and testing sets, respectively. Results The discriminative ability of our machine learning models, including logistic regression, extra tree classifier, random forest, gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and light gradient boosting machine were evaluated across the cohort. XGBoost yielded the highest area under the receiver operating characteristic curve (AUC) of 0.953, followed by extra tree and GBDT, with AUC values of 0.952 and 0.938 on the testing dataset. The SHapley Additive explanation summary plot in the XGBoost model illustrated that the top five important features included baseline serum creatinine, mean serum creatine within 1 year before the diagnosis of T2DM, high-sensitivity C-reactive protein, spot urine protein-to-creatinine ratio and female gender. Conclusions Because our machine learning prediction models were based on routinely collected clinical features, they can be used as risk assessment tools for developing ESRD. By identifying high-risk patients, intervention strategies may be provided at an early stage.

An 86-year-old man presented to the emergency room with vomiting and melena. The patient was hemodynamically stable and remained alert and orientated. According to his family, ingestion of a pack of disposable hand warmers, which he mistook for black sesame powder, occurred 17 h prior to admission. Before ingestion, he mixed the powder with warm water. Physical examination revealed no thermal injury of the oral mucosa with no abdominal pain or tenderness. An abdominal plain film showed multiple scattered radiopaque material with zonal distribution over the right abdomen. An intravenous 500-mg deferoxamine challenge test showed no vin rosé urine discoloration. Serial serum iron levels remained within the normal range. The patient remained clinically stable with no medical complications. He was discharged 3 days after admission. The hand warmers consisted of iron powder (50% w/w), sodium chloride, activated charcoal, and nontoxic vermiculite: a potential risk for intestinal thermal injury. In this case, the water added beforehand rapidly terminated the iron oxidation reaction. This explained the lack of thermal injury. Ferric oxide is poorly absorbed by the digestive tract and explained the absence of iron intoxication. Therefore, clinicians should clarify the method of ingestion. If a hand warmer has been premixed with water, less mucosa injury can be expected with a lower risk of iron intoxication. This report also provided evidence that abdominal plain films can be used to confirm the ingestion of iron and monitor its elimination.

The 2019 Kidney Disease Outcome Quality Initiative (K/DOQI) guideline recommended evaluating arteriovenous fistula (AVF) malfunction risks primarily based on clinical monitoring, which can be assisted with the value of vascular access flow (Qa). Nevertheless, Qa thresholds recommended by different guidelines vary, ranging from 300 to 500 ml/min. This study investigated the optimal Qa threshold to predict future functional patency in AVFs with Qa 500 ml/min.Both the clinical indicators of access dysfunction and the Qa value were monitored in patients receiving hemodialysis by the radiocephalic AVF. Routine access flow surveillance was performed by the ultrasound dilution method (HD03, Transonic Inc.). The development of clinically significant indicators of access dysfunction, which necessitated percutaneous transluminal angiography (PTA) to maintain functional patency, was analyzed in this cohort.Among the enrolled 302 patients, Qa of 52 patients was under 500 ml/min. These 52 patients received 2 Qa measurements during the follow-up period. Of these 52 patients, serial Qa of 17 patients varied trivially and their AVF remained functional. Multivariable logistic regression analysis revealed that a low Qa per ideal body weight (IBW) is an independent predictor of AVF functional loss. Receiver operating characteristic curve analysis of Qa/IBW in predicting future AVF functional loss revealed that the best cutoff value of Qa is 7.1 times the IBW.For radiocephalic AVFs with Qa 500 ml/min, the minimally required Qa to maintain access function is associated with individual IBW. The IBW-based Qa threshold assessment would allow more flexibility in the treatment of patients and reduce unnecessary invasive measures.

End-stage kidney disease (ESKD) is a global burden that reflects each country's unique condition. We used the National Health Insurance Research Database (NHIRD) of Taiwan to decipher changes in the mortality and international survival rates and to determine the effectiveness of the pre-end-stage renal disease care program (pre-ESRD care program) to guide future health policies for ESKD.We conducted a retrospective cohort analysis of the NHIRD data along with records from the catastrophic illness certificate program of ESKD patients from 2010 to 2018.From 2010 to 2018, the annual dialysis-related mortality rate in Taiwan increased from 10.6 to 11.8 deaths per hundred patient-years. The mortality rate for patients below 40 years appears to be decreasing, reflecting the improved quality of care for ESKD patients. Patients above 75 years showed increasing mortality, indicating the prolonged survival and aging of the ESKD population. Patients undergoing dialysis who participated in the pre-ESRD care program had a higher post-dialysis initiation life expectancy than those who did not participate. Among the program enrollees, the post-dialysis initiation life expectancy was higher in patients who had participated for more than one year. Taiwan has one of the highest ESKD patient survival rates globally.From 2010 to 2018, the reduced mortality in young patients and aging of the ESKD population might indicate that the quality of care in Taiwan for ESKD has improved. Furthermore, a better survival rate after dialysis initiation was observed in the pre-ESRD care program participants.

Introduction: Viable vascular access is the lifeline for hemodialysis patients. In the nondialysis population, emerging evidence suggests that circulating pentraxin 3 (PTX3), neutrophil gelatinase-associated lipocalin (NGAL), and chitinase-3-like protein 1 (CHI3L1) are associated with cardiovascular inflammation and endothelial injury. However, predictive values of these three biomarkers on arteriovenous fistula (AVF) outcomes are unknown. Methods: This prospective observational cohort study enrolled 135 hemodialysis patients using AVF and then followed them for 3 years. Plasma levels of PTX3, NGAL, and CHI3L1 were measured. Patients were followed up prospectively for two clinical outcomes, including AVF functional patency loss and death. Cox proportional hazards regression models were used to analyze hazard ratios for the commencement of AVF functional patency loss and mortality. Results: Among 135 patients, the mean age was 66.0 ± 15.7 years old and 48.1% were male. The plasma level of PTX3, NGAL, and CHI3L1 was 2.8 ± 2.3 ng/mL, 349.2 ± 111.4 ng/mL, and 185.5 ± 66.8 ng/mL, respectively. During a 3-year follow-up period, the plasma level of PTX3 was an independent predictor for AVF functional patency loss (per 1 ng/mL increase, HR 1.112 [95% CI: 1.001–1.235], p = 0.048). Besides, patients with higher plasma levels of PTX3 were more likely to suffer from cardiovascular mortality (per 1 ng/mL increase, HR 1.320 [95% CI: 1.023–1.703], p = 0.033), infectious mortality (per 1 ng/mL increase, HR 1.394 [95% CI: 1.099–1.769], p = 0.006), and all-cause mortality (per 1 ng/mL increase, HR 1.233 [95% CI: 1.031–1.476], p = 0.022). Conclusions: The plasma level of PTX3, not NGAL or CHI3L1, was associated with higher risks of AVF functional patency loss in chronic hemodialysis patients, showing its value in reflecting AVF endothelial dysfunction. Furthermore, PTX3 also predicts mortality in chronic hemodialysis patients.

One of the critical factors of project success is the interface management. Past project interface management mainly relies on knowledge and experience of the project managers. The existing studies of project interface management also mainly focused on the definition and the classification of project interfaces. There is no workable and flexible framework for construction interface problem identification and solutions. This study conducted an analogic study of contradiction matrix at Theory of Inventive Problem Solving (TRIZ) to develop such a framework. This research collected around six hundred interface management cases from civil works and building projects. For comparison, this research defined an experimental group (TRIZ case) and a control group (experience-oriented solution case) based on the concept of clinical experiments in medical science to evaluate and improve the rationality of the matrix. Subsequently, based upon the theory of information retrieval (IR), this research conducted statistical evaluation and TRIZ features remedies to develop generalized construction interface problem identification and solutions. For solving project management interface problems, the TRIZ-analogic construction interface problem identification and solutions framework provides a systematic approach to develop more robust solutions for interface problems in construction engineering rather than just simply relying on intuitive experience.

The heart and kidneys had demonstrated a bidirectional interaction that dysfunction of the heart or kidneys can induce dysfunction in the other organ.Renal function and its decline during hospitalization may have impact on cardiovascular outcomes in patients with acute decompensated heart failure (ADHF).A total of 119 consecutive Chinese patients admitted for ADHF were prospectively enrolled. The course of renal function was presented with estimated glomerular filtration rate (eGFR), calculated by the four-variable equation proposed by the Modification of Diet in Renal Disease (MDRD) Study. Worsening renal function (WRF) was defined as eGFR decline between admission (eGFRDuring an average 2.6 ± 3.2 years follow-up, 66 patients (55%) experienced 4P-MACE. Patients with impaired eGFRImpaired renal function before discharge, but not impaired renal function on admission or WRF, is a significant risk factor for poor outcomes in patients with ADHF.

This study applies the dynamic slacks-based measure (DSBM) and the total-factor agricultural efficiency (TFAE) to explore the overall agricultural production efficiency of 30 administrative regions and the eastern, central, and western regions of China from 2012 to 2016. The previous literature has mainly focused on China’s economic development and experience, but as the economy continues to grow, more food is needed and agricultural labor is shifting to urban areas. Little attention has been paid to the impact of limited agricultural land on agricultural production efficiency. Therefore, this paper uses the agricultural land area as the carry-over variable and uses agricultural labor, total agricultural machinery power, rural electricity consumption, agricultural fertilizer use, and agricultural GDP as variables to discuss the efficiency of agricultural production in different regions. The empirical results show that from 2012 to 2016, the best administrative region in terms of overall agricultural production efficiency in China was the east. In terms of the overall analysis of the region, the east had the highest overall agricultural production efficiency, while the central region had the lowest. The input variable that needed the most improvement was rural electricity consumption, with the largest adjustment in rural electricity consumption being observed in Hebei and Liaoning provinces of the eastern region. Furthermore, from 2012 to 2016, both overall agricultural production efficiency and agricultural GDP showed upward trends. However, adjustments are still needed for other relevant agricultural input variables to effectively allocate resources and improve the overall agricultural production efficiency.

ObjectiveSLC12A3 (solute carrier family 12 member 3) gene variants are associated with diabetic nephropathy; however, their association with hypertensive nephropathy remains unknown. We aimed to investigate the association between SLC12A3 gene polymorphisms and renal function in patients with hypertension.MethodsParticipants from three non-diabetic hypertensive cohorts, including young-onset hypertension (cohort 1, n = 882), treatment-naïve hypertension (cohort 2, n = 90), and follow-up cohort (cohort 3, n = 166), underwent genotyping for single nucleotide polymorphisms in SLC12A3. Renal events were defined as a >25 and >50% decline in estimated glomerular filtration rate (eGFR).ResultsIn cohort 1, SLC12A3 rs16963397 C/C or C/G (P = 0.005), rs13334864 C/C or C/T (P = 0.020), and rs7187932 A/A or A/G polymorphisms (P = 0.014) had higher eGFRs compared to their counterparts, with similar findings observed in cohort 2. In cohort 3, over a mean follow-up of 5.8 ± 1.7 years, participants with either SLC12A3 rs16963397 C/C or rs13334864 C/C polymorphisms had more >25 and >50% eGFR decline than their counterparts (log-rank test, P = 0.058 and P = 0.038, respectively). Cox regression analysis revealed that SLC12A3 rs16963397 C/C and rs13334864 C/C polymorphisms were significantly associated with an increased risk of >25% [hazard ratio (HR), 3.294; 95% confidence interval (CI), 1.158–9.368; P = 0.025] and >50% decline in eGFR (HR, 18.630; 95% CI, 1.529–227.005, P = 0.022) than their counterparts.ConclusionSLC12A3 polymorphisms are associated with renal function in Chinese patients with hypertension.

BACKGROUND Anterior cruciate ligament (ACL) injuries are common in sports and are critical knee injuries that require prompt diagnosis. Magnetic resonance imaging (MRI) is a strong, noninvasive tool for detecting ACL tears, which requires training to read accurately. Clinicians with different experiences in reading MR images require different information for the diagnosis of ACL tears. Artificial intelligence (AI) image processing could be a promising approach in the diagnosis of ACL tears. OBJECTIVE This study sought to use AI to (1) diagnose ACL tears from complete MR images, (2) identify torn-ACL images from complete MR images with a diagnosis of ACL tears, and (3) differentiate intact-ACL and torn-ACL MR images from the selected MR images. METHODS The sagittal MR images of torn ACL (n=1205) and intact ACL (n=1018) from 800 cases and the complete knee MR images of 200 cases (100 torn ACL and 100 intact ACL) from patients aged 20-40 years were retrospectively collected. An AI approach using a convolutional neural network was applied to build models for the objective. The MR images of 200 independent cases (100 torn ACL and 100 intact ACL) were used as the test set for the models. The MR images of 40 randomly selected cases from the test set were used to compare the reading accuracy of ACL tears between the trained model and clinicians with different levels of experience. RESULTS The first model differentiated between torn-ACL, intact-ACL, and other images from complete MR images with an accuracy of 0.9946, and the sensitivity, specificity, precision, and F1-score were 0.9344, 0.9743, 0.8659, and 0.8980, respectively. The final accuracy for ACL-tear diagnosis was 0.96. The model showed a significantly higher reading accuracy than less experienced clinicians. The second model identified torn-ACL images from complete MR images with a diagnosis of ACL tear with an accuracy of 0.9943, and the sensitivity, specificity, precision, and F1-score were 0.9154, 0.9660, 0.8167, and 0.8632, respectively. The third model differentiated torn- and intact-ACL images with an accuracy of 0.9691, and the sensitivity, specificity, precision, and F1-score were 0.9827, 0.9519, 0.9632, and 0.9728, respectively. CONCLUSIONS This study demonstrates the feasibility of using an AI approach to provide information to clinicians who need different information from MRI to diagnose ACL tears.

ObjectivesMaintenance of vascular access (VA) patency after percutaneous transluminal angioplasty (PTA) is important and remains a challenge despite VA monitoring and surveillance. The aim of this study was to examine factors affecting the post-PTA arteriovenous access (AVA) patency in patients who have been on close VA monitoring and surveillance for access flow.DesignRetrospective cohort study.SettingA single medical centre in Taiwan.ParticipantsRecords of patients who received chronic haemodialysis between 1 January 2017 and 31 December 2018 were retrospectively reviewed. Patients were divided into two groups (without or with PTA intervention on AVA).Primary and secondary outcomePatients were followed until reintervention PTA, termination or abandoned VA or end of study. In addition to routine monitoring, VA flow surveillance was performed every 3 months for detection of VA dysfunction adhering to Kidney Disease Outcomes Quality Initiative guidelines.ResultsA total of 508 patients were selected for study inclusion (with PTA, n=231; without PTA, n=277). At baseline, variables that differed between groups included malignancy and levels of albumin, uric acid, potassium, phosphorous, high-density lipoprotein, total bilirubin and ferritin (all pConclusionsAVG access type, acute myocardial infarction, and high ferritin levels are risk factors for re-intervention post-PTA. These findings may be useful in the development of prophylactic strategies for monitoring VA function and tailoring surveillance programs for these dialysis patients.

Objectives Renal replacement therapy-requiring acute kidney injury frequently occurs in ICUs, which require evidence-based medical attention. However, in the postacute kidney injury patient population, the evidence regarding effective therapies to improve patient outcomes is lacking. Therefore, we aimed to examine whether the renin-angiotensin-aldosterone system blockade is effective in improving renal outcomes in postacute kidney injury patients who experienced temporary renal replacement therapy and have hypertension. Design A retrospective cohort study. Setting A nationwide database in Taiwan. Patients From January 1, 2000, to December 31, 2013, we identified 8,558 acute kidney injury patients with hypertension in the national registry database. All these patients experienced an acute kidney injury episode, which required temporary renal replacement therapy for at least once. Interventions Users (n = 3,885) and nonusers (n = 4,673) of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers. Measurements and main results We used Cox proportional hazards regression models to analyze hazard ratios for the commencement of end-stage renal disease and all-cause mortality for angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker users (n = 3,885) and nonusers (n = 4,673). In a median follow-up of 4.3 years, 5,880 patients (68.7%) required long-term dialysis, and 4,841 patients (56.6%) died. Compared with postacute kidney injury patients who did not use angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker, angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker users are marginally less likely to progress to end-stage renal disease (adjusted hazard ratio 0.95; 95% CI 0.90-1.01; p = 0.06) and significantly less likely to suffer from all-cause mortality (adjusted hazard ratio 0.93; 95% CI 0.87-0.98; p = 0.011). Conclusions In patients who experienced renal replacement therapy-requiring acute kidney injury and have hypertension, angiotensin-converting enzyme inhibitor/angiotensin II receptor blocker use is associated with better survival outcomes compared with nonuser.

The successful deployment of many emerging technologies, including the Internet of Things (IoT), will require battery-free electric power. Ideally, these emerging technologies will connect multiple, wide-ranging deployed nodes that can independently monitor and collect data, manage resources, and provide services efficiently and in real time. The increased demand for IoT applications in daily life will, in turn, propel demand for billions of sensor nodes [1] for tracking, assessing awareness and cognitive function, and human-machine interfacing, among other purposes [2]. Sensor nodes have already contributed to the past decade's massive development of low-power electronic devices for daily/weekly continuous operation. However, those devices still rely on batteries for power.

This paper builds a two-sector, two-factor environmental model in which agents optimally choose the clean and dirty goods in order to display their social status. In contrast to the conventional notion, we show that greater social aspirations in consumption regardless of either clean or dirty goods have an ambiguous impact on growth, depending on whether the production of conspicuous goods is relatively labor- or capital-intensive, whether the production of conspicuous goods generates more or fewer emissions, and whether labor supply is or is not responsive to social status seeking. By connecting two conflicting aspects of consumer preference involving social aspirations and environmental concerns, our analysis offers a novel explanation for the environmental Kuznets curve and a theoretical support for the empirical possibility of a negative employment-growth relationship and the so-called Green New Deal. Our welfare analysis shows that social comparisons in consumption may increase, rather than decrease, social welfare. The Pigovian tax may only be socially sub-optimal in the two-sector economy because it is unable to completely correct the distortion caused by consumption externalities.

It is well known that the heart and kidney have a bi-directional correlation, in which organ dysfunction results in maladaptive changes in the other. We aimed to investigate the impact of renal function and its decline during hospitalization on clinical outcomes in patients with acute decompensated heart failure (ADHF). A total of 119 consecutive Chinese patients admitted for ADHF were prospectively enrolled. The course of renal function was presented with estimated glomerular filtration rate (eGFR), calculated by the four-variable equation proposed by the Modification of Diet in Renal Disease (MDRD) Study. Worsening renal function (WRF), defined as eGFR decline between admission (eGFRadmission) and pre-discharge (eGFRpredischarge), occurred in 41 patients. Clinical outcomes during the follow-up period were defined as 4P-major adverse cardiovascular events (4P-MACE), including the composition of cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, and nonfatal HF hospitalization. During an average follow-up period of 2.6±3.2 years, 66 patients experienced 4P-MACE. Cox regression analysis revealed that impaired eGFRpredischarge, but not eGFRadmission or WRF, was significantly correlated with the development of 4P-MACE (HR, 2.003; 95% CI, 1.072–3.744; P=0.029). In conclusion, impaired renal function before discharge, but not WRF, is a significant risk factor for poor outcomes in patients with ADHF.

Arteriovenous fistula (AVF) is the vascular access of choice for renal replacement therapy. However, AVF is susceptible to calcification with a high prevalence of 40%-65% in chronic hemodialysis patients. Repeated needle puncture for hemodialysis cannulation results in intimal denudation of AVF. We hypothesized that exposure to blood shear stress in the medial layer promotes venous smooth muscle cell (SMC) osteogenesis. While previous studies of shear stress focused on arterial-type SMCs, SMCs isolated from the vein had not been investigated. This study established a venous cell model of AVF using the fluid shear device, combined with a high phosphate medium to mimic the uremic milieu. Osteogenic gene expression of venous SMCs upon mechanical and chemical cues was analyzed in addition to the activated cell signaling pathways. Our findings indicated that upon shear stress and high phosphate environment, mechanical stimulation (shear stress) had an additive effect in up-regulation of an early osteogenic marker, Runx2. We further identified that the integrin β1-ERK1/2 signaling pathway was responsible for the molecular basis of venous SMC osteogenesis upon shear stress exposure. Mitochondrial biogenesis also took part in the early stage of this venopathy pathogenesis, evident by the up-regulated mitochondrial transcription factor A and mitochondrial DNA polymerase γ in venous SMCs. In conclusion, synergistic effects of fluid shear stress and high phosphate induce venous SMC osteogenesis via the ERK1/2 pathway through activating the mechanosensing integrin β1 signaling. The present study identified a promising druggable target for reducing AVF calcification, which deserves further in vivo investigations.

Polyacrylonitrile (AN69) filter membranes adsorb cytokines during continuous venovenous hemofiltration (CVVH). Although high-volume hemofiltration has shown limited benefits, the dose-effect relationship in CVVH with AN69 membranes on severe sepsis remains undetermined. This multi-centered study enrolled 266 patients with sepsis-induced multiorgan dysfunction syndrome (MODS) who underwent CVVH with AN69 membranes between 2014 and 2015. We investigated the effects of ultrafiltration rates (UFR) on mortality. We categorized patients that were treated with UFR of 20–25 mL/kg/h as the standard UFR group (n = 124) and those that were treated with a UFR &gt, 25 mL/kg/h as the high UFR group (n = 142). Among the patient characteristics, the baseline estimated glomerular filtration rates (eGFR) &lt, 60 mL/min/1.73 m2, hemoglobin levels &lt, 10 g/dL, and a sequential organ failure assessment (SOFA) score ≥15 at CVVH initiation were independently associated with in-hospital mortality. In the subgroup analysis, for patients with SOFA scores that were ≥15, the 90-day survival rate was higher in the high UFR group than in the standard UFR group (HR 0.54, CI: 0.36–0.79, p = 0.005). We concluded that in patients with sepsis-induced MODS, SOFA scores ≥15 predicted a poor rate of survival. High UFR setting &gt, 25 mL/kg/h in CVVH with AN69 membranes may reduce the mortality risk in these high-risk patients.

Venous stenosis is the most common cause of arteriovenous fistula (AVF) failure in hemodialysis patients. For patients with AVF stenosis, the pressure over the antecedent part of the AVF stenotic lesion will increase if arterial inflow is sufficient. We report a chronic hemodialysis patient who received an angiographic examination for the juxta-anastomosis stenosis of his AVF. A unique feature of a collateral venous branch antecedent to the stenotic lesion was noted, resembling a musical sign as the “eighth note.” After percutaneous transluminal angioplasty, the eighth note attenuated markedly at once. Of note, the eighth note sign is not seen frequently, and thus we postulate that the formation of an eighth note sign on the radiocephalic fistula should fulfill the following requirements, including a sufficient arterial inflow, an adjacent collateral branch close enough to the arteriovenous anastomosis, a severe juxta-anastomotic stenotic lesion, and an intact ulnar venous drainage system.

In the present study, acute onset of severe lupus nephritis was successfully treated in mice using a new, benzamide-linked, small molecule that targets immune modulation and the NLRP3 inflammasome. Specifically, 6-(2,4-difluorophenyl)-3-(3-(trifluoromethyl)phenyl)-2H-benzo[e][1,3]oxazine-2,4(3H)-dione (Cf-02) (a) reduced serum levels of IgG anti-dsDNA, IL-1β, IL-6, and TNF-α, (b) inhibited activation of dendritic cells and differentially regulated T cell functions, and (c) suppressed the NF-κB/NLRP3 inflammasome axis, targeting priming and activating signals of the inflammasome. Moreover, treatment with Cf-02 significantly inhibited secretion of IL-1β in lipopolysaccharide-stimulated macrophages, but this effect was abolished by autophagy induction. These results recommend Cf-02 as a promising drug candidate for the serious renal conditions associated with systemic lupus erythematosus. Future investigations should examine whether Cf-02 may also be therapeutic in other types of chronic kidney disease involving NLRP3 inflammasome-driven signaling.

Background Anterior cruciate ligament (ACL) injuries are common in sports and are critical knee injuries that require prompt diagnosis. Magnetic resonance imaging (MRI) is a strong, noninvasive tool for detecting ACL tears, which requires training to read accurately. Clinicians with different experiences in reading MR images require different information for the diagnosis of ACL tears. Artificial intelligence (AI) image processing could be a promising approach in the diagnosis of ACL tears. Objective This study sought to use AI to (1) diagnose ACL tears from complete MR images, (2) identify torn-ACL images from complete MR images with a diagnosis of ACL tears, and (3) differentiate intact-ACL and torn-ACL MR images from the selected MR images. Methods The sagittal MR images of torn ACL (n=1205) and intact ACL (n=1018) from 800 cases and the complete knee MR images of 200 cases (100 torn ACL and 100 intact ACL) from patients aged 20-40 years were retrospectively collected. An AI approach using a convolutional neural network was applied to build models for the objective. The MR images of 200 independent cases (100 torn ACL and 100 intact ACL) were used as the test set for the models. The MR images of 40 randomly selected cases from the test set were used to compare the reading accuracy of ACL tears between the trained model and clinicians with different levels of experience. Results The first model differentiated between torn-ACL, intact-ACL, and other images from complete MR images with an accuracy of 0.9946, and the sensitivity, specificity, precision, and F1-score were 0.9344, 0.9743, 0.8659, and 0.8980, respectively. The final accuracy for ACL-tear diagnosis was 0.96. The model showed a significantly higher reading accuracy than less experienced clinicians. The second model identified torn-ACL images from complete MR images with a diagnosis of ACL tear with an accuracy of 0.9943, and the sensitivity, specificity, precision, and F1-score were 0.9154, 0.9660, 0.8167, and 0.8632, respectively. The third model differentiated torn- and intact-ACL images with an accuracy of 0.9691, and the sensitivity, specificity, precision, and F1-score were 0.9827, 0.9519, 0.9632, and 0.9728, respectively. Conclusions This study demonstrates the feasibility of using an AI approach to provide information to clinicians who need different information from MRI to diagnose ACL tears.

Background: The two ends of arteriovenous graft (AVG) are anastomosed to the upper limb vessels by surgery for hemodialysis therapy. However, the size of upper limb vessels varies to a large extent among different individuals. Methods: According to the shape and size of neck vessels quantified from the preoperative computed tomography angiographic scan, the ethylene-vinyl acetate (EVA)-based AVG was produced in H-shape by the three-dimensional (3D) printer and then sterilized. This study investigated the function of this novel 3D-printed AVG in vitro and in vivo. Results: This 3D-printed AVG can be implanted in the rabbit’s common carotid artery and common jugular vein with ease and functions in vivo. The surgical procedure was quick, and no suture was required. The blood loss was minimal, and no hematoma was noted at least 1 week after the surgery. The blood flow velocity within the implanted AVG was 14.9 ± 3.7 cm/s. Additionally, the in vitro characterization experiments demonstrated that this EVA-based biomaterial is biocompatible and possesses a superior recovery property than ePTFE after hemodialysis needle cannulation. Conclusions: Through the 3D printing technology, the EVA-based AVG can be tailor-made to fit the specific vessel size. This kind of 3D-printed AVG is functioning in vivo, and our results realize personalized vascular implants. Further large-animal studies are warranted to examine the long-term patency.

Emerging evidence suggests that intestinal dysbiosis plays an important role in host inflammation locally and systemically. Such pathological condition is even more prevailing in patients with chronic kidney disease (CKD). Of note, indoxyl sulphate (IS), a gut-derived uremic toxin, is notorious for its pro-inflammatory feature in CKD patients. IS accumulates in the body as the urinary excretion of uremic toxins is impaired, and further worsens the kidney function in a vicious cycle to CKD. Dietary restriction in vegetables, fruits and yogurt leads to the predominance of indole-producing intestinal microbial flora and further exaggerates the accumulation of IS in CKD patients. Recently, interventional studies have shown that circulating IS can be reduced by dietary prebiotic and/or probiotic supplements. However, further randomized controlled trials are warranted to examine whether such beneficial effect of dietary prebiotic/probiotic supplements could be extrapolated to better hard outcomes in CKD population. In this review, we would also like to emphasize the importance of achieving sufficient intake of dietary fibre by proper vegetable pre-treatment and accurate fruit selection, instead of directly avoiding these potassium-rich yet fibre-rich and base-producing foods.

Background Life-long peritoneal dialysis (PD) as a renal replacement therapy is limited by peritoneal fibrosis. Previous studies showed immunomodulatory and antifibrotic effects of adipose-derived mesenchymal stem cells (ADSCs) on peritoneal fibrosis. However, the role of the peritoneal macrophage in this process remains uninvestigated. Methods We examined the therapeutic effects of ADSC and bone marrow-derived mesenchymal stem cells (BM-MSC) in the rat model of dialysis-induced peritoneal fibrosis using methylglyoxal. In addition, treatment of macrophages with the conditioned medium of ADSC and BM-MSC was performed individually to identify the beneficial component of the stem cell secretome. Results In the in vivo experiments, we found dialysis-induced rat peritoneal fibrosis was attenuated by both ADSC and BM-MSC. Interestingly, ADSC possessed a more prominent therapeutic effect than BM-MSC in ameliorating peritoneal membrane thickening while also upregulating epithelial cell markers in rat peritoneal tissues. The therapeutic effects of ADSC were positively associated with M2 macrophage polarization. In the in vitro experiments, we confirmed that interleukin-6 (IL-6) secreted by MSCs upon transforming growth factor-β1 stimulation promotes M2 macrophage polarization. Conclusions In dialysis-induced peritoneal fibrosis, MSCs are situated in an inflammatory environment of TGF-β1 and secrete IL-6 to polarize macrophages into the M2 phenotype. Our findings reveal a previously unidentified role of tissue macrophage in this antifibrotic process. ADSC has the advantage of abundance and accessibility, making the application values extremely promising. Graphical abstract In dialysis-induced peritoneal fibrosis, peritoneal mesothelial cells secrete transforming growth factor-β1 (TGF-β1) when exposed to methylglyoxal (MGO)-containing peritoneal dialysate. When situated in TGF-β1, the inflammatory environment induces mesenchymal stem cells to secrete interleukin-6 (IL-6), IL-6 polarizes macrophages into the M2 phenotype. The dominant peritoneal tissue M2 macrophages, marked by upregulated Arg-1 expression, account for the attenuation of MGO-induced dedifferentiation of peritoneal mesothelial cells to maintain epithelial integrity.

BK polyomavirus nephropathy (BKVN) and allograft rejection are two closely-associated diseases on opposite ends of the immune scale in kidney transplant recipients. The principle of balancing the immune system remains the mainstay of therapeutic strategy. While patient outcomes can be improved through screening, risk factors identification, and rapid reduction of immunosuppressants, a lack of standard curative therapy is the primary concern during clinical practice. Additionally, difficulty in pathological differential diagnosis and clinicopathology’s dissociation pose problems for a definite diagnosis. This article discusses the delicate evaluation needed to optimize immunosuppression and reviews recent advances in molecular diagnosis and immunological therapy for BKVN patients. New biomarkers for BKVN diagnosis are under development. For example, measurement of virus-specific T cell level may play a role in steering immunosuppressants. The development of cellular therapy may provide prevention, even a cure, for BKVN, a complex post-transplant complication.

In the past, energy and environmental research focused on the performance of individual efficiencies. In order to make up for the research deficiencies, this research uses SBM (slack-based measures) dynamic network DEA (DN-SBM) to assess energy, health efficiency, and DN-TFP productivity changes from 2011 to 2015. This research uses forest area as the carryover that can objectively measure the performance of OECD energy, health, and total efficiency, and calls for the importance of forest protection and planting. The empirical results show that Estonia, Finland, Hungary, Iceland, Mexico, New Zealand, Portugal, Slovenia, Sweden, and Turkey have the best overall efficiency performance, while Ireland (0.4469), Israel (0.4179), and the Netherlands (0.3697) are the three worst. In total, 29 economies show progress in terms of productivity. Moreover, Chile (0.9706), Mexico (0.9995), Slovak Republic (0.9942), Turkey (0.9815), and the UK (0.9886) exhibit a slight decline. The overall efficiency value of 20 countries is greater than the average, and their productivity is showing an upward trend. Only the UK (0.5081, 0.9886) has an overall efficiency value that is less than the overall average with productivity that is showing a drop. About research method, this study utilizes dynamic intertemporal data to evaluate the changes in the overall efficiency and productivity of OECD members with DN-SBM and DN-TFP indices in order to offer more objective research results for various economies that are useful for formulating policies related to energy, national health, and forest conservation.

BACKGROUND Hemodialysis (HD) therapy is an indispensable tool used in critical care management. Patients undergoing HD are at risk for intradialytic adverse events, ranging from muscle cramps to cardiac arrest. So far, there is no effective HD device–integrated algorithm to assist medical staff in response to these adverse events a step earlier during HD. OBJECTIVE We aimed to develop machine learning algorithms to predict intradialytic adverse events in an unbiased manner. METHODS Three-month dialysis and physiological time-series data were collected from all patients who underwent maintenance HD therapy at a tertiary care referral center. Dialysis data were collected automatically by HD devices, and physiological data were recorded by medical staff. Intradialytic adverse events were documented by medical staff according to patient complaints. Features extracted from the time series data sets by linear and differential analyses were used for machine learning to predict adverse events during HD. RESULTS Time series dialysis data were collected during the 4-hour HD session in 108 patients who underwent maintenance HD therapy. There were a total of 4221 HD sessions, 406 of which involved at least one intradialytic adverse event. Models were built by classification algorithms and evaluated by four-fold cross-validation. The developed algorithm predicted overall intradialytic adverse events, with an area under the curve (AUC) of 0.83, sensitivity of 0.53, and specificity of 0.96. The algorithm also predicted muscle cramps, with an AUC of 0.85, and blood pressure elevation, with an AUC of 0.93. In addition, the model built based on ultrafiltration-unrelated features predicted all types of adverse events, with an AUC of 0.81, indicating that ultrafiltration-unrelated factors also contribute to the onset of adverse events. CONCLUSIONS Our results demonstrated that algorithms combining linear and differential analyses with two-class classification machine learning can predict intradialytic adverse events in quasi-real time with high AUCs. Such a methodology implemented with local cloud computation and real-time optimization by personalized HD data could warn clinicians to take timely actions in advance.

This case report describes a 56-year-old woman receiving regular hemodialysis for three years who presented with an unsteady gait for one month, dysarthria, and frequent choking on liquids for two weeks. Brain MRI revealed a characteristic "lentiform fork sign" with hyperintense T2W/FLAIR signal in the bilateral lentiform nuclei and restricted diffusion in bilateral globus pallidus. She was inadvertently prescribed metformin 1,000 mg per day one month ago by a physician who was unaware of her end-stage kidney disease. After intensive hemodialysis therapy with eight hemodialysis sessions within 12 days, her neurological deficits fully resolved. Clinicians should be aware of metformin-induced encephalopathy, presenting with relevant medication history, neurological symptoms, and the lentiform fork sign.

Background: Immunoglobulin M (IgM) mesangial deposition in pediatric minimal change disease (MCD) has been reported to be associated with steroid dependence and poor renal outcomes. However, the evidence regarding the impact of IgM mesangial deposition on the treatment responses or outcomes in adult-onset MCD is lacking.Methods: In this retrospective cohort study, 37 adult patients with MCD received kidney biopsy from January 2010 to May 2020. According to IgM mesangial deposition by immunofluorescence microscopy, the patients were divided into two groups (12 patients with positive IgM deposition; 25 patients with negative IgM deposition). We analyzed the clinical features, the dosage of immunosuppressive agents, and the response to treatment for two years between the two groups.Results: Regarding the clinical symptoms, the dosage of immunosuppressive treatment, and the time to remission, there was no statistically significant difference between the two groups. Compared to the negative IgM group, the frequency of relapses was significantly higher in the positive IgM group within the two-year follow-up period (the negative IgM group 0.25 episodes/year; the positive IgM group 0.75 episodes/year, p = 0.029). Furthermore, multivariate linear regression revealed that the positivity of IgM mesangial deposition is independently associated with the frequency of relapses (regression coefficient B 0.450, 95% CI 0.116-0.784, p = 0.010).Conclusions: Our findings indicated that adult-onset MCD patients with IgM mesangial deposition have a high risk of relapses. Therefore, prolonged and combined immunosuppressive therapy with close follow-up may be considered in MCD adults with IgM mesangial deposition.

Background and Objectives: Osteoporosis and anemia are prevalent among chronic kidney disease stage 5D (CKD stage 5D) patients. Osteoblasts are known as the niche cells of hematopoietic stem cells (HSCs) and stimulate HSCs to form blood-cell lineages within bone marrow microenvironments. We hypothesized that an inverse correlation may exist between mean corpuscular volume (MCV), a surrogate for ineffective hematopoiesis, and bone mineral density (BMD) in the CKD stage 5D population. Materials and Methods: This is a cross-sectional designed cohort study evaluating CKD stage 5D patients who have received dialysis therapy for over three months. Baseline clinical characteristics and laboratory data were prospectively collected. The dual-energy X-ray absorptiometry (DXA) method was used to measure BMD at five sites, which were bilateral femoral neck, total hip, and lumbar spine 1–4. The Pearson correlation test was initially adopted, and a multivariate linear regression model was further applied for potential confounder adjustments. Results: From September 2020 to January 2021, a total of 123 CKD stage 5D patients were enrolled. The Pearson correlation test revealed a significant inverse association between MCV and BMD at bilateral femoral neck and lumbar spine. The lowest T-score of the five body sites was determined as the recorded T-score. After adjustments for several potential confounding factors, the multivariate linear regression model found consistent negative associations between T-score and MCV. Conclusions: The present study found significant inverse correlations between MCV and BMD at specific body locations in patients on dialysis. A decreased T-score was also found to be associated with macrocytosis after adjustments for confounding variables. However, direct evidence for the causative etiology was lacking.

In the original publication of the article, the second sentence under the heading, Case presentation appears incorrectly as A computed tomographic (CT) scan demonstrated left-sided hydronephrosis (Fig. 1).

International audience; Bacterial chemotaxis, the directed migration of bacteria in a gradient of chemoattractant, is one of the most well-studied and well-understood processes in cell biology. On the other hand, bacterial thermotaxis, the directed migration of bacteria in a gradient of temperature, is understood relatively poorly, with somewhat conflicting reports by different groups. One of the reasons for that is the relative technical difficulty of the generation of well-defined gradients of temperature that are sufficiently steep to elicit readily detectable thermotaxis. Here, we used a specially designed microfluidic device to study thermotaxis of Escherichia coli in a broad range of thermal gradients with a high rate of data collection. We found that in shallow temperature gradients with narrow temperature ranges, E. coli tended to aggregate near a sidewall of the gradient channel at either the lowest or the highest temperature. On the other hand, in sufficiently steep gradients with wide temperature ranges, E. coli aggregated at intermediate temperatures, with maximal cell concentrations found away from the sidewalls. We observed this intermediate temperature aggregation in a motility buffer that did not contain any major chemoattractants of E. coli, in contradiction to some previous reports, which suggested that this type of aggregation required the presence of at least one major chemoattractant in the medium. Even more surprisingly, the aggregation temperature strongly depended on the gradient steepness, decreasing by ∼10° as the steepness was increased from 27 to 53°C/mm. Our experiments also highlight the fact that assessments of thermal gradients by changes in fluorescence of temperature-sensitive fluorescent dyes need to account for thermophoresis of the dyes.

Background Our aim was to characterize etiologic diagnoses obtained from bronchoalveolar lavage fluid (BALF) and blood specimens, and to identify risk factors for mortality in systemic lupus erythematosus (SLE) patients with pneumonia and respiratory failure. Methods We conducted a retrospective analysis of SLE patients with pneumonia and respiratory failure. Clinical characteristics, laboratory profiles, and microbiology in BALF and blood samples were evaluated. We performed univariable analyses to identify mortality risk factors. Results All 24 patients (F:M = 21:3, median age 46.5 years; disease duration 11 years) received mechanical ventilation (median duration: 11 days). Pathogens identified in BALF included Pneumocystis jiroveci (12 patients [50%]), cytomegalovirus (CMV, 7 patients [29.2%]), and bacteria (11 patients [45.8%]). Thirteen patients (54.2%) yielded pathogens in blood (CMV in 8 patients [33.3%] and Escherichia coli in 5 patients [20.8%]). Eight developed septic shock, and 9 died within 30 days. Univariable analysis identified thrombocytopenia (odds ratio [OR]: 8.0, 95% confidence interval [CI]: 1.23–52.25), bacteremia within 30 days before or after endotracheal intubation (OR: 8.0, 95% CI: 1.23–52.5), and P. jiroveci pneumonia (PJP, OR: 7.0, 95% CI: 1.04–46.95) as risk factors for 30-day mortality. Kaplan–Meier analysis confirmed an increased risk of 30-day mortality with thrombocytopenia and bacteremia. Conclusion There are high prevalence rates of PJP and CMV infections as evidenced by BALF analyses in SLE patients with pneumonia and respiratory failure. BALF analysis can facilitate rescue therapy per pathogen. Thrombocytopenia, bacteremia, and PJP in SLE patients can increase their 30-day mortality, so warrant early and aggressive treatments.

Additional file 5:Table S1. Clinical and biochemical characteristics of patients with proliferative diabetic retinopathy. Table S2. Clinical and biochemical characteristics of patients with non-proliferative diabetic retinopathy. Table S3. Clinical and biochemical characteristics of patients without diabetic retinopathy & with DM duration ≥5 years. Table S4. Clinical and biochemical characteristics of patients without diabetic retinopathy & with DM duration

The classifier of support vector machine (SVM) learning for assessing quality of arteriovenous fistula (AVF) at hemodialysis (HD) patients using a new photoplethysmography (PPG) sensor are presented in this work. Based on current medical standard, there are two important indices for assessing AVF quality, the blood flow volume (BFV) and the degree of stenosis (DOS). In current clinical practice, BFV and DOS of AVFs are assessed by using an ultrasound Doppler machine, which is bulky, expensive, hard-to-use and time-consuming. Therefore, a new PPG sensor module is designed to provide patients and doctors an inexpensive and small-sized solution to assess AVF quality. The readout of the sensor is successfully optimized to increase the signal to noise ratio (SNR) and reduce the environment interference, the readout circuitries are designed to fit the full dynamic range of analog-digital converter (ADC) and to filter out the noise. To assess quality of AVF, three different machine learning classifiers are developed, where the input features are selected based on optical Beer Lambert’s law and hemodynamic model. Finally, the clinical experiment results show that the proposed PPG sensor successfully achieves an accuracy of 87.838% in assessing AVF quality based on satisfactory DOS and BFV measured.

A new theoretical developments of measuring blood flow volume at arteriovenous fistula (AVF) using a photoplethysmography (PPG) sensor is presented in this work. The mathematical equation is derived under the practical perspective, aiming at applying to small-size, portable, inexpensive and easy-to-use PPG sensor, in order to replace bulky, expensive Doppler machines which is the commonly used instruments for accessing AVF noninvasively nowadays. Furthermore, a new, portable and wireless PPG sensor with ambient light compensation and motion artifact detection, is designed for performing clinical validation of the proposed equation. After neural network calibration with the gold standard, dilution concentration sensor, the experiment result reveals that the PPG sensors implementing the proposed equation successfully achieve much higher correlation (R2 = 0.8064) and much lower error (RMSE = 171.68 ml/min, MAPE = 15.84%) compared to the commercial Doppler machine and other previous works.

A novel blood-flow volume (BFV) sensor is presented for assessing quality of arteriovenous fistula in hemodialysis patients via noninvasive reflectance-type photoplethysmography (PPG). BFV is nowadays in clinic practices evaluated using an ultrasound Doppler monitor, which is expensive, bulky, and can only be operated by well-trained medical personnels. This study is devoted to develop a low-cost, small-sized, portable, and easy-to-use PPG sensor that is capable of continuous measurement of BFV. New designs of front-end analog circuits, signal processing, and an intelligent neural network calibration method are employed to finally achieve high correlation ( R 2 = 0.7176), as opposed to the ultrasound Doppler monitor, with the root-mean-squared errors successfully controlled under 289 ml/min.

Background Hemodialysis (HD) therapy is an indispensable tool used in critical care management. Patients undergoing HD are at risk for intradialytic adverse events, ranging from muscle cramps to cardiac arrest. So far, there is no effective HD device–integrated algorithm to assist medical staff in response to these adverse events a step earlier during HD. Objective We aimed to develop machine learning algorithms to predict intradialytic adverse events in an unbiased manner. Methods Three-month dialysis and physiological time-series data were collected from all patients who underwent maintenance HD therapy at a tertiary care referral center. Dialysis data were collected automatically by HD devices, and physiological data were recorded by medical staff. Intradialytic adverse events were documented by medical staff according to patient complaints. Features extracted from the time series data sets by linear and differential analyses were used for machine learning to predict adverse events during HD. Results Time series dialysis data were collected during the 4-hour HD session in 108 patients who underwent maintenance HD therapy. There were a total of 4221 HD sessions, 406 of which involved at least one intradialytic adverse event. Models were built by classification algorithms and evaluated by four-fold cross-validation. The developed algorithm predicted overall intradialytic adverse events, with an area under the curve (AUC) of 0.83, sensitivity of 0.53, and specificity of 0.96. The algorithm also predicted muscle cramps, with an AUC of 0.85, and blood pressure elevation, with an AUC of 0.93. In addition, the model built based on ultrafiltration-unrelated features predicted all types of adverse events, with an AUC of 0.81, indicating that ultrafiltration-unrelated factors also contribute to the onset of adverse events. Conclusions Our results demonstrated that algorithms combining linear and differential analyses with two-class classification machine learning can predict intradialytic adverse events in quasi-real time with high AUCs. Such a methodology implemented with local cloud computation and real-time optimization by personalized HD data could warn clinicians to take timely actions in advance.

This study introduces the translation adjustment model of Seiford and Zhu (2002) into dynamic DEA models to measure and analyze the dynamic energy efficiency of Asia-Pacific Economic Cooperation (APEC) economies from 2010 to 2014. The APEC economies are divided into annual energy and overall energy efficiency ratings, and improvement directions are proposed for the different variables. With the proposal of magnitude, this study discusses the changes in intertemporal conversion variables and proposes suggestions for improvement. Finally, this study analyzes the implications of energy investment and the efficiency policies of APEC economies. The results show that economies with the lowest overall energy efficiency ratings have great potential for improvement. Reducing capital stock, labor, fossil fuel consumption, and CO2 emissions while increasing GDP can increase energy efficiency ratings. However, economies do not want to reduce the state’s capital stock, and labor and population birth adjustments are difficult. Energy efficiency can only start by adjusting the consumption of fossil fuels, CO2 emissions, and GDP. The results indicate that to improve energy efficiency and reduce fossil fuel consumption and CO2 emissions, economies are expected to increase their GDP unless they enact cuts through policy and technical approaches, appropriately adjust their energy policies, and actively develop new energy technologies to effectively reduce CO2 emissions and achieve optimal energy efficiency.

We report a 71-year-old woman who presented with unilateral flank pain and sepsis. A computed tomographic (CT) scan demonstrated left-sided hydronephrosis. Subsequent percutaneous nephrotomy drainage showed pus-like material, confirming the diagnosis of pyonephrosis. The ureteral stricture was caused by previous radiation injury for cervical cancer in this ESRD patient who was on chronic dialysis for years. In our case, the grade IVB hydronephrosis is a result of an extremely atrophic kidney, pyonephrosis, and ureteral stricture. The CT section of pyonephrosis in an extremely atrophic kidney resembles a sagittal section of a Nautilus shell, as the shell corresponds to the diffusely thinned renal cortex.

The objective of this study was to prepare an electromagnetic interference shielding material, waterborne polyurethane (WPU) filled with silver-nanoparticle-decorated functional reduced graphene oxide (Ag@FRGO). Functional reduced graphene oxide (FRGO) was functionalized through free-radical polymerization before chemical reduction, to prevent restacking and aggregation during the reduction. After the functionalization, the homogeneous dispersion of FRGO promoted the formation of conductive networks throughout the WPU matrix. To enhance the electrical conductivity and electromagnetic interference shielding effectiveness (EMI SE) of the composites, silver nanoparticles (Ag NPs) were deposited on the FRGO surface. Subsequently, WPU composites were synthesized through the solution-mixing method. Their microstructure, morphology, electrical conductivity, and EMI SE were investigated, and the results showed that, among Ag@FRGO/WPU composites with different values for the weight ratio of Ag NPs to FRGO, the Ag@FRGO/WPU composite with 5 wt% FRGO and a weight ratio of Ag to NPs of 10:1 (10Ag@FRGO/WPU) exhibited the highest electrical conductivity (25.52 S/m) and an EMI SE of 35 dB in the frequency range of 8.2–12.4 GHz (X-band).

Emerging evidence suggests that intestinal dysbiosis plays an important role in host inflammation locally and systemically. Such pathological condition is even more prevailing in patients with chronic kidney disease (CKD). Of note, indoxyl sulphate (IS), a gut-derived uremic toxin, is notorious for its pro-inflammatory feature in CKD patients. IS accumulates in the body as the urinary excretion of uremic toxins is impaired, and further worsens the kidney function in a vicious cycle to CKD. Dietary restriction in vegetables, fruits and yogurt leads to the predominance of indole-producing intestinal microbial flora and further exaggerates the accumulation of IS in CKD patients. Recently, interventional studies have shown that circulating IS can be reduced by dietary prebiotic and/or probiotic supplements. However, further randomized controlled trials are warranted to examine whether such beneficial effect of dietary prebiotic/probiotic supplements could be extrapolated to better hard outcomes in CKD population. In this review, we would also like to emphasize the importance of achieving sufficient intake of dietary fibre by proper vegetable pre-treatment and accurate fruit selection, instead of directly avoiding these potassium-rich yet fibre-rich and base-producing foods.