Publications by authors named "Ailin Lan"

Objective: Compared with other diseases with similar global burdens, little is known about how lifestyle factors other than smoking affect respiratory health, and few studies have systematically investigated the combined associations between diet and respiratory health. The aim of this research was to examine the Dietary Inflammation Index (DII), Healthy Eating Index (HEI)-2015, and individual food and nutrient associations with multiple respiratory outcomes.

Methods: This study combined a cross-sectional study with a prospective cohort study to systematically evaluate data from adults aged 40 years or older ( = 13,227) from 4 National Health and Nutrition Examination Survey cycles (2005-2006 through 2011-2012) with lung function measures in a subset ( = 6337).

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Aristolochic acid I (AAI), which is one of the main forms of aristolochic acid, can cause aristolochic acid nephropathy. Abnormal activation or inhibition of the Wnt7b/β-catenin signaling pathway may lead to the occurrence and development of kidney disease. This study aimed to investigate the effect of the Wnt7b/β-catenin signaling pathway on the damage and repair processes of renal tubular epithelial cells (RTECs) using mouse and zebrafish models of acute aristolochic acid intoxication.

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In this study, we aimed to investigate the mechanism by which fluoride exposure causes bone damage and the relationship with the loss of dorsal longitudinal anastomotic vessel (DLAV) formation in zebrafish larvae to further understanding of skeletal fluorosis. We assessed the development of chondrogenesis, osteogenesis, and DLAV angiogenesis, and reactive oxygen species (ROS) in zebrafish larvae subjected to blank control group (Con), low-fluoride group (LF), and high-fluoride group (HF). Abnormal development of the cartilage area, bone mineralization accompanied with abnormal mRNA expression of osteoblast-related OC, ALP, and Runx2b genes and osteoclast-related OPG and RANKL genes, and abnormal DLAV angiogenesis and ROS levels in zebrafish larvae were affected to varying degrees with the increase of fluoride exposure.

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Article Synopsis
  • - Endocrine resistance is a major issue for patients with hormone receptor-positive, HER2-negative breast cancer, often linked to dysregulation of estrogen receptor (ER) and ERBB signaling pathways, though how these pathways interact is not fully understood.
  • - The study investigates SMAD4's role in this resistance, finding that lower SMAD4 levels in breast cancer tissues correlate with poor patient outcomes, and that its depletion triggers resistance to endocrine therapy by enhancing ER and ERBB signaling.
  • - The results suggest that targeting SMAD4 alongside ER, ERBB, and autophagy pathways could offer a new treatment approach for patients facing endocrine resistance in HR+ HER2- breast cancer.
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  • The study investigates how depressive symptoms and sleep disturbances impact mortality among cancer survivors, using data from nearly 3,000 participants from the National Health and Nutrition Examination Survey (NHANES) collected between 2007 and 2018.
  • Results showed that higher scores on the Patient Health Questionnaire (PHQ-9), indicating more severe depression, were linked to increased risks of dying from all causes, particularly for those scoring 10 or higher.
  • Interestingly, individual sleep disturbances did not significantly affect mortality risk, but when combined with higher depressive symptoms, they did show an increased risk for all-cause and cancer-specific mortality compared to individuals with lower depressive symptoms and no sleep issues.
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  • Utrophin (UTRN) is identified as a potential tumor suppressor in breast cancer, showing decreased expression in cancerous tissues compared to normal ones and correlating with better patient outcomes.* -
  • Research revealed that high UTRN levels are linked to increased sensitivity to tamoxifen, a common breast cancer treatment, suggesting low UTRN expression may lead to drug resistance.* -
  • UTRN is proposed as a promising diagnostic biomarker for breast cancer, with associations to immune cell activity and the ability to enhance diagnostic accuracy and clinical decisions.*
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  • Breast cancer is a prevalent malignancy worldwide, and early detection of tumor recurrence post-treatment can enhance patient survival rates.
  • This study focuses on creating machine learning models to forecast significant events (tumor relapse, secondary tumors, or patient death) in breast cancer patients after neoadjuvant chemotherapy.
  • Results indicate that the random forest model outperforms logistic regression in terms of sensitivity, specificity, and overall performance for predicting these events at one and five years post-treatment.
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  • Recent studies have looked into low HER2 expression in breast cancer, but findings have varied; this study aimed to compare the pathology and survival rates of HER2-low versus HER2-0 patients.
  • A total of 693 HER2-negative breast cancer patients treated with neoadjuvant chemotherapy were analyzed for their pathological complete response (pCR) rates and disease-free survival (DFS), with findings showing no significant differences in these rates between HER2-low and HER2-0 groups, though HR status affected outcomes.
  • The study concluded that HER2 status does not correlate with pCR or DFS, and longer DFS was observed in HER2-low patients without pCR, suggesting a vital role of HR and HER2 interaction in patient prognosis.
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Purpose: While a pathologic complete response (pCR) is regarded as a surrogate endpoint for pos-itive outcomes in breast cancer (BC) patients receiving neoadjuvant chemotherapy (NAC), fore-casting the prognosis of non-pCR patients is still an open issue. This study aimed to create and evaluate nomogram models for estimating the likelihood of disease-free survival (DFS) for non-pCR patients.

Methods: A retrospective analysis of 607 non-pCR BC patients was conducted (2012-2018).

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Purpose: Pathological complete response (pCR), the goal of NAC, is considered a surrogate for favorable outcomes in breast cancer (BC) patients administrated neoadjuvant chemotherapy (NAC). This study aimed to develop and assess a novel nomogram model for predicting the probability of pCR based on the core biopsy. Methods: This was a retrospective study involving 920 BC patients administered NAC between January 2012 and December 2018.

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Background: The role of postmastectomy radiation therapy (PMRT) in clinical T1-2N1 breast cancer patients who achieve axillary pathological complete response (ypN0) after neoadjuvant chemotherapy (NAC) is controversial.

Methods: Data from cT1-2N1 breast cancer patients who converted to ypN0 after NAC and subsequent surgery were retrospectively analyzed. Disease-free survival (DFS) and overall survival (OS) were estimated using the Kaplan‒Meier method.

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Based on TCGA, GTEx, and TIMER databases and various bioinformatics analysis methods, the potential biological roles of cuprotosis-related genes in pancreatic cancer were deeply explored, and a predictive model for pancreatic cancer patients was constructed. We downloaded the RNA-Seq data and clinicopathological and predictive data of 179 pancreatic cancer tissues and 332 adjacent normal tissues from TCGA and GTEx databases. The differential expression of cuprotosis-related genes in pancreatic cancer tissue and adjacent normal tissue was analyzed, and the LASSO regression algorithm was used to construct a prediction model and verify the validity of the model prediction.

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Purpose: This study aimed to determine the effect of neoadjuvant chemotherapy (NAC) on circulating levels of reproductive hormones and evaluate the correlation of hormone changes after NAC with hormone receptors expression alterations and relapse-free survival (RFS) outcomes in breast cancer.

Methods: Information from 181 breast cancer patients who received NAC was retrospectively analyzed. For hormones parameters, the median and interquartile range (IQR) were provided at baseline and the end of NAC then was compared by Wilcoxon signed-rank test.

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This study is aimed at exploring the potential mechanism of angiogenesis, a biological process-related gene in breast cancer (BRCA), and constructing a risk model related to the prognosis of BRCA patients. We used multiple bioinformatics databases and multiple bioinformatics analysis methods to complete our exploration in this research. First, we use the RNA-seq transcriptome data in the TCGA database to conduct a preliminary screening of angiogenesis-related genes through univariate Cox curve analysis and then use LASSO regression curve analysis for secondary screening.

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Background: Metastatic rectal cancer (mRC) of the breast is an extremely rare clinical situation. There are few reported cases in domestic or foreign literature. The clinicopathologic characteristics along with the diagnostic and therapeutic strategies of such cases remain relatively unclear.

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Purpose: This study aimed to evaluate the correlation of pre-treatment circulating reproductive hormones levels with pathological and survival outcomes in breast cancer patients received neoadjuvant chemotherapy (NAC).

Methods: Information from 196 premenopausal and 137 postmenopausal breast cancer patients who received NAC were retrospectively analyzed. Treatment response to NAC, with odds ratios (OR) and 95% confidence intervals (95% CI) was estimated using logistic regression adjusted for key confounders.

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Background: The aim of this study was to evaluate the relationship between pre-treatment plasma fibrinogen (Fib) level and pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and to assess the role of plasma Fib as a predictive factor.

Methods: Data from 1004 consecutive patients with invasive breast cancer who received NAC and subsequent surgery were retrospectively analysed. Both univariate and multivariate analyses based on logistic regression model were performed to identify clinicopathological factors associated with pCR to NAC.

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KLHL5 (Kelch Like Family Member 5) is differentially expressed in gastric cancer, but its correlation with prognosis and functioning mechanism in gastric cancer remain unclear. The Oncomine database and TIMER were employed to appraise the KLHL5 expression in a variety of cancers. The correlation between KLHL5 expression and patient prognosis was extracted from the Kaplan-Meier plotter, GEPIA, and PrognoScan database.

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