Jibran Ahmad Khan

Case: A 19-year-old man presented with a progressive kyphoscoliosis deformity, pelvic obliquity, neck flexion, and bilateral lower limb contractures. Evaluation showed previously undiagnosed spinal osteoid osteoma. The patient underwent surgical resection with instrumentation of L3-L4. At the 2-year follow-up, the patient showed almost complete resolution of his complex spine deformity and improvement in radiological parameters. Conclusion: The current case described the most severe thoracolumbar deformity secondary to an osteoid osteoma of the lumbar spine in the literature. An intralesional curettage with short, instrumented fusion showed satisfactory outcomes without the need for further deformity correction.

Cardiovascular diseases (CVD) are the primary cause of death and disability around the world. Over the past decades, several conventional model systems based on two-dimensional (3D) monolayer cultures or experimental animals have been adopted to dissect and understand heart diseases in order to develop treatment modalities. However, traditional models exhibit several limitations in recapitulating human-specific key physiological and pathological characteristics, which highlights the necessity of developing physiologically relevant models. In recent years, tissue engineering approaches have been extensively employed to generate revolutionary three-dimensional (3D) cardiac models. In particular, the combined use of various bioengineering strategies and cellular reprogramming approaches has facilitated the development of various models. This review presents an overview of different approaches (bioprinting, scaffolding, and electrospinning) for creating bioengineered cardiac tissue models. Next, a broad survey of recent research related to the modeling of various cardiac diseases is presented. Finally, current challenges and future directions are proposed to foster further developments in the field of cardiac tissue engineering.

Artificial intelligence (AI) is increasingly becoming integral to medical practice, potentially enhancing outcomes in thoracic surgery. AI-driven models have shown significant accuracy in diagnosing non-small-cell lung cancer (NSCLC), predicting lymph node metastasis, and aiding in the efficient extraction of electronic medical record (EMR) data. Moreover, AI applications in robotic-assisted thoracic surgery (RATS) and perioperative management reveal the potential to improve surgical precision, patient safety, and overall care efficiency. Despite these advancements, challenges such as data privacy, biases, and ethical concerns remain. This manuscript explores AI applications, particularly machine learning (ML) and natural language processing (NLP), in thoracic surgery, emphasizing their role in diagnosis and perioperative management. It also provides a comprehensive overview of the current state, benefits, and limitations of AI in thoracic surgery, highlighting future directions in the field.

Artificial Intelligence (AI) is increasingly becoming integral to medical practice, potentially enhancing outcomes in thoracic surgery. AI-driven models have shown significant accuracy in diagnosing non-small cell lung cancer (NSCLC), predicting lymph node metastasis, and aiding in the efficient extraction of electronic medical records (EMR) data. Moreover, AI applications in robotic-assisted thoracic surgery (RATS) and perioperative management reveal potential in improving surgical precision, patient safety, and overall care efficiency. Despite these advancements, challenges such as data privacy, biases, and ethical concerns remain. This manuscript explores AI applications, particularly machine learning (ML) and natural language processing (NLP), in thoracic surgery, emphasizing their role in diagnosis and peri-operative management. It also provides a comprehensive overview of the current state, benefits, and limitations of AI in thoracic surgery, highlighting future directions in the field.

Introduction: Lung cancer remains a global health concern, with non-small cell lung cancer (NSCLC) comprising the majority of cases. Early detection of lung cancer has led to an increased number of cases identified in the earlier stages of NSCLC. This required the revaluation of the NSCLC treatment approaches for early stage NSCLC. Methods: We conducted a comprehensive search using multiple databases to identify relevant studies on treatment modalities for early stage NSCLC. Inclusion criteria prioritized, but were not limited to, clinical trials and meta-analyses on surgical approaches to early stage NSCLC conducted from 2021 onwards. Discussion: Minimally invasive approaches, such as VATS and RATS, along with lung resection techniques, including sublobar resection, have emerged as treatments for early stage NSCLC. Ground-glass opacities (GGOs) have shown prognostic significance, especially when analyzing the consolidation/tumor ratio (CTR). There have also been updates on managing GGOs, including the non-surgical approaches, the extent of lung resection indicated, and the level of lymphadenectomy required. Conclusions: The management of early stage NSCLC requires a further assessment of treatment strategies. This includes understanding the required extent of surgical resection, interpreting the significance of GGOs (specifically GGOs with a high CTR), and evaluating the efficacy of alternative therapies. Customized treatment involving surgical and non-surgical interventions is essential for advancing patient care.

Introduction: Lung cancer remains a global health concern, with non-small cell lung cancer (NSCLC) comprising the majority of cases. Early detection of lung cancer has led to an increased number of cases identified in the earlier stages of NSCLC. This required the revaluation of the NSCLC treatment approaches for early-stage NSCLC. Methods: We conducted a comprehensive search using multiple databases to identify relevant studies on treatment modalities for early-stage NSCLC. Inclusion criteria prioritized but were not limited to, clinical trials and meta-analyses on surgical approaches to early-stage NSCLC conducted from 2021 onwards. Discussion: Minimally invasive approaches, such as VATS and RATS, along with lung resection techniques, including sublobar resection have emerged as treatments for early-stage NSCLC. Ground-glass opacities (GGOs) hve shown prognostic significance, especially when analyzing the consolidation-tumor ratio (CTR). There have also been updates on managing GGOs, including the non-surgical approaches, the extent of lung resection indicated, and the level of lymphadenectomy required. Conclusion: The management of early-stage NSCLC requires further assessment of treatment strategies. This includes understanding the required extent of surgical resection, interpreting the significance of GGOs (specifically GGOs with a high CTR), and evaluating the efficacy of alternative therapies. Customized treatment involving surgical and non-surgical interventions is essential for advancing patient care.

Hepatic cancer is widely regarded as the leading cause of cancer-related mortality worldwide. Despite recent advances in treatment options, the prognosis of liver cancer remains poor. Therefore, there is an urgent need to develop more representative in vitro models of liver cancer for pathophysiology and drug screening studies. Fortunately, an exciting new development for generating liver models in recent years has been the advent of organoid technology. Organoid models hold huge potential as an in vitro research tool because they can recapitulate the spatial architecture of primary liver cancers and maintain the molecular and functional variations of the native tissue counterparts during long-term culture in vitro. This review provides a comprehensive overview and discussion of the establishment and application of liver organoid models in vitro. Bioengineering strategies used to construct organoid models are also discussed. In addition, the clinical potential and other relevant applications of liver organoid models in different functional states are explored. In the end, this review discusses current limitations and future prospects to encourage further development.

Neutrophils are the most abundant of the circulating immune cells and are the first to be recruited to sites of inflammation. Neutrophils are a heterogeneous group of immune cells from which are derived extracellular traps (NETs), reactive oxygen species, cytokines, chemokines, immunomodulatory factors, and alarmins that regulate the recruitment and phenotypes of neutrophils, macrophages, dendritic cells, T cells, and B cells. In addition, cytokine-stimulated neutrophils can express class II major histocompatibility complex and the internal machinery necessary for successful antigen presentation to memory CD4⁺ T cells. This may be relevant in the context of vaccine memory. Neutrophils thus emerge as orchestrators of immune responses that play a key role in determining the outcome of infections, vaccine efficacy, and chronic diseases like autoimmunity and cancer. This review aims to provide a synthesis of current evidence as regards the role of these functions of neutrophils in homeostasis and disease.