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Cancer evolution: mathematical models and computational inference.

Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilisti

Оценка роли объемной информации о мозге в множестве склерозов.

Множественный склероз — хроническое аутоиммунное заболевание, которое влияет на центральную нервную систему. Понимание множественных склерозов и выявление связанных с ними структур мозга имеют решающее значение для индивидуализированных решений о лечении. В морфометрии, основанной на деформации, используется анатомическая магнитная резонансная визуализация для количественной оценки объемных изменений мозга на уровне вокселя, что дает представление о том, как каждая область мозга способствует клинической прогрессии в отношении нейродегенерации. Используя такие данные на уровне воксела, полученн

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… The feature importance scores in RF-Imp are generated as the average difference in out-of-bag prediction error across decision trees when the corresponding feature is permuted. In principle, the bagging and feature subsets for each decision tree share some similarities with minipatch ensembling. … Incorporating shuffled feature values onto already-trained decision trees can create large erroneous changes to predictions that would otherwise have fine performance if retrained without the feature. This may introduce unnecessary instability to RF-Imp when compared with LOCO-MP. …

Гут микробиота и ее влияние на ось Гут-Брэйна в сравнении с пациентами, страдающими химиотерапией, и данными о безраковых методах контроля в вычислительной перспективе рака груди.

Рак груди (БК) по-прежнему является одной из основных причин связанных с раком заболеваний и смертности среди женщин во всем мире. Традиционное лечение включает хирургию, радиацию, гормональную терапию и химиотерапию, но эти методы часто сталкиваются с трудностями из - за изменчивости реакции пациента и неблагоприятных последствий. В рамках этого исследования изучалась взаимосвязь между разнообразием кишечного микробиома, составом общины и анализом путей развития у женщин, проходящих химиотерапию в Британской Колумбии (Время лечения - DT), по сравнению с мерами по борьбе с раком (КФК). Использ

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… An ensemble of decision trees is used in the machine learning method known as “random forest classification” to generate predictions. A majority vote or average of the individual guesses determines the predictions made individually by each tree in the forest. …

Levels of active tyrosine kinase receptor determine the tumor response to Zalypsis.

BackgroundZalypsis(®) is a marine compound in phase II clinical trials for multiple myeloma, cervical and endometrial cancer, and Ewing's sarcoma. However, the determinants of the response to Zalypsis are not well known. The identification of biomarkers for Zalypsis activity would also contribute to broaden the spectrum of tumors by selecting those patients more likely to respond to this therapy.MethodsUsing in vitro drug sensitivity data coupled with a set of molecular data from a panel of sarcoma cell lines, we developed molecular signatures that predict sensitivity to Zalypsis. We verified

Идентификация two Ротавирус A генотипы, G35 и P[50], от перуанских фекалий альпаки.

Ротавирус A (RVA) Alp11B был обнаружен из неонатального перуанского альпака, подаваемого диареей, и гены Alp11B VP7, VP4, VP6, NSP4, и NSP5 были секвенированы. Часть генотипа этого штамма, RVA/Alpaca-wt/PER/Alp11B/2010, было решено, что G35-P[50]-I13-E16-H6.

Иммуномодуляторы и иммунопрессанты для прогрессивного множественного склероза: сетевой метаанализ.

В последние годы для лиц с прогрессивными формами множественного склероза (ПМС) был разработан более широкий спектр методов иммуномодуляционного и иммуноподавляющего лечения. Хотя консенсус поддерживает эти варианты в качестве сокращения рецидивов, их относительные преимущества и характеристики безопасности остаются неясными из-за отсутствия прямых сравнительных испытаний. 1-a и бета 1-bИнтерферон beta-1b (Бетаферон), интерферон beta-1a (Avonex, Rebif), лакинимод, лефлюномид, метотрексат, миноциклин, митоксантрон, микофенолат мофетил, натализумаб, окролизумаб, атумумаб, озанимод, пегилированны

Survival risk prediction in hematopoietic stem cell transplantation for multiple myeloma.

This paper investigates the application of Survival Analysis (SA) techniques to forecast outcomes after autologous Hematopoietic Stem Cell Transplantation (aHSCT) for Multiple Myeloma (MM). By leveraging six SA models, we examine their predictive capabilities, measured through the Concordance Index (C-index) metric. Beyond evaluating model performance, we analyze feature importance using permutation and SHAP methods, highlighting key clinical factors such as treatment history, disease stage, and prior disease progression or relapse as critical predictors of survival. The findings suggest that

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… Regarding the prediction of donor availability, various ML algorithms, including boosted decision trees, have demonstrated high effectiveness, achieving remarkable accuracy in identifying compatible hematopoietic stem cell donors [ 9 ]. … Consequently, although a preliminary analysis based solely on the C-index may suggest that any of these models could be appropriate for clinical application, a more thorough examination of feature importance reveals that models like Coxnet or those utilizing decision trees (e.g., RSF) offer a more balanced …

clevRvis: visualization techniques for clonal evolution.

BackgroundA thorough analysis of clonal evolution commonly requires integration of diverse sources of data (e.g., karyotyping, next-generation sequencing, and clinical information). Subsequent to actual reconstruction of clonal evolution, detailed analysis and interpretation of the results are essential. Often, however, only few tumor samples per patient are available. Thus, information on clonal development and therapy effect may be incomplete. Furthermore, analysis of biallelic events-considered of high relevance with respect to disease course-can commonly only be realized by time-consuming

Current multiple myeloma treatment strategies with novel agents: a European perspective.

The treatment of multiple myeloma (MM) has undergone significant developments in recent years. The availability of the novel agents thalidomide, bortezomib, and lenalidomide has expanded treatment options and has improved the outcome of patients with MM. Following the introduction of these agents in the relapsed/refractory setting, they are also undergoing investigation in the initial treatment of MM. A number of phase III trials have demonstrated the efficacy of novel agent combinations in the transplant and nontransplant settings, and based on these results standard induction regimens are be

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… T reatment D ecisions for N ewly D iagnosed D isease Decision trees for the front-line treatment of MM have been developed, and Figure 1 shows a possible treatment tree based on available data from novel agents. … T reatment D ecisions at R elapse Figure 2 shows a possible treatment decision tree for the treatment of MM at relapse, with a focus on incorporating novel agents into the treatment. …

Supping with the Devil: Belief and the Imaginary World of Multiple Myeloma Therapies Invented by the Institute for Clinical and Economic Review.

Previous commentaries in Innovations in Pharmacy and other peer reviewed journals have made the case that the analytical framework, if that is not too strong a term, to support pricing and access recommendations endorsed by the Institute for Clinical and Economic Review (ICER) fails to meet the standards of normal science. By any criteria the ICER analysis is best described as pseudoscience; it fails the demarcation test between biological evolution and intelligent design. Like intelligent design it has its believers; a meme for all seasons. ICER is fully aware of the fact that it fails these

Artificial Intelligence-Augmented Propensity Score, Cost Effectiveness and Computational Ethical Analysis of Cardiac Arrest and Active Cancer with Novel Mortality Predictive Score.

Background and objectives: Little is known about outcome improvements and disparities in cardiac arrest and active cancer. We performed the first known AI and propensity score (PS)-augmented clinical, cost-effectiveness, and computational ethical analysis of cardio-oncology cardiac arrests including left heart catheterization (LHC)-related mortality reduction and related disparities. Materials and methods: A nationally representative cohort analysis was performed for mortality and cost by active cancer using the largest United States all-payer inpatient dataset, the National Inpatient Sample,

Анатомические и морфологические вариации, связанные с микрографированием в оливках in vitro с использованием клональных корнеплодов.

Микрографтация является мощным биотехнологическим инструментом для микропродукции фруктовых деревьев и может применяться для клонального распространения непристойных видов, искоренения вирусов, управления патогенами, раннего выявления совместимости с скионом/кротовым скотом и размножения. Однако в оливках этот метод по-прежнему недостаточно изучен, особенно в том, что касается пересадки на полностью клональные корнеплоды. В этом исследовании мы разработали протокол in vitro микрографирования (IVM), основанный исключительно на клонально распространяемом материале. Two Культиваторы: "Galega" и "

Artificial Intelligence and Machine Learning Technology Driven Modern Drug Discovery and Development.

The discovery and advances of medicines may be considered as the ultimate relevant translational science effort that adds to human invulnerability and happiness. But advancing a fresh medication is a quite convoluted, costly, and protracted operation, normally costing USD ~2.6 billion and consuming a mean time span of 12 years. Methods to cut back expenditure and hasten new drug discovery have prompted an arduous and compelling brainstorming exercise in the pharmaceutical industry. The engagement of Artificial Intelligence (AI), including the deep-learning (DL) component in particular, has bee

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… A blend of human endeavor and AI have been utilized, wherein first-round data from manufacturing sets were scrutinized and decision trees originated. They were subsequently transliterated into axioms and explored by the operators to facilitate the manufacturing cycle afterwards [ 225 ]. …

From the Clinic to the Bench and Back Again in One Dog Year: How a Cross-Species Pipeline to Identify New Treatments for Sarcoma Illuminates the Path Forward in Precision Medicine.

Cancer drug discovery is an inefficient process, with more than 90% of newly-discovered therapies failing to gain regulatory approval. Patient-derived models of cancer offer a promising new approach to identify new treatments; however, for rare cancers, such as sarcomas, access to patient samples is limited, which precludes development of patient-derived models. To address the limited access to patient samples, we have turned to pet dogs with naturally-occurring sarcomas. Although sarcomas make up <1% of all human cancers, sarcomas represent 15% of cancers in dogs. Because dogs have similar im

Применение искусственного интеллекта в перипостетической суставной инфекции.

Перипростетическая суставная инфекция (ПСО) представляет собой one Из наиболее разрушительных осложнений, вызванных общей совместной артропластикой, часто требующих дополнительных операций и антимикробной терапии, и потенциально ведущих к инвалидности. Это значительно увеличивает нагрузку как на пациентов, так и на систему здравоохранения. С учетом значительных страданий, причиняемых ПСО, его профилактика и лечение уже давно являются ключевыми факторами, вызывающими озабоченность. Вместе с тем сохраняются проблемы, связанные с точной оценкой индивидуального риска, предотвращением инфекции, сов

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… ML algorithms, such as Random Forest (RF), utilize ensemble decision trees for classification/regression tasks, enabling robust risk stratification and factor identification [21] , [33] . … Paranjape et al. developed an ML algorithm that combines unsupervised and supervised techniques, using methods like principal component analysis (PCA), unsupervised clustering (K-Means), and decision tree models [106] . …

SiMON-PRO-Hematology®: Digital techology for pharmacotherapeutic and patient reported outcomes monitoring in patients with hematologic malignancies.

INTRODUCTION: Advances in hematologic malignancy treatment have improved survival, but patients often experience treatment-related toxicities. Traditional clinical follow-up often overlooks the patient's subjective experience, highlighting the need for integrated patient-reported outcome measures (PROMs). The primary objective of this study was to describe the design and implementation of the SiMON-PRO-Hematology® system, a comprehensive information tool supporting the pharmacotherapeutic follow-up of patients with hematological malignancies. A secondary objective was to detail the process for

Research on RNA modification in disease diagnosis and prognostic biomarkers: current status and challenges.

RNA modification, as a crucial post-transcriptional regulatory mechanism, plays a pivotal role in normal physiological processes and is closely associated with the onset and progression of various human diseases. Recent studies have highlighted significant alterations in the level of RNA modifications, including m6A, m6Am, m1A, m5C, m7G, ac4C, Ψ, and A-to-I editing, across multiple diseases. These findings suggest the potential of RNA modifications and their regulatory factors as biomarkers for early disease diagnosis and prognosis. This review provides an overview of statistical methods, mach

Patients and healthcare professionals' perspectives on the implementation of shared decision making in multiple myeloma: a multinational qualitative study.

BACKGROUND: Shared decision making (SDM) is highly relevant in oncology and cancer care, yet its application within multiple myeloma (MM) remains underexplored. This study aims to (1) investigate SDM implementation in MM clinical practice, (2) assess the role of various stakeholders next to haematologists in the SDM process, and (3) identify barriers and potential solutions to SDM implementation in MM care. METHODS: This qualitative study consisted of semi-structured interviews with patients (n = 39), haematologists (n = 15), and haematology nurses (n = 5) from nine countries in Europe and Is

The 2023 Latin America report of the Lancet Countdown on health and climate change: the imperative for health-centred climate-resilient development.

In 2023, a series of climatological and political events unfolded, partly driving forward the global climate and health agenda while simultaneously exposing important disparities and vulnerabilities to climate-related events. On the policy front, a significant step forward was marked by the inaugural Health Day at COP28, acknowledging the profound impacts of climate change on health. However, the first-ever Global Stocktake showed an important gap between the current progress and the targets outlined in the Paris Agreement, underscoring the urgent need for further and decisive action. From a L

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