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The purpose of this research was to evaluate the effectiveness and safety of neoadjuvant chemotherapy plus radical surgery (NCRS) and concurrent chemoradiotherapy (CCRT) based on three-dimensional conformal radiation therapy (3DCRT) for FIGO 2018 stage IB3/IIA2 patients with cervical squamous cell carcinoma in a resource-limited setting. The clinical outcomes and incidence of complications in 137 patients who underwent NCRS with those of 163 patients who CCRT based on 3DCRT were compared. Propensity score matching (PSM) analysis was used to match the two groups to enable further statistical comparisons. Survival analysis was performed utilizing Cox proportional hazards regression analyses, Kaplan-Meier curves, and log-rank tests. Furthermore, the incidence of complications between the two groups was also compared using chi-squared tests. PSM analysis identified 103 matched pairs of patients. The NCRS and CCRT groups exhibited 5-year overall survival (OS) rates of 85.4% and 91.2%, respectively (p=0.19). Additionally, the NCRS and CCRT groups exhibited 5-year disease-free survival (DFS) rates of 76.7% and 89.3% (p=0.02), and the recurrence rates were 20.4% and 9.7% (p=0.03), respectively. However, the CCRT group exhibited a higher incidence of early any-grade complications (79.6% vs 35.9%, p<0.001) and early grade 3 complications (15.5% vs 2.9%, p=0.002) compared to the NCRS group. In terms of overall late complications, there was no significant difference in the incidence between the two groups. Multivariate analysis revealed that stage IIA2 emerged as an independent risk factor for OS (aHR 8.89; p=0.033). Moreover, histologic grade 2-3 (aHR 5.3; p=0.022), stage IIA2 (aHR 2.95; p=0.043), NCRS treatment (aHR 2.41; p=0.012) were identified as independent risk factors for DFS. In resource-limited settings, for patients with FIGO 2018 stage IB3/IIA2 cervical squamous cell carcinoma, 3DCRT-based CCRT offers superior disease-free survival and reduced recurrence rates compared to NCRS, despite increased early complication rates.

Targeted therapies have revolutionized oncology but are accompanied by significant cardiovascular complications, with heart failure being a major dose-limiting toxicity. This review primarily focuses on heart failure induced by targeted anticancer agents, while also contextualizing findings with insights from classical chemotherapeutics and radiotherapy where they inform mechanistic understanding or combination regimen management. We detail the multifaceted pathophysiological mechanisms, which vary by drug class, including direct cardiomyocyte injury via HER2/ErbB signaling disruption, mitochondrial dysfunction, oxidative stress, and novel pathways such as ferroptosis and autophagy dysregulation. The review evaluates strategies for risk assessment, highlighting the utility and limitations of clinical tools like Heart Failure Association-International Cardio-Oncology Society (HFA-ICOS) risk score, and acknowledges that while biomarkers and advanced imaging parameters like global longitudinal strain (GLS) are often reported to have high sensitivity for early detection, their performance can vary depending on the specific definitions of cardiotoxicity used and the clinical context. Current management paradigms are discussed, encompassing pharmacological cardioprotection, treatment modification protocols, and the safe continuation of therapy with concomitant cardiac medications. Furthermore, we explore emerging strategies from traditional natural products and gene-based therapies to advanced drug delivery systems aimed at providing targeted cardioprotection. Finally, future perspectives are outlined, focusing on personalized risk prediction through multi-omics and artificial intelligence, and the development of novel therapeutics with improved cardiovascular safety profiles. This mini review underscores the importance of a multidisciplinary cardio-oncology approach to optimize both oncological efficacy and long-term cardiovascular health for cancer patients.

SMARCA4 deficient thoracic tumors represent an aggressive subset of malignancies characterized by inactivating mutations in the SMARCA4 gene, a core component of the SWI/SNF chromatin remodeling complex. These tumors, including SMARCA4-deficient non-small cell lung cancer (SMARCA4-dNSCLC) and SMARCA4-deficient undifferentiated thoracic tumor (SMARCA4-UT), typically occur in older male smokers. They are characterized by poor differentiation, advanced stage at diagnosis, and a dismal prognosis. Despite the transformative impact of immune checkpoint inhibitors (ICIs) in advanced NSCLC, patients with SMARCA4-deficient tumors often demonstrate limited responses due to an immunosuppressive tumor microenvironment (TME), characterized by minimal T-cell infiltration, impaired antigen presentation, and epigenetic dysregulation. Co-mutations in STK11 and KEAP1 further contribute to immune evasion and resistance to immunotherapy. While conventional biomarkers such as PD-L1 expression and tumor mutational burden (TMB) show limited predictive value in this context, preliminary evidence from retrospective studies and case series suggests that specific mutation classes and combinatorial therapeutic approaches—such as chemoimmunotherapy, anti-angiogenic agents, and ferroptosis inducers—may enhance clinical outcomes. This review synthesizes current knowledge on the clinicopathological and molecular features of SMARCA4-dNSCLC, explores mechanisms of immunotherapy resistance, and evaluates therapeutic strategies. Where instructive, insights from the related SMARCA4-UT are integrated to provide a comparative perspective on the profound impact of SMARCA4 deficiency across thoracic malignancies.

ObjectiveTo develop a new inflammatory biomarker-based and simple-to-use nomogram for the early identification of acute pulmonary embolism (PE) patients at a high-risk mortality in intensive care unit (ICU).MethodsWe randomly allocated 1083 acute PE patients from the Medical Information Mart for Intensive Care IV database to derivation and internal validation cohort. We used logistic regression analysis to determine independent risk factors and to construct a predictive nomogram. We subsequently evaluated the calibration, discrimination and clinical usefulness of the nomogram.ResultsAge>66, neutrophil-to-lymphocyte ratio (NLR) > 10.1, lymphocyte-to-monocyte ratio (LMR) < 1.5, red cell distribution width (RDW) > 14.35, respiratory rate (RR) > 26bpm, oxygen saturation (SPO ), vasopressor use and malignant cancer were detected as important determinants of 28-day mortality and included in our nomogram. The calibration plot revealed an adequate fit of the nomogram for predicting the risk of 28-day mortality. Regarding discriminative power, receiver operating characteristic curve analysis showed that the nomogram had an area under the curve of 0.772 (95% CI:0.732, 0.811,  < .001) in the primary cohort, outperforming other scores.ConclusionsThis proposed simple-to-use nomogram based on age, NLR, LMR, RDW, vasopressor use, RR, SPO and malignant cancer provides accurate death prediction for acute PE patients in ICU.

Purpose There are no well-recognized guidelines for antiemesis during concurrent chemoradiotherapy (CCRT) for cervical cancer (CC) and nasopharyngeal cancer (NPC) until now. The study was designed to assess the efficacy and safety of fosaprepitant combined with tropisetron and dexamethasone in preventing nausea and vomiting during 5 weeks of fractionated radiotherapy and concomitant weekly low-dose cisplatin chemotherapy in patients with CC or NPC. Methods Patients with CC or NPC were scheduled to receive fractionated radiotherapy and weekly cisplatin (25–40 mg/m 2 ) chemotherapy for at least 5 weeks. Patients stratified by tumor type and induction chemotherapy were 1:1 randomly assigned to receive fosaprepitant, tropisetron, and dexamethasone or tropisetron plus dexamethasone as an antiemetic regimen. Efficacy was assessed primarily by the cumulative incidence of emesis after 5 weeks of treatment, and safety by adverse events (AEs). Results Between July 2020 and July 2022, 116 patients consented to the study of whom 103 were included in this interim analysis (fosaprepitant group [ N  = 52] vs control group [ N  = 51]). The cumulative incidence of emesis at 5 weeks (competing risk analysis) was 25% (95% CI 14.2–37.4) for the fosaprepitant group compared with 59% (95% CI 43.9–71.0) for the control group. There was a significantly lower cumulative risk of emesis in the fosaprepitant group (HR 0.35 [95% CI 0.19–0.64]; p  < 0.001). Fosaprepitant was well tolerated as the incidences of adverse events in the two groups were comparable. Conclusion The addition of fosaprepitant to tropisetron plus dexamethasone significantly reduced the risk of nausea and vomiting during 5 weeks of CCRT in patients with CC or NPC, and fosaprepitant was well tolerated. Trial registration The trial was registered with ClinicalTrials.gov on October 3, 2022, number NCT05564286.

•Integrated meta-analysis and connectivity-behavior correlation to find SA-related regions.•Built edge-weighted connectivity networks for public, private, and composite SA.•Characterized multi-level topographic and topological features of SA networks.•Pathological study showed multi-level connectivity disruptions in SZ and MDD. Self-awareness (SA) research is crucial for understanding cognition, social behavior, mental health, and education, but SA's underlying network architecture, particularly connectivity patterns, remains largely uncharted. We integrated meta-analytic findings with connectivity-behavior correlation analyses to systematically identify SA-related regions and connections in healthy adults. Edge-weighted networks capturing public, private, and composite SA dimensions were established, where weights represented correlation strengths between tractography-derived structural connectivities and SA levels quantified through behavioral assessments. Then, multilevel SA networks were extracted across a spectrum of correlation thresholds. Robust full-threshold analyses revealed their hierarchical continuum encompassing distinct lateralization patterns, topological transitions, and characteristic hourglass-like architectures. Pathological analysis demonstrated SA connectivity disruptions in schizophrenia (SZ) and major depressive disorder (MDD): approximately 40 % of SA-related connectivities were altered in SZ and 20 % in MDD, with 90 % of MDD alterations overlapping with SZ. While disease-specific and shared alterations were also observed in network-level topological properties, the core SA connectivity framework remained preserved in both disorders. Collectively, these findings significantly advanced our understanding of SA's neurobiological substrates and their pathological deviations. [Display omitted]

Anatomical and functional heterogeneous substantia nigra (SN) has been extensively studied in humans and animals like rhesus monkeys given its crucial role in modulating a broad range of behaviors. Increasingly important cross‐species research of SN may require connectionally homogeneous and homologous subregions of SN as objective and stable starting points from which the evolutionary characteristics of brain could be inspected. However, existing atlases of SN were all inaccurate mappings as a cross‐species connectome atlas due to inadequate homology constraint during their constructions, and arbitrary paired use of these atlases might cause unreliable findings. In this study, a reliable blind‐source cross‐species parcellation of SN was developed based on the following rationale: striatonigrostriatal circuits form major structure of nigral connectivity; different nigral components have unique striatonigrostriatal connectivity; and inter‐species corresponding human and macaque nigral components have similar striatonigrostriatal connectivity. Specifically, all voxels in human and macaque SN were grouped together and then classified based on inter‐species identically characterized striatonigrostriatal connectivity attributes. Our results delineated a pars compacta‐pars reticulate‐like parcellation and further demonstrated its reliability by illustrating best‐matched whole‐brain structural and functional connectivity profiles of inter‐species corresponding nigral subregions. Detailed inter‐species and inter‐regional differences in multi‐aspect connectivities of these nigral subregions were inspected. It is expected that this cross‐species connectome atlas of SN can offer biologically reliable cornerstones and important information to facilitate future cross‐species research. Our single‐species parcellations provided more reliable delineation of nigral subregions in human brain and filled a gap in macaque‐related research. More importantly, a reliable cross‐species parcellation scheme was developed and used to construct a cross‐species connectome atlas of human and macaque substantia nigra.

To date, reliable biomarkers remain unclear that could link functional connectivity to patients’ symptoms for detecting and predicting the process from normal aging to Alzheimer’s disease (AD) in elderly people with specific genotypes. To address this, individual-specific functional connectivity is constructed for elderly participants with/without APOE ε4 allele. Then, we utilize recursive feature selection-based machine learning to reveal individual brain-behavior relationships and to predict the symptom transition in different genotypes. Our findings reveal that compared with conventional atlas-based functional connectivity, individual-specific functional connectivity exhibits higher classification and prediction performance from normal aging to AD in both APOE ε4 groups, while no significant performance is detected when the data of two genotyping groups are combined. Furthermore, individual-specific between-network connectivity constitutes a major contributor to assessing cognitive symptoms. This study highlights the essential role of individual variation in cortical functional anatomy and the integration of brain and behavior in predicting individualized symptoms. Analysis of individual-specific functional connectivity can differentiate between normal ageing and Alzheimer Disease and individual-specific between-network connectivity constitute a major contributor for assessing cognitive symptoms in both APOE ε4 carriers and non-carriers.

To date, no reliable biomarkers are available that link individual-specific functional connectivity and patients' individualized symptoms for early detection and prediction of Alzheimer's disease (AD) in elderly people with specific genotypes. Meanwhile, functional magnetic resonance imaging (MRI) and machine learning are promising tools that can reveal the relationships between brain and behavior at individual level towards predicting the transition to AD. In this study, individual-specific functional connectivity was constructed in elderly participants with Apolipoprotein E (APOE) ε4 allele (N = 120) and without APOE ε4 allele (N = 115), respectively. In particular, machine learning based on a recursive feature selection technique was carried out to track multiple clinical symptoms among differing genotypes at individual level from normal aging (NA) and AD. It was found that the captured neuroimaging features in both APOE genotyping groups were able to distinguish the changes of clinical symptoms from NA to AD. Besides, our findings illustrated that the connections between individual-specific functional regions exhibited significantly higher correlation between estimated and observed scores in multiple clinical symptoms than those from atlas-based functional connectivity for both APOE genotyping groups, while no significant performance was detected when the data of two APOE genotyping groups were combined for the estimation models. Further, individual-specific between-network connectivity constitutes a major contributor for accessing cognitive symptoms in both APOE genotyping groups. Therefore, this study demonstrated the essential role of individual variation in cortical functional anatomy and the significance in combining brain and behavior for improving the accuracy in detection and prediction of AD in elderly people with specific genotypes.Competing Interest StatementThe authors have declared no competing interest.