Pivotal Shift Research Articles

Advancements in the Treatment of Diuretic Resistance in Congestive Heart Failure.

This narrative evaluates the dynamic developments that have significantly transformed treatment strategies in the constantly evolving domain of diuretic resistance (DR) management in congestive heart failure (CHF). The discourse explores historical challenges and the current state of therapeutic approaches as it investigates the crucial matter of DR in patients with CHF. An introduction provides a synopsis of the pivotal function diuretics performed in the management of fluid excess and the intricacies associated with CHF. The narrative explores the progressive exposure of the constraints that traditional treatments face, thus underscoring the persistent issue of DR and the imperative for innovative methodologies. The text underscores advancements in pharmacotherapy that demonstrate efficacy in surmounting resistance, including innovative diuretics and combination therapies. Furthermore, it outlines the pivotal shift towards personalized medicine, an approach that transforms the results of treatments through the integration of genetic knowledge and individualized strategies. Furthermore, the text delves into nonpharmacological strategies, including ultrafiltration and renal denervation, that enhance the overall comprehension of the intricate battle against diuretic resistance. In summary, this narrative exemplifies resolute perseverance in the pursuit of solutions, presenting a promising future wherein various developments converge to restore hope in regard to the control of DR and the improvement of the health status of chronic heart failure patients.

Enzyme catalytic efficiency prediction: employing convolutional neural networks and XGBoost

IntroductionIn the intricate realm of enzymology, the precise quantification of enzyme efficiency, epitomized by the turnover number (kcat), is a paramount yet elusive objective. Existing methodologies, though sophisticated, often grapple with the inherent stochasticity and multifaceted nature of enzymatic reactions. Thus, there arises a necessity to explore avant-garde computational paradigms.MethodsIn this context, we introduce “enzyme catalytic efficiency prediction (ECEP),” leveraging advanced deep learning techniques to enhance the previous implementation, TurNuP, for predicting the enzyme catalase kcat. Our approach significantly outperforms prior methodologies, incorporating new features derived from enzyme sequences and chemical reaction dynamics. Through ECEP, we unravel the intricate enzyme-substrate interactions, capturing the nuanced interplay of molecular determinants.ResultsPreliminary assessments, compared against established models like TurNuP and DLKcat, underscore the superior predictive capabilities of ECEP, marking a pivotal shift in silico enzymatic turnover number estimation. This study enriches the computational toolkit available to enzymologists and lays the groundwork for future explorations in the burgeoning field of bioinformatics. This paper suggested a multi-feature ensemble deep learning-based approach to predict enzyme kinetic parameters using an ensemble convolution neural network and XGBoost by calculating weighted-average of each feature-based model’s output to outperform traditional machine learning methods. The proposed “ECEP” model significantly outperformed existing methodologies, achieving a mean squared error (MSE) reduction of 0.35 from 0.81 to 0.46 and R-squared score from 0.44 to 0.54, thereby demonstrating its superior accuracy and effectiveness in enzyme catalytic efficiency prediction.DiscussionThis improvement underscores the model’s potential to enhance the field of bioinformatics, setting a new benchmark for performance.

Challenges and strategies for implementing the Ramsar Convention. Balancing Economic Development and Wetland Conservation

Ramsar Convention on Wetlands of International Importance, particularly focusing on waterfowl habitats, signifies a pivotal shift in global attitudes towards wetland conservation. Historically viewed as hindrances to development, wetlands have suffered from drainage and reclamation efforts, resulting in significant biodiversity loss. However, a growing recognition of their ecological significance has spurred international action. The Convention, established in 1971, serves as a landmark agreement to safeguard wetland ecosystems. It mandates member states to designate and conserve wetlands within their territories, emphasizing the importance of international cooperation due to the transboundary nature of wetland ecosystems. The Convention’s objectives encompass sustainable development goals, including water quality, biodiversity, and climate change mitigation. Implementation relies on national policies and collaboration among stakeholders. Furthermore, the Convention aligns with other environmental agreements, fostering synergies to enhance wetland protection globally. Despite these positive developments, there are significant challenges in ensuring the effective implementation of the Convention, particularly when economic interests conflict with environmental conservation. As highlighted in the case of the Bystroe Canal project in the Danube Delta, balancing development with wetland protection remains a critical issue. This article addresses the question of whether the Ramsar Convention can effectively apply its provisions in such cases, arguing that while it provides a strong framework, its effectiveness is often undermined by competing economic priorities. Without stronger enforcement mechanisms and increased international cooperation, the objectives of the Convention risk being compromised.

Internal Quality Control and the Role of Learning Management Systems (LMS) in Higher Education Institutions in Sierra Leone: Then, Now, and Later

The paper explores the evolution of Internal Quality Control (IQC) in Sierra Leone's higher education institutions (HEIs) with a specific focus on the transformative role of Learning Management Systems (LMS). Beginning with the colonial era, the paper traces the historical context of IQC, emphasizing its informal nature. The post-independence expansion of HEIs introduced quality challenges compounded by economic constraints and political instability. The civil war further disrupted the education sector, and the reconstruction period saw the establishment of the Tertiary Education Commission (TEC), formalizing IQC processes. The introduction of LMS platforms, such as Moodle and Google Classroom, marked a pivotal shift in enhancing educational quality. LMS has significantly contributed to data-driven decision-making, standardized educational processes, and continuous feedback mechanisms. However, challenges remain, including infrastructural limitations and the urban-rural digital divide. The paper also projects the future of IQC, highlighting the potential integration of advanced technologies such as artificial intelligence, big data analytics, and blockchain in LMS platforms. These advancements promise to revolutionize the educational experience, offering new possibilities for quality assurance and student engagement.

Navigating Palliative Care: A qualitative study of the needs and challenges of newly qualified nurses

Summary Background: Newly qualified nurses are expected to care for life-threateningly ill patients and their relatives. However, there is currently a significant research gap concerning the experiences and challenges faced by newly qualified Danish nurses when encountering basic palliative care in practice. Aim: To explore the experiences of newly qualified nurses providing basic palliative care. Methods: Individual in-depth interviews with nine nurses were conducted, and data analyzed through qualitative, descriptive analysis. Findings: The study underscores the pivotal shift from being a student to becoming a practicing nurse, revealing uncertainties and a need to engage in palliative care during clinical training. Additionally, the study unveils a pervasive sense of busyness in the practice of healthcare, preventing a balance between efficiency and calmness in palliative care. Administering medication, handling crisis-reactions, and communicating with fearful patients and relatives requires courage and experience. The emotional impact is profound, necessitating support and dialogue. The identified challenges are explored in the discussion, emphasizing how busyness impacts palliative care, and highlighting the significance of structured support mechanisms to enhance newly qualified nurses’ competences and confidence in their work in palliative nursing. Conclusion: Newly qualified nurses face challenges transitioning to professional practice. The fast-paced healthcare system impedes their ability to deliver sensitive, person-oriented care, causing uncertainty and fear of failure. Ongoing dialogue and support from experienced colleagues are crucial for helping newly qualified nurses prioritize tasks, make informed clinical decisions, and develop leadership skills in basic palliative care. Keywords: Palliation; Newly qualified nurses; Nursing education; Qualitative research; Healthcare system dynamics; Collegial support

Genetic Variation for Tolerance to High Temperatures in Tomato Using Critical Sterility Temperature

Tomato (Solanum lycopersicum L.) reproduction is influenced by temperature, prominently impacting yield. The ideal daytime range is between 25°C and 30°C and the nighttime temperature is around 20°C for tomato and deviations of a few degrees from these temperatures can have negative effects. The study assessed the effect of temperature on tomato pollen germination and aimed to ascertain the critical sterility temperature for pollen germination. In an open field, pollen from 10 genotypes (Anagha, Manuprabha, Vellayani Vijay, Akshaya, Nandi, IIHR26372, Pusa Rohini, Arka Saurabh, Arka Rakshak, and Arka Vikas) underwent In-vitro temperature exposure ranging from 32 to 40°C at 2°C intervals. Variations in In-vitro pollen germination percentage were observed across the genotypes, notably revealing a sharp decline after 36°C. This decline indicated a pivotal shift in pollen germination and viability. Genotypes, Anagha and Arka Saurabh, were identified as temperature tolerant and susceptible, respectively. The findings present an opportunity to incorporate temperature-dependent pollen response functions and identified genotypes into tomato breeding programs, offering significant implications for enhancing yield under varying temperature conditions.

The Use of Artificial Intelligence in Predicting Chemotherapy-Induced Toxicities in Metastatic Colorectal Cancer: A Data-Driven Approach for Personalized Oncology.

Machine learning models learn about general behavior from data by finding the relationships between features. Our purpose was to develop a predictive model to identify and predict which subset of colorectal cancer patients are more likely to experience chemotherapy-induced toxicity and to determine the specific attributes that influence the presence of treatment-related side effects. The predictor was general toxicity, and for the construction of our data training, we selected 95 characteristics that represent the health state of 74 patients prior to their first round of chemotherapy. After the data were processed, Random Forest models were trained to offer an optimal balance between accuracy and interpretability. We constructed a machine learning predictor with an emphasis on assessing the importance of numerical and categorical variables in relation to toxicity. The incorporation of artificial intelligence in personalizing colorectal cancer management by anticipating and overseeing toxicities more effectively illustrates a pivotal shift towards more personalized and precise medical care.

Development of a Wave Model Component in the First Coupled Global Ensemble Forecast System at NOAA

Abstract We describe the development of the wave component in the first global-scale coupled operational forecast system using the Unified Forecasting System (UFS) at the National Oceanic and Atmospheric Administration (NOAA), part of the US National Weather Service (NWS) operational forecasting suite. The operational implementation of the atmosphere-wave coupled Global Ensemble Forecast System version 12 (GEFSv12) in September 2020 was a critical step in NOAA’s transition to the broader community-based UFS framework. GEFSv12 represents a significant advancement, extending forecast ranges and empowering the NWS to deliver advanced weather predictions with extended lead times for high-impact events. The integration of a coupled wave component with higher spatial and temporal resolution and optimized physics parameterizations notably enhanced forecast skill and predictability, particularly benefiting winter storm predictions of wave heights and peak wave periods. This successful endeavor encountered challenges that were addressed by the simultaneous development of new features that enhanced wave model forecast skill and product quality and facilitated by a multidisciplinary team collaborating with NOAA’s operational forecasting centers. The GEFSv12 upgrade marks a pivotal shift in NOAA’s global forecasting capabilities, setting a new standard in wave prediction. We also describe the coupled GEFSv12-Wave component impacts on NOAA operational forecasts, and ongoing experimental enhancements, which altogether represent a substantial contribution to NOAA’s transition to the fully-coupled UFS framework.

Lorenz Fries on the defense of Avicenna, the prince of physicians: Addressed to the medics of Germany (1530).

During the 14th century CE, a pivotal shift took place in the world of medicine as its epicenter transitioned from the Middle East to Europe. The emergence of the European Renaissance sparked skepticism regarding the significance of Avicenna's contributions to the advancement of medicine. This paper explores how the rise of secularization and the Renaissance in Europe marked significant cultural transformations, fostering the spread of literacy. These societal shifts influenced the trajectory of medical thought, and Avicenna's "Canon of Medicine" received both praise and condemnation amidst the evolving intellectual landscape. In this context, Lorenz Fries composed his "Defense of Avicenna," a testament to his profound admiration for Avicenna's legacy. This paper presents an English translation of Fries' 1530 work, and introduces Fries and Avicenna's "Canon," contextualizing Fries' defense within the broader rejection of Arab-language medical texts in the 16th century. It also explores Avicenna's influence on European medicine and anatomy during the Renaissance and highlights the enduring relevance of his contributions to the annals of science. Fries' defense underscores Avicenna's methodological acumen and emphasizes the importance of a robust theoretical foundation in medical practice. Avicenna's integration of Aristotelianism with Platonism highlighted the necessity of a rigorous method informed by theory in medical analysis. Fries' defense remains relevant today, particularly in advocating for systematic medical analysis against subjective approaches. Avicenna's medical philosophy seems nested within a larger, hopeful attempt to resolve the tensions between science or naturalism and religion or spiritualism. The rejection of Avicenna reflects broader conflicts between Aristotelian and Neoplatonic traditions, suggesting a complex interplay of secularization and theological influences in shaping medical thought during the Renaissance.

Diversity of style in the works of the artist (Naziha Selim)

Iraqi art underwent a significant transformation in the second half of the 20th century, seeking to remove established norms, which led to ground-breaking outputs from artists like Naziha Salim. Her work represents a pivotal shift, rooted in two main aspects: the inspiration from cultural heritage and its contemporary application. Salim's art exemplifies beauty through the use of modern techniques, diverse materials, varying styles, and the interplay of lines and space, alongside the strategic use of color masses. This diversity is the cornerstone of this study. The research is structured into four chapters. The first chapter addresses the research problem, stemming from the question: To what extent does the diversity of style manifest in Naziha Salim's works? The aim is to explore this diversity, alongside highlighting the research's significance and scope. The second chapter comprises two sections: the first reviews the multiplicity of styles in modern European art schools, while the second delves into the diversity of styles in contemporary Iraqi painting, particularly focusing on the experiences of various artists, with a special emphasis on Naziha Salim's work. The third chapter outlines the research methodology, detailing the study population, which includes 15 of Salim's artworks. The sample consists of three works, selected and analyzed based on expert recommendations, employing a descriptive analytical approach to meet the study's objectives and derive conclusions. The fourth chapter presents the research findings, such as Salim's reflection of the social environment and the juxtaposition of reality's tragedies, forming a stylistic, intellectual, and nationalistic vision. The conclusions suggest that the artistic scene revolves around the genuine impetus behind creating art and its relationship with environment, history, and the artist’s introspection. Additionally, the chapter includes recommendations and proposals, concluding with images of the analyzed artworks.

Smooth vetch covering alters soil aggregate microbial metabolic limitations in citrus orchards

Green manure covering alters the supply-demand relationship between soil resources and microorganisms by improving soil structure and increasing carbon inputs. However, it remain unclear how soil microorganism respond to the imbalance between resources and demands at the aggregate scale. The present study analyzed the stoichiometric ratios of organic carbon, nitrogen, and phosphorus nutrients, microbial extracellular enzyme activities, and biomass in large macroaggregates (LMA, 2–8 mm), small macroaggregates (SMA, 0.25–2 mm), and microaggregates (MIA, < 0.25 mm) under smooth vetch covering. The relationship between microbial carbon use efficiency and nutrient restriction in soil aggregates was elucidated and the alteration was revealed in microbial metabolic pathways and carbon sequestration functions within soil aggregates under green manure covering. The results showed that: (1) Smooth vetch covering significantly increased the C: N resource imbalance (ln(MBC: MBN)/ln(SOC: TN)) in soil aggregates from 0.50 to 0.69, and thus increased the nitrogen requirement of soil aggregates. However, the N:P resource imbalance (ln(MBN: MBP)/ln(TN: TP)) decreased from 2.25 to 1.78, especially in microaggregates. (2) To mitigate the limitation imposed by nitrogen availability at the aggregate level, microorganisms have ramped up the activity of C- (46.72 %–98.64 %), N- (2.32 %–121.00 %), and P- acquiring enzymes (119.11 %–187.78 %). Nevertheless, the spatial heterogeneity inherent in soil aggregates, characterized by varying particle sizes, has led to a pivotal shift in microbial nutrient limitation. As soil aggregate size diminishes, the primary constraint on microbial activity transitions from nitrogen limitation to phosphorus limitation, reflecting the dynamic interplay between soil structure and nutrient availability. (3) In addition, smooth vetch covering increased the microbial carbon use efficiency of soil aggregates, and it increased with the increase of the particle size of soil aggregates: LMA (178.80 %) > SMA (147.23 %) > MIA (9.99 %). Microorganisms allocated more energy to generate biomass instead of obtaining limiting nutrient elements. These results indicate that smooth vetch covering could increase the organic carbon content of soil aggregates. In addition, in order to adapt to nutrient imbalance, soil aggregates microorganisms choose a “egoistic” metabolic pathway, which alleviates nutrient limitation and assimilated more energy and nutrients into their own biomass and reduces the release of organic carbon. It is evident that integrating Vicia villosa Roth var. glabresens Koch as a ‘green manure’ in orchards serves a dual purpose: it mitigates the environmental impact of chemical fertilizers while simultaneously promoting soil carbon sequestration. This approach offers a robust theoretical framework for achieving the harmonious integration of ecological sustainability and economic viability in economic forestry, such as citrus orchards.

An Overview of the Reformation brought by Christianity: A Historical and Bibliometric Perspective

Abstract: This paper provides a comprehensive historical and bibliometric analysis of the Reformation in Christianity, emphasizing its profound influence on religious, social, and political landscapes. The Reformation, initiated by key figures such as Martin Luther, marked a pivotal shift from the doctrines of the Roman Catholic Church, leading to the establishment of various Protestant denominations and significant reforms within the Catholic Church. This study integrates historical narratives with bibliometric methodologies to identify prevailing trends, influential works, and key contributors in Reformation studies. Analysing scholarly publications from 1964 to 2024, the paper highlights the evolution of research focus, emerging areas of interest, and the broader implications of Reformation principles on contemporary issues, including human rights, environmental activism, and socio-political reforms. The findings underscore the enduring legacy of the Reformation and its relevance to modern-day religious and socio-political contexts.

The impact and future of artificial intelligence in medical genetics and molecular medicine: an ongoing revolution.

Artificial intelligence (AI) platforms have emerged as pivotal tools in genetics and molecular medicine, as in many other fields. The growth in patient data, identification of new diseases and phenotypes, discovery of new intracellular pathways, availability of greater sets of omics data, and the need to continuously analyse them have led to the development of new AI platforms. AI continues to weave its way into the fabric of genetics with the potential to unlock new discoveries and enhance patient care. This technology is setting the stage for breakthroughs across various domains, including dysmorphology, rare hereditary diseases, cancers, clinical microbiomics, the investigation of zoonotic diseases, omics studies in all medical disciplines. AI's role in facilitating a deeper understanding of these areas heralds a new era of personalised medicine, where treatments and diagnoses are tailored to the individual's molecular features, offering a more precise approach to combating genetic or acquired disorders. The significance of these AI platforms is growing as they assist healthcare professionals in the diagnostic and treatment processes, marking a pivotal shift towards more informed, efficient, and effective medical practice. In this review, we will explore the range of AI tools available and show how they have become vital in various sectors of genomic research supporting clinical decisions.

Increasing WNP tropical cyclone-related extreme precipitation over East Asia during boreal summer associated with PDO shift

Over the past two decades, there has been a significant shift in tropical cyclone (TC) activity in the western North Pacific (WNP) basin during the boreal summer. Our analysis of data spanning from 1979 to 2021 reveals significant shifts in the WNP TC characteristics and rainfall pattern variation. To deepen our understanding of TC-related precipitation dynamics, we expressly address the difference between TC-related core precipitation (TCP) and remote precipitation (TRP). The results show that TRP significantly impacts the East Asian (EA) continent, especially on the Korean Peninsula. Notably, TCP exhibits decadal variability, with a pronounced negative correlation identified between it and the Pacific decadal oscillation (PDO) following a strong climate shift. This pivotal shift was marked by the PDO first transitioning to its negative phase in 1997, a notable change since 1979, resulting in a marked increase in TC-related extreme rainfall over the EA area. Concurrently, the rising sea surface temperatures (SSTs) over the WNP have intensified the western Pacific subtropical high (WPSH) circulation. The easterly steering flow associated with the WPSH then strengthened, leading to the continental migration of TC trajectories, thereby intensifying TC-related extreme precipitation.

Molecular epidemiology and population immunity of SARS-CoV-2 in Guangdong (2022–2023) following a pivotal shift in the pandemic

The SARS-CoV-2 Omicron variant sparked the largest wave of infections worldwide. Mainland China eased its strict COVID-19 measures in late 2022 and experienced two nationwide Omicron waves in 2023. Here, we investigated lineage distribution and virus evolution in Guangdong, China, 2022-2023 by comparing 5813 local viral genomes with the datasets from other regions of China and worldwide. Additionally, we conducted three large-scale serological surveys involving 1696 participants to measure their immune response to the BA.5 and XBB.1.9 before and after the corresponding waves. Our findings revealed the Omicron variants, mainly the BA.5.2.48 lineage, causing infections in over 90% of individuals across different age groups within a month. This rapid spread led to the establishment of widespread immunity, limiting the virus’s ability to further adaptive mutation and dissemination. While similar immune responses to BA.5 were observed across all age groups after the initial wave, children aged 3 to 11 developed a stronger cross immune response to the XBB.1.9 strain, possibly explaining their lower infection rates in the following XBB.1 wave. Reinfection with Omicron XBB.1 variant triggered a more potent neutralizing immune response among older adults. These findings highlight the impact of age-specific immune responses on viral spread in potential future waves.

Skill Education under NEP 2020: A Pathway to Enhanced Employability and Economic Growth

The National Education Policy (NEP) 2020 marks a pivotal shift in the Indian education system by integrating skill education to boost student employability and foster economic growth. This study evaluates the impact of NEP 2020's skill education strategies on job readiness and their broader economic implications. Through policy document analysis, educational frameworks, and empirical data, this research reveals how NEP 2020 aligns educational outcomes with industry requirements. Findings suggest that the policy’s emphasis on vocational training, experiential learning, and competency-based education effectively enhances graduate employability. Additionally, NEP 2020’s focus on lifelong learning and adaptability prepares students for a dynamic job market, contributing to economic development. This paper underscores NEP 2020's role in reshaping India's educational landscape and cultivating a workforce ready for the 21st-century economy. Keywords: NEP 2020, Skill Education, Employability Skills, Hands-on Practice, Transformation, NCERT, NCVT

Polyphenol-Enabled 2D Nanopatch for Enhanced Nasal Mucoadhesion and Immune Activation.

The advancement of effective nasal mucoadhesive delivery faces challenges due to rapid mucociliary clearance (MCC). Conventional studies have employed mucoadhesive materials, mainly forming spherical nanoparticles, but these offer limited adhesion to the nasal mucosa. This study hypothesizes that a 2D nanoscale structure utilizing adhesive polyphenols can provide a superior strategy for countering MCC, aligning with the planar mucosal layers. We explore the use of tannic acid (TA), a polyphenolic molecule known for its adhesive properties and ability to form complexes with biomolecules. Our study introduces an unprecedented 2D nanopatch, assembled through the interaction of TA with green fluorescent protein (GFP), and cell-penetrating peptide (CPP). This 2D nanopatch demonstrates robust adhesion to nasal mucosa and significantly enhances immunoglobulin A secretions, suggesting its potential for enhancing nasal vaccine delivery. The promise of a polyphenol-enabled adhesive 2D nanopatch signifies a pivotal shift from conventional spherical nanoparticles, opening new pathways for delivery strategies through respiratory mucoadhesion.

An advanced Artificial Intelligence platform for a personalised treatment of Eating Disorders.

Eating Disorders (EDs) affect individuals globally and are associated with significant physical and mental health challenges. However, access to adequate treatment is often hindered by societal stigma, limited awareness, and resource constraints. The project aims to utilize the power of Artificial Intelligence (AI), particularly Machine Learning (ML) and Deep Learning (DL), to improve EDs diagnosis and treatment. The Master Data Plan (MDP) will collect and analyze data from diverse sources, utilize AI algorithms for risk factor identificat io n, treatment planning, and relapse prediction, and provide a patient-facing chatbot for information and support. This platform will integrate patient data, support healthcare professionals, and empower patients, thereby enhancing care accessibility, personalizing treatment plans, and optimizing care pathways. Robust data governance measures will ensure ethical and secure data management. Anticipated outcomes include enhanced care accessibility and efficiency, personalized treatment plans leading to improved patient outcomes, reduced waiting lists, heightened patient engagement, and increased awareness of EDs with improved resource allocation. This project signifies a pivotal shift towards data-driven, patient-centered ED care in Italy. By integrat ing AI and promoting collaboration, it seeks to redefine mental healthcare standards and foster better well- being among individuals with EDs.

Pembrolizumab in combination with trastuzumab for treatment of HER2-positive advanced gastric or gastro-esophageal junction cancer.

Gastric cancer remains a challenging malignancy with a high global mortality rate. Recent advances in targeted therapy and immunotherapy have shown promise in improving patient outcomes. This paper reviews the impact of incorporating targeted agents such as trastuzumab and immunotherapeutic agents like pembrolizumab into standard chemotherapy regimens for gastric cancer treatment. A comprehensive analysis was conducted on pivotal clinical trials, including KEYNOTE-590, KEYNOTE-811, and ToGA, focusing on their methodologies, patient populations, treatment regimens, and outcome measures. The review also explored emerging research avenues in precision medicine, particularly genomic sequencing and biomarker identification. To assess the efficacy and survival benefits of adding trastuzumab and pembrolizumab to standard chemotherapy in the treatment of gastric cancer and to outline future directions in gastric cancer research. Including trastuzumab and pembrolizumab in treatment regimens for human epidermal growth factor receptor 2 (HER2)-positive and PD-L1-expressing gastric cancers significantly improved progression-free and overall survival rates compared to chemotherapy alone. These findings highlight the potential of personalized therapy in enhancing treatment outcomes. Furthermore, ongoing research into the gastric cancer microenvironment and the role of the microbiome suggests novel targets for future therapeutic interventions. The integration of targeted and immunotherapeutic agents with traditional chemotherapy represents a pivotal shift in gastric cancer treatment, moving towards more personalized and effective regimens.

Elacestrant in the treatment landscape of ER-positive, HER2-negative, ESR1-mutated advanced breast cancer: a contemporary narrative review.

Estrogen receptor-positive (ER+), human epidermal growth factor receptor 2-negative (HER2-) breast cancer with ESR1 mutations presents a significant therapeutic challenge due to its adaptive resistance mechanisms to chemotherapy, especially endocrine treatment. Elacestrant, a novel oral selective estrogen receptor degrader (SERD), has emerged as a promising agent in this treatment-resistant era. A comprehensive search was conducted on pivotal clinical trials, including the RAD1901-005 Trial, EMERALD TRIAL, ELIPSE, and ELEVATE, focusing on their methodologies, patient populations, treatment regimens, and outcomes. This narrative review describes the available preclinical and clinical evidence on elacestrant, focusing on its pharmacodynamics, pharmacokinetics, efficacy, and safety within the existing literature. Elacestrant has demonstrated excellent activity against ESR1 mutations associated with resistance to first-line endocrine therapies. Clinical trials have shown improved progression-free survival in patients with advanced ER+/HER2-, ESR1-mutated breast cancer. Safety profiles indicate a tolerable side effect spectrum consistent with other agents. Its oral bioavailability offers a convenient alternative to injectable SERDs, with potential implications for patient adherence and quality of life. The review also discusses the comparative efficacy of elacestrant relative to existing endocrine therapies and its possible use in combination regimens. Ongoing clinical trials assessing elacestrant and other SERDs will yield data that might aid clinicians in determining the optimal selection and order of endocrine treatment drugs for ER+ breast cancer. The integration of targeted and immunotherapeutic agents with traditional chemotherapy represents a pivotal shift in Breast Cancer treatment, moving towards more personalized and effective regimens.