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This paper proposes a time-varying unmanned aerial vehicle (UAV) formation control method based on trajectory prediction and nonlinear model predictive control (NMPC). First, in formation control, the nominal controller is constructed using a linear model and consensus for theoretical stability assurance. The time-varying formation control of nonholonomic UAVs subsequently is achieved by integrating the nonholonomic model with the NMPC, using the desired state derived from the nominal controller. Furthermore, considering the optimal obstacle avoidance problem of moving obstacles, the transformer is used to predict the trajectory in the predictive horizon, the safety constraints are established in combination with the discrete control barrier function (DCBF), and the optimal obstacle avoidance is realized by reducing the additional motion generated during obstacle avoidance. Subsequently, the NMPC-DCBF-transformer is integrated to realize the optimal obstacle avoidance control of nonholonomic UAV time-varying formation. Finally, the algorithm's effectiveness was verified by numerical simulation, and the advantages of the algorithm were verified by comparison. [ABSTRACT FROM AUTHOR]

Background: The global burden of invasive fungal infections (IFIs) has shown an upsurge in recent years due to the higher load of immunocompromised patients suffering from various diseases. The role of early and accurate diagnosis in the aggressive containment of the fungal infection at the initial stages becomes crucial thus, preventing the development of a life-threatening situation. With the changing demands of clinical mycology, the field of fungal diagnostics has evolved and come a long way from traditional methods of microscopy and culturing to more advanced non-culture-based tools. With the advent of more powerful approaches such as novel PCR assays, T2 Candida, microfluidic chip technology, next generation sequencing, new generation biosensors, nanotechnology-based tools, artificial intelligence-based models, the face of fungal diagnostics is constantly changing for the better. All these advances have been reviewed here giving the latest update to our readers in the most orderly flow. Main text: A detailed literature survey was conducted by the team followed by data collection, pertinent data extraction, in-depth analysis, and composing the various sub-sections and the final review. The review is unique in its kind as it discusses the advances in molecular methods; advances in serology-based methods; advances in biosensor technology; and advances in machine learning-based models, all under one roof. To the best of our knowledge, there has been no review covering all of these fields (especially biosensor technology and machine learning using artificial intelligence) with relevance to invasive fungal infections. Conclusion: The review will undoubtedly assist in updating the scientific community's understanding of the most recent advancements that are on the horizon and that may be implemented as adjuncts to the traditional diagnostic algorithms. [ABSTRACT FROM AUTHOR]

Background: Inflammatory biomarkers in the peripheral blood have been established as predictors for immunotherapeutic efficacy in advanced non-small cell lung cancer (NSCLC). Whether they can also predict major pathological response (MPR) in neoadjuvant setting remains unclear. Methods: In this multi-center retrospective study, 122 and 92 stage I-IIIB NSCLC patients from six hospitals who received neoadjuvant chemoimmunotherapy followed by surgery were included in the discovery and external validation cohort, respectively. Baseline and on-treatment neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) were calculated and associated with MPR. Furthermore, resected tumor samples from 37 patients were collected for RNA-sequencing to investigate the immune-related tumor microenvironment. Results: In both the discovery and validation cohorts, the on-treatment NLR, dNLR, PLR, and SII levels were significantly lower in the patients with MPR versus non-MPR. On-treatment SII remained an independent predictor of MPR in multivariate logistic regression analysis. The area under the curve (AUC) of on-treatment SII for predicting MPR was 0.75 (95%CI, 0.67–0.84) in the discovery cohort. Moreover, the predictive value was further improved by combining the on-treatment SII and radiological tumor regression data, demonstrating an AUC of 0.82 (95%CI, 0.74–0.90). The predictive accuracy was validated in the external cohort. Compared with the SII-high group, patients with SII-Low were associated with the activated B cell receptor signaling pathway and a higher intratumoral immune cell infiltration level. Conclusions: On-treatment SII was independently associated with MPR in NSCLC patients receiving neoadjuvant chemoimmunotherapy. Further prospective studies are warranted. [ABSTRACT FROM AUTHOR]

Peptide- and protein-based therapeutics have drawn significant attention over the past few decades for the treatment of infectious diseases, genetic disorders, oncology, and many other clinical needs. Yet, protecting peptide- and protein-based drugs from degradation and denaturation during processing, storage and delivery remain significant challenges. In this review, we introduce the properties of peptide- and protein-based drugs and the challenges associated with their stability and delivery. Then, we discuss delivery strategies using synthetic polymers and their advantages and limitations. This is followed by a focus on silk protein-based materials for peptide/protein drug processing, storage, and delivery, as a path to overcome stability and delivery challenges with current systems. [Display omitted] • The challenges of delivering peptide and protein-based drugs are discussed • The advantages and limitations of synthetic polymer delivery system is introduced for protein and peptide-based drugs • Silk based delivery system is highlighted for deliverying and stabilizing protein and peptide-based drugs [ABSTRACT FROM AUTHOR]

• A real-world study including 76 resectable NSCLC patients having received neoadjuvant chemoimmunotherapy was conducted. • A major pathologic response rate of 64% (49/76) was achieved through the combination therapy. • MPR was associated with increased infiltration of cytotoxic immune cells with tertiary lymphoid structures. Early stage non-small cell lung cancer (NSCLC) patients who undergo complete resection continue to demonstrate high risk of recurrence and death. The advent of the neoadjuvant regimen has brought new hope for these patients. The present study aims to further demonstrate the efficacy of neoadjuvant chemoimmunotherapy. A real-world observational study was conducted concerning patients who received neoadjuvant pembrolizumab or nivolumab combined with chemotherapy between January 2018 and December 2020 in Shanghai Pulmonary Hospital. The primary endpoint was major pathologic response (MPR), and the secondary endpoints were objective response rate (ORR), pathologic complete response (pCR), disease-free survival (DFS) and toxicity. A total of 76 patients were analyzed and divided into the pembrolizumab (n = 42) and nivolumab groups (n = 34) with a median follow-up time of 12.2 months. Most patients (92%) had stage III disease, with 41 (54%) and 29 (38%) patients initially diagnosed clinical stage IIIA and IIIB, respectively. Fifty (66%), 21 (28%) and 5 (6%) patients received two, three and four cycles of neoadjuvant treatment, separately, achieving an ORR of 75%. None of them needed a reduced initial dose or delay due to intolerable adverse events. Forty-nine (64%) and 28 (37%) patients achieved MPR and pCR, respectively. RNA sequencing showed that MPR associated with increased infiltration of cytotoxic immune cells with tertiary lymphoid structures (TLSs). Histological evaluation highlighted the localization of B cells within TLSs. Forty-two (69%) patients with clinically N2 disease at baseline were downstaged to pathological N0 (39 patients) or N1 (3 patients). One-year-PFS rate of stage III patients was 91%. No difference in baseline characteristics and treatment outcomes was observed between 2 groups. The feasibility of neoadjuvant chemoimmunotherapy for resectable NSCLC was further validated, with a high MPR rate and manageable adverse events. [ABSTRACT FROM AUTHOR]

The coordination of green economy, education development, and technological innovation is of great significance for reversing the trend of ecological environmental deterioration and promoting high-quality economic development. This study first designs the indicator system of green economy, education development, and technological innovation, then uses the entropy method to calculate the comprehensive level of green economy, education development, and technological innovation of 30 provinces and cities in China, and finally uses the coupling coordination model to measure the coordination level among them. The research shows that, first, the comprehensive level of green economy, education development, and technological innovation in 30 provinces and cities in China showed a rising trend from 2005 to 2016, but there were some regional differences in their levels. Second, the coordination level of green economy, education development, and technological innovation in different regions of China was in a rising trend from 2005 to 2016, but in 2005, they were extremely uncoordinated. Also, the coordination level of green economy, education development, and technological innovation in most regions of China grew very slowly from 2005 to 2010 but showed a rapid increase from 2011 to 2016. The coordination level of green economy, education development, and technological innovation in eastern China was visibly higher than that of the central region. The coordination level of the central region was higher than that of the northeast region, and the coordination level of the northeast region was higher than that of the western region. Finally, the limitations of this paper are summarized and proposed the direction of future research. [ABSTRACT FROM AUTHOR]

• The prognosis of chest wall invasion cases was differed according to the depth. • Rib invasion cases had worse prognosis than superficial structure invasion cases. • The prognosis of rib invasion cases was inferior to that of pT3 cases. • The prognosis of rib invasion cases was similar with that of pT4 cases. To evaluate the prognosis between patients with non-small cell lung cancer (NSCLC) invading difference depth of chest wall and estimate the impact of rib invasion on the pathological T classifications (pT). We retrospectively evaluated 521 patients with resected pT3-4 NSCLC. Propensity-score matching (PSM) balanced the known confounders of the prognosis, resulting in two sets (rib invasion vs the pT3 and pT4 group). Recurrence-free survival (RFS) and Overall survival (OS) was assessed by Cox regression and Kaplan-Meier methods. Time-dependent receiver operating characteristic (ROC) curves were used to assess the additional benefit for survival prediction after reclassifying rib invasion cases. Chest wall invasion occurred in 171 patients (62 rib invasion, 51 parietal pleural invasion [PL3] and 58 soft tissue invasion). Rib invasion was found to be an independent prognostic factor for both RFS (p = 0.006) and OS (p < 0.001) of pT3-4 NSCLC. The survival of rib invasion group was the worst (RFS: 13.1%; OS: 19.8%), followed by PL3 (RFS: 34.2%, P = 0.001; OS: 48.8%; p < 0.001) and the soft tissue invasion group (RFS: 40.6%, p = 0.001; OS: 57.7%, p < 0.001). Besides, the prognosis of rib invasion group was also found to be worse than those of pT3 (RFS: p < 0.001; OS: p < 0.001) and pT4 group (RFS: p = 0.002; OS: p < 0.001). After PSM, the 5-year RFS rate of rib invasion group were still lower than that of pT3 and pT4 group (p < 0.001); the 5-year OS rate of rib invasion was similar with that of pT4 group (p = 0.066) but lower than that of pT3 group (p = 0.014). The time-dependent ROC curves demonstrated that reclassifying rib invasion as pT4 disease provided an additional benefit for survival prediction (p < 0.001). The rib invasion group had a worse prognosis than the PL3 and pT3 groups. The prognostic impact of rib invasion should be further validated as a pT4 disease in the TNM classification. [ABSTRACT FROM AUTHOR]

OBJECTIVES The goal of this study was to compare the feasibility and safety of uniportal thoracoscopic segmentectomy (UTS) with that of multiportal thoracoscopic segmentectomy (MTS). METHODS From January 2014 to December 2015, a total of 1056 patients who underwent thoracoscopic segmentectomy were identified, including 375 and 681 who had simple and complex segmentectomies, respectively. A propensity matched analysis was applied to compare perioperative indicators. Survival outcomes, which included disease-free survival and overall survival, were assessed by Kaplan–Meier estimates and Cox hazards regression analysis. RESULTS Propensity matching generated 454 paired patients for the UTS and MTS cohorts; the perioperative results were comparable. Survival analysis indicated that the surgical approach (UTS versus MTS) was not an independent risk factor in either disease-free survival (P  =   0.247) or overall survival (P  =   0.870) of patients with invasive adenocarcinoma. A shorter operative time was observed in patients who had a UTS (P  <   0.001) or an MTS (P  =   0.011) via a simple segmentectomy compared with those who had a complex segmentectomy. Moreover, 147 and 266 corresponding cases were selected to compare the UTS and MTS in the simple and complex segmentectomy groups, respectively. MTS showed slightly longer operative times (119 vs 108 min; P  =   0.007) and drainage duration (P  =   0.010) in the simple segmentectomy group. In contrast, UTS was associated with statistically longer operative times (141 vs 133 min; P  =   0.016) in the complex segmentectomy group. CONCLUSIONS Although minor differences could be found in the simple and complex segmentectomy groups, respectively, these results were clinically irrelevant. Our study supports UTS as a feasible and safe surgical technique. [ABSTRACT FROM AUTHOR]

Understanding energy consumption patterns is crucial for energy demand-side management. Unlike traditional data mining or machine learning-based methods, this paper presents visual analysis methods for exploring energy consumption data from spatial, temporal, and spatiotemporal dimensions, including variability, segmentation, and energy demand shifts. To support the proposed methods, we develop a visual analysis tool that allows users to explore consumption data and validate their hypotheses based on visual results through human–client–server interactions. In particular, we propose a novel potential flow-based method to model energy demand shift patterns and have integrated it into the proposed analysis tool. We comprehensively evaluate the proposed methods and the tool using real-world electricity consumption data from the Shanghai Pudong district, and compare with traditional data mining methods. The results demonstrated the effectiveness and superiority of the proposed visual analysis methods, including its ability to discover the spatiotemporal variability of energy demand, customer groups, and demand shift patterns across different geographical areas and time horizons. All results can be well explained by knowledge of the energy consumption in the study region. • Visualization and visual analysis for energy demand-side management. • A visual based method for exploring consumption variability, customer segmentation, and demand shift patterns. • A potential flow method to model energy demand dynamics. [ABSTRACT FROM AUTHOR]

Energy demand-side management, especially empowered by the fine-grained smart meter data, plays a significant role in the rational allocation of energy, monitoring and supervision of energy consumption behaviors. Through the in-depth demand analysis including quantification of energy consumption dynamics and consumer preferences, energy decision-makers can develop reasonable and forethoughtful energy efficiency plans and demand-response programs. Previous work in energy-demand behavioral research relied primarily on ideal socio-economic models or data-driven approaches, both of which lack flexibility, intuition and interpretability. This paper proposes a novel spatio-temporal visual analysis approach for urban energy consumption pattern discovery in order to identify energy-saving potentials, plan energy supply and improve energy efficiency. In this approach, energy consumption time series are embeded into a two-dimensional scatterplot for coordinated visual exploration. Users can interactively explore and discover different patterns for decision-making purposes. In addition, we propose the method for modeling energy demand shift patterns based on a potential flow method and integrate it into a pattern exploration tool. The proposed approach is comprehensively evaluated through empirical studies using the real-world electricity consumption data from Pudong district, Shanghai. We identify five typical energy consumption patterns and demand shift patterns across different geographical locations, which can be well interpreted by the knowledge of energy consumption in the area of interest. The results demonstrate the effectiveness of the proposed approach and the tool. This tool can be integrated into smart energy systems for a better understanding of user energy consumption behaviors and preferences. • Understand the spatial and temporal dynamics of urban energy use through visual analysis and visualization. • A visual analysis tool to facilitate the discovery of energy consumption patterns for smart energy systems. • Development of dimension reduction and visualization methods for high-dimensional time series. • Discovery of typical energy consumption patterns and spatio-temporal shift patterns through an empirical case study. [ABSTRACT FROM AUTHOR]

Peripheral nerve injury leads to severe neuropathic pain. Previous studies have highlighted the beneficial effects of physical exercise on alleviating neuropathic pain. Exercise regulating transforming growth factor-β1 (TGF-β1) can improve several diseases and relieve neuropathic pain induced by peripheral nerve injury. Here, we investigated whether exercise could alleviate neuropathic pain by modulating TGF-β1 expression. We assessed mechanical and cold pain behavior and conducted molecular evaluation of the spinal cord. We found that spared nerve injury (SNI) led to mechanical and cold allodynia in the hind paw, elevated the expression of latency-associated peptide- (LAP-) TGF-β1, and activated astroglial in the spinal cord. Exercise decreases allodynia, astroglial activation, and LAP-TGF-β1 in SNI mice. Intrathecal injection of a TGF-type I receptor inhibitor attenuated exercise analgesia and enhanced astroglial activation. These findings demonstrate that exercise induces analgesia by promoting TGF-β1 activation and inhibiting astrogliosis. Our study reveals a new underlying mechanism for exercise-attenuated neuropathic pain in the maintenance stage of neuropathic pain after nerve injury. [ABSTRACT FROM AUTHOR]

This paper proposes a multiple unmanned aerial vehicles (UAVs) cooperative landing algorithm based on deep reinforcement learning. First, to solve the partial observation problem, we propose the recurrent neural network to predict the moving platform trajectory. Afterwards, with the centralized multiagent framework, we present a parameter sharing method to realize multi-UAV cooperation. Finally, focusing on the sensor noise problem of the actual UAV flight, we propose a noise compensation recurrent proximal policy optimization (NC-RPPO) algorithm to extract images' features to compensate for inertial measurement unit (IMU) and GPS errors. We utilize AirSim to construct a simulated 3D environment resembling an offshore oil development zone. In this setting, we evaluate the effectiveness of our proposed multi-UAV cooperative landing algorithm while considering the presence of sensor noise. Through experimental trials, we demonstrate that our NC-RPPO algorithm enables UAVs to accurately predict the trajectory of a mobile platform and successfully land on it cooperatively in real time. Notably, the experimental outcomes obtained through our image-assisted noise correction method closely align with those obtained from the ground truth experiment. [ABSTRACT FROM AUTHOR]

Objectives: The performance of positron emission tomography/computed tomography (PET/CT) for the prediction of ypN2 disease in non-small cell lung cancer (NSCLC) after neoadjuvant chemoimmunotherapy has not been reported. This multicenter study investigated the utility of PET/CT to assess ypN2 disease in these patients. Methods: A total of 181 consecutive patients (chemoimmunotherapy = 86, chemotherapy = 95) at four institutions were enrolled in this study. Every patient received a PET/CT scan prior to surgery and complete resection with systematic nodal dissection. The diagnostic performance was evaluated through area under the curve (AUC). Kaplan–Meier method and Cox analysis were performed to identify the risk factors affecting recurrences. Results: The sensitivity, specificity, and accuracy of PET/CT for ypN2 diseases were 0.667, 0.835, and 0.779, respectively. Therefore, the AUC was 0.751. Compared with the false positive cases, the mean value of max standardized uptake value (SUVmax) (6.024 vs. 2.672, p < 0.001) of N2 nodes was significantly higher in true positive patients. Moreover, the SUVmax of true positive (7.671 vs. 5.976, p = 0.365) and false (2.433 vs. 2.339, p = 0.990) positive cases were similar between chemoimmunotherapy and chemotherapy, respectively. Survival analysis proved that pathologic N (ypN) 2 patients could be stratified by PET/CT-N2(+ vs. -) for both chemoimmunotherapy (p = 0.023) and chemotherapy (p = 0.010). Conclusions: PET/CT is an accurate and non-invasive test for mediastinal restaging of NSCLC patients who receive neoadjuvant chemoimmunotherapy. The ypN2 patients with PET/CT-N2(+) are identified as an independent prognostic factor compared with PET/CT-N2(-). Clinical relevance statement: Imaging with 18F-fluorodeoxyglucose positron emission tomography/computed tomography (PET/CT) plays an integral role during disease diagnosis, staging, and therapeutic response assessments in patients with NSCLC. PET/CT could be an effective non-invasive tool for predicting ypN2 diseases after neoadjuvant chemoimmunotherapy. Key Points: • PET/CT could serve as an effective non-invasive tool for predicting ypN2 diseases. • The ypN2 patients with PET/CT-N2(+) were a strong and independent prognostic factor. • The application of PET/CT for restaging should be encouraged in clinical practice. [ABSTRACT FROM AUTHOR]

Introduction: The benefits of adjuvant chemoradiation therapy (CRT) for heterogeneous pathological N2 (pN2) diseases remain unclear in non-small cell lung cancer (NSCLC). This study aimed to investigate suitable pN2 patients for adjuvant CRT. Material and methods: This study retrospectively reviewed the data of patients with pN2 NSCLC in Shanghai Pulmonary Hospital from January 2012 to December 2016. Included cases were subdivided as highest mediastinal lymph node (HM) (n = 732) metastasis and non-HM metastasis (n = 677) groups according to the International Association for the Study of Lung Cancer (IASLC). Furthermore, the Kaplan–Meier and Cox models were used to evaluate the prognostic benefits of adjuvant CRT in heterogeneous pN2 subgroups. Results: A total of 1409 patients were enrolled in this study, with a median follow-up time of 63.8 months. Patients with HM involvement had worse prognoses (p < 0.001 for recurrence-free survival (RFS) and overall survival (OS)). Furthermore, the survival improvement of adjuvant CRT was significant for these patients (p < 0.001 for RFS and p = 0.032 for OS), regardless of whether it was single (p < 0.001 for RFS and p = 0.029 for OS) or multiple pN2 (p < 0.001 for RFS and p = 0.026 for OS) diseases. According to multivariable cox analysis, the long-term RFS and OS in the cancerous HM group were independently predicted by pathological N stage (p = 0.002 for RFS and p < 0.001 for OS) and adjuvant CRT (p < 0.001 for RFS and p = 0.011 for OS). Conclusion: Metastatic HM was associated with a worse prognosis in pN2 disease. Our analysis supported that adjuvant CRT significantly improved both RFS and OS for these patients. [ABSTRACT FROM AUTHOR]

• ΔSUV max % could efficiently predict major pathologic response (MPR) in NSCLC patients treated with neoadjuvant therapy. • Remained SUV max is also an effective prognostic indicator for neoadjuvant chemoimmunotherapy. • PFKFB4, which is an enzyme of glycolysis, was identified as a potential biomarker for the treatment resistance. Reliable predictive markers are lacking for resectable non-small cell lung cancer (NSCLC) patients treated with neoadjuvant chemoimmunotherapy. The present study investigated the utility of SUV max values acquired from PET/CT to predict the response to neoadjuvant chemoimmunotherapy for resectable NSCLC. SUV max , clinical and pathological outcomes, were collected from patients in 5 hospitals. Patients who received dynamic PET/CT surveillance were divided into cohorts A (chemoimmunotherapy) and B (chemotherapy), respectively, while cohort C (chemoimmunotherapy) comprised patients undergoing post-therapy PET/CT. Associations between SUV max and major pathologic response (MPR) were evaluated through receiver operating characteristic (ROC) curves. A total of 129 cases with an MPR rate of 46.5 % was identified. In neoadjuvant chemoimmunotherapy, ΔSUV max % (AUC: 0.890, 95 % CI: 0.761–0.949) and post-therapy SUV max (AUC: 0.933, 95 % CI: 0.802–0.959) could accurately predict MPR. On the contrary, the baseline SUV max was not associated with MPR (p = 0.184). Furthermore, an independent cohort C proved that post-therapy SUV max could serve as an independent predictor (AUC: 0.928, 95 % CI: 0.823–0.958). In addition, robust predictive performance could be observed when we use the optimal cut-off point of both ΔSUV max % (54.4 %, AUC: 0.912, 95 % CI: 0.824–0.994) and post-therapy SUV max (3.565, AUC: 0.912, 95 % CI: 0.824–0.994) in neoadjuvant chemoimmunotherapy. The RNA data revealed that the expression of PFKFB4, a key enzyme in glycolysis, was positively correlated with SUV max value and tumor cell proliferation after neoadjuvant chemoimmunotherapy. These findings highlighted that the ΔSUV max % and remained SUV max were accurate and non-invasive tests for the prediction of MPR after neoadjuvant chemoimmunotherapy. [ABSTRACT FROM AUTHOR]

• The pT8 could discriminate the RFS and OS in LP− lung adenocarcinoma (LUAD), but not in LP+ tumors. • LP+ was revealed as a significant favorable prognostic factor in pathological stage I LUAD regardless of lepidic ratio. • The pTm holds better discrimination performances for LUAD prognosis after incorporating LP as an additional T descriptor. The Lepidic Component (LP) identifies a subgroup with an excellent prognosis for lung adenocarcinoma (LUAD). Our research aimed to propose an improved pathological T (pT) stage for LUAD based on LP. Totally, 3335 surgical patients with pathological stage I LUAD were incorporated. Factors affecting survival were investigated by analyzing recurrence-free survival (RFS) and overall survival (OS) using the Kaplan-Meier method and Cox regression analyses. Subgroup analysis based on Lepidic Ratio (LR) was further evaluated. The net benefit from the modified pT category (pTm) was assessed using the Area Under the time-dependent Receiver Operating Curve (AUC), Harrell's Concordance Index (C-index), Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI). The presence of LP (LP+) was identified in 1425 (42.7 %) patients, indicating a significantly better RFS (P < 0.001) and OS (P < 0.001) than those without LP, and similar results were reproduced in pT1a-pT2a subcategory (P < 0.050 for all). Multivariable Cox analysis revealed LP+ as an independent prognostic factor for both RFS (HR, 0.622; P < 0.001) and OS (HR, 0.710; P = 0.019). However, lepidic ratio (LR) was not independently associated with both RFS and OS for LP+ patients. The 5-year RFS and OS rates between T1a (LP−) and T1b (LP+), T1b (LP−) and T1c (LP+), and T1b (LP−) and T2a (LP+) were comparable (P > 0.050 for all). After modification, compared with current 8th edition pT stage system (pT8), pTm independently predicted RFS and OS, and AUCs, c-index, NRI, and IDI analysis all demonstrated pTm holds better discrimination performances than pT8 for LUAD prognosis. LP can be an additional down-staged T descriptor for pathological stage I LUAD and improve the survival predictive performance of reclassification. [ABSTRACT FROM AUTHOR]

Open in new tab Download slide Open in new tab Download slide OBJECTIVES To investigate the impact of lung window (LW) and mediastinal window (MW) settings on the clinical T classifications and prognostic prediction of patients with subsolid nodules. METHODS Seven hundred and nineteen surgically resected subsolid nodules were reviewed, grouping into pure ground-glass nodules (n  = 179) or part-solid nodules (n  = 540) using LW. Interobserver agreement on nodule classifications was assessed via kappa-value, and predictive performance of the solid portion measurement in LW and MW for pathological invasiveness and malignancy were compared using receiver-operating characteristic analysis. Cox regression was used to identify prognostic factors. Prognostic significance of T classifications based on LW (c[l]T) and MW (c[m]T) was evaluated by Kaplan–Meier method after propensity score matching. The performance of c(m)T for discrimination survival was estimated via the concordance index (C-index), net reclassification improvement and integrated-discrimination improvement. RESULTS By adopting MW, 124 part-solid nodules were reclassified as pure ground-glass nodules, and interobserver agreement improved to 0.917 (95% confidence interval 0.888–0.946). The solid portion size under MW more strongly predicted pathological invasiveness (P  =   0.030), but did not better predict pathological malignancy. For remaining 416 part-solid nodules, c(l)T and c(m)T were both independent risk factors. c(m)T led to T classifications shifts in 321 nodules (14 upstaged and 307 downstaged) with no significant prognostic difference existing between the shifted c(m)T and matching c(l)T group after propensity score matching. The corrected C-index was improved to 0.695 (0.620–1.000) when adopting c(m)T with no significant difference in net reclassification improvement (P  =   0.098) and integrated-discrimination improvement (P  =   0.13) analysis. CONCLUSIONS As there is no significant benefit provided by MW in evaluating clinical T classification and prognosis, the current usage of LW is appropriate for assessing subsolid nodules. [ABSTRACT FROM AUTHOR]

We evaluated the prognostic impact of the presence of ground glass opacity (GGO) component and compared a modified clinical T categorization (cT m) with the current 8th classification (cT 8) for survival prediction in Chinese patients with clinical stage I non–small cell lung cancer (NSCLC). According to cT m and cT 8 classifications, we retrospectively evaluated 1461 patients with part-solid or pure-solid lesions. The recurrence-free survival (RFS) and overall survival (OS) were analyzed by Kaplan-Meier method and Cox proportional hazard model. The concordance index (C- index), reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA) were performed to estimate reclassification net benefits of cT m for survival prediction. The cT 8 classification clearly stratifies the survival outcomes in solid tumors but not in part-solid tumors. The presence of GGO components was an independent prognostic factor for both RFS and OS (p < 0.001), indicating a better outcome in each clinical T stage. The C-index was significantly improved from 0.650 to 0.730 for RFS (p < 0.001) and 0.647 to 0.730 for OS (p < 0.001) after reclassifying by cT m categorization. The DCA, NRI (RFS: 0.342, OS: 0.302), and IDI (RFS: 0.070, OS: 0.054) demonstrated that the cT m classification provided more net benefit in the survival prediction compared with the current cT 8 classification. The current cT 8 classification may not be appropriate for part-solid lesions because the presence of GGO components is associated with excellent prognosis despite clinical stage. Also, the cT m classification for part-solid lesions showed an improvement in survival prediction. [ABSTRACT FROM AUTHOR]

The incidence of life-threatening fungal infections has dramatically increased for decades. In order to develop novel antifungal agents, two series of (2 R ,3 R )-1-(1 H -1,2,4-triazol-1-yl)-2-(2,4-difluorophenyl)-3-( N -substitutied)-2-butanols ( 3a-o , 5a-f , 8a-u ), which were analogues of voriconazole, were designed, synthesized and characterized by 1 H NMR, 13 C NMR and HRMS. The MIC 80 values showed that the target compounds 3a-o indicated better activities than fluconazole on three important fungal pathogens except for 3i . Significant activity of compounds 3d , 3k , 3n , 3m and 3o was observed on the Aspergillus fumigatus strain (MIC 80 range: 1–0.125 μg/ml). Especially, compound 3k had strong activity to inhibit the growth of ten fungal pathogens. But it didn't exhibit good activity in in vivo value. Molecular docking experiments demonstrated that 3k possessed superior affinity with target enzyme by strong hydrogen bond from morpholine ring. [ABSTRACT FROM AUTHOR]

A properly designed sensing interface is crucial for the accurate and sensitive detection of biologically active molecules. Single-atom nanozymes from transition metal and nitrogen-doped carbon materials (M-N-C) have caught attention owing to their large surface area and strong bionic enzyme activity. Herein, a three-dimensional layered electrochemical electrode consisting of a Co–N–C nanoenzyme embedded in a reduced graphene oxide aerogel was prepared for the detection of hydrogen peroxide (H 2 O 2), dopamine (DA) and uric acid (UA). Due to its unique three-dimensional layered structure, rGA has excellent electrical conductivity and high material loading and is used to enhance the electrocatalytic performance of Co–N–C. The combination of single-atom nanozymes and electrochemical detection shows unique advantages in catalytic activity and selectivity. The limit of detection and detection range are 0.74 μM and 3–2991 μM respectively for H 2 O 2. Furthermore, it has been successfully implemented for the in-situ detection of H 2 O 2 in living cells. In addition, their simultaneous detection is also realized by the sensors for DA and UA. And it can accurately capture the signal of UA and DA in the urine. Meanwhile, the electrode displays satisfactory stability and repeatability. Therefore, this paper provides a new detection strategy for a variety of bioactive molecules, showing great potential in cell biology, pathophysiology and diagnostics. A novel electrochemical sensor based on single-atom nanozymes Co–N–C for bioactive molecules detection. [Display omitted] • Single-atom nanozymes Co–N–C exhibited peroxidase activity. • Co–N–C/rGA was used to detect H 2 O 2 in living cells, and successfully realized the simultaneous detection of DA and UA. • It provides a new method for the detection of bioactive molecules. [ABSTRACT FROM AUTHOR]