A scoping review of cardiovascular risk factor screening rates in general or family practice attendees living with severe mental ill-health.

BACKGROUND: Primary care is essential to address the unmet physical health needs of people with severe mental ill-health. Continued poor cardiovascular health demands improved screening and preventive care. No previous reviews have examined primary care cardiovascular screening rates for people living with severe mental ill-health; termed in the literature "severe mental illness". METHODS: A scoping review following Joanna Briggs Institute methodology was conducted. Cardiovascular risk factor screening rates in adults with severe mental ill-health were examined in general or family practices (as the main delivery sites of primary care). Literature published between 2001 and 2023 was searched using electronic databases including Medline, Embase, Web of Science, PsychINFO and CINAHL. Two reviewers independently screened titles and abstracts and conducted a full-text review. The term "severe mental illness" was applied as the term applied in the literature over the past decades. Study information, participant details and cardiovascular risk factor screening rates for people with 'severe mental illness' were extracted and synthesised. RESULTS: Thirteen studies were included. Nine studies were from the United Kingdom and one each from Canada, Spain, New Zealand and the Netherlands. The general and/or family practice cardiovascular disease screening rates varied considerably across studies, ranging from 0 % to 75 % for people grouped within the term "severe mental illness". Lipids and blood pressure were the most screened risk factors. CONCLUSIONS: Cardiovascular disease screening rates in primary care settings for adults living with severe mental ill-health varied considerably. Tailored and targeted cardiovascular risk screening will enable more comprehensive preventive care to improve heart health outcomes and address this urgent health inequity.

Electron-beam writing of a relaxor ferroelectric polymer for multiplexing information storage and encryption.

To meet the strong demand for high-level encryption security, several efforts have been focused on developing new encryption techniques with high density and data security. Herein we employed a template-free electron beam lithography (EBL) technique to write various nanopatterns on poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) (P(VDF-TrFE-CTFE)) films and applied it to electron-beam/electric multiplexing memory. Furthermore, electron beams can arbitrarily tailor down the domain structure evolutions and dipole directions, as proved by a combination of AFM-IR and PFM. Finally, our devices could function concurrently as an electron-beam write-only-memory (EB-WOM) and FeRAM, where the information could be encoded with the metastable phase evolutions from the ferroelectric phase to the paraelectric phase and variable bi-level ferroelectric signals. Our systematic study provides an inspiring idea for the design of information encryption devices with high-security requirements in flexible electronic fields.

Altered dynamic functional connectivity of insular subregions could predict symptom severity of male patients with autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by difficulties with social communication and restricted or repetitive patterns of behavior. This disorder was characterized by widespread abnormalities involving distributed brain networks. As one such key network node, the insular cortex has been regarded as a research focus of ASD neuropathology. The insula is a functionally complex brain structure. However, it is not fully clear if dynamic characteristics of resting-state functional magnetic resonance imaging (R-fMRI) signals in insular heterogeneous could be used to depict abnormalities in ASD. To address this question, we investigated dynamic functional connectivity (dFC) of 12 insular subregions. Data were obtained from 44 individuals with ASD and 65 typically developing age-matched controls (TDC). We assessed dFC by sliding-window method and quantified its temporal variability. Multivariable linear regression models were constructed to determine whether dFC support complementary information about symptom severity of individuals with ASD rather than static functional connectivity (sFC). The results showed that individuals with ASD exhibited dFC and sFC alterations in distinct insular subregions. Some brain regions showed only abnormal dFC but not sFC with insular subregions. These abnormal dFC could significantly predict the symptom severity of individuals with ASD. Our findings might advance our knowledge about the potential of insular heterogeneity and dynamic characteristics in understanding the neuropathology mechanism of ASD and in developing neuroimaging biomarkers for clinical applications.

Comprehensive analyses reveal TKI-induced remodeling of the tumor immune microenvironment in EGFR/ALK-positive non-small-cell lung cancer.

Tyrosine kinase inhibitors (TKI) play a pivotal role in the treatment of non-small-cell lung cancer (NSCLC) with mutations in epidermal growth factor receptor (EGFR) and rearrangements in anaplastic lymphoma kinase (ALK). However, the influences of TKIs on the tumor immune microenvironment (TIM), especially dynamic changes of responders, have not yet been fully elucidated. Therefore, RNA sequencing and whole-exome sequencing were performed on EGFR/ALK-positive NSCLC samples before and after TKI treatment. In combination with neoantigen and mutational-load estimations, xCell and single-sample gene set enrichment analysis (ssGSEA) were used to assess tumor immune-cell infiltration and activity. Furthermore, weighted-gene correlation network analysis and the bottleneck method were used to identify the hub genes that affected treatment-related immune responses. We found that TKI treatment remodeled the TIM in treatment-responsive samples. Profound increases in the rate of anti-tumor cell infiltration and cytotoxicity was observed following TKI treatment, while antigen presentation was limited in ALK-rearranged samples. However, no significant change in anti-tumor cell infiltration or cytotoxicity was found between pre-treatment and post-progression samples. Subsequently, we found that neurofilament heavy (NEFH) mutations were enriched in samples after TKI treatment and were associated with reduced neutrophil infiltration. The cytotoxicity of EGFR-mutant NSCLCs with co-driver TP53 mutation and ALK-rearranged samples with wild-type TP53 seems to be more easily induced by TKI. Finally, the immune-associated score generated by hub genes was positively correlated with immune infiltration, immune activation, and a favorable prognosis. In conclusion, the dynamic changes in the TIM provide clues to drug selection and timing for TKI-immunotherapy combinations.

Tumor microenvironment evaluation promotes precise checkpoint immunotherapy of advanced gastric cancer.

BACKGROUND: Durable efficacy of immune checkpoint blockade (ICB) occurred in a small number of patients with metastatic gastric cancer (mGC) and the determinant biomarker of response to ICB remains unclear. METHODS: We developed an open-source TMEscore R package, to quantify the tumor microenvironment (TME) to aid in addressing this dilemma. Two advanced gastric cancer cohorts (RNAseq, N=45 and NanoString, N=48) and other advanced cancer (N=534) treated with ICB were leveraged to investigate the predictive value of TMEscore. Simultaneously, multi-omics data from The Cancer Genome Atlas of Stomach Adenocarcinoma (TCGA-STAD) and Asian Cancer Research Group (ACRG) were interrogated for underlying mechanisms. RESULTS: The predictive capacity of TMEscore was corroborated in patient with mGC cohorts treated with pembrolizumab in a prospective phase 2 clinical trial (NCT02589496, N=45, area under the curve (AUC)=0.891). Notably, TMEscore, which has a larger AUC than programmed death-ligand 1 combined positive score, tumor mutation burden, microsatellite instability, and Epstein-Barr virus, was also validated in the multicenter advanced gastric cancer cohort using NanoString technology (N=48, AUC=0.877). Exploration of the intrinsic mechanisms of TMEscore with TCGA and ACRG multi-omics data identified TME pertinent mechanisms including mutations, metabolism pathways, and epigenetic features. CONCLUSIONS: Current study highlighted the promising predictive value of TMEscore for patients with mGC. Exploration of TME in multi-omics gastric cancer data may provide the impetus for precision immunotherapy.