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Abstract Background Monitoring hand hygiene compliance (HHC) of healthcare providers (HCPs) in healthcare facilities is critical for hand hygiene (HH) promotion. However, less is known about the cost and effectiveness of different HHC monitoring tools. In this study, we aimed to compare various health economic indicators corresponding to electronic system-based monitoring (ESM) and manual paper-based monitoring (MPM) for HHC to provide evidence-based advice for HHC monitoring measures targeted selecting. Methods A before and after study in 40 clinical departments with 4,524 healthcare providers was conducted from December 2022 to January 2023 (MPM implementation phase) and March 2023 to May 2023 (ESM implementation phase). The cost-effectiveness, cost-efficiency, the extent of the Hawthorne effect, and indirect cost-benefit of the two monitoring methods were compared. Results The total cost spent on ESM for the 40 departments (17,702.92 CNY) was 4,123.76 CNY lower than that of MPM (21,826.68 CNY). The HHC of MPM (80.16%) was higher than that of ESM (69.82%) (p

Summary: Antipsychotic drugs have been shown to have antitumor effects but have had limited potency in the clinic. Here, we unveil that pimozide inhibits lysosome hydrolytic function to suppress fatty acid and cholesterol release in glioblastoma (GBM), the most lethal brain tumor. Unexpectedly, GBM develops resistance to pimozide by boosting glutamine consumption and lipogenesis. These elevations are driven by SREBP-1, which we find upregulates the expression of ASCT2, a key glutamine transporter. Glutamine, in turn, intensifies SREBP-1 activation through the release of ammonia, creating a feedforward loop that amplifies both glutamine metabolism and lipid synthesis, leading to drug resistance. Disrupting this loop via pharmacological targeting of ASCT2 or glutaminase, in combination with pimozide, induces remarkable mitochondrial damage and oxidative stress, leading to GBM cell death in vitro and in vivo. Our findings underscore the promising therapeutic potential of effectively targeting GBM by combining glutamine metabolism inhibition with lysosome suppression.

Abstract We introduce a computational approach for the design of target-specific peptides. Our method integrates a Gated Recurrent Unit-based Variational Autoencoder with Rosetta FlexPepDock for peptide sequence generation and binding affinity assessment. Subsequently, molecular dynamics simulations are employed to narrow down the selection of peptides for experimental assays. We apply this computational strategy to design peptide inhibitors that specifically target β-catenin and NF-κB essential modulator. Among the twelve β-catenin inhibitors, six exhibit improved binding affinity compared to the parent peptide. Notably, the best C-terminal peptide binds β-catenin with an IC50 of 0.010 ± 0.06 μM, which is 15-fold better than the parent peptide. For NF-κB essential modulator, two of the four tested peptides display substantially enhanced binding compared to the parent peptide. Collectively, this study underscores the successful integration of deep learning and structure-based modeling and simulation for target specific peptide design.

BackgroundParenting a preterm infant can be incredibly challenging and stressful, particularly in the first year after discharge. Desirable parental role adaptation leads to appropriate parenting behaviors and parent-infant interaction, which are essential to child health and development.AimTo investigate the level of parental role adaptation and its influencing factors among parents of preterm infants in the first year after hospital discharge according to Belsky’s parenting process model among parents of preterm infants in the first year after hospital discharge.MethodsA cross-sectional study design was adopted using convenience sampling. Data were collected using the Parental Role Adaptation Scale (PRAS) in parents with preterm infants, the Perceived Social Support Scale (PSSS), the Coping Adaptation Processing Scale (CAPS-15), and a sociodemographic questionnaire. Descriptive statistics, non-parametric tests, Spearman correlation analyses, and multivariate linear regression were used to analyze the data.ResultsIn total, 300 Chinese parents were included in the analysis. In the multivariate analysis, first-time parent (p = 0.003), master’s degree and above (p = 0.042), coping adaptation processing (p = 0.000), residence location (towns: p = 0.019, city: p = 0.028), monthly family income (6000–10,000: p = 0.000, >10,000: p = 0.000), and perceived social support (p = 0.001) were all significant predictors of parental role adaptation and collectively accounted for 56.8% of the variation in parental role adaptation of parents with preterm infants (F = 16.473, p

Purpose – The paper aims to address the organizational transformation of firms for value creation resulting from cloud computing (CC). Design/methodology/approach – With reference to the theory of organizational fit, we modeled organizational transformation as a function of five aspects of CC practice: functionality, data management, roles and competences of information technology services, control and organizational culture. The output variable was tested against a set of input variables defined with reference to the technology–organization–environment (TOE) and technology acceptance model (TAM). Based on a sample of 487 companies in seven countries in Europe, Asia, and the United States, the authors distinguished two groups of firms: transformational and hyper transformational. Findings – The results highlight the key factors that determine whether a firm falls into one of these two groups, and include perceived usefulness and perceived ease of use, complexity and compatibility of CC technology, and adequacy of resources. Top management support and government policy are found to only play a role for the transformational group while, surprisingly, vendor support had no impact for either group. Originality/value – This research contributes to the literature on the role of digital transformation in value creation and on digitization of firms and organizational design, notably by considering the contribution of CC to the organizational dimension. To the best of the authors’ knowledge, this is the first study to make the link between TOE and TAM models and organizational fit theory, thereby going beyond the general approach to adoption found in information system research.

Abstract Male infertility caused by genetic mutations is an important type of infertility. Currently, there is no reliable method in the clinic to address this medical need. The emergence of mRNA therapy provides a possible strategy for restoring mutant genes in the reproductive system. However, effective delivery of mRNA to spermatocytes remains a formidable challenge. Here a series of cholesterol‐amino‐phosphate (CAP) lipids are reported by integrating three bioactive moieties into a geometric structure, which is favorable for mRNA delivery. The results demonstrate that CAP‐derived lipid nanoparticles (CAP LNPs) can deliver RNA including traditional mRNA and self‐amplifying RNA (saRNA) encoding DNA Meiotic Recombinase 1 (Dmc1) protein in spermatocytes and treat male infertility caused by the Dmc1 gene mutation. Notably, the delivery efficiency of CAP LNPs is significantly higher than that of the MC3 and ALC‐0315 LNPs, which is consistent with the design of CAP molecules. More importantly, a single injection of CAP LNPs–saRNA can produce Dmc1 protein for an extended period, which restores the spermatogenesis in the Dmc1 gene knockout mouse model. Overall, this study proves the concept of LNPs for the delivery of mRNA to spermatocytes, which provides a unique method to probe male infertility caused by the genetic mutation.

The smart grid connects components of power systems and communication networks in an interdependent two-way system that delivers electricity to consumers and collects data that enables it to react to usage levels and interference from threats, such as cyber-attacks. In this paper, we propose a novel cyber-attack failure propagation model in smart grids. Our realistic failure propagation model addresses the system’s heterogeneity by assigning different roles to its components. We define rules for and interdependencies of failure propagation and propose a new approach to studying cascading failures. In addition, our graph model identifies the most-vulnerable nodes. The model implements power flow analysis to guarantee that all transmission lines work below capacity and remove lines exceeding capacity. The model also considers that control packets could encounter different delays regarding the communication network structure and investigates the impact of communication delay on the failure of power components. Our results establish that by considering both power and communication characteristics and interdependencies, cascading failures can be modeled more accurately. We show that when we run the power flow analysis, there are a negligible number of failed nodes, which means that our model accurately identifies system failures.

COVID-19 has become an unprecedented threat to human health. The SARS-CoV-2 envelope (E) protein plays a critical role in the viral maturation process and pathogenesis. Despite intensive investigation, its structure in physiological conditions remains mysterious: no high-resolution full-length structure is available and only an NMR structure of the transmembrane (TM) region has been determined. Here, we present a refined E protein structure, using molecular dynamics (MD) simulations to investigate its structure and dynamics in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer system. Our initial homology model based upon the SARS-CoV E protein structure is shown to be unstable in the lipid bilayer, and the H3 helices tend to move away from the membrane center to the membrane-water interface. A more stable model was developed by replacing all H3 helices with the fully equilibrated H3 structure sampled in the MD simulations. This refined model exhibited more favorable contacts with lipids and water than the original homology model and induced local membrane curvature, decreasing local lipid order. Interestingly, the pore radius profiles showed that the channel in both homology and refined models remained in a closed state throughout the simulations. We also demonstrated the utility of this structure to develop anti-SARS-CoV-2 drugs by docking a library of FDA-approved, investigational, and experimental drugs to the refined E protein structure, identifying 20 potential channel blockers. This highlights the power of MD simulations to refine low-resolution structures of membrane proteins in a native-like membrane environment, shedding light on the structural features of the E protein and providing a platform for the development of novel antiviral treatments.

Mutations in ENT3, encoded by SLC29A3, result in anaemia and erythroid hypoplasia, suggesting roles in erythropoiesis. Here the authors show that ENT3 acts as a lysosomal bile acid transporter, and mutation compromises taurine conjugated bile acid transport in erythroid progenitors leading to ER stress, and anaemia.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is the most common pancreatic malignancy. Due to its wide heterogeneity, PDAC acts aggressively and responds poorly to most chemotherapies, causing an urgent need for the development of new therapeutic strategies. Cell lines have been used as the foundation for drug development and disease modeling. CRISPR-Cas9 plays a key role in every step-in drug discovery: from target identification and validation to preclinical cancer cell testing. Using cell-line models and CRISPR-Cas9 technology together make drug target prediction feasible. However, there is still a large gap between predicted results and actionable targets in real tumors. Biological network models provide great modus to mimic genetic interactions in real biological systems, which can benefit gene perturbation studies and potential target identification for treating PDAC. Nevertheless, building a network model that takes cell-line data and CRISPR-Cas9 data as input to accurately predict potential targets that will respond well on real tissue remains unsolved. Methods We developed a novel algorithm ‘Spectral Clustering for Network-based target Ranking’ (SCNrank) that systematically integrates three types of data: expression profiles from tumor tissue, normal tissue and cell-line PDAC; protein-protein interaction network (PPI); and CRISPR-Cas9 data to prioritize potential drug targets for PDAC. The whole algorithm can be classified into three steps: 1. using STRING PPI network skeleton, SCNrank constructs tissue-specific networks with PDAC tumor and normal pancreas tissues from expression profiles; 2. With the same network skeleton, SCNrank constructs cell-line-specific networks using the cell-line PDAC expression profiles and CRISPR-Cas 9 data from pancreatic cancer cell-lines; 3. SCNrank applies a novel spectral clustering approach to reduce data dimension and generate gene clusters that carry common features from both networks. Finally, SCNrank applies a scoring scheme called ‘Target Influence score’ (TI), which estimates a given target’s influence towards the cluster it belongs to, for scoring and ranking each drug target. Results We applied SCNrank to analyze 263 expression profiles, CRPSPR-Cas9 data from 22 different pancreatic cancer cell-lines and the STRING protein-protein interaction (PPI) network. With SCNrank, we successfully constructed an integrated tissue PDAC network and an integrated cell-line PDAC network, both of which contain 4414 selected genes that are overexpressed in tumor tissue samples. After clustering, 4414 genes are distributed into 198 clusters, which include 367 targets of FDA approved drugs. These drug targets are all scored and ranked by their TI scores, which we defined to measure their influence towards the network. We validated top-ranked targets in three aspects: Firstly, mapping them onto the existing clinical drug targets of PDAC to measure the concordance. Secondly, we performed enrichment analysis to these drug targets and the clusters there are within, to reveal functional associations between clusters and PDAC; Thirdly, we performed survival analysis for the top-ranked targets to connect targets with clinical outcomes. Survival analysis reveals that overexpression of three top-ranked genes, PGK1, HMMR and POLE2, significantly increases the risk of death in PDAC patients. Conclusion SCNrank is an unbiased algorithm that systematically integrates multiple types of omics data to do potential drug target selection and ranking. SCNrank shows great capability in predicting drug targets for PDAC. Pancreatic cancer-associated gene candidates predicted by our SCNrank approach have the potential to guide genetics-based anti-pancreatic drug discovery.

Real-time tool tracking in minimally invasive-surgery (MIS) has numerous applications for computer-assisted interventions (CAIs). Visual tracking approaches are a promising solution to real-time surgical tool tracking, however, many approaches may fail to complete tracking when the tracker suffers from issues such as motion blur, adverse lighting, specular reflections, shadows, and occlusions. We propose an automatic real-time method for two-dimensional tool detection and tracking based on a spatial transformer network (STN) and spatio-temporal context (STC). Our method exploits both the ability of a convolutional neural network (CNN) with an in-house trained STN and STC to accurately locate the tool at high speed. Then we compared our method experimentally with other four general of CAIs’ visual tracking methods using eight existing online and in-house datasets, covering both in vivo abdominal, cardiac and retinal clinical cases in which different surgical instruments were employed. The experiments demonstrate that our method achieved great performance with respect to the accuracy and the speed. It can track a surgical tool without labels in real time in the most challenging of cases, with an accuracy that is equal to and sometimes surpasses most state-of-the-art tracking algorithms. Further improvements to our method will focus on conditions of occlusion and multi-instruments.

To achieve the purpose of accurately grasping a random target with the upper limb prosthesis, the acquisition of target localization information is especially important. For this reason, a novel type of random target localization algorithm is proposed. Firstly, an initial localization algorithm (ILA) that uses two 3D attitude sensors and a laser range sensor to detect the target attitude and distance is presented. Secondly, an error correction algorithm where a multipopulation genetic algorithm (MPGA) optimizes backpropagation neural network (BPNN) is utilized to improve the accuracy of ILA. Thirdly, a general regression neural network (GRNN) algorithm is proposed to calculate the joint angles, which are used to control the upper limb prosthetic gripper to move to the target position. Finally, the proposed algorithm is applied to the 5-DOF upper limb prosthesis, and the simulations and experiments are proved to demonstrate the validity of the proposed localization algorithm and inverse kinematics (IK) algorithm.

The Aedes aegypti mosquito serves as a major vector for viral diseases, such as dengue, chikungunya, and Zika, which are spreading across the globe and threatening public health. In addition to increased vector transmission, the prevalence of insecticide-resistant mosquitoes is also on the rise, thus solidifying the need for new, safe and effective insecticides to control mosquito populations. We recently discovered that cinnamodial, a unique drimane sesquiterpene dialdehyde of the Malagasy medicinal plant Cinnamosma fragrans, exhibited significant larval and adult toxicity to Ae. aegypti and was more efficacious than DEET-the gold standard for insect repellents-at repelling adult female Ae. aegypti from blood feeding. In this study several semi-synthetic analogues of cinnamodial were prepared to probe the structure-activity relationship (SAR) for larvicidal, adulticidal and antifeedant activity against Ae. aegypti. Initial efforts were focused on modification of the dialdehyde functionality to produce more stable active analogues and to understand the importance of the 1,4-dialdehyde and the α,ß-unsaturated carbonyl in the observed bioactivity of cinnamodial against mosquitoes. This study represents the first investigation into the SAR of cinnamodial as an insecticide and antifeedant against the medically important Ae. aegypti mosquito.

Different from traditional redundant manipulators, the redundant manipulators used in the surgical environment require the end effector (EE) to have high pose (position and orientation) accuracy to ensure the smooth progress of the operation. When analyzing the inverse kinematics (IK) of traditional redundant manipulators, gradient-projection method (GPM) and weighted least-norm (WLN) method are commonly used methods to avoid joint position limits. However, for the traditional GPM and WLN method, when joints are close to their limits, they stop moving, which greatly reduces the accuracy of the IK solution. When robotic manipulators enter a singular region, although traditional damped least-squares (DLS) algorithms are used to handle singularities effectively, motion errors of the EE will be introduced. Furthermore, selecting singular region through trial and error may cause some joint velocities exceed their corresponding limits. More importantly, traditional DLS algorithms cannot guide robotic manipulators away from singular regions. Inspired by the merits of GPM, WLN, and DLS methods, an improved weighted gradient projection method (IWGPM) is proposed to solve the IK problem of redundant manipulators used in the surgical environment with avoiding joint position limits and singularities. The weighted matrix of the WLN method and the damping factor of the DLS algorithm have been improved, and a joint limit repulsive potential field function and singular repulsive potential field function belong to the null space are introduced to completely keep joints away from the damping interval and redundant manipulators away from the unsafe region. To verify the validity of the proposed IWGPM, simulations on a 7 degree of freedom (DOF) redundant manipulator used in laparoscopic surgery indicate that the proposed method can not only achieve higher accuracy IK solution but also avoid joint position limits and singularities effectively by comparing them with the results of the traditional GPM and WLN method, respectively. Furthermore, based on the proposed IWGPM, simulation tests in two cases show that joint position limits have a great impact on the orientation accuracy, and singular potential energy function has a great impact on the position accuracy.

The membrane transport of many cationic prescription drugs depends on facilitated transport by organic cation transporters of which several members, including OCT2 (SLC22A2), are sensitive to inhibition by select tyrosine kinase inhibitors (TKIs). We hypothesized that TKIs may differentially interact with the renal transporter MATE1 (SLC47A1) and influence the elimination and toxicity of the MATE1 substrate oxaliplatin. Interactions with FDA-approved TKIs were evaluated in transfected HEK293 cells, and in vivo pharmacokinetic studies were performed in wild-type, MATE1-deficient, and OCT2/MATE1-deficient mice. Of 57 TKIs evaluated, 37 potently inhibited MATE1 function by >80% through a non-competitive, reversible, substrate-independent mechanism. The urinary excretion of oxaliplatin was reduced by about 2-fold in mice with a deficiency of MATE1 or both OCT2 and MATE1 (p < 0.05), without impacting markers of acute renal injury. In addition, genetic or pharmacological inhibition of MATE1 did not significantly alter plasma levels of oxaliplatin, suggesting that MATE1 inhibitors are unlikely to influence the safety or drug-drug interaction liability of oxaliplatin-based chemotherapy.

Docking profiles for (+)-strebloside, a cytotoxic cardiac glycoside identified from Streblus asper, and some of its derivatives and Na+/K+-ATPase have been investigated. In addition, binding between (+)-strebloside and its aglycone, strophanthidin, and several of their other molecular targets, including FIH-1, HDAC, KEAP1 and MDM2 (negative regulators of Nrf2 and p53, respectively), NF-κB, and PI3K and Akt1, have been inspected and compared with those for digoxin and its aglycone, digoxigenin. The results showed that (+)-strebloside, digoxin, and their aglycones bind to KEAP1 and MDM2, while (+)-strebloside, strophanthidin, and digoxigenin dock to the active pocket of PI3K, and (+)-strebloside and digoxin interact with FIH-1. Thus, these cardiac glycosides could directly target HIF-1, Nrf2, and p53 protein–protein interactions, Na+/K+-ATPase, and PI3K to mediate their antitumor activity. Overall, (+)-strebloside seems more promising than digoxin for the development of potential anticancer agents.

Surgical instrument detection in robot-assisted surgery videos is an import vision component for these systems. Most of the current deep learning methods focus on single-tool detection and suffer from low detection speed. To address this, the authors propose a novel frame-by-frame detection method using a cascading convolutional neural network (CNN) which consists of two different CNNs for real-time multi-tool detection. An hourglass network and a modified visual geometry group (VGG) network are applied to jointly predict the localisation. The former CNN outputs detection heatmaps representing the location of tool tip areas, and the latter performs bounding-box regression for tool tip areas on these heatmaps stacked with input RGB image frames. The authors’ method is tested on the publicly available EndoVis Challenge dataset and the ATLAS Dione dataset. The experimental results show that their method achieves better performance than mainstream detection methods in terms of detection accuracy and speed.

Digoxin is a cardiac glycoside long used to treat congestive heart failure and found recently to show antitumor potential. The hydroxy groups connected at the C-12, C-14, and C-3′a positions; the C-17 unsaturated lactone unit; the conformation of the steroid core; and the C-3 saccharide moiety have been demonstrated as being important for digoxin’s cytotoxicity and interactions with Na+/K+-ATPase. The docking profiles for digoxin and several derivatives and Na+/K+-ATPase were investigated; an additional small Asn130 side pocket was revealed, which could be useful in the design of novel digoxin-like antitumor agents. In addition, the docking scores for digoxin and its derivatives were found to correlate with their cytotoxicity, indicating a potential use of these values in the prediction of the cancer cell cytotoxicity of other cardiac glycosides. Moreover, in these docking studies, digoxin was found to bind to FIH-1 and NF-κB but not HDAC, IAP, and PI3K, suggesting that this cardiac glycoside directly targets FIH-1, Na+/K+-ATPase, and NF-κB to mediate its antitumor potential. Differentially, digoxigenin, the aglycon of digoxin, binds to HDAC and PI3K, but not FIH-1, IAP, Na+/K+-ATPase, and NF-κB, indicating that this compound may target tumor autophagy and metabolism to mediate its antitumor propensity.

Amyloid is a complex pathologic matrix comprised principally of paracrystalline protein fibrils and heparan sulfate proteoglycans. Systemic amyloid diseases are rare, thus, routine diagnosis is often challenging. The glycosaminoglycans ubiquitously present in amyloid deposits are biochemically and electrochemically distinct from those found in the healthy tissues due to the high degree of sulfation. We have exploited this unique property and evaluated heparin-reactive peptides, such as p5+14, as novel agents for specifically targeting and imaging amyloid. Herein, we demonstrate that radiolabeled p5+14 effectively bound murine AA amyloid in vivo by using molecular imaging. Biotinylated peptide also reacted with the major forms of human amyloid in tissue sections as evidenced immunohistochemically. Furthermore, we have demonstrated that the peptide also binds synthetic amyloid fibrils that lack glycosaminoglycans implying that the dense anionic motif present on heparin is mimicked by the amyloid protein fibril itself. These biochemical and functional data support the translation of radiolabeled peptide p5+14 for the clinical imaging of amyloid in patients.

Examining the fundamental structure and processes of living cells at the nanoscale poses a unique analytical challenge, as cells are dynamic, chemically diverse, and fragile. A case in point is the cell membrane, which is too small to be seen directly with optical microscopy and provides little observational contrast for other methods. As a consequence, nanoscale characterization of the membrane has been performed ex vivo or in the presence of exogenous labels used to enhance contrast and impart specificity. Here, we introduce an isotopic labeling strategy in the gram-positive bacterium Bacillus subtilis to investigate the nanoscale structure and organization of its plasma membrane in vivo. Through genetic and chemical manipulation of the organism, we labeled the cell and its membrane independently with specific amounts of hydrogen (H) and deuterium (D). These isotopes have different neutron scattering properties without altering the chemical composition of the cells. From neutron scattering spectra, we confirmed that the B. subtilis cell membrane is lamellar and determined that its average hydrophobic thickness is 24.3 ± 0.9 Ångstroms (Å). Furthermore, by creating neutron contrast within the plane of the membrane using a mixture of H- and D-fatty acids, we detected lateral features smaller than 40 nm that are consistent with the notion of lipid rafts. These experiments-performed under biologically relevant conditions-answer long-standing questions in membrane biology and illustrate a fundamentally new approach for systematic in vivo investigations of cell membrane structure.

The overuse of insecticides with limited modes of action has led to resistance in mosquito vectors. Thus, insecticides with novel modes of action are needed. Secondary metabolites in Madagascan plants of the genus Cinnamosma (Canellaceae) are commonly used in traditional remedies and known to elicit antifeedant and toxic effects in insect pests. Here we test the hypothesis that extracts of Cinnamosma sp. enriched in drimane sesquiterpenes are toxic and/or antifeedant to the yellow fever mosquito Aedes aegypti. We show that the bark and root extracts, which contain a higher abundance of drimane sesquiterpenes compared to leaves, were the most efficacious. Screening isolated compounds revealed cinnamodial to be the primary driver of adulticidal activity, whereas cinnamodial, polygodial, cinnafragrin A, and capsicodendrin contributed to the larvicidal activity. Moreover, an abundant lactone (cinnamosmolide) in the root extract synergized the larvicidal effects of cinnamodial. The antifeedant activity of the extracts was primarily contributed to cinnamodial, polygodial, and cinnamolide. Parallel experiments with warburganal isolated from Warburgia ugandensis (Canellaceae) revealed that aldehydes are critical for—and a hydroxyl modulates—insecticidal activity. Our results indicate that plant drimane sesquiterpenes provide valuable chemical platforms for developing insecticides and repellents to control mosquito vectors.

OBJECTIVE:To compare the natural fertility outcomes of salpingotomy and salpingectomy among women treated for tubal pregnancy. METHODS:An online database search including PubMed, Embase, CENTRAL and Web of Science was performed to identify studies comparing salpingotomy and salpingectomy to treat women with tubal pregnancy. The search included papers published after the databases were established until May 2015. Two reviewers independently screened literature according to the inclusion and exclusion criteria and then extracted data and assessed the methodological quality of all of the included studies. The meta-analysis was conducted using RevMan 5.3 software. The registration number is CRD42015017545 in PROSPERO. RESULTS:Two randomized controlled trials (RCTs) and eight cohort studies, including a total of 1,229 patients, were znalyzed. The meta-analysis of the RCT subgroup indicated that there was no statistically significant difference in IUP rates (RR = 1.04, 95% CI = 0.89-1.21, P = 0.61) nor the repeat ectopic pregnancy (REP) rate (RR = 1.30, 95% CI = 0.72-2.38, P = 0.39) between the salpingotomy and salpingectomy group. In contrast, the cohort study subgroup analysis revealed that the IUP rate was higher in the salpingotomy group compared with the salpingectomy group (RR = 1.24, 95% CI = 1.08-1.42, P = 0.002); Salpingotomy also increased the risk of REP rate (RR = 2.27, 95% CI = 1.12-4.58, P = 0.02). The persistent ectopic pregnancy (PEP) occurred more frequently in the salpingotomy group than the salpingectomy group (RR = 11.61, 95% CI = 3.17-42.46, P = 0.0002). An IUP would be more likely to occur after salpingotomy than salpingectomy when the follow-up time was more than 36 months (RR = 1.16, 95% CI = 1.02-1.32, P = 0.03). The IUP rate (RR = 1.13, 95% CI = 1.01-1.26, P = 0.03), and the REP rate (RR = 1.62, 95% CI = 1.02-2.56, P = 0.04) was higher after salpingotomy than salpingectomy among patients from Europe compared with those from America. CONCLUSIONS:Based on the available evidence, we believe that for patients with a healthy contralateral tube operated for tubal pregnancy, the subsequent fertility after salpingectomy and salpingotomy are similar in the long term. The fertility prospects will not be improved via salpingotomy compared with salpingectomy.

Constitutive activation of the Hedgehog (Hh) signaling pathway has been implicated in the development of many human malignancies. Hh targets, such as Patched (PTCH), smoothened (SMO), Sonic hedgehog (SHH) and glioma-associated oncogene homologue 1 (GLI1), are markers of Hh signaling activation and expressed in most Hh-associated tumors. The protein kinase LKB1 has been shown to slow proliferation and induce cell-cycle arrest in many cell lines. In this study, we observed that activated LKB1 decreased the expression of factors related to Hh reporter activity in MDA-MB-231 breast cancer cells, including of SMO, SHH and GLI1. In contrast, LKB1 siRNA increased the expression of these target genes. The same results were shown to inhibit the Hh factors Sufu and Hip. Furthermore, we also observed negative correlation between LKB1 and glioma-associated oncogene homologue 1 (GLI1) in three breast cancer cell lines. Meanwhile, LKB1 siRNA rescued the inhibition of cell growth by 3-Keto-N-(aminoethyl-N'-aminocaproyldihydrocinnamoyl) cyclopamine (KAAD-cyclopamine), an antagonist of the Hh element SMO, which suggests that LKB1 acts as the downstream of SMO. In vivo, LKB1 siRNA increased tumor growth in the mammary fat pad, and the expression levels of Hh displayed similar results in vitro. Overexpression of the LKB1 protein in human breast cancers is associated with the expression of Hh. We found that breast carcinomas with detectable Hh had weak or undetectable expression of LKB1, whereas tumors that expressed high levels of LKB1 had undetectable Hh signaling. In this study, we find that LKB1 are negatively correlated with the expression of Hh related transcription factors. These findings suggest that LKB1 may inhibit tumorigenesis by regulating Hh signaling in certain cancers.

We used molecular dynamics (MD) simulations to explore the transport of single cations through the channel of the muscle nicotinic acetylcholine receptor (nAChR). Four MD simulations of 16 ns were performed at physiological and hyperpolarized membrane potentials, with and without restraints of the structure, but all without bound agonist. With the structure unrestrained and a potential of -100 mV, one cation traversed the channel during a transient period of channel hydration; at -200 mV, the channel was continuously hydrated and two cations traversed the channel. With the structure restrained, however, cations did not traverse the channel at either membrane potential, even though the channel was continuously hydrated. The overall results show that cation selective transport through the nAChR channel is governed by electrostatic interactions to achieve charge selectivity, but ion translocation relies on channel hydration, facilitated by a trans-membrane field, coupled with dynamic fluctuations of the channel structure.

The initial coupling between ligand binding and channel gating in the human alpha7 nicotinic acetylcholine receptor (nAChR) has been investigated with targeted molecular dynamics (TMD) simulation. During the simulation, eight residues at the tip of the C-loop in two alternating subunits were forced to move toward a ligand-bound conformation as captured in the crystallographic structure of acetylcholine binding protein (AChBP) in complex with carbamoylcholine. Comparison of apo- and ligand-bound AChBP structures shows only minor rearrangements distal from the ligand-binding site. In contrast, comparison of apo and TMD simulation structures of the nAChR reveals significant changes toward the bottom of the ligand-binding domain. These structural rearrangements are subsequently translated to the pore domain, leading to a partly open channel within 4 ns of TMD simulation. Furthermore, we confirmed that two highly conserved residue pairs, one located near the ligand-binding pocket (Lys145 and Tyr188), and the other located toward the bottom of the ligand-binding domain (Arg206 and Glu45), are likely to play important roles in coupling agonist binding to channel gating. Overall, our simulations suggest that gating movements of the alpha7 receptor may involve relatively small structural changes within the ligand-binding domain, implying that the gating transition is energy-efficient and can be easily modulated by agonist binding/unbinding.

Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that is highly expressed in various types of cancers including breast cancer. However, the role of AhR with its endogenous ligand 2-(1'H-indole-3'-carbonyl)-thiazole-4-carboxylic acid methyl ester (ITE) on the progression of breast cancer remains poorly understood. We aimed to investigate cell proliferation and migration states in breast cancer after activating AhR with the endogenous ligand ITE. Breast cancer tissue was evaluated by cell lines, immunohistochemistry, reverse transcription-polymerase chain reaction, cell proliferation, flow cytometry, migration assays and western blot techniques. We found that AhR was widely expressed in breast cancer tissues and metastasis lymph node tissues, but not in normal tissues. The expression AhR was independent between the age, grades and TNM classifications for breast cancer tissues. ITE treatment significantly induced the activation of AhR in a time-dependent manner in both MCF-7 and T47D breast cancer cell lines. Meanwhile, ITE did not affect the cell migration but significantly suppressed the cell proliferation in estrogen receptor positive (ER+) MCF-7 and T47D cells, which probably attribute to the induction of cell cycle arrest in G1 phase and shortened S phase. Further mechanism study showed that ERK1/2 and AKT signaling were required for the activation of AhR in MCF-7 cells. These data suggest that AhR is a potential new target for treating patients with breast cancer. ITE may be more potentially used for therapeutic intervention for breast cancer with the kind of ER(+). [ABSTRACT FROM AUTHOR]