Carbon sinks/sources' spatiotemporal heterogeneity and their spatial response to economic-social factors in relatively developed regions: A case of China's coastal area.

With the global climate change, carbon reduction in economically active regions has gradually become a focus of attention and its underlying drivers were essential for understanding alterations in ecosystems in response to human behavior. However, the exploration of Carbon Sinks/Sources Patterns (CSSP) in an Economic-Social context was lacking. Distinguished from traditional Net Ecosystem Productivity (NEP) estimation methods, we optimized model parameters, adjusted estimation logic, and revealed CSSP more reasonably. Moreover, spatial econometric model was used to reveal the spatial effects mechanism of Economic-Social Development on CSSP. Over the past 20 years, we revealed that: (a) The pattern of NEP exhibited distinct spatial heterogeneity, with higher sinks observed in the north and offshore regions. It demonstrated regular cyclic fluctuations, averaging a 3-4-year cycle, featuring a gradual ascent followed by a rapid descent; (b) The Carbon Sequestration Capacity (CSC) of vegetation significantly increased. Based on the carbon sink properties, the study area was distinctly divided into three clusters; (c) CSSP have been profoundly affected by economic-social factors. Economic growth and industrial structure optimization contributed to the enhancement of CSC, but population aggregation and urban expansion had negative impacts. The direct effect of innovation capacity and the spatial spillover effect of industrial structure optimization were negative. Overall, exploring CSSP against the backdrop of economic-social factors not only provides a new perspective for understanding the regularities of change and the underlying mechanisms driven by human factors but also offers valuable insights for achieving sustainable development and green growth in other coastal regions globally.

Biosensor-Based Multiple Cross Displacement Amplification for the Rapid Detection of Mycobacterium leprae.

Leprosy is an ancient disease caused by Mycobacterium leprae (ML) that remains a public health problem in poverty-stricken areas worldwide. Although many ML detection techniques have been used, a rapid and sensitive tool is essential for the early detection and treatment of leprosy. Herein, we developed a rapid ML detection technique by combining multiple cross displacement amplification (MCDA) with a nanoparticle-based lateral flow biosensor (LFB), termed ML-MCDA-LFB. MCDA induced a rapid isothermal reaction using specific primers targeting the RLEP gene, and the LFB enabled instant visual amplicon detection. The pure genomic DNA of ML and nucleic acids from various pathogens were employed to evaluate and optimize the ML-MCDA-LFB assay. The optimal conditions for ML-MCDA-LFB were 68 °C and 35 min, respectively. The limit of detection for pure ML genomic DNA was 150 fg per vessel, and the specificity of detection was 100% for the experimental strains. Additionally, the entire detection process could be performed within 40 min, including the isothermal amplification (35 min) and result confirmation (1-2 min). Hence, the ML-MCDA-LFB assay was shown to be a rapid, sensitive, and visual method for detecting ML and could be used as a potential tool for early clinical diagnosis and field screening of leprosy.

Highly sensitive and rapid determination of Mycobacterium leprae based on real-time multiple cross displacement amplification.

BACKGROUND: Mycobacterium leprae (ML) is the pathogen that causes leprosy, which has a long history and still exists today. ML is an intracellular mycobacterium that dominantly induces leprosy by causing permanent damage to the skin, nerves, limbs and eyes as well as deformities and disabilities. Moreover, ML grows slowly and is nonculturable in vitro. Given the prevalence of leprosy, a highly sensitive and rapid method for the early diagnosis of leprosy is urgently needed. RESULTS: In this study, we devised a novel tool for the diagnosis of leprosy by combining restriction endonuclease, real-time fluorescence analysis and multiple cross displacement amplification (E-RT-MCDA). To establish the system, primers for the target gene RLEP were designed, and the optimal conditions for E-RT-MCDA at 67 °C for 36 min were determined. Genomic DNA from ML, various pathogens and clinical samples was used to evaluate and optimize the E-RT-MCDA assay. The limit of detection (LoD) was 48.6 fg per vessel for pure ML genomic DNA, and the specificity of detection was as high as 100%. In addition, the detection process could be completed in 36 min by using a real-time monitor. CONCLUSION: The E-RT-MCDA method devised in the current study is a reliable, sensitive and rapid technique for leprosy diagnosis and could be used as a potential tool in clinical settings.

STK24 Promotes Progression of LUAD and Modulates the Immune Microenvironment.

Objective: Recent studies have shown that serine/threonine-protein kinase 24 (STK24) plays an important role in cancer development. However, the significance of STK24 in lung adenocarcinoma (LUAD) remains to be determined. This study is aimed at investigating the significance of STK24 in LUAD. Methods: STK24 was silenced and overexpressed by siRNAs and lentivirus, respectively. Cellular function was assessed by CCK8, colony formation, transwell, apoptosis, and cell cycle. mRNA and protein abundance was checked by qRT-PCR and WB assay, respectively. Luciferase reporter activity was evaluated to examine the regulation of KLF5 on STK24. Various public databases and tools were applied to investigate the immune function and clinical significance of STK24 in LUAD. Results: We found that STK24 was overexpressed in lung adenocarcinoma (LUAD) tissues. High expression of STK24 predicted poor survival of LUAD patients. In vitro, STK24 enhanced the proliferation and colony growth ability of A549 and H1299 cells. STK24 knockdown induced apoptosis and cell cycle arrest at G0/G1 phase. Furthermore, Krüppel-like factor 5 (KLF5) activated STK24 in lung cancer cells and tissues. Enhanced lung cancer cell growth and migration triggered by KLF5 could be reversed by silencing of STK24. Finally, the bioinformatics results showed that STK24 may be involved in the regulation of the immunoregulatory process of LUAD. Conclusion: KLF5 upregulation of STK24 contributes to cell proliferation and migration in LUAD. Moreover, STK24 may participate in the immunomodulatory process of LUAD. Targeting KLF5/STK24 axis may be a potential therapeutic strategy for LUAD.

Ultrafast, One-Step, Label-Based Biosensor Diagnosis Platform for the Detection of Mycobacterium tuberculosis in Clinical Applications.

Tuberculosis (TB) is a chronic infectious disease caused by the etiological agent Mycobacterium tuberculosis (MTB). Because the majority of TB patients come from poor economic backgrounds, the development of a simple, specific, low-cost, and highly sensitive detection method for the pathogen is extremely important for the prevention and treatment of this disease. In the current study, an efficient detection method for visual, rapid, and highly sensitive detection of MTB utilizing multiplex loop-mediated isothermal amplification combined with a label-based lateral flow immunoassay biosensor (mLAMP-LFIA) was developed. Three specific primer sets targeting the MTB genes IS6110 and mpb64 were successfully designed and synthesized for the LAMP assay. The optimal reaction conditions for the mLAMP-LFIA assay were confirmed to be 67 °C for 40 min. The mLAMP amplicons were intuitively verified using the LFIA biosensor within 5 min. The entire process, including clinical sample processing, amplification reaction, and product verification, was completed within 80 min. The limit of detection of the mLAMP-LFIA assay established in the current study was 100 fg per reaction for the genomic DNA of MTB H37Rv. The analytical specificity of the mLAMP-LFIA assay was one hundred percent, and no cross-reactions with non-target strains were detected. Compared with the GeneXpert test, the sensitivity of mLAMP-LFIA for 148 clinical specimens was 100% (97/97), and the specificity was 98.04% (50/51) in the preliminary evaluation of the clinical application. Hence, the mLAMP-LFIA method, targeting the IS6110 and mpb64 genes, is an ultrafast, one-step, low-cost, and highly sensitive detection method that could be used as a screening and/or diagnostic tool for MTB in the clinical setting, basic science laboratories, and especially in resource-poor regions.

Development of CRISPR/Cas12b-Based Multiple Cross Displacement Amplification Technique for the Detection of Mycobacterium tuberculosis Complex in Clinical Settings.

Tuberculosis (TB) is a chronic infectious disease with high mortality caused by the Mycobacterium tuberculosis complex (MTC). Its clinical symptoms include a prolonged cough with mucus, pleuritic chest pain, hemoptysis, etc., and predominant complications such as tuberculous meningitis and pleural effusion. Thus, developing rapid, ultrasensitive, and highly specific detection techniques plays an important role in controlling TB. Here, we devised CRISPR/CRISPR-associated 12b nuclease (CRISPR/Cas12b)-based multiple cross displacement amplification technique (CRISPR-MCDA) targeting the IS6110 sequence and used it to detect MTC pathogens. A newly engineered protospacer adjacent motif (PAM) site (TTTC) was modified in the linker region of the CP1 primer. In the CRISPR-MCDA system, the exponentially amplified MCDA amplicons with the PAM sites can guide the Cas12b/gRNA complex to quickly and accurately recognize its target regions, which successfully activates the CRISPR/Cas12b effector and enables ultrafast trans-cleavage of single-stranded DNA reporter molecules. The limit of detection of the CRISPR-MCDA assay was 5 fg/µL of genomic DNA extracted from the MTB reference strain H37Rv. The CRISPR-MCDA assay successfully detected all examined MTC strains and there was no cross-reaction with non-MTC pathogens, confirming that its specificity is 100%. The entire detection process can be completed within 70 min using real-time fluorescence analysis. Moreover, visualization detection (under UV light) was also designed to verify the results, eliminating the use of specialized instruments. In conclusion, the CRISPR-MCDA assay established in this report can be used as a valuable detection technique for MTC infection. IMPORTANCE The Mycobacterium tuberculosis complex pathogen is a crucial infectious agent of tuberculosis. Hence, improving the capability of MTC detection is one of the most urgently required strategies for preventing and controlling TB. In this report, we successfully developed and implemented CRISPR/Cas12b-based multiple cross displacement amplification targeting the IS6110 sequence to detect MTC pathogens. These results demonstrated that the CRISPR-MCDA assay developed in this study was a rapid, ultrasensitive, highly specific, and readily available method which can be used as a valuable diagnostic tool for MTC infection in clinical settings.

Improving the elicitation of critical customer requirements through an understanding of their sensitivity.

Customer requirements (CRs) are the essential driven forces of product development. Constrained by the rigid budget and time allocated to product development, much attentions and resources should be paid on critical customer requirements (CCRs). Product design occurs with an increasingly frenetic pace of change in today's competitive market, and the changes of external environment will lead to the changes of CRs. Thus, involving the sensitivity of CRs toward influence factors to identify CCRs is of great significance to grasp the directions of product evolution and enhance market competitiveness. To fill this gap, this study proposes a CCRs identification method integrated Kano model and structural equation model (SEM). First, the Kano model is adopted to determine the category of each CR. Second, based on CRs' categorization, an SEM model is established to measure the sensitivity of CRs toward the turbulence of influence factors. Then the importance of each CR is calculated, and by integrating the sensitivity and importance, a four-quadrant diagram is constructed to identify the CCRs. Finally, the identification of CCRs for smartphone is implemented as an example to demonstrate the feasibility and additional value of the proposed method.

HEY1-mediated cisplatin resistance in lung adenocarcinoma via epithelial-mesenchymal transition.

Lung cancer is one of the most common malignancies and the leading cause of cancer-related death in the world. In patients with advanced lung adenocarcinoma who are negative for driver gene mutations, platinum-based chemotherapy represented by cisplatin remain the standard of care. Therefore, studying the mechanism behind inevitable cisplatin resistance in lung adenocarcinoma is still important. In this study, the potentially related differential expression gene for cisplatin resistance in lung adenocarcinoma was screened in the GEO database. The expression level of HEY1 in cell lines of lung adenocarcinoma was detected and HEY1 expression was up-regulated in cisplatin-resistant lung adenocarcinoma tissues and cell lines A549/DDP. Patients with high HEY1 expression have poor prognosis after cisplatin therapy. Gain and loss function assays uncovered that HEY1 could regulate the cisplatin sensitivity of NSCLC cells. In vivo experiments have confirmed that silence of HEY1 expression can induce cisplatin resistance, and epithelial-mesenchymal transition (EMT) changes occur during this process. Mechanically, HEY1 silencing significantly up-regulated E-cadherin expression and down-regulated Vimentin in A549/DDP cells. While up-regulation of HEY1 resulted in down-regulation of E-cadherin and up-regulation of Vimentin in A549 cells. Immunohistochemical experiments confirmed that E-cadherin was significantly decreased, and Vimentin expression was significantly up-regulated in cisplatin-resistant lung adenocarcinoma tissues. HEY1 can mediate the occurrence of cisplatin-acquired resistance in lung adenocarcinoma, and the possible mechanism is to regulate the EMT. The results of this study can provide a new direction and target for clinical research on the reversal of cisplatin resistance in lung adenocarcinoma.

Clinical significance of the diverse interlobar veins hidden in the upper oblique fissure.

Background: The interlobar veins hidden in the upper oblique fissure (UOF) of the right lung are usually mismanaged cursorily according to the target lobe, which results in accidental injury of the interlobar veins and complications. The detailed classification of interlobar veins based on surgical anatomical analysis is of great clinical significance. Methods: Three-dimensional computed tomography bronchography and angiography (3D-CTBA) reconstructed images of 398 patients from January 2019 to June 2020 were retrospectively analyzed. The interlobar veins in the UOF were observed and classified according to their morphology and distribution. The classification model was further validated in 153 patients who underwent surgery involving dissection of the UOF, and related surgical results were analyzed. Results: The distribution of interlobar veins was diverse, and the general morphology could be divided into 2 main categories and 30 subtypes in the 3D-CTBA images of the 398 patients. Analysis of the 153 patients' surgical data showed that 60 patients suffered from interlobar vein injury. Interlobar veins hidden in an incomplete UOF were the most susceptible to accidental damage (χ2=12.856, P=0.020). A receiver operating characteristic (ROC) curve analysis showed that an interlobar vein diameter larger than 2.4 mm for the oblique fissure interlobar vein type or less than 2 mm for the mediastinal interlobar vein type was associated with a higher risk of injuries (P<0.001). Conclusions: The diversity of interlobar veins and the completeness of the UOF were noteworthy risk factors in surgery involving dissection of the UOF.

Why Do We "Like" on WeChat Moments: The Effects of Personality Traits and Content Characteristics.

To probe the motivational roles of hedonic gratification and social gratification in giving "Like" feedback on social media, we developed a set of novel pictures to simulate WeChat Moments. We subsequently examined how the personality trait of extraversion and stimulus content characteristics (e.g., emotional valence, personal relevance) influenced "Liking" behavior. A 2 (extraversion: extrovert group vs. introvert group) × 3 (emotional valence: positive vs. neutral vs. negative) × 2 (personal relevance: personally relevant vs. personally irrelevant)-mixed experimental design was applied to data obtained from 56 WeChat Moments users. These participants included 28 individuals with the highest extraversion scale scores (the extrovert group), and 28 individuals with the lowest extraversion scale scores (the introvert group), according to the NEO Five-Factor Inventory. Briefly, participants observed pictures on an interface similar to that of WeChat Moments and were given the option to "Like" each picture. "Like" rates and response time were then compared across groups and conditions by applying a mixed-design analysis of variance. Pearson's correlation coefficients were calculated to explore relationships between the "Like" rates under each condition and the scores for each personality trait. Compared with the neutral pictures, the positive and negative pictures were "Liked" more and less frequently, respectively (F 2, 108 = 46.22, p < 0.001). Compared with the poster-unrelated pictures, the personally related pictures were "Liked" more frequently (F 1, 54 = 19.54, p < 0.001). In the extrovert group, the frequency of "Likes" given to unrelated negative content positively associated with neuroticism (r = 0.42, p = 0.025) and negatively associated with conscientiousness (r = -0.46, p = 0.014). No correlations were observed in the introvert group. Compared with not giving "Like" feedback, participants gave "Likes" to positive and negative pictures more quickly (p = 0.035) and slowly (p < 0.001), respectively.These results support the hypothesis that hedonic gratification and social gratification motivate "Like" feedback for positive content and personally related content, respectively. "Liking" behavior was not affected by extraversion, but was related to neuroticism and conscientiousness. Content-related differences in time intervals for giving "Like" feedback in this study suggest that people do not hesitate to give "Like" feedback to positive content on WeChat Moments, yet linger in deciding to give "Like" feedback to negative content.

Two target genes based multiple cross displacement amplification combined with a lateral flow biosensor for the detection of Mycobacterium tuberculosis complex.

BACKGROUND: Tuberculosis (TB) is a serious chronic infectious disease caused by Mycobacterium tuberculosis complex (MTBC). Hence, the development of a novel, simple, rapid and sensitive method to detect MTBC is of great significance for the prevention and treatment of TB. RESULTS: In this study, multiple cross displacement amplification (MCDA) combined with a nanoparticle-based lateral flow biosensor (LFB) was developed to simultaneously detect two target genes (IS6110 and mpb64) of MTBC (MCDA-LFB). One suite of specific MCDA primers designed for the IS6110 and mpb64 genes was validated using genomic DNA extracted from the reference strain H37Rv. The MCDA amplicons were analyzed using a real-time turbidimeter, colorimetric indicator (malachite green, MG) and LFBs. The optimal amplification temperature and time were confirmed, and the MCDA-LFB method established in the current report was evaluated by detecting various pathogens (i.e., reference strains, isolates and clinical sputum samples). The results showed that the two sets of MCDA primers targeting the IS6110 and mpb64 genes could effectively detect MTBC strains. The optimal reaction conditions for the MCDA assay were determined to be 67 °C for 35 min. The MCDA assay limit of detection (LoD) was 100 fg per reaction for pure genomic DNA. The specificity of the MCDA-LFB assay was 100%, and there were no cross-reactions for non-MTBC strains. For sputum samples and MTBC strain detection, the positive rate of MCDA-LFB for the detection of MTBC strains was consistent with seminested automatic real-time PCR (Xpert MTB/RIF) and higher than acid-fast staining (AFS) and culture assays when used for sputum samples. The MCDA-LFB assay was a rapid tool, and the whole procedure for MCDA-LFB, including DNA template preparation, MCDA reaction and amplification product analysis, was completed within 70 min. CONCLUSION: The MCDA-LFB assay targeting the IS6110 and mpb64 genes is a simple, rapid, sensitive and reliable detection method, and it has potential significance for the prevention and treatment of TB.

Tumor-derived exosomal miR-3157-3p promotes angiogenesis, vascular permeability and metastasis by targeting TIMP/KLF2 in non-small cell lung cancer.

Metastasis is the main cause of death in patients with advanced lung cancer. The exosomes released by cancer cells create tumor microenvironment, and then accelerate tumor metastasis. Cancer-derived exosomes are considered to be the main driving force for metastasis niche formation at foreign sites, but the mechanism in Non-small cell lung carcinoma (NSCLC) is unclear. In metastatic NSCLC patients, the expression level of miR-3157-3p in circulating exosomes was significantly higher than that of non-metastatic NSCLC patients. Here, we found that miR-3157-3p can be transferred from NSCLC cells to vascular endothelial cells through exosomes. Our work indicates that exosome miR-3157-3p is involved in the formation of pre-metastatic niche formation before tumor metastasis and may be used as a blood-based biomarker for NSCLC metastasis. Exosome miR-3157-3p has regulated the expression of VEGF/MMP2/MMP9 and occludin in endothelial cells by targeting TIMP/KLF2, thereby promoted angiogenesis and increased vascular permeability. In addition, exosome miR-3157-3p promoted the metastasis of NSCLC in vivo.

Rapid and Visual Differentiation of Mycobacterium tuberculosis From the Mycobacterium tuberculosis Complex Using Multiplex Loop-Mediated Isothermal Amplification Coupled With a Nanoparticle-Based Lateral Flow Biosensor.

Tuberculosis (TB) is a chronic infectious disease mainly caused by Mycobacterium tuberculosis (MTB), but other members of the Mycobacterium tuberculosis complex (MTBC), especially Mycobacterium bovis (pyrazinamide-resistant organisms), may also be involved. Thus, the ability to rapidly detect and identify MTB from other MTBC members (e.g., M. bovis, Mycobacterium microti, Mycobacterium africanum) is essential for the prevention and treatment of TB. A novel diagnostic method for the rapid detection and differentiation of MTB, which employs multiplex loop-mediated isothermal amplification (mLAMP) combined with a nanoparticle-based lateral flow biosensor (LFB), was established (mLAMP-LFB). Two sets of specific primers that target the IS6110 and mtp40 genes were designed according to the principle of LAMP. Various pathogens were used to optimize and evaluate the mLAMP-LFB assay. The optimal conditions for mLAMP-LFB were determined to be 66°C and 40 min, and the amplicons were directly verified by observing the test lines on the biosensor. The LAMP assay limit of detection (LoD) was 125 fg per vessel for the pure genomic DNA of MTB and 4.8 × 103 CFU/ml for the sputum samples, and the analytical specificity was 100%. In addition, the whole process, including the clinical specimen processing (35 min), isothermal amplification (40 min), and result confirmation (1-2 min), could be completed in approximately 80 min. Thus, mLAMP-LFB is a rapid, reliable, and sensitive method that is able to detect representative members of MTBC and simultaneously differentiate MTB from other MTBC members, and it can be used as a potential screening tool for TB in clinical, field, and basic laboratory settings.

Highly specific and sensitive detection of the Mycobacterium tuberculosis complex using multiplex loop-mediated isothermal amplification combined with a nanoparticle-based lateral flow biosensor.

Tuberculosis (TB) is the deadliest infectious caused by Mycobacterium tuberculosis complex (MTBC). Because most TB cases occur within low-income populations, developing a specific, sensitive, cost-saving, and rapid point-of-care test for the early diagnosis of TB is important for achieving the WHO's End Tuberculosis Strategy. In the current study, a novel nucleic acid detection strategy that includes multiplex loop-mediated isothermal amplification combined with a nanoparticle-based lateral flow biosensor (mLAMP-LFB) was used to detect MTBC. The two sets of LAMP primers specific to the IS6110 and gyrB genes of MTBC were successfully designed and validated for the detection of MTBC. The preferred reaction conditions for this assay were confirmed to be 65 °C for 40 min, and the amplification products could be visually identified through LFB within 2 min. The full assay process, including genomic DNA template extraction, LAMP reaction, and product detection, could be completed in 80 min. The limit detection of the assay was 100 fg of DNA in pure culture. The specificity of the assay was 100%, and it had no cross-reactions to other strains. Thus, the m-LAMP-LFB technology established in the present study was an objective, rapid, simple, and sensitive assay for MTBC identification, which could be applied in a clinical setting, especially in resource-constrained regions of the world.

Development and evaluation of deep learning-based segmentation of histologic structures in the kidney cortex with multiple histologic stains.

The application of deep learning for automated segmentation (delineation of boundaries) of histologic primitives (structures) from whole slide images can facilitate the establishment of novel protocols for kidney biopsy assessment. Here, we developed and validated deep learning networks for the segmentation of histologic structures on kidney biopsies and nephrectomies. For development, we examined 125 biopsies for Minimal Change Disease collected across 29 NEPTUNE enrolling centers along with 459 whole slide images stained with Hematoxylin & Eosin (125), Periodic Acid Schiff (125), Silver (102), and Trichrome (107) divided into training, validation and testing sets (ratio 6:1:3). Histologic structures were manually segmented (30048 total annotations) by five nephropathologists. Twenty deep learning models were trained with optimal digital magnification across the structures and stains. Periodic Acid Schiff-stained whole slide images yielded the best concordance between pathologists and deep learning segmentation across all structures (F-scores: 0.93 for glomerular tufts, 0.94 for glomerular tuft plus Bowman's capsule, 0.91 for proximal tubules, 0.93 for distal tubular segments, 0.81 for peritubular capillaries, and 0.85 for arteries and afferent arterioles). Optimal digital magnifications were 5X for glomerular tuft/tuft plus Bowman's capsule, 10X for proximal/distal tubule, arteries and afferent arterioles, and 40X for peritubular capillaries. Silver stained whole slide images yielded the worst deep learning performance. Thus, this largest study to date adapted deep learning for the segmentation of kidney histologic structures across multiple stains and pathology laboratories. All data used for training and testing and a detailed online tutorial will be publicly available.

Assessment of a computerized quantitative quality control tool for whole slide images of kidney biopsies.

Inconsistencies in the preparation of histology slides and whole-slide images (WSIs) may lead to challenges with subsequent image analysis and machine learning approaches for interrogating the WSI. These variabilities are especially pronounced in multicenter cohorts, where batch effects (i.e. systematic technical artifacts unrelated to biological variability) may introduce biases to machine learning algorithms. To date, manual quality control (QC) has been the de facto standard for dataset curation, but remains highly subjective and is too laborious in light of the increasing scale of tissue slide digitization efforts. This study aimed to evaluate a computer-aided QC pipeline for facilitating a reproducible QC process of WSI datasets. An open source tool, HistoQC, was employed to identify image artifacts and compute quantitative metrics describing visual attributes of WSIs to the Nephrotic Syndrome Study Network (NEPTUNE) digital pathology repository. A comparison in inter-reader concordance between HistoQC aided and unaided curation was performed to quantify improvements in curation reproducibility. HistoQC metrics were additionally employed to quantify the presence of batch effects within NEPTUNE WSIs. Of the 1814 WSIs (458 H&E, 470 PAS, 438 silver, 448 trichrome) from n = 512 cases considered in this study, approximately 9% (163) were identified as unsuitable for subsequent computational analysis. The concordance in the identification of these WSIs among computational pathologists rose from moderate (Gwet's AC1 range 0.43 to 0.59 across stains) to excellent (Gwet's AC1 range 0.79 to 0.93 across stains) agreement when aided by HistoQC. Furthermore, statistically significant batch effects (p < 0.001) in the NEPTUNE WSI dataset were discovered. Taken together, our findings strongly suggest that quantitative QC is a necessary step in the curation of digital pathology cohorts. © 2020 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

miR-550a-5p Functions as a Tumor Promoter by Targeting LIMD1 in Lung Adenocarcinoma.

Lung adenocarcinoma accounts for half of all lung cancer cases in most countries. Mounting evidence has demonstrated that microRNAs play important roles in cancer progression, and some of them can be identified as potential biomarkers. This study aimed to explore the role of miR-550a-5p, a lung adenocarcinoma-associated mature microRNA screened out from the TCGA database via R-studio and Perl, with abundant expression in samples and with 5-year survival prognosis difference, as well as having not been studied in lung cancer yet. Potential target genes were predicted by the online database. Gene ontology enrichment, pathway enrichment, protein-protein interaction network, and hub genes-microRNA network were constructed by FunRich, STRING database, and Cytoscape. Then, LIMD1, a known tumor suppressor gene reported by multiple articles, was found to have a negative correlation with miR-550a-5p. The expression of miR-550a-5p was up-regulated in tumor samples and tumor-associated cell lines. Its high expression was also correlated with tumor size. Cell line A549 treated with miR-550a-5p overexpression promoted tumor proliferation, while H1299 treated with miR-550a-5p knockdown showed the opposite result. Mechanically, miR-550a-5p negatively regulated LIMD1 by directly binding to its 3'-UTR validated by dual luciferase assay. In summary, a new potential prognostic and therapeutic biomarker, miR-550a-5p, has been identified by bioinformatics analysis and experimental validation in vitro and in vivo, which promotes lung adenocarcinoma by silencing a known suppressor oncogene LIMD1.

Circular RNA LPAR3 sponges microRNA-198 to facilitate esophageal cancer migration, invasion, and metastasis.

In this study, we explored expression and functions of circular RNA LPAR3 (circLPAR3) in esophageal squamous cell carcinoma (ESCC). The differential expression of circular RNAs (circRNAs) in 10 ESCC and corresponding paracarcinoma tissues was analyzed through circRNA microarray, then the candidate circRNAs were detected and verified through quantitative RT-PCR, and a novel circRNA was screened, which was circLPAR3. Circular RNA LPAR3 showed apparently high expression in ESCC tissues and cells, which was closely correlated with the clinical stage and lymph node metastasis of ESCC patients. Circular RNA LPAR3 was mainly located in the cytoplasm of ESCC cells, which was more stable than the baseline gene. Circular RNA LPAR3 upregulated MET gene expression through sponge adsorption of microRNA (miR)-198, activated the RAS/MAPK and the PI3K/Akt pathways, and promoted ESCC cell migration, invasion, and metastasis in vivo and in vitro. However, it had no effect on ESCC cell proliferation. Circular RNA LPAR3 can regulate the miR-198-MET signal axis to promote the migration, invasion, and metastasis of esophageal cancer cells, which can thereby serve as a potential diagnostic and therapeutic target of esophageal cancer.

Quantitative Assessment of the Effects of Compression on Deep Learning in Digital Pathology Image Analysis.

PURPOSE: Deep learning (DL), a class of approaches involving self-learned discriminative features, is increasingly being applied to digital pathology (DP) images for tasks such as disease identification and segmentation of tissue primitives (eg, nuclei, glands, lymphocytes). One application of DP is in telepathology, which involves digitally transmitting DP slides over the Internet for secondary diagnosis by an expert at a remote location. Unfortunately, the places benefiting most from telepathology often have poor Internet quality, resulting in prohibitive transmission times of DP images. Image compression may help, but the degree to which image compression affects performance of DL algorithms has been largely unexplored. METHODS: We investigated the effects of image compression on the performance of DL strategies in the context of 3 representative use cases involving segmentation of nuclei (n = 137), segmentation of lymph node metastasis (n = 380), and lymphocyte detection (n = 100). For each use case, test images at various levels of compression (JPEG compression quality score ranging from 1-100 and JPEG2000 compression peak signal-to-noise ratio ranging from 18-100 dB) were evaluated by a DL classifier. Performance metrics including F1 score and area under the receiver operating characteristic curve were computed at the various compression levels. RESULTS: Our results suggest that DP images can be compressed by 85% while still maintaining the performance of the DL algorithms at 95% of what is achievable without any compression. Interestingly, the maximum compression level sustainable by DL algorithms is similar to where pathologists also reported difficulties in providing accurate interpretations. CONCLUSION: Our findings seem to suggest that in low-resource settings, DP images can be significantly compressed before transmission for DL-based telepathology applications.