A critical predictive marker for anti-PD-1/PD-L1 therapy is programmed death-ligand 1 (PD-L1) expression, assessed by immunohistochemistry (IHC). This paper explores a novel automated framework using deep learning to accurately evaluate PD-L1 expression from whole slide images (WSIs) of non-small cell lung cancer (NSCLC), aiming to improve the precision and consistency of Tumor Proportion Score (TPS) evaluation, which is essential for determining patient eligibility for immunotherapy. Automating TPS evaluation can enhance accuracy and consistency while reducing pathologists' workload. The proposed automated framework encompasses three stages: identifying tumor patches, segmenting tumor areas, and detecting cell nuclei within these areas, followed by estimating the TPS based on the ratio of positively stained to total viable tumor cells. This study utilized a Reference Medicine (Phoenix, Arizona) dataset containing 66 NSCLC tissue samples, adopting a hybrid human-machine approach for annotating extensive WSIs. Patches of size 1000x1000 pixels were generated to train classification models such as EfficientNet, Inception, and Vision Transformer models. Additionally, segmentation performance was evaluated across various UNet and DeepLabV3 architectures, and the pre-trained StarDist model was employed for nuclei detection, replacing traditional watershed techniques. PD-L1 expression was categorized into three levels based on TPS: negative expression (TPS < 1%), low expression (TPS 1-49%), and high expression (TPS ≥ 50%). The Vision Transformer-based model excelled in classification, achieving an F1-score of 97.54%, while the modified DeepLabV3+ model led in segmentation, attaining a Dice Similarity Coefficient of 83.47%. The TPS predicted by the framework closely correlated with the pathologist's TPS at 0.9635, and the framework's three-level classification F1-score was 93.89%. The proposed deep learning framework for automatically evaluating the TPS of PD-L1 expression in NSCLC demonstrated promising performance. This framework presents a potential tool that could produce clinically significant results more efficiently and cost-effectively.

Cyclosporine A (CsA) is widely used as an immunosuppressant in organ transplantation to improve graft survival and prevent tissue rejection. The impact of CsA on cancer progression is highly complex, influenced by the intricate relationship between immunosuppression and malignancy. While individuals with compromised immune systems, notably organ transplant recipients, face an elevated risk of cancer invasion and progression due to immunosuppressive regimens, CsA’s role in either promoting or inhibiting cancer remains elusive. Divergent outcomes from in vitro and in vivo studies suggest suppression of cancer progression under CsA treatment and complicate the translation of findings to clinical scenarios. Despite promising in vitro and in vivo results, the clinical application of CsA in oncology necessitates careful consideration of its toxicity profile in in vivo models, starting at 50–200 mg/kg/d. The divergence between preclinical and clinical findings highlights the need for further research to elucidate the true nature of CsA’s impact on cancer, providing a foundation for more informed and targeted therapeutic approaches.

This review assesses the burden of human papillomavirus (HPV)-related cancers in Bosnia and Herzegovina (BH), aiming to inform strategies for prevention and early detection. Despite the availability of highly effective HPV vaccines and screening programs, HPV-related cancers remain a significant public health burden worldwide. We conducted a comprehensive search of PubMed and GLOBOCAN to identify all available data on HPV prevalence/genotype and HPV-related malignancies in BH, including information on HPV vaccination and cervical cancer screening. A comprehensive literature search revealed limited data on HPV prevalence and HPV-related cancers, as well as the absence of a national HPV vaccination or cervical cancer screening program in BH. In the largest study with available data from BH, HPV prevalence was 43% among women undergoing routine gynecologic exams. HPV-16 was identified as the most common cause of cervical cancer. The HPV prevalence was 50% in head and neck cancer, with HPV-18 being the most prevalent subtype. HPV was detected in 80% of patients with colorectal cancer, and HPV-16 was the most common subtype. Conclusions. HPV-related cancers, particularly cervical cancer, represent a significant public health problem in BH. Implementation of a national HPV vaccination program, along with organized cervical cancer screening is essential to reduce HPV-related morbidity and mortality. Addressing systemic challenges, such as establishing a comprehensive cancer registry, is essential for effective HPV prevention and control. Raising public awareness about HPV infection, its consequences, and the importance of prevention is essential for vaccine acceptance and promoting healthy behaviors. By investing in HPV prevention, BH can significantly improve the health and well-being of its population, particularly women.

Simple Summary This study investigates lung cancer detection by combining metabolomics and advanced machine learning to identify small cell lung cancer (SCLC) with high accuracy. We analyzed 461 serum samples from publicly available data to create a stacking-based ensemble model that can distinguish between SCLC, non-small cell lung cancer (NSCLC), and healthy controls. The model has 85.03% accuracy in multi-class classification and 88.19% accuracy in binary classification (SCLC vs. NSCLC). This innovation relies on sophisticated feature selection techniques to identify significant metabolites, particularly positive ions. SHAP analysis identifies key predictors such as benzoic acid, DL-lactate, and L-arginine, shedding new light on cancer metabolism. This non-invasive approach presents a promising alternative to traditional diagnostic methods, with the potential to transform early lung cancer detection. By combining metabolomics and machine learning, the study paves the way for faster, more accurate, and patient-friendly cancer diagnostics, potentially improving treatment outcomes and survival rates.

Abstract Duplication of the vermiform appendix is a rare anomaly observed in patients undergoing appendectomy. A 27-month-old male toddler presented with a 9-day history of abdominal pain, vomiting, and diarrhea, progressing to an acute abdomen with signs of severe peritonitis. Intraoperative findings revealed a periappendicular infiltrate from a perforated vermiform appendix of the tenia coli type. A second, inflamed appendix was incidentally discovered in its typical location during the procedure. Vermiform appendix duplication presents a clinical challenge due to its rarity and potential for complications. According to the Cave–Wallbridge classification, this case represents Type B2, or the tenia coli variant, characterized by a perforated appendix originating at the tenia coli convergence and a smaller, secondary appendix in a retrocecal position. This case emphasizes the importance of thorough distal and proximal exploration during initial appendectomy when this anomaly is suspected, particularly in cases of Type B2.

Neutropenic enterocolitis (NE) is a potentially life-threatening condition, primarily affecting neutropenic patients with hematologic malignancies. The clinical manifestations of NE in patients receiving antineoplastic drugs range from fever, diarrhea, nausea, vomiting, and abdominal pain to intestinal perforation and shock. We report the case of a 12-year-old boy with acute myelogenous leukemia, undergoing chemotherapy, who presented with an atypical case of NE. Due to numerous jejunal perforations and severe rectal bleeding, he experienced abdominal distension without any accompanying tenderness and the unexpected rapid onset of shock. Surgery was performed, and his postoperative course was uneventful. However, seven days later, Pseudomonas aeruginosa-induced sepsis made his condition rapidly worse due to severe neutropenia and thrombocytopenia. Despite intensive supportive therapy, the patient unfortunately passed away. NE remains a life-threatening complication in pediatric immunosuppressed leukemic patients. A high index of suspicion, prompt diagnosis, aggressive treatment with broad-spectrum antibiotics, and correction of fluid-electrolyte imbalances are crucial in reducing morbidity and mortality.

Chylothorax represents the accumulation of chyle in the pleural cavity due to leakage from the thoracic duct or its tributaries. Intraoperative intrathoracic lymphatic injury is a common cause, but it can also occur on its own. Management of chylothorax involves both medical therapy and, in some cases, surgery for postoperative patients and those who haven't responded to medical therapy. We describe a case of a one-month-old female infant with right-sided chylothorax following primary esophageal atresia repair, who underwent successful thoracic duct ligation by open thoracotomy after unsuccessful medical treatment. Minimally invasive radiology is now the standard treatment for traumatic chylothorax because it is safe and effective. However, surgical ligation of the thoracic duct remains an effective option for treating high-output or recurring chylothorax in countries with limited resources.