On the Robustness of Average Losses for Partial-Label Learning

Partial-label learning (PLL) utilizes instances with PLs, where a PL includes several candidate labels but only one is the true label (TL). In PLL, identification-based strategy (IBS) purifies each PL on the fly to select the (most likely) TL for training; average-based strategy (ABS) treats all candidate labels equally for training and let trained models be able to predict TL. Although PLL research has focused on IBS for better performance, ABS is also worthy of study since modern IBS behaves like ABS in the beginning of training to prepare for PL purification and TL selection. In this paper, we analyze why ABS was unsatisfactory and propose how to improve it. Theoretically, we propose two problem settings of PLL and prove that average PL losses (APLLs) with bounded multi-class losses are always robust, while APLLs with unbounded losses may be non-robust, which is the first robustness analysis for PLL. Experimentally, we have two promising findings: ABS using bounded losses can match/exceed state-of-the-art performance of IBS using unbounded losses; after using robust APLLs to warm start, IBS can further improve upon itself. Our work draws attention to ABS research, which can in turn boost IBS and push forward the whole PLL.

PiCO+: Contrastive Label Disambiguation for Robust Partial Label Learning

Partial label learning (PLL) is an important problem that allows each training example to be labeled with a coarse candidate set with the ground-truth label included. However, in a more practical but challenging scenario, the annotator may miss the ground-truth and provide a wrong candidate set, which is known as the noisy PLL problem. To remedy this problem, we propose the PiCO+ framework that simultaneously disambiguates the candidate sets and mitigates label noise. Core to PiCO+, we develop a novel label disambiguation algorithm PiCO that consists of a contrastive learning module along with a novel class prototype-based disambiguation method. Theoretically, we show that these two components are mutually beneficial, and can be rigorously justified from an expectation-maximization (EM) algorithm perspective. To handle label noise, we extend PiCO to PiCO+, which further performs distance-based clean sample selection, and learns robust classifiers by a semi-supervised contrastive learning algorithm. Beyond this, we further investigate the robustness of PiCO+ in the context of out-of-distribution noise and incorporate a novel energy-based rejection method for improved robustness. Extensive experiments demonstrate that our proposed methods significantly outperform the current state-of-the-art approaches in standard and noisy PLL tasks and even achieve comparable results to fully supervised learning.

Advances in Understanding Fusarium graminearum: Genes Involved in the Regulation of Sexual Development, Pathogenesis, and Deoxynivalenol Biosynthesis

The wheat head blight disease caused by Fusarium graminearum is a major concern for food security and the health of both humans and animals. As a pathogenic microorganism, F. graminearum produces virulence factors during infection to increase pathogenicity, including various macromolecular and small molecular compounds. Among these virulence factors, secreted proteins and deoxynivalenol (DON) are important weapons for the expansion and colonization of F. graminearum. Besides the presence of virulence factors, sexual reproduction is also crucial for the infection process of F. graminearum and is indispensable for the emergence and spread of wheat head blight. Over the last ten years, there have been notable breakthroughs in researching the virulence factors and sexual reproduction of F. graminearum. This review aims to analyze the research progress of sexual reproduction, secreted proteins, and DON of F. graminearum, emphasizing the regulation of sexual reproduction and DON synthesis. We also discuss the application of new gene engineering technologies in the prevention and control of wheat head blight.

CD206 modulates the role of M2 macrophages in the origin of metastatic tumors

Tumor metastasis is a key factor affecting the life of patients with malignant tumors. For the past hundred years, scientists have focused on how to kill cancer cells and inhibit their metastasis in vivo, but few breakthroughs have been made. Here we hypothesized a novel mode for cancer metastasis. We show that the phagocytosis of apoptotic tumor cells by macrophages leads to their polarization into the M2 phenotype, and that the expression of stem cell related as well as drug resistance related genes was induced. Therefore, it appears that M2 macrophages have "defected" and have been transformed into the initial "metastatic cancer cells", and thus are the source, at least in part, of the distal tissue tumor metastasis. This assumption is supported by the presence of fused cells with characteristics of both macrophage and tumor cell observed in the peripheral blood and ascites of patients with ovarian cancer. By eliminating the expression of CD206 in M2 macrophages using siRNA, we show that the growth and metastasis of tumors was suppressed using both in vitro cell line and with experimental in vivo mouse models. In summary, we show that M2 macrophages in the blood circulation underwent a "change of loyalty" to become "cancer cells" that transformed into distal tissue metastasis, which could be suppressed by the knockdown of CD206 expression.

A 3-year follow-up clinical study on the preservation for vitality of involved tooth in jaw cysts through an innovative method

Jaw cysts commonly affect the oral and maxillofacial region, involving adjacent tooth roots. The management of these teeth, particularly regarding root canal therapy and apicoectomy, lacks consensus. This study introduces a novel treatment concept and refined surgical approach to preserve pulp viability in teeth involved in jaw cysts. The objective was to investigate the effectiveness and potential benefits of this approach over a 36-month follow-up period. A conservative management approach prioritized vitality preservation, reserving root canal treatment and apicectomy for cases with post-operative discomfort. A comprehensive follow-up of 108 involved teeth from 36 jaw cyst cases treated with the modified method was conducted. Clinical observation, X-ray imaging, cone-beam computed tomography (CBCT), and pulp vitality testing assessed changes in cyst size, tooth color, pulp vitality, root structure, and surrounding alveolar bone. After 36 months, our modified surgical approach successfully preserved tooth vitality in 84 involved teeth. Adverse symptoms in 19 teeth, such as redness, swelling, fistula, and pain, resolved with postoperative root canal therapy. Follow-up was lost for five teeth in two cases. No cyst recurrences were observed, and in 34 cases, the bone cavity gradually disappeared, restoring normal bone density during long-term follow-up. Our modified surgical method effectively preserves tooth vitality in jaw cysts. This innovative approach has the potential to improve the management of teeth involved in jaw cysts.

RPTOR blockade suppresses brain metastases of NSCLC by interfering the ceramide metabolism via hijacking YY1 binding

BACKGROUND

Ceramide metabolism is crucial in the progress of brain metastasis (BM). However, it remains unexplored whether targeting ceramide metabolism may arrest BM.

METHODS

RNA sequencing was applied to screen different genes in primary and metastatic foci and whole-exome sequencing (WES) to seek crucial abnormal pathway in BM + and BM-patients. Cellular arrays were applied to analyze the permeability of blood-brain barrier (BBB) and the activation or inhibition of pathway. Database and Co-Immunoprecipitation (Co-IP) assay were adopted to verify the protein-protein interaction. Xenograft and zebrafish model were further employed to verify the cellular results.

RESULTS

RNA sequencing and WES reported the involvement of RPTOR and ceramide metabolism in BM progress. RPTOR was significantly upregulated in BM foci and increased the permeability of BBB, while RPTOR deficiency attenuated the cell invasiveness and protected extracellular matrix. Exogenous RPTOR boosted the SPHK2/S1P/STAT3 cascades by binding YY1, in which YY1 bound to the regions of SPHK2 promoter (at -353 ~ -365 nt), further promoting the expression of SPHK2. The latter was rescued by YY1 RNAi. Xenograft and zebrafish model showed that RPTOR blockade suppressed BM of non-small cell lung cancer (NSCLC) and impaired the SPHK2/S1P/STAT3 pathway.

CONCLUSION

RPTOR is a key driver gene in the brain metastasis of lung cancer, which signifies that RPTOR blockade may serve as a promising therapeutic candidate for clinical application.

Achieving 2.2 GPa Ultra-High Strength in Low-Alloy Steel Using a Direct Quenching and Partitioning Process

Advanced high-strength steels (AHSS) have a wide range of applications in equipment safety and lightweight design, and enhancing the strength of AHSS to the ultra-high level of 2 GPa is currently a key focus. In this study, a new process of thermo-mechanical control process followed by direct quenching and partitioning (TMCP-DQP) was developed based on Fe-0.4C-1Mn-0.6Si (wt.%) low-alloy steel, and the effects of microstructure evolution on mechanical properties under TMCP-DQP process and conventional hot rolled quenched and tempered process (HR-QT) were comparatively studied. The results show that the TMCP-DQP process not only shortened the processing steps but also achieved outstanding comprehensive mechanical properties. The TMCP-DQP steel exhibited a tensile strength of 2.23 GPa, accompanied by 11.9% elongation and a Brinell hardness of 624 HBW, with an impact toughness of 28.5 J at -20 °C. In contrast, the HR-QT steel exhibited tensile strengths ranging from 2.16 GPa to 1.7 GPa and elongations between 5.2% and 12.2%. The microstructure of TMCP-DQP steel primarily consisted of lath martensite, containing thin-film retained austenite (RA), nanoscale rod-shaped carbides, and a minor number of nanoscale twins. The volume fraction of RA reached 7.7%, with an average carbon content of 7.1 at.% measured by three-dimensional atom probe tomography (3DAP). Compared with the HR-QT process, the TMCP-DQP process resulted in a finer microstructure, with a prior austenite grain (PAG) size of 11.91 μm, forming packets and blocks with widths of 5.12 μm and 1.63 μm. The TMCP-DQP process achieved the ultra-high strength of low-alloy steel through the synergistic effects of grain refinement, dislocation strengthening, and precipitation strengthening. The dynamic partitioning stage stabilized the RA through carbon enrichment, while the relaxation stage reduced a small portion of the dislocations generated by thermal deformation, and the self-tempering stage eliminated internal stresses, all guaranteeing considerable ductility and toughness. The TMCP-DQP process may offer a means for industries to streamline their manufacturing processes and provide a technological reference for producing 2.2 GPa grade AHSS.

A Parametrical Model for Instance-Dependent Label Noise

In label-noise learning, estimating the transition matrix is a hot topic as the matrix plays an important role in building statistically consistent classifiers. Traditionally, the transition from clean labels to noisy labels (i.e., clean-label transition matrix (CLTM)) has been widely exploited on class-dependent label-noise (wherein all samples in a clean class share the same label transition matrix). However, the CLTM cannot handle the more common instance-dependent label-noise well (wherein the clean-to-noisy label transition matrix needs to be estimated at the instance level by considering the input quality). Motivated by the fact that classifiers mostly output Bayes optimal labels for prediction, in this paper, we study to directly model the transition from Bayes optimal labels to noisy labels (i.e., Bayes-Label Transition Matrix (BLTM)) and learn a classifier to predict Bayes optimal labels. Note that given only noisy data, it is ill-posed to estimate either the CLTM or the BLTM. But favorably, Bayes optimal labels have no uncertainty compared with the clean labels, i.e., the class posteriors of Bayes optimal labels are one-hot vectors while those of clean labels are not. This enables two advantages to estimate the BLTM, i.e., (a) a set of examples with theoretically guaranteed Bayes optimal labels can be collected out of noisy data; (b) the feasible solution space is much smaller. By exploiting the advantages, this work proposes a parametrical model for estimating the instance-dependent label-noise transition matrix by employing a deep neural network, leading to better generalization and superior classification performance.

Improving Bond Strength of Translucent Zirconia Through Surface Treatment With SiO2-ZrO2 Coatings

BACKGROUND

Translucent monolithic zirconia ceramics have been applied in dental clinics due to their esthetic translucent formulations and mechanical properties. Considering inherent ceramic brittleness, adhesive bonding with resin composite increases the fracture resistance of ceramic restorations. However, zirconia is a chemically stable material that is difficult to adhesively bond with resin.

OBJECTIVES

To investigate the influences of SiO2-ZrO2 coatings on adhesive bonding of zirconia and the surface characterization of those coatings.

METHODS AND MATERIALS

Translucent zirconia discs were classified into groups based on surface treatments: CT (control), SB (sandblasting), C21(SiO2:ZrO2=2:1), C11(SiO2:ZrO2=1:1), and C12 (SiO2:ZrO2=1:2) (n=10). Surface characterization of coatings on zirconia were analyzed by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), surface roughness assessment (Ra), X-ray diffraction (XRD), water contact angle (WCA), translucency parameter (TP), and shear bond strength (SBS). Two-way ANOVA for shear bond strength results and ANOVA for Ra and WCA were performed.

RESULTS

SEM images revealed SiO2 islands on zirconia disks coated with SiO2-ZrO2. Surface roughness of C12, C11, and C21 groups was significantly larger than those of groups SB and CT (p<0.05). XRD results showed that phase transformation of zirconia disks was detected only in the SB group. In addition, SiO2-ZrO2 coatings reduced WCA. The translucency decreased only in group C21. Group C11 showed the highest shear bond strength under both aging conditions.

CONCLUSION

SiO2-ZrO2 coating is a promising method to enhance the adhesive resin bonding of translucent zirconia without causing phase transformation of translucent zirconia.

Learning Intention-Aware Policies in Deep Reinforcement Learning

Deep reinforcement learning (DRL) provides an agent with an optimal policy so as to maximize the cumulative rewards. The policy defined in DRL mainly depends on the state, historical memory, and policy model parameters. However, we humans usually take actions according to our own intentions, such as moving fast or slow, besides the elements included in the traditional policy models. In order to make the action-choosing mechanism more similar to humans and make the agent to select actions that incorporate intentions, we propose an intention-aware policy learning method in this letter To formalize this process, we first define an intention-aware policy by incorporating the intention information into the policy model, which is learned by maximizing the cumulative rewards with the mutual information (MI) between the intention and the action. Then we derive an approximation of the MI objective that can be optimized efficiently. Finally, we demonstrate the effectiveness of the intention-aware policy in the classical MuJoCo control task and the multigoal continuous chain walking task.

Comprehensive nomogram models for predicting checkpoint inhibitor pneumonitis

Checkpoint inhibitor pneumonitis (CIP) is a common type of immune-related adverse events (irAEs) with poor clinical prognosis. Currently, there is a lack of effective biomarkers and predictive models to predict the occurrence of CIP. This study retrospectively enrolled 547 patients who received immunotherapy. The patients were divided into CIP cohorts of any grade, or grade ≥2 or ≥3. Multivariate logistic regression analysis was used to determine the independent risk factors, based on which we established Nomogram A and B for respectively predicting any grade or grade ≥2 CIP. For Nomogram A to predict any grade CIP, the C indexes in the training and validation cohorts were 0.827 (95% CI=0.772-0.881) and 0.860 (95% CI=0.741-0.918), respectively. Similarly, for Nomogram B to predict grade 2 or higher CIP, the C indexes of the training and validation cohorts were 0.873 (95% CI=0.826-0.921) and 0.904 (95% CI=0.804-0.973), respectively. In conclusion, the predictive power of nomograms A and B has proven satisfactory following internal and external verification. They are promising clinical tools that are convenient, visual, and personalized for assessing the risks of developing CIP.

On the Effectiveness of Adversarial Training Against Backdoor Attacks

Although adversarial training (AT) is regarded as a potential defense against backdoor attacks, AT and its variants have only yielded unsatisfactory results or have even inversely strengthened backdoor attacks. The large discrepancy between expectations and reality motivates us to thoroughly evaluate the effectiveness of AT against backdoor attacks across various settings for AT and backdoor attacks. We find that the type and budget of perturbations used in AT are important, and AT with common perturbations is only effective for certain backdoor trigger patterns. Based on these empirical findings, we present some practical suggestions for backdoor defense, including relaxed adversarial perturbation and composite AT. This work not only boosts our confidence in AT's ability to defend against backdoor attacks but also provides some important insights for future research.

Patients without Increased Lymphocyte Counts and Decreased CT Scores During the Early 2nd Week of Illness Onset may Develop to Severe COVID-19

BACKGROUND

Lymphopenia and high CT score is associated with COVID-19 severity. Herein we describe the change pattern in lymphocyte count and CT score during hospitalization and explore a possible association with the severity of COVID-19.

METHODS

In this retrospective study, 13 non-severe COVID-19 patients diagnosed at admission were enrolled. One patient progressed to severe disease. Change patterns in lymphocyte counts and CT scores of all patients were analyzed.

RESULTS

Lymphocyte count increased gradually from day 5 post-illness onset (day 5 vs. day 15, p = 0.001). Lymphocyte count of the severe patient fluctuated at low levels throughout the 15-day period. Chest CT scores of non-severe patients increased significantly during the first 5 days of illness onset, but decreased gradually beginning day 9 (illness onset vs. day 5, p = 0.002, day 9 vs. day 15, p = 0.015). In the severe patient, CT score continued to increase over the 11 days post-illness onset period.

CONCLUSIONS

Non-severe COVID-19 patients had significantly increased lymphocyte counts and decreased CT scores beginning day 5 and day 9 of illness onset, respectively. The patients without increased lymphocyte counts and decreased CT scores during the early 2nd week of illness onset may develop to severe COVID-19.

FDA Approval Summary: Lutetium Lu 177 Vipivotide Tetraxetan for Patients with Metastatic Castration-Resistant Prostate Cancer

On March 23, 2022, the FDA approved Pluvicto (lutetium Lu 177 vipivotide tetraxetan, also known as 177Lu-PSMA-617) for the treatment of adult patients with prostate-specific membrane antigen (PSMA)-positive metastatic castration-resistant prostate cancer (mCRPC) who have been treated with androgen receptor pathway inhibition and taxane-based chemotherapy. The recommended 177Lu-PSMA-617 dose is 7.4 gigabecquerels (GBq; 200 mCi) intravenously every 6 weeks for up to six doses, or until disease progression or unacceptable toxicity. The FDA granted traditional approval based on VISION (NCT03511664), which was a randomized (2:1), multicenter, open-label trial that assessed the efficacy and safety of 177Lu-PSMA-617 plus best standard of care (BSoC; n = 551) or BSoC alone (n = 280) in men with progressive, PSMA-positive mCRPC. Patients were required to have received ≥1 androgen receptor pathway inhibitor, and one or two prior taxane-based chemotherapy regimens. There was a statistically significant and clinically meaningful improvement in overall survival (OS), with a median OS of 15.3 months in the 177Lu-PSMA-617 plus BSoC arm and 11.3 months in the BSoC arm, respectively (HR: 0.62; 95% confidence interval: 0.52-0.74; P < 0.001). The most common adverse reactions (≥20%) occurring at a higher incidence in patients receiving 177Lu-PSMA-617 were fatigue, dry mouth, nausea, anemia, decreased appetite, and constipation. The most common laboratory abnormalities that worsened from baseline in ≥30% of patients receiving 177Lu-PSMA-617 were decreased lymphocytes, decreased hemoglobin, decreased leukocytes, decreased platelets, decreased calcium, and decreased sodium. This article summarizes the FDA review of data supporting traditional approval of 177Lu-PSMA-617 for this indication.

Class-Wise Denoising for Robust Learning Under Label Noise

Label noise is ubiquitous in many real-world scenarios which often misleads training algorithm and brings about the degraded classification performance. Therefore, many approaches have been proposed to correct the loss function given corrupted labels to combat such label noise. Among them, a trend of works achieve this goal by unbiasedly estimating the data centroid, which plays an important role in constructing an unbiased risk estimator for minimization. However, they usually handle the noisy labels in different classes all at once, so the local information inherited by each class is ignored which often leads to unsatisfactory performance. To address this defect, this paper presents a novel robust learning algorithm dubbed "Class-Wise Denoising" (CWD), which tackles the noisy labels in a class-wise way to ease the entire noise correction task. Specifically, two virtual auxiliary sets are respectively constructed by presuming that the positive and negative labels in the training set are clean, so the original false-negative labels and false-positive ones are tackled separately. As a result, an improved centroid estimator can be designed which helps to yield more accurate risk estimator. Theoretically, we prove that: 1) the variance in centroid estimation can often be reduced by our CWD when compared with existing methods with unbiased centroid estimator; and 2) the performance of CWD trained on the noisy set will converge to that of the optimal classifier trained on the clean set with a convergence rate [Formula: see text] where n is the number of the training examples. These sound theoretical properties critically enable our CWD to produce the improved classification performance under label noise, which is also demonstrated by the comparisons with ten representative state-of-the-art methods on a variety of benchmark datasets.

Effects of Charge Trapping on Memory Characteristics for HfO2-Based Ferroelectric Field Effect Transistors

A full understanding of the impact of charge trapping on the memory window (MW) of HfO₂-based ferroelectric field effect transistors (FeFETs) will permit the design of program and erase protocols, which will guide the application of these devices and maximize their useful life. The effects of charge trapping have been studied by changing the parameters of the applied program and erase pulses in a test sequence. With increasing the pulse amplitude and pulse width, the MW increases first and then decreases, a result attributed to the competition between charge trapping (CT) and ferroelectric switching (FS). This interaction between CT and FS is analyzed in detail using a single-pulse technique. In addition, the experimental data show that the conductance modulation characteristics are affected by the CT in the analog synaptic behavior of the FeFET. Finally, a theoretical investigation is performed in Sentaurus TCAD, providing a plausible explanation of the CT effect on the memory characteristics of the FeFET. This work is helpful to the study of the endurance fatigue process caused by the CT effect and to optimizing the analog synaptic behavior of the FeFET.

Dynamic contrast-enhanced MRI perfusion parameters are imaging biomarkers for angiogenesis in lung cancer

BACKGROUND

Quantitative parameters of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) may have the potential to reflect angiogenesis and proliferation of pulmonary neoplasms.

PURPOSE

To verify whether DCE-MRI can identify pulmonary neoplasm property and evaluate the correlation of DCE-MRI perfusion parameters with microvessel density (MVD) and Ki-67 in lung cancer.

MATERIAL AND METHODS

This study enrolled 65 patients with one pulmonary neoplasm who underwent computed tomography-guided percutaneous lung biopsy with pathological diagnosis (43 malignant, 22 benign; mean age = 59.71 ± 11.72 years). All patients did DCE-MRI before biopsy. Quantitative MRI parameters including endothelial transfer constant (K^trans), flux rate constant (K_ep), and fractional extravascular extracellular space (EES) volume (V_e) were calculated by extended Tofts linear model. MVD was evaluated by CD34-expressing tumor vessels. Proliferation was assessed by Ki-67 staining. The correlations of parameters with MVD and Ki-67 expression were analyzed.

RESULTS

K^trans and K_ep values were significantly increased in malignant lesions compared to benign lesions (P = 0.001 and 0.022, respectively), whereas no statistical difference in V_e was found. The CD34 expression was positively correlated to K^trans (r = 0.608; P = 0.004) and K_ep (r = 0.556; P = 0.001). Subsequent subtype analyses also showed positive correlations of K^trans and K_ep with MVD in adenocarcinoma group (r = 0.550 and 0.563; P = 0.012 and 0.015, respectively). No significant correlation was found between these parameters and Ki-67.

CONCLUSION

K^trans and K_ep may distinguish benign and malignant pulmonary neoplasm. K^trans and K_ep, with their positive correlation to MVD, can be used as non-invasive parameters reflecting lung cancer angiogenesis.

Multiwavelength High-Detectivity MoS2 Photodetectors with Schottky Contacts

Photodetection is one of the vital functions for the multifunctional "More than Moore" (MtM) microchips urgently required by Internet of Things (IoT) and artificial intelligence (AI) applications. The further improvement of the performance of photodetectors faces various challenges, including materials, fabrication processes, and device structures. We demonstrate in this work MoS₂ photodetectors with a nanoscale channel length and a back-gate device structure. With the mechanically exfoliated six-monolayer-thick MoS₂, a Schottky contact between source/drain electrodes and MoS₂, a high responsivity of 4.1 × 10³ A W^-1, and a detectivity of 1.34 × 10¹³ cm Hz^1/2 W^-1 at 650 nm were achieved. The devices are also sensitive to multiwavelength lights, including 520 and 405 nm. The electrical and optoelectronic properties of the MoS₂ photodetectors were studied in depth, and the working mechanism of the devices was analyzed. The photoinduced Schottky barrier lowering (PIBL) was found to be important for the high performance of the phototransistor.

Eosinophil as a biomarker for diagnosis, prediction, and prognosis evaluation of severe checkpoint inhibitor pneumonitis

Introduction

Checkpoint inhibitor pneumonitis (CIP) is a common serious adverse event caused by immune checkpoint inhibitors (ICIs), and severe CIP can be life-threatening. We aimed to investigate the role of peripheral blood cells in diagnosis, prediction, and prognosis evaluation for all and severe CIP.

Materials and methods

Patients with lung cancer receiving ICIs were enrolled in this retrospective study. Baseline was defined as the time of ICI initiation, endpoint was defined as the time of clinical diagnosis of CIP or the last ICI treatment, and follow-up point was defined as 1 week after CIP. Eosinophil percentages at baseline, endpoint, and follow-up point were shortened to “E_bas”, “E_end and “E_fol”, respectively.

Results

Among 430 patients included, the incidence of CIP was 15.6%, and severe CIP was 3.7%. The E_end/E_bas value was lower in patients with CIP (p = 0.001), especially severe CIP (p = 0.036). Receiver operating characteristic curves revealed that E_end/E_bas could serve as a biomarker to diagnose CIP (p = 0.004) and severe CIP (p < 0.001). For severe CIP, the eosinophil percentage declined before the symptoms appeared and CT diagnosis. The eosinophil percentage significantly elevated at the follow-up point in the recovery group but not in the non-recovery group. The CIP patients with E_fol/E_bas ≥1.0 had significantly prolonged overall survival (p = 0.024) and after-CIP survival (AS) (p = 0.043). The same results were found in severe CIP but without a statistical difference.

Conclusions

Eosinophil percentage was associated with the diagnosis, prediction, and prognosis of CIP and severe CIP.

Does laser treatment restore the bond strength of resin composites to recently bleached enamel? A systematic review and meta-analysis

PURPOSE

To do a systematic review and meta-analysis to determine whether laser treatment affects the bond strength of resin composites to recently bleached enamel.

METHODS

This report follows the Preferred Reporting Items for Systematic Reviews and Qualitative Analyses (PRISMA) statement. Medline via PubMed, Embase, Web of Science, and the Cochrane Library databases were searched with no limits on publication year. Two reviewers independently screened all titles and abstracts to perform the study selection, data extraction, and risk-of-bias assessments. A random-effects meta-analysis model was performed using Review Manager software (version 5.3, Cochrane Collaboration).

RESULTS

From the 93 records identified, seven articles that met all the inclusion criteria were included in the systematic review, and six studies were included in the meta-analysis. The overall results showed a statistically significant difference in bond strength between the control group and laser-treated group (P= 0.04; mean difference: 5.27; 95% confidence interval: 0.28 to 10.27), favoring the laser-treated group. Subgroup analyses revealed that the tooth source (bovine or human teeth) contributed to the effect of laser treatment on the bleached enamel.

CLINICAL SIGNIFICANCE

Laser treatment may increase the bond strength of resin composites to recently bleached enamel. Pretreatment with a laser, preferably with Nd:YAG (1 W, frequency of 10 Hz, irradiation time of 60 seconds) or CO2 lasers (0.5 W, frequency of 10 Hz, irradiation time of 60 seconds), may be recommended to restore the bond strength of recently bleached enamel.

All electrospun fabrics based piezoelectric tactile sensor

Tactile sensors have been widely used in the areas of health monitoring and intelligent human-machine interface. Flexible tactile sensors based on nanofiber mats made by electrospinning can meet the requirements of comfortability and breathability for wearing the body very well. Here, we developed a flexible and self-powered tactile sensor that was sandwich assembled by electrospun organic electrodes and a piezoelectric layer. The metal-free organic electrodes of thermal plastic polyurethane (PU) nanofibers decorated with multi-walled carbon nanotubes were fabricated by electrospinning followed by ultrasonication treatment. The electrospun polyvinylidene fluoride-trifluoroethylene (PVDF-TrFE) mat was utilized as the piezoelectric layer, and it was found that the piezoelectric performance of PVDF-TrFE nanofiber mat added with barium titanate (BaTiO₃) nanoparticles was enhanced about 187% than that of the pure PVDF-TrFE nanofiber mat. For practical application, the as-prepared piezoelectric tactile sensor exhibited an approximative linear relationship between the external force and the electrical output. Then the array of fabricated sensors was attached to the fingertips of a glove to grab a cup of water for tactile sensing, and the mass of water can be directly estimated according to the outputs of the sensor array. Attributed to the integrated merits of good flexibility, enhanced piezoelectric performance, light weight, and efficient gas permeability, the developed tactile sensor could be widely used as wearable devices for robot execution end or prosthesis for tactile feedback.

Predicting checkpoint inhibitors pneumonitis in non-small cell lung cancer using a dynamic online hypertension nomogram

OBJECTIVES

Checkpoint inhibitors pneumonitis (CIP) is one of the most lethal adverse events in non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). Currently, there is no recognized and effective predictive model to predict CIP in NSCLC.

MATERIALS AND METHODS

This study retrospectively analyzed 460 NSCLC patients who were first treated with ICIs. Patients were divided into three cohorts based on the occurrence of CIP: any grade CIP cohort, grade ≥ 2 CIP cohort and grade ≥ 3 CIP cohort.

RESULTS

A dynamic hypertension nomogram was constructed with elements including hypertension, interstitial lung disease (ILD), emphysema at baseline, and higher baseline platelet/lymphocyte ratio (PLR). The C indices of the training cohort and the internal and external validation cohort in any grade CIP cohort were 0.872, 0.833 and 0.840, respectively. The constructed hypertension nomogram was applied to grade ≥ 2 cohort and grade ≥ 3 cohort, and their C indices were 0.844 and 0.866, respectively. Compared with the non-hypertension nomogram, the hypertension nomogram presented better predictive power.

CONCLUSIONS

After validated by internal and external validation cohorts, the dynamic online hypertension has the potential to become a convenient, intuitive, and personalized clinical tool for assessing the risk of CIP in NSCLC patients.

Long non-coding RNA PAXIP-AS1 promotes viability, invasion, and migration of HTR-8/SVneo cells through miR-210-3p/BDNF axis

OBJECTIVE

The aim of this research was to explore the role and potential mechanism of long non-coding RNA PAXIP-AS1 in preeclampsia.

METHODS

To investigate the effects of PAXIP-AS1 on cell viability, migration, and invasion. The miR-210-3p-targeted relationship with lncRNA PAXIP-AS1 or BDNF was verified.

RESULTS

PAXIP-AS1 was inversely correlated with miR-210-3p and BDNF was targeted by miR-210-3p. BDNF was positively correlated with PAXIP-AS1 in the serum of preeclampsia patients. The promotion effects of PAXIP-AS1 on cell viability, migration, and invasion were reversed by miR-210-3p up-regulation or BDNF knockdown in trophoblast cells.

CONCLUSION

PAXIP-AS1 promoted the viability, migration, and invasion of trophoblast cells by regulating the miR-210-3p/BDNF axis.

Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid

Background

It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope.

Objective

This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage.

Method

The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly.

Results

With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists.

Conclusion

A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.

A coordinate positioning puncture method under robot-assisted CT-guidance: phantom and animal experiments

PURPOSE

To evaluate the accuracy of the robot-assisted computed tomography (CT)-guided coordinate positioning puncture method by phantom and animal experiments.

MATERIAL AND METHODS

In the phantom experiment, seven robot-assisted punctures were made to evaluate the accuracy of the method. In the animal experiment, 18 punctures (nine robotic and nine manual) were made in the livers of nine rabbits. The indicators, such as needle-tract length, angle deviation, puncture accuracy, number of scans required, and radiation exposure dose were compared between manual and robotic punctures. The paired-samples t-test was used for analysis.

RESULTS

In the phantom experiment, the mean accuracy of seven punctures was 2.67 mm. In the animal experiment, there was no significant difference in needle-tract length (32.58 mm vs. 34.04 mm, p = .606), angle deviation (17.21° vs. 21.23° p = .557) and puncture accuracy (8.42 vs. 8.77 mm, p = .851) between the two groups. However, the number CT scans required (2.44 vs. 3.33, p = .002), and the radiation exposure dose (772.98 vs. 1077.89 mGy/cm, p = .003) were lower in the robot group than in the manual group.

CONCLUSIONS

The coordinate positioning puncture method under robot-assisted CT-guidance can reach an accuracy that is comparable to that of the traditional manual CT-guided puncture method and with fewer CT scanning times accompanied with a lower radiation dosage.

Single-Beam Acoustic Tweezer Prepared by Lead-Free KNN-Based Textured Ceramics

Acoustic tweezers for microparticle non-contact manipulation have attracted attention in the biomedical engineering field. The key components of acoustic tweezers are piezoelectric materials, which convert electrical energy to mechanical energy. The most widely used piezoelectric materials are lead-based materials. Because of the requirement of environmental protection, lead-free piezoelectric materials have been widely researched in past years. In our previous work, textured lead-free (K, Na)NbO3 (KNN)-based piezoelectric ceramics with high piezoelectric performance were prepared. In addition, the acoustic impedance of the KNN-based ceramics is lower than that of lead-based materials. The low acoustic impedance could improve the transmission efficiency of the mechanical energy between acoustic tweezers and water. In this work, acoustic tweezers were prepared to fill the gap between lead-free piezoelectric materials research and applications. The tweezers achieved 13 MHz center frequency and 89% −6 dB bandwidth. The −6 dB lateral and axial resolution of the tweezers were 195 μm and 114 μm, respectively. Furthermore, the map of acoustic pressure measurement and acoustic radiation calculation for the tweezers supported the trapping behavior for 100 μm diameter polystyrene microspheres. Moreover, the trapping and manipulation of the microspheres was achieved. These results suggest that the KNN-based acoustic tweezers have a great potential for further applications.

Establishment and Verification of Neural Network for Rapid and Accurate Cytological Examination of Four Types of Cerebrospinal Fluid Cells

Fast and accurate cerebrospinal fluid cytology is the key to the diagnosis of many central nervous system diseases. However, in actual clinical work, cytological counting and classification of cerebrospinal fluid are often time-consuming and prone to human error. In this report, we have developed a deep neural network (DNN) for cell counting and classification of cerebrospinal fluid cytology. The May-Grünwald-Giemsa (MGG) stained image is annotated and input into the DNN network. The main cell types include lymphocytes, monocytes, neutrophils, and red blood cells. In clinical practice, the use of DNN is compared with the results of expert examinations in the professional cerebrospinal fluid room of a First-line 3A Hospital. The results show that the report produced by the DNN network is more accurate, with an accuracy of 95% and a reduction in turnaround time by 86%. This study shows the feasibility of applying DNN to clinical cerebrospinal fluid cytology.

High Curie temperature bismuth-based piezo-/ferroelectric single crystals of complex perovskite structure: recent progress and perspectives

The recent progress in high TC bismuth-based piezo-/ferroelectric single crystals is reviewed in terms of materials design, crystal growth, physical properties, crystal chemistry, and complex domain structures, and the future perspectives are discussed.

A Hierarchical Bayesian Latent Class Model for the Diagnostic Performance of Mini-Mental State Examination and Montreal Cognitive Assessment in Screening Mild Cognitive Impairment Due to Alzheimer's Disease

BACKGROUND

The Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) are low costing and noninvasive neuropsychological tests in screening Mild Cognitive Impairment (MCI) due to Alzheimer's disease (AD). There is no consensus on which test performs better in detecting MCI due to AD based on the different imperfect reference standards. Therefore, we conducted a meta-analysis to assess the diagnostic performance of MMSE and MoCA for screening MCI due to AD in the absence of a gold standard.

METHODS

Six electronic databases were searched for relevant studies until April, 2022. A hierarchical Bayesian latent class model was used to estimate the pooled sensitivity and specificity of MoCA and MMSE in the absence of a gold standard.

RESULTS

90 eligible studies covering 21273 individuals for MMSE, 26631 individuals for MoCA were included in this meta-analysis. The pooled sensitivity was 0.71(95%CI: 0.67-0.74) for MMSE and 0.85(95%CI: 0.83-0.88) for MoCA, while the pooled specificity was 0.71(95%CI: 0.68-0.74) for MMSE and 0.79(95%CI: 0.76-0.81) for MoCA. MoCA was useful to "rule in" and "rule out" the diagnosis of MCI due to AD with higher positive likelihood ratio (4.07; 95%CI: 3.60-4.62) and lower negative likelihood ratio (0.18; 95%CI: 0.16-0.22). Moreover, the diagnostic odds ratio of MoCA was 22.08(95%CI: 17.24-28.29), which showed significantly favorable diagnostic performance.

CONCLUSIONS

It suggests that MoCA has greater diagnostic performance than MMSE for differentiating MCI due to AD when the gold standard is absent. However, these results should be taken with caution given the heterogeneity observed.

Effect of Immune-Related Adverse Events and Pneumonitis on Prognosis in Advanced Non-Small Cell Lung Cancer: A Comprehensive Systematic Review and Meta-analysis

OBJECTIVE

The correlation between immune-related adverse events (irAEs) and prognosis remains controversial in advanced non-small cell lung cancer (NSCLC). The aim of this study was to systematically evaluate the effect of irAEs, especially checkpoint inhibitor pneumonitis (CIP), on the survival and treatment response in advanced NSCLC.

METHODS

The primary outcomes were overall survival (OS) and objective response rate (ORR). Databases were searched for relevant studies, and meta-analysis was conducted with RevMan.

RESULTS

A total of 51 studies involving 12,600 participants were included. The development of irAEs had an advantageous effect on OS and ORR in advanced NSCLC (OS: hazard ratio [HR], 0.56 [95% confidence interval [CI] 0.46 to 0.67]; ORR: odds ratio [OR], 3.13 [2.41 to 4.06]). The occurrence of endocrine and skin irAEs had advantageous effects on both OS and ORR (endocrine OS, HR, 0.47 [-0.37 to 0.59]; endocrine ORR: OR, 1.90 [1.27 to 2.84]; skin OS: HR, 0.48 [0.38 to 0.61]; skin ORR: OR, 4.30 [2.68 to 6.91]). Severe-grade irAEs resulted in shorter OS than low-grade irAEs (HR, 1.49 [1.06, 2.09]), and multiple irAEs resulted in better ORR compared with 1 irAE (OR, 2.04 [1.41 to 2.94]). The occurrence of CIP had no significant effect on OS (HR, 1.14 [0.70 to 1.86]), but it was associated with better ORR (OR, 2.12 [1.06 to 4.25]). Severe-grade CIP had no effect on OS or ORR, but CIP leading to treatment discontinuation resulted in shorter OS (HR, 2.35 [1.17 to 4.72]).

CONCLUSION

The development of irAEs had advantageous effects on survival and response in advanced NSCLC. CIP had no effect on survival, but it predicted better response.

Assessment of radiation doses and image quality of multiple low-dose CT exams in COVID-19 clinical management

PURPOSE

The Corona Virus Disease 2019 (COVID-19) was first reported in December 2019 from an outbreak of unexplained pneumonia in Wuhan (Hubei, China) that subsequently spread rapidly around the world. Because of the public health emergency, chest CT has been widely used for sensitive detection and diagnosis, monitoring the changes of lesions and also for treatment evaluation. The purpose of this study was to investigate radiation dose and image quality of chest CT scans received by COVID-19 patients and to evaluate the oncogenic risk of multiple chest CT examinations.

METHODS

A retrospective review of 33 patients with RT-PCR confirmed COVID-19 infection was performed from January 31, 2020 to February 19, 2020. The date of each CT exam and respective radiation dose for each exam was recorded for all patients. Multiple pulmonary CT scans were obtained during diagnosis and treatment procedure. Scan frequency, total scan times, radiation dose, and image quality were determined.

RESULTS

Thirty-three patients (15 males and 18 females, age 21-82 years) with confirmed COVID-19 pneumonia underwent a total of 143 chest CT scans. The number of CT scans per patient was 4 ± 1, with a range of 2-6. The time interval between two consecutive chest CT scans was 3 ± 1 days. The average effective dose from a single chest CT scan was 1.21 ± 0.10 mSv, with a range of 1.02-1.44 mSv. The average cumulative effective dose per patient was 5.25 ± 1.52 mSv, with a range of 2.24-7.48 mSv. The maximum cumulative effective dose was 7.48 mSv for six CT examinations during COVID-19 treatment. Based on subjective image quality analysis, the visual scoring of CT findings was 11.23 ± 1.35 points out of 15 points.

CONCLUSIONS

The frequency, total number and image quality of chest CT scans should be reviewed carefully to guarantee minimally required CT scans during the COVID-19 management.

Hybrid System Combining Two-Dimensional Materials and Ferroelectrics and Its Application in Photodetection

Photodetectors are one of the most important components for a future "Internet-of-Things" information society. Compared to the mainstream semiconductor-based photodetectors, emerging devices based on two-dimensional (2D) materials and ferroelectrics as well as their hybrid systems have been extensively studied in recent decades due to their outstanding performances and related interesting physical, electrical, and optoelectronic phenomena. In this paper, we review the photodetection based on 2D materials and ferroelectric hybrid systems. The fundamentals of 2D and ferroelectric materials as well as the interaction in the hybrid system will be introduced. Ferroelectricity modulated optoelectronic properties in the hybrid system will be discussed in detail. After the basics and figures of merit of photodetectors are summarized, the 2D-ferroelectrics devices with different structures including p-n diodes, Schottky diodes, and field-effect transistors will be reviewed and compared. The polarization of ferroelectrics offers the possibility of the modulation and enhancement of the photodetection in the hybrid detectors, which will be discussed in depth. Finally, the challenges and perspectives of the photodetectors based on 2D ferroelectrics will be proposed. This Review outlines the important aspects of the recent development of the hybrid system of 2D and ferroelectric materials, which could interact with each other and thus lead to photodetectors with higher performances. Such a Review will be helpful for the research of emerging physical phenomena and for the design of multifunctional nanoscale electronic and optoelectronic devices.

Direction Matters: On Influence-Preserving Graph Summarization and Max-Cut Principle for Directed Graphs

Summarizing large-scale directed graphs into small-scale representations is a useful but less-studied problem setting. Conventional clustering approaches, based on Min-Cut-style criteria, compress both the vertices and edges of the graph into the communities, which lead to a loss of directed edge information. On the other hand, compressing the vertices while preserving the directed-edge information provides a way to learn the small-scale representation of a directed graph. The reconstruction error, which measures the edge information preserved by the summarized graph, can be used to learn such representation. Compared to the original graphs, the summarized graphs are easier to analyze and are capable of extracting group-level features, useful for efficient interventions of population behavior. In this letter, we present a model, based on minimizing reconstruction error with nonnegative constraints, which relates to a Max-Cut criterion that simultaneously identifies the compressed nodes and the directed compressed relations between these nodes. A multiplicative update algorithm with column-wise normalization is proposed. We further provide theoretical results on the identifiability of the model and the convergence of the proposed algorithms. Experiments are conducted to demonstrate the accuracy and robustness of the proposed method.

DAGM: A novel modelling framework to assess the risk of HER2-negative breast cancer based on germline rare coding mutations

BACKGROUND

Breast cancers can be divided into HER2-negative and HER2-positive subtypes according to different status of HER2 gene. Despite extensive studies connecting germline mutations with possible risk of HER2-negative breast cancer, the main category of breast cancer, it remains challenging to obtain accurate risk assessment and to understand the potential underlying mechanisms.

METHODS

We developed a novel framework named Damage Assessment of Genomic Mutations (DAGM), which projects rare coding mutations and gene expressions into Activity Profiles of Signalling Pathways (APSPs).

FINDINGS

We characterized and validated DAGM framework at multiple levels. Based on an input of germline rare coding mutations, we obtained the corresponding APSP spectrum to calculate the APSP risk score, which was capable of distinguish HER2-negative from HER2-positive cases. These findings were validated using breast cancer data from TCGA (AUC = 0.7). DAGM revealed that HER2 signalling pathway was up-regulated in germline of HER2-negative patients, and those with high APSP risk scores had exhibited immune suppression. These findings were validated using RNA sequencing, phosphoproteome analysis, and CyTOF. Moreover, using germline mutations, DAGM could evaluate the risk for HER2-negative breast cancer, not only in women carrying BRCA1/2 mutations, but also in those without known disease-associated mutations.

INTERPRETATION

The DAGM can facilitate the screening of subjects at high risk of HER2-negative breast cancer for primary prevention. This study also provides new insights into the potential mechanisms of developing HER2-negative breast cancer. The DAGM has the potential to be applied in the prevention, diagnosis, and treatment of HER2-negative breast cancer.

FUNDING

This work was supported by the National Key Research and Development Program of China (grant no. 2018YFC0910406 and 2018AAA0103302 to CZ); the National Natural Science Foundation of China (grant no. 81202076 and 82072939 to MY, 81871513 to KW); the Guangzhou Science and Technology Program key projects (grant no. 2014J2200007 to MY, 202002030236 to KW); the National Key R&D Program of China (grant no. 2017YFC1309100 to CL); Shenzhen Science and Technology Planning Project (grant no. JCYJ20170817095211560 574 to YN); and the Natural Science Foundation of Guangdong Province (grant no. 2017A030313882 to KW and S2013010012048 to MY); Hefei National Laboratory for Physical Sciences at the Microscale (grant no. KF2020009 to GN); and RGC General Research Fund (grant no. 17114519 to YQS).

Energy restriction causes metaphase delay and chromosome mis-segregation in cancer cells

ATP metabolism during mitosis needs to be coordinated with numerous energy-demanding activities, especially in cancer cells whose metabolic pathways are reprogramed to sustain rapid proliferation in a nutrient-deficient environment. Although strategies targeting the energy metabolic pathways have shown therapeutic efficacy in preclinical cancer models, how normal cells and cancer cells differentially respond to energy shortage is unclear. In this study, using time-lapse microscopy, we found that cancer cells displayed unique mitotic phenotypes in a dose-dependent manner upon decreasing ATP (i.e. energy) supply. When reduction in ATP concentration was moderate, chromosome movements in mitosis were barely affected, while the metaphase-anaphase transition was significantly prolonged due to reduced tension between the sister-kinetochores, which delayed the satisfaction of the spindle assembly checkpoint. Further reduction in ATP concentration led to a decreased level of Aurora-B at the centromere, resulting in increased chromosome mis-segregation after metaphase delay. In contrast to cancer cells, ATP restriction in non-transformed cells induced cell cycle arrest in interphase, rather than causing mitotic defects. In addition, data mining of cancer patient database showed a correlation between signatures of energy production and chromosomal instability possibly resulted from mitotic defects. Together, these results reveal that energy restriction induces differential responses in normal and cancer cells, with chromosome mis-segregation only observed in cancer cells. This points to targeting energy metabolism as a potentially cancer-selective therapeutic strategy.

Nomogram model to predict pneumothorax after computed tomography-guided coaxial core needle lung biopsy

PURPOSE

To develop a predictive model to determine risk factors of pneumothorax in patients undergoing the computed tomography (CT)¹-guided coaxial core needle lung biopsy (CCNB).

METHODS

A total of 489 patients who underwent CCNBs with an 18-gauge coaxial core needle were retrospectively included. Patient characteristics, primary pulmonary disease, target lesion image characteristics and biopsy-related variables were evaluated as potential risk factors of pneumothorax which was determined on the chest X-ray and CT scans. Univariate and multivariate logistic regressions were used to identify the independent risk factors of pneumothorax and establish the predictive model, which was presented in the form of a nomogram. The discrimination and calibration of the model were evaluated as well.

RESULTS

The incidence of pneumothorax was 32.91 % and 31.42 % in the development and validation groups, respectively. Age, emphysema, pleural thickening, lesion location, lobulation sign, and size grade were identified independent risk factors of pneumothorax at the multivariate logistic regression model. The forming model produced an area under the curve of 0.718 (95 % CI = 0.660-0.776) and 0.722 (95 % CI = 0.638-0.805) in development and validation group, respectively. The calibration curve showed good agreement between predicted and actual probability.

CONCLUSIONS

The predictive model for pneumothorax after CCNBs had good discrimination and calibration, which could help in clinical practice.

Lead-Free KNN-Based Textured Ceramics for High-Frequency Ultrasonic Transducer Application

Environment-friendly lead-free piezoelectric materials with excellent piezoelectric properties are needed for high-frequency ultrasonic transducer applications. Recently, lead-free 0.915(K_0.45Na_0.5Li_0.05)NbO₃-0.075BaZrO 3-0.01(Bi_0.5Na_0.5)TiO₃ (KNLN-BZ-BNT) textured piezo- electric ceramics have high piezoelectric response, superior thermal stability, and excellent fatigue resistance, which are promising for devices applications. In this work, the KNLN-BZ-BNT textured ceramics were prepared by the tape-casting method. Microstructural morphology, phase transition, and electrical properties of KNLN-BZ-BNT textured ceramics were investigated. High-frequency needle-type ultrasonic transducers were designed and fabricated with these textured ceramics. The tightly focused transducers have a center frequency higher than 80 MHz and a -6-dB fractional bandwidth of 52%. Such transducers were built for an f -number close to 1, and the desired focal depth was achieved by press-focusing technology associated with a set of customer design fixture. Its lateral resolution was better than [Formula: see text] by scanning a 15- [Formula: see text] tungsten wire target. These promising results demonstrate that the lead-free KNLN-BZ-BNT textured ceramic is a good candidate for high-frequency ultrasonic transducer applications.

Characterizing the air pollution of the cities in the closure of corona virus disease 2019 in China

With the rapid development of industrialization and urbanization in China, energy and vehicle consumption have continued to increase in recent years and air pollution has become serious. In early 2020, Corona Virus Disease 2019 broke out in Wuhan, China. From January 29, 2020, several sources of the air pollution almost all stopped working, including gasoline burning vehicles, dust producing building sites, coal-fired factories, etc. Five indicators of the atmospheric environmental quality were observed from December 19, 2019 to April 30, 2020 in nine cities and 1-h average concentrations, 24-h average concentrations and Air Quality Index were assessed. The 1-h average concentrations of the nitrogen dioxide, the ozone and the sulfur dioxide showed obvious difference though the closure did not change the sequence of the five pollutants' concentrations in the air at diverse sampling moments. The changing of the 24-h average concentrations of the five pollutants indicated the amount of pollutants in the air were greatly affected by human activities. The nitrogen dioxide, the sulfur dioxide and the particulate matters decreased obviously in the closure. The air in the metropolis and the south-east cities were relatively clean and the pollutants' concentrations decreased slightly during the closure period. The northern and the heavy industrial cities showed significant drop on air pollution indicators and the air quality of the two city groups could be greatly improved if some effective measures could be taken of environmental management and regional development.

Nanomedicine promotes ferroptosis to inhibit tumour proliferation in vivo

miR-101–3p may play a therapeutic role in various tumours. However, its anti-tumour mechanism remains unclear, and a definitive strategy to treat tumour cells in vivo is lacking. The objective of this study was to investigate the inhibitory mechanism of miR-101–3p on tumour cells and to develop relevant nanomedicines for in vivo therapy. The expression levels of miR-101–3p and its target protein TBLR1 in tumour tissues and cells were detected, and their relationship with ferroptosis was clarified. Furthermore, the efficacy of nanocarriers in achieving in vivo therapeutic gene delivery was evaluated. Nanomedicine was further developed, with the anti-proliferative in vivo therapeutic effect validated using a subcutaneous xenograft cancer model. The expression level of miR-101–3p negatively correlated with clinical tumour size and TNM stage. miR-101–3p restores ferroptosis in tumour cells by directly targeting TBLR1, which in turn promotes apoptosis and inhibits proliferation. We developed nanomedicine that can deliver miR-101–3p to tumour cells in vivo to achieve ferroptosis recovery, as well as to inhibit in vivo tumour proliferation. The miR-101–3p/TBLR1 axis plays an important role in tumour ferroptosis. Nanopharmaceuticals that increase miR-101–3p levels may be effective therapies to inhibit tumour proliferation.

Abstract PS8-29: Rare variants in the germline genome holistically determine receptor-independent Her2 signaling pathway activation and immune suppression, shaping pathological type and risk of HER2-negative breast cancer

Background: Pathogenic factors embedded in the germline genome are widely recognized as being crucial to breast cancer development. However, current knowledge is either concentrated on the pathogenic variants of a few individual genes or SNPs distributed sparsely across the genome in non-coding regions. Methods: We developed a multi-layered framework, DAGG, which converts somatic mutations or germline rare coding variants (gRCVs) into a functional spectrum of dozens of cellular functions and signaling pathways to identify potential pathogenic factors.Findings: We analyzed whole-exome sequencing (WES) data of 726 germline DNA samples and 169 breast tumor DNA samples from breast cancer patients with various pathological types and cancer-free female subjects, we found that germline pathogens of breast cancers were (1) mainly distributed in HER2-negative subtypes, and (2) involved Her2 signaling pathway activation and immune suppression. These computational discoveries were experimentally validated and can provide digital features to explain the germline differences between diseased and healthy genome (AUC = 0.76). Furthermore, an individual’s risk for breast cancer can be estimated by calculating the combined effects of these identified germline pathogens. Carriers of BRCA1/2 pathogenic variants were found to have a significantly higher average risk (p = 0.02). Interpretation: The results demonstrated that the identified pathogenic mechanisms by DAGG were compatible with our current understanding of the causes of breast cancer. Moreover, DAGG provides improved performance over currently used polygenic risk score method of measuring complex disease risks. Our framework promises possible future applications for the prevention, diagnosis, and treatment of breast cancer.

Citation Format: Mei Yang, Yanhui Fan, Zhi-Yong Wu, Zhendong Feng, Qiangzu Zhang, Shunhua Han, Zhonghai Zhang, Xu Li, Yiqing Xue, Xiaoling Li, Meixia Hu, Jieqing Li, Weiping Li, Hongfei Gao, Ciqiu Yang, Chunming Zhang, Liulu Zhang, Teng Zhu, Minyi Cheng, Fei Ji, Juntao Xu, Hening Cui, Guangming Tan, Michael Q Zhang, Changhong Liang, Zaiyi Liu, You-Qiang Song, Gang Niu, Kun Wang. Rare variants in the germline genome holistically determine receptor-independent Her2 signaling pathway activation and immune suppression, shaping pathological type and risk of HER2-negative breast cancer [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS8-29.

Ultra-low-dose CT-guided lung biopsy in clinic: radiation dose, accuracy, image quality, and complication rate

BACKGROUND

Computed tomography (CT)-guided percutaneous lung biopsy is usually performed by helical scanning. However, there are no studies on radiation dose, diagnostic accuracy, image quality, and complications based on axial scan mode.

PURPOSE

To determine radiation dose, accuracy, image quality, and complication rate following an ultra-low-dose (ULD) protocol for CT-guided lung biopsy in clinic.

MATERIAL AND METHODS

A total of 105 patients were enrolled to receive CT-guided lung biopsy. The use of an ULD protocol (axial scan) for CT-guided biopsy was initiated. Patients were randomly assigned to axial mode (Group A) and conventional helical mode (Group B) CT groups. 64-slice CT was performed for CT-guided pulmonary biopsy with an 18-G coaxial cutting biopsy needle. The radiation dose, accuracy, image quality, and complication rate were measured.

RESULTS

Ninety-seven patients were selected for the final phase of the study. There was no significant difference between the two groups for pulmonary nodule characteristics (P > 0.05). The mean effective dose in group A (0.077 ± 0.010 mSv) was significantly reduced relative to group B (0.653 ± 0.177 mSv, P < 0.001). There was no significant difference in accuracy, image quality, and complication rate (P > 0.050) between the two modes.

CONCLUSION

An ULD protocol for CT-guided lung nodule biopsy yields a reduction in the radiation dose without significant change in the accuracy, image quality, and complication rate relative to the conventional helical mode scan.

Peritoneal Metastasis After Treated With Abemaciclib Plus Fulvestrant for Metastatic Invasive Lobular Breast Cancer: A Case Report and Review of the Literature

Peritoneal metastases from invasive lobular carcinoma (ILC) of breast are uncommon and usually related to poor prognosis due to difficulty of detection in clinical practice and drug resistance. Therefore, recognizing the entities of peritoneal metastases of ILC and the potential mechanism of drug resistance is of great significance for early detection and providing accurate management. We herein report a case of a 60-year-old female who presented with nausea and vomiting as the first manifestation after treated with abemaciclib (a CDK4/6 inhibitor) plus fulvestrant for 23 months due to bone metastasis of ILC. Exploratory laparotomy found multiple nodules in the peritoneum and omentum, and immunohistochemistry confirmed that the peritoneal metastatic lesions were consistent with ILC. Palliative therapy was initiated, but the patient died two months later due to disease progression with malignant ascites. Whole exome sequencing (WES) was used to detect the tumor samples and showed the peritoneal metastatic lesions had acquired ESR1 and PI3KCA mutations, potentially explaining the mechanism of endocrine therapy resistance. We argue that early diagnosis of peritoneal metastasis from breast cancer is crucial for prompt and adequate treatment and WES might be an effective supplementary technique for detection of potential gene mutations and providing accurate treatment for metastatic breast cancer patients.