Leveraging Serial Low-Dose CT Scans in Radiomics-based Reinforcement Learning to Improve Early Diagnosis of Lung Cancer at Baseline Screening.

Purpose To evaluate the feasibility of leveraging serial low-dose CT (LDCT) scans to develop a radiomics-based reinforcement learning (RRL) model for improving early diagnosis of lung cancer at baseline screening. Materials and Methods In this retrospective study, 1951 participants (female patients, 822; median age, 61 years [range, 55-74 years]) (male patients, 1129; median age, 62 years [range, 55-74 years]) were randomly selected from the National Lung Screening Trial between August 2002 and April 2004. An RRL model using serial LDCT scans (S-RRL) was trained and validated using data from 1404 participants (372 with lung cancer) containing 2525 available serial LDCT scans up to 3 years. A baseline RRL (B-RRL) model was trained with only LDCT scans acquired at baseline screening for comparison. The 547 held-out individuals (150 with lung cancer) were used as an independent test set for performance evaluation. The area under the receiver operating characteristic curve (AUC) and the net reclassification index (NRI) were used to assess the performances of the models in the classification of screen-detected nodules. Results Deployment to the held-out baseline scans showed that the S-RRL model achieved a significantly higher test AUC (0.88 [95% CI: 0.85, 0.91]) than both the Brock model (AUC, 0.84 [95% CI: 0.81, 0.88]; P = .02) and the B-RRL model (AUC, 0.86 [95% CI: 0.83, 0.90]; P = .02). Lung cancer risk stratification was significantly improved by the S-RRL model as compared with Lung CT Screening Reporting and Data System (NRI, 0.29; P < .001) and the Brock model (NRI, 0.12; P = .008). Conclusion The S-RRL model demonstrated the potential to improve early diagnosis and risk stratification for lung cancer at baseline screening as compared with the B-RRL model and clinical models. Keywords: Radiomics-based Reinforcement Learning, Lung Cancer Screening, Low-Dose CT, Machine Learning © RSNA, 2024 Supplemental material is available for this article.

Dynamic Active Sites In Situ Formed in Metal Nanoparticle Reshaping under Reaction Conditions.

Understanding the nonequilibrium transformation of nanocatalysts under reaction conditions is important because metastable atomic structures may be created during the process, which offers unique activities in reactions. Although reshaping of metal nanoparticles (NPs) under reaction conditions has been widely recognized, the dynamic reshaping process has been less studied at the atomic scale. Here, we develop an atomistic kinetic Monte Carlo model to simulate the complete reshaping process of Pt nanoparticles in a CO environment and reveal the in situ formation of atomic clusters on the NP surface, a new type of active site beyond conventional understanding, boosting the reactivities in the CO oxidation reaction. Interestingly, highly active peninsula and inactive island clusters both form on the (111) facets and interchange in varying states of dynamic equilibrium, which influences the catalytic activities significantly. This study provides new fundamental knowledge of nanocatalysis and new guidance for the rational design of nanocatalysts.

Optimizing early neurological deterioration prediction in acute ischemic stroke patients following intravenous thrombolysis: a LASSO regression model approach.

Background: Acute ischemic stroke (AIS) remains a leading cause of disability and mortality globally among adults. Despite Intravenous Thrombolysis (IVT) with recombinant tissue plasminogen activator (rt-PA) emerging as the standard treatment for AIS, approximately 6-40% of patients undergoing IVT experience Early Neurological Deterioration (END), significantly impacting treatment efficacy and patient prognosis. Objective: This study aimed to develop and validate a predictive model for END in AIS patients post rt-PA administration using the Least Absolute Shrinkage and Selection Operator (LASSO) regression approach. Methods: In this retrospective cohort study, data from 531 AIS patients treated with intravenous alteplase across two hospitals were analyzed. LASSO regression was employed to identify significant predictors of END, leading to the construction of a multivariate predictive model. Results: Six key predictors significantly associated with END were identified through LASSO regression analysis: previous stroke history, Body Mass Index (BMI), age, Onset to Treatment Time (OTT), lymphocyte count, and glucose levels. A predictive nomogram incorporating these factors was developed, effectively estimating the probability of END post-IVT. The model demonstrated robust predictive performance, with an Area Under the Curve (AUC) of 0.867 in the training set and 0.880 in the validation set. Conclusion: The LASSO regression-based predictive model accurately identifies critical risk factors leading to END in AIS patients following IVT. This model facilitates timely identification of high-risk patients by clinicians, enabling more personalized treatment strategies and optimizing patient management and outcomes.

Effects of laparoscopic radical prostatectomy on wound infection of surgery in patients with prostate cancer: A meta-analysis.

This meta-analysis aims to comprehensively assess the impact of laparoscopic radical prostatectomy (LRP) on wound infection in patients with prostate cancer (PCa). A systematic search was conducted, from database inception to November 2023, in EMBASE, Google Scholar, Cochrane Library, PubMed, Wanfang and China National Knowledge Infrastructure databases for randomized controlled trials (RCTs) comparing LRP with open radical prostatectomy (ORP) in the treatment of PCa. Two researchers independently screened the literature, extracted data and conducted quality assessments based on pre-defined inclusion and exclusion criteria. Stata 17.0 software was employed for data analysis. Overall, 15 RCTs involving 1458 PCa patients were included. The analysis revealed the incidence of wound infection (odds ratio [OR] = 0.28, 95% confidence interval [CI] = 0.16-0.51, p < 0.001) and complications (OR = 0.27, 95% CI = 0.20-0.37, p < 0.001) was significantly lower in the LRP group compared to the ORP group. This study demonstrates that LRP in PCa patients can effectively reduce the incidence of wound infections and complications, indicating significant therapeutic efficacy and justifying its broader clinical application.

A Novel Interpretable Radiomics Model to Distinguish Nodular Goiter From Malignant Thyroid Nodules.

OBJECTIVES: The purpose of this study is to inquire about the potential association between radiomics features and the pathological nature of thyroid nodules (TNs), and to propose an interpretable radiomics-based model for predicting the risk of malignant TN. METHODS: In this retrospective study, computed tomography (CT) imaging and pathological data from 141 patients with TN were collected. The data were randomly stratified into a training group (n = 112) and a validation group (n = 29) at a ratio of 4:1. A total of 1316 radiomics features were extracted by using the pyradiomics tool. The redundant features were removed through correlation testing, and the least absolute shrinkage and selection operator (LASSO) or the minimum redundancy maximum relevance standard was used to select features. Finally, 4 different machine learning models (RF Hybrid Feature, SVM Hybrid Feature, RF, and LASSO) were constructed. The performance of the 4 models was evaluated using the receiver operating characteristic curve. The calibration curve, decision curve analysis, and SHapley Additive exPlanations method were used to evaluate or explain the best radiomics machine learning model. RESULTS: The optimal radiomics model (RF Hybrid Feature model) demonstrated a relatively high degree of discrimination with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% CI, 0.70-0.97; P < 0.001) for the validation cohort. Compared with the commonly used LASSO model (AUC, 0.78; 95% CI, 0.60-0.91; P < 0.01), there is a significant improvement in AUC in the validation set, net reclassification improvement, 0.79 (95% CI, 0.13-1.46; P < 0.05), and integrated discrimination improvement, 0. 20 (95% CI, 0.10-0.30; P < 0.001). CONCLUSION: The interpretable radiomics model based on CT performs well in predicting benign and malignant TNs by using quantitative radiomics features of the unilateral total thyroid. In addition, the data preprocessing method incorporating different layers of features has achieved excellent experimental results. CLINICAL RELEVANCE STATEMENT: As the detection rate of TNs continues to increase, so does the diagnostic burden on radiologists. This study establishes a noninvasive, interpretable and accurate machine learning model to rapidly identify the nature of TN found in CT.

Integrative analysis from multi-center studies identifies a weighted gene co-expression network analysis-based Tregs signature in ovarian cancer.

Ovarian cancer (OC) is a malignancy associated with poor prognosis and has been linked to regulatory T cells (Tregs) in the immune microenvironment. Nevertheless, the association between Tregs-related genes (TRGs) and OC prognosis remains incompletely understood. The xCell algorithm was used to analyze Tregs scores across multiple cohorts. Weighted gene co-expression network analysis (WGCNA) was utilized to identify potential TRGs and molecular subtypes. Furthermore, we used nine machine learning algorithms to create risk models with prognostic indicators for patients. Reverse transcription-quantitative polymerase chain reaction and immunofluorescence staining were used to demonstrate the immunosuppressive ability of Tregs and the expression of key TRGs in clinical samples. Our study found that higher Tregs scores were significantly correlated with poorer overall survival. Recurrent patients exhibited increased Tregs infiltration and reduced CD8+ T cell. Moreover, molecular subtyping using seven key TRGs revealed that subtype B exhibited higher enrichment of multiple oncogenic pathways and had a worse prognosis. Notably, subtype B exhibited high Tregs levels, suggesting immune suppression. In addition, we validated machine learning-derived prognostic models across multiple platform cohorts to better distinguish patient survival and predict immunotherapy efficacy. Finally, the differential expression of key TRGs was validated using clinical samples. Our study provides novel insights into the role of Tregs in the immune microenvironment of OC. We identified potential therapeutic targets derived from Tregs (CD24, FHL2, GPM6A, HOXD8, NAP1L5, REN, and TOX3) for personalized treatment and created a machining learning-based prognostic model for OC patients, which could be useful in clinical practice.

Disorder-tunable entanglement at infinite temperature.

Emerging quantum technologies hold the promise of unravelling difficult problems ranging from condensed matter to high-energy physics while, at the same time, motivating the search for unprecedented phenomena in their setting. Here, we use a custom-built superconducting qubit ladder to realize non-thermalizing states with rich entanglement structures in the middle of the energy spectrum. Despite effectively forming an "infinite" temperature ensemble, these states robustly encode quantum information far from equilibrium, as we demonstrate by measuring the fidelity and entanglement entropy in the quench dynamics of the ladder. Our approach harnesses the recently proposed type of non-ergodic behavior known as "rainbow scar," which allows us to obtain analytically exact eigenfunctions whose ergodicity-breaking properties can be conveniently controlled by randomizing the couplings of the model without affecting their energy. The on-demand tunability of quantum correlations via disorder allows for in situ control over ergodicity breaking, and it provides a knob for designing exotic many-body states that defy thermalization.

Protein Z and Protein Z-dependent protease inhibitor in patients with acute ischemic stroke: A prospective mechanistic study.

OBJECTIVES: Protein Z (PZ) /Protein Z-dependent protease inhibitor (ZPI) (PZ/ZPI) system is a new anticoagulant system discovered in recent years, which plays an important role in many diseases. We aimed to compare the plasma PZ/ZPI levels of acute ischemic stroke (AIS) patients and non-stroke control participants and the role of PZ/ZPI in the development of stroke was preliminarily analyzed. MATERIALS AND METHODS: Enzyme linked immunosorbent assay (ELISA) was used to detect and compare plasma PZ levels of 86 patients with acute AIS and 85 non-stroke control patients. Multivariable Logistic regression was used to analyze whether PZ was an independent risk factor for AIS. RESULTS: In the present study, plasma PZ is closely related to inflammatory response, coagulation process and platelet activation, and may participate in the development of AIS by inducing inflammatory responses and interfering with the coagulation process. CONCLUSIONS: Our results suggested that plasma PZ level is one of the independent risk factors of AIS, and plasma ZPI was closely related to coagulation and platelet parameter and may play a role in the coagulation process during AIS.

High or Low Coordination: Insight into the Active Site of Pt Nanoparticles toward CO Oxidation.

The catalytic activity of metal nanoparticles (NPs) is highly dependent on the coordination environment of the surface sites. Understanding the role of different sites in reactions is essential for gaining insights into catalytic activity and the precise design of catalysts. Herein, we used first-principles calculation-based kinetic Monte Carlo simulations to investigate correlations between different sites on Pt NPs in CO oxidation reactions. Low-coordinated (LC) sites favor the CO adsorption and reaction, whereas the oxygen mainly adsorbs on high-coordinated (HC) sites and diffuses to LC sites for reaction at low temperatures. Compared with step-dominated and terrace-dominated structures, the step-terrace structures exhibit higher activities. This reveals that the catalytic performance is not simply determined by the sites where the reaction occurs but is dramatically affected by the kinetic synergies between different sites. A proper way to optimize the activity of Pt catalysts is to balance the LC and HC sites.

Neuroprotective Effects of Leptin on the APP/PS1 Alzheimer's Disease Mouse Model: Role of Microglial and Neuroinflammation.

Background: Microglia are closely linked to Alzheimer's disease (AD) many years ago; however, the pathological mechanisms of AD remain unclear. The purpose of this study was to determine whether leptin affected microglia in the hippocampus of young and aged male APP/PS1 mice. Objective: In a transgenic model of AD, we investigated the association between intraperitoneal injection of leptin and microglia. Methods: We intraperitoneal injection of leptin (1mg/kg) every day for one week and analyzed inflammatory markers in microglia in the hippocampus of adult (6 months) and aged (12 months) APP/PS1 mice. Results: In all leptin treatment group, the brain Aß levels were decrease. We found increased levels of IL-1ß, IL-6 and microglial activation in the hippocampus of adult mice. Using aged mice as an experimental model for chronic neuroinflammation and leptin resistance, the number of Iba-1+ microglia and the levels of IL-1ß/IL-6 in the hippocampus were greatly increased as compared to the adult. But between the leptin treatment and un-treatment, there were no difference. Conclusion: Leptin signaling would regulate the activation of microglia and the release of inflammatory factors, but it is not the only underlying mechanism in the neuroprotective effects of AD pathogenesis.

Green Vertical-Cavity Surface-Emitting Lasers Based on InGaN Quantum Dots and Short Cavity.

Room temperature low threshold lasing of green GaN-based vertical cavity surface emitting laser (VCSEL) was demonstrated under continuous wave (CW) operation. By using self-formed InGaN quantum dots (QDs) as the active region, the VCSEL emitting at 524.0 nm has a threshold current density of 51.97 A cm-2, the lowest ever reported. The QD epitaxial wafer featured with a high IQE of 69.94% and the δ-function-like density of states plays an important role in achieving low threshold current. Besides, a short cavity of the device (~ 4.0 λ) is vital to enhance the spontaneous emission coupling factor to 0.094, increase the gain coefficient factor, and decrease the optical loss. To improve heat dissipation, AlN layer was used as the current confinement layer and electroplated copper plate was used to replace metal bonding. The results provide important guidance to achieving high performance GaN-based VCSELs.

Enhanced photothermal therapy performance of D-A conjugated polymers based on [1,2,3]triazolo[4,5-g]quinoxaline by manipulating molecular motion.

Donor-acceptor (D-A) conjugated polymers can favor the nonradiative thermal dissipation process, due to the formation of an intramolecular charge transfer (ICT) state resulting from the electron cloud delocalization of the HOMO (highest occupied molecular orbital) and LUMO (lowest unoccupied molecular orbital). Thus, to realize a high extinction coefficient and excellent photothermal conversion ability for a single photothermal agent, donor-acceptor type conjugated polymers PBDT-QTz and PCDT-QTz, comprising a new electron-deficient unit 2-(2-decyltetradecyl)-6,7-dimethyl-2H-[1,2,3]triazolo [4,5-g] quinoxaline (QTz) as the acceptor and 4,8-di(thiophen-2-yl)benzo[1,2-b:4,5-b']dithiophene (BDT) or 4H-cyclopenta[2,1-b:3,4-b'] dithiophene (CDT) as the donor, are designed and synthesized by manipulating intramolecular motion. The high extinction coefficient of 28.5 L g-1 cm-1 at 850 nm and the optimal photothermal conversion efficiency of 64.3% under an 808 nm laser are achieved based on PBDT-QTz. Consequently, PBDT-QTz nanoparticles can be successfully used for both in vitro and in vivo experiments. After intravenous administration and 808 nm laser irradiation, HeLa tumor-bearing mice achieve complete tumor remission without recurrence. The results provide an efficient photothermal agent by manipulating molecular motion.

Identification of [1,2,4]Triazolo[4,3-a]pyrazine PARP1 inhibitors with overcome acquired resistance activities.

Poly(ADP-ribose) polymerase 1 (PARP1) inhibitors can selectively kill homologous recombination (HR) deficient cancer cells and elicit anticancer effect through a mechanism of synthetic lethality. In this study, we designed, synthesized and pharmacologically evaluated a series of [1,2,4]triazolo[4,3-a]pyrazine derivatives as a class of potent PARP1 inhibitors. Among them, compounds 17m, 19a, 19c, 19e, 19i and 19k not only displayed more potent inhibitory activities (IC50s < 4.1 nM) than 9 and 1 against PARP1, but also exhibited nanomolar range of antiproliferative effects against MDA-MB-436 (BRCA1-/-, IC50s < 1.9 nM) and Capan-1 (BRCA2-/-, IC50s < 21.6 nM) cells. Notably, 19k significantly inhibited proliferation of resistant Capan-1 cells (IC50s < 0.3 nM). Collectively, the newly discovered PARP1 inhibitors act as a useful pharmacological tool for investigating the mechanism of acquired resistance to PARP1 inhibitors, and may also represent promising therapeutic agents for the treatment of HR deficient cancers with the potential to overcome the acquired resistance.

Quinoxalineimide-Based Semiconducting Polymer Nanoparticles as an Effective Phototheranostic for the Second Near-Infrared Fluorescence Imaging and Photothermal Therapy.

Multifunctional theranostics play a critical role in improving the efficacy of photothermal therapy and tumor fluorescence imaging; however, they require the integration of complex components into a single theranostic system, and their response in the second near-infrared (NIR-II) region is constrained by wavelengths of a photosensitizer. To address this issue, we herein developed a novel multifunctional thiazole-fused quinoxalineimide semiconducting polymer (named PQIA-BDTT), which exhibits NIR-II fluorescence and photothermal properties. PQIA-BDTT nanoparticles achieved an impressively high photothermal conversion efficiency (72.6%) in laser (1064 nm)-induced photothermal therapy at a safe maximum permissible exposure, demonstrating their capability as an effective photothermal agent. Moreover, PQIA-BDTT nanoparticles can be used as a reference for NIR-II fluorescence imaging under a low laser fluence. The tumor size and location in 4T1 mice intravenously injected with the PQIA-BDTT nanoparticles could be precisely identified through NIR-II fluorescence imaging, which also exhibited remarkable photothermal antitumor efficacy by in vitro and in vivo therapy. Overall, this study demonstrates that introducing a thiazole-fused quinoxalineimide acceptor unit into a donor-acceptor conjugated polymer is an effective strategy for the synthesis of novel multifunctional theranostic systems, which provides a novel platform for designing theranostic agents for biomedical applications.

Achieving Bright Organic Light-Emitting Field-Effect Transistors with Sustained Efficiency through Hybrid Contact Design.

Organic light-emitting field-effect transistors (OLEFETs) with bilayer structures have been widely studied due to their potential to integrate high-mobility organic transistors and efficient organic light-emitting diodes. However, these devices face a major challenge of imbalance charge transport, leading to a severe efficiency roll-off at high brightness. Here, we propose a solution to this challenge by introducing a transparent organic/inorganic hybrid contact with specially designed electronic structures. Our design aims to steadily accumulate the electrons injected into the emissive polymer, allowing the light-emitting interface to effectively capture more holes even when the hole current increases. Our numerical simulations show that the capture efficiency of these steady electrons will dominate charge recombination and lead to a sustained external quantum efficiency of 0.23% over 3 orders of magnitude of brightness (4 to 7700 cd/m2) and current density (1.2 to 2700 mA/cm2) from -4 to -100 V. The same enhancement is retained even after increasing the external quantum efficiency (EQE) to 0.51%. The high and tunable brightness with stable efficiency offered by hybrid-contact OLEFETs makes them ideal light-emitting devices for various applications. These devices have the potential to revolutionize the field of organic electronics by overcoming the fundamental challenge of imbalance charge transport.

Mastering morphology of non-fullerene acceptors towards long-term stable organic solar cells.

Despite the rapid progress of organic solar cells based on non-fullerene acceptors, simultaneously achieving high power conversion efficiency and long-term stability for commercialization requires sustainable research effort. Here, we demonstrate stable devices by integrating a wide bandgap electron-donating polymer (namely PTzBI-dF) and two acceptors (namely L8BO and Y6) that feature similar structures yet different thermal and morphological properties. The organic solar cell based on PTzBI-dF:L8BO:Y6 could achieve a promising efficiency of 18.26% in the conventional device structure. In the inverted structure, excellent long-term thermal stability over 1400 h under 85 °C continuous heating is obtained. The improved performance can be ascribed to suppressed charge recombination along with appropriate charge transport. We find that the morphological features in terms of crystalline coherence length of fresh and aged films can be gradually regulated by the weight ratio of L8BO:Y6. Additionally, the occurrence of melting point decrease and reduced enthalpy in PTzBI-dF:L8BO:Y6 films could prohibit the amorphous phase to cluster, and consequently overcome the energetic traps accumulation aroused by thermal stress, which is a critical issue in high efficiency non-fullerene acceptors-based devices. This work provides insight into understanding non-fullerene acceptors-based organic solar cells for improved efficiency and stability.

Sustained remission of type 2 diabetes in rodents by centrally administered fibroblast growth factor 4.

Type 2 diabetes (T2D) is a major health and economic burden worldwide. Despite the availability of multiple drugs for short-term management, sustained remission of T2D is currently not achievable pharmacologically. Intracerebroventricular administration of fibroblast growth factor 1 (icvFGF1) induces sustained remission in T2D rodents, propelling intense research efforts to understand its mechanism of action. Whether other FGFs possess similar therapeutic benefits is currently unknown. Here, we show that icvFGF4 also elicits a sustained antidiabetic effect in both male db/db mice and diet-induced obese mice by activating FGF receptor 1 (FGFR1) expressed in glucose-sensing neurons within the mediobasal hypothalamus. Specifically, FGF4 excites glucose-excited (GE) neurons while inhibiting glucose-inhibited (GI) neurons. Moreover, icvFGF4 restores the percentage of GI neurons in db/db mice. Importantly, intranasal delivery of FGF4 alleviates hyperglycemia in db/db mice, paving the way for non-invasive therapy. We conclude that icvFGF4 holds significant therapeutic potential for achieving sustained remission of T2D.

Dysregulation of iron homeostasis by TfR-1 renders EZH2 wild type diffuse large B-cell lymphoma resistance to EZH2 inhibition.

EZH2 has been regarded as an efficient target for diffuse large B-cell lymphoma (DLBCL), but the clinical benefits of EZH2 inhibitors (EZH2i) are limited. To date, only EPZ-6438 has been approved by FDA for the treatment of follicular lymphoma and epithelioid sarcoma. We have discovered a novel EZH1/2 inhibitor HH2853 with a better antitumor effect than EPZ-6438 in preclinical studies. In this study we explored the molecular mechanism underlying the primary resistance to EZH2 inhibitors and sought for combination therapy strategy to overcome it. By analyzing EPZ-6438 and HH2853 response profiling, we found that EZH2 inhibition increased intracellular iron through upregulation of transferrin receptor 1 (TfR-1), ultimately triggered resistance to EZH2i in DLBCL cells. We demonstrated that H3K27ac gain by EZH2i enhanced c-Myc transcription, which contributed to TfR-1 overexpression in insensitive U-2932 and WILL-2 cells. On the other hand, EZH2i impaired the occurrence of ferroptosis by upregulating the heat shock protein family A (Hsp70) member 5 (HSPA5) and stabilizing glutathione peroxidase 4 (GPX4), a ferroptosis suppressor; co-treatment with ferroptosis inducer erastin effectively overrode the resistance of DLBCL to EZH2i in vitro and in vivo. Altogether, this study reveals iron-dependent resistance evoked by EZH2i in DLBCL cells, and suggests that combination with ferroptosis inducer may be a promising therapeutic strategy.