Advancements in the Understanding of Small-Cell Neuroendocrine Cervical Cancer: Where We Stand and What Lies Ahead.

Small-cell neuroendocrine cervical carcinoma (SCNCC) is a rare yet aggressive gynecological malignancy associated with dismal clinical outcomes. Its rarity has led to a limited number of retrospective studies and an absence of prospective research, posing significant challenges for evidence-based treatment approaches. As a result, most gynecologic oncology centers have limited experience with this tumor, emphasizing the urgent need for a comprehensive review and summary. This article systematically reviews the pathogenesis, immunohistochemical and molecular characteristics, prognostic factors, and clinical management of gynecologic SCNCC. We specifically focused on reviewing the distinct genomic characteristics of SCNCC identified via next-generation sequencing technologies, including loss of heterozygosity (LOH), somatic mutations, structural variations (SVs), and microRNA alterations. The identification of these actionable genomic events offers promise for discovering new molecular targets for drug development and enhancing therapeutic outcomes. Additionally, we delve deeper into key clinical challenges, such as determining the optimal treatment modality between chemoradiation and surgery for International Federation of Gynecology and Obstetrics (FIGO) stage I phase patients within a precision stratification framework, as well as the role of targeted therapy within the homologous recombination (HR) pathway, immune checkpoint inhibitors (ICIs), and prophylactic cranial irradiation (PCI) in the management of SCNCC. Finally, we anticipate the utilization of multiple SCNCC models, including cancer tissue-originated spheroid (CTOS) lines and patient-derived xenografts (PDXs), to decipher driver events and develop individualized therapeutic strategies for clinical application.

The cost-effectiveness of a real-time seizure detection application for people with epilepsy.

OBJECTIVES: Automated seizure detection modalities can increase safety among people with epilepsy (PWE) and reduce seizure-related anxiety. We evaluated the potential cost-effectiveness of a seizure detection mobile application for PWE in Singapore. METHODS: We used a Markov cohort model to estimate the expected changes to total costs and health outcomes from a decision to adopt the seizure detection application versus the current standard of care from the health provider perspective. The time horizon is ten years and cycle duration is one month. Parameter values were updated from national databases and published literature. As we do not know the application efficacy in reducing seizure-related injuries, a conservative estimate of 1% reduction was used. Probabilistic sensitivity analysis, scenario analyses, and value of information analysis were performed. RESULTS: At a willingness-to-pay of $45,000/ quality-adjusted life-years (QALY), the incremental cost-effectiveness ratio was $1,096/QALY, and the incremental net monetary benefit was $13,656. Probabilistic sensitivity analyses reported that the application had a 99.5% chance of being cost-effective. In a scenario analysis in which the reduction in risk of seizure-related injury was 20%, there was a 99.8% chance that the application was cost-effective. Value of information analysis revealed that health utilities was the most important parameter group contributing to model uncertainty. CONCLUSIONS: This early-stage modeling study reveals that the seizure detection application is likely to be cost-effective compared to current standard of care. Future prospective trials will be needed to demonstrate the real-world impact of the application. Changes in health-related quality of life should also be measured in future trials.

A decision-support tool for funding health innovations at a tertiary academic medical center.

OBJECTIVES: To report the processes used to design and implement an assessment tool to inform funding decisions for competing health innovations in a tertiary hospital. METHODS: We designed an assessment tool for health innovation proposals with three components: "value to the institution," "novelty," and "potential for adoption and scaling." The "value to the institution" component consisted of twelve weighted value attributes identified from the host institution's annual report; weights were allocated based on a survey of the hospital's leaders. The second and third components consisted of open-ended questions on "novelty" and "barriers to implementation" to support further dialogue. Purposive literature review was performed independently by two researchers for each assessment. The assessment tool was piloted during an institutional health innovation funding cycle. RESULTS: We used 17 days to evaluate ten proposals. The completed assessments were shared with an independent group of panellists, who selected five projects for funding. Proposals with the lowest scores for "value to the institution" had less perceived impact on the patient-related value attributes of "access," "patient centeredness," "health outcomes," "prevention," and "safety." Similar innovations were reported in literature in seven proposals; potential barriers to implementation were identified in six proposals. We included a worked example to illustrate the assessment process. CONCLUSIONS: We developed an assessment tool that is aligned with local institutional priorities. Our tool can augment the decision-making process when funding health innovation projects. The tool can be adapted by others facing similar challenges of trying to choose the best health innovations to fund.

Detection of Green Asparagus in Complex Environments Based on the Improved YOLOv5 Algorithm.

An improved YOLOv5 algorithm for the efficient recognition and detection of asparagus with a high accuracy in complex environments was proposed in this study to realize the intelligent machine harvesting of green asparagus. The coordinate attention (CA) mechanism was added to the backbone feature extraction network, which focused more attention on the growth characteristics of asparagus. In the neck part of the algorithm, PANet was replaced with BiFPN, which enhanced the feature propagation and reuse. At the same time, a dataset of asparagus in complex environments under different weather conditions was constructed, and the performance variations of the models with distinct attention mechanisms and feature fusion networks were compared through experiments. Experimental results showed that the mAP@0.5 of the improved YOLOv5 model increased by 4.22% and reached 98.69%, compared with the YOLOv5 prototype network. Thus, the improved YOLOv5 algorithm can effectively detect asparagus and provide technical support for intelligent machine harvesting of asparagus in different weather conditions and complex environments.

Estrogen-regulated PTTG1 promotes breast cancer progression by regulating cyclin kinase expression.

BACKGROUND: The present study aims to investigate the effects of pituitary tumor transforming gene (PTTG) 1 on breast cancer and its underlying mechanism. METHODS: GEO data set was applied to analyze the relationship between PTTG1 and survival status and the TCGA breast cancer dataset was used to explore its possible targets. The stable cell lines including PTTG1 knockdown cells, estrogen receptor (ESR) 1 knockdown cells, and PTTG1 overexpression cells were constructed. MTT was used to determine cell viabilities. Propidium iodide (PI) staining and flow cytometry were used to analyze the cell cycle. Quantitative polymerase chain reaction (qPCR) was employed to determine the mRNA expressions. Points mutations and luciferase reporter assays were used to determine the binding sites of estrogen. RESULTS: PTTG1 was associated with poor survival rates in breast cancer. In vitro study demonstrated that PTTG1 affected cell viabilities of MCF7 and T47D cells. Besides, PTTG1 affected cell cycle arrest of breast cancer cells. Overexpression of PTTG1 led to more breast cancer cells distributed in S phase. The levels of PTTG1 were associated with estrogen and further results showed that the levels of PTTG1 were positively correlated to tamoxifen resistance. Two genes including CCNA2 and CCNB2 were identified to be possible targets of PTTG1. CONCLUSION: Estrogen-regulated PTTG1 promotes the development of breast cancer cells by the regulation of the cell cycle.

Prognostic value of EGFR 19-del and 21-L858R mutations in patients with non-small cell lung cancer.

Previous studies have demonstrated a significant difference in clinical characteristics between patients with non-small cell lung cancer (NSCLC) harboring exon 19 deletion (19-del) and an exon point mutation (21-L858R) in EGFR. The present retrospective study aimed to investigate the differential prognosis in patients with NSCLC harboring exon 19-del and 21-L858R mutations. The clinical and follow-up data of 137 patients treated at the Zhongnan Hospital of Wuhan University (Wuhan, Hubei, China) between August 2012 and August 2016, who were diagnosed with stage IIIB-IV NSCLC harboring either exon 19-del or 21-L858R mutations, were analyzed. The patients were divided into the first-line tyrosine kinase inhibitor (TKI), first-line chemotherapy and second-line TKI treatment groups. The median progression-free survival (PFS) time of patients harboring the exon 19-del mutation was significantly improved compared with that in patients harboring the 21-L858R mutation (11.3 vs. 8.8 months, respectively; P=0.017) following first-line TKI treatments. However, no significant difference in the median PFS time was observed between the exon 19-del and 21-L858R groups following the first-line chemotherapy or second-line TKI treatment. In patients with the exon 19-del, first-line TKI treatment achieved an increased objective response rate (ORR; 51.9 vs. 18.5%; P=0.004) and disease control rate (96.2 vs. 77.8%; P=0.030), and a longer PFS time (11.3 vs. 8.0 months; P=0.034) compared with that in the patients following first-line chemotherapy. First- and second-line TKI treatment achieved a similar PFS time (11.3 vs. 11.0 months, respectively; P=0.140). However, in patients with the 21-L858R mutation, the first-line TKI therapy and first-line chemotherapy groups exhibited a similar PFS time (8.8 vs. 3.5 months, respectively; P=0.063), while the second-line TKI treatment group exhibited a significantly longer PFS time compared with the first-line TKI treatment group (13.6 vs. 8.8 months, respectively; P=0.030). There was a differential sensitivity to treatment between patients harboring the exon 19-del and 21-L858R mutations. Therefore, chemotherapy may increase the sensitivity to TKIs in patients harboring the 21-L858R mutation.

Comprehensive analysis of a novel lncRNA profile reveals potential prognostic biomarkers in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the main subtype of malignant kidney cancer. Long non­coding RNA (lncRNA) serves a key role in predicting survival in patients with cancer. The present study aimed to develop an lncRNA­related signature of prognostic values for patients with ccRCC. RNA sequencing data of 454 patients were analyzed from The Cancer Genome Atlas (TCGA). To identify the differentially expressed lncRNAs, the patients from four groups classified by tumor stages were compared. The association between survival outcome and lncRNA expression profile was assessed by the univariate and multivariate Cox proportional hazards model. Survival was analyzed using the log­rank test, and functions of target lncRNAs were investigated through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. Finally, 19 lncRNAs were identified as significantly associated with overall survival (OS) time. These lncRNAs were gathered as a signal prognostic signature, which may be a potential biomarker for the prognosis of ccRCC. The risk score was built to evaluate the predictive value of the lncRNA signature. There was a significant positive correlation between ccRCC patients with the low­risk score and OS time (P<0.001). Reverse transcription­quantitative polymerase chain reaction (RT­qPCR) was used to verify the result in 17 pairs of ccRCC and adjacent non­tumor tissues. Functional enrichment analysis revealed that these lncRNAs were associated with several molecular pathways of the tumor. The RT­qPCR validation was consistent with the TCGA bioinformatics results. In conclusion, a tumor­specific lncRNA signature of 19 lncRNAs was identified and the joint prognostic power was evaluated in the present study, and this signature was determined to be a potential biomarker for the prognosis of ccRCC.

Dysregulated lncRNA-UCA1 contributes to the progression of gastric cancer through regulation of the PI3K-Akt-mTOR signaling pathway.

The long non-coding RNA (lncRNA) urothelial carcinoma-associated 1 (UCA1) has been recently shown to be dysregulated during disease occurrence and to play an important role in the progression of several cancers. However, the biological role and potential regulation mechanism of UCA1 in the carcinogenesis of gastric cancer remain unclear. In the present study, we found that UCA1 was aberrantly upregulated in gastric cancer tissues and gastric cancer cell lines, and was associated with TNM stage and metastasis. UCA1 silencing significantly inhibited gastric cancer BGC-823 cell proliferation and increased its apoptosis. We also found that UCA1 played an important role in the migration and invasion of gastric cancer cells in vitro and in vivo. The molecular mechanism of UCA1 suggested that UCA1 regulates the PI3K-Akt-mTOR signaling proteins and their downstream mediators, to alter gastric cancer progression in vitro and in vivo. Collectively, the results showed a pivotal role of UCA1 in the tumorigenesis of gastric cancer. In addition, the study characterized a novel lncRNA-mRNA regulatory network, which may lead to a better understanding of the pathogenesis of gastric cancer and assist in lncRNA-directed diagnosis and therapy for this malignancy.

Differential expression profiles of microRNAs as potential biomarkers for the early diagnosis of lung cancer.

Lung cancer is one of the most lethal malignancies worldwide. To reduce the high morbidity and mortality of the disease, sensitive and specific biomarkers for early detection are urgently needed. Tumor-specific microRNAs (miRNAs) seem to be potential biomarkers for the early diagnosis and treatment of cancer. In this study, the microarray of miRNAs and mRNAs on the same samples was performed and the intersection taken with The Cancer Genome Atlas (TCGA) lung cancer miRNA/RNAseq dataset. Then, miRNA-mRNA regulatory network was constructed to identify miRNA candidates associated with lung cancer through integrating gene expression and miRNA-target prediction. Furthermore, the expression levels of miRNA candidates were validated by stem-loop real-time reverse transcription PCR (qRT-PCR) in larger lung cancer population. The relationship between signature miRNAs and the risk of lung cancer were assessed by conditional logistic regression analysis. Diagnostic value of these miRNAs was determined by areas under receiver operating characteristic curves (ROC). The Affymetrix microarray analysis identified a total of 116 miRNAs and 502 mRNAs that could distinguish lung tumor tissues from adjacent non-tumor tissues, of which 70 miRNAs and 136 mRNAs were upregulated, while 46 miRNAs and 366 mRNAs were downregulated, respectively. In combination with TCGA analysis, we identified 32 miRNAs and 377 mRNAs related to lung cancer. Then, 28 key miRNAs related to 61 inter-section mRNAs were identified by miRNA-mRNA network analysis. The miRNA function analysis was indicative of that 18 upregulated and 10 downregulated miRNAs involved in signaling pathways related to Environmental Information Processing and Human Diseases. Population result showed that the expression of 7 miRNAs (miR-205-5p, miR-3917, miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p and miR-27a-5p) was consistent with the analysis result of microarray and TCGA. In addition, upregulation of miR-205-5p, miR-3917 and downregulation of miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p, miR-27a-5p increased the risk of lung cancer by conditional logistic regression analysis. The diagnostic accuracy of miR-205-5p, miR-3917, miR-27a-5p, miR-30a-3p, miR-30a-5p, miR-30c-2-3p, miR-30d-5p showed that their corresponding AUCs were 0.728, 0.661, 0.637, 0.758, 0.772, 0.734, 0.776, respectively. Therefore, there are a set of signature miRNAs which may be promising biomarkers for the early screening of high-risk populations and early diagnosis of lung cancer.

Integrated analysis of long non-coding RNA­associated ceRNA network reveals potential lncRNA biomarkers in human lung adenocarcinoma.

Accumulating evidence has highlighted the important roles of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in tumor biology. However, the roles of cancer specific lncRNAs in lncRNA-related ceRNA network of lung adenocarcinoma (LUAD) are still unclear. In the present study, the 465 RNA sequencing profiles in LUAD patients were obtained from the cancer genome atlas (TCGA) database, which provides large sample RNA sequencing data free of charge, and 41 cancer specific lncRNAs, 25 miRNAs and 1053 mRNAs (fold change >2, p<0.05) were identified. Then, the lncRNA-miRNA-mRNA ceRNA network of LUAD was constructed with 29 key lncRNAs, 24 miRNAs and 72 mRNAs. Subsequently, we selected these 29 key lncRNAs to analyze their correlation with clinical features, and 21 of them were aberrantly expressed with tumor pathological stage, TNM staging system, lymph node metastasis and patient outcome assessment, respectively. Furthermore, there were 5 lncRNAs (BCRP3, LINC00472, CHIAP2, BMS1P20 and UNQ6494) positively correlated with overall survival (OS, log-rank p<0.05). Finally, 7 cancer specific lncRNAs were randomly selected to verify the expression in 53 newly diagnosed LUAD patients using qRT-PCR. The expression results between TCGA and qRT-PCR were 100% in agreement. The correlation between AFAP1-AS1 and LINC00472 and clinical features were also confirmed. Thus, our results showed the lncRNA expression profiles and we constructed an lncRNA-miRNA-mRNA ceRNA network in LUAD. The present study provides novel insight for better understanding of lncRNA-related ceRNA network in LUAD and facilitates the identification of potential biomarkers for diagnosis and prognosis.

Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer.

Abnormal expression of long non-coding RNAs (lncRNAs) have been shown to play an important role in tumor biology. The Cancer Genome Atlas (TCGA) platform is a large sample sequencing database of lncRNAs, and further analysis of the associations between these data and patients' clinical related information can provide new approaches to find the functions of lncRNA. In the present study, 361 RNA sequencing profiles of gastric cancer (GC) patients were selected from TCGA. Then, we constructed the lncRNA-miRNA-mRNA competitive endogenous RNA (ceRNA) network of GC. There were 25 GC specific lncRNAs (fold change >2, p<0.05) identified, 19 of them were included in ceRNA network. Subsequently, we selected these 19 key lncRNAs and analyzed the correlations with clinical features and overall survival, 14 of them were discriminatively expressed with tumor size, tumor grade, TNM stage and lymphatic metastasis (p<0.05). In addition, eight lncRNAs (RPLP0P2, FOXD2-AS1, H19, TINCR, SLC26A4-AS1, SMIM10L2A, SMIM10L2B and SNORD116-4) were found to be significantly associated with overall survival (log-rank p<0.05). Finally, two key lncRNAs HOTAIR and UCA1 were selected for validation of their expression levels in 82 newly diagnosed GC patients by qRT-PCR. Results showed that the fold changes between TCGA and qRT-PCR were 100% in agreement. In addition, we also found that HOTAIR was significantly correlated with tumor size and lymphatic metastasis (p<0.05), and UCA1 was significantly correlated with tumor size, TNM stage and lymphatic metastasis (p<0.05). The clinical relevance of the two lncRNAs and the bioinformatics analysis results were almost the same. Overall, our study showed the GC specific lncRNAs expression patterns and a ceRNA network in GC. Clinical features related to GC specific lncRNAs also suggested these lncRNAs are worthwhile for further study as novel candidate biomarkers for the clinical diagnosis of GC and potential indicators for prognosis.

Availability and range of tobacco products for sale in Massachusetts pharmacies.

OBJECTIVE: New tobacco control policies have been introduced in Massachusetts which restrict tobacco product sales in pharmacies. The purpose of this investigation was to outline the scope of pharmacy involvement in the tobacco market by assessing the availability and range of tobacco products sold in Massachusetts pharmacies. METHODS: Public listings of licenced pharmacies and tobacco retailers in Massachusetts were examined to determine the proportion of pharmacies licenced to sell tobacco, and the proportion of tobacco retailers possessing a pharmacy licence. Telephone interviews were conducted with a random sample (n=70) of pharmacies possessing a tobacco licence to assess the availability and range of tobacco products for sale. The availability of nicotine replacement therapy (NRT) products was assessed as a comparison. RESULTS: The majority of pharmacies in Massachusetts possessed a tobacco licence (69%), and pharmacies made up 9% of licenced tobacco retailers. Among pharmacies surveyed that reported selling tobacco (90%), cigarettes were the most available tobacco product for sale (100%), followed by cigars (69%), little cigars/cigarillos (66%), moist snuff (53%), pipe tobacco (49%), roll-your-own tobacco (34%), snus (14%), dissolvable tobacco (11%) and electronic cigarettes (2%). Nearly all pharmacies selling tobacco offered the nicotine patch (100%), gum (100%) and lozenge (98%). CONCLUSIONS: Tobacco-free pharmacy policies would affect a majority of Massachusetts pharmacies and remove a variety of tobacco products from their store shelves. Further, nearly one in ten tobacco retailers would be eliminated by prohibiting tobacco sales in Massachusetts pharmacies statewide.

Esterase-catalyzed dePEGylation of pH-sensitive vesicles modified with cleavable PEG-lipid derivatives.

To make vesicles for the better controlled content release, we modified cholesteryl hemisuccinate (CHEMS)-derived vesicles with PEG-lipid derivatives. Two cholesterol analogs, cholesteryl hemisuccinate (CHEMS) and cholesteryl chloroformate (CHM), have been conjugated to the polyethylene glycol (PEG) via their ester bonds for the vesicle modifications, so the PEGs can be cleaved by esterases. The effects of PEG-lipid proportions, serum concentrations and the lipid types on the esterase-catalyzed cleavage of PEG polymer off the vesicles surface were determined. We observed that PEG cleavages decreased as the molar ratios of the PEG-lipids in vesicles increased; on the other hand, PEG cleavages gradually increased with the increased serum concentrations. In contrast to conventional long circulation materials mPEG-DSPE and mPEG-CHOL, the two new conjugates enabled higher degrees of PEG cleavages from modified vesicles. After incubation in the serum at acidic conditions, esterase-catalyzed dePEGylation destabilized these vesicles, increasing the mean particle sizes and promoting content releases. These results suggested that ester linkages between the PEG and lipid anchors allow faster content releases in the suitable conditions. Together, the two esterase cleavable PEG-lipid conjugations may be applied not only to stabilize vesicles and prolong their circulation time, but also to provide more efficient content releases by the esterase controlled dePEGylation.