Prediction of subsolid pulmonary nodule growth rate using radiomics.

BACKGROUND: Pulmonary nodule growth rate assessment is critical in the management of subsolid pulmonary nodules (SSNs) during clinical follow-up. The present study aimed to develop a model to predict the growth rate of SSNs. METHODS: A total of 273 growing SSNs with clinical information and 857 computed tomography (CT) scans were retrospectively analyzed. The images were randomly divided into training and validation sets. All images were categorized into fast-growth (volume doubling time (VDT) ≤ 400 days) and slow-growth (VDT > 400 days) groups. Models for predicting the growth rate of SSNs were developed using radiomics and clinical features. The models' performance was evaluated using the area under the curve (AUC) values for the receiver operating characteristic curve. RESULTS: The fast- and slow-growth groups included 108 and 749 scans, respectively, and 10 radiomics features and three radiographic features (nodule density, presence of spiculation, and presence of vascular changes) were selected to predict the growth rate of SSNs. The nomogram integrating radiomics and radiographic features (AUC = 0.928 and AUC = 0.905, respectively) performed better than the radiographic (AUC = 0.668 and AUC = 0.689, respectively) and radiomics (AUC = 0.888 and AUC = 0.816, respectively) models alone in both the training and validation sets. CONCLUSION: The nomogram model developed by combining radiomics with radiographic features can predict the growth rate of SSNs more accurately than traditional radiographic models. It can also optimize clinical treatment decisions for patients with SSNs and improve their long-term management.

[How to deduce the seven basic class asci of ordered tetrads in Neurospora].

Genetic analysis is an important part of undergraduate genetics teaching and tetrad analysis is unique and integral for genetic analysis of fungi. The ordered tetrad in Neurospora is an important material for genetic analysis, which can not only be used to study recombination between genes and centromeres, but also between genes themselves, as well as study the fine cross patterns between non-sister chromatids of homologous chromosomes. However, in textbooks and related professional journals, there is a lack of specific introduction to the induction methods of the seven basic class asci used in two genes analysis. In the present paper, we designed a table presenting the correlation between the three tetrad types (PD, NPD, T) and the four segregation pattern groups (Ⅰ Ⅰ, Ⅱ Ⅱ, Ⅰ Ⅱ, Ⅱ Ⅰ) to visually show the 12 possible combinations (3×4=12). Then five of them were excluded through the "×" symbol and in addition with three comments attached with the table, thus finally we obtained seven basic ascus types. We hope that this analytical method can assist the teaching of ordered tetrad analysis in Neurospora.

Therapeutic targets and biomarkers of tumor immunotherapy: response versus non-response.

Cancers are highly complex diseases that are characterized by not only the overgrowth of malignant cells but also an altered immune response. The inhibition and reprogramming of the immune system play critical roles in tumor initiation and progression. Immunotherapy aims to reactivate antitumor immune cells and overcome the immune escape mechanisms of tumors. Represented by immune checkpoint blockade and adoptive cell transfer, tumor immunotherapy has seen tremendous success in the clinic, with the capability to induce long-term regression of some tumors that are refractory to all other treatments. Among them, immune checkpoint blocking therapy, represented by PD-1/PD-L1 inhibitors (nivolumab) and CTLA-4 inhibitors (ipilimumab), has shown encouraging therapeutic effects in the treatment of various malignant tumors, such as non-small cell lung cancer (NSCLC) and melanoma. In addition, with the advent of CAR-T, CAR-M and other novel immunotherapy methods, immunotherapy has entered a new era. At present, evidence indicates that the combination of multiple immunotherapy methods may be one way to improve the therapeutic effect. However, the overall clinical response rate of tumor immunotherapy still needs improvement, which warrants the development of novel therapeutic designs as well as the discovery of biomarkers that can guide the prescription of these agents. Learning from the past success and failure of both clinical and basic research is critical for the rational design of studies in the future. In this article, we describe the efforts to manipulate the immune system against cancer and discuss different targets and cell types that can be exploited to promote the antitumor immune response.

Systems-Based Interactome Analysis for Hematopoiesis Effect of Angelicae sinensis Radix: Regulated Network of Cell Proliferation towards Hemopoiesis.

OBJECTIVE: To explore the molecular-level mechanism on the hematopoiesis effect of Angelicae sinensis Radix (ASR) with systems-based interactome analysis. METHODS: This systems-based interactome analysis was designed to enforce the workflow of "ASR (herb)→compound→target protein→internal protein actions→ending regulated protein for hematopoiesis". This workflow was deployed with restrictions on regulated proteins expresses in bone marrow and anemia disease and futher validated with experiments. RESULTS: The hematopoiesis mechanism of ASR might be accomplished through regulating pathways of cell proliferation towards hemopoiesis with cross-talking agents of spleen tyrosine kinase (SYK), Janus kinase 2 (JAK2), and interleukin-2-inducible T-cell kinase (ITK). The hematopoietic function of ASR was also validated by colony-forming assay performed on mice bone marrow cells. As a result, SYK, JAK2 and ITK were activated. CONCLUSION: This study provides a new approach to systematically study and predict the therapeutic mechanism for ASR based on interactome analysis towards biological process with experimental validations.

Associations of gene­wide SNPs in SNAI1 and TWIST1 with breast cancer and ovarian cancer susceptibility among Chinese Han women.

Extensive evidence suggests that the genetic etiologies of breast cancer (BC) and ovarian cancer (OC) show a certain degree of similarity. This study aimed to find out whether the single nucleotide polymorphisms (SNPs) of genes SNAI1 and TWIST1 may affect BC and OC susceptibility. A total of 7 tagging­SNPs (tSNPs) were directly genotyped in 1,161 BC cases, 286 OC cases and 1,273 cancer­free controls among Chinese Han women. Twenty­eight variants in these 2 genes were genotyped by 'in silico' genotype imputation. Logistic regression (LR) revealed that tSNPs SNAI1 rs6125849, TWIST1 rs4721746 and TWIST1 rs4721745 were protective genetic variants for BC/OC. Allelic association tests of gene­wide SNPs demonstrated that the minor alleles of SNAI1 rs6125849, TWIST1 rs4721745 and TWIST1 rs11973396 were strongly associated with BC/OC susceptibility. Multivariate LR presented that SNAI1 rs6125849, TWIST1 rs4721745, rs4721746 and rs11973396 affected BC/OC susceptibility independently, and women harboring all four protective genoytpes had the lowest risk. Multifactor dimensionality reduction analysis further showed that SNAI1 rs6125849 and TWIST1 rs4721745 had the strongest synergistic interaction. Functional annotation predicted that the minor alleles of SNAI1 rs6125849 and TWIST1 rs4721745 altered their binding affinities with transcription factors E2F6 and TCF11­MafG respectively. These results indicate that genetic variants in SNAI1 and TWIST1, most probably SNAI1 rs6125849 and TWIST1 rs4721745, may modulate BC and OC susceptibility.

Genetic Polymorphisms of TGFB1, TGFBR1, SNAI1 and TWIST1 Are Associated with Endometrial Cancer Susceptibility in Chinese Han Women.

Endometrial cancer (EC) is a complex disease involving multiple gene-gene and gene-environment interactions. TGF-ß signaling plays pivotal roles in EC development. This study aimed to investigate whether the genetic polymorphisms of TGF-ß signaling related genes TGFB1, TGFBR1, SNAI1 and TWIST1 contribute to EC susceptibility. Using the TaqMan Genotyping Assay, 19 tagging-SNPs of these four genes were genotyped in 516 EC cases and 707 controls among Chinese Han women. Logistic regression (LR) showed that the genetic variants of TGFB1 rs1800469, TGFBR1 rs6478974 and rs10733710, TWIST1 rs4721745 were associated with decreased EC risk, and these four loci showed a dose-dependent effect (Ptrend < 0.0001). Classification and regression tree (CART) demonstrated that women carrying both the genotypes of TGFBR1 rs6478974 TT and rs10512263 TC/CC had the highest risk of EC (aOR = 7.86, 95% CI = 3.42-18.07, P<0.0001). Multifactor dimensionality reduction (MDR) revealed that TGFB1 rs1800469 plus TGFBR1 rs6478974 was the best interactional model to detect EC risk. LR, CART and MDR all revealed that TGFBR1 rs6478974 was the most important protective locus for EC. In haplotype association study, TGFBR1 haplotype CACGA carrier showed the lowest EC risk among women with longer menarche-first full term pregnancy intervals (˃11 years) and BMI˂24 (aOR = 0.39, 95% CI = 0.17-0.90, P = 0.0275). These results suggest that polymorphisms in TGFB1, TGFBR1, SNAI1 and TWIST1 may modulate EC susceptibility, both separately and corporately.

Music therapy improves sleep quality in acute and chronic sleep disorders: a meta-analysis of 10 randomized studies.

OBJECTIVE: To evaluate the efficacy of music therapy for acute and chronic sleep disorders in adults. DESIGN: Systematic review and meta-analysis. DATA SOURCES: A systematic search of publications in PubMed, Embase, and the Cochrane Library without language restriction was performed. REVIEW METHODS: Studies with randomized controlled design and adult participants were included if music was applied in a passive way to improve sleep quality. Subgroup analysis was conducted to explore the sources of heterogeneity. RESULTS: Ten studies involving 557 participants were identified. The sleep quality was improved significantly by music (standard mean difference: -0.63; 95% CI: -0.92 to -0.34; p<0.001), with significant heterogeneity across studies. Subgroup analysis found heterogeneity between subgroups with objective or subjective assessing methods of sleep quality, and between subgroups with difference follow-up durations. No evidence of publication bias was observed. CONCLUSION: Music can assist in improving sleep quality of patients with acute and chronic sleep disorders. For chronic sleep disorders, music showed a cumulative dose effect and a follow-up duration more than three weeks is necessary for assessing its efficacy.