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Машинное обучение для интерпретации серума протеина и иммунофиксации электрофореза в мультипликационной миеломе: обзор скопирования.

Фон: Для диагностики множественной миэломы (ММ) необходимы электрофорез сухого белка (СФЭ) и электрофорез иммунофиксации (ИФЕ). Методы машинного обучения (ML) стали потенциальным подходом к автоматизации процесса интерпретации электрофореза в целях повышения эффективности диагностики и увеличения времени перехода. В ходе этого аналитического обзора были выявлены нынешние виды применения ML в диагностике и классификации MM с уделением особого внимания автоматизированному толкованию ОИН и IFE. Методы: базы данных PubMed, Web of Science и Scopus были подвергнуты обыску в соответствии с руководящи

Пространственные омики нейроинфламмации: осмысления заболеваний мозга.

Нейроинфламмация является общей патологической особенностью различных заболеваний мозга, однако подстрекательская активность редко распределяется равномерно по заболевшим тканям. Вместо этого микроглии, астроциты, проникающие в иммунные клетки и подстрекательские посредники, часто организуются вокруг конкретных патологических структур, включая амилоидные таблетки, демиелинированные поражающие ободья, ишемические границы, некротические области опухоли и белые отсеки периваскулярной материи. Хотя в рамках одноклеточных подходов, основанных на оптовых и диссоциационных подходах, было определено м

Evaluating the Accuracy and Efficiency of Imaging Modalities in Guiding Ablation for Metastatic Spinal Column Tumors: A Systematic Review.

Background/objectivesSpinal metastases are a frequent and serious complication in cancer patients, often causing severe pain, instability, and neurological deficits. Thermal ablation techniques such as radiofrequency ablation (RFA), microwave ablation (MWA), and cryoablation (CA) have emerged as minimally invasive treatments. These techniques rely on precise imaging guidance to effectively target lesions while minimizing complications. This systematic review aims to compare the efficacy of different imaging modalities-computed tomography (CT), magnetic resonance imaging (MRI), fluoroscopy, and

Redefining Breast Cancer Care by Harnessing Computational Drug Repositioning.

Breast cancer faces significant therapeutic challenges, particularly for triple-negative breast cancer (TNBC), due to limited targeted therapies and drug resistance. Drug repositioning leverages existing safety and pharmacokinetic data to expedite the identification of new indications with cost-effective benefits compared to de novo drug discovery. In this critical narrative review, we examine recent advances in computational repositioning strategies for breast cancer, focusing on network-based methods, computer-aided drug design, artificial intelligence and machine learning, transcriptomic si

Neuroimmune crosstalk and its impact on cancer therapy and research.

Cancer is a major health problem as it is the first or second leading cause of death worldwide. The global cancer burden is expected to rise 47% relative to 2020 cancer incidence. Recently, the fields of neuroscience, neuroimmunology and oncology have elaborated the neuroimmune crosstalk role in tumor initiation, invasion, progression, and metastases. The nervous system exerts a broad impact on the tumor microenvironment by interacting with a complex network of cells such as stromal, endothelial, malignant cells and immune cells. This communication modulates cancer proliferation, invasion, met

Genome-scale analysis to identify prognostic markers in patients with early-stage pancreatic ductal adenocarcinoma after pancreaticoduodenectomy.

BackgroundMolecular analysis is a promising source of clinically useful prognostic biomarkers. The aim of this investigation was to identify prognostic biomarkers for patients with early-stage pancreatic ductal adenocarcinoma (PDAC) after pancreaticoduodenectomy.MethodsAn RNA sequencing dataset of PDAC was obtained from The Cancer Genome Atlas. Survival analysis and weighted gene co-expression network analysis were used to investigate the prognostic markers of early-stage PDAC after pancreaticoduodenectomy.ResultsUsing whole genome expression level screening, we identified 1,238 markers that w

Artificial Intelligence in the Management of Hereditary and Acquired Hemophilia: From Genomics to Treatment Optimization.

Hemophilia, an X-linked bleeding disorder, is characterized by a deficiency in coagulation factors. It manifests as spontaneous bleeding, leading to severe complications if not properly managed. In contrast, acquired hemophilia is an autoimmune condition marked by the development of inhibitory antibodies against coagulation factors. Both forms present significant diagnostic and therapeutic challenges, highlighting the need for advanced genetic, molecular, laboratory, and clinical assessments. Recent advances in artificial intelligence have opened new avenues for the management of hemophilia. M

Radiomics-based classification of medication-related osteonecrosis of the jaw using panoramic radiographs.

OBJECTIVES: Medication-related osteonecrosis of the jaw (MRONJ) caused by bone resorption inhibitors is difficult to treat and reduces the patient's quality of life. We aimed to classify the likelihood of MRONJ development using panoramic radiographs taken prior to bone resorption inhibitor administration. METHODS: We included patients who underwent panoramic radiographic evaluation at Hiroshima University Hospital prior to bone resorption inhibitor administration. Thirty-two patients with MRON of the mandible (16 men and 16 women) and 57 without MRONJ (23 men and 34 women) were selected. The

A real-world analysis of FDA Adverse Event Reporting System (FAERS) events for liposomal and conventional doxorubicins.

The clinical application of conventional doxorubicin (CDOX) was constrained by its side effects. Liposomal doxorubicin was developed to mitigate these limitations, showing improved toxicity profiles. However, the adverse events associated with liposomal doxorubicin and CDOX have not yet been comprehensively evaluated in clinical settings. The FAERS data from January 2004 to December 2022 were collected to analyze the adverse events of liposomal doxorubicin and CDOX. Disproportionate analysis and Bayesian analysis were employed to quantify this association. Our analysis incorporated 68,803 adve

Cell-based immunotherapy of glioblastoma multiforme.

Glioblastoma multiforme (GBM) is the most aggressive and lethal primary glial brain tumor. It has an unfavorable prognosis and relatively ineffective treatment protocols, with the median survival of patients being ~15 months. Tumor resistance to treatment is associated with its cancer stem cells (CSCs). At present, there is no medication or technologies that have the ability to completely eradicate CSCs, and immunotherapy (IT) is only able to prolong the patient's life. The present review aimed to investigate systemic solutions for issues associated with immunosuppression, such as ineffective

Цифровой дистанционный мониторинг людей с множественным склерозом.

ВВЕДЕНИЕ: Множественный склероз (MS) является хроническим нейродегенеративным заболеванием, которое затрагивает более 2,8 млн. человек во всем мире и приводит к значительным симптомам моторного и немоторного происхождения. Эффективный мониторинг заболеваний имеет решающее значение для улучшения результатов лечения пациентов, но часто затрудняется ограниченностью редких клинических оценок. Цифровые средства дистанционного мониторинга с использованием больших данных, и МА открывает новые возможности для отслеживания симптомов в режиме реального времени и выявления развития заболеваний. МЕТОДЫ: В

Machine Learning for Differentiating Essential Tremor: A Scoping Review.

BackgroundEssential tremor (ET) is the most common movement disorder, affecting ~6% of adults over 65 [1]. Differentiating ET from other tremors remains clinically challenging due to overlapping features and variable presentation. Artificial intelligence (AI), particularly machine learning (ML), has emerged a potential tool to support neurologists by enhancing pattern recognition and complementing traditional assessments in complex cases. This is the first scoping review examining ML's potential role in distinguishing essential tremor from other tremor types.MethodsA systematic, scoping search

Development of Anticancer Peptides Using Artificial Intelligence and Combinational Therapy for Cancer Therapeutics.

Cancer is a group of diseases causing abnormal cell growth, altering the genome, and invading or spreading to other parts of the body. Among therapeutic peptide drugs, anticancer peptides (ACPs) have been considered to target and kill cancer cells because cancer cells have unique characteristics such as a high negative charge and abundance of microvilli in the cell membrane when compared to a normal cell. ACPs have several advantages, such as high specificity, cost-effectiveness, low immunogenicity, minimal toxicity, and high tolerance under normal physiological conditions. However, the develo

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… Long short-term memory (LSTM) [ 25 ], convolutional neural network (CNN) [ 63 ], CNN-recurrent neural network (RNN) [ 63 ], and attention [ 64 ] structures are used as DL models. CNN is a neural network architecture for DL that learns directly from data [ 138 ]. … Generating Text with recurrent neural networks Proceedings of the 28th International Conference on Machine Learning (ICML-11) Bellevue, WA, USA 28 June–2 July 2011 1017 1024 140. Abiodun O.I. Jantan A. Omolara A.E. Dada K.V. Mohamed N.A. Arshad H. …

Advancing Medulloblastoma Treatment: Molecular Mechanisms, Drug Repurposing, and Precision Therapies.

Medulloblastomas are the most common malignant pediatric brain tumors, representing approximately 20% of the central nervous system cancers in children. These tumors are highly heterogeneous and classified into four molecular subgroups-WNT, SHH, Group 3, and Group 4-each with distinct genetic and epigenetic profiles that influence tumor behavior, therapeutic response, and patient outcomes. Advances in molecular diagnostics have improved the subclassification of medulloblastomas, yet treatment outcomes for high-risk subtypes, particularly Group 3, remain poor, with current modalities often asso

Therapeutic Targeting of Cancer Stem Cells in Human Glioblastoma by Manipulating the Renin-Angiotensin System.

Patients with glioblastoma (GB), a highly aggressive brain tumor, have a median survival of 14.6 months following neurosurgical resection and adjuvant chemoradiotherapy. Quiescent GB cancer stem cells (CSCs) invariably cause local recurrence. These GB CSCs can be identified by embryonic stem cell markers, express components of the renin-angiotensin system (RAS) and are associated with circulating CSCs. Despite the presence of circulating CSCs, GB patients rarely develop distant metastasis outside the central nervous system. This paper reviews the current literature on GB growth inhibition in r

Federated Computing in Orthopaedic Surgery: A Paradigm Shift in Collaborative Multicenter Research.

➢ Multicenter studies remain rare in orthopaedics (9.9% of recent publications) due to regulatory complexity, restrictive data-sharing policies, and administrative delays, despite their proven value in generating robust, generalizable evidence. ➢ Federated computing (FC) brings analytic code to each institution's data and returns only encrypted, aggregated results. This preserves patient privacy, maintains institutional control, and streamlines compliance by reducing or eliminating the need for complex data-use agreements. ➢ Extensive applications in other medical fields show that FC can match

PET Molecular Imaging: A Holistic Review of Current Practice and Emerging Perspectives for Diagnosis, Therapeutic Evaluation and Prognosis in Clinical Oncology.

PET/CT molecular imaging has been imposed in clinical oncological practice over the past 20 years, driven by its two well-grounded foundations: quantification and radiolabeled molecular probe vectorization. From basic visual interpretation to more sophisticated full kinetic modeling, PET technology provides a unique opportunity to characterize various biological processes with different levels of analysis. In clinical practice, many efforts have been made during the last two decades to standardize image analyses at the international level, but advanced metrics are still under use in practice.

МикроРНК-219 в центральной нервной системе: потенциальный тераностический подход.

Несмотря на недавние терапевтические достижения в области неврологических расстройств, лечебная терапия во многих случаях остается серьезной проблемой. Несмотря на то, что в последние годы мы стали свидетелями развития генной терапии из различных терапевтических подходов, влияющих на патофизиологические механизмы, существуют интригующие аспекты, касающиеся эффективности, безопасности и механизма действий генной терапии. Микрорибонуклеиновая кислота (микроRNA-miRNA) в качестве основного генного регулятора регулирует рибонуклеиновую кислоту курьера (mRNA) путем прямого соединения через 3'неперев

Репрессии на цикле синергии со стороны HDAC/EZH2 H3K27-altered диффузная средняя глиома.

Diffuse midline glioma (DMG) — агрессивная хитрость под воздействием H3K27M онкохистоуна, приводящая к глобальному эпигенетическому регулированию и ограниченной эффективности одноагентной эпигенетической терапии. Ранее мы наблюдали клиническую выгоду от ингибитора HDAC/EZH2, но механистическая основа была неясной. Для принятия ответных мер в связи с наркотиками и проведения функциональных анализов использовалась группа культур ДИМ-глиомы стволовых клеток (ГНК) от опухолей головного мозга и спинного мозга, при этом репрезентативные модели были дополнительно проанализированы на предмет транскрип

Стриато-лимбическая и лобная дисфункция, лежащая в основе дисбаланса в мотивации вознаграждения и когнитивном контроле в навязанном сексуальном поведении: нейроимационный метаанализ.

СТРУКТУРА: Навязчивое сексуальное расстройство (CSBD) связано с неконтролируемыми сексуальными желаниями и поведением, вызывающими расстройство или функциональные расстройства. Несмотря на то, что он классифицируется как расстройство контроля импульсов в МКБ-11, его нейробиологическая основа и когнитивные недостатки по-прежнему плохо понимаются. Достижения в крупных языковых моделях (МЛМ) позволяют производить масштабируемую обработку литературы и синтез мультимодальных нейроимаций. В этом исследовании использовались основанные на LLM рамки для метаанализа на основе координат и функционального