A unicentric center, multicenter, and mixed-type Castleman disease: Three case reports and a review of the literature.

RATIONALE: Due to the lack of specificity symptoms and site of onset of castleman disease (CD), it is difficult to diagnose and poses unique challenges for both patients and clinicians, leading to confusion in diagnosis and delays in treatment. To enhance understanding, we present 3 cases of CD treated at our hospital, including a single-center, multicenter, and mixed-type CD. PATIENT CONCERNS: Case 1: A 53-year-old female patient was admitted with a chief complaint of "abdominal pain and fever for 10 days." Marked enlargement of inguinal lymph nodes on both sides was observed. Case 2: A 58-year-old female patient was admitted with the main complaint of "discovering a left lower abdominal mass during a routine checkup for the past 10 days." Upon deep palpation, a palpable mass of approximately 5.0 * 3.0 cm was identified in the left lower abdomen. Case 3: A 40-year-old male patient was admitted with the main complaint of "progressive right upper abdominal and lumbar back pain for over 6 months." Computed tomography examination revealed multiple nodular soft tissue masses between the abdominal aorta and inferior vena cava, with the largest measuring 5.0 * 4.0 cm. DIAGNOSES: Based on the immunohistochemical results, the diagnoses for the 3 patients are as follows: Case 1: Multicentric Castleman's Disease (Mixed Type). Case 2: Pelvic Retroperitoneal Castleman Disease (Hyaline Vascular Type). Case 3: Castleman Disease Multicentric Type. INTERVENTION: Case 1: cyclophosphamide 0.6-1 g + vincristine 2 mg + methylprednisolone 50 mg/5 days. Cyclophosphamide 1 g + prednisone 30-50 mg/5 days. This alternating chemotherapy cycle is repeated every 6 months. Case 2: Laparoscopic pelvic mass excision surgery. Case 3: Surgical excision of the mass. OUTCOMES: Case 1: After a 43-month follow-up, the patient's general symptoms have improved compared to before, but regular chemotherapy is still necessary at present. Case 2: The patient did not take any medication postoperatively, and there has been no evidence of metastasis or recurrence during the 18-month follow-up. Case 3: The patient did not take any medication, and there has been no evidence of metastasis or recurrence during the 21-month follow-up. LESSONS SUBSECTIONS: The lack of specific signs on imaging studies and nonspecific blood tests increases the difficulty of diagnosis. However, tissue biopsy remains a feasible option. Therefore, we recommend conducting thorough examinations for suspected CD patients to reduce misdiagnosis and determine the CD type for effective targeted treatment.

A Novel Hybrid Deep Learning Model for Metastatic Cancer Detection.

Cancer has been found as a heterogeneous disease with various subtypes and aims to destroy the body's normal cells abruptly. As a result, it is essential to detect and prognosis the distinct type of cancer since they may help cancer survivors with treatment in the early stage. It must also divide cancer patients into high- and low-risk groups. While realizing efficient detection of cancer is frequently a time-taking and exhausting task with the high possibility of pathologist errors and previous studies employed data mining and machine learning (ML) techniques to identify cancer, these strategies rely on handcrafted feature extraction techniques that result in incorrect classification. On the contrary, deep learning (DL) is robust in feature extraction and has recently been widely used for classification and detection purposes. This research implemented a novel hybrid AlexNet-gated recurrent unit (AlexNet-GRU) model for the lymph node (LN) breast cancer detection and classification. We have used a well-known Kaggle (PCam) data set to classify LN cancer samples. This study is tested and compared among three models: convolutional neural network GRU (CNN-GRU), CNN long short-term memory (CNN-LSTM), and the proposed AlexNet-GRU. The experimental results indicated that the performance metrics accuracy, precision, sensitivity, and specificity (99.50%, 98.10%, 98.90%, and 97.50) of the proposed model can reduce the pathologist errors that occur during the diagnosis process of incorrect classification and significantly better performance than CNN-GRU and CNN-LSTM models. The proposed model is compared with other recent ML/DL algorithms to analyze the model's efficiency, which reveals that the proposed AlexNet-GRU model is computationally efficient. Also, the proposed model presents its superiority over state-of-the-art methods for LN breast cancer detection and classification.

Protective Effects of Cinnamaldehyde against Mesenteric Ischemia-Reperfusion-Induced Lung and Liver Injuries in Rats.

The aim of this study was to characterize and reveal the protective effects of cinnamaldehyde (CA) against mesenteric ischemia-reperfusion- (I/R-) induced lung and liver injuries and the related mechanisms. Sprague-Dawley (SPD) rats were pretreated for three days with 10 or 40 mg/kg/d, ig of CA, and then induced with mesenteric ischemia for 1 h and reperfusion for 2 h. The results indicated that pretreatment with 10 or 40 mg/kg of CA attenuated morphological damage in both lung and liver tissues of mesenteric I/R-injured rats. CA pretreatment significantly restored the levels of aspartate transaminase (AST) and alanine transaminase (ALT) in mesenteric I/R-injured liver tissues, indicating the improvement of hepatic function. CA also significantly attenuated the inflammation via reducing myeloperoxidase (MOP) activity and downregulating the expression of inflammation-related proteins, including interleukin-6 (IL-6), interleukin-1ß (IL-1ß), cyclooxygenase-2 (Cox-2), and tumor necrosis factor receptor type-2 (TNFR-2) in both lung and liver tissues of mesenteric I/R-injured rats. Pretreatment with CA significantly downregulated nuclear factor kappa B- (NF-κB-) related protein expressions (NF-κB p65, NF-κB p50, I kappa B alpha (IK-α), and inhibitor of nuclear factor kappa-B kinase subunit beta (IKKß)) in both lung and liver tissues of mesenteric I/R-injured rats. CA also significantly downregulated the protein expression of p53 family members, including caspase-3, caspase-9, Bax, and p53, and restored Bcl-2 in both lung and liver tissues of mesenteric I/R-injured rats. CA pretreatment significantly reduced TUNEL-apoptotic cells and significantly inhibited p53 and NF-κB p65 nuclear translocation in both lung and liver tissues of mesenteric I/R-injured rats. CA neither induced pulmonary and hepatic histological alterations nor affected the parameters of inflammation and apoptosis in sham rats. We conclude that CA alleviated mesenteric I/R-induced pulmonary and hepatic injuries via attenuating apoptosis and inflammation through inhibition of NF-κB and p53 pathways in rats, suggesting the potential role of CA in remote organ ischemic injury protection.