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Purpose: To understand real-world eye drop adherence among glaucoma patients and evaluate the performance of our proposed cloud-based support for eye drop adherence (CASEA)., Design: Prospective, observational case series., Methods: Setting: The Department of Ophthalmology at Tsukazaki Hospital. Patient or study population: Glaucoma patients treated at the hospital from May 2021 to September 2022, with 61 patients initially enrolled. Intervention or observation procedures: Pharmacists guided eye drop administration before the study. Changes in bottle orientation were detected using an accelerometer attached to the container, and acceleration waveforms and date/time data were recorded. Patients visited the clinic during the 4th and 8th weeks to report their eye drop administration, and the data were uploaded to the cloud. Main outcome measures: Two AI models (B-LSTM) were created to analyze the eye drop bottle movement time-series data for patients treating one or both eyes. The models were evaluated by comparing the true administration status with the AI model judgment., Results: Four of the 61 study subjects dropped out. The remaining 57 patients achieved recall, precision, and accuracy values of 98.6 %, 98.6 %, and 95.9 %, respectively, for the two-eyes model and 95.8 %, 98.8 %, and 95.6 % for the one-eye model. Three low-accuracy participants (77.1 %, 71.0 %, and 81.0 %) improved to 100 %, 99.1 %, and 100 %, respectively, after undergoing an additional 8-week performance validation using an aid-type container designed to ensure that the bottle was fully inverted during instillation., Conclusions: CASEA precisely monitored daily eye drop adherence and enhanced treatment efficacy by identifying patients with difficulty self-medicating. This system has the potential to improve glaucoma patient outcomes by supporting adherence., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Purpose: We demonstrated real-time evaluation technology for cataract surgery using artificial intelligence (AI) to residents and supervising doctors (doctors), and performed a comparison between the two groups in terms of risk indicators and duration for two of the important processes of surgery, continuous curvilinear capsulorhexis (CCC) and phacoemulsification (Phaco)., Materials and Methods: Each of three residents with operative experience of fewer than 100 cases, and three supervising doctors with operative experience of 1000 or more cases, performed cataract surgeries on three cases, respectably, a total of 18 cases. The mean values of the risk indicators in the CCC and Phaco processes measured in real-time during the surgery were statistically compared between the residents' group and the doctors' group., Results: The mean values (standard deviation) of the risk indicator (the safest, 0 to most risky, 1) for CCC were 0.556 (0.384) in the residents and 0.433 (0.421) in the doctors, those for Phaco were 0.511 (0.423) in the residents and 0.377 (0.406) in the doctors. The doctors' risk indicators were significantly better in both processes ( P = 0.0003, P < 0.0001 by Wilcoxon test)., Conclusion: We successfully implemented a real-time surgical technique evaluation system for cataract surgery and collected data. The risk indicators were significantly better in the doctors than in the resident's group, suggesting that AI can objectively serve as a new indicator to intraoperatively identify surgical risks., Competing Interests: The authors declare that there are no conflicts of interests of this paper., (Copyright: © 2022 Taiwan J Ophthalmol.)

Surgical skill levels of young ophthalmologists tend to be instinctively judged by ophthalmologists in practice, and hence a stable evaluation is not always made for a single ophthalmologist. Although it has been said that standardizing skill levels presents difficulty as surgical methods vary greatly, approaches based on machine learning seem to be promising for this objective. In this study, we propose a method for displaying the information necessary to quantify the surgical techniques of cataract surgery in real-time. The proposed method consists of two steps. First, we use InceptionV3, an image classification network, to extract important surgical phases and to detect surgical problems. Next, one of the segmentation networks, scSE-FC-DenseNet, is used to detect the cornea and the tip of the surgical instrument and the incisional site in the continuous curvilinear capsulorrhexis, a particularly important phase in cataract surgery. The first and second steps are evaluated in terms of the area under curve (i.e., AUC) of the figure of the true positive rate versus (1-false positive rate) and the intersection over union (i.e., IoU) obtained by the ground truth and prediction associated with the region of interest. As a result, in the first step, the network was able to detect surgical problems with an AUC of 0.97. In the second step, the detection rate of the cornea was 99.7% when the IoU was 0.8 or more, and the detection rates of the tips of the forceps and the incisional site were 86.9% and 94.9% when the IoU was 0.1 or more, respectively. It was thus expected that the proposed method is one of the basic techniques to achieve the standardization of surgical skill levels.

The present study aimed to conduct a real-time automatic analysis of two important surgical phases, which are continuous curvilinear capsulorrhexis (CCC), nuclear extraction, and three other surgical phases of cataract surgery using artificial intelligence technology. A total of 303 cases of cataract surgery registered in the clinical database of the Ophthalmology Department of Tsukazaki Hospital were used as a dataset. Surgical videos were downsampled to a resolution of 299 × 168 at 1 FPS to image each frame. Next, based on the start and end times of each surgical phase recorded by an ophthalmologist, the obtained images were labeled correctly. Using the data, a neural network model, known as InceptionV3, was developed to identify the given surgical phase for each image. Then, the obtained images were processed in chronological order using the neural network model, where the moving average of the output result of five consecutive images was derived. The class with the maximum output value was defined as the surgical phase. For each surgical phase, the time at which a phase was first identified was defined as the start time, and the time at which a phase was last identified was defined as the end time. The performance was evaluated by finding the mean absolute error between the start and end times of each important phase recorded by the ophthalmologist as well as the start and end times determined by the model. The correct response rate of the cataract surgical phase classification was 90.7% for CCC, 94.5% for nuclear extraction, and 97.9% for other phases, with a mean correct response rate of 96.5%. The errors between each phase's start and end times recorded by the ophthalmologist and those determined by the neural network model were as follows: CCC's start and end times, 3.34 seconds and 4.43 seconds, respectively and nuclear extraction's start and end times, 7.21 seconds and 6.04 seconds, respectively, with a mean of 5.25 seconds. The neural network model used in this study was able to perform the classification of the surgical phase by only referring to the last 5 seconds of video images. Therefore, our method has performed like a real-time classification.

Background: Proliferative glomerulonephritis with monoclonal IgG deposits (PGNMID) is a form of renal involvement by monoclonal IgG deposits that was found in mesangial, subendothelial or subepithelial regions. The distribution of glomerular deposits was completely different from that in monoclonal immunoglobulin deposition disease. PGNMID is reported to be rarely associated with a hematological malignancy. Previously, only five cases of PGNMID with multiple myeloma have been reported. However, the pathogenic relationship between PGNMID and multiple myeloma was unclear because a detailed description was not provided. We report that a patient with PGNMID associated with multiple myeloma was treated with bortezomib and dexamethasone and underwent the second renal biopsy after treatment, showing that chemotherapy was effective for PGNMID clinically and pathologically., Case Presentation: A 75-year-old man presented with progressive leg edema, had nephrotic range proteinuria, hypoalbuminemia, moderate renal failure, and occult blood in his urine. Electrophoresis results showed serum and urinary monoclonal spikes of IgGκ type immunoglobulin. A renal biopsy specimen showed lobular mesangial proliferation with mesangiolysis, glomerular micro-aneurysm, and endocapillary hypercellularity. Immunofluorescence results revealed strong granular capillary and mesangial staining for IgG1, C3 and κ light chain in glomeruli without tubular deposits of any immunoglobulin. Electron microscopy also showed dense granular deposits in subendothelial and mesangial areas. PGNMID associated with multiple myeloma (IgGκ type) was diagnosed on the basis of a subsequent bone marrow examination. Bortezomib and dexamethasone therapy significantly reduced proteinuria and elevated serum albumin level. Eight months later, the second renal biopsy showed no active lesions and that the IgG1 and κ light chain deposits had drastically disappeared., Conclusions: This is the first case of PGNMID with multiple myeloma successfully treated with bortezomib and dexamethasone in which comparative renal biopsies were performed before and after treatment. Our findings suggest the pathogenesis of PGNMID and therapeutic options for PGNMID.

The M-type phospholipase A2 receptor (PLA2R1) was identified recently as a specific target antigen in idiopathic membranous nephropathy. However, the influence of different sample preparation techniques on the immunostaining of PLA2R1 is unclear. Previous studies have identified IgG4 as the dominant subclass of PLA2R1 antibodies. However, it remains unclear whether the IgG subclass profiles of the glomerular immune complexes of PLA2R1-positive and -negative idiopathic membranous nephropathy cases are similar. To address these questions, we conducted the present study of 58 idiopathic membranous nephropathy cases. The PLA2R1 positivity rate for the paraffin-embedded sections was 61%, whereas that for the frozen sections was 65%. Nonspecific background staining was observed in the frozen sections. Discrepancies between different sample preparations occurred in three cases (6%); two cases were PLA2R1-positive in paraffin sections and PLA2R1-negative in frozen sections and one case was PLA2R1-negative in paraffin sections and PLA2R1-positive in frozen sections. Regarding the IgG subclass profile, 89% of the PLA2R1-positive cases demonstrated the IgG4-dominant/codominant phenotype versus 31% of the PLA2R1-negative cases (p < 0.001). Clinical characteristics and pathological findings did not significantly differ between PLA2R1-positive and -negative cases. In summary, the PLA2R1 immunofluorescence results were not affected by the different sample preparation techniques, although paraffin-embedded sections were preferred for the histological detection of PLA2R1 because of the nonspecific background staining observed in frozen sections. The observed lower frequency of the non-IgG4-dominant/codominant phenotype in PLA2R1-negative idiopathic membranous nephropathy cases may suggest that there are heterogeneous subgroups of this disease.

Purpose: In patients on dialysis, the most common cause of death is cardiovascular disease. This is caused, at least in part, by excessive vascular calcification. Studies that have examined coronary calcification have been published, but these measurements require expensive equipment. Here, we used computed tomography to determine aortic calcification and evaluated these data as prognostic markers for cardiovascular disease., Methods: Computed tomography with contrast medium was performed on 49 patients undergoing hemodialysis (29 males and 20 females; average age, 68.9 ± 11.0 years). A calcification score (CS) was defined as the ratio of the volume of vascular calcification to the volume of the thoracic aorta. All patients were monitored for cardiovascular end points, which included cerebral infarction or hemorrhage, myocardial infarction, electrocardiographic, or echocardiographic abnormalities that suggested myocardial ischemia, cardiac surgery, leg amputation, and hospitalization or death due to heart failure., Results: Patients were followed for 3 years, with 12 patients reaching the end point. Both high CS (p = 0.007) and male gender (p = 0.009) were significantly associated with cardiovascular events. In contrast, events were not related to age, dialysis duration, diabetes mellitus, smoking status, low-density lipoprotein cholesterol level, pulse-wave velocity, maximum intima-media thickness of the carotid artery wall, systolic blood pressure, or left ventricular hypertrophy. Multiple logistic regression analysis revealed that a high baseline CS was a significant predictor for cardiovascular events (p < 0.05)., Conclusions: Calcification of the thoracic aorta determined by three-dimensional computed tomography predicts cardiovascular complications in patients on hemodialysis.

MyoR was originally identified as a transcriptional repressor in embryonic skeletal muscle precursors, but its function in adult kidney has not been clarified. In this study, we tried to clarify the functional role of MyoR using MyoR(-/-) mice. Cisplatin induced a significantly higher degree of severe renal dysfunction, tubular injury, and mortality in MyoR(-/-) mice than in wild-type mice. The injection of cisplatin significantly increased the number of apoptotic cells in the kidney tissues of MyoR(-/-) mice, compared with that in wild-type mice. To clarify the mechanism of severe cisplatin-induced damage and apoptosis in MyoR(-/-) mice, we focused on the p53 signaling pathway and bone morphogenic protein-7 (BMP-7). Treatment with cisplatin significantly activated p53 signaling in cultured renal proximal tubular epithelial cells (RTECs) in both wild-type and MyoR(-/-) mice, but no significant difference between the groups was observed. The injection of cisplatin significantly increased the expression of BMP-7 in the kidney tissues of wild-type mice, but no increase was observed in the MyoR(-/-) mice. Treatment with cisplatin significantly increased the expression of BMP-7 in cultured RTECs from wild-type mice but not in those from MyoR(-/-) mice. Moreover, treatment with recombinant BMP-7 rescued the cisplatin-induced apoptosis in RTECs from MyoR(-/-) mice. Taken together, our results demonstrate a new protective role of MyoR in adult kidneys that acts through the regulation of BMP-7.

Fish oil containing n-3 polyunsaturated fatty acids such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) is well known to prevent the progression of IgA nephropathy. However, the mechanism through which fish oil prevents the progression of renal injury remains uncertain. We tried to clarify the effects of EPA on tubulointerstitial injury in the kidney both in vivo and in vitro. We examined the effects of EPA, especially to focus on nuclear factor kappa B (NF-κB), using Thy-1 nephritis models. Also the mechanism of EPA was investigated using small-interfering RNA (siRNA) in lipopolysaccharide (LPS)-stimulated proximal tubular epithelial cells (PTECs). In Thy-1 nephritis models, EPA significantly inhibited tubulointerstitial injury and the infiltration of macrophages into tubulointerstitial lesions except severe glomerular injury at early stage. Compared with control animals, NF-κB activation was significantly augmented in the Thy-1 nephritic kidney. However, treatment with EPA significantly reduced NF-κB activation, down-regulated the expressions of NF-κB-dependent molecules. Also in LPS-stimulated PTECs, LPS augmented NF-κB activation and the expression of NF-κB-dependent molecules. As in the case with the Thy-1 nephritis models, treatment with EPA inhibited them, prevented the degradation of IκBα in LPS-stimulated PTECs. Pre-treatment with siRNA for IκBα abolished the inhibitory effect of EPA on LPS-induced NF-κB activation, suggesting that EPA inhibited NF-κB activation by regulating IκBα. Our results indicate that EPA prevents the early progression of tubulointerstitial injury in Thy-1 nephritis models, and the inhibitory effect of EPA on the expression of inflammatory molecules via the regulation of IκBα in cultured cells may explain this mechanism., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Associative memory networks based on quaternionic Hopfield neural network are investigated in this paper. These networks are composed of quaternionic neurons, and input, output, threshold, and connection weights are represented in quaternions, which is a class of hypercomplex number systems. The energy function of the network and the Hebbian rule for embedding patterns are introduced. The stable states and their basins are explored for the networks with three neurons and four neurons. It is clarified that there exist at most 16 stable states, called multiplet components, as the degenerated stored patterns, and each of these states has its basin in the quaternionic networks.