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Machine learning in onco-pharmacogenomics: a path to precision medicine with many challenges.

Over the past two decades, Next-Generation Sequencing (NGS) has revolutionized the approach to cancer research. Applications of NGS include the identification of tumor specific alterations that can influence tumor pathobiology and also impact diagnosis, prognosis and therapeutic options. Pharmacogenomics (PGx) studies the role of inheritance of individual genetic patterns in drug response and has taken advantage of NGS technology as it provides access to high-throughput data that can, however, be difficult to manage. Machine learning (ML) has recently been used in the life sciences to discover

How to Choose the Right Treatment for Membranous Nephropathy

Membranous nephropathy is an autoimmune disease affecting the glomeruli and is one of the most common causes of nephrotic syndrome. In the absence of any therapy, 35% of patients develop end-stage renal disease. The discovery of autoantibodies such as phospholipase A2 receptor 1, antithrombospondin and neural epidermal growth factor-like 1 protein has greatly helped us to understand the pathogenesis and enable the diagnosis of this disease and to guide its treatment. Depending on the complications of nephrotic syndrome, patients with this disease receive supportive treatment with diuretics, AC

Estimating survival in patients with operable skeletal metastases: an application of a bayesian belief network.

BackgroundAccurate estimations of life expectancy are important in the management of patients with metastatic cancer affecting the extremities, and help set patient, family, and physician expectations. Clinically, the decision whether to operate on patients with skeletal metastases, as well as the choice of surgical procedure, are predicated on an individual patient's estimated survival. Currently, there are no reliable methods for estimating survival in this patient population. Bayesian classification, which includes bayesian belief network (BBN) modeling, is a statistical method that explore

Oncogenic influences of neurotrophin receptors: Shedding light on Trk biology.

During critical stages of neurodevelopment, tropomyosin receptor kinase receptors, encoded by NTRK genes, exhibit temporally driven differential peaks of expression to properly guide the establishment of the peripheral and central nervous systems. In addition, these neuronal systems exhibit non-canonical regulation of surrounding tissues, impacting organogenesis, homeostasis, plasticity, and regeneration. The same processes that guide neurodevelopment, such as differentiation, plasticity, and neuronal survival, are also hijacked in cancer, making the NTRK family an ideal candidate to study. Th

Искусственный интеллект основывается на достижениях в области наномедицины для лечения мозговых расстройств: обновленный обзор повествования.

Наномедицина - это наномасштабные, биосопоставимые материалы, которые предлагают перспективные альтернативы традиционным методам лечения расстройств мозга. Технологические достижения в области искусственного интеллекта (АИ), в частности машинного обучения (МЛ) и глубокого обучения (ДЛ), трансформируют область наномедицины путем совершенствования диагностики заболеваний, биомаркировки, прогнозирования и мониторинга заболеваний, целевых поставок наркотиков и терапевтического вмешательства, а также содействия расчетным и методологическим разработкам. Эти успехи могут быть достигнуты за счет анали

Revolutionizing hematological disorder diagnosis: unraveling the role of artificial intelligence.

The integration of artificial intelligence (AI) into medical diagnostics is transforming the landscape of healthcare, particularly in hematology. AI technologies, leveraging advanced machine learning algorithms and big data analytics, are revolutionizing the diagnosis of hematological disorders such as anemia, leukemia, and lymphoma. This review explores how AI enhances diagnostic accuracy, efficiency, and patient outcomes by processing complex datasets and identifying patterns beyond human capability. AI-driven advancements in hematology include innovations in image analysis, genomic data int

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… Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) Networks are used for analyzing time-series data and sequential information. In hematology, these models can track changes in patient data over time to predict disease progression or treatment responses. …

Unlocking the therapeutic potential of cellular mechanobiology.

Mechanobiology is a rapidly advancing field at the intersection of biology, physics, and engineering that reveals how mechanical forces shape cellular behavior, tissue architecture, and disease progression. By elucidating how cells sense and transduce mechanical cues, mechanobiology has fundamentally advanced our understanding of processes ranging from migration and differentiation to immune responses and tissue remodeling. These advances have driven the development of innovative biophysical tools and engineered biomaterials that enable precise modulation of the cellular microenvironment. Tran

Accuracy of artificial intelligence in detecting tumor bone metastases: a systematic review and meta-analysis.

BackgroundBone metastases (BM) represent a prevalent complication of tumors. Early and accurate diagnosis, however, is a significant hurdle for radiologists. Recently, artificial intelligence (AI) has emerged as a valuable tool to assist radiologists in the detection of BM. This meta-analysis was undertaken to evaluate the AI diagnostic accuracy for BM.MethodsTwo reviewers performed an exhaustive search of several databases, including Wei Pu (VIP) database, China National Knowledge Infrastructure (CNKI), Web of Science, Cochrane Library, Ovid-Embase, Ovid-Medline, Wan Fang database, and China

Окисляющие молекулярные сигнатуры в неизлечимых заболеваниях: систематический обзор комплексных подходов к машинному обучению и системной биологии.

Окисляющий стресс является одним из основных факторов патогенеза иммунных заболеваний в результате его воздействия на клеточный метаболизм, митохондриальную функцию, иммунную сигнализацию и воспалительную травму тканей. Разрушение гомеостазиса способствует метаболическому перепрограммированию и постоянной активации врожденной и адаптивной иммунной реакции, что способствует прогрессированию заболеваний через многочисленные подстрекательские и аутоиммунные расстройства. Последние достижения в области высокопроизводительных молекулярных технологий привели к созданию крупномасштабных многомерных н

Inflammation and Cancer: Molecular Mechanisms and Therapeutic Targets.

Inflammation is a core pathological factor regulating tumor initiation, progression, and therapeutic resistance, and elucidating its molecular crosstalk with tumors is crucial for developing effective clinical therapies. Internal drivers of inflammation-tumor transformation include genomic disorder, epigenetic memory, mitochondrial stress, and metabolic reprogramming, which synergistically initiate carcinogenesis. External factors amplifying tumor progression cover immune dysfunction, stromal fibrosis, microbial dysbiosis, vascular neoplasia, and neurotoxicity, collectively accelerating tumor

Neurotransmitters in cancer: how receptor signaling and posttranslational modifications modulate tumor progression and offer new therapeutic targets.

Recent studies highlight the multifaceted roles of neurotransmitters in tumor immunomodulation, offering novel avenues for increasing therapeutic efficacy. These signaling molecules are classified into cholinergic agents, monoamines, amino acids, and peptides and regulate tumorigenesis, metastasis, and immune evasion via autocrine/paracrine pathways and receptor-mediated interactions. Notably, neurotransmitters influence tumor cell proliferation, apoptosis, and immune cell activity by modulating intracellular signaling cascades through posttranslational modifications (serotonylation and dopami

Survival and Functional Outcomes in Patients with Thoracic Spinal Epidural Lymphoma with Spinal Cord Compromise: Three Cases Requiring Emergent Surgical Management.

Spinal epidural lymphoma is a rare pathological entity that usually responds well to chemotherapy. However, it occasionally requires immediate surgical treatment for progressive neurological symptoms caused by a bulky epidural mass and bone destruction. In the management of spinal epidural lymphoma, the role of surgical interventions has not yet been fully defined, and few reports on long-term functional outcomes are available. We report 3 cases of thoracic spinal epidural lymphoma that required emergent surgical management for neural decompression and were followed postoperatively over 2 year

The Applications of Machine Learning in the Management of Patients Undergoing Stem Cell Transplantation: Are We Ready?

Hematopoietic stem cell transplantation (HSCT) is a life-saving therapy for hematologic malignancies, such as leukemia and lymphoma and other severe conditions but is associated with significant risks, including graft versus host disease (GVHD), relapse, and treatment-related mortality. The increasing complexity of clinical, genomic, and biomarker data has spurred interest in machine learning (ML), which has emerged as a transformative tool to enhance decision-making and optimize outcomes in HSCT. This review examines the applications of ML in HSCT, focusing on donor selection, conditioning re

Объединение АИ, вакцин РНК и ЦАР-Т ячеек для индивидуального лечения.

Онкология претерпевает глубокие преобразования, вызванные конвергенцией искусственного интеллекта (AI), вакцин на основе РНК и химерика антигенного рецептора Т-клеток (CAR-T). В индивидуальном порядке эти технологии позволяют диагностировать рак, лечить и стратифицировать пациента. Подходы, основанные на принципе АИ, способствуют обнаружению наркотиков, оптимизации клинических опытных разработок и создают возможности для индивидуализированного терапевтического принятия решений. Вакцины RNA обеспечивают гибкую платформу для кодирования неонантигенов опухоли, в то время как CAR-T-терапия дает во

Карта знаний об искусственном интеллекте в нейродегенеративных болезнях: исследование библиометрии и визуализации на протяжении десяти лет.

По мере увеличения заболеваемости нейродегенеративными заболеваниями соответствующие исследования ИИ становятся все более и более передовыми. В этом исследовании мы анализируем литературу в этой области за последнее десятилетие с помощью методов библиометрии и визуализации с целью разработки известных журналов, институтов, авторов и стран в этой области и анализа ключевых слов, с тем чтобы предположить возможные будущие тенденции в области исследований. МЕТОДЫ: Извлечено наше исследование 1,921 соответствующие публикации, охватывающие 2015-2025 из базы данных " Web of Science Core Collect

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… The other article is about the development of a comprehensive framework utilizing multimodal recurrent neural networks with the integration of longitudinal multidomain data. Using this framework, the accuracy of predictive models for MCI to AD conversion was improved ( Lee et al., 2019 ). …

Association between miR-182 rs76481776 Polymorphism and Antidepressant Treatment Response in Patients with Depression.

ObjectiveThe efficacy of antidepressants is influenced by a combination of genetic, individual, and environmental factors. This study aimed to investigate the association between the miR-182 rs76481776 polymorphism and the response to antidepressant treatment in major depressive disorder (MDD) patients, and its underlying molecular mechanisms.MethodsThis study enrolled 180 MDD patients and 180 healthy controls. The rs76481776 genotype was determined using TaqMan-based qPCR. The severity of depression and treatment response were assessed using the Hamilton Depression Rating Scale (HAMD). The ex

Emerging therapeutic strategies in glioblastsoma: drug repurposing, mechanisms of resistance, precision medicine, and technological innovations.

Glioblastoma (GBM) is an aggressive Grade IV brain tumor with a poor prognosis. It results from genetic mutations, epigenetic changes, and factors within the tumor microenvironment (TME). Traditional treatments like surgery, radiotherapy, and chemotherapy provide limited survival benefits due to the tumor's heterogeneity and resistance mechanisms. This review examines novel approaches for treating GBM, focusing on repurposing existing medications such as antipsychotics, antidepressants, and statins for their potential anti-GBM effects. Advances in molecular profiling, including next-generation

Регулирование на основе Virobiome микробиота-гут-мозговой оси сигнализирует и нейроиммунный гомеостаз.

Ось человеческого кишечника все чаще признается как сложная двунаправленная коммуникационная система, объединяющая микробные, нейронные, эндокринные и иммунные сети, формирующие неврологическое здоровье. Хотя бактериальный вклад в этот диалог получил широкую окраску, вирусный компонент кишечной экосистемы, виром, стал важным компонентом, связанным с физиологическим регулированием принимающей стороны. В этом обзоре обобщены данные, свидетельствующие о том, что бактериофаги и эукариотические вирусы могут способствовать микробному и иммунальному гомеостазу и оказывать влияние на сигнализацию вдол

The updated landscape of tumor microenvironment and drug repurposing.

Accumulating evidence shows that cellular and acellular components in tumor microenvironment (TME) can reprogram tumor initiation, growth, invasion, metastasis, and response to therapies. Cancer research and treatment have switched from a cancer-centric model to a TME-centric one, considering the increasing significance of TME in cancer biology. Nonetheless, the clinical efficacy of therapeutic strategies targeting TME, especially the specific cells or pathways of TME, remains unsatisfactory. Classifying the chemopathological characteristics of TME and crosstalk among one another can greatly b

Библиометрический анализ кишечного микробиота и демиелионирующие заболевания, в частности множественный склероз, с тех пор 2014.

Ось кишечника (GBA) представляет собой сложную двунаправленную сеть связи, соединяющую центральную нервную систему (CNS) и желудочно-кишечную систему. Наше исследование было нацелено на изучение взаимосвязи между кишечной микробиотой и демиелинирующими заболеваниями с библиометрической точки зрения с уделением особого внимания исследованиям с тех пор. 2014. МЕТОДЫ: Был проведен всесторонний поиск на базе " Web of Science Core Collection " (WoSCC) с целью поиска исследований, посвященных кишечной микробиоте и демиелионирующим заболеваниям, с уделением особого внимания публикациям, под