Nighttime sleep and daytime sleepiness patterns among left ventricular assist device patients.

Despite the high prevalence of sleep disturbance in the heart failure population, information about its consequence on daytime function in patients with left-ventricular assist devices (LVADs) is limited. This study examined the nighttime and daytime sleep patterns and changes from pre-implant to 6 months post-implant. This study included 32 LVAD patients. Demographics, nighttime and daytime sleep variables were collected pre-implant and at 1, 3, and 6 months post-implant. Wrist actigraphy and self-report questionnaires measured objective and subjective sleep, respectively. Objective nighttime sleep data were sleep efficiency (SE), sleep latency (SL), total sleep time (TST), wake after sleep onset (WASO), and sleep fragmentation (SF). Objective daytime sleep data were nap times. Self-reported Subjective Sleep Quality Scale (SSQS) and Stanford Sleepiness Scale (SSS) were subjective measures. Increased SF and WASO scores and decreased TST and SE scores were found pre-LVAD implant, indicative of poor sleep quality. TST, SE, naptime and SSQS scores were higher at 3 and 6 months post-implant compared to baseline. Decreases in TST and SF scores were observed at 3 and 6 months post-implant along with increases in SSS scores. Increasing SSS scores and decreasing overall scores from pre- and up to 6 months post-implant suggest improvement in daytime function. This study provides information on sleep-daytime function in the LVAD patient population. Improvements in daytime sleepiness do not imply "good" sleep quality, consistent with the extant knowledge in LVAD literature. Future investigations should elucidate the mechanism by which sleep-daytime function influences quality of life.

Tumor Microenvironment and Genes Affecting the Prognosis of Temozolomide-Treated Glioblastoma.

Glioblastoma (GBM) is the most frequent primary brain tumor in adults and has a poor prognosis due to its resistance to Temozolomide (TMZ). However, there is limited research regarding the tumor microenvironment and genes related to the prognosis of TMZ-treated GBM patients. This study aimed to identify putative transcriptomic biomarkers with predictive value in patients with GBM who were treated with TMZ. Publicly available datasets from The Cancer Genome Atlas and Gene Expression Omnibus were analyzed using CIBERSORTx and Weighted Gene Co-expression Network Analysis (WGCNA) to obtain types of highly expressed cell types and gene clusters. Differentially Expressed Genes analysis was performed and was intersected with the WGCNA results to obtain a candidate gene list. Cox proportional-hazard survival analysis was performed to acquire genes related to the prognosis of TMZ-treated GBM patients. Inflammatory microglial cells, dendritic cells, myeloid cells, and glioma stem cells were highly expressed in GBM tissue, and ACP7, EPPK1, PCDHA8, RHOD, DRC1, ZIC3, and PRLR were significantly associated with survival. While the listed genes have been previously reported to be related to glioblastoma or other types of cancer, ACP7 was identified as a novel gene related to the prognosis of GBM. These findings may have potential implications for developing a diagnostic tool to predict GBM resistance and optimize treatment decisions.