A New SPQC Biosensor for the Detection of a New Target of Escherichia/Shigella Genera Based on a Novel Method of Synthesizing Long-Range DNA.

The rapid and sensitive detection of Escherichia/Shigella genera is crucial for human disease and health. This study introduces a novel series of piezoelectric quartz crystal (SPQC) sensors for detecting Escherichia/Shigella genera. In this innovative biosensor, we propose a new target and novel method for synthesizing long-range DNA. The method relies on the amplification of two DNA probes, referred to as H and P amplification (HPA), resulting in the products of long-range DNA named Sn. The new target was screened from the 16S rRNA gene and utilized as a biomarker. The SPQC sensor operates as follows: the Capture probe is modified on the electrodes. In the presence of a Displace probe and target, the Capture can form a complex with the Displace probe. The resulting complex hybridizes with Sn, bridging the gap between the electrodes. Finally, silver wires are deposited between the electrodes using Sn as a template. This process results in a sensitive response from the SPQC. The detection limit of the SPQC sensor is 1 CFU/mL, and the detection time is within 2 h. This sensor would be of great benefit for food safety monitoring and clinical diagnosis.

Ultrasensitive Detection of Tumor Suppressor Gene Methylation by Piezoelectric Sensing Based on Enrichment of Transcription Activator-Like Effectors.

The detection of DNA methylation at cytosine/guanine dinucleotide (CpG) islands in promoter regions of tumor suppressor genes has great potential for early cancer screening, diagnosis, and prognosis monitoring. Nevertheless, achieving accurate, sensitive, cost-effective, and quantitative detection of target methylated DNA remains challenging. Herein, we propose a novel piezoelectric sensor (series piezoelectric quartz crystal (SPQC)) based on transcription activator-like effectors (TALEs) for detecting DNA methylation of Ras association domain family 1 isoform A (RASSF1A) tumor suppressor genes (R-5mC). The sensor employs TALEs-Ni magnetic beads to specifically recognize and separate the R-5mC, thereby improving the detection selectivity. The TALEs-Ni magnetic beads-R-5mC complex is sheared by a nucleic acid enzyme (DNAzyme) to release the single-stranded DNA (ST). ST initiates a catalyzed hairpin assembly (CHA) reaction on the surface of the electrode, which in turn triggers the hybridization chain reaction (HCR) and silver staining for enhanced detection sensitivity. The strategy exhibits a linear response in the detection of R-5mC in the range of 1 fM to 1 nM with a detection limit of 0.79 fM. R-5mC as low as 0.01% can be detected, even in the presence of large numbers of unmethylated DNA. The detection of R-5mC in circulating cell-free DNA (cfDNA) derived from clinical plasma specimens of lung cancer patients yielded satisfactory results.

Genome-wide identification of MAPK family in papaya (Carica papaya) and their involvement in fruit postharvest ripening.

BACKGROUND: Papaya (Carica papaya) is an economically important fruit cultivated in the tropical and subtropical regions of China. However, the rapid softening rate after postharvest leads to a short shelf-life and considerable economic losses. Accordingly, understanding the mechanisms underlying fruit postharvest softening will be a reasonable way to maintain fruit quality and extend its shelf-life. RESULTS: Mitogen-activated protein kinases (MAPKs) are conserved and play essential roles in response to biotic and abiotic stresses. However, the MAPK family remain poorly studied in papaya. Here, a total of nine putative CpMAPK members were identified within papaya genome, and a comprehensive genome-wide characterization of the CpMAPKs was performed, including evolutionary relationships, conserved domains, gene structures, chromosomal locations, cis-regulatory elements and expression profiles in response to phytohormone and antioxidant organic compound treatments during fruit postharvest ripening. Our findings showed that nearly all CpMAPKs harbored the conserved P-loop, C-loop and activation loop domains. Phylogenetic analysis showed that CpMAPK members could be categorized into four groups (A-D), with the members within the same groups displaying high similarity in protein domains and intron-exon organizations. Moreover, a number of cis-acting elements related to hormone signaling, circadian rhythm, or low-temperature stresses were identified in the promoters of CpMAPKs. Notably, gene expression profiles demonstrated that CpMAPKs exhibited various responses to 2-chloroethylphosphonic acid (ethephon), 1-methylcyclopropene (1-MCP) and the combined ascorbic acid (AsA) and chitosan (CTS) treatments during papaya postharvest ripening. Among them, both CpMAPK9 and CpMAPK20 displayed significant induction in papaya flesh by ethephon treatment, and were pronounced inhibition after AsA and CTS treatments at 16 d compared to those of natural ripening control, suggesting that they potentially involve in fruit postharvest ripening through ethylene signaling pathway or modulating cell wall metabolism. CONCLUSION: This study will provide some valuable insights into future functional characterization of CpMAPKs, and hold great potential for further understanding the molecular mechanisms underlying papaya fruit postharvest ripening.

Characterization of the biological and transcriptomic landscapes of bone marrow-derived mesenchymal stem cells in patients with multiple myeloma.

BACKGROUND: Mesenchymal stem/stromal cells (MSCs) have been acknowledged as the most important stromal cells in the bone marrow (BM) microenvironment for physiologic hematopoiesis and the concomitant hematologic malignancies. However, the systematic and detailed dissection of the biological and transcriptomic signatures of BM-MSCs in multiple myeloma (MM) are largely unknown. METHODS: In this study, we isolated and identified BM-MSCs from 10 primary MM patients and 10 healthy donors (HD). On the one hand, we compared the multifaceted biological characteristics of the indicated two BM-MSCs, including biomarker expression pattern, multilineage differentiation potential, stemness and karyotyping, together with the cellular vitality and immunosuppressive property. On the other hand, we took advantage of RNA-SEQ and bioinformatics analysis to verify the similarities and differences at the transcriptomic level between MM-MSCs and HD-MSCs. RESULTS: As to biological phenotypes and biofunctions, MM-MSCs revealed conservation in immunophenotype, stemness and differentiation towards adipocytes and chondrocytes with HD-MSCs, whereas with impaired osteogenic differentiation potential, cellular vitality and immunosuppressive property. As to transcriptomic properties, MM-MSCs revealed multidimensional alterations in gene expression profiling and genetic variations. CONCLUSIONS: Overall, our date systematic and detailed reflected the multifaceted similarities and variations between MM-MSCs and HD-MSCs both at the cellular and molecular levels, and in particular, the alterations of immunomodulation and cellular viability of MM-MSCs, which wound benefit the further exploration of the pathogenesis and new drug application (NDA) of multiple myeloma from the view of BM-MSCs.

Hospitalization, case fatality, comorbidities, and isolated pathogens of adult inpatients with pneumonia from 2013 to 2022: a real-world study in Guangzhou, China.

BACKGROUND: In the context of increasing population aging, ongoing drug-resistant pathogens and the COVID-19 epidemic, the changes in the epidemiological and clinical characteristics of patients with pneumonia remain unclear. This study aimed to assess the trends in hospitalization, case fatality, comorbidities, and isolated pathogens of pneumonia-related adult inpatients in Guangzhou during the last decade. METHODS: We retrospectively enrolled hospitalized adults who had doctor-diagnosed pneumonia in the First Affiliated Hospital of Guangzhou Medical University from January 1, 2013 to December 31, 2022. A natural language processing system was applied to automatically extract the clinical data from electronic health records. We evaluated the proportion of pneumonia-related hospitalizations in total hospitalizations, pneumonia-related in-hospital case fatality, comorbidities, and species of isolated pathogens during the last decade. Binary logistic regression analysis was used to assess predictors for patients with prolonged length of stay (LOS). RESULTS: A total of 38,870 cases were finally included in this study, with 70% males, median age of 64 (53, 73) years and median LOS of 7.9 (5.1, 12.8) days. Although the number of pneumonia-related hospitalizations showed an upward trend, the proportion of pneumonia-related hospitalizations decreased from 199.6 per 1000 inpatients in 2013 to 123.4 per 1000 in 2021, and the case fatality decreased from 50.2 per 1000 in 2013 to 23.9 per 1000 in 2022 (all P < 0.05). The most common comorbidities were chronic obstructive pulmonary disease, lung malignancy, cardiovascular diseases and diabetes. The most common pathogens were Pseudomonas aeruginosa, Candida albicans, Acinetobacter baumannii, Stenotrophomonas maltophilia, Klebsiella pneumoniae, and Staphylococcus aureus. Glucocorticoid use during hospitalization (Odd Ratio [OR] = 1.86, 95% Confidence Interval (CI): 1.14-3.06), immunosuppressant use during hospitalization (OR = 1.99, 1.14-3.46), ICU admission (OR = 16.23, 95%CI: 11.25-23.83), receiving mechanical ventilation (OR = 3.58, 95%CI: 2.60-4.97), presence of other underlying diseases (OR = 1.54, 95%CI: 1.15-2.06), and elevated procalcitonin (OR = 1.61, 95%CI: 1.19-2.19) were identified as independent predictors for prolonged LOS. CONCLUSION: The proportion of pneumonia-related hospitalizations and the in-hospital case fatality showed downward trends during the last decade. Pneumonia inpatients were often complicated by chronic underlying diseases and isolated with gram-negative bacteria. ICU admission was a significant predictor for prolonged LOS in pneumonia inpatients.

Supervised training models with or without manual lesion delineation outperform clinicians in distinguishing pulmonary cryptococcosis from lung adenocarcinoma on chest CT.

BACKGROUND: The role of artificial intelligence (AI) in the discrimination between pulmonary cryptococcosis (PC) and lung adenocarcinoma (LA) warrants further research. OBJECTIVES: To compare the performances of AI models with clinicians in distinguishing PC from LA on chest CT. METHODS: Patients diagnosed with confirmed PC or LA were retrospectively recruited from three tertiary hospitals in Guangzhou. A deep learning framework was employed to develop two models: an undelineated supervised training (UST) model utilising original CT images, and a delineated supervised training (DST) model utilising CT images with manual lesion annotations provided by physicians. A subset of 20 cases was randomly selected from the entire dataset and reviewed by clinicians through a network questionnaire. The sensitivity, specificity and accuracy of the models and the clinicians were calculated. RESULTS: A total of 395 PC cases and 249 LA cases were included in the final analysis. The internal validation results for the UST model showed a sensitivity of 85.3%, specificity of 81.0%, accuracy of 83.6% and an area under the curve (AUC) of 0.93. Similarly, the DST model exhibited a sensitivity of 88.2%, specificity of 88.1%, accuracy of 88.2% and an AUC of 0.94. The external validation of the two models yielded AUC values of 0.74 and 0.77, respectively. The average sensitivity, specificity and accuracy of 102 clinicians were determined to be 63.1%, 53.7% and 59.3%, respectively. CONCLUSIONS: Both models outperformed the clinicians in distinguishing between PC and LA on chest CT, with the UST model exhibiting comparable performance to the DST model.

Echo-Level SAR Imaging Simulation of Wakes Excited by a Submerged Body.

The paper introduces a numerical simulation method for Synthetic Aperture Radar (SAR) imaging of submerged body wakes by integrating hydrodynamics, electromagnetic scattering, and SAR imaging simulation. This work is helpful for better understanding SAR images of submerged body wakes. Among these, the hydrodynamic model consists of two sets of ocean dynamics closely related to SAR imaging, namely the wake of the submerged body and wind waves. For the wake, we simulated it using computational fluid dynamics (CFD) numerical methods. Furthermore, we compared and computed the electromagnetic scattering characteristics of wakes under various navigation parameters and sea surface conditions. Following that, based on the operational principles and imaging theory of synthetic aperture radar (SAR), we established the SAR raw echo signal of the wake. Employing a Range-Doppler (RD) algorithm, we generated simulated SAR images of the wake. The results indicate that utilizing Computational Fluid Dynamics (CFD) numerical methods enables the simulation of wake characteristics generated by the motion of a submerged body with different velocities. The backscattering features of wakes are closely associated with the relative orientation between the wake and the radar line of sight. Under specific wind speeds, the wake gets masked within the sea surface background, resulting in less discernible characteristics of the wake in SAR images. This suggests that at lower speeds of submerged body or under specific wind conditions, the detectability of the wake in SAR images significantly diminishes.

Neural Stem Cells Transplanted into Rhesus Monkey Cortical Traumatic Brain Injury Can Survive and Differentiate into Neurons.

Cortical traumatic brain injury (TBI) is a major cause of cognitive impairment accompanied by motor and behavioral deficits, and there is no effective treatment strategy in the clinic. Cell transplantation is a promising therapeutic strategy, and it is necessary to verify the survival and differentiation of cells after transplantation in large animal models like rhesus monkeys. In this study, we transplanted neural stem cells (NSCs) and simultaneously injected basic fibroblast growth factor/epidermal growth factor (bFGF/EGF) into the cortex (visual and sensory cortices) of rhesus monkeys with superficial TBI. The results showed that the transplanted NSCs did not enter the cerebrospinal fluid (CSF) and were confined to the transplantation site for at least one year. The transplanted NSCs differentiated into mature neurons that formed synaptic connections with host neurons, but glial scar formation between the graft and the host tissue did not occur. This study is the first to explore the repairing effect of transplanting NSCs into the superficial cerebral cortex of rhesus monkeys after TBI, and the results show the ability of NSCs to survive long-term and differentiate into neurons, demonstrating the potential of NSC transplantation for cortical TBI.

Pseudolaric acid B exerts an antifungal effect and targets SIRT1 to ameliorate inflammation by regulating Nrf2/NF-κB pathways in fungal keratitis.

Fungal keratitis (FK) is a vision-threatening infection. We aimed to explore the antifungal and anti-inflammatory effects of pseudolaric acid B (PAB) on FK and the underlying mechanisms involved. Network pharmacology utilized to acquire the potential target genes, and silent information regulator 1 (SIRT1) was consistently downregulated in Gene Expression Omnibus dataset and clinical samples. Molecular docking analysis showed that PAB and SIRT1 had good binding activity. No toxicity was observed in vivo and in vitro with a PAB concentration below 0.3 µM. PAB exerted its antifungal activity by destroying the integrity of hyphae, and alleviated the severity of FK in rats by decreasing clinical scores, fungal burden and inhibiting inflammatory cell infiltration. PAB increased SIRT1 to regulate the crosstalk between nuclear factor erythroid 2-related factor 2 (Nrf2) and nuclear factor kappa-B (NF-κB), decreasing the levels of inflammatory cytokines tumor necrosis factor (TNF)-α, interleukin (IL)-1ß, and IL-6; and pattern recognition receptors, C-type lectin domain containing 7A (Dectin-1), lectin-like oxidized low-density lipoprotein receptor 1 (LOX-1), toll like receptor (TLR)-2, and TLR4 both in vivo and in vitro. However, this anti-inflammatory effect of PAB was abolished by the SIRT1 inhibitor EX527. This study provides new evidence that PAB has antifungal and anti-inflammatory effects in FK and may provide a novel therapeutic strategy for the treatment of FK.

Activity-Stability Balance: The Role of Electron Supply Effect of Support in Acidic Oxygen Evolution.

Developing efficient and durable electrocatalysts for the oxygen evolution reaction (OER) in proton exchange membrane (PEM) electrolyzers represents a significant challenge. Herein, the cobalt-ruthenium oxide nano-heterostructures are successfully synthesized on carbon cloth (CoOx /RuOx -CC) for acidic OER through a simple and fast solution combustion strategy. The rapid oxidation process endows CoOx /RuOx -CC with abundant interfacial sites and defect structures, which enhances the number of active sites and the charge transfer at the electrolyte-catalyst interface, promoting the OER kinetics. Moreover, the electron supply effect of the CoOx support allows electrons to transfer from Co to Ru sites during the OER process, which is beneficial to alleviate the ion leaching and over-oxidation of Ru sites, improving the catalyst activity and stability. As a self-supported electrocatalyst, CoOx /RuOx -CC displays an ultralow overpotential of 180 mV at 10 mA cm-2 for OER. Notably, the PEM electrolyzer using CoOx /RuOx -CC as the anode can be operated at 100 mA cm-2 stably for 100 h. Mechanistic analysis shows that the strong catalyst-support interaction is beneficial to redistribute the electronic structure of RuO bond to weaken its covalency, thereby optimizing the binding energy of OER intermediates and lowering the reaction energy barrier.

A situational analysis of human resource and non-communicable diseases management for community health workers in Chengdu, China: a cross-sectional study.

BACKGROUND: Non-communicable diseases (NCDs) pose a major challenge to health economic cost and residents' health status. Community health workers (CHWs) are the gatekeeper of primary health care. OBJECTIVE: This study aimed to conduct a situational analysis of current human resource and requirements of NCDs-related training among CHWs in Chengdu with regard to address to understand the suggestions for improvement of challenges and barriers. METHODS: A descriptive online cross-sectional survey was conducted among CHWs (doctors and nurses) from 23 districts and counties in Chengdu. Sociodemographic and NCDs-related variables were collected. Univariate analysis and multiple response analysis were used to describe the characteristics of these variables. RESULTS: 711 doctors and 637 nurses completely responded. There were significant differences among gender, age, educational levels, professional title, working year, type of institution, urban circle and registration in general practice between doctors and nurses (P < 0.001). 60.6% of doctors were female, compared to 98.0% for nurses. 58.2% of doctors held a bachelor's degree compared with 45.4% of nurses, while 48.3% of nurses held a junior college degree compared with 25.7% of doctors. Higher levels of professional title and registration in general practice were found in doctors compared with nurses. The proportions of NCDs' category, NCDs-related roles and tasks, NCDs-related training contents and forms that CHWs have attend and hoped to gain more were significantly different between doctors and nurses (P < 0.001). In general, the proportions in nurses were much lower than those of doctors (P < 0.05). The top five diseases managed by CHWs were hypertension, diabetes, cerebrovascular disease, chronic respiratory diseases and mental diseases. The five most reported roles performed among doctors included the distribution of health education (91.4%), following up (85.9%), establishing archives (71.3%), medicine adjustment (64.7%) and treatment implementation (52.0%). The top three diseases managed by nurses were same with doctors. The top four and five tasks were contact with patients or health services (39.6%) and referral (16.6%) in nurses. Most CHWs had received primary and common diseases-related trainings, but they had few opportunities to study in a tertiary hospital (40.4% in doctors and 20.9% in nurses, respectively), attend domestic academic conferences (26.9% in doctors vs. 9.7% in nurses), and take part in training courses (44.9% in nurses). CHWs hoped that the above-discussed training contents and forms could be provided more in the future. Besides basic skills related trainings, some specific skills related trainings should be strengthened. CONCLUSION: The qualifications in doctors were much better than those of nurses. The roles performed by CHWs in NCDs management are varied form common and frequent disease management to subsequent follow up and supervision. CHWs hope to receive more desired and oriented trainings. There is a need for building capacity of CHWs, optimizing and defining CHWs' role, facilitating postgraduate medical education support and strengthening multidisciplinary collaboration would be effective in NCDs management.

Effects of a brief self-compassion intervention for college students with impostor phenomenon.

The present study used a latent growth curve modeling approach to (a) examine the effectiveness of a brief self-compassion intervention on reducing impostor phenomenon, maladaptive perfectionism, and psychological distress and (b) explore who would benefit more from this intervention. A total of 227 college students at a large Midwest university were randomly assigned to participate in either a 4-week brief self-compassion intervention group or a nonintervention control group. Analyses of the effectiveness of the intervention suggested the brief self-compassion intervention had significant treatment effects for reducing impostor phenomenon and maladaptive perfectionism. Moreover, this study also examined whether participants with different levels of fear of self-compassion and core self-evaluation would report different levels of treatment effectiveness. Fear of self-compassion was found to be a significant moderator of the intervention effects in reducing maladaptive perfectionism and psychological distress. Specifically, participants in the intervention group with higher levels of fear of self-compassion reported a greater decline in both maladaptive perfectionism and psychological distress over time when compared to those with lower levels of fear of self-compassion. Core self-evaluation significantly moderated the effectiveness of this intervention in reducing participants' levels of impostor phenomenon and maladaptive perfectionism. Specifically, participants in the intervention group with lower core self-evaluation reported a greater reduction in maladaptive perfectionism over time when compared to those with higher core self-evaluation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Nanoscale Heating of an Ultrathin Oxide Film Studied by Tip-Enhanced Raman Spectroscopy.

We report on the nanoscale heating mechanism of an ultrathin ZnO film using low-temperature tip-enhanced Raman spectroscopy. Under the resonance condition, intense Stokes and anti-Stokes Raman scattering can be observed for the phonon modes of a two-monolayer (ML) ZnO on an Ag(111) surface, enabling us to monitor local heating at the nanoscale. It is revealed that the local heating originates mainly from inelastic electron tunneling through the electronic resonance when the bias voltage exceeds the conduction band edge of the 2-ML ZnO. When the bias voltage is lower than the conduction band edge, the local heating arises from two different contributions, namely direct optical excitation between the interface state and the conduction band of 2-ML ZnO or injection of photoexcited electrons from an Ag tip into the conduction band. These optical heating processes are promoted by localized surface plasmon excitation. Simultaneous mapping of tip-enhanced Raman spectroscopy and scanning tunneling spectroscopy for 2-ML ZnO including an atomic-scale defect demonstrates visualizing a correlation between the heating efficiency and the local density of states, which further allows us to analyze the local electron-phonon coupling strength with ∼2 nm spatial resolution.

Radiomics in precision medicine for gastric cancer: opportunities and challenges.

OBJECTIVES: Radiomic features derived from routine medical images show great potential for personalized medicine in gastric cancer (GC). We aimed to evaluate the current status and quality of radiomic research as well as its potential for identifying biomarkers to predict therapy response and prognosis in patients with GC. METHODS: We performed a systematic search of the PubMed and Embase databases for articles published from inception through July 10, 2021. The phase classification criteria for image mining studies and the radiomics quality scoring (RQS) tool were applied to evaluate scientific and reporting quality. RESULTS: Twenty-five studies consisting of 10,432 patients were included. 96% of studies extracted radiomic features from CT images. Association between radiomic signature and therapy response was evaluated in seven (28%) studies; association with survival was evaluated in 17 (68%) studies; one (4%) study analyzed both. All results of the included studies showed significant associations. Based on the phase classification criteria for image mining studies, 18 (72%) studies were classified as phase II, with two, four, and one studies as discovery science, phase 0 and phase I, respectively. The median RQS score for the radiomic studies was 44.4% (range, 0 to 55.6%). There was extensive heterogeneity in the study population, tumor stage, treatment protocol, and radiomic workflow amongst the studies. CONCLUSIONS: Although radiomic research in GC is highly heterogeneous and of relatively low quality, it holds promise for predicting therapy response and prognosis. Efforts towards standardization and collaboration are needed to utilize radiomics for clinical application. KEY POINTS: • Radiomics application of gastric cancer is increasingly being reported, particularly in predicting therapy response and survival. • Although radiomics research in gastric cancer is highly heterogeneous and relatively low quality, it holds promise for predicting clinical outcomes. • Standardized imaging protocols and radiomic workflow are needed to facilitate radiomics into clinical use.

Analysis on the relationship between effort-reward imbalance and job satisfaction among family doctors in China: a cross-sectional study.

BACKGROUND: Family doctor contract services was launched in Sichuan province in 2016. The focus was mainly on developing primary health care services but paying less attention to the work stress and job satisfaction of in-service family doctors. OBJECTIVE: This study aims to explore the influencing factors of job satisfaction, and the relation between work stress indicators and job satisfaction among family physicians. METHODS: An analytical online cross-sectional survey was performed among 1,105 family doctors from 23 districts and counties in Chengdu. Self-administered questionnaire was completed. Sociodemographic factors, work stress measured by Effort-Reward Imbalance (ERI)scale, and job satisfaction assessed by the short Chinese version of the Minnesota Satisfaction Questionnaire (MSQ) were collected in this study. A statistical analysis and hierarchical linear regression analysis were performed to explore the influencing factors and the correlations among related variables. RESULTS: The overall mean MSQ score was 52.01 ± 13.23. Analysis of doctor satisfaction indicated that age, education, job rank, type of institution, years of working and monthly income were statistically significant (P < 0.05). There were negative correlation coefficients between general job satisfaction and effort/reward ratio (ERR) (r = -0.130, P < 0.001) and overcommitment (r = -0.615, P < 0.001). CONCLUSION: The level of job satisfaction among family doctors was considerable low. Age, education, job rank, type of institution, years of working and monthly income were influencing factors of job satisfaction. ERI and overcommitment had a negative correlation with general job satisfaction.

Research on Ultra-Wideband NLFM Waveform Synthesis and Grating Lobe Suppression.

Ultra-wideband (UWB) nonlinear frequency modulation (NLFM) waveforms have the advantages of low sidelobes and high resolution. By extending the frequency domain wideband synthesis method to the NLFM waveform, the synthetic bandwidth will be limited, and the grating lobe will grow as the number of subpulses increases at a fixed synthetic bandwidth. Aiming for the highly periodic grating lobes caused by equally spaced splicing and small subpulse time-bandwidth products (TxBW), a multisubpulse UWB NLFM waveform synthesis method is proposed in this paper. Random frequency hopping and spectral correction are utilized to disperse the energy of periodic grating lobes and optimize the matched filter of the subpulse, thereby reducing notches and Fresnel ripples in the synthesized spectrum. The results of the hardware-in-the-loop simulation experiment show that the peak sidelobe ratio (PSLR) and the integral sidelobe ratio (ISLR) of the NLFM synthetic wideband waveform (SWW) obtained by 50 subpulses with a bandwidth of 36 MHz are improved by 4.8 dBs and 4.5 dBs, respectively, when compared to the frequency domain wideband synthesis method, and that the grating lobe is suppressed by an average of 10.6 dBs. It also performs well in terms of point target resolution, and it has potential for 2D radar super-resolution imaging.

Atomic Point Contact Raman Spectroscopy of a Si(111)-7 × 7 Surface.

Tip-enhanced Raman scattering (TERS) has recently demonstrated the exceptional sensitivity to observe vibrational structures on the atomic scale. However, it strongly relies on electromagnetic enhancement in plasmonic nanogaps. Here, we demonstrate that atomic point contact (APC) formation between a plasmonic tip and the surface of a bulk Si sample can lead to a dramatic enhancement of Raman scattering and consequently the phonons of the reconstructed Si(111)-7 × 7 surface can be detected. Furthermore, we demonstrate the chemical sensitivity of APC-TERS by probing local vibrations resulting from Si-O bonds on the partially oxidized Si(111)-7 × 7 surface. This approach will expand the applicability of ultrasensitive TERS, exceeding the previous measurement strategies that exploit intense gap-mode plasmons, typically requiring a plasmonic substrate.

Deep Learning With 3D Convolutional Neural Network for Noninvasive Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

BACKGROUND: Microvascular invasion (MVI) is a critical prognostic factor of hepatocellular carcinoma (HCC). However, it could only be obtained by postoperative histological examination. PURPOSE: To develop an end-to-end deep-learning models based on MRI images for preoperative prediction of MVI in HCC patients who underwent surgical resection. STUDY TYPE: Retrospective. POPULATION: Two hundred and thirty-seven patients with histologically confirmed HCC. FIELD STRENGTH: 1.5 T and 3.0 T. SEQUENCE: Axial T2 -weighted (T2 -w) with turbo spin echo sequence, T2 -Spectral Presaturation with Inversion Recovery (T2 -SPIR), and dynamic contrast-enhanced (DCE) imaging with fat suppressed enhanced T1 high-resolution isotropic volume examination. ASSESSMENT: The patients were randomly divided into training (N = 158) and validation (N = 79) sets. Data augmentation by random rotation was performed on the training set and the sample size increased to 1940 for each MR sequence. A three-dimensional convolutional neural network (3D CNN) was used to develop four deep-learning models, including three single-layer models based on single-sequence, and fusion model combining three sequences. MVI status was obtained from the postoperative pathology reports. STATISTICAL TESTS: The dice similarity coefficient (DSC) and Hausdorff distance (HD) were applied to assess the similarity and reproducibility between the manual segmentations of tumor from two radiologists. Receiver operating characteristic curve analysis was used to evaluate model performance. MVI was identified in 92 (38.8%) patients. Good reproducibility with interobserver DSCs of 0.90, 0.89, and 0.89 and HDs of 4.09, 3.67, and 3.60 was observed for PVP, T2 WI, and T2 -SPIR, respectively. The fusion model achieved an area under the curve (AUC) of 0.81, sensitivity of 69%, and specificity of 79% in the training set and 0.72, sensitivity of 55%, and specificity of 81% in the validation set. DATA CONCLUSION: 3D CNN model may serve as a noninvasive tool to predict MVI in HCC, whereas its accuracy needs to be enhanced with larger cohort. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

MRI-Based Deep-Learning Model for Distant Metastasis-Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma.

BACKGROUND: Distant metastasis is the primary cause of treatment failure in locoregionally advanced nasopharyngeal carcinoma (LANPC). PURPOSE: To develop a model to evaluate distant metastasis-free survival (DMFS) in LANPC and to explore the value of additional chemotherapy to concurrent chemoradiotherapy (CCRT) for different risk groups. STUDY TYPE: Retrospective. POPULATION: In all, 233 patients with biopsy-confirmed nasopharyngeal carcinoma (NPC) from two hospitals. FIELD STRENGTH: 1.5T and 3T. SEQUENCE: Axial T2 -weighted (T2 -w) and contrast-enhanced T1 -weighted (CET1 -w) images. ASSESSMENT: Deep learning was used to build a model based on MRI images (including axial T2 -w and CET1 -w images) and clinical variables. Hospital 1 patients were randomly divided into training (n = 169) and validation (n = 19) cohorts; Hospital 2 patients were assigned to a testing cohort (n = 45). LANPC patients were divided into low- and high-risk groups according to their DMFS (P < 0.05). Kaplan-Meier survival analysis was performed to compare the DMFS of different risk groups and subgroup analysis was performed to compare patients treated with CCRT alone and treated with additional chemotherapy to CCRT in different risk groups, respectively. STATISTICAL TESTS: Univariate analysis was performed to identify significant clinical variables. The area under the receiver operating characteristic (ROC) curve (AUC) was used to assess the model performance. RESULTS: Our deep-learning model integrating the deep-learning signature, node (N) stage (from TNM staging), plasma Epstein-Barr virus (EBV)-DNA, and treatment regimens yielded an AUC of 0.796 (95% confidence interval [CI]: 0.729-0.863), 0.795 (95% CI: 0.540-1.000), and 0.808 (95% CI: 0.654-0.962) in the training, internal validation, and external testing cohorts, respectively. Low-risk patients treated with CCRT alone had longer DMFS than patients treated with additional chemotherapy to CCRT (P < 0.05). DATA CONCLUSION: The proposed deep-learning model, based on MRI features and clinical variates, facilitated the prediction of DMFS in LANPC patients. LEVEL OF EVIDENCE: 3. TECHNICAL EFFICACY STAGE: 4.

Latent profile analysis of interpersonal problems: Attachment, basic psychological need frustration, and psychological outcomes.

The purpose of this project was to identify distinct profiles of circumplex interpersonal problems, cross-validate the profiles, and examine construct validity through associations with adult attachment, basic psychological needs frustration, and psychological outcomes. Undergraduates at two universities provided survey data. In Study 1 (N = 469), latent profile analysis identified three distinct profiles of interpersonal problems. We labeled these: Flexible-Adaptive, Exploitable-Subservient, and Hostile-Avoidant. Construct validity analyses suggested the Flexible-Adaptive profile was distinguished from the other two by lower attachment anxiety, whereas the Hostile-Avoidant profile was distinguished from the other two by higher attachment avoidance. In Study 2 (N = 423), we conducted profile similarity analyses to cross-validate Study 1 results, following the multistep procedure proposed by Morin et al. (Organizational Research Methods, 2016, 19, p. 231). Results suggested that when the data from Study 2 were constrained to fit the profile model derived from Study 1, with respect to means, variance, and latent profile membership, the model fit was equivalent. In Study 2, further evidence of construct validity suggested that the Flexible-Adaptive profile was distinguished from the other two by lower relatedness frustration and by lower competence frustration. Additionally, the Hostile-Avoidant profile was distinguished from the Exploitable-Subservient profile by higher relatedness need frustration. Validity evidence for these profiles indicated that those with the Hostile-Avoidant profile reported the most negative psychological outcomes, followed by those with the Exploitable-Subservient profile, while those with the Flexible-Adaptive profile reported the best psychological outcomes. (PsycInfo Database Record (c) 2021 APA, all rights reserved).