A case report on incidentally detected pulmonary sclerosing pneumocytoma: a diagnostic challenge.

Introduction and importance: Pulmonary sclerosing pneumocytoma (PSP) is a rare non-cancerous lung tumor that is usually asymptomatic, but may cause respiratory distress if it becomes large. PSPs are often detected incidentally because of their slow growth, lack of symptoms, characteristic radiographic features, and increased use of imaging studies. Although it is not a malignant tumor, it can mimic malignancy on imaging and histology, leading to misdiagnosis and unnecessary surgery. Case presentation: A 23-year-old asymptomatic female was incidentally diagnosed with PSP during evaluation for a breast fibroadenoma. A chest CT revealed a 3 cm lobulated mass in the left upper lobe. Cytology showed malignant cells with necrotic debris. Immunohistochemistry was positive for TTF-1 and EMA, negative for p63 and AE1/AE3. Histopathology confirmed a well-circumscribed benign neoplasm, consistent with pulmonary sclerosing pneumocytoma. There was no mediastinal lymph node invasion, and the post-surgery prognosis was good. Clinical discussion: PSP is a slow-growing tumor that is often asymptomatic until it reaches a significant size. Owing to their well-circumscribed margins and the presence of calcifications, they are often detected incidentally during imaging studies, such as routine chest radiography or CT scans for unrelated conditions. Although these tumors are often incidental, it is important to diagnose and treat them appropriately to prevent potential complications and malignant transformation. Conclusion: The findings of this study contribute to the existing literature, increase awareness of this rare tumor, and provide insights into its diagnosis, treatment, and follow-up.

Investigating the toxicity of polylactic acid microplastics on the health and physiology of freshwater fish, Cirrhinus mrigala.

The widespread presence of microplastics (MPs) in aquatic ecosystems has raised growing concerns among ecotoxicologists regarding their potential toxicity. This study explored the impacts of polylactic acid (PLA) MPs on the physiology and health of freshwater fish, Cirrhinus mrigala, by dietary exposure for 90 days. The experiment consisted of six groups: five treatment groups (0.5%, 1%, 1.5%, 2%, and 2.5% PLA-MP) and a control group (0% PLA-MP). Each group was comprised of fifteen fish, and the experiment was replicated three times. The exposure severity of PLA-MPs varied from low to high, with treatment levels ranging from 0.5% to 2.5% PLA-MPs, relative to the control group. This exposure significantly affected their growth performance. Additionally, the apparent digestibility of the SFM-based diet decreased with increasing PLA-MPs concentration. Exposure to PLA-MPs induced considerable changes in body composition, characterized by increased moisture and crude fat content and decreased ash content and crude protein. The blood profile, including MCHC, RBCs, Hb, PLT and PCV exhibited significant declines in the high treatment group (2.5% PLA-MPs), while MCH, WBCs and MCV showed notable increases. Furthermore, histopathological examination of the intestine revealed an increase in abnormalities in the intestine at 2.5% PLA-MPs level. The high treatment group (2.5% PLA-MPs) showed the lowest mineral content in the fish muscles. In summary, dietary exposure to PLA-MPs led to alterations in overall body performance across the treatment groups, ranging from low to high severity levels.

Leishmania infantum infection in European badgers (Meles meles) from northeastern Spain: a histopathological and immunohistochemical investigation.

The European badger (Meles meles) is a common mustelid species known as a significant reservoir for various human and animal diseases. Studies investigating Leishmania infection in European badgers across Mediterranean regions have yielded inconsistent findings. In Spain, results are particularly controversial: some studies confirm the presence of Leishmania in badgers, while others do not. Our study aimed to conduct a retrospective histopathological and immunohistochemical analysis to detect Leishmania in tissues of nine European badgers from northeastern Spain, a region previously unevaluated for Leishmania infection in this species. Microscopic examination revealed lesions indicative of leishmaniosis in the lymph nodes and spleens of six badgers. In one of them, Leishmania-like structures were identified in multiple organs and confirmed via immunohistochemistry. Parasites were detected in the lymph nodes, spleen, adrenal glands, and pancreas. The parasite load was high in the adrenal glands, moderate in the lymph nodes and spleen, and low in the pancreas. No parasites were found in other examined organs. This finding represents a frequency of 11.11% (1/9) of Leishmania infection among the badgers we studied. Further investigation of wildlife and atypical reservoirs can enhance our understanding of the pathogenesis of this significant zoonotic disease.

Defining the Etiology of Renal Allograft Dysfunction Using Banff 2019 Classification: Correlation with Post-Transplant Duration and Creatinine Levels-A Comprehensive Analysis of 200 Renal Biopsies at a Tertiary Care Medical Center Hospital.

OBJECTIVE: Chronic kidney disease is a growing global health issue, contributing significantly to morbidity and mortality. The incidence of end-stage renal disease (ESRD) is approximately 100 per million population. Renal transplantation remains the cornerstone treatment for ESRD, with a projected 20-year survival rate of 60%. We aim to define the etiology of renal allograft dysfunction using the Banff 2019 classification by analyzing 200 renal allograft biopsies in correlation with creatinine levels across post-transplant time frames. METHODOLOGY: 200 renal allograft biopsies are analyzed using the recent Banff 2019 classification with creatinine levels and post-transplant duration correlation. RESULTS: The study included 150 (75%) male patients and 50 (25%) female patients, with the majority 78 (39%) representing the age group of 16-30 years. 36 (18%) biopsies were within 3-month post-transplant, while 92 (46%) were 2-year post-transplant. According to the Banff 2019 classification, 92 (46.0%) transplant rejection biopsies were identified, with most 54 (27%) exhibiting antibody-mediated rejection (Category 2), including 40 (20%) active acute antibody-mediated rejection (ABMR) and 14 (7.0%) chronic active ABMR. T-cell-mediated rejection (TCMR; Category 4) represented 12 (6%) biopsies, including 10 (5%) acute TCMR and 2 (1%) chronic active TCMR. Category 5, the miscellaneous group, represented 100 (50%) biopsies, out of which 32 (16%) exhibited calcineurin inhibitor (CNI) toxicity, 38 (19%) acute tubular necrosis, and 8 (4%) thrombotic microangiopathy. A notable variation in the dysfunction distribution across different post-transplant time frames indicated a temporal evolution in the underlying causes of allograft dysfunction. Specific Banff categories showed a robust association with renal dysfunction, potentially contributing to the elevation of creatinine levels and renal function deterioration. CONCLUSION: Our study highlights the intricate pathophysiology of renal allograft dysfunction. Most biopsies were attributed to ABMR whereas one-third of biopsies exhibited mixed lesions (ABMR and TCMR or ABMR and calcineurin inhibitor toxicity (CNIT)). Additionally, this study suggests that renal allograft rejection remains a significant contributor to graft dysfunction. A complex interplay between histological findings, Banff classification, and renal function is noted. A significant difference in the distribution of dysfunction across post-transplant time frames is noted suggesting a temporal evolution in the etiology of allograft dysfunction. Certain Banff categories demonstrate a stronger association with renal dysfunction that may influence creatinine level increase and renal function deterioration. In correspondence to the recent Banff 2019 guidelines for diagnosing ABMR, we emphasize the role of C4d staining on immunofluorescence or immunohistochemistry in allograft biopsies as imperative for timely diagnosis and immunosuppressant therapy adjustment, ultimately enhancing graft survival. Further research is needed to elucidate the underlying mechanisms driving renal dysfunction in different Banff categories, ultimately informing personalized management strategies for patients with renal allograft dysfunction. In line with the Banff 2019 guidelines for diagnosing ABMR, this study highlights the critical role of C4d staining through immunofluorescence or immunohistochemistry in allograft biopsies for early diagnosis and timely adjustment of immunosuppressive therapy, ultimately improving graft survival.

The expanding role of artificial intelligence in the histopathological diagnosis in urological oncology: a literature review.

The ongoing growth of artificial intelligence (AI) involves virtually every aspect of oncologic care in medicine. Although AI is in its infancy, it has shown great promise in the diagnosis of oncologic urological conditions. This paper aims to explore the expanding role of artificial intelligence in the histopathological diagnosis in urological oncology. We conducted a focused review of the literature on AI in urological oncology, searching PubMed and Google Scholar for recent advancements in histopathological diagnosis using AI. Various keyword combinations were used to find relevant sources published before April 2nd, 2024. We approached this article by focusing on the impact of AI on common urological malignancies by incorporating the use of different AI algorithms. We targeted the capabilities of AI's potential in aiding urologists and pathologists in histological cancer diagnosis. Promising results suggest AI can enhance diagnosis and personalized patient care, yet further refinements are needed before widespread hospital adoption. AI is transforming urological oncology by improving histopathological diagnosis and patient care. This review highlights AI's advancements in diagnosing prostate, renal cell, and bladder cancer. It is anticipated that as AI becomes more integrated into clinical practice, it will have a greater influence on diagnosis and improve patient outcomes.

Locally Advanced Adenoid Cystic Carcinoma of the Right Submandibular Gland With Tuberculosis: A Case Report and Review of the Literature.

Adenoid cystic carcinoma (ACC) is an aggressive form of salivary gland cancer that mostly affects the accessory, parotid, and submandibular salivary glands. This tumor is characterized by slower development, perineural invasion, and possible local recurrence in clinical and pathological findings. A male patient, aged 71, who was from a remote area, appeared with a lesion affecting the right submandibular gland and had been experiencing discomfort in the same region for four months. Following a biopsy and the histological confirmation of ACC in the right submandibular gland, the tumor was widely excised locally.

Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features.

PURPOSE: This study investigates the application of Radiomic features within graph neural networks (GNNs) for the classification of multiple-epitope-ligand cartography (MELC) pathology samples. It aims to enhance the diagnosis of often misdiagnosed skin diseases such as eczema, lymphoma, and melanoma. The novel contribution lies in integrating Radiomic features with GNNs and comparing their efficacy against traditional multi-stain profiles. METHODS: We utilized GNNs to process multiple pathological slides as cell-level graphs, comparing their performance with XGBoost and Random Forest classifiers. The analysis included two feature types: multi-stain profiles and Radiomic features. Dimensionality reduction techniques such as UMAP and t-SNE were applied to optimize the feature space, and graph connectivity was based on spatial and feature closeness. RESULTS: Integrating Radiomic features into spatially connected graphs significantly improved classification accuracy over traditional models. The application of UMAP further enhanced the performance of GNNs, particularly in classifying diseases with similar pathological features. The GNN model outperformed baseline methods, demonstrating its robustness in handling complex histopathological data. CONCLUSION: Radiomic features processed through GNNs show significant promise for multi-disease classification, improving diagnostic accuracy. This study's findings suggest that integrating advanced imaging analysis with graph-based modeling can lead to better diagnostic tools. Future research should expand these methods to a wider range of diseases to validate their generalizability and effectiveness.

Randomized clinical trial on accelerated preoperative hyperfractionated radiotherapy (HART) vs preoperative hyperfractionated radio-chemotherapy (HART-CT) in locally advanced rectal cancer.

OBJECTIVES: The aim of this study was to compare pathological response rates after reoperative hyperfractionated radiotherapy with co-administration of chemotherapy based on 5FU (HART-CT) vs. preoperative hyperfractionated radiotherapy (HART) in patients with resectable rectal cancer. METHODS: Patients with T2/N+ or T3/any N rectal cancer were randomized either to HART twice a day (28 fractions of 1.5 Gy) to total dose 42 Gy or to HART-CT. Tumor regression grade was postoperatively assessed according to the 4-point scale as recommended by the AJCC. The secondary endpoints included overall survival (OS), disease-free survival (DFS), toxicity of preoperative treatment, locoregional and distant failure rates. There were 187 patients eligible for analysis: 95 in HART and 92 in the HART-CT. Median follow-up was 5.6 years. RESULTS: The analysis demonstrated a significantly higher chance of achieving pCR in HART-CT arm: complete response was achieved in 4/95, 4% (HART) and 11/92, 12% (HART-CT) (p = 0.045). The differences in OS and DFS, while tending to favor HART-CT, were not significant (p = 0.13, HR = 0.82, 95% CI 0.63-1.06) and (p = 0.32; HR = 0.88, 95% CI 0.69-1.13), respectively. The locoregional failure and distant metastases rates did not statistically differ between the trial arms. The rate of late complications were similar (p = 0.51), grade 3+ being 8% versus 11% in the HART/HART-CT group, respectively. CONCLUSIONS: The hyperfractionated preoperative radiotherapy with concurrent 5-Fu based chemotherapy (HART-CT) improved pathological response rate compared to HART. This translated into favorable OS and DFS in HART-CT, but the differences did not reach the threshold for significance. ADVANCES IN KNOWLEDGE: A new hyperfractionated chemo-RT scheme is proposed. Histopathological major response (TRG 0-1) is associated with better clinical outcome.

SG-Fusion: A swin-transformer and graph convolution-based multi-modal deep neural network for glioma prognosis.

The integration of morphological attributes extracted from histopathological images and genomic data holds significant importance in advancing tumor diagnosis, prognosis, and grading. Histopathological images are acquired through microscopic examination of tissue slices, providing valuable insights into cellular structures and pathological features. On the other hand, genomic data provides information about tumor gene expression and functionality. The fusion of these two distinct data types is crucial for gaining a more comprehensive understanding of tumor characteristics and progression. In the past, many studies relied on single-modal approaches for tumor diagnosis. However, these approaches had limitations as they were unable to fully harness the information from multiple data sources. To address these limitations, researchers have turned to multi-modal methods that concurrently leverage both histopathological images and genomic data. These methods better capture the multifaceted nature of tumors and enhance diagnostic accuracy. Nonetheless, existing multi-modal methods have, to some extent, oversimplified the extraction processes for both modalities and the fusion process. In this study, we presented a dual-branch neural network, namely SG-Fusion. Specifically, for the histopathological modality, we utilize the Swin-Transformer structure to capture both local and global features and incorporate contrastive learning to encourage the model to discern commonalities and differences in the representation space. For the genomic modality, we developed a graph convolutional network based on gene functional and expression level similarities. Additionally, our model integrates a cross-attention module to enhance information interaction and employs divergence-based regularization to enhance the model's generalization performance. Validation conducted on glioma datasets from the Cancer Genome Atlas unequivocally demonstrates that our SG-Fusion model outperforms both single-modal methods and existing multi-modal approaches in both survival analysis and tumor grading.

A Case of Conjunctival Cyst Required Removal Six Months After Strabismus Surgery.

A conjunctival cyst is a rare yet significant complication following strabismus surgery. This report describes a nine-year-old girl who developed a conjunctival cyst after undergoing bilateral lateral rectus recession surgery for intermittent exotropia. Despite an uneventful surgery and standard postoperative care, she presented with a gradually enlarging subconjunctival mass in the left eye three months later. Initial conservative treatment with topical antibiotics and steroids proved ineffective, leading to surgical excision six months postoperatively. Histopathological examination confirmed the cyst as a conjunctival epithelial inclusion cyst, characterized by cuboidal epithelium containing goblet cells. The patient's postoperative course was uneventful, with no recurrence of the cyst at six months follow-up, stable visual acuity, and maintained strabismus correction. In managing this case, two crucial lessons were learned. Firstly, the need for precise surgical techniques and the use of adequate pre- and intraoperative disinfection measures to prevent postoperative complications. Ensuring that the conjunctival tissue is not inadvertently included in the wound closure and maintaining a sterile environment throughout the surgery are critical steps. Secondly, the importance of early recognition and timely intervention for postoperative complications. The patient's cyst developed three months post-surgery and did not respond to conservative treatments, necessitating surgical excision. This reinforces the need for heightened awareness and prompt surgical intervention when conservative measures fail, ensuring optimal patient outcomes and avoiding unnecessary discomfort or cosmetic issues. In conclusion, meticulous surgical technique and proper pre- and intraoperative disinfection are paramount in preventing postoperative complications such as conjunctival cysts. Early recognition and timely surgical intervention are essential for managing these cysts effectively. This case reinforces the importance for ophthalmic surgeons to remain vigilant in their surgical practices and to promptly address any postoperative complications, thereby improving surgical outcomes and enhancing patient care in strabismus surgery.

Development of an ultrasound-guided radiofrequency ablation technique in the equine cadaveric distal limb: histological findings and potential for treating chronic lameness.

Introduction: Radiofrequency (RF) relieves chronic pain in humans, but it is unexplored in horses affected by chronic lameness. This study aims to describe the technique and the histological effects of ultrasound (US)-guided radiofrequency ablation (RFA) of palmar digital nerves (PDNs) in horse's fetlock and pastern, ex vivo. Methods: After assessing the US anatomy of lateral and medial PDNs in fetlock and pastern in vivo (n = 10 horses; 20 forelimbs), US-guided RFA was performed on these sites in cadaveric forelimbs (n = 10) applying four different settings with increasing invasiveness (n = 40 total treatments): 60°C, 6 min (GROUP LOW); 70°C, 4 min (GROUP MEDIUM); 90°C, 2 min (GROUP HIGH); 80°C, 8 min (GROUP VERY HIGH). Needle-tip-to-nerve proximity was assessed with US and methylene blue, injected through the port of the RF needle. Nerves were collected for microscopical assessment. Results: Transverse palmaro-lateral and palmaro-medial US images of fetlock and pastern detected PDNs consistently, close to the palmar digital artery. With in-plane US technique, RFA was performed at target in 31/40 cases, with significantly higher number of failures in fetlock (p = 0.008). PDNs histology identified thermal injury/coagulation with axonal degeneration and collagen homogenation. Nuclear smearing of arterial leyomyocytes was also observed. Nerve coagulation was significantly associated with treatment (p = 0.03) and needle-tip-to-nerve proximity (US distance: p = 0.009; blue distance: p = 0.04). Discussion: The PDNs were easily visualized and reached with the RF needle by US in-plane-guided technique. RFA produced axonal thermal damage and intensity-related coagulation effectiveness. To ensure effective nerve coagulation, it is crucial that the needle is accurately positioned in close proximity to the target nerve. Based on the histopathological findings, HIGH and VERY HIGH RFA treatments might be worth of being tested in vivo in clinical studies aimed at treating chronic lameness of the distal forelimb in horses.

Proven anti-virulence therapies in combating methicillin- and vancomycin-resistant Staphylococcus aureus infections.

Introduction: Despite years of efforts to develop new antibiotics for eradicating multidrug-resistant (MDR) and multi-virulent Methicillin-Resistant Staphylococcus aureus (MRSA) and Vancomycin-Resistant Staphylococcus aureus (VRSA) infections, treatment failures and poor prognoses in most cases have been common. Therefore, there is an urgent need for new therapeutic approaches targeting virulence arrays. Our aim is to discover new anti-virulence therapies targeting MRSA and VRSA virulence arrays. Methodology: We employed phenotypic, molecular docking, and genetic studies to screen for anti-virulence activities among selected promising compounds: Coumarin, Simvastatin, and Ibuprofen. Results: We found that nearly all detected MRSA and VRSA strains exhibited MDR and multi-virulent profiles. The molecular docking results aligned with the phenotypic and genetic assessments of virulence production. Biofilm and hemolysin productions were inhibited, and all virulence genes were downregulated upon treatment with sub-minimum inhibitory concentration (sub-MIC) of these promising compounds. Ibuprofen was the most active compound, exhibiting the highest inhibition and downregulation of virulence gene products. Moreover, in vivo and histopathological studies confirmed these results. Interestingly, we observed a significant decrease in wound area and improvements in re-epithelialization and tissue organization in the Ibuprofen and antimicrobial treated group compared with the group treated with antimicrobial alone. These findings support the idea that a combination of Ibuprofen and antimicrobial drugs may offer a promising new therapy for MRSA and VRSA infections. Conclusion: We hope that our findings can be implemented in clinical practice to assist physicians in making the most suitable treatment decisions.

Comparison of histopathological and triphenyl tetrazolium chloride test in diagnosing myocardial infarction: An autopsy study.

Background: Sudden and unexpected deaths are increasing drastically. The main cause of sudden death is cardiovascular disease, out of which coronary artery disease predominates forming 80% of the cases. Most of the time, detecting early changes in myocardial infarction during the autopsy is challenging since gross infarct changes do not appear until after 24 to 48 hours of myocardial ischemia injury. So, the aim of this study was to compare two test to detect early changes of Myocardial Infarction one by using Triphenyl Tetrazolium Chloride (TTC) staining of the myocardial tissue, during autopsy and other by histopathological examination. Methods: The sample size of 60 hearts taken from all the sudden deaths cases brought to Mortuary with suspected cause of death due to cardiac origin. The heart was obtained from the deceased by standard post-mortem technique. Serial full-thickness transverse sections of the heart were taken at 2 cm intervals from the apex to the atrioventricular groove. All the serial slices of heart are taken for histochemical staining and TTC staining. Results: In histopathological examination 34 hearts were diagnosed with myocardial infarction and 26 hearts reported non myocardial infarction. With TTC 40 hearts remained unstained suggestive of myocardial infarction and 20 hearts were stained suggestive of non-infarcted hearts. TTC staining in our study shows an accuracy of 88.33%. Conclusion: The result of this study shows that the Triphenyl Tetrazolium Chloride test, a histochemical staining technique of heart, is reliable approach for forensic pathologists to diagnose early myocardial infarction during the post-mortem examination.

Exploiting histopathological imaging for early detection of lung and colon cancer via ensemble deep learning model.

Cancer seems to have a vast number of deaths due to its heterogeneity, aggressiveness, and significant propensity for metastasis. The predominant categories of cancer that may affect males and females and occur worldwide are colon and lung cancer. A precise and on-time analysis of this cancer can increase the survival rate and improve the appropriate treatment characteristics. An efficient and effective method for the speedy and accurate recognition of tumours in the colon and lung areas is provided as an alternative to cancer recognition methods. Earlier diagnosis of the disease on the front drastically reduces the chance of death. Machine learning (ML) and deep learning (DL) approaches can accelerate this cancer diagnosis, facilitating researcher workers to study a vast majority of patients in a limited period and at a low cost. This research presents Histopathological Imaging for the Early Detection of Lung and Colon Cancer via Ensemble DL (HIELCC-EDL) model. The HIELCC-EDL technique utilizes histopathological images to identify lung and colon cancer (LCC). To achieve this, the HIELCC-EDL technique uses the Wiener filtering (WF) method for noise elimination. In addition, the HIELCC-EDL model uses the channel attention Residual Network (CA-ResNet50) model for learning complex feature patterns. Moreover, the hyperparameter selection of the CA-ResNet50 model is performed using the tuna swarm optimization (TSO) technique. Finally, the detection of LCC is achieved by using the ensemble of three classifiers such as extreme learning machine (ELM), competitive neural networks (CNNs), and long short-term memory (LSTM). To illustrate the promising performance of the HIELCC-EDL model, a complete set of experimentations was performed on a benchmark dataset. The experimental validation of the HIELCC-EDL model portrayed a superior accuracy value of 99.60% over recent approaches.

Clinicopathological Pattern of Renal Biopsies in Children with Nephrotic Syndrome.

Background: A renal biopsy is essential for the identification and management of renal disorders. Although considered an invasive operation, it is necessary for a definitive diagnosis and treatment of many renal diseases. The primary goal of this study was to assess the clinicopathological aspect of renal diseases undergoing biopsy in children receiving tertiary care.Patients and Methods: Children (≤18 years) hospitalized with nephrotic syndrome were the subjects of this cross-sectional study, and comprehensive assessments confirmed the need for a kidney biopsy. Included were 277 children who met the inclusion and exclusion criteria. Data on patient outcomes, biopsy indications, complications, histopathologic results, and demographic information were documented.Results: Of the 277 patients who underwent renal biopsy, 63.2% were male, and 36.8% were female. Average age of the patients was 15 ± 2.9 years, with age distribution ranging from 3 to 18 years. The most frequent indication for renal biopsy was atypical age of <1 and >10-years-old (91.7%), steroid-resistant (5.1%), asymptomatic hematuria (21.3%), abnormal glomerular filtration rate (16.2%), and proteinuria (14.8%). The most common histopathological findings were focal segmental glomerulosclerosis (FSGS) (36.5%), followed by minimal change disease (MCD) (13.4%), membranoproliferative glomerulonephritis (MPGN) (10.5%), membranous glomerulonephritis (MGN) (7.94%), IgA nephropathy (IGAN) (7.58%), non-proliferative glomerulonephritis (NPGN) (7.58%), diffuse proliferative glomerulonephritis (DPGN) (6.9%), crescentic GN (5.8%), and systemic lupus erythematosus (SLE) (3.97%). The high frequency of positive samples was seen in SLE, followed by DPGN, MPGN, IGAN, and MGN. In contrast, MCD, crescentic GN, and NPGN showed negativity in all differential item functioning (DIF) parameters.Conclusion: Renal biopsy is a safe and effective procedure in the diagnosis and treatment of in children with nephrotic syndrome. FSGS had the highest frequency in examined biopsies.

Mucinous Carcinoma of the Breast With Neuroendocrine Differentiation: A Case Report of Cyto-Histopathology Findings.

Mucinous breast carcinoma is a rare neoplasm. A minority of breast neoplasms exhibit a mucinous component, with purely mucinous cases being less frequent. It is more typically found in postmenopausal women. The etiology is multifactorial and involves dietary factors, reproductive factors, and hormonal factors. Mucinous carcinoma can grow to a large size at the time of diagnosis, although it typically grows slowly and palpable. Transcriptomic genetic studies have explained that mucinous tumors are of luminal A molecular subtype. Mucinous A tumors have different transcriptome characteristics than mucinous B tumors, which have a gene expression pattern resembling neuroendocrine (NE) carcinomas. Diagnosis of mucinous carcinoma with NE differentiation by fine needle aspiration cytology (FNAC) is reported infrequently. Histopathology is mandatory in the evaluation of mucinous breast carcinoma. NE carcinoma of the breast is an underestimated subtype of BC which has characteristics of heterogenicity, rarity, and poor differentiation. In this instance, we present a case of breast carcinoma exhibiting NE differentiation. A postmenopausal woman aged 63, with no family history of breast cancer, presented with a firm mass in the upper lateral quadrant of her right breast. This lump, causing discomfort for the past two years, was accompanied by nipple retraction and the discharge of bloody fluid. The clinical examination revealed the palpable presence of the lump. Ultrasonography-guided FNAC suggested Mucinous breast carcinoma with NE differentiation. The patient underwent a modified radical mastectomy, and the tissue was evaluated by immunohistochemistry which confirmed the diagnosis.

Augmented histopathology: Enhancing colon cancer detection through deep learning and ensemble techniques.

Colon cancer poses a significant threat to human life with a high global mortality rate. Early and accurate detection is crucial for improving treatment quality and the survival rate. This paper presents a comprehensive approach to enhance colon cancer detection and classification. The histopathological images are gathered from the CRC-VAL-HE-7K dataset. The images undergo preprocessing to improve quality, followed by augmentation to increase dataset size and enhance model generalization. A deep learning based transformer model is designed for efficient feature extraction and enhancing classification by incorporating a convolutional neural network (CNN). A cross-transformation model captures long-range dependencies between regions, and an attention mechanism assigns weights to highlight crucial features. To boost classification accuracy, a Siamese network distinguishes colon cancer tissue classes based on probabilities. Optimization algorithms fine-tune model parameters, categorizing colon cancer tissues into different classes. The multi-class classification performance is evaluated in the experimental evaluation, which demonstrates that the proposed model provided highest accuracy rate of 98.84%. In this research article, the proposed method achieved better performance in all analyses by comparing with other existing methods. RESEARCH HIGHLIGHTS: Deep learning-based techniques are proposed. DL methods are used to enhance colon cancer detection and classification. CRC-VAL-HE-7K dataset is utilized to enhance image quality. Hybrid particle swarm optimization (PSO) and dwarf mongoose optimization (DMO) are used. The deep learning models are tuned by implementing the PSO-DMO algorithm.