Sulfite-Assisted Acetate Conversion from CO Electroreduction.

The efficient acetate conversion from CO electroreduction is challenging due to the poor selectivity at high reaction rate, which requires the competition with H2 and other C2+ (i. e., ethylene, ethanol, n-propanol) reduction products. Electrolyte engineering is one of the efficient strategies to regulate the reaction microenvironment. In this work, the adding of sulfite (SO3 2-) with high nucleophilicity in KOH electrolytes was demonstrated to enable improving the CO-to-acetate conversion via generating a S-O chemical bond between SO3 2- and oxygenated *C2 intermediates (i. e., *CO-CO, *CO-COH) compared with that in pure KOH system on both synthesized Cu(200)- and normal commercial Cu(111)-facets-exposed metallic Cu catalysts. As a result, the prepared Cu(200)-facets-exposed metallic Cu catalyst with surface ions modification showed an superior Faradaic efficiency of 63.6 % at -0.6 A ⋅ cm-2, and extraordinary absolute value of peak partial current density as high as 1.52 A ⋅ cm-2 with adding SO3 2- in KOH electrolytes, compared to the best reported values in both CO and CO2 electroreduction. Our work suggests an attractive strategy to introduce the oxyanion with high nucleophilicity in electrolytes to regulate the microenvironment for industrial-current-density electrosynthesis of acetate from CO electroreduction.

Facilitating safe and sustained submucosal lift through an endoscopically injectable shear-thinning carboxymethyl starch sodium hydrogel.

Traditional submucosal filling materials frequently show insufficient lifting height and duration during clinical procedures. Here, the anionic polysaccharide polymer sodium carboxymethyl starch and cationic Laponite to prepare a hydrogel with excellent shear-thinning ability through physical cross-linking, so that it can achieve continuous improvement of the mucosal cushion through endoscopic injection. The results showed that the hydrogel (56.54 kPa) had a lower injection pressure compared to MucoUp (68.56 kPa). The height of submucosal lifting height produced by hydrogel was higher than MucoUp, and the height maintenance ability after 2 h was 3.20 times that of MucoUp. At the same time, the hydrogel also showed satisfactory degradability and biosafety, completely degrading within 200 h. The hemolysis rate is as low as 0.76 %, and the cell survival rate > 80 %. Subcutaneous implantation experiments confirmed that the hydrogel showed no obvious systemic toxicity. Animal experiments clearly demonstrated the in vivo feasibility of using hydrogels for submucosal uplift. Furthermore, successful endoscopic submucosal dissection was executed on a live pig stomach, affirming the capacity of hydrogel to safely and effectively facilitate submucosal dissection and mitigate adverse events, such as bleeding. These results indicate that shear-thinning hydrogels have a wide range applications as submucosal injection materials.

Hamstring Strain Injury Risk Factors in Australian Football Change over the Course of the Season.

BACKGROUND/AIM: This study aimed to determine which factors were most predictive of hamstring strain injury (HSI) during different stages of the competition in professional Australian Football. METHODS: Across two competitive seasons, eccentric knee flexor strength and biceps femoris long head architecture of 311 Australian Football players (455 player seasons) were assessed at the start and end of preseason and in the middle of the competitive season. Details of any prospective HSI were collated by medical staff of participating teams. Multiple logistic regression models were built to identify important risk factors for HSI at the different time points across the season. RESULTS: There were 16, 33, and 21 new HSIs reported in preseason, early in-season, and late in-season, respectively, across two competitive seasons. Multivariate logistic regression and recursive feature selection revealed that risk factors were different for preseason, early in-season, and late in-season HSIs. A combination of previous HSI, age, height, and muscle thickness were most associated with preseason injuries (median area under the curve [AUC], 0.83). Pennation angle and fascicle length had the strongest association with early in-season injuries (median AUC, 0.86). None of the input variables were associated with late in-season injuries (median AUC, 0.46). The identification of early in-season HSI and late in-season HSI was not improved by the magnitude of change of data across preseason (median AUC, 0.67). CONCLUSIONS: Risk factors associated with prospective HSI were different across the season in Australian Rules Football, with nonmodifiable factors (previous HSI, age, and height) mostly associated with preseason injuries. Early in-season HSI were associated with modifiable factors, notably biceps femoris long head architectural measures. The prediction of in-season HSI was not improved by assessing the magnitude of change in data across preseason.

Versatile Injectable Carboxymethyl Chitosan Hydrogel for Immediate Hemostasis, Robust Tissue Adhesion Barrier, and Antibacterial Applications.

Iatrogenic ulcers resulting from endoscopic submucosal dissection surgery remain a significant clinical concern due to the risk of uncontrolled bleeding. Herein, we have developed an injectable shear-thinning hydrogel cross-linked through electrostatic interactions and hydrogen bonding. The hydrogel underwent comprehensive characterization, focusing on rheological behavior, injectability, microstructure, film-forming capability, adhesion, swelling behavior, degradation kinetics, antibacterial efficacy, hemostatic performance, and biocompatibility. The incorporation of poly(vinyl alcohol) notably enhanced the internal structural stability and injection pressure, while the Laponite content influenced self-healing ability, modulus, and viscosity. Additionally, the hydrogel exhibited pH sensitivity, appropriate degradation, and swelling rates and displayed favorable film-forming and adhesion properties. Notably, it demonstrated excellent resistance against Escherichia coli and Staphylococcus aureus, highlighting its potential to create an optimal wound environment. In vivo studies further confirmed the hydrogel's exceptional hemostatic performance, positioning it as an optimal material for endoscopic submucosal dissection (ESD) surgery. Moreover, cell experiments and hemolysis tests revealed high biocompatibility, supporting their potential to facilitate the healing of iatrogenic ulcers post-ESD surgery. In conclusion, our hydrogels hold great promise as endoscopic treatment materials for ESD-induced ulcers given their outstanding properties.

Emerging materials and technologies for electrocatalytic seawater splitting.

The limited availability of freshwater in renewable energy-rich areas has led to the exploration of seawater electrolysis for green hydrogen production. However, the complex composition of seawater presents substantial challenges such as electrode corrosion and electrolyzer failure, calling into question the technological and economic feasibility of direct seawater splitting. Despite many efforts, a comprehensive overview and analysis of seawater electrolysis, including electrochemical fundamentals, materials, and technologies of recent breakthroughs, is still lacking. In this review, we systematically examine recent advances in electrocatalytic seawater splitting and critically evaluate the obstacles to optimizing water supply, materials, and devices for stable hydrogen production from seawater. We demonstrate that robust materials and innovative technologies, especially selective catalysts and high-performance devices, are critical for efficient seawater electrolysis. We then outline and discuss future directions that could advance the techno-economic feasibility of this emerging field, providing a roadmap toward the design and commercialization of materials that can enable efficient, cost-effective, and sustainable seawater electrolysis.

Individualized tumor-informed circulating tumor DNA analysis for postoperative monitoring of non-small cell lung cancer.

We report a personalized tumor-informed technology, Patient-specific pROgnostic and Potential tHErapeutic marker Tracking (PROPHET) using deep sequencing of 50 patient-specific variants to detect molecular residual disease (MRD) with a limit of detection of 0.004%. PROPHET and state-of-the-art fixed-panel assays were applied to 760 plasma samples from 181 prospectively enrolled early stage non-small cell lung cancer patients. PROPHET shows higher sensitivity of 45% at baseline with circulating tumor DNA (ctDNA). It outperforms fixed-panel assays in prognostic analysis and demonstrates a median lead-time of 299 days to radiologically confirmed recurrence. Personalized non-canonical variants account for 98.2% with prognostic effects similar to canonical variants. The proposed tumor-node-metastasis-blood (TNMB) classification surpasses TNM staging for prognostic prediction at the decision point of adjuvant treatment. PROPHET shows potential to evaluate the effect of adjuvant therapy and serve as an arbiter of the equivocal radiological diagnosis. These findings highlight the potential advantages of personalized cancer techniques in MRD detection.

Individualized dynamic methylation-based analysis of cell-free DNA in postoperative monitoring of lung cancer.

BACKGROUND: The feasibility of DNA methylation-based assays in detecting minimal residual disease (MRD) and postoperative monitoring remains unestablished. We aim to investigate the dynamic characteristics of cancer-related methylation signals and the feasibility of methylation-based MRD detection in surgical lung cancer patients. METHODS: Matched tumor, tumor-adjacent tissues, and longitudinal blood samples from a cohort (MEDAL) were analyzed by ultra-deep targeted sequencing and bisulfite sequencing. A tumor-informed methylation-based MRD (timMRD) was employed to evaluate the methylation status of each blood sample. Survival analysis was performed in the MEDAL cohort (n = 195) and validated in an independent cohort (DYNAMIC, n = 36). RESULTS: Tumor-informed methylation status enabled an accurate recurrence risk assessment better than the tumor-naïve methylation approach. Baseline timMRD-scores were positively correlated with tumor burden, invasiveness, and the existence and abundance of somatic mutations. Patients with higher timMRD-scores at postoperative time-points demonstrated significantly shorter disease-free survival in the MEDAL cohort (HR: 3.08, 95% CI: 1.48-6.42; P = 0.002) and the independent DYNAMIC cohort (HR: 2.80, 95% CI: 0.96-8.20; P = 0.041). Multivariable regression analysis identified postoperative timMRD-score as an independent prognostic factor for lung cancer. Compared to tumor-informed somatic mutation status, timMRD-scores yielded better performance in identifying the relapsed patients during postoperative follow-up, including subgroups with lower tumor burden like stage I, and was more accurate among relapsed patients with baseline ctDNA-negative status. Comparing to the average lead time of ctDNA mutation, timMRD-score yielded a negative predictive value of 97.2% at 120 days prior to relapse. CONCLUSIONS: The dynamic methylation-based analysis of peripheral blood provides a promising strategy for postoperative cancer surveillance. TRIAL REGISTRATION: This study (MEDAL, MEthylation based Dynamic Analysis for Lung cancer) was registered on ClinicalTrials.gov on 08/05/2018 (NCT03634826). https://clinicaltrials.gov/ct2/show/NCT03634826 .

SF3B1 mutation and ATM deletion codrive leukemogenesis via centromeric R-loop dysregulation.

RNA splicing factor SF3B1 is recurrently mutated in various cancers, particularly in hematologic malignancies. We previously reported that coexpression of Sf3b1 mutation and Atm deletion in B cells, but not either lesion alone, leads to the onset of chronic lymphocytic leukemia (CLL) with CLL cells harboring chromosome amplification. However, the exact role of Sf3b1 mutation and Atm deletion in chromosomal instability (CIN) remains unclear. Here, we demonstrated that SF3B1 mutation promotes centromeric R-loop (cen-R-loop) accumulation, leading to increased chromosome oscillation, impaired chromosome segregation, altered spindle architecture, and aneuploidy, which could be alleviated by removal of cen-R-loop and exaggerated by deletion of ATM. Aberrant splicing of key genes involved in R-loop processing underlay augmentation of cen-R-loop, as overexpression of the normal isoform, but not the altered form, mitigated mitotic stress in SF3B1-mutant cells. Our study identifies a critical role of splice variants in linking RNA splicing dysregulation and CIN and highlights cen-R-loop augmentation as a key mechanism for leukemogenesis.

Acidic CO2-to-HCOOH electrolysis with industrial-level current on phase engineered tin sulfide.

Acidic CO2-to-HCOOH electrolysis represents a sustainable route for value-added CO2 transformations. However, competing hydrogen evolution reaction (HER) in acid remains a great challenge for selective CO2-to-HCOOH production, especially in industrial-level current densities. Main group metal sulfides derived S-doped metals have demonstrated enhanced CO2-to-HCOOH selectivity in alkaline and neutral media by suppressing HER and tuning CO2 reduction intermediates. Yet stabilizing these derived sulfur dopants on metal surfaces at large reductive potentials for industrial-level HCOOH production is still challenging in acidic medium. Herein, we report a phase-engineered tin sulfide pre-catalyst (π-SnS) with uniform rhombic dodecahedron structure that can derive metallic Sn catalyst with stabilized sulfur dopants for selective acidic CO2-to-HCOOH electrolysis at industrial-level current densities. In situ characterizations and theoretical calculations reveal the π-SnS has stronger intrinsic Sn-S binding strength than the conventional phase, facilitating the stabilization of residual sulfur species in the Sn subsurface. These dopants effectively modulate the CO2RR intermediates coverage in acidic medium by enhancing *OCHO intermediate adsorption and weakening *H binding. As a result, the derived catalyst (Sn(S)-H) demonstrates significantly high Faradaic efficiency (92.15 %) and carbon efficiency (36.43 %) to HCOOH at industrial current densities (up to -1 A cm-2) in acidic medium.

CircPVT1 promotes ER-positive breast tumorigenesis and drug resistance by targeting ESR1 and MAVS.

The molecular mechanisms underlying estrogen receptor (ER)-positive breast carcinogenesis and endocrine therapy resistance remain incompletely understood. Here, we report that circPVT1, a circular RNA generated from the lncRNA PVT1, is highly expressed in ERα-positive breast cancer cell lines and tumor samples and is functionally important in promoting ERα-positive breast tumorigenesis and endocrine therapy resistance. CircPVT1 acts as a competing endogenous RNA (ceRNA) to sponge miR-181a-2-3p, promoting the expression of ESR1 and downstream ERα-target genes and breast cancer cell growth. Furthermore, circPVT1 directly interacts with MAVS protein to disrupt the RIGI-MAVS complex formation, inhibiting type I interferon (IFN) signaling pathway and anti-tumor immunity. Anti-sense oligonucleotide (ASO)-targeting circPVT1 inhibits ERα-positive breast cancer cell and tumor growth, re-sensitizing tamoxifen-resistant ERα-positive breast cancer cells to tamoxifen treatment. Taken together, our data demonstrated that circPVT1 can work through both ceRNA and protein scaffolding mechanisms to promote cancer. Thus, circPVT1 may serve as a diagnostic biomarker and therapeutic target for ERα-positive breast cancer in the clinic.

ER-localized JmjC domain-containing protein JMJD8 targets STING to promote immune evasion and tumor growth in breast cancer.

The STING-mediated type I interferon (IFN) signaling pathway has been shown to play critical roles in antitumor immunity. Here, we demonstrate that an endoplasmic reticulum (ER)-localized JmjC domain-containing protein, JMJD8, inhibits STING-induced type I IFN responses to promote immune evasion and breast tumorigenesis. Mechanistically, JMJD8 competes with TBK1 for binding with STING, blocking STING-TBK1 complex formation and restricting type I IFN and IFN-stimulated gene (ISG) expression as well as immune cell infiltration. JMJD8 knockdown improves the efficacy of chemotherapy and immune checkpoint therapy in treating both human and mouse breast cancer cell-derived implanted tumors. The clinical relevance is highlighted in that JMJD8 is highly expressed in human breast tumor samples, and its expression is inversely correlated with that of type I IFN and ISGs as well as immune cell infiltration. Overall, our study found that JMJD8 regulates type I IFN responses, and targeting JMJD8 triggers antitumor immunity.

Simultaneous quantification of 3',4'-dimethoxy flavonol-3-O-glucoside and its major metabolite in human plasma by LC-MS/MS and its application to a clinical pharmacokinetic study.

Hyperlipidemia is a disease characterized by abnormal blood lipid levels and is the leading risk factor for cardiovascular disease. 3',4'-Dimethoxy flavonol-3-O-glucoside (abbreviated DF3G) is a new lipid-lowering drug created as a flavonoid structural analog. The principal metabolite of DF3G in human plasma is the aglycone glucuronide conjugate M2. The purpose of this study is to use liquid chromatography-tandem mass spectrometry to develop and validate a quantitative analysis method for DF3G and its metabolite M2 in human plasma, and to use the method to investigate the pharmacokinetics of DF3G and M2 in a clinical trial. This method employed DF3G-d6 as the internal standard, and plasma samples were processed by protein precipitation. Isocratic separation could accurately differentiate DF3G, M2, and DF3G-d6 from endogenous components in the matrix or other components in the samples, and endogenous components in the matrix had little impact on ionization efficiency. Positive electrospray ionization with multiple reaction monitoring (MRM) transitions of m/z 461.2 → 299.0 for DF3G, m/z 475.1 → 299.1 for M2 and m/z 467.1 → 305.1 for DF3G-d6 was used for quantification. The DF3G and M2 linear range for plasma were in the range of 4.00/4.00 ng/mL to 4000/4000 ng/mL. Both the analytes and the internal standard were stable regardless of whether they were in solution or plasma samples. The accuracy of the average concentration of the quality control samples was within 15% of the theoretical value, and the RSD was less than 15%. The method is rapid, accurate, straightforward, and precise. It is appropriate for the determination of DF3G and M2 concentrations in human plasma and has been successfully applied to determine the pharmacokinetic analysis in phase I clinical trials.

Potential clinical utility of liquid biopsy in early-stage non-small cell lung cancer.

BACKGROUND: Liquid biopsy has been widely researched for early diagnosis, prognostication and disease monitoring in lung cancer, but there is a need to investigate its clinical utility for early-stage non-small cell lung cancer (NSCLC). METHODS: We performed a meta-analysis and systematic review to evaluate diagnostic and prognostic values of liquid biopsy for early-stage NSCLC, regarding the common biomarkers, circulating tumor cells, circulating tumor DNA (ctDNA), methylation signatures, and microRNAs. Cochrane Library, PubMed, EMBASE databases, ClinicalTrials.gov, and reference lists were searched for eligible studies since inception to 17 May 2022. Sensitivity, specificity and area under the curve (AUC) were assessed for diagnostic values. Hazard ratio (HR) with a 95% confidence interval (CI) was extracted from the recurrence-free survival (RFS) and overall survival (OS) plots for prognostic analysis. Also, potential predictive values and treatment response evaluation were further investigated. RESULTS: In this meta-analysis, there were 34 studies eligible for diagnostic assessment and 21 for prognostic analysis. The estimated diagnostic values of biomarkers for early-stage NSCLC with AUCs ranged from 0.84 to 0.87. The factors TNM stage I, T1 stage, N0 stage, adenocarcinoma, young age, and nonsmoking contributed to a lower tumor burden, with a median cell-free DNA concentration of 8.64 ng/ml. For prognostic analysis, the presence of molecular residual disease (MRD) detection was a strong predictor of disease relapse (RFS, HR, 4.95; 95% CI, 3.06-8.02; p < 0.001) and inferior OS (HR, 3.93; 95% CI, 1.97-7.83; p < 0.001), with average lead time of 179 ± 74 days between molecular recurrence and radiographic progression. Predictive values analysis showed adjuvant therapy significantly benefited the RFS of MRD + patients (HR, 0.27; p < 0.001), while an opposite tendency was detected for MRD - patients (HR, 1.51; p = 0.19). For treatment response evaluation, a strong correlation between pathological response and ctDNA clearance was detected, and both were associated with longer survival after neoadjuvant therapy. CONCLUSIONS: In conclusion, our study indicated liquid biopsy could reliably facilitate more precision and effective management of early-stage NSCLC. Improvement of liquid biopsy techniques and detection approaches and platforms is still needed, and higher-quality trials are required to provide more rigorous evidence prior to their routine clinical application.

Research Progress on Postoperative Minimal/Molecular Residual Disease Detection in Lung Cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide. Approximately 10%-50% of patients experience relapse after radical surgery, which may be attributed to the persistence of minimal/molecular residual disease (MRD). Circulating tumor DNA (ctDNA), a common liquid biopsy approach, has been demonstrated to have significant clinical merit. In this study, we review the evidence supporting the use of ctDNA for MRD detection and discuss the potential clinical applications of postoperative MRD detection, including monitoring recurrence, guiding adjuvant treatment, and driving clinical trials in lung cancer. We will also discuss the problems that prevent the routine application of ctDNA MRD detection. Multi-analyte methods and identification of specific genetic and molecular alterations, especially methylation, are effective detection strategies and show considerable prospects for future development. Interventional prospective studies based on ctDNA detection are needed to determine whether the application of postoperative MRD detection can improve the clinical outcomes of lung cancer patients, and the accuracy, sensitivity, specificity, and robustness of different detection methods still require optimization and refinement.

Spatiotemporal genomic analysis reveals distinct molecular features in recurrent stage I non-small cell lung cancers.

Stage I non-small cell lung cancer (NSCLC) presents diverse outcomes. To identify molecular features leading to tumor recurrence in early-stage NSCLC, we perform multiregional whole-exome sequencing (WES), RNA sequencing, and plasma-targeted circulating tumor DNA (ctDNA) detection analysis between recurrent and recurrent-free stage I NSCLC patients (CHN-P cohort) who had undergone R0 resection with a median 5-year follow-up time. Integrated analysis indicates that the multidimensional clinical and genomic model can stratify the prognosis of stage I NSCLC in both CHN-P and EUR-T cohorts and correlates with positive pre-surgical deep next generation sequencing (NGS) ctDNA detection. Increased genomic instability related to DNA interstrand crosslinks and double-strand break repair processes is significantly associated with early tumor relapse. This study reveals important molecular insights into stage I NSCLC and may inform clinical postoperative treatment and follow-up strategies.

Quantitative Analysis of Broken Rotor Bars in Cage Motor Based on Energy Characteristics of Vibration Signals.

The rotor, as the power output device of a cage motor, is subject to a type of invisible fault, BRB, during long-term use. The conventional motor vibration signal fault monitoring system only analyzes the rotor qualitatively for the fault of BRBs and cannot evaluate the fault degree of BRBs quantitatively. Moreover, the vibration signal used for monitoring has nonstationary and nonlinear characteristics. It is necessary to manually determine the time window and basis function when extracting the characteristics of the time-frequency domain. To address these problems, this paper proposes a method for quantitative analysis of BRBs based on CEEMD decomposition and weight transformation for feature extraction and then uses the AdaBoost to construct a classifier. The method applies CEEMD for adaptive decomposition while extracting IMFs' energy as the initial feature values, uses OOB for contribution evaluation of features to construct weight vectors, and performs a spatial transformation on the original feature values to expand the differences between the feature vectors. To verify the effectiveness and superiority of the method, vibration signals were collected from motors in four BRB states to produce rotor fault data sets in this paper. The experiment results show that the feature extraction method based on CEEMD decomposition and weight transformation can better extract the feature vectors from the vibration signals, and the constructed classifier can accurately perform quantitative analysis of BRB fault.

Comprehensive Analysis of Clinical Logistic and Machine Learning-Based Models for the Evaluation of Pulmonary Nodules.

Introduction: Over the years, multiple models have been developed for the evaluation of pulmonary nodules (PNs). This study aimed to comprehensively investigate clinical models for estimating the malignancy probability in patients with PNs. Methods: PubMed, EMBASE, Cochrane Library, and Web of Science were searched for studies reporting mathematical models for PN evaluation until March 2020. Eligible models were summarized, and network meta-analysis was performed on externally validated models (PROSPERO database CRD42020154731). The cut-off value of 40% was used to separate patients into high prevalence (HP) and low prevalence (LP), and a subgroup analysis was performed. Results: A total of 23 original models were proposed in 42 included articles. Age and nodule size were most often used in the models, whereas results of positron emission tomography-computed tomography were used when collected. The Mayo model was validated in 28 studies. The area under the curve values of four most often used models (PKU, Brock, Mayo, VA) were 0.830, 0.785, 0.743, and 0.750, respectively. High-prevalence group (HP) models had better results in HP patients with a pooled sensitivity and specificity of 0.83 (95% confidence interval [CI]: 0.78-0.88) and 0.71 (95% CI: 0.71-0.79), whereas LP models only achieved pooled sensitivity and specificity of 0.70 (95% CI: 0.60-0.79) and 0.70 (95% CI: 0.62-0.77). For LP patients, the pooled sensitivity and specificity decreased from 0.68 (95% CI: 0.57-0.78) and 0.93 (95% CI: 0.87-0.97) to 0.57 (95% CI: 0.21-0.88) and 0.82 (95% CI: 0.65-0.92) when the model changed from LP to HP models. Compared with the clinical models, artificial intelligence-based models have promising preliminary results. Conclusions: Mathematical models can facilitate the evaluation of lung nodules. Nevertheless, suitable model should be used on appropriate cohorts to achieve an accurate result.

CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification.

Convolutional neural networks (CNNs) have gained significant popularity in orthopedic imaging in recent years due to their ability to solve fracture classification problems. A common criticism of CNNs is their opaque learning and reasoning process, making it difficult to trust machine diagnosis and the subsequent adoption of such algorithms in clinical setting. This is especially true when the CNN is trained with limited amount of medical data, which is a common issue as curating sufficiently large amount of annotated medical imaging data is a long and costly process. While interest has been devoted to explaining CNN learnt knowledge by visualizing network attention, the utilization of the visualized attention to improve network learning has been rarely investigated. This paper explores the effectiveness of regularizing CNN network with human-provided attention guidance on where in the image the network should look for answering clues. On two orthopedics radiographic fracture classification datasets, through extensive experiments we demonstrate that explicit human-guided attention indeed can direct correct network attention and consequently significantly improve classification performance. The development code for the proposed attention guidance is publicly available on https://github.com/zhibinliao89/fracture_attention_guidance.

Comparison of Clinical and Pathological Characteristics Between Extremely Multiple GGNs and Single GGNs.

OBJECTIVE: This study aims to compare the clinical and pathological characteristics between patients undergoing surgery for extremely multiple ground-glass nodules (GGNs) and those for single GGN. METHODS: We defined extremely multiple GGNs as follows: (i) number of GGNs ≥3, (ii) GGN diameter between 3 and 30 mm, and (iii) no less than three nodules that were surgically removed and pathologically diagnosed. Patients with extremely multiple GGNs and single GGNs who underwent surgery at the same time were retrospectively analyzed. The patients were divided into three groups according to the number of nodules: exceedingly multiple nodules (EMN) group (>10), highly multiple nodules (HMN) group (three to 10), and single nodule (SN) group. The clinical and pathological characteristics, surgical methods and prognosis were analyzed. RESULTS: Ninety-nine patients with single nodules and 102 patients with extremely multiple nodules were enrolled. Among the patients with extremely multiple nodules, 43 (42.2%) had >10 nodules. There were no significant differences in demographic characteristics, such as age, sex, and smoking history, between the groups, but there were differences in tumor characteristics. All patients with >10 nodules showed bilateral pulmonary nodules and presented with both pure and mixed GGNs. The single GGNs were smaller in diameter, and the proportion of mixed GGNs and pathologically invasive adenocarcinoma was lower than that of the primary nodules in the exceedingly multiple GGNs group (p < 0.05). However, the proportion of both mixed GGNs and malignant nodules decreased significantly with the increasing number of total lesions. During postoperative follow-up, one patient in the highly multiple nodules group had a local recurrence, and 16 (15.7%) patients in the extremely multiple GGNs group and 10 (9.8%) patients in the single GGN group had enlarged unresected GGNs or additional GGNs. CONCLUSIONS: Our study revealed the clinical and pathologic characteristics, surgical methods, and prognosis of patients with extremely multiple GGNs and compared them with those of patients with a single GGN. Although the primary nodules in extremely multiple GGNs may have higher malignancy than those in the single nodule group, the proportion of both mGGNs and malignant nodules decreased significantly with the increasing number of lesions, and the prognosis of patients with extremely multiple GGNs was satisfied.