医学专业英语

One of the greatest challenges to cancer therapy is tumor cell plasticity. Cancer cells can rapidly alter their phenotype to promote survival and evade immune cell attack, while the plasticity of other cells in the tumor microenvironment (such as immune cells, which need to be able to respond to a diverse range of bodily threats) can be leveraged to further promote tumor growth and progression. This Essay discusses the mutual plasticity of cancer and immune cells, with a focus on epithelial–mesenchymal plasticity in tumor cells, and explores how this interplay contributes to tumor progression and can be targeted therapeutically.

Metastasis is the predominant cause of cancer mortality, primarily driven by complex tumor–host interactions within specialized metastatic niches. Recent advances in single-cell technologies have provided unprecedented insights into metastatic niche formation, evolution and function, including how primary tumors precondition distant organs for metastases and how disseminated tumor cells dynamically interact with host cells to modulate their environments. Integrated single-cell studies across multiple cancer types have also revealed divergent and convergent metastatic adaptation strategies. These findings collectively highlight metastasis as a dynamic, cooperative process shaped by intricate tumor–host interactions, and provide a foundation for novel therapeutic strategies targeting components of the metastatic microenvironment.

The automated generation of free-text radiology reports is crucial for improving diagnosis and treatment in clinical practice. The latest chest X-ray report generation models utilize large vision language model (LVLM) architectures, which demand a higher level of interpretability for clinical deployment. Uncertainty estimation scores can assist clinicians in evaluating the reliability of these model outputs and promoting broader adoption of automated systems. In this paper, we conduct a comprehensive evaluation of the correlation between 16 LLM uncertainty scores and 6 radiology report evaluation metrics across 4 state-of-the-art LVLMs for CXR report generation. Our findings show a strong Pearson correlation, ranging from 0.4 to 0.6 on a scale from -1 to 1, for several models. We provide a detailed analysis of these uncertainty scores and evaluation metrics, offering insights in applying these methods in real clinical settings. This study is the first to evaluate LLM-based uncertainty estimation scores for X-ray report generation LVLM models, establishing a benchmark and laying the groundwork for their adoption in clinical practice.

Background: The American Heart Association recently issued guidelines introducing the concept of cardiovascular–kidney–metabolic (CKM) syndrome to emphasize the importance of multidisciplinary approaches to prevention, risk stratification, and treatment for these diseases. This study assessed the prevalence of CKM syndrome stages and the mortality risk associated with its components in a large Asian cohort.

Methods and findings: We analyzed a retrospective cohort of 515,602 participants aged ≥20 years from a health screening program conducted between 1996 and 2017 in Taiwan. We assessed the associations of all-cause mortality, cardiovascular disease (CVD) mortality, and cause-specific mortality with CKM stages and its components—hypertension, diabetes mellitus, chronic kidney disease (CKD), metabolic syndrome, and hyperlipidemia. All participants were followed for a median of 16.5 years (interquartile range: 11.5, 21.2 years). Multivariate Cox proportional hazards models, adjusted for age, sex, educational level, smoking status, alcohol drinking status, and physical activity groups, were used to calculate hazard ratios (HRs). We used Chiang’s life table method to estimate years of life lost due to each CKM component. Among all participants, 257,535 (49.9%) were female. The majority of participants ( n = 368,578 participants, (71.5%)) met criteria for CKM syndrome, with prevalence rates of 19.5%, 46.3%, 1.9%, and 3.8% for stages 1, 2, 3, and 4, respectively. CKM syndrome was associated with higher risks of all-cause mortality (HR: 1.33; 95% confidence interval, CI: 1.28, 1.39), CVD mortality (HR: 2.81; 95% CI: 2.45, 3.22), and incident end-stage kidney disease (ESKD) (HR: 10.15; 95% CI: 7.54, 13.67). Each additional CKM component was associated with a 22% increase in the risk of all-cause mortality (HR: 1.22; 95% CI: 1.21, 1.23), a 37% increase in the risk of CVD mortality (HR: 1.37; 95% CI: 1.35, 1.40) compared with those without any CKM components. In addition, each additional component reduced average life expectancy by 3 years. The population-attributable fractions of CKM syndrome were 18.7% (95% CI: 15.8, 21.7) for all-cause mortality and 55.0% (95% CI: 49.0, 60.4) for CVD mortality. We estimated that failing to include CKD in CKM syndrome could result in the missed attribution of 11% of CVD deaths. The primary limitation is that our analysis relied on baseline measurements only, without accounting for longitudinal changes.

Conclusions: In the large cohort study, the prevalence of CKM syndrome and its components were associated with risks of all-cause mortality, CVD mortality, and ESKD. These findings highlight the clinical need for integrated care within CKM health.

Background: Depression is associated with a range of adverse physical health outcomes. We aimed to quantify the association between depression and the subsequent rate of accrual of long-term physical health conditions in middle and older age.

Methods and findings: We included 172,556 participants from the UK Biobank (UKB) cohort study, aged 40–71 years old at baseline assessment (2006–2010), who had linked primary care data available. Using self-report, primary care, hospital admission, cancer registry, and death records, we ascertained 69 long-term physical health conditions at both UKB baseline assessment and during a mean follow-up of 6.9 years. We used quasi-Poisson models to estimate associations between history of depression at baseline and subsequent rate of physical condition accrual. Within our cohort, 30,770 (17.8%) had a history of depression. Compared to those without depression, participants with depression had more physical conditions at baseline (mean 2.9 [SD 2.3] versus 2.1 [SD 1.9]) and accrued additional physical conditions at a faster rate (mean 0.20 versus 0.16 additional conditions/year during follow-up). After adjustment for age and sex, participants with depression accrued physical morbidities at a faster rate than those without depression (RR 1.32, 95% confidence interval [CI] [1.31, 1.34]). After adjustment for all sociodemographic characteristics, the rate of condition accrual remained higher in those with versus without depression (RR 1.30, 95% CI [1.28, 1.32]). This association attenuated but remained statistically significant after additional adjustment for baseline condition count and social/lifestyle factors (RR 1.10, 95% CI [1.09, 1.12]). The main limitation of this study is healthy volunteer selection bias, which may limit generalisability of findings to the wider population.

Conclusions: Middle-aged and older adults with a history of depression have more long-term physical health conditions at baseline and accrue additional physical conditions at a faster rate than those without a history of depression. Our findings highlight the importance of integrated approaches to managing both mental and physical health outcomes.

Background: Increasing evidence suggests that insomnia plays an important role in the development of depression, supporting insomnia intervention as a promising approach to prevent depression in youth. This randomized controlled trial evaluated the effectiveness of app-based cognitive behavioral therapy for insomnia (CBT-I) in preventing future onset of major depressive disorder (MDD) in youth.

Methods and findings: This was a randomized, assessor-blind, parallel group-controlled trial in Chinese youth (aged 15−25 years) with insomnia disorder and subclinical depressive symptoms. Participants were randomly assigned (1:1) to 6-week app-based CBT-I or 6-week app-based health education (HE) delivered through smartphones. Online assessments and telephone clinical interviews were conducted at baseline, post-intervention, 6- and 12-month follow-ups. The primary outcome was time to onset of MDD. The secondary outcomes included depressive symptoms and insomnia at both symptom and disorder levels. Between September 9, 2019, and November 25, 2022, 708 participants (407 females [57%]; mean age, 22.1 years [SD = 1.9]) were randomly allocated to app-based CBT-I group ( n = 354) or app-based HE group ( n = 354). Thirty-seven participants (10%) in the intervention group and 62 participants (18%) in the control group developed new-onset MDD throughout the 12-month follow-up, with a hazard ratio of 0.58 (95% confidence interval 0.38–0.87; p = 0.008). The number needed to treat to prevent MDD at 1 year was 10.9 (6.8–26.6). The app-based CBT-I group has higher remission rates of insomnia disorder than the controls at post-intervention (52% versus 28%; relative risk 1.83 [1.49–2.24]; p < 0.001) and throughout 12-month follow-up. In addition, the CBT-I group reported a greater decrease in depressive (adjusted difference −1.0 [−1.6 to −0.5]; Cohen’s d = 0.53; p < 0.001) and insomnia symptoms (−2.0 [−2.7 to −1.3], d = 0.78; p < 0.001) than the controls at post-intervention and throughout 6-month follow-up. Insomnia was a mediator of intervention effects on depression. No adverse events related to the interventions were reported.

Conclusions: App-based CBT-I is effective in preventing future onset of major depression and improving insomnia outcomes among youth with insomnia and subclinical depression. These findings highlight the importance of targeting insomnia to prevent the onset of MDD and emphasize the need for wider dissemination of digital CBT-I to promote sleep and mental health in the youth population.

Trial registration: ClinicalTrials.Gov ( NCT04069247 ).