Development and validation of a nomogram for predicting survival of pulmonary invasive mucinous adenocarcinoma based on surveillance, epidemiology, and end results (SEER) database.

BACKGROUND: Lung cancer remains the leading cause of cancer death globally. In 2015, the cancer classification guidelines of the World Health Organization were updated. The term "invasive mucinous adenocarcinoma (IMA)" aroused people's attention, while the clinicopathological factors that may influence survival were unclear. METHODS: Data of IMA patients was downloaded from SEER database. Kaplan-Meier methods and log-rank tests were used to compare the differences in OS and LCSS. The nomogram was developed based on the result of the multivariable analysis. The discrimination and accuracy were tested by Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, calibration curve and decision curve analyses (DCA). Integrated discrimination improvement (IDI) index was used to evaluate the clinical efficacy. RESULTS: According to multivariate analysis, the prognosis of IMAs was associated with age, differentiation grade, TNM stage and treatments. Surgery might be the only way that would improve survival. Area under the curve (AUC) of the training cohort was 0.834and 0.830 for3-and 5-year OS, respectively. AUC for 3-and 5-year LCSS were separately 0.839 and 0.839. The new model was then evaluated by calibration curve, DCA and IDI index. CONCLUSION: Based on this study, prognosis of IMAs was systematically reviewed, and a new nomogram was developed and validated. This model helps us understand IMA in depth and provides new ideas for IMA treatment.

Regulation of flagellar motor switching by c-di-GMP phosphodiesterases in Pseudomonas aeruginosa.

The second messenger cyclic diguanylate (c-di-GMP) plays a prominent role in regulating flagellum-dependent motility in the single-flagellated pathogenic bacterium Pseudomonas aeruginosa The c-di-GMP-mediated signaling pathways and mechanisms that control flagellar output remain to be fully unveiled. Studying surface-tethered and free-swimming P. aeruginosa PAO1 cells, we found that the overexpression of an exogenous diguanylate cyclase (DGC) raises the global cellular c-di-GMP concentration and thereby inhibits flagellar motor switching and decreases motor speed, reducing swimming speed and reversal frequency, respectively. We noted that the inhibiting effect of c-di-GMP on flagellar motor switching, but not motor speed, is exerted through the c-di-GMP-binding adaptor protein MapZ and associated chemotactic pathways. Among the 22 putative c-di-GMP phosphodiesterases, we found that three of them (DipA, NbdA, and RbdA) can significantly inhibit flagellar motor switching and swimming directional reversal in a MapZ-dependent manner. These results disclose a network of c-di-GMP-signaling proteins that regulate chemotactic responses and flagellar motor switching in P. aeruginosa and establish MapZ as a key signaling hub that integrates inputs from different c-di-GMP-signaling pathways to control flagellar output and bacterial motility. We rationalized these experimental findings by invoking a model that postulates the regulation of flagellar motor switching by subcellular c-di-GMP pools.

Structural analyses unravel the molecular mechanism of cyclic di-GMP regulation of bacterial chemotaxis via a PilZ adaptor protein.

The bacterial second messenger cyclic di-GMP (c-di-GMP) has emerged as a prominent mediator of bacterial physiology, motility, and pathogenicity. c-di-GMP often regulates the function of its protein targets through a unique mechanism that involves a discrete PilZ adaptor protein. However, the molecular mechanism for PilZ protein-mediated protein regulation is unclear. Here, we present the structure of the PilZ adaptor protein MapZ cocrystallized in complex with c-di-GMP and its protein target CheR1, a chemotaxis-regulating methyltransferase in Pseudomonas aeruginosa This cocrystal structure, together with the structure of free CheR1, revealed that the binding of c-di-GMP induces dramatic structural changes in MapZ that are crucial for CheR1 binding. Importantly, we found that restructuring and repositioning of two C-terminal helices enable MapZ to disrupt the CheR1 active site by dislodging a structural domain. The crystallographic observations are reinforced by protein-protein binding and single cell-based flagellar motor switching analyses. Our studies further suggest that the regulation of chemotaxis by c-di-GMP through MapZ orthologs/homologs is widespread in proteobacteria and that the use of allosterically regulated C-terminal motifs could be a common mechanism for PilZ adaptor proteins. Together, the findings provide detailed structural insights into how c-di-GMP controls the activity of an enzyme target indirectly through a PilZ adaptor protein.

POPX2 phosphatase regulates the KIF3 kinesin motor complex.

The kinesin motors are important in the regulation of cellular functions such as protein trafficking, spindle organization and centrosome separation. In this study, we have identified POPX2, a serine-threonine phosphatase, as an interacting partner of the KAP3 subunit of the kinesin-2 motor. The kinesin-2 motor is a heterotrimeric complex composed of KIF3A, KIF3B motor subunits and KAP3, the non-motor subunit, which binds the cargo. Here we report that the phosphatase POPX2 is a negative regulator of the trafficking of N-cadherin and other cargoes; consequently, it markedly influences cell-cell adhesion. POPX2 affects trafficking by determining the phosphorylation status of KIF3A at serine 690. This is consistent with the observation that the KIF3A-S690A mutant is defective in cargo trafficking. Our studies also implicate CaMKII as the kinase that phosphorylates KIF3A at serine 690. These results strongly suggest that POPX2 and CaMKII are a phosphatase-kinase pair that regulates kinesin-mediated transport and cell-cell adhesion.

Prediction of hepatic metastasis in esophageal cancer based on machine learning.

This study aimed to establish a machine learning (ML) model for predicting hepatic metastasis in esophageal cancer. We retrospectively analyzed patients with esophageal cancer recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2020. We identified 11 indicators associated with the risk of liver metastasis through univariate and multivariate logistic regression. Subsequently, these indicators were incorporated into six ML classifiers to build corresponding predictive models. The performance of these models was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. A total of 17,800 patients diagnosed with esophageal cancer were included in this study. Age, primary site, histology, tumor grade, T stage, N stage, surgical intervention, radiotherapy, chemotherapy, bone metastasis, and lung metastasis were independent risk factors for hepatic metastasis in esophageal cancer patients. Among the six models developed, the ML model constructed using the GBM algorithm exhibited the highest performance during internal validation of the dataset, with AUC, accuracy, sensitivity, and specificity of 0.885, 0.868, 0.667, and 0.888, respectively. Based on the GBM algorithm, we developed an accessible web-based prediction tool (accessible at https://project2-dngisws9d7xkygjcvnue8u.streamlit.app/ ) for predicting the risk of hepatic metastasis in esophageal cancer.

Use machine learning to predict pulmonary metastasis of esophageal cancer: a population-based study.

BACKGROUND: This study aims to establish a predictive model for assessing the risk of esophageal cancer lung metastasis using machine learning techniques. METHODS: Data on esophageal cancer patients from 2010 to 2020 were extracted from the surveillance, epidemiology, and end results (SEER) database. Through univariate and multivariate logistic regression analyses, eight indicators related to the risk of lung metastasis were selected. These indicators were incorporated into six machine learning classifiers to develop corresponding predictive models. The performance of these models was evaluated and compared using metrics such as The area under curve (AUC), accuracy, sensitivity, specificity, and F1 score. RESULTS: A total of 20,249 confirmed cases of esophageal cancer were included in this study. Among them, 14,174 cases (70%) were assigned to the training set while 6075 cases (30%) constituted the internal test set. Primary site location, tumor histology, tumor grade classification system T staging criteria N staging criteria brain metastasis bone metastasis liver metastasis emerged as independent risk factors for esophageal cancer with lung metastasis. Amongst the six constructed models, the GBM algorithm-based machine learning model demonstrated superior performance during internal dataset validation. AUC, accuracy, sensitivity, and specificity values achieved by this model stood at respectively at 0.803, 0.849, 0.604, and 0.867. CONCLUSION: We have developed an online calculator based on the GBM model ( https://lvgrkyxcgdvo7ugoyxyywe.streamlit.app/)to aid clinical decision-making and treatment planning.

The role of cell-matrix adhesion and cell migration in breast tumor growth and progression.

During breast cancer progression, there is typically increased collagen deposition resulting in elevated extracellular matrix rigidity. This results in changes to cell-matrix adhesion and cell migration, impacting processes such as the epithelial-mesenchymal transition (EMT) and metastasis. We aim to investigate the roles of cell-matrix adhesion and cell migration on breast tumor growth and progression by studying the impacts of different types of extracellular matrices and their rigidities. We embedded MCF7 spheroids within three-dimensional (3D) collagen matrices and agarose matrices. MCF7 cells adhere to collagen but not agarose. Contrasting the results between these two matrices allows us to infer the role of cell-matrix adhesion. We found that MCF7 spheroids exhibited the fastest growth rate when embedded in a collagen matrix with a rigidity of 5.1 kPa (0.5 mg/mL collagen), whereas, for the agarose matrix, the rigidity for the fastest growth rate is 15 kPa (1.0% agarose) instead. This discrepancy is attributable to the presence of cell adhesion molecules in the collagen matrix, which initiates collagen matrix remodeling and facilitates cell migration from the tumor through the EMT. As breast tumors do not adhere to agarose matrices, it is suitable to simulate the cell-cell interactions during the early stage of breast tumor growth. We conducted further analysis to characterize the stresses exerted by the expanding spheroid on the agarose matrix. We identified two distinct MCF7 cell populations, namely, those that are non-dividing and those that are dividing, which exerted low and high expansion stresses on the agarose matrix, respectively. We confirmed this using Western blot which showed the upregulation of proliferating cell nuclear antigen, a proliferation marker, in spheroids grown in the 1.0% agarose (≈13 kPa). By treating the embedded MCF7 spheroids with an inhibitor or activator of myosin contractility, we showed that the optimum spheroids' growth can be increased or decreased, respectively. This finding suggests that tumor growth in the early stage, where cell-cell interaction is more prominent, is determined by actomyosin tension, which alters cell rounding pressure during cell division. However, when breast tumors begin generating collagen into the surrounding matrix, collagen remodeling triggers EMT to promote cell migration and invasion, ultimately leading to metastasis.

Comprehensive analysis of suppressor of cytokine signaling 2 protein in the malignant transformation of NSCLC.

Suppressor of cytokine signaling 2 (SOCS2) plays an essential role in a number of physiological phenomena and functions as a tumor suppressor. Understanding the predictive effects of SOCS2 on non-small cell lung cancer (NSCLC) is urgently needed. The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to assess SOCS2 gene expression levels in NSCLC. The clinical significance of SOCS2 was evaluated through Kaplan-Meier curve analysis and the analysis of related clinical factors. Gene Set Enrichment Analysis (GSEA) was used to identify the biological functions of SOCS2. Subsequently proliferation, wound-healing, colony formation and Transwell assays, and carboplatin drug experiments were used for verification. The results revealed that SOCS2 expression was low in the NSCLC tissues of patients in TCGA and GEO database analyses. Downregulated SOCS2 was associated with poor prognosis, as determined by Kaplan-Meier survival analysis (HR 0.61, 95% CI 0.52-0.73; P<0.001). GSEA showed that SOCS2 was involved in intracellular reactions, including epithelial-mesenchymal transition (EMT). Cell experiments indicated that knockdown of SOCS2 caused the malignant progression of NSCLC cell lines. Furthermore, the drug experiment showed that silencing of SOCS2 promoted the resistance of NSCLC cells to carboplatin. In conclusion, low expression of SOCS2 was associated with poor clinical prognosis by effecting EMT and causing drug resistance in NSCLC cell lines. Furthermore, SOCS2 could act as a predictive indicator for NSCLC.

High-Efficiency Antibacterial Hemostatic AgNP@Zeolite/Chitin/Bamboo Composite Sponge for Wound Healing without Heat Injury.

Chitin is a popular hemostatic material, but there are still many deficiencies in its ability to effectively stop bleeding, prevent infection, and fit wounds. Herein, AgNP@zeolite/chitin/bamboo (AgZ-CB) composite sponges with shape recovery are prepared to minimize blood loss, kill bacteria, and promote wound healing. Notably, the bamboo powder is used for the first time to remarkably enhance the softness of the composite sponge (volumetric expansion ratio >5). The fabricated AgZ-CB sponge exhibits an excellent killing effect (≈100% bactericidal rate) against both Escherichia coli and Staphylococcus aureus and activates internal and external coagulation pathways to accelerate hemostasis without causing thermal damage (≈5 °C temperature difference). Moreover, the AgZ-CB sponge shows less blood loss (26 mg) and a shorter time to hemostasis (42 s) than the commercial polyvinyl formal sponge (84 mg and 76 s) in the full-thickness liver injury model. The in vivo wound healing and biodegradation experiment indicate that AgZ-CB with excellent biocompatibility can close wounds efficiently. Overall, the AgZ-CB sponge has great potential in combating a series of obstacles in wound healing.

Trim21 depletion alleviates bone loss in osteoporosis via activation of YAP1/ß-catenin signaling.

Despite the diverse roles of tripartite motif (Trim)-containing proteins in the regulation of autophagy, the innate immune response, and cell differentiation, their roles in skeletal diseases are largely unknown. We recently demonstrated that Trim21 plays a crucial role in regulating osteoblast (OB) differentiation in osteosarcoma. However, how Trim21 contributes to skeletal degenerative disorders, including osteoporosis, remains unknown. First, human and mouse bone specimens were evaluated, and the results showed that Trim21 expression was significantly elevated in bone tissues obtained from osteoporosis patients. Next, we found that global knockout of the Trim21 gene (KO, Trim21-/-) resulted in higher bone mass compared to that of the control littermates. We further demonstrated that loss of Trim21 promoted bone formation by enhancing the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) and elevating the activity of OBs; moreover, Trim21 depletion suppressed osteoclast (OC) formation of RAW264.7 cells. In addition, the differentiation of OCs from bone marrow-derived macrophages (BMMs) isolated from Trim21-/- and Ctsk-cre; Trim21f/f mice was largely compromised compared to that of the littermate control mice. Mechanistically, YAP1/ß-catenin signaling was identified and demonstrated to be required for the Trim21-mediated osteogenic differentiation of BMSCs. More importantly, the loss of Trim21 prevented ovariectomy (OVX)- and lipopolysaccharide (LPS)-induced bone loss in vivo by orchestrating the coupling of OBs and OCs through YAP1 signaling. Our current study demonstrated that Trim21 is crucial for regulating OB-mediated bone formation and OC-mediated bone resorption, thereby providing a basis for exploring Trim21 as a novel dual-targeting approach for treating osteoporosis and pathological bone loss.

The Prognostic Model and Drug Sensitivity of LKB1-Mutant Lung Adenocarcinoma Based on Immune Landscape.

Background: Lung cancer is the most common cause of cancer-related deaths worldwide. LKB1-mutant lung adenocarcinoma (LUAD) is a unique subtype of this deadly cancer. LKB1 mutations cause functional changes in a variety of cell processes, including immune functions, that affect prognosis. To date, the potential role of immunity in the prognosis of LKB1-mutant LUAD is not well understood. Methods: We systematically analyzed immune-related genes in LUAD samples from The Cancer Genome Atlas (TCGA) database. ESTIMATE and CIBERSORT algorithms were used to explore the immune microenvironment. A prognostic risk model was constructed, and prognostic, immune function, drug sensitivity, and model specificity analyses were performed to identify the effectiveness of the model. Results: Our results showed that LKB1 mutations suppressed immune function in LUAD. A three-gene signature was constructed to stratify patients into two risk groups. The risk score was an independent predictor for overall survival (OS) in multivariate Cox regression analyses [hazard ratio (HR) > 1, p = 0.002]. Receiver operating characteristic (ROC) curve analyses confirmed that the risk score has better performance than clinicopathological characteristics. Functional analysis revealed that the immune status was different between the risk groups. ZM.447439 was an appropriate treatment for the high-risk group of patients. This risk model is only suitable for LKB1-mutant tumors; it performed poorly in LUAD patients with wild-type LKB1. Conclusion: Our findings indicate the potential role of immunity in LKB1-mutant LUAD, providing novel insights into prognosis and guiding effective immunotherapy.

Prognostic analysis and clinical characteristics of dual primary lung cancer: a population study based on surveillance, epidemiology, and end results (SEER) database.

BACKGROUND: The peculiarity and the lack of clinical studies of dual primary lung cancer (DPLC) led to limited knowledge about its clinical characteristics and prognosis. This study performed a retrospective analysis to assess the prognostic factors and clinical characteristics of DPLC. METHODS: A total of 1419 DPLC patients from SEER were analyzed by univariate and multivariable Cox regression analyses. The independent prognostic factors were included to establish a nomogram. The accuracy and reliability of prognostic model were evaluated by C indexes, calibration plots, receiver operating characteristic (ROC) curves, decision curve analyses (DCA) and integrated discrimination improvement (IDI) scores. Chi-square test was used to assess the differences between DPLC and single primary lung cancer (SPLC) or synchronous DPLC (sDPLC) and metachronous DPLC (mDPLC). RESULTS: Cox regression analysis showed that age, sex, histological type, stage, lymph node (LN) metastasis, surgery, chemotherapy were independent prognostic factors, we included these factors to establish a nomogram. In the training cohort, the C index was 0.690, and the area under curves (AUC) of 3 and 5-year survival time were 0.720 and 0.723. The calibration plots in training cohort and validation cohort were in excellent agreement. DCA and IDI showed that the predictive effect of the novel prognostic model was better than the model based on 8th AJCC TNM system. Chi-square test indicated that DPLC and SPLC had statistical differences on pathological and clinical features. CONCLUSIONS: The clinical and pathological characteristics of DPLC were different from the SPLC. The nomogram could provide accurate and individualized survival predictions for DPLC.

Senescent skeletal cells cross-talk with synovial cells plays a key role in the pathogenesis of osteoarthritis.

Osteoarthritis (OA) has been recognized as an age-related degenerative disease commonly seen in the elderly that affects the whole "organ" including cartilage, subchondral bone, synovium, and muscles. An increasing number of studies have suggested that the accumulation of senescent cells triggering by various stresses in the local joint contributes to the pathogenesis of age-related diseases including OA. In this review, we mainly focus on the role of the senescent skeletal cells (chondrocytes, osteoblasts, osteoclasts, osteocyte, and muscle cells) in initiating the development and progression of OA alone or through cross-talk with the macrophages/synovial cells. Accordingly, we summarize the current OA-targeted therapies based on the abovementioned theory, e.g., by eliminating senescent skeletal cells and/or inhibiting the senescence-associated secretory phenotype (SASP) that drives senescence. Furthermore, the existing animal models for the study of OA from the perspective of senescence are highlighted to fill the gap between basic research and clinical applications. Overall, in this review, we systematically assess the current understanding of cellular senescence in OA, which in turn might shed light on the stratified OA treatments.

Investigating circular dorsal ruffles through varying substrate stiffness and mathematical modeling.

Circular dorsal ruffles (CDRs) are transient actin-rich ringlike structures that form on the dorsal surface of growth-factor stimulated cells. However, the dynamics and mechanism of formation of CDRs are still unknown. It has been observed that CDR formation leads to stress fibers disappearing near the CDRs. Because stress fiber formation can be modified by substrate stiffness, we examined the effect of substrate stiffness on CDR formation by seeding NIH 3T3 fibroblasts on glass and polydimethylsiloxane substrates of varying stiffnesses from 20 kPa to 1800 kPa. We found that increasing substrate stiffness increased the lifetime of the CDRs. We developed a mathematical model of the signaling pathways involved in CDR formation to provide insight into this lifetime and size dependence that is linked to substrate stiffness via Rac-Rho antagonism. From the model, increasing stiffness raised mDia1-nucleated stress fiber formation due to Rho activation. The increased stress fibers present increased replenishment of the G-actin pool, therefore prolonging Arp2/3-nucleated CDR formation due to Rac activation. Negative feedback by WAVE-related RacGAP on Rac explained how CDR actin propagates as an excitable wave, much like wave propagation in other excitable medium, e.g., nerve signal transmission.

Prognostic model of AU-rich genes predicting the prognosis of lung adenocarcinoma.

BACKGROUND: AU-rich elements (ARE) are vital cis-acting short sequences in the 3'UTR affecting mRNA stability and translation. The deregulation of ARE-mediated pathways can contribute to tumorigenesis and development. Consequently, ARE-genes are promising to predict prognosis of lung adenocarcinoma (LUAD) patients. METHODS: Differentially expressed ARE-genes between LUAD and adjacent tissues in TCGA were investigated by Wilcoxon test. LASSO and Cox regression analyses were performed to identify a prognostic genetic signature. The genetic signature was combined with clinicopathological features to establish a prognostic model. LUAD patients were divided into high- and low-risk groups by the model. Kaplan-Meier curve, Harrell's concordance index (C-index), calibration curves and decision curve analyses (DCA) were used to assess the model. Function enrichment analysis, immunity and tumor mutation analyses were performed to further explore the underlying molecular mechanisms. GEO data were used for external validation. RESULTS: Twelve prognostic genes were identified. The gene riskScore, age and stage were independent prognostic factors. The high-risk group had worse overall survival and was less sensitive to chemotherapy and radiotherapy (P < 0.01). C-index and calibration curves showed good performance on survival prediction in both TCGA (1, 3, 5-year ROC: 0.788, 0.776, 0.766) and the GSE13213 validation cohort (1, 3, 5-year ROC: 0.781, 0.811, 0.734). DCA showed the model had notable clinical net benefit. Furthermore, the high-risk group were enriched in cell cycle, DNA damage response, multiple oncological pathways and associated with higher PD-L1 expression, M1 macrophage infiltration. There was no significant difference in tumor mutation burden (TMB) between high- and low-risk groups. CONCLUSION: ARE-genes can reliably predict prognosis of LUAD and may become new therapeutic targets for LUAD.

Dynamic swimming pattern of Pseudomonas aeruginosa near a vertical wall during initial attachment stages of biofilm formation.

Studying the swimming behaviour of bacteria in 3 dimensions (3D) allows us to understand critical biological processes, such as biofilm formation. It is still unclear how near wall swimming behaviour may regulate the initial attachment and biofilm formation. It is challenging to address this as visualizing the movement of bacteria with reasonable spatial and temporal resolution in a high-throughput manner is technically difficult. Here, we compared the near wall (vertical) swimming behaviour of P. aeruginosa (PAO1) and its mutants ΔdipA (reduced in swarming motility and increased in biofilm formation) and ΔfimX (deficient in twitching motility and reduced in biofilm formation) using our new imaging technique based on light sheet microscopy. We found that P. aeruginosa (PAO1) increases its speed and changes its swimming angle drastically when it gets closer to a wall. In contrast, ΔdipA mutant moves toward the wall with steady speed without changing of swimming angle. The near wall behavior of ΔdipA allows it to be more effective to interact with the wall or wall-attached cells, thus leading to more adhesion events and a larger biofilm volume during initial attachment when compared with PAO1. Furthermore, we found that ΔfimX has a similar near wall swimming behavior as PAO1. However, it has a higher dispersal frequency and smaller biofilm formation when compared with PAO1 which can be explained by its poor twitching motility. Together, we propose that near wall swimming behavior of P. aeruginosa plays an important role in the regulation of initial attachment and biofilm formation.

The role of surgery for atypical bronchopulmonary carcinoid tumor: Development and validation of a model based on Surveillance, Epidemiology, and End Results (SEER) database.

OBJECTIVES: The rarity of atypical carcinoid (AC) of lung and the lack of prospective clinical trials lead to limited knowledge of its biology, treatment information and prognosis. The current study analyzed AC patients from the Surveillance, Epidemiology, and End Results (SEER) database to better understand the clinical characteristics of this disease and build a prognostic nomogram for clinical practice. MATERIALS AND METHODS: A total of 507 AC patients with pathological confirmation from SEER database were performed with univariate Cox regression analyses for both overall survival (OS) and lung cancer specific survival (LCSS) analyses. Of the 507 observations, 464 were used in the multivariable Cox proportional hazards model as training cohort of new nomogram. A new nomogram was constructed based on the training cohort and validated by an external validation cohort to predict the 3-, 5- and 10-year OS of ACs. The accuracy and clinical practicability were separately tested by Harrell's C-indexes, calibration plots and decision curve analyses (DCA). RESULTS: Lobectomy and segmental resection were found to be protective factors for AC patients. Age, primary tumor size, N stage, M stage, surgery and regional lymph nodes examination were shown as significant prognostic factors in Cox regression analyses and included in the nomogram as predictors. The C-index in the training cohort for 3-, 5-, and 10-year OS were 0.722, 0.737 and 0.712, respectively. The internal and external calibration plots for predictions of the 3-, 5-, and 10-year OS were in excellent agreement. An online webserver was built based on the proposed nomogram for convenient clinical use. CONCLUSION: AC patients with lobectomy or segmental resection tended to have better OS and LCSS. A nomogram was constructed and validated to predict the OS for AC patients and to provide accurate and individualized survival predictions.

Wedge resection is equal to segmental resection for pulmonary typical carcinoid patients at localized stage: a population-based analysis.

BACKGROUND: Medical institutions worldwide have not reached a consensus on what surgery is the most advisable for pulmonary typical carcinoid (TC) patients at the localized stage. This research focuses on exploring whether wedge resection or segmental resection is the superior option. METHODS: The demographic and clinical information of 1,887 TC patients diagnosed at the localized stage from 2004 to 2015 was collected from the Surveillance, Epidemiology, and End Results (SEER) Program. Patient prognosis was evaluated by KM curves. The chi-square test was used to examine the variation between different groups that would be eliminated by propensity score matching (PSM). Univariate and multivariate Cox proportional hazard model analyses were used to evaluate prognostic values of relative factors. RESULTS: The prognosis of TC was the most favorable for patients suffering from pulmonary squamous cell carcinoma (SCC), adenocarcinoma (ADC), and pulmonary carcinoids (PCs). The choice to have surgery, not the type of surgery chosen, was the most significant independent prognostic factor correlated with overall survival (OS) and lung cancer-special survival (LCSS). The prognostic result of the comparison between wedge resection and segmental resection was not statistically significant before or after PSM. In subgroup analysis, the inference still held.

Enrichment and Identification of Neural Stem Cells in Neurospheres Using Rigidity-Tunable Gels.

IMPACT STATEMENT: Neural stem cells (NCSs) are integral to establishing in vitro models and regenerative medicine. To this day, there is an unmet need to enrich these cells from a heterogeneous cell population for clinical applications without irreversible manipulation. We identified a method to propagate human NCSs via computational analysis of their mechanical signature. In this study, we report a novel analytical method for mechanical forces in three-dimensional cultures. Further, our results revealed that stemness may, in part, be mediated by physical properties of the extracellular matrix. In conclusion, our findings have potential implications in understanding stem cell mechanobiology for enrichment or differentiation.

Human mesenchymal stem cell basal membrane bending on gratings is dependent on both grating width and curvature.

The topography of the extracellular substrate provides physical cues to elicit specific downstream biophysical and biochemical effects in cells. An example of such a topographical substrate is periodic gratings, where the dimensions of the periodic gratings influence cell morphology and directs cell differentiation. We first develop a novel sample preparation technique using Spurr's resin to allow for cross-sectional transmission electron microscopy imaging of cells on grating grooves, and observed that the plasma membrane on the basal surface of these cells can deform and bend into grooves between the gratings. We postulate that such membrane bending is an important first step in eliciting downstream effects. Thus, we use a combination of image analysis and mathematical modeling to explain the extent of bending of basal membrane into grooves. We show that the extent to which the basal membrane bends into grooves depends on both groove width and angle of the grating ridge. Our model predicts that the basal membrane will bend into grooves when they are wider than 1.9 µm in width. The existence of such a threshold may provide an explanation for how the width of periodic gratings may bring about cellular downstream effects, such as cell proliferation or differentiation.