Longitudinal impact of perceived harm and addiction on e-cigarette initiation among tobacco-naïve youth: Population Assessment of Tobacco and Health study (Waves 1-5)

OBJECTIVES

This study investigates the effect of e-cigarette-related harm and addiction perceptions on e-cigarette initiation among US tobacco-naïve adolescents.

STUDY DESIGN

This is a longitudinal study.

METHODS

Using data from five waves (2013-2019) of the Population Assessment of Tobacco and Health Study, we created a longitudinal data set for 2775 youth aged 12-17 years who had no prior use of tobacco products at Wave 1. E-cigarette initiation was defined as transitioning from non-use at Wave 1 to ever use in subsequent waves. Kaplan-Meier survival and Cox proportional hazard regression models were used to assess the impact of harm and addiction perceptions on e-cigarette initiation.

RESULTS

Our analytic sample comprised 63.1% of youth who had never used tobacco products at Wave 1 and consequently initiated e-cigarette use in subsequent waves. Over time, fewer individuals perceived e-cigarettes as harmless (14.1%-2.1%), whereas more perceived them as likely to cause addiction (53.7%-76.6%). Compared with perceiving e-cigarettes as a lot of harm, those perceiving some harm (adjusted hazard ratio [aHR] = 1.30, 95% confidence interval [CI]: 1.12-1.52), little harm (aHR = 1.42, 95% CI: 1.20-1.68), or no harm (aHR = 2.09, 95% CI: 1.64-2.65) were more likely to initiate e-cigarette use. Demographic factors for initiation included being Black or Hispanic ethnicity (vs White), younger age (12-14 vs15-17 years), and receiving over $20 per week (vs $0) in pocket money, with P-values <0.05. However, in adjusted results, addiction perceptions did not significantly impact e-cigarette initiation (P-values >0.05).

CONCLUSIONS

Among youth without prior tobacco/nicotine use, perceiving e-cigarettes as having low harm significantly predicted initiation over time. Effective prevention strategies, including targeted risk communication interventions, are essential for discouraging e-cigarette use among youth.

Unraveling the Ligand-Binding Sites of CYP3A4 by Molecular Dynamics Simulations with Solvent Probes

Cytochrome P450 3A4 (CYP3A4) is one of the most important drug-metabolizing enzymes in the human body and is well known for its complicated, atypical kinetic characteristics. The existence of multiple ligand-binding sites in CYP3A4 has been widely recognized as being capable of interfering with the active pocket through allosteric effects. The identification of ligand-binding sites other than the canonical active site above the heme is especially important for understanding the atypical kinetic characteristics of CYP3A4 and the intriguing association between the ligand and the receptor. In this study, we first employed mixed-solvent molecular dynamics (MixMD) simulations coupled with the online computational predictive tools to explore potential ligand-binding sites in CYP3A4. The MixMD approach demonstrates better performance in dealing with the receptor flexibility compared with other computational tools. From the sites identified by MixMD, we then picked out multiple sites for further exploration using ensemble docking and conventional molecular dynamics (cMD) simulations. Our results indicate that three extra sites are suitable for ligand binding in CYP3A4, including one experimentally confirmed site and two novel sites.

admetSAR3.0: a comprehensive platform for exploration, prediction and optimization of chemical ADMET properties

Absorption, distribution, metabolism, excretion and toxicity (ADMET) properties play a crucial role in drug discovery and chemical safety assessment. Built on the achievements of admetSAR and its successor, admetSAR2.0, this paper introduced the new version of the series, admetSAR3.0, as a comprehensive platform for chemical ADMET assessment, including search, prediction and optimization modules. In the search module, admetSAR3.0 hosted over 370 000 high-quality experimental ADMET data for 104 652 unique compounds, and supplemented chemical structure similarity search function to facilitate read-across. In the prediction module, we introduced comprehensive ADMET endpoints and two new sections for environmental and cosmetic risk assessments, empowering admetSAR3.0 to provide prediction for 119 endpoints, more than double numbers compared to the previous version. Furthermore, the advanced multi-task graph neural network framework offered robust and reliable support for ADMET prediction. In particular, a module named ADMETopt was added to automatically optimize the ADMET properties of query molecules through transformation rules or scaffold hopping. Finally, admetSAR3.0 provides user-friendly interfaces for multiple types of input data, such as SMILES string, chemical structure and batch molecule file, and supports various output types, including digital, chart displays and file downloads. In summary, admetSAR3.0 is anticipated to be a valuable and powerful tool in drug discovery and chemical safety assessment at http://lmmd.ecust.edu.cn/admetsar3/.

Effect of S-Ketamine on Postoperative Nausea and Vomiting in Patients Undergoing Video-Assisted Thoracic Surgery: A Randomized Controlled Trial

Purpose

Postoperative nausea and vomiting (PONV) frequently occur in patients after surgery. In this study, the authors investigated whether perioperative S-ketamine infusion could decrease the incidence of PONV in patients undergoing video-assisted thoracoscopic surgery (VATS) lobectomy.

Patients and Methods

This prospective, randomized, double-blinded, controlled study was conducted a total of 420 patients from September 2021 to May 2023 at Xuzhou Central Hospital in China, who underwent elective VATS lobectomy under general anesthesia with tracheal intubation. The patients were randomly assigned to either the S-ketamine group or the control group. The S-ketamine group received a bolus injection of 0.5 mg/kg S-ketamine and an intraoperative continuous infusion of S-ketamine at a rate of 0.25 mg/kg/h. The control group received an equivalent volume of saline. All patients were equipped with patient-controlled intravenous analgesia (PCIA), with a continuous infusion rate of 0.03 mg/kg/h S-ketamine in the S-ketamine group or 0.03 μg/kg/h sufentanil in the control group. The primary outcome was the incidence of PONV. Secondary outcomes included perioperative opioid consumption, hemodynamics, postoperative pain, and adverse events.

Results

The incidence of PONV in the S-ketamine group (9.7%) was significantly lower than in the control group (30.5%). Analysis of perioperative opioid usage revealed that remifentanil usage was 40.0% lower in the S-ketamine group compared to the control group (1414.8 μg vs 2358.2 μg), while sufentanil consumption was 75.2% lower (33.1 μg vs 133.6 μg). The S-ketamine group demonstrated better maintenance of hemodynamic stability. Additionally, the visual analogue scale (VAS) scores on postoperative day 1 (POD-1) and postoperative day 3 (POD-3) were significantly lower in the S-ketamine group. Finally, no statistically significant difference in other postoperative adverse reactions was observed between the two groups.

Conclusion

The results of this trial indicate that perioperative S-ketamine infusion can effectively reduce the incidence of PONV in patients undergoing VATS lobectomy.

Ba3SnGa10-xInxO20 (0 ≤ x ≤ 2): site-selective doping, band structure engineering and photocatalytic overall water splitting

Developing new photocatalysts and deciphering the structure-property relationship are always the central topics in photocatalysis. In this study, a new photocatalyst Ba3SnGa10O20 containing two d10 metal cations was prepared by a high temperature solid state reaction, and its crystal structure was investigated by Rietveld refinements of monochromatic X-ray powder diffraction data for the first time. There are 2 Ba, 4 metal cations and 6 O independent atoms in a unit cell. Sn4+ and Ga3+ co-occupy the octahedral cavities named M1 and M2 sites, and the other two metal sites are fully occupied by Ga3+. Rational In3+-to-Ga3+ substitution was performed to reduce the potential of the conduction band minimum and enhance the light absorption ability, which was indeed confirmed using UV-vis diffuse reflectance spectra and Mott-Schottky plots for Ba3SnGa10-xInxO20 (0 ≤ x ≤ 2). Interestingly, In3+ exhibits site selective doping at M1 and M2 sites exclusively. With the light absorption ability enhanced, the photocatalytic overall water splitting activity was also improved, i.e. the photocatalytic H2 generation rate was 1.7(1) μmol h-1 for Ba3SnGa10O20, and the optimal catalyst Ba3SnGa8.5In1.5O20 loaded with 1.0 wt% Pd exhibited the H2 generation rate of 27.5(4) μmol h-1 and the apparent quantum yield at 254 nm was estimated to be 2.28% in pure water.

Modulation of lipid profile by secretory phospholipase A2 group IIA: Verification with a transgenic mouse model

We previously demonstrated a positive relation of secretory phospholipase A2 group IIA (sPLA2-IIA) with circulating high-density lipoprotein cholesterol (HDL-C) in patients with coronary artery disease, and sPLA2-IIA increased cholesterol efflux in THP-1 cells through peroxisome proliferator-activated receptor-γ (PPAR-γ)/liver X receptor α/ATP-binding cassette transporter A1 (ABCA1) signaling pathway. The aim of the present study was to examine the role of sPLA2-IIA over-expression on lipid profile in a transgenic mouse model. Fifteen apoE-/- and C57BL/7 female mice received bone marrow transplantation from transgenic SPLA2-IIA mice, and treated with specific PPAR-γ inhibitor GW9662. High fat diet was given after one week of bone marrow transplantation, and animals were sacrificed after twelve weeks. Immunohistochemical staining showed over-expression of sPLA2-IIA protein in the lung and spleen. The circulating level of HDL-C, but not that of low-density lipoprotein cholesterol (LDL-C), total cholesterol, or total triglyceride, was increased by sPLA2-IIA over-expression, and was subsequently reversed by GW9662 treatment. Over-expression of sPLA2-IIA resulted in augmented expression of cholesterol transporter ABCA1 at mRNA level in the aortas, and at protein level in macrophages, co-localized with macrophage specific antigen CD68. GW9662 exerted potent inhibitory effects on sPLA2-IIA-induced ABCA1 expression. Conclusively, we demonstrated the effects of sPLA2-IIA on circulating HDL-C level and the expression of ABCA1, possibly through regulation of PPAR-γ signaling in transgenic mouse model, that is in concert with the conditions in patients with coronary artery disease.

Association of the triglyceride-glucose index variability with blood pressure and hypertension: a cohort study

BACKGROUND

Several studies have indicated that the triglyceride-glucose index (TyG) index is associated with hypertension; however, evidence on the association of change in the TyG index with blood pressure and hypertension is limited.

AIMS

To assess the association of the TyG index with blood pressure and hypertension.

DESIGN

A cohort study.

METHODS

We included 17 977 individuals with a mean age of 60.5 years from the Dongfeng-Tongji cohort. The TyG index was calculated as ln [fasting triglyceride (mg/dl)×fasting glucose (mg/dl)/2]. Hypertension was defined as blood pressure ≥140/90 mmHg, self-reported current use of antihypertensive medication or self-reported physician diagnosis of hypertension.

RESULTS

In the longitudinal analyses, we found a linear dose-response relationship between changes in the TyG index and change in blood pressure. Each one-unit change in the TyG index was associated with a 1.93 (1.23-2.63) mmHg increase in systolic blood pressure (SBP) and a 1.78 (1.42-2.16) mmHg increase in diastolic blood pressure (DBP). During a median follow-up of 9.37 years, a total of 3594 individuals were newly diagnosed with hypertension. We also found a linear dose-response relationship between the TyG index and the incidence of hypertension. The hazard ratio (HR) of hypertension for each one-unit increase in the TyG index was 1.21 (1.13-1.29). In addition, the best cut-off point of TyG for predicting hypertension was 8.4797, with sensitivity, and specificity of 57.85% and 55.40%, respectively.

CONCLUSIONS

The TyG index had a positive dose-response relationship with blood pressure and could be used to predict the risk of hypertension.

CD74/SLC34A2-ROS1 Fusion Variants Involving the Transmembrane Region Predict Poor Response to Crizotinib in NSCLC Independent of TP53 Mutations

INTRODUCTION

Variable partners and breakpoints have been reported in patients with ROS1-rearranged NSCLC. Here, we investigated the association of fusion partners and breakpoints with crizotinib efficacy in NSCLCs with common ROS1 fusions.

METHODS

DNA and RNA next-generation sequencing (NGS) and immunohistochemistry were performed to characterize ROS1 fusions.

RESULTS

Using DNA NGS, we identified ROS1 fusions in 210 cases, comprising 171 common (CD74/EZR/TPM3/SDC4/SLC34A2-ROS1) and 39 uncommon (variants identified in <5%) ROS1 fusion cases. DNA NGS detected variable ROS1 genomic breakpoints in common ROS1 fusions, whereas RNA NGS found ROS1 breakpoints mainly occurring in exons 32, 34 and 35, resulting in long (exon 32) and short (exon 34 or 35) ROS1 fusions. ROS1 immunohistochemistry revealed that membranous and cytoplasmic staining was predominant in long ROS1 fusions, whereas cytoplasmic staining was predominant in short ROS1 fusions (p = 0.006). For patients who received first-line crizotinib, median progression-free survival (mPFS) was lower in patients with long ROS1 fusions than those with short ROS1 fusions (8.0 versus 24.0 mo, p = 0.006). Moreover, mPFS for patients with and without TP53 mutations was 8.0 and 19.0 months, respectively (p = 0.159); mPFS for patients with and without BIM deletion polymorphism was 5.0 and 22.0 months, respectively (p = 0.003). When analyzing together with fusion partners, patients with long CD74/SLC34A2-ROS1 fusions were found to have shorter PFS than those with other ROS1, regardless of the presence or absence of TP53 mutations (p < 0.001 and p = 0.002, respectively).

CONCLUSIONS

Long CD74/SLC34A2-ROS1 fusions, which retain transmembrane regions in ROS1 and fusion partners, are associated with poor response to crizotinib independent of TP53 mutations.

UCFNNet: Ulcerative colitis evaluation based on fine-grained lesion learner and noise suppression gating

BACKGROUND AND OBJECTIVE

Ulcerative colitis (UC) is a chronic disease characterized by recurrent symptoms and significant morbidity. The exact cause of the disease remains unknown. The selection of current treatment options for ulcerative colitis depends on the severity and location of the disease in each patient. Therefore, developing a fully automated endoscopic images for evaluating UC is crucial for guiding treatment plans and facilitating early prevention efforts.

METHODS

We propose a network called ulcerative colitis evaluation based on fine-grained lesion learner and noise suppression gating (UCFNNet). UCFNNet contains three novel modules. Firstly, a fine-grained lesion feature learner (FG-LF Learner) is proposed by integrating local features and a Softmax category prediction (SCP) module to improve the feature accuracy in small lesion areas. Subsequently, a graph convolutional feature combiner (GCFC) is developed to connect features across adjacent convolutional layers and to incorporate short connections between input and output, thereby mitigating feature loss during transmission. Thereafter, a noise suppression gating (NS gating) technique is designed by implementing a grid attention mechanism and a feature gating (FG) module to prioritize significant lesion features and suppress irrelevant and noisy regions in the input feature map.

RESULTS

We evaluate the performance of the proposed network on both privately-collected and publicly-available datasets. The evaluation of UC achieves excellent results on privately-collected dataset, with an accuracy (ACC) of 89.57 %, Matthews correlation coefficient (MCC) of 85.52 %, precision of 89.26 %, recall of 89.48 %, and F1-score of 89.78 %. The results are also impressive on publicly-available dataset, with ACC of 85.47 %, MCC of 80.42 %, precision of 85.62 %, recall of 84.00 %, and F1-score of 84.53 %, surpassing the performance of state-of-the-art techniques.

CONCLUSION

Our proposed model introduces three innovative algorithm modules, which outperform the current state-of-the-art methods and achieve high ACC and F1-score. This indicates that our method has superior performance compared to traditional machine learning and existing deep methods, which means that our method has good application prospects. Meanwhile, it has been verified that the proposed model demonstrates good interpretability. The source code is available at github.com/YinLeRenNB/UCFNNet.

Stability Analysis for H∞-Controlled Active Quarter-Vehicle Suspension Systems With a Resilient Event-Triggered Scheme Under Periodic DoS Attacks

The stability analysis is studied for H∞ controlled networked active quarter-vehicle suspension systems with a resilient event-triggered scheme (RETS) under periodic denial-of-service (DoS) jamming attacks in this article. For the networked suspension system, the system-state signals are measured by sensors and transmitted to the cloud controller through a wireless network and then the control signal is transferred to the actuator to control it. An event-triggered scheme (ETS) is designed to reduce the workload of data transmission, which is effective to select some most useful information to transmit and discard some redundant data. DoS attacks can block the data transmission when it is active, so a resilient event-triggered H∞ control method is built based on the Lyapunov stability theory. The exponential stability of the controlled suspension system, as well as the H∞ performance, is analyzed in this article. Some simulation results show that the proposed control method is effective to improve driving comfort and driving safety and reduce the workload of data transmission under periodic DoS attacks.

Predicting slight freezing of gait in Parkinson's disease with anticipatory postural adjustments and limits of stability

INTRODUCTION

Gait initiation (GI) includes automatic and voluntary movements. However, research on their impact on the first step in patients with Parkinson's disease (PD) and their relationship to freezing of gait (FOG) is lacking. We examined the effects of automatic movements (anticipatory postural adjustments [APAs]) and voluntary movements (limits of stability [LOS]) on the first step (first-step duration and first-step range of motion), along with their early recognition and prediction of slight FOG.

METHODS

Twenty-three patients with PD and slight freezing (PD + FOG) and 25 non-freezing patients with PD (PD-FOG) were tested while off medications and compared with 24 healthy controls (HC). All participants completed a 7-m Stand and Walk Test (7 m SAW) and wore inertial sensors to quantify the APAs and first step. LOS was quantified by dynamic posturography in different directions using a pressure platform. We compared differences among all three groups, analysed correlations, and evaluated their predictive value for slight FOG.

RESULTS

In PD + FOG, APAs and LOS were worse than those in the PD-FOG and HC groups (p < 0.001), and the first step was worse than that in HC (p < 0.001). APAs were correlated mainly with the first-step duration. APAs and LOS were correlated with the first-step range of motion. APAs have been recognized as independent predictors of FOG, and their combination with LOS enhances predictive sensitivity.

CONCLUSION

APAs and LOS in patients with PD directly affect the first step during GI. In addition, the combination of APAs and LOS helped predict slight FOG.

Observation of WWγ Production and Search for Hγ Production in Proton-Proton Collisions at sqrt[s]=13 TeV

The observation of WWγ production in proton-proton collisions at a center-of-mass energy of 13 TeV with an integrated luminosity of 138  fb^{-1} is presented. The observed (expected) significance is 5.6 (5.1) standard deviations. Events are selected by requiring exactly two leptons (one electron and one muon) of opposite charge, moderate missing transverse momentum, and a photon. The measured fiducial cross section for WWγ is 5.9±0.8(stat)±0.8(syst)±0.7(modeling)  fb, in agreement with the next-to-leading order quantum chromodynamics prediction. The analysis is extended with a search for the associated production of the Higgs boson and a photon, which is generated by a coupling of the Higgs boson to light quarks. The result is used to constrain the Higgs boson couplings to light quarks.

In Silico Prediction of Chemical Acute Dermal Toxicity Using Explainable Machine Learning Methods

The research on acute dermal toxicity has consistently been a crucial component in assessing the potential risks of human exposure to active ingredients in pesticides and related plant protection products. However, it is difficult to directly identify the acute dermal toxicity of potential compounds through animal experiments alone. In our study, we separately integrated 1735 experimental data based on rabbits and 1679 experimental data based on rats to construct acute dermal toxicity prediction models using machine learning and deep learning algorithms. The best models for the two animal species achieved AUC values of 78.0 and 82.0%, respectively, on 10-fold cross-validation. Additionally, we employed SARpy to extract structural alerts, and in conjunction with Shapley additive explanation and attentive FP heatmap, we identified important features and structural fragments associated with acute dermal toxicity. This approach offers valuable insights for the detection of positive compounds. Moreover, a standalone software tool was developed to make acute dermal toxicity prediction easier. In summary, our research would provide an effective tool for acute dermal toxicity evaluation of pesticides, cosmetics, and drug safety assessment.

FluPMT: Prediction of Predominant Strains of Influenza A Viruses Via Multi-task Learning

Seasonal influenza vaccines play a crucial role in saving numerous lives annually. However, the constant evolution of the influenza A virus necessitates frequent vaccine updates to ensure its ongoing effectiveness. The decision to develop a new vaccine strain is generally based on the assessment of the current predominant strains. Nevertheless, the process of vaccine production and distribution is very time-consuming, leaving a window for the emergence of new variants that could decrease vaccine effectiveness, so predictions of influenza A virus evolution can inform vaccine evaluation and selection. Hence, we present FluPMT, a novel sequence prediction model that applies an encoder-decoder architecture to predict the hemagglutinin (HA) protein sequence of the upcoming season's predominant strain by capturing the patterns of evolution of influenza A viruses. Specifically, we employ time series to model the evolution of influenza A viruses, and utilize attention mechanisms to explore dependencies among residues of sequences. Additionally, antigenic distance prediction based on graph network representation learning is incorporated into the sequence prediction as an auxiliary task through a multi-task learning framework. Experimental results on two influenza datasets highlight the exceptional predictive performance of FluPMT, offering valuable insights into virus evolutionary dynamics, as well as vaccine evaluation and production.

Modeling and analysis of the effect of optimal virus control on the spread of HFMD

A within-host and between-host hand, foot and mouth disease (HFMD) mathematical model is established and the affect of optimal control in its within-host part on HFMD transmission is studied. Through define two basic reproduction numbers, by using the fast-slow system analysis method of time scale, the global stabilities of the between-host (slow) system and within-host (fast) system are researched, respectively. An optimal control problem with drug-treatment control on coupled within-host and between-host HFMD model is formulated and analysed theoretically. Finally, the purposed optimal control measures are applied to the actual HFMD epidemic analysis in Zhejiang Province, China from April 1, 2021 to June 30, 2021. The numerical results show that the drug control strategies can reduce the virus load per capita and can effectively prevent large-scale outbreaks of HFMD.

New Structures in the J/ψJ/ψ Mass Spectrum in Proton-Proton Collisions at sqrt[s]=13 TeV

A search is reported for near-threshold structures in the J/ψJ/ψ invariant mass spectrum produced in proton-proton collisions at sqrt[s]=13  TeV from data collected by the CMS experiment, corresponding to an integrated luminosity of 135  fb^{-1}. Three structures are found, and a model with quantum interference among these structures provides a good description of the data. A new structure is observed with a local significance above 5 standard deviations at a mass of 6638_{-38}^{+43}(stat)_{-31}^{+16}(syst)  MeV. Another structure with even higher significance is found at a mass of 6847_{-28}^{+44}(stat)_{-20}^{+48}(syst)  MeV, which is consistent with the X(6900) resonance reported by the LHCb experiment and confirmed by the ATLAS experiment. Evidence for another new structure, with a local significance of 4.7 standard deviations, is found at a mass of 7134_{-25}^{+48}(stat)_{-15}^{+41}(syst)  MeV. Results are also reported for a model without interference, which does not fit the data as well and shows mass shifts up to 150 MeV relative to the model with interference.

[Effect of preemptive analgesia with ibuprofen on postoperative pain after mandibular third molar extraction: a randomized controlled trial]

Objective: To evaluate the impact of preemptive analgesia with ibuprofen on postoperative pain following the extraction of impacted mandibular third molars in a Chinese population, aiming to provide a clinical reference for its application. Methods: This multicenter, randomized, double-blind, placebo-controlled parallel-group trial was conducted from April 2022 to October 2023 at the Capital Medical University School of Stomatology (40 cases), Beijing TianTan Hospital, Capital Medical University (22 cases), and Beijing Chao-Yang Hospital, Capital Medical University (20 cases). It included 82 patients with impacted mandibular third molars, with 41 in the ibuprofen group and 41 in the control group. Participants in the ibuprofen group received 300 mg of sustained-release ibuprofen capsules orally 15 min before surgery, while the control group received a placebo. Both groups were instructed to take sustained-release ibuprofen capsules as planned for 3 days post-surgery. Pain intensity was measured using the numerical rating scale at 30 min, 4 h, 6 h, 8 h, 24 h, 48 h, and 72 h after surgery, and the use of additional analgesic medication was recorded during days 4 to 6 postoperatively. Results: All 82 patients completed the study according to the protocol. No adverse events such as nausea, vomiting, or allergies were reported in either group during the trial. The ibuprofen group exhibited significantly lower pain scores at 4 h [2.0 (1.0, 4.0) vs. 4.0 (3.0, 5.0)] (Z=-3.73, P<0.001), 6 h [2.0 (1.0, 4.0) vs. 5.0(2.5, 6.0)] (Z=-3.38, P<0.001), and 8 h [2.0 (1.0, 4.0) vs. 5.0 (2.0, 6.0)] (Z=-2.11, P=0.035) postoperatively compared to the control group. There were no statistically significant differences in pain scores between the groups at 30 min, 24 h, 48 h, and 72 h postoperatively (P>0.05). Additionally, 11 out of 41 patients (26.8%) in the ibuprofen group and 23 out of 41 patients (56.1%) in the control group required extra analgesic medication between days 4 and 6 post-surgery, with the ibuprofen group taking significantly fewer additional pills [0.0 (0.0, 1.0) vs. 1.0 (0.0, 3.0)] (Z=-2.81, P=0.005). Conclusions: A pain management regimen involving 300 mg of oral sustained-release ibuprofen capsules administered 15 minutes before surgery and continued for 3 d postoperatively effectively reduces pain levels and the total amount of analgesic medication used after the extraction of impacted mandibular third molars. Considering its efficacy, safety, and cost-effectiveness, ibuprofen is recommended as a first-line drug for perioperative pain management, enhancing patient comfort during diagnosis and treatment in a feasible manner.

Passive microfluidic devices for cell separation

The separation of specific cell populations is instrumental in gaining insights into cellular processes, elucidating disease mechanisms, and advancing applications in tissue engineering, regenerative medicine, diagnostics, and cell therapies. Microfluidic methods for cell separation have propelled the field forward, benefitting from miniaturization, advanced fabrication technologies, a profound understanding of fluid dynamics governing particle separation mechanisms, and a surge in interdisciplinary investigations focused on diverse applications. Cell separation methodologies can be categorized according to their underlying separation mechanisms. Passive microfluidic separation systems rely on channel structures and fluidic rheology, obviating the necessity for external force fields to facilitate label-free cell separation. These passive approaches offer a compelling combination of cost-effectiveness and scalability when compared to active methods that depend on external fields to manipulate cells. This review delves into the extensive utilization of passive microfluidic techniques for cell separation, encompassing various strategies such as filtration, sedimentation, adhesion-based techniques, pinched flow fractionation (PFF), deterministic lateral displacement (DLD), inertial microfluidics, hydrophoresis, viscoelastic microfluidics, and hybrid microfluidics. Besides, the review provides an in-depth discussion concerning cell types, separation markers, and the commercialization of these technologies. Subsequently, it outlines the current challenges faced in the field and presents a forward-looking perspective on potential future developments. This work hopes to aid in facilitating the dissemination of knowledge in cell separation, guiding future research, and informing practical applications across diverse scientific disciplines.

Two-Dimensional Amorphous Titanium Dioxide/Silver (TiO2/Ag) Nanosheets as a Surface-Enhanced Raman Spectroscopy Substrate for Highly Sensitive Detection

For the purpose of investigating the chemical enhancement of amorphous semiconductors as well as increasing the sensitivity of the surface-enhanced Raman spectroscopy (SERS) substrate, titanium dioxide (TiO2) precursors were calcined at different temperatures to generate crystallized TiO2 (c-TiO2) and amorphous TiO2 (a-TiO2) nanosheets, respectively. Afterward, a two-dimensional (2D) a-TiO2/Ag nanosheet SERS substrate was successfully fabricated using electrostatic interaction between a-TiO2 and Ag nanoparticles. In order to demonstrate a greater SERS sensitivity on a-TiO2/Ag compared to either c-TiO2 or Ag nanoparticles alone, the SERS probe molecules rhodamine 6G (R6G) and malachite green (MG) were utilized. Based on the results of SERS detections for probe molecules and contaminants, it demonstrates that a-TiO2/Ag nanosheets produce highly sensitive and repeatable Raman signals. The detectable concentration limits for R6G and MG were found to be 10-11 M and 10-10 M, respectively. And it has been determined that the system exhibits an enhancement factor (EF) of up to 1  ×  108. The limit of detection for 4-mercaptobenzoic acid and alizarin red can both reach 1  ×  10-8. Furthermore, a finite-difference time-domain simulation is performed in order to evaluate the magnetic field strength generated by Ag nanoparticles. As a result of the simulation, it is evident that the actual EF is smaller than the calculated one, leading support to the view that a-TiO2 nanosheets have a beneficial effect on the chemical enhancement of SERS.

In Silico prediction of inhibitors for multiple transporters via machine learning methods

Transporters play an indispensable role in facilitating the transport of nutrients, signaling molecules and the elimination of metabolites and toxins in human cells. Contemporary computational methods have been employed in the prediction of transporter inhibitors. However, these methods often focus on isolated endpoints, overlooking the interactions between transporters and lacking good interpretation. In this study, we integrated a comprehensive dataset and constructed models to assess the inhibitory effects on seven transporters. Both conventional machine learning and multi-task deep learning methods were employed. The results demonstrated that the MLT-GAT model achieved superior performance with an average AUC value of 0.882. It is noteworthy that our model excels not only in prediction performance but also in achieving robust interpretability, aided by GNN-Explainer. It provided valuable insights into transporter inhibition. The reliability of our model's predictions positioned it as a promising and valuable tool in the field of transporter inhibition research. Related data and code are available at https://gitee.com/wutiantian99/transporter_code.git.

High-speed multihull anti-pitching control based on heave velocity and pitch angular velocity estimation

This paper proposes a novel anti-pitching control algorithm based on algebraic model predictive control (AMPC) for high-speed multihull, in which the heave velocity and pitch angular velocity cannot be measured directly. Specifically, a multihull vertical control model is established with the employed anti-pitching appendages, and the uncertainty of the model as well as the coupling between heave and pitch motion are investigated. To address unmeasurable of the heave velocity and pitch angular velocity, a novel kinematics-based Kalman filter is designed to estimate these states online, which is substantially different from the existing works. Then, the AMPC strategy for varying receding-horizon optimization is proposed, which significantly reduces the amount of online calculation. To estimate the lumped uncertainty, the second-order filter data of input and output is used to design a disturbance observer with less parameters, which can perform feed-forward compensation to enhance the robustness. The convergence of the disturbance observer and the closed-loop system is analyzed mathematically. Finally, the advantages of the proposed anti-pitching control approach are demonstrated in both theory and simulation.

Photocurable and Temperature-Sensitive Bioadhesive Hydrogels for Sutureless Sealing of Full-Thickness Corneal Wounds

Penetrating corneal wounds can cause severe vision impairment and require prompt intervention to restore globe integrity and minimize the risk of infection. Tissue adhesives have emerged as a promising alternative to suturing for mitigating postoperative complications. However, conventional water-soluble adhesives suffer formidable challenges in sealing penetrating corneal wounds due to dilution or loss in a moist environment. Inspired by the robust adhesion of mussels in aquatic conditions, an injectable photocurable bioadhesive hydrogel (referred to as F20HD5) composed of polyether F127 diacrylate and dopamine-modified hyaluronic acid methacrylate is developed for sutureless closure of corneal full-thickness wounds. F20HD5 exhibits high transparency, wound-sealing ability, proper viscosity, biodegradability, and excellent biocompatibility. It allows in situ cross-linking via visible light, thereby providing sufficient mechanical strength and adhesiveness. In vivo, the adhesive hydrogel effectively closed penetrating linear corneal incisions and corneal injuries with minimal tissue loss in rabbits. During the 56-day follow-up, the hydrogel facilitates the repair of the injured corneas, resulting in more symmetrical curvatures and less scarring in distinction to the untreated control. Thus, bioinspired hydrogel holds promise as an effective adhesive for sealing full-thickness corneal wounds.

Effect of UV irradiation on the densification behavior, microstructure, and microwave dielectric properties of low temperature sintering Al2O3 ceramics

In this paper, Al2O3 ceramics co-doped with 0.3 wt%CuO-0.6 wt%TiO2-0.1 wt%MnCO3 (CTM, the same below) were prepared. The effect of CTM and UV irradiation on the sintering behavior, microstructure, and microwave dielectric properties have been investigated systematically. The results indicate that the sintering temperature of Al2O3 ceramics could be effectively decreased to about 1200 °C by adding 1 wt% CTM. UV irradiation can further increase the density of the Al2O3 ceramics, improve its microstructure and microwave dielectric properties. By using the Al2O3 powders UV irradiated for 15 min as raw materials, CTM co-doped Al2O3 ceramics can sintered at 1200 °C with a high density of 3.93 g/cm3 and a very high Q × f value of 175,086 GHz.

AttentiveSkin: To Predict Skin Corrosion/Irritation Potentials of Chemicals via Explainable Machine Learning Methods

Skin Corrosion/Irritation (Corr./Irrit.) has long been a health hazard in the Globally Harmonized System (GHS). Several in silico models have been built to predict Skin Corr./Irrit. as an alternative to the increasingly restricted animal testing. However, current studies are limited by data amount/quality and model availability. To address these issues, we compiled a traceable consensus GHS data set comprising 731 Corr., 1283 Irrit., and 1205 negative (Neg.) samples from 6 governmental databases and 2 external data sets. Then, a series of binary classifiers were developed with five machine learning (ML) algorithms and six molecular representations. For 10-fold cross-validation, the best Corr. vs Neg. classifier achieved an Area Under the Receiver Operating Characteristic Curve (AUC) of 97.1%, while the best Irrit. vs Neg. classifier achieved an AUC of 84.7%. Compared with existing in silico tools on external validation, our Attentive FP classifiers showed the highest metrics on Corr. vs Neg. and the second highest accuracy on Irrit. vs Neg. The SHapley Additive exPlanation approach was further applied to figure out important molecular features, and the attention weights were visualized to perform interpretable prediction. Structural alerts associated with Skin Corr./Irrit. were also identified. The interpretable Attentive FP classifiers were integrated into the software AttentiveSkin at https://github.com/BeeBeeWong/AttentiveSkin. The conventional ML classifiers are also provided on our platform admetSAR at http://lmmd.ecust.edu.cn/admetsar2/. Considering the data deficiency and the limited model availability of Skin Corr./Irrit., we believe that our data set and models could facilitate chemical safety assessment and relevant studies.

AptaDB: a comprehensive database integrating aptamer-target interactions

Aptamers have emerged as research hotspots of the next generation due to excellent performance benefits and application potentials in pharmacology, medicine, and analytical chemistry. Despite the numerous aptamer investigations, the lack of comprehensive data integration has hindered the development of computational methods for aptamers and the reuse of aptamers. A public access database named AptaDB, derived from experimentally validated data manually collected from the literature, was hence developed, integrating comprehensive aptamer-related data, which include six key components: (i) experimentally validated aptamer-target interaction information, (ii) aptamer property information, (iii) structure information of aptamer, (iv) target information, (v) experimental activity information, and (vi) algorithmically calculated similar aptamers. AptaDB currently contains 1350 experimentally validated aptamer-target interactions, 1230 binding affinity constants, 1293 aptamer sequences, and more. Compared to other aptamer databases, it contains twice the number of entries found in available databases. The collection and integration of the above information categories is unique among available aptamer databases and provides a user-friendly interface. AptaDB will also be continuously updated as aptamer research evolves. We expect that AptaDB will become a powerful source for aptamer rational design and a valuable tool for aptamer screening in the future. For access to AptaDB, please visit http://lmmd.ecust.edu.cn/aptadb/.

Teleoperated Grasping Using Data Gloves Based on Fuzzy Logic Controller

Teleoperated robots have attracted significant interest in recent years, and data gloves are one of the commonly used devices for their operation. However, existing solutions still encounter two challenges: the ways in which data gloves capture human operational intentions and achieve accurate mapping. In order to address these challenges, we propose a novel teleoperation method using data gloves based on fuzzy logic controller. Firstly, the data are collected and normalized from the flex sensors on data gloves to identify human manipulation intentions. Then, a fuzzy logic controller is designed to convert finger flexion information into motion control commands for robot arms. Finally, experiments are conducted to demonstrate the effectiveness and precision of the proposed method.

Effects of Shixiao Huoxue Decoction on pain, tumor necrosis factor-α, and interleukin-8 in patients with adenomyosis

OBJECTIVE

To explore the effect of Shixiao Huoxue Decoction on pain and tumor necrosis factor (TNF)-α and interleukin (IL)-8 levels in patients with adenomyosis.

METHODS

A total of 65 patients with adenomyosis admitted to South District of Guang'anmen Hospital from January 2020 to December 2021 were divided into two groups according to the treatment methods. The control group was treated with pregnatrienone, and the study group was treated with additional Shixiaohuoxue decoction. The incidence of complications, treatment efficacy, levels of inflammatory factors, Traditional Chinese Medicine symptom score, dysmenorrhea score, menstrual volume score, dysmenorrhea symptom score, changes in uterine volume, level of insulin-like growth factor 1 (IGF-1), and changes in the level of carbohydrate antigen (CA125) were observed before and after treatment in both two groups. Univariate Logistic analysis showed that uterine volume, IGF-1, CA125, serum IL-8 and TNF-α were correlated with the short-term efficacy of Meixiaohuoxue Decoction in the treatment of uterine adenomyosis (P<0.05).

RESULTS

The levels of IL-8 and TNF-α in the study group were significantly lower than those in the control group after treatment (P<0.05). The scores of dyspareunia and non-menstrual pelvic pain in the study group were significantly lower than those in the control group (P<0.05). The overall response rate in the study group (93.75%) was significantly higher than that in the control group (66.66%) (P<0.05). The scores of Traditional Chinese Medicine symptoms, dysmenorrhea, menstrual volume, and dysmenorrhea symptoms in the study group were significantly lower than those in the control group after treatment (P<0.05). The IGF-1 and CA125 levels in the study group were significantly lower than those in the control group after treatment (P<0.05). However, no significant difference in uterine volume was found between the two groups after treatment (P>0.05).

CONCLUSION

Xiaoxiao Huoxue Decoction demonstrated a better treatment efficacy in patients with adenomyosis through improving dysmenorrhea and Traditional Chinese Medicine symptoms, as well as reducing the levels of body inflammatory factors, non-menstrual pelvic pain, and dyspareunia, thus contributing to early recovery of patients. Therefore, Xiaoxiao Huoxue Decoction is worthy of promotion in clinical treatment of adenomyosis.

Compliant-Control-Based Assisted Walking with Mobile Manipulator

In this paper, a new approach involving the use of a mobile manipulator to assist humans with mobility impairments to walk is proposed. First, in order to achieve flexible interaction between humans and mobile manipulators, we propose a variable admittance controller that can adaptively regulate the virtual mass and damping parameters based on the interaction forces and the human motion intention predicted using the fuzzy theory. Moreover, a feedforward velocity compensator based on a designed state observer is proposed to decrease the inertia resistance of the manipulator, effectively enhancing the compliance of the human-robot interaction. Then, the configuration of the mobile manipulator is optimized based on a null-space approach by considering the singularity, force capacity, and deformation induced by gravity. Finally, the proposed assisted walking approach for the mobile manipulator is implemented using the human-robot interaction controller and the null-space controller. The validity of the proposed controllers and the feasibility of assisted human walking are verified by conducting a set of tests involving different human volunteers.

Search for Scalar Leptoquarks Produced via τ-Lepton-Quark Scattering in pp Collisions at sqrt[s]=13 TeV

The first search for scalar leptoquarks produced in τ-lepton-quark collisions is presented. It is based on a set of proton-proton collision data recorded with the CMS detector at the LHC at a center-of-mass energy of 13 TeV corresponding to an integrated luminosity of 138  fb^{-1}. The reconstructed final state consists of a jet, significant missing transverse momentum, and a τ lepton reconstructed through its hadronic or leptonic decays. Limits are set on the product of the leptoquark production cross section and branching fraction and interpreted as exclusions in the plane of the leptoquark mass and the leptoquark-τ-quark coupling strength.

In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches

The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicology, there is a growing emphasis on refining, reducing, and replacing animal testing in safety evaluations. Therefore, the development of robust computational tools is crucial for regulatory applications. The performance of predictive models is heavily reliant on the quality and quantity of data. In this investigation, we amalgamated the most extensive dataset (4901 compounds) sourced from governmental GHS-compliant databases and literature to develop binary classification models of chemical ocular toxicity. We employed 12 molecular representations in conjunction with six machine learning algorithms and two deep learning algorithms to create a series of binary classification models. The findings indicated that the deep learning method GCN outperformed the machine learning models in cross-validation, achieving an impressive AUC of 0.915. However, the top-performing machine learning model (RF-Descriptor) demonstrated excellent performance with an AUC of 0.869 on the test set and was therefore selected as the best model. To enhance model interpretability, we conducted the SHAP method and attention weights analysis. The two approaches offered visual depictions of the relevance of key descriptors and substructures in predicting ocular toxicity of chemicals. Thus, we successfully struck a delicate balance between data quality and model interpretability, rendering our model valuable for predicting and comprehending potential ocular-toxic compounds in the early stages of drug discovery.

[System analysis of the ecological distribution of bacteriophages in hospital wastewater]

Phage therapy is one of the most important tools for the treatment of infections with multi-drug resistant bacteria. Such phages are usually isolated from hospital effluents, however, no systematic study on the distribution of phages in hospital effluents has been conducted so far. The aim of this study was to isolate the corresponding phages of common pathogenic bacteria isolated in the clinic as hosts, so as to assess the ecological distribution of phages in hospital wastewater and to provide a reference for the isolation and application of phages of drug-resistant bacteria in the clinic. A cross-sectional study design was used in this study. The 125 pathogenic bacteria (belonging to 16 different strains) isolated from the clinical microbiology laboratory of Qilu Hospital of Shandong University from May to June 2023 were selected as the target strains, and the phages corresponding to these strains were isolated and purified from the hospital wastewater by using the double-layer plate sandwich method. At the same time, the distribution of pathogenic bacteria in the same batch of wastewater was analyzed with the help of mNGS sequencing technology, so as to preliminarily investigate the abundance correspondence between pathogenic bacteria and phages in wastewater. The results showed that a total of 56 phage strains were isolated from 125 clinical pathogens as hosts, corresponding to six pathogens, including Acinetobacter baumannii, Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia. All six pathogenic bacteria contained strains with different degrees of drug resistance, with a higher percentage of multi-drug resistant strains in A. baumannii, Escherichia coli and P. aeruginosa. The phage acquisition rates of these six pathogens were, in descending order, Escherichia coli (80%), Stenotrophomonas maltophilia (75%), Pseudomonas aeruginosa (70%), Klebsiella pneumoniae (66.67%), Acinetobacter baumannii (36.36%) and Staphylococcus aureus (12.5%). Preliminary mNGS sequencing results showed that the pathogenic bacteria with higher abundance in the batch of effluent were Enterococcus faecalis, Klebsiella pneumoniae, Escherichia coli, Enterococcus faecalis, Acinetobacter baumannii, Klebsiella aerogenes, Klebsiella michiganensis and Pseudomonas aeruginosa. In conclusion, phages of most common clinical Gram-negative pathogens were isolated from hospital wastewater with high isolation rates; however, phages of Gram-positive pathogens were isolated at lower rates, and only phages corresponding to Staphylococcus aureus were isolated in this study. The corresponding mNGS sequencing results showed that the distribution of Gram-negative pathogens in sewage may had a positive correlation with the ecological distribution of phages.

Microscopic Origins of the Distinct Mechanical Response of ABA and ABC Block Copolymer Nanostructures

It has been commonly believed that the ordered thermoplastic elastomers formed by the ABC triblock copolymer should have better mechanical performance than that by the ABA counterpart due to the higher bridging fraction. However, the thermoplastic elastomer of ABA was often observed to perform better than that of ABC. To compare the performance of two kinds of thermoplastic elastomers and unveil the underlying microscopic mechanism, we have calculated their stress-strain curves using coarse-grained molecular dynamics simulations in conjunction with self-consistent field theory. It is revealed that the stretching degree of the bridging blocks and the network connectivity play important roles in determining the mechanical properties in addition to the bridging fraction. The higher degree in the stretching of bridging blocks and network connectivity of the structure formed by the ABA triblock copolymer enables its superior mechanical performance over the ABC block copolymer.

A new method to estimate the histological stage of primary biliary cholangitis

OBJECTIVE

To analyze the diagnostic efficacy of the periportal hypoechoic band (PHB) in the histological stage of patients with primary biliary cholangitis (PBC).

METHODS

We prospectively included 77 cases of PBC pathologically or clinically confirmed, and high-frequency ultrasound (HFUS) measurements of the PHB were performed in all included patients. Ludwig staging system of histopathology was used as the gold standard.

RESULTS

The width of the PHB was positively correlated with histological staging (r = 0.844, p < 0.001). By area under the receiving operating characteristic curve (AUROC), the best cutoff value for PHB for advanced stage (≥ stage 3) was 2.4 mm (AUROC: 0.934; 95%CI: 0.841-0.981) and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The correct rate for early-stage PBC was 87.9% and for the progressive stage was 93.1%. After multi-factor regression analysis, the PHB (OR = 1.331, CI = 1.105-1.603, p = 0.003) and total bilirubin (OR = 1.156, CI = 1.041-1.285, p = 0.007) were independent influencing factors for progressive PBC.

CONCLUSIONS

Measurement of the PHB to assess advanced PBC is a simple and effective method. This method may complement current methods for the histological staging assessment of patients with PBC.

REGISTRATION

Clinical trial registration: ChiCTR 2000032053, 2020/04/19.

CLINICAL RELEVANCE STATEMENT

The measurement of periportal hypoechoic band (PHB) provides a simple and easy assessment of the degree of disease progression in patients with PBC and provides an important clinical reference in predicting the histological staging of PBC from an ultrasound perspective.

KEY POINTS

• The PHB is correlated with histological staging in the patient with PBC. • The area under the ROC curves of PHB for detecting advanced stage (≥ stage 3) were 0.934 and 0.93 for sensitivity, and 0.91 for specificity, the concordance rates of PHB vs. liver biopsy was 90.3%. The application of PHB can better assess the advanced PBC. • Measurement of the PHB to assess advanced PBC is a simple and effective method that can significantly reduce the need for liver biopsy.

Curcumin alleviates myocardial inflammation, apoptosis, and oxidative stress induced by acute pulmonary embolism by regulating microRNA-145-5P/insulin receptor substrate 1 axis

The treatment of patients with acute pulmonary embolism (APE) is extremely challenging due to the complex clinical presentation and prognosis of APE related to the patient's hemodynamic status and insufficient arterial blood flow and right ventricular overload. Protective efficacy against cardiovascular diseases of curcumin, a common natural polyphenolic compound, which has antithrombotic properties and reduces platelet accumulation in the circulation by inhibiting thromboxane synthesis has been demonstrated. However, the direct effect of curcumin on APE has rarely been studied. Therefore, the present study aimed to investigate the therapeutic potential of curcumin in APE and associated myocardial injury to provide new insights into curcumin as a promising competitive new target for the treatment of APE. A suspension of 12 mg/kg microspheres was injected intravenously into rats. An APE rat model was built. Before modeling, intragastric 100 mg/kg curcumin was given, and/or lentiviral plasmid vector targeting microRNA-145-5p or insulin receptor substrate 1 (IRS1) was injected. Pulmonary artery pressure was measured to assess right ventricular systolic pressure (RVSP). Hematoxylin and eosin (H&E) staining was performed on liver tissues and myocardial tissues of APE rats. TUNEL (terminal deoxynucleotidyl transferase biotin-dUTP nick end labeling) staining and immunohistochemical (IHC) staining were conducted to measure apoptosis and CyPA-CD147 expression in the myocardium, respectively. Inflammatory indices interleukin-1beta (IL-1β), interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-α) were measured by ELISA in cardiac tissues. RT-qPCR and Western blot were performed to determine the expression levels of related genes. In addition, by dual luciferase reporter assay and RIP assay, the relationship between microRNA-145-5p and insulin receptor substrate 1 (IRS1) was confirmed. In results: curcumin improved APE-induced myocardial injury, reduced myocardial tissue edema, and thrombus volume. It attenuated APE-induced myocardial inflammation and apoptosis, as well as reduced lung injury and pulmonary artery pressure. Curcumin promoted microRNA-145-5p expression in APE rat myocardium. MicroRNA-145-5p overexpression protected against APE-induced myocardial injury, and microRNA-145-5p silencing abolished the beneficial effects of curcumin in APE-induced myocardial injury. IRS1 was targeted by microRNA-145-5p. IRS1 silencing attenuated APE-induced myocardial injury, and enhanced therapeutic effect of curcumin on myocardial injury in APE rats. In conclusion, curcumin alleviates myocardial inflammation, apoptosis, and oxidative stress induced by APE by regulating microRNA-145-5p/IRS1 axis.

A review of nuclear Dbf2-related kinase 1 (NDR1) protein interaction as promising new target for cancer therapy

Nuclear Dbf2-related kinase 1 (NDR1) is a nuclear Dbf2-related (NDR) protein kinase family member, which regulates cell functions and participates in cell proliferation and differentiation through kinase activity. NDR1 regulates physiological functions by interacting with different proteins. Protein-protein interactions (PPIs) are crucial for regulating biological processes and controlling cell fate, and as a result, it is beneficial to study the actions of PPIs to elucidate the pathological mechanism of diseases. The previous studies also show that the expression of NDR1 is deregulated in numerous human cancer samples and it needs the context-specific targeting strategies for NDR1. Thus, a comprehensive understanding of the direct interaction between NDR1 and varieties of proteins may provide new insights into cancer therapies. In this review, we summarize recent studies of NDR1 in solid tumors, such as prostate cancer and breast cancer, and explore the mechanism of action of PPIs of NDR1 in tumors.

Effect of occlusal stabilisation splint with or without arthroscopic disc repositioning on condylar bone remodelling in adolescent patients

The aim of this study was to investigate the treatment effects of a stabilisation splint (SS) with and without arthroscopic disc repositioning (ADR) on condylar bone remodelling in adolescent patients with anterior disc displacement without reduction (ADDwoR). Cone beam computed tomography and magnetic resonance imaging were used to analyse condylar bone remodelling, condyle position, and disc position. Twenty-two temporomandibular joints of 14 patients who underwent ADR (age range 12-20 years; mean follow-up 12.5 ± 7.8 months) and 21 temporomandibular joints of 14 patients who did not undergo ADR (age range 13-20 years; mean follow-up 11.1 ± 5.1 months) were included. The change in bone volume (P < 0.001), rate of bone volume change (P < 0.001), and change in condyle height (P = 0.031) were significantly greater in patients with ADR than in those without ADR. The changes in posterior joint space (P = 0.013), superior joint space (P = 0.020), and ratio of condyle sagittal position (P = 0.013) were significantly greater in patients with ADR than in those without ADR. All discs in patients who underwent ADR and one disc in those who did not undergo ADR were backward repositioned. In conclusion, in adolescent patients with ADDwoR, ADR with SS therapy achieved better condyle and disc position than SS therapy alone, and also induced bone generation.

Bronchiolar adenoma/ciliated muconodular papillary tumour: advancing clinical, pathological, and imaging insights for future perspectives

Bronchiolar adenoma/ciliated muconodular papillary tumour (BA/CMPT) is a benign peripheral lung tumour composed of bilayered bronchiolar-type epithelium containing a continuous basal cell layer; however, the similarities in imaging and tissue biopsy findings at histopathology between BA/CMPT and malignant tumours, including lung adenocarcinoma, pose significant challenges in accurately diagnosing BA/CMPT preoperatively. This difficulty in differentiation often results in misdiagnosis and unnecessary overtreatment. The objective of this article is to provide a comprehensive and systematic review of BA/CMPT, encompassing its clinical manifestations, pathological basis, imaging features, and differential diagnosis. By enhancing healthcare professionals' understanding of this disease, we aim to improve the accuracy of preoperative BA/CMPT diagnosis. This improvement is crucial for the development of appropriate therapeutic strategies and the overall improvement of patient prognosis.

Focused solar annealing for block copolymer fast self-assembly

Block copolymer (BCP) self-assembly has tremendous potential applications in next-generation nanolithography. It offers significant advantages, including high resolution and cost-effectiveness, effectively overcoming the limitations associated with conventional optical lithography. In this work, we demonstrate a focused solar annealing (FSA) technique that is facile, eco-friendly, and energy-efficient for fast self-assembly of polystyrene-block-poly(methyl methacrylate) (PS-b-PMMA) thin films. The FSA principle involves utilizing a common biconvex lens to converge incident solar radiation into a high-temperature spot, which is directly used to drive the microphase separation of PS-b-PMMA thin films. As a result, PS-b-PMMA undergoes self-assembly, forming ordered nanostructures in a vertical orientation at seconds timescales on silicon substrates with a neutral layer. In addition, the FSA technique can be employed for grafting neutral polymer brushes onto the silicon substrate. Furthermore, the FSA's compatibility with graphoepitaxy-directed self-assembly (DSA) of BCP is also demonstrated in the patterning of contact holes. The results of contact hole shrinking show that contact hole prepatterns of ∼60.4 nm could be uniformly shrunk to ∼20.5 nm DSA hole patterns with a hole open yield (HOY) of 100 %. For contact hole multiplication, doublet DSA holes were successfully generated on elliptical templates, revealing an average DSA hole size of ∼21.3 nm. Most importantly, due to the direct use of solar energy, the FSA technique provides many significant advantages such as simplicity, environmental friendliness, solvent-free, low cost, and net-zero carbon emissions, and will open up a new direction for BCP lithography that is sustainable, pollution-free, and carbon-neutral.

Real-world outcomes of chemoimmunotherapy and selective RET inhibitors in Chinese patients with RET fusion-positive non-small cell lung cancer

Background

Rearranged during transfection (RET) gene fusion is a target for non-small cell lung cancer (NSCLC) treatment, and RET inhibitors are approved for advanced NSCLC. The role of immune checkpoint inhibitors (ICIs) in RET fusion-positive NSCLC remains controversial. This retrospective study analyzed the efficacy of ICIs and RET inhibitors in Chinese patients with RET fusion-positive NSCLC.

Methods

Data from patients diagnosed with advanced NSCLC harboring RET fusion from Jan 2017 to Sep 2021 were analyzed. Clinicopathological characteristics and outcomes of ICIs and RET inhibitors treatments were collected.

Results

Seventy-five patients with RET fusion-positive advanced NSCLC were identified. The median age of patients was 57 years, half of the patients were female (50.3%), and most were non-smokers or light smokers (72%). Of the cancer types diagnosed in study patients, the KIF5B-RET fusion subtype accounted for 73.3% (55/75), twelve patients (16%) had CCDC6-RET fusion, and three (4%) had NCOA4-RET fusion. Sixteen patients were treated with ICIs. In previously untreated patients, we observed an objective response rate (ORR) of 71.4% and median progression free survival (PFS) of 7.5 months in seven assessable patients. Of four patients with PD-L1 overexpression (>50%) one received pembrolizumab and the other three patients received pemetrexed, carboplatin, and pembrolizumab or camrelizumab. In these patients, the ORR was 75% and disease control rate was 100%. Fifteen patients received selective RET inhibitors (pralsetinib and selpercatinib), resulting in an ORR of 53.3% (8/15) and median PFS of 10.0 months (95% CI 5.2-14.9).

Conclusions

ICIs for PD-L overexpression and treatment naive patients offer comparable benefits for RET fusion-positive NSCLC, warranting further investigation.

Search for Inelastic Dark Matter in Events with Two Displaced Muons and Missing Transverse Momentum in Proton-Proton Collisions at sqrt[s]=13 TeV

A search for dark matter in events with a displaced nonresonant muon pair and missing transverse momentum is presented. The analysis is performed using an integrated luminosity of 138  fb^{-1} of proton-proton (pp) collision data at a center-of-mass energy of 13 TeV produced by the LHC in 2016-2018. No significant excess over the predicted backgrounds is observed. Upper limits are set on the product of the inelastic dark matter production cross section σ(pp→A^{'}→χ_{1}χ_{2}) and the decay branching fraction B(χ_{2}→χ_{1}μ^{+}μ^{-}), where A^{'} is a dark photon and χ_{1} and χ_{2} are states in the dark sector with near mass degeneracy. This is the first dedicated collider search for inelastic dark matter.

Liquid Metal Composites-Enabled Real-Time Hand Gesture Recognizer with Superior Recognition Speed and Accuracy

Prosthetic hands play a vital role in restoring forearm functionality for patients who have suffered hand loss or deformity. The hand gesture intention recognition system serves as a critical component within the prosthetic hand system. However, accurately and swiftly identifying hand gesture intentions remains a challenge in existing approaches. Here, a real-time motion intention recognition system utilizing liquid metal composite sensor bracelets is proposed. The sensor bracelet detects pressure signals generated by forearm muscle movements to recognize hand gesture intent. Leveraging the remarkable pressure sensitivity of liquid metal composites and the efficient classifier based on the optimized recognition algorithm, this system achieves an average offline and real-time recognition accuracy of 98.2% and 92.04%, respectively, with an average recognition speed of 0.364 s. Thus, this wearable system shows advantages in superior recognition speed and accuracy. Furthermore, this system finds applications in master-slave control of prosthetic hands in unmanned scenarios, such as electrically powered operations, space exploration, and telemedicine. The proposed system promises significant advances in next-generation intent-controlled prosthetic hands and robots.

Detecting Emotional Context for Safer Digital Mental Health Agents

Digital tools for mental health show great promise, but concerns arise when they fail to recognize the user state. We train a classifier to detect the emotional context of dialogs among 6 categories, achieving 78% accuracy on top choice. Importantly greatest areas of confusion (excited-hopeful, angry-sad) are not of the most unsafe kind. Such a classifier could serve as a resource to the dialog managers of future digital mental health agents.

The synergistic effect of diabetes mellitus and osteoporosis on the all-cause mortality: a cohort study of an American population

Background

The increasing incidence of diabetes mellitus (DM) and osteoporosis have different effects on prognosis. The two often co-occur, so we aimed to investigate whether DM and osteoporosis have an effect on all-cause death and whether DM and osteoporosis have a synergistic effect.

Methods

This study analyzed 18,658 subjects from five cycles of the National Health and Nutrition Examination Survey (NHANES). The primary endpoint was all-cause death. The subjects were divided into four groups based on the presence or absence of DM and osteoporosis. Survival curves and Cox regression analysis based on NHANES recommended weights were used to assess the risk of all-cause death between the diseased and non-diseased groups and to calculate additive interactions to assess whether there was a synergistic effect between diabetes and osteoporosis.

Results

The group with DM and osteoporosis had the lowest survival rate. After full adjustment for confounders, patients with DM alone had a 30% higher risk of all-cause death compared with those without DM and osteoporosis (HR: 1.30, 95%CI: 1.09-1.55). Patients with osteoporosis alone had a 67% higher risk of all-cause death (HR: 1.67, 95%CI:1.16-2.43) and patients with combined DM and osteoporosis had a 127% higher risk of all-cause death (HR:2.27, 95%CI: 1.57-3.27). There was an additive interaction between DM and osteoporosis [RERI (95%CI): 1.03(0.55-1.50)] and excess mortality risk of 38% [AP (95% CI) 0.38(0.30-0.46)].

Conclusions

There might be a synergistic effect of DM and osteoporosis on all-cause mortality, and patients with both conditions have a higher risk of death.

A nomogram based on CT intratumoral and peritumoral radiomics features preoperatively predicts poorly differentiated invasive pulmonary adenocarcinoma manifesting as subsolid or solid lesions: a double-center study

Background

The novel International Association for the Study of Lung Cancer (IASLC) grading system suggests that poorly differentiated invasive pulmonary adenocarcinoma (IPA) has a worse prognosis. Therefore, prediction of poorly differentiated IPA before treatment can provide an essential reference for therapeutic modality and personalized follow-up strategy. This study intended to train a nomogram based on CT intratumoral and peritumoral radiomics features combined with clinical semantic features, which predicted poorly differentiated IPA and was tested in independent data cohorts regarding models' generalization ability.

Methods

We retrospectively recruited 480 patients with IPA appearing as subsolid or solid lesions, confirmed by surgical pathology from two medical centers and collected their CT images and clinical information. Patients from the first center (n =363) were randomly assigned to the development cohort (n = 254) and internal testing cohort (n = 109) in a 7:3 ratio; patients (n = 117) from the second center served as the external testing cohort. Feature selection was performed by univariate analysis, multivariate analysis, Spearman correlation analysis, minimum redundancy maximum relevance, and least absolute shrinkage and selection operator. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the model performance.

Results

The AUCs of the combined model based on intratumoral and peritumoral radiomics signatures in internal testing cohort and external testing cohort were 0.906 and 0.886, respectively. The AUCs of the nomogram that integrated clinical semantic features and combined radiomics signatures in internal testing cohort and external testing cohort were 0.921 and 0.887, respectively. The Delong test showed that the AUCs of the nomogram were significantly higher than that of the clinical semantic model in both the internal testing cohort(0.921 vs 0.789, p< 0.05) and external testing cohort(0.887 vs 0.829, p< 0.05).

Conclusion

The nomogram based on CT intratumoral and peritumoral radiomics signatures with clinical semantic features has the potential to predict poorly differentiated IPA manifesting as subsolid or solid lesions preoperatively.

High-Density Packing of Spherical Microdomains from A(AB3)3 Dendron-like Miktoarm Star Copolymer

An A(AB3)3 dendron-like miktoarm star copolymer consisting of polystyrene (PS, A) and poly(2-vinylpyridine) (P2VP, B) was synthesized using a series of anionic polymerization, atom-transfer radical polymerization (ATRP), and click reaction. The morphology of A(AB3)3 changed greatly depending on the volume fraction of A and the chain asymmetry. Interestingly, a body-centered cubic spherical phase was found even at fA = 0.51 because the chain architecture of A(AB3)3 stabilizes the large interfacial curvature toward A domains. On the other hand, when the length difference between the end and middle A blocks decreased, a hexagonally packed cylindrical phase was formed at fA = 0.50. This is attributed to the fact that the middle A chains are arranged in a more relaxed way, resulting in a milder interfacial curvature toward A domains. The experimental observations are well-consistent with the predictions based on self-consistent-field theory.

Hierarchically Structured Nanocomposites via Mixed-Graft Block Copolymer Templating: Achieving Controlled Nanostructure and Functionality

Integrating inorganic and polymerized organic functionalities to create composite materials presents an efficient strategy for the discovery and fabrication of multifunctional materials. The characteristics of these composites go beyond a simple sum of individual component properties; they are profoundly influenced by the spatial arrangement of these components and the resulting homo-/hetero-interactions. In this work, we develop a facile and highly adaptable approach for crafting nanostructured polymer-inorganic composites, leveraging hierarchically assembling mixed-graft block copolymers (mGBCPs) as templates. These mGBCPs, composed of diverse polymeric side chains that are covalently tethered with a defined sequence to a linear backbone polymer, self-assemble into ordered hierarchical structures with independently tuned nano- and mesoscale lattice features. Through the coassembly of mGBCPs with diversely sized inorganic fillers such as metal ions (ca. 0.1 nm), metal oxide clusters (0.5-2 nm), and metallic nanoparticles (>2 nm), we create three-dimensional filler arrays with controlled interfiller separation and arrangement. Multiple types of inorganic fillers are simultaneously integrated into the mGBCP matrix by introducing orthogonal interactions between distinct fillers and mGBCP side chains. This results in nanocomposites where each type of filler is selectively segregated into specific nanodomains with matrix-defined orientations. The developed coassembly strategy offers a versatile and scalable pathway for hierarchically structured nanocomposites, unlocking new possibilities for advanced materials in the fields of optoelectronics, sensing, and catalysis.

Self-Assembled Three-Dimensional Polyamide/Silver Nanoparticle Pore Array as a Highly Sensitive and Reproducible SERS Substrate for Pesticide Detection in Water

In this study, silver nanoparticles (AgNPs) are self-assembled onto the polyamide (PA) pore array through hydrogen bonding, resulting in and optimizing the PA/Ag 3D pore array substrates. The best surface-enhanced Raman scattering (SERS) substrate is obtained with a pore depth of 500 nm in the PA array, 30 nm AgNPs, at a pH of 5.0, and a 24 h assembly time. The SERS performance of the substrates is assessed using rhodamine 6G (R6G) as a probe molecule. The detection limit of the R6G molecule reaches 10-13 M, and the relative standard deviation is under 20%, indicating good enhancement ability and reproducibility. Furthermore, label-free detection of pesticide contaminant diquat with a detection limit of 2.69 × 10-9 M is achieved using the optimized 3D substrate, which meets environmental monitoring requirements for drinking water. The findings demonstrate that this 3D SERS substrate has promising potential for use and development in the fields of contaminant detection and chemical sensing.

Luminosity determination using Z boson production at the CMS experiment

The measurement of Z boson production is presented as a method to determine the integrated luminosity of CMS data sets. The analysis uses proton-proton collision data, recorded by the CMS experiment at the CERN LHC in 2017 at a center-of-mass energy of 13Te V . Events with Z bosons decaying into a pair of muons are selected. The total number of Z bosons produced in a fiducial volume is determined, together with the identification efficiencies and correlations from the same data set, in small intervals of 20pb - 1 of integrated luminosity, thus facilitating the efficiency and rate measurement as a function of time and instantaneous luminosity. Using the ratio of the efficiency-corrected numbers of Z bosons, the precisely measured integrated luminosity of one data set is used to determine the luminosity of another. For the first time, a full quantitative uncertainty analysis of the use of Z  bosons for the integrated luminosity measurement is performed. The uncertainty in the extrapolation between two data sets, recorded in 2017 at low and high instantaneous luminosity, is less than 0.5%. We show that the Z boson rate measurement constitutes a precise method, complementary to traditional methods, with the potential to improve the measurement of the integrated luminosity.