Histomorphometric Study of the Tunics of Ductus Arteriosus in Human Fetal Cadavers Using the ImageJ Software.

INTRODUCTION: The ductus arteriosus (DA) connects the left pulmonary artery with the aorta during fetal life. Although it connects two elastic arteries, histological studies have shown that it is a muscular artery. There are very few studies on the histomorphometry of human fetal cadaveric DA. There are few studies on the changes in the tunics of the DA at various stages of fetal development. The present study aimed to observe the histomorphometric features of DA and its histological variations according to the gestational age of the fetus. METHODS: The study sample was DA dissected from 34 fetal cadavers of different gestational ages and stained with standard hematoxylin and eosin staining (H&E). We studied the structure of DA under a light microscope. We used ImageJ software (National Institutes of Health, Bethesda, Maryland) to measure the thickness of all three layers of the DA wall. RESULTS: The thickness of the DA wall was directly proportional to the gestational age of the fetus. In each trimester, we observed distinct histological changes in the tunics. CONCLUSION: The formation of multiple intimal mounds and the increase in intimal thickness observed during the last trimester are responsible for the closure of the ductus after birth. Elastosis is associated with patent DA. The disappearance of elastosis at a later gestational age ensures the closure of the ductus.

Deep learning-enabled classification of kidney allograft rejection on whole slide histopathologic images.

Background: Diagnosis of kidney transplant rejection currently relies on manual histopathological assessment, which is subjective and susceptible to inter-observer variability, leading to limited reproducibility. We aim to develop a deep learning system for automated assessment of whole-slide images (WSIs) from kidney allograft biopsies to enable detection and subtyping of rejection and to predict the prognosis of rejection. Method: We collected H&E-stained WSIs of kidney allograft biopsies at 400x magnification from January 2015 to September 2023 at two hospitals. These biopsy specimens were classified as T cell-mediated rejection, antibody-mediated rejection, and other lesions based on the consensus reached by two experienced transplant pathologists. To achieve feature extraction, feature aggregation, and global classification, we employed multi-instance learning and common convolution neural networks (CNNs). The performance of the developed models was evaluated using various metrics, including confusion matrix, receiver operating characteristic curves, the area under the curve (AUC), classification map, heat map, and pathologist-machine confrontations. Results: In total, 906 WSIs from 302 kidney allograft biopsies were included for analysis. The model based on multi-instance learning enables detection and subtyping of rejection, named renal rejection artificial intelligence model (RRAIM), with the overall 3-category AUC of 0.798 in the independent test set, which is superior to that of three transplant pathologists under nearly routine assessment conditions. Moreover, the prognosis models accurately predicted graft loss within 1 year following rejection and treatment response for rejection, achieving AUC of 0.936 and 0.756, respectively. Conclusion: We first developed deep-learning models utilizing multi-instance learning for the detection and subtyping of rejection and prediction of rejection prognosis in kidney allograft biopsies. These models performed well and may be useful in assisting the pathological diagnosis.

Nanopore-based targeted next-generation sequencing of tissue samples for tuberculosis diagnosis.

Objective: Diagnosing tuberculosis (TB) can be particularly challenging in the absence of sputum for pulmonary tuberculosis cases and extrapulmonary TB (EPTB). This study evaluated the utility of nanopore-based targeted next-generation sequencing (tNGS) for diagnosing TB in tissue samples, and compared its efficacy with other established diagnostic methods. Methods: A total of 110 tissue samples from clinical cases were examined. The sensitivity and specificity of tNGS were benchmarked against a range of existing diagnostic approaches including hematoxylin and eosin (HE) staining in conjunction with acid-fast bacilli (AFB) detection, HE staining combined with PCR, HE staining paired with immunohistochemistry (IHC) using anti-MPT64, and the Xpert Mycobacterium tuberculosis (MTB)/rifampicin (RIF) assay. Results: The sensitivity and specificity of tNGS were 88.2 and 94.1%, respectively. The respective sensitivities for HE staining combined with AFB, HE staining combined with PCR, HE staining combined with IHC using anti-MPT64, and Xpert MTB/RIF were 30.1, 49.5, 47.3, and 59.1%. The specificities for these methods were 82.4, 88.2, 94.1, and 94.1%, respectively. Analysis of drug resistance based on tNGS results indicated that 10 of 93 TB patients (10.75%) had potential drug resistance. Conclusion: Targeted next-generation sequencing achieved higher accuracy than other established diagnostic methods, and can play a crucial role in the rapid and accurate diagnosis of TB, including drug-resistant TB.

Training immunophenotyping deep learning models with the same-section ground truth cell label derivation method improves virtual staining accuracy.

Introduction: Deep learning (DL) models predicting biomarker expression in images of hematoxylin and eosin (H&E)-stained tissues can improve access to multi-marker immunophenotyping, crucial for therapeutic monitoring, biomarker discovery, and personalized treatment development. Conventionally, these models are trained on ground truth cell labels derived from IHC-stained tissue sections adjacent to H&E-stained ones, which might be less accurate than labels from the same section. Although many such DL models have been developed, the impact of ground truth cell label derivation methods on their performance has not been studied. Methodology: In this study, we assess the impact of cell label derivation on H&E model performance, with CD3+ T-cells in lung cancer tissues as a proof-of-concept. We compare two Pix2Pix generative adversarial network (P2P-GAN)-based virtual staining models: one trained with cell labels obtained from the same tissue section as the H&E-stained section (the 'same-section' model) and one trained on cell labels from an adjacent tissue section (the 'serial-section' model). Results: We show that the same-section model exhibited significantly improved prediction performance compared to the 'serial-section' model. Furthermore, the same-section model outperformed the serial-section model in stratifying lung cancer patients within a public lung cancer cohort based on survival outcomes, demonstrating its potential clinical utility. Discussion: Collectively, our findings suggest that employing ground truth cell labels obtained through the same-section approach boosts immunophenotyping DL solutions.

Comparison of staining quality between rapid and routine hematoxylin and eosin staining of frozen breast tissue sections: an observational study.

OBJECTIVE: To compare the staining quality between rapid hematoxylin and eosin (H&E) staining and routine H&E staining of frozen breast tissue sections. METHODS: In this cross-sectional observational study, 120 frozen breast tissue sections were randomly assigned to rapid or routine H&E staining (n = 60 per group). Rapid H&E staining used a 7:1 mixture of modified Gill's hematoxylin and alcohol-soluble 1% eosin Y. The staining quality of each section was evaluated and scored. A score of >7 was considered excellent, a score of 6 to 7 good, and a score of ≤5 poor. RESULTS: The staining time for rapid staining was approximately 3 minutes, whereas that of routine staining was approximately 12 minutes. There were no significant differences in the staining quality scores or proportions of sections in each grade between the two staining methods. The proportions of sections that were classified as excellent or good were 96.7% and 98.3% for rapid and routine staining, respectively. CONCLUSIONS: In frozen breast tissue sections, rapid H&E staining may provide staining quality that is comparable to that of routine staining, while markedly reducing the staining time.

Development of a Time-Resolved Fluorescence Resonance Energy Transfer ultra-high throughput screening assay for targeting SYK and FCER1G interaction.

The spleen tyrosine kinase (SYK) and high affinity immunoglobulin epsilon receptor subunit gamma (FCER1G) interaction has a major role in the normal innate and adaptive immune responses, but dysregulation of this interaction is implicated in several human diseases, including autoimmune disorders, hematological malignancies, and Alzheimer's Disease. Development of small molecule chemical probes could aid in studying this pathway both in normal and aberrant contexts. Herein, we describe the miniaturization of a time-resolved fluorescence resonance energy transfer (TR-FRET) assay to measure the interaction between SYK and FCER1G in a 1536-well ultrahigh throughput screening (uHTS) format. The assay utilizes the His-SH2 domains of SYK, which are indirectly labeled with anti-His-terbium to serve as TR-FRET donor and a FITC-conjugated phosphorylated ITAM domain peptide of FCER1G to serve as acceptor. We have optimized the assay into 384-well HTS format and further miniaturized the assay into a 1536-well uHTS format. Robust assay performance has been achieved with a Z' factor > 0.8 and signal-to-background (S/B) ratio > 15. The utilization of this uHTS TR-FRET assay for compound screening has been validated by a pilot screening of 2,036 FDA-approved and bioactive compounds library. Several primary hits have been identified from the pilot uHTS. One compound, hematoxylin, was confirmed to disrupt the SYK/FECR1G interaction in an orthogonal protein-protein interaction assay. Thus, our optimized and miniaturized uHTS assay could be applied to future scaling up of a screening campaign to identify small molecule inhibitors targeting the SYK and FCER1G interaction.

Establishment of a rabbit model of different degrees of testicular torsion.

INTRODUCTION AND OBJECTIVES: Different degrees of testicular torsion result in varying degrees of testicular damage, which influences treatment options and outcomes. Therefore, establishing a testicular torsion model with different degrees is necessary for clinical diagnosis. MATERIALS AND METHODS: Rabbits were randomly divided into four groups and their spermatic cords were twisted at 0 °, 180 °, 360 °, and 720 °, respectively. Color Doppler flow imaging (CDFI) were performed to evaluate the blood supply in testicles. The twisted testicles were surgically removed at six hours post-operation and were evaluated by morphological observation and Hematoxylin and Eosin staining. RESULTS: CDFI signals were gradually decreased as the degree of testicular torsion increased, and scores of CDFI in the 360 ° and 720 ° groups were significantly decreased at postoperative six hours compared to pre-surgery. Compared to the sham, the testicle in the 180 ° group exhibited slight congestion, whereas the testicles in the 360 ° and 720 ° groups were dark red in color and had severe congestion and unrecognizable vessels. Hematoxylin and Eosin staining showed mild spermatogenic cell reduction and testicular interstitial hemorrhage in the 180 ° group. In the 360 ° and 720 ° groups, disordered seminiferous tubules, shed spermatogenic cells in tubules, inflammatory cell infiltration, and severe hemorrhage were found. In comparison with the sham, interstitial hemorrhage scores in the 360 ° and 720 ° groups were significantly higher, and scores of germinal epithelial cell thickness in the three testicular torsion groups were significantly decreased. CONCLUSIONS: Collectively, we successfully constructed a testicular torsion model with different degrees in rabbits.

The return of natural dyes: the case of logwood tree (Haematoxylum campechianum L.).

In recent years, a worldwide reassessment of natural dyes has occurred, driven by the health and environmental issues associated with synthetic dyes. Haematoxylum campechianum L. is a tropical tree from which wood extracts were widely used in the textile industry during the 16th century. The logwood tree extract serves as a contemporary source of hematoxylin, a key dye in the globally prevalent hematoxylin-eosin staining method, a cornerstone in histopathological procedures. This paper will initially explore the re-emergence of natural dyes. Subsequently, it will focus on the historical, conventional, and innovative applications of logwood in the fields of medicine, histopathology, and nanotechnology, along with the status and alternative uses of the hematoxylin-eosin stain. Lastly, this paper will examine the current state of conservation and utilization of Haematoxylum campechianum in Campeche, Mexico, a leading global producer of hematoxylin.

A simple and economical method for unbiasedly quantifying the alveolar size of entire mouse lung tissue utilizing Hematoxylin and Eosin Staining.

Alveolar, the smallest structural and functional units within the respiratory system, play a crucial role in maintaining lung function. Alveolar damage is a typical pathological hallmark of respiratory diseases. Nevertheless, there is currently no simple, rapid, economical, and unbiased method for quantifying alveolar size for entire lung tissue. Here, firstly, we conducted lung sample slicing based on the size, shape, and distribution of airway branches of different lobes. Next, we performed HE staining on different slices. Then, we provided an unbiased quantification of alveolar size using free software ImageJ. Through this protocol, we demonstrated that C57Bl/6 mice exhibit varying alveolar sizes among different lobes. Collectively, we provided a simple and unbiased method for a more comprehensive quantification of alveolar size in mice, which holds promise for a broader range of respiratory research using mouse models.

Prognostic significance of Klotho expression in patients with renal cell carcinoma.

INTRODUCTION: Various molecular markers have been investigated in renal cell carcinoma (RCC) without significant reliability. We analyzed Klotho (tumor suppressive protein) expression in RCC to investigate its association with tumor-stage, grade, disease-free-survival (DFS) and overall-survival (OS). METHODS: Data of histologically confirmed patients of RCC with complete clinical follow-up were retrieved from Medical-Record-Library. Tissue sections of tumor and normal parenchyma were prepared from the blocks. Immunohistochemical studies for Klotho were done with commercially available kit (EPR6856, Ab181373; Abcam, Cambridge MA, USA). Klotho expression was scored between 0-3 and grouped into weak/absent (0, 1) and moderate/strong (2, 3). Tumors stages and grades were grouped into low stage (I and II) and high stage (III and IV) and into low grade (grade 1 and 2) and high grade (grade 3 and 4) according to WHO/ISUP grading. The histopathologists were blinded as to the clinical and follow-up data. Various prognostic factors were analyzed with respect to Klotho expression. Kaplan-Meier curves were created for DFS and OS. RESULTS: Fifty-four patients of mean age 55.15 ± 13.34 years and M:F ratio of 1.8:1 were included. Normal renal tissue had strong expression of Klotho in all. In tumor tissue 20 (37%) had negative, 7 (13%) had weak, 14 (25.9%) had moderate and 13 (24.1%) had strong Klotho expression. Significantly more patients had absent/weak Klotho expression with higher grade (16/24 (66.7%) vs 7/25 (28%); p = 0.007), higher stage (22/33 (66%) vs 5/21 (23.8%); p = 0.002), LVI (12/14 (85.7%) vs 2/14 (14.3%); p = 0.002), sinus-fat-invasion (16/21 (76.2%) vs 5/21 (23.8%); p = 0.002), renal-vein-involvement (14/18 (77.8%) vs 4/18 (22.2%); p = 0.004), necrosis (17/26 (65.3%) vs 9/26 (34.6%); p = 0.029) and metastasis (8/9 (88.9%) vs 1/9 (11.1%); p = 0.01). Median DFS and OS were significantly lower in patients with weak/absent Klotho expression (12 vs 23 months, p = 0.023 and 15 vs 33 months, p = 0.006 respectively). Kaplan-Meier curves showed lower estimated DFS and OS in patients with weak/absent expression. CONCLUSIONS: We conclude that Klotho expression in renal tumor could be a good prognostic marker in patients with RCC.

Rumen Development of Tianhua Mutton Sheep Was Better than That of Gansu Alpine Fine Wool Sheep under Grazing Conditions.

The purpose of this experiment was to investigate the differences in rumen tissue morphology, volatile fatty acid content, and rumen microflora between Tianhua mutton sheep and Gansu alpine fine wool sheep under the same grazing conditions. Twelve 30-day-old lambs were randomly selected from two different flocks in Duolong Village and grazed together for a period of 150 days. The rumen tissue was fixed with 4% paraformaldehyde and brought back to the laboratory for H&E staining, the volatile fatty acid content of the rumen contents was detected by gas chromatography, and the rumen flora structure was sequenced by full-length sequencing of the bacterial 16S rRNA gene using the PacBio sequencing platform. The acetic acid and total acid contents of the rumen contents of Tianhua mutton sheep were significantly higher than those of Gansu alpine fine wool sheep (p < 0.05). The rumen papillae height of Tianhua mutton sheep was significantly higher than that of Gansu alpine fine wool sheep (p < 0.05). The diversity and richness of the rumen flora of Tianhua mutton sheep were higher than those of Gansu alpine fine wool sheep, and Beta analysis showed that the microflora structure of the two fine wool sheep was significantly different. At the phylum level, Firmicutes and Bacteroidetes dominated the rumen flora of Tianhua mutton sheep and Gansu alpine fine wool sheep. At the genus level, the dominant strains were Christensenellaceae_R_7_group and Rikenellaceae_RC9_gut_group. LEfSe analysis showed that Prevotella was a highly abundant differential species in Tianhua mutton sheep and lachnospiraccac was a highly abundant differential species in Gansu alpine fine wool sheep. Finally, both the KEGG and COG databases showed that the enrichment of biometabolic pathways, such as replication and repair and translation, were significantly higher in Tianhua mutton sheep than in Gansu alpine fine wool sheep (p < 0.05). In general, there were some similarities between Tianhua mutton sheep and Gansu alpine fine wool sheep in the rumen tissue morphology, rumen fermentation ability, and rumen flora structure. However, Tianhua mutton sheep had a better performance in the rumen acetic acid content, rumen papillae height, and beneficial bacteria content. These differences may be one of the reasons why Tianhua mutton sheep are more suitable for growing in alpine pastoral areas than Gansu alpine fine wool sheep.

Dapagliflozin mitigates oxidative stress, inflammatory, and histopathological markers of aging in mice.

Aging, a complex physiological process affecting all living things, is a major area of research, particularly focused on interventions to slow its progression. This study assessed the antiaging efficacy of dapagliflozin (DAPA) on various aging-related parameters in a mouse model artificially induced to age. Forty male Swiss albino mice were randomly divided into four groups of ten animals each. The control group (Group I) received normal saline. The aging model group (Group II) was administered D-galactose orally at 500mg/kg to induce aging. Following the aging induction, the positive control group received Vitamin C supplementation (Group III), while the DAPA group (Group IV) was treated with dapagliflozin. The inflammatory mediators (TNF-α and IL-1ß) showed similar patterns of change. No statistically significant difference was observed between groups III and IV. Both groups had significantly lower values compared to GII, while it was significantly higher compared to GI. Glutathione peroxidase (GSH-Px) showed no statistically significant difference between groups GIII and GIV, but it was higher in GIII compared to GII and significantly lower in GIII compared to GI. The study demonstrated that dapagliflozin exerts a beneficial impact on many indicators of aging in mice. The intervention resulted in a reduction in hypertrophy in cardiomyocytes, an enhancement in skin vitality, a decrease in the presence of inflammatory mediators, and an improvement in the efficacy of antioxidants.

Artificial intelligence-based differential diagnosis of orbital MALT lymphoma and IgG4 related ophthalmic disease using hematoxylin-eosin images.

PURPOSE: To investigate the possibility of distinguishing between IgG4-related ophthalmic disease (IgG4-ROD) and orbital MALT lymphoma using artificial intelligence (AI) and hematoxylin-eosin (HE) images. METHODS: After identifying a total of 127 patients from whom we were able to procure tissue blocks with IgG4-ROD and orbital MALT lymphoma, we performed histological and molecular genetic analyses, such as gene rearrangement. Subsequently, pathological HE images were collected from these patients followed by the cutting out of 10 different image patches from the HE image of each patient. A total of 970 image patches from the 97 patients were used to construct nine different models of deep learning, and the 300 image patches from the remaining 30 patients were used to evaluate the diagnostic performance of the models. Area under the curve (AUC) and accuracy (ACC) were used for the performance evaluation of the deep learning models. In addition, four ophthalmologists performed the binary classification between IgG4-ROD and orbital MALT lymphoma. RESULTS: EVA, which is a vision-centric foundation model to explore the limits of visual representation, was the best deep learning model among the nine models. The results of EVA were ACC = 73.3% and AUC = 0.807. The ACC of the four ophthalmologists ranged from 40 to 60%. CONCLUSIONS: It was possible to construct an AI software based on deep learning that was able to distinguish between IgG4-ROD and orbital MALT. This AI model may be useful as an initial screening tool to direct further ancillary investigations.

Hepatic and renal effects of oral stingless bee honey in a streptozotocin-induced diabetic rat model.

BACKGROUND: Diabetes is known damage the liver and kidney, leading to hepatic dysfunction and kidney failure. Honey is believed to help in lowering the blood glucose levels of diabetic patients and reducing diabetic complications. However, the effect of stingless bee honey (SBH) administration in relieving liver and kidney damage in diabetes has not been well-studied. AIM: To investigate the effect of SBH administration on the kidney and liver of streptozotocin-induced (STZ; 55 mg/kg) diabetic Sprague Dawley rats. METHODS: The rats were grouped as follows (n = 6 per group): non-diabetic (ND), untreated diabetic (UNT), metformin-treated (MET), and SBH+metformin-treated (SBME) groups. After successful diabetic induction, ND and UNT rats were given normal saline, whereas the treatment groups received SBH (2.0 g/kg and/or metformin (250 mg/kg) for 12 d. Serum biochemical parameters and histological changes using hematoxylin and eosin (H&E) and periodic acid-Schiff (PAS) staining were evaluated. RESULTS: On H&E and PAS staining, the ND group showed normal architecture and cellularity of Bowman's capsule and tubules, whereas the UNT and MET groups had an increased glomerular cellularity and thickened basement membrane. The SBH-treated group showed a decrease in hydropic changes and mild cellularity of the glomerulus vs the ND group based on H&E staining, but the two were similar on PAS staining. Likewise, the SBME-treated group had an increase in cellularity of the glomerulus on H&E staining, but it was comparable to the SBH and ND groups on PAS staining. UNT diabetic rats had tubular hydropic tubules, which were smaller than other groups. Reduced fatty vacuole formation and dilated blood sinusoids in liver tissue were seen in the SBH group. Conversely, the UNT group had high glucose levels, which subsequently increased MDA levels, ultimately leading to liver damage. SBH treatment reduced this damage, as evidenced by having the lowest fasting glucose, serum alanine transaminase, aspartate transaminase, and alkaline phosphatase levels compared to other groups, although the levels of liver enzymes were not statistically significant. CONCLUSION: The cellularity of the Bowman's capsule, as well as histological alteration of kidney tubules, glomerular membranes, and liver tissues in diabetic rats after oral SBH resembled those of ND rats. Therefore, SBH exhibited a protective hepatorenal effect in a diabetic rat model.

Pediatric upper lip myopericytoma: a case report and comprehensive review.

BACKGROUND: Myopericytoma is a rare spindle cell tumor of mesenchymal origin, typically benign, characterized by concentric proliferation of tumor cells around blood vessels within subcutaneous tissue. It primarily occurs in middle-aged adults and is often located in distal extremities, although cases have been reported in proximal extremities and head-neck regions. However, occurrences within the oral cavity are exceedingly rare. To date, literature reviews have identified only two cases in children under 10 years old and reported only five cases of myopericytoma occurring in the lip region. We provide a comprehensive review and analysis of all documented cases to better understand this condition. CASE PRESENTATION: A 7-year-old girl presented to oral and maxillofacial surgery with the discovery of a painless mass on the inner aspect of the upper lip. The diagnosis of myopericytoma was confirmed by histological examination (HE staining), alcian blue staining, and immunohistochemistry. CONCLUSIONS: Following surgical excision, there were no signs of recurrence at a 3-month follow-up. The pathological diagnosis of myopericytoma is quite challenging, and immunohistochemical testing is necessary.

Transparency-enhancing technology allows the three-dimensional assessment of esophageal carcinoma obtained by endoscopic submucosal dissection.

BACKGROUND: Although much progress has been made in diagnosis of carcinomas, no established methods have been confirmed to elucidate their morphological features. METHODS: Three-dimensional structure of esophageal carcinomas was assessed using transparency-enhancing technology. Endoscopically resected esophageal squamous cell carcinoma was fluorescently stained, optically cleared using a transparency-enhancing reagent called LUCID, and visualized using laser scanning microscopy. The resulting microscope images were converted to virtual HE images for observation using ImageJ software. RESULTS: Microscopic observation and image editing enabled three-dimensional image reconstruction and conversion to virtual HE images. The structure of abnormal blood vessels in esophageal carcinoma recognized by endoscopy could be observed in the 3 dimensions. Squamous cell carcinoma and normal squamous epithelium could be distinguished in the virtual HE images. CONCLUSIONS: The results suggested that transparency-enhancing technology and virtual HE images may be feasible for clinical application and represent a novel histopathological method for evaluating endoscopically resected specimens.

Evolution of staining methods in neuroanatomy: Impetus for emanation of neuron doctrine during the turn of 20th century.

The nervous system is distinctive as compared to other tissue systems in human body owing to intricate structural organization. Histological studies played a key role in unveiling complex details of nervous tissue. However, the process of developing suitable staining method for nerve cells was arduous and spanned across almost half a century. The present study explored details of the journey involving quest for propitious staining method in neuroanatomy culminating in promulgation of neuron doctrine at the onset of 20th century. Initial efforts involving hematoxylin (including its diverse modifications) and subsequent adoption of analogous dye-based stains (like Nissl's method) had limited success in visualization of different parts of a nerve cell and structural details of nervous tissue. This was due to inability of dye-based stains to penetrate the connective tissue sheath of nervous tissue. Eventually, advent of metallic stains in form of silver impregnation method (Golgi stain), reduced silver impregnation method with gold stain (Cajal's stain) and silver carbonate staining method of Río-Hortega unraveled the structure of nervous tissue. The evolution of staining methods catalyzed the refinement of theories pertinent to constitution of nervous tissue. Golgi's staining led to emergence of reticular theory (neurons exist as a network) and Nissl's staining was the basis of the concept of Nervösen Grau (nerve cells and glial cells are embedded in mass of gray matter). Finally, Cajal's staining method successfully elucidated the complex anatomy of nerve terminals and resulted in emanation of neuron doctrine (neurons exists as individual units with adjacent connections).

The Mechanism of Astragaloside IV in NOD-like Receptor Family Pyrin Domain Containing 3 Inflammasome-mediated Pyroptosis after Intracerebral Hemorrhage.

BACKGROUND: Intracerebral hemorrhage (ICH) is one of the most common subtypes of stroke. OBJECTIVES: This study aimed to investigate the mechanism of Astragaloside IV (AS-IV) on inflammatory injury after ICH. METHODS: The ICH model was established by the injection of collagenase and treated with ASIV (20 mg/kg or 40 mg/kg). The neurological function, water content of the bilateral cerebral hemisphere and cerebellum, and pathological changes in brain tissue were assessed. The levels of interleukin-1 beta (IL-1ß), IL-18, tumor necrosis factor-alpha, interferon-gamma, and IL-10 were detected by enzyme-linked immunosorbent assay. The levels of Kruppel-like factor 2 (KLF2), NOD-like receptor family pyrin domain containing 3 (NLRP3), GSDMD-N, and cleaved-caspase-1 were detected by reverse transcription-quantitative polymerase chain reaction and Western blot assay. The binding relationship between KLF2 and NLRP3 was verified by chromatin-immunoprecipitation and dual-luciferase assays. KLF2 inhibition or NLRP3 overexpression was achieved in mice to observe pathological changes. RESULTS: The decreased neurological function, increased water content, severe pathological damage, and inflammatory response were observed in mice after ICH, with increased levels of NLRP3/GSDMD-N/cleaved-caspase-1/IL-1ß/IL-18 and poorly-expressed KLF2 in brain tissue. After AS-IV treatment, the neurological dysfunction, high brain water content, inflammatory response, and pyroptosis were alleviated, while KLF2 expression was increased. KLF2 bonded to the NLRP3 promoter region and inhibited its transcription. Down-regulation of KLF2 or upregulation of NLRP3 reversed the effect of AS-IV on inhibiting pyroptosis and reducing inflammatory injury in mice after ICH. CONCLUSION: AS-IV inhibited NLRP3-mediated pyroptosis by promoting KLF2 expression and alleviated inflammatory injury in mice after ICH.

Morphology-based molecular classification of spinal cord ependymomas using deep neural networks.

Based on DNA-methylation, ependymomas growing in the spinal cord comprise two major molecular types termed spinal (SP-EPN) and myxopapillary ependymomas (MPE(-A/B)), which differ with respect to their clinical features and prognosis. Due to the existing discrepancy between histomorphogical diagnoses and classification using methylation data, we asked whether deep neural networks can predict the DNA methylation class of spinal cord ependymomas from hematoxylin and eosin stained whole-slide images. Using explainable AI, we further aimed to prospectively improve the consistency of histology-based diagnoses with DNA methylation profiling by identifying and quantifying distinct morphological patterns of these molecular ependymoma types. We assembled a case series of 139 molecularly characterized spinal cord ependymomas (nMPE = 84, nSP-EPN = 55). Self-supervised and weakly-supervised neural networks were used for classification. We employed attention analysis and supervised machine-learning methods for the discovery and quantification of morphological features and their correlation to the diagnoses of experienced neuropathologists. Our best performing model predicted the DNA methylation class with 98% test accuracy and used self-supervised learning to outperform pretrained encoder-networks (86% test accuracy). In contrast, the diagnoses of neuropathologists matched the DNA methylation class in only 83% of cases. Domain-adaptation techniques improved model generalization to an external validation cohort by up to 22%. Statistically significant morphological features were identified per molecular type and quantitatively correlated to human diagnoses. The approach was extended to recently defined subtypes of myxopapillary ependymomas (MPE-(A/B), 80% test accuracy). In summary, we demonstrated the accurate prediction of the DNA methylation class of spinal cord ependymomas (SP-EPN, MPE(-A/B)) using hematoxylin and eosin stained whole-slide images. Our approach may prospectively serve as a supplementary resource for integrated diagnostics and may even help to establish a standardized, high-quality level of histology-based diagnostics across institutions-in particular in low-income countries, where expensive DNA-methylation analyses may not be readily available.

HoLy-Net: Segmentation of histological images of diffuse large B-cell lymphoma.

Over the last years, there has been large progress in automated segmentation and classification methods in histological whole slide images (WSIs) stained with hematoxylin and eosin (H&E). Current state-of-the-art (SOTA) techniques are based on diverse datasets of H&E-stained WSIs of different types of predominantly solid cancer. However, there is a scarcity of methods and datasets enabling segmentation of tumors of the lymphatic system (lymphomas). Here, we propose a solution for segmentation of diffuse large B-cell lymphoma (DLBCL), the most common non-Hodgkin's lymphoma. Our method applies to both H&E-stained slides and to a broad range of markers stained with immunohistochemistry (IHC). While IHC staining is an important tool in cancer diagnosis and treatment decisions, there are few automated segmentation and classification methods for IHC-stained WSIs. To address the challenges of nuclei segmentation in H&E- and IHC-stained DLBCL images, we propose HoLy-Net - a HoVer-Net-based deep learning model for lymphoma segmentation. We train two different models, one for segmenting H&E- and one for IHC-stained images and compare the test results with the SOTA methods as well as with the original version of HoVer-Net. Subsequently, we segment patient WSIs and perform single cell-level analysis of different cell types to identify patient-specific tumor characteristics such as high level of immune infiltration. Our method outperforms general-purpose segmentation methods for H&E staining in lymphoma WSIs (with an F1 score of 0.899) and is also a unique automated method for IHC slide segmentation (with an F1 score of 0.913). With our solution, we provide a new dataset we denote LyNSeC (lymphoma nuclear segmentation and classification) containing 73,931 annotated cell nuclei from H&E and 87,316 from IHC slides. Our method and dataset open up new avenues for quantitative, large-scale studies of morphology and microenvironment of lymphomas overlooked by the current automated segmentation methods.