Artificial intelligence-assisted quantification and assessment of whole slide images for pediatric kidney disease diagnosis.

MOTIVATION: Pediatric kidney disease is a widespread, progressive condition that severely impacts growth and development of children. Chronic kidney disease is often more insidious in children than in adults, usually requiring a renal biopsy for diagnosis. Biopsy evaluation requires copious examination by trained pathologists, which can be tedious and prone to human error. In this study, we propose an artificial intelligence (AI) method to assist pathologists in accurate segmentation and classification of pediatric kidney structures, named as AI-based Pediatric Kidney Diagnosis (APKD). RESULTS: We collected 2935 pediatric patients diagnosed with kidney disease for the development of APKD. The dataset comprised 93 932 histological structures annotated manually by three skilled nephropathologists. APKD scored an average accuracy of 94% for each kidney structure category, including 99% in the glomerulus. We found strong correlation between the model and manual detection in detected glomeruli (Spearman correlation coefficient r = 0.98, P < .001; intraclass correlation coefficient ICC = 0.98, 95% CI = 0.96-0.98). Compared to manual detection, APKD was approximately 5.5 times faster in segmenting glomeruli. Finally, we show how the pathological features extracted by APKD can identify focal abnormalities of the glomerular capillary wall to aid in the early diagnosis of pediatric kidney disease. AVAILABILITY AND IMPLEMENTATION: https://github.com/ChunyueFeng/Kidney-DataSet.

Variations of topological charge of vortex beam based on a diffraction plate with spiral transmission structures.

The phenomenon of vortex beams passing through a diffraction plate with rotationally symmetric superposition of spiral pinholes array is investigated. The variations of the topological charges of vortex beams are theoretically analyzed, numerically simulated and experimentally observed. It proves that the obtained topological charge value (l) is a combination of that of incident beam (l0) and the number of the spiral structures (m). The relationship is l = Mm-l0, where M is an integer. With this study, we proved that spiral transmission structures can also achieve the variations of the topological charge of a vortex beam. And this method is simple and costless. With the advantages of this method, it might have important applications in optical communications and optical tweezers.

A new labdane diterpenoid glycoside from Nervilia fordii.

To study the chemical constituents of Nervilia fordii (Hance) Schltr., various chromatographic methods were used, including D101 macroporous resin, silica gel, ODS and preparative HPLC chromatographic techniques. A new labdane diterpenoid glycoside named as nervilifordoside A was isolated from 60% EtOH extract of Nerviliafordii. The structure of compound 1 was elucidated as 12, 17-epoxy-3-hydroxy-17-methoxy-labdan-13-en-16, 15-olide 3-O-alpha-rhamnopyranosyl-(1 --> 2)-O-beta-glucopyranoside on the basis of HR-MS, 1D and 2D NMR spectroscopic data as well as chemical methods.

Positive buttress reduction in femoral neck fractures: a literature review.

BACKGROUND: Femoral neck fractures (FNFs) in young adults are usually caused by high-energy trauma, and their treatment remains a challenging issue for orthopedic surgeons. The quality of reduction is considered an important factor in improving the poor prognosis of patients with FNFs. In recent years, positive buttress closed reduction technique has received widespread attention in the treatment of FNFs. This comprehensive literature review is designed to encapsulate the impacts of both non-anatomic and anatomic reduction on the biomechanical stability, clinical outcomes, and postoperative complications in the management of FNFs, conjecture the efficacy of positively braced reduction techniques and provide a thorough summarization of the clinical outcomes. METHODS: In this literature review, we have examined all clinical and biomechanical studies related to the treatment of FNFs using non-anatomical reduction or positive and negative buttress reduction. PubMed, Web of Science, Google Scholar and Embase Library databases were searched systematically for studies published before September 1, 2023. Published literature on fracture reduction techniques for treating FNFs was reviewed. In addition, we evaluated the included literature using the MINORs tool. RESULTS: Although the "arch bridge" structure formed by the positive buttress reduction technique improved the support to the cortical bone and provided a more stable biomechanical structure, no significant differences were noted in the clinical efficacy and incidence of postoperative complications between the positive buttress reduction and anatomical reduction. CONCLUSION: Positive buttress reduction is an effective treatment method for young patients with FNFs. When facing difficult-to-reduce FNF, positive buttress reduction should be considered first, followed by anatomical reduction. However, negative buttress reduction should be avoided.

A comprehensive AI model development framework for consistent Gleason grading.

BACKGROUND: Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. METHODS: We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI. RESULTS: Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance. CONCLUSIONS: This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.

Gleason grading is a well-accepted diagnostic standard to assess the severity of prostate cancer in patients' tissue samples, based on how abnormal the cells in their prostate tumor look under a microscope. This process can be complex and time-consuming. We explore how artificial intelligence (AI) can help pathologists perform Gleason grading more efficiently and consistently. We build an AI-based system which automatically checks image quality, standardizes the appearance of images from different equipment, learns from pathologists' feedback, and constantly improves model performance. Testing shows that our approach achieves consistent results across different equipment and improves efficiency of the grading process. With further testing and implementation in the clinic, our approach could potentially improve prostate cancer diagnosis and management.

Electro-optical characteristics of holographic polymer dispersed liquid crystal gratings doped with nanosilver.

We report on the synthesis and characteristics of a holographic polymer dispersed liquid crystal (H-PDLC) switchable grating based on nano-Ag particles. The influence of doping different concentrations of nano-Ag on the diffraction efficiency, driving voltage, and response time of the H-PDLC grating is investigated. The best grating characteristics were achieved with 0.05% nano-Ag doping. Calculated and experimental results reveal that the improvement of the characteristics is likely due to the surface plasmon effect of nano-Ag.

Five new flavonoid glycosides from Nervilia fordii.

Five new flavonoid glycosides, namely nervilifordins F-J (1-5), were isolated from the 60% EtOH extract of the aerial parts of Nervilia fordii, along with three first isolated flavonoids (7, 8, and 13) and five known flavonoids (6, 9-12). The structures of new compounds were elucidated on the basis of 1D and 2D NMR and MS studies. Their anti-inflammatory activities were tested by measuring their inhibitory effects on nitric oxide production in lipopolysaccharide-activated RAW264.7 macrophages. Compounds 2 and 5 showed interesting inhibition effects with their EC50 values of 15.15 µM and 14.80 µM, respectively.

Parallel detection experiment of fluorescence confocal microscopy using DMD.

Parallel detection of fluorescence confocal microscopy (PDFCM) system based on Digital Micromirror Device (DMD) is reported in this paper in order to realize simultaneous multi-channel imaging and improve detection speed. DMD is added into PDFCM system, working to take replace of the single traditional pinhole in the confocal system, which divides the laser source into multiple excitation beams. The PDFCM imaging system based on DMD is experimentally set up. The multi-channel image of fluorescence signal of potato cells sample is detected by parallel lateral scanning in order to verify the feasibility of introducing the DMD into fluorescence confocal microscope. In addition, for the purpose of characterizing the microscope, the depth response curve is also acquired. The experimental result shows that in contrast to conventional microscopy, the DMD-based PDFCM system has higher axial resolution and faster detection speed, which may bring some potential benefits in the biology and medicine analysis. SCANNING 38:234-239, 2016. © 2015 Wiley Periodicals, Inc.

[Optimization of urban green space spatial arrangement based on supply-demand analysis: a case study in Nanjing City, China].

Urban green space has the functions of ecological and social services, and the two services levels are decided by the supply-demand relationship. However, the supply-demand of green space not only involves in quantity, but also refers to spatial distribution. Therefore, only greening indicators can not wholly reflect the true levels of green space services. Based on the supply-demand analysis and supported by the ArcGIS, this paper examined the ecological and social services levels of the urban green spaces in Nanjing City by using the evenness indicator and the rate the people could enjoy the public green space in their accessible area. Accordingly, the ecological and social services levels of the green space in the City were investigated. The results showed that in the east of Nanjing City, green spaces were rich, but high accessible ones were lack, which resulted in a moderate social service level. In the center of the City, green spaces were lack and distributed unevenly, resulting in the low levels of ecological and social services. In Hexi area, due to the shortage in ecological green space and its uneven distribution, the green spaces had a high level social service but a low level ecological service. In the southern and northern areas of the City, green spaces were in deficiency, uneven distribution, and lack in high accessible.