Value of circulating tumor cell assisting low-dose computed tomography in screening pulmonary nodules based on existing liquid biopsy techniques: a systematic review with meta-analysis and trial sequential analysis.

OBJECTIVE: This study aims to assess the diagnostic utility of circulating tumor cells (CTCs) in conjunction with low-dose computed tomography (LDCT) for differentiating between benign and malignant pulmonary nodules and to substantiate the foundation for their integration into clinical practice. METHODS: A systematic literature review was performed independently by two researchers utilizing databases including PubMed, Web of Science, The Cochrane Library, Embase, and Medline, to collate studies up to September 15, 2023, that investigated the application of CTCs in diagnosing pulmonary nodules. A meta-analysis was executed employing Stata 15.0 and Revman 5.4 to calculate the pooled sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and the area under the receiver operating characteristic curve (AUC). Additionally, trial sequential analysis was conducted using dedicated TSA software. RESULTS: The selection criteria identified 16 studies, encompassing a total of 3409 patients. The meta-analysis revealed that CTCs achieved a pooled sensitivity of 0.84 (95% CI 0.80 to 0.87), specificity of 0.80 (95% CI 0.73 to 0.86), PLR of 4.23 (95% CI 3.12 to 5.72), NLR of 0.20 (95% CI 0.16 to 0.25), DOR of 20.92 (95% CI 13.52 to 32.36), and AUC of 0.89 (95% CI 0.86 to 0.93). CONCLUSIONS: Circulating tumor cells demonstrate substantial diagnostic accuracy in distinguishing benign from malignant pulmonary nodules. The incorporation of CTCs into the diagnostic protocol can significantly augment the diagnostic efficacy of LDCT in screening for malignant lung diseases.

Contactless mechanical stimulation of the skin using shear waves.

The skin, the outermost organ of the human body, is vital for sensing and responding to stimuli through mechanotransduction. It is constantly exposed to mechanical stress. Consequently, various mechanical therapies, including compression, massage, and microneedling, have become routine practices for skin healing and regeneration. However, these traditional methods require direct skin contact, restricting their applicability. To address this constraint, we developed shear wave stimulation (SWS), a contactless mechanical stimulation technique. The effectiveness of SWS was compared with that of a commercial compression bioreactor used on reconstructed skin at various stages of maturity. Despite the distinct stimulus conditions applied by the two methods, SWS yielded remarkable outcomes, similar to the effects of the compression bioreactor. It significantly increased the shear modulus of tissue-engineered skin, heightened the density of collagen and elastin fibers, and resulted in an augmentation of fibroblasts in terms of their number and length. Notably, SWS exhibited diverse effects in the low- and high-frequency modes, highlighting the importance of fine-tuning the stimulus intensity. These results unequivocally demonstrated the capability of SWS to enhance the mechanical functions of the skin in vitro, making it a promising option for addressing wound healing and stretch mark recovery.

Estrogen Receptor Mutations as Novel Targets for Immunotherapy in Metastatic Estrogen Receptor-positive Breast Cancer.

Estrogen receptor-positive (ER+) breast cancer is not considered immunogenic and, to date, has been proven resistant to immunotherapy. Endocrine therapy remains the cornerstone of treatment for ER+ breast cancers. However, constitutively activating mutations in the estrogen receptor alpha (ESR1) gene can emerge during treatment, rendering tumors resistant to endocrine therapy. Although these mutations represent a pathway of resistance, they also represent a potential source of neoepitopes that can be targeted by immunotherapy. In this study, we investigated ESR1 mutations as novel targets for breast cancer immunotherapy. Using machine learning algorithms, we identified ESR1-derived peptides predicted to form stable complexes with HLA-A*0201. We then validated the binding affinity and stability of the top predicted peptides through in vitro binding and dissociation assays and showed that these peptides bind HLA-A*0201 with high affinity and stability. Using tetramer assays, we confirmed the presence and expansion potential of antigen-specific CTLs from healthy female donors. Finally, using in vitro cytotoxicity assays, we showed the lysis of peptide-pulsed targets and breast cancer cells expressing common ESR1 mutations by expanded antigen-specific CTLs. Ultimately, we identified five peptides derived from the three most common ESR1 mutations (D538G, Y537S, and E380Q) and their associated wild-type peptides, which were the most immunogenic. Overall, these data confirm the immunogenicity of epitopes derived from ESR1 and highlight the potential of these peptides to be targeted by novel immunotherapy strategies. SIGNIFICANCE: Estrogen receptor (ESR1) mutations have emerged as a key factor in endocrine therapy resistance. We identified and validated five novel, immunogenic ESR1-derived peptides that could be targeted through vaccine-based immunotherapy.

Associations of Lipoprotein(a) Level with Cerebral Small Vessel Disease in Patients with Alzheimer's Disease.

BACKGROUND: This study aimed to examine the association of lipoprotein(a) [Lp(a)] level with the burden of cerebral small vessel disease (CSVD) in patients with Alzheimer's disease (AD). METHODS: Data from 111 consecutive patients with AD admitted to Nanjing First Hospital from 2015 to 2022 were retrospectively analyzed in this study. Serum Lp(a) concentrations were grouped into tertiles (T1-T3). Brain magnetic resonance imaging (MRI) was rated for the presence of CSVD, including enlarged perivascular spaces (EPVS), lacunes, white-matter lesions, and cerebral microbleeds (CMBs). The CSVD burden was calculated by summing the scores of each MRI marker at baseline. A binary or ordinal logistic regression model was used to estimate the relationship of serum Lp(a) levels with CSVD burden and each MRI marker. RESULTS: Patients with higher tertiles of Lp(a) levels were less likely to have any CSVD (T1, 94.6%; T2, 78.4%; T3, 66.2%; p = 0.013). Multivariable analysis found that Lp(a) levels were inversely associated with the presence of CSVD (T2 vs. T1: adjusted odds ratio [aOR] 0.132, 95% confidence interval [CI] 0.018-0.946, p = 0.044; T3 vs. T1: aOR 0.109, 95% CI 0.016-0.737, p = 0.023) and CSVD burden (T3 vs. T1: aOR 0.576, 95% CI 0.362-0.915, p = 0.019). The independent relationship between Lp(a) levels and individual CSVD features was significant for moderate-to-severe EPVS in the centrum semiovale (T2 vs. T1: aOR 0.059, 95% CI 0.006-0.542, p = 0.012; T3 vs. T1: aOR 0.029, 95% CI 0.003-0.273, p = 0.002) and CMBs (T3 vs. T1: aOR 0.144, 95% CI 0.029-0.716, p = 0.018). CONCLUSIONS: In this study, serum Lp(a) level was inversely associated with CSVD in AD patients.

Based on CT radiomics model for predicting the response to first-line chemotherapy of diffuse large B-cell lymphoma / 中华肿瘤杂志

Objective: To investigate the potential value of CT Radiomics model in predicting the response to first-line chemotherapy in diffuse large B-cell lymphoma (DLBCL). Methods: Pre-treatment CT images and clinical data of DLBCL patients treated at Shanxi Cancer Hospital from January 2013 to May 2018 were retrospectively analyzed and divided into refractory patients (73 cases) and non-refractory patients (57 cases) according to the Lugano 2014 efficacy evaluation criteria. The least absolute shrinkage and selection operator (LASSO) regression algorithm, univariate and multivariate logistic regression analyses were used to screen out clinical factors and CT radiomics features associated with efficacy response, followed by radiomics model and nomogram model. Receiver operating characteristic (ROC) curve, calibration curve and clinical decision curve were used to evaluate the models in terms of the diagnostic efficacy, calibration and clinical value in predicting chemotherapy response. Results: Based on pre-chemotherapy CT images, 850 CT texture features were extracted from each patient, and 6 features highly correlated with the first-line chemotherapy effect of DLBCL were selected, including 1 first order feature, 1 gray level co-occurence matrix, 3 grey level dependence matrix, 1 neighboring grey tone difference matrix. Then, the corresponding radiomics model was established, whose ROC curves showed AUC values of 0.82 (95% CI: 0.76-0.89) and 0.73 (95% CI: 0.60-0.86) in the training and validation groups, respectively. The nomogram model, built by combining validated clinical factors (Ann Arbor stage, serum LDH level) and CT radiomics features, showed an AUC of 0.95 (95% CI: 0.90-0.99) and 0.91 (95% CI: 0.82-1.00) in the training group and the validation group, respectively, with significantly better diagnostic efficacy than that of the radiomics model. In addition, the calibration curve and clinical decision curve showed that the nomogram model had good consistency and high clinical value in the assessment of DLBCL efficacy. Conclusion: The nomogram model based on clinical factors and radiomics features shows potential clinical value in predicting the response to first-line chemotherapy of DLBCL patients.

Divergent effects of lycopene on pancreatic alpha and beta cells / 生理学报

Lycopene is an antioxidant which has potential anti-diabetic activity, but the cellular mechanisms have not been clarified. In this study, different concentrations of lycopene were used to treat pancreatic alpha and beta cell lines, and the changes of cell growth, cell apoptosis, cell cycle, reactive oxygen species (ROS), ATP levels and expression of related cytokines were determined. The results exhibited that lycopene did not affect cell growth, cell apoptosis, cell cycle, ROS and ATP levels of alpha cells, while it promoted the growth of beta cells, increased the ratio of S phase, reduced the ROS levels and increased the ATP levels of beta cells. At the same time, lycopene treatment elevated the mRNA expression levels of tnfα, tgfβ and hif1α in beta cells. These findings suggest that lycopene plays cell-specific role and activates pancreatic beta cells, supporting its application in diabetes therapy.