The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding of the brain, unlocking new possibilities in research, diagnosis, and therapy. This review explores how AI’s cutting-edge algorithms—ranging from deep learning to neuromorphic computing—are revolutionizing neuroscience by enabling the analysis of complex neural datasets, from neuroimaging and electrophysiology to genomic profiling. These advancements are transforming the early detection of neurological disorders, enhancing brain–computer interfaces, and driving personalized medicine, paving the way for more precise and adaptive treatments. Beyond applications, neuroscience itself has inspired AI innovations, with neural architectures and brain-like processes shaping advances in learning algorithms and explainable models. This bidirectional exchange has fueled breakthroughs such as dynamic connectivity mapping, real-time neural decoding, and closed-loop brain–computer systems that adaptively respond to neural states. However, challenges persist, including issues of data integration, ethical considerations, and the “black-box” nature of many AI systems, underscoring the need for transparent, equitable, and interdisciplinary approaches. By synthesizing the latest breakthroughs and identifying future opportunities, this review charts a path forward for the integration of AI and neuroscience. From harnessing multimodal data to enabling cognitive augmentation, the fusion of these fields is not just transforming brain science, it is reimagining human potential. This partnership promises a future where the mysteries of the brain are unlocked, offering unprecedented advancements in healthcare, technology, and beyond.

This review aims to address the significant challenges of treating central nervous system (CNS) disorders such as neurodegenerative diseases, strokes, spinal cord injuries, and brain tumors. These disorders are difficult to manage due to the complexity of disease mechanisms and the protective blood–brain barrier (BBB), which restricts drug delivery. Recent advancements in nanoparticle (NP) technologies offer promising solutions, with potential applications in drug delivery, neuroprotection, and neuroregeneration. By examining current research, we explore how NPs can cross the BBB, deliver medications directly to targeted CNS regions, and enhance both diagnostics and treatment. Key NP strategies, such as passive targeting, receptor-mediated transport, and stimuli-responsive systems, demonstrate encouraging results. Studies show that NPs may improve drug delivery, minimize side effects, and increase therapeutic effectiveness in models of Alzheimer’s, Parkinson’s, stroke, and glioblastoma. NP technologies thus represent a promising approach for CNS disorder management, combining drug delivery and diagnostic capabilities to enable more precise and effective treatments that could significantly benefit patient outcomes.

This review offers an in-depth examination of amyotrophic lateral sclerosis (ALS), addressing its epidemiology, pathophysiology, clinical presentation, diagnostic techniques, and current as well as emerging treatments. The purpose is to condense key findings and illustrate the complexity of ALS, which is shaped by both genetic and environmental influences. We reviewed the literature to discuss recent advancements in understanding molecular mechanisms such as protein misfolding, mitochondrial dysfunction, oxidative stress, and axonal transport defects, which are critical for identifying potential therapeutic targets. Significant progress has been made in refining diagnostic criteria and identifying biomarkers, leading to earlier and more precise diagnoses. Although current drug treatments provide some benefits, there is a clear need for more effective therapies. Emerging treatments, such as gene therapy and stem cell therapy, show potential in modifying disease progression and improving the quality of life for ALS patients. The review emphasizes the importance of continued research to address challenges such as disease variability and the limited effectiveness of existing treatments. Future research should concentrate on further exploring the molecular foundations of ALS and developing new therapeutic approaches. The implications for clinical practice include ensuring the accessibility of new treatments and that healthcare systems are equipped to support ongoing research and patient care.

Biomarkers in colorectal cancer (CRC) are of great interest in the current literature due to improvements in techniques such as liquid biopsy and next-generation sequencing (NGS). However, screening methods vary globally, with multi-target stool DNA (mt-sDNA) predominantly used in the USA and, more recently, the Cologuard Plus; biomarkers such as the Galectins family and septins show promise in early detection. Gut microbiome assessments, such as Fusobacterium nucleatum, are under intense exploration. Diagnostic tests, such as circulating DNA analysis via NGS, exhibit effectiveness and are being increasingly adopted. Circulating tumor cells emerge as potential alternatives to traditional methods in terms of diagnosis and prognosis. Predictive biomarkers are well established in guidelines; nonetheless, with the aid of machine learning and artificial intelligence, these biomarkers may be improved. This review critically explores the actual dynamic landscape of CRC biomarkers and future, promising biomarkers involved in screening, diagnosis, and prognosis.

Because almost one fourth of patients with rectal adenocarcinoma (RC) achieve pathological complete response (pCR) after neoadjuvant chemoradiation therapy (CRT), having significantly higher survival rates than those without pCR, the assessment of pCR represents a highly important challenge nowadays. Moreover, recent studies revealed that organ-sparing approaches could represent a reasonable alternative to radical surgery (RS) in patients with pCR, achieving similar long-term outcomes with lower morbidity rates and improved quality of life. Unfortunately, the decision of a rectum-sparing approach should be based only on clinical, endoscopic (with or without biopsy) and radiological methods, that must accurately predict the pCR after neoadjuvant CRT, in the absence of the pathological examination of the RS specimen. Thus, a surrogate parameter called clinical complete response (cCR) emerged, to assess the results of neoadjuvant CRT. The evolving accuracy of recent endoscopic and imaging methods in assessment of cCR and their predictive value for estimation of pCR achievement are presented. The usefulness of combining the results of these evaluation methods (resulting in the development of few nomograms) for a more accurate estimation of pCR, as well as the predictive factors for pCR achievement are also debated. Moreover, the changing landscape of therapeutic approaches based on cCR assessment is discussed, emphasizing the advantages and pitfalls of rectum-sparing approaches, compared to RS. Because there are no reliable methods to estimate with 100% accuracy the pCR, the only way to decrease as much as possible the risk of misleading treatment choices is the multidisciplinary team-based decision.

CD30, also known as TNFRSF8 (tumor necrosis factor receptor superfamily member 8), is a protein receptor that is heavily glycosylated inside the Golgi apparatus, as well as a tumor marker that is found on the surface of specific cells in the body, including certain immune cells and cancer ones. This review aims to shed light on the critical importance of CD30, from its emergence in the cell to its position in diagnosing various diseases, including Hodgkin lymphoma, where it is expressed on Hodgkin and Reed–Sternberg cells, as well as embryonal carcinoma, anaplastic large cell lymphoma (ALCL), and cutaneous T-cell lymphoma (CTCL). In addition to its role in positive diagnosis, targeting CD30 has been a promising approach treating CD30-positive lymphomas, and there is ongoing research into the potential use of CD30-targeted therapies for autoimmune disorders. We aim to elaborate on CD30’s roles as a tumor marker, supporting thus the hypothesis that this receptor might be the aim of cytostatic treatment.