Achieving optimal trade-off for student dropout prediction with multi-objective reinforcement learning.

Student dropout prediction (SDP) in educational research has gained prominence for its role in analyzing student learning behaviors through time series models. Traditional methods often focus singularly on either prediction accuracy or earliness, leading to sub-optimal interventions for at-risk students. This issue underlines the necessity for methods that effectively manage the trade-off between accuracy and earliness. Recognizing the limitations of existing methods, this study introduces a novel approach leveraging multi-objective reinforcement learning (MORL) to optimize the trade-off between prediction accuracy and earliness in SDP tasks. By framing SDP as a partial sequence classification problem, we model it through a multiple-objective Markov decision process (MOMDP), incorporating a vectorized reward function that maintains the distinctiveness of each objective, thereby preventing information loss and enabling more nuanced optimization strategies. Furthermore, we introduce an advanced envelope Q-learning technique to foster a comprehensive exploration of the solution space, aiming to identify Pareto-optimal strategies that accommodate a broader spectrum of preferences. The efficacy of our model has been rigorously validated through comprehensive evaluations on real-world MOOC datasets. These evaluations have demonstrated our model's superiority, outperforming existing methods in achieving optimal trade-off between accuracy and earliness, thus marking a significant advancement in the field of SDP.

Pathogenic factors of maxillary sinus mucosal thickening observed by cone-beam computed tomography (CBCT).

OBJECTIVE: To explore the pathogenic factors associated with maxillary sinus mucosal thickening with Cone-beam computed Tomography (CBCT). METHODS: From 2016 through 2020, 93 patients with periapical periodontitis or periodontitis in the maxillary posterior dental region were selected. RESULTS: The preoperative thickness of the periodontitis group was significantly higher than that of the periapical periodontitis group (P < 0.05). The difference achieves statistical significance for the comparison of the thickness change with various severity of inflammation (F = 54.824, P = 0.000), the change with time (F = 312.741, P = 0.000). and the change with the interaction severity of inflammation and time（F = 86.132, P = 0.000). CONCLUSIONS: Patients with maxillary sinus mucosa thickening caused by periodontitis and periapical periodontitis should be extracted their infectious teeth and get thoroughly debridement. Maxillary sinus augmentation can perform favorable efforts 3-6 months after extracting teeth.

Study on AEMs with Excellent Comprehensive Performance Prepared by Covalently Cross-Linked p-Triphenyl with SEBS Remotely Grafted Piperidine Cations.

A series of SEBS-C6-PIP-yPTP (y = 0-15%) AEMs with good mechanical and chemical stability were prepared by combining the strong rigidity of p-triphenyl, good toughness of SEBS, and excellent stability of PIP cations. After the introduction of a p-triphenyl polymer into the main chain, a clear hydrophilic-hydrophobic phase separation structure was constructed within the membrane, forming a continuous and interconnected ion transport channel to improve ion transport efficiency. Moreover, the molecular chains of the cross-linked AEMs change from chain-like to network-like, and the tighter binding between each molecule increases the tensile strength. The special structure of the six-membered ring makes PIP have a significant constraint effect; when nucleophilic substitution and Hoffman elimination occur at the α and ß positions, the required transition state potential energy increases, making the reaction difficult to occur and improving the alkaline stability of the polymer membrane. The SEBS-C6-PIP-15%PTP membrane has the best mechanical properties (Ts = 38.79 MPa, Eb = 183.09% at 80 °C, 100% RH), the highest ion conductivity (102.02 mS. cm-1 at 80 °C), and the best alkaline stability (6.23% degradation at 80 °C in a 2 M NaOH solution for 1400 h). It can be seen that organic-organic covalent cross-linking is an effective means to improve the comprehensive performance of AEMs.

18 F-FDG PET/CT Imaging of Isolated Myeloid Sarcoma in the Right Humerus.

ABSTRACT: Myeloid sarcoma is a neoplastic mass formed by the infiltration of primitive or immature myeloid cells into organs and tissues outside the bone marrow. It may occur before, at the same time, or manifest as the recurrence of acute myeloid leukemia, myelodysplastic syndromes, and chronic myeloproliferative syndromes. It may involve any organ or tissue, including skin, soft tissue, lymph nodes, and gastrointestinal tract and bone. Isolated humerus involvement is extremely rare. Herein, we present the FDG PET/CT findings of a rare case of isolate myeloid sarcoma in the right humerus, which showed only increased bone density with moderate FDG uptake.

Correlation between carcinoembryonic antigen (CEA) expression and EGFR mutations in non-small-cell lung cancer: a meta-analysis.

OBJECTIVES: The purpose of this meta-analysis was to investigate the relationship between serum carcinoembryonic antigen (CEA) expression and epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer (NSCLC). METHODS: Databases such as PubMed, Cochrane, EMBASE and Google Scholar were systematically searched to identify studies assessing the association of serum CEA expression with EGFR mutations. Across 19 studies, 4168 patients were included between CEA expression and EGFR mutations odds ratio (OR) conjoint analysis of correlations. RESULTS: Compared with CEA-negative NSCLC, CEA-positive tumors had an increased EGFR mutation rate (OR = 1.85, 95% confidence interval: 1.48-2.32, P < 0.00001). This association was observed in both stage IIIB/IV patients (OR = 1.60, 95% CI: 1.18-2.15, P = 0.002) and stage I-IIIA (OR = 1.67, 95% CI: 1.01-2.77, P = 0.05) patients. In addition, CEA expression was associated with exon 19 (OR = 1.97, 95% CI: 1.25-3.11, P = 0.003) and exon 21 (OR = 1.51, 95% CI: 1.07-2.12, P = 0.02) EGFR mutations. In ADC pathological type had also showed the correlation (OR = 1.84, 95% CI: 1.31-2.57, P = 0.0004). CONCLUSIONS: This meta-analysis indicated that serum CEA expression was associated with EGFR mutations in NSCLC patients. The results of this study suggest that CEA level may play a predictive role in the EGFR mutation status of NSCLC patients. Detecting serum CEA expression levels can give a good suggestion to those patients who are confused about whether to undergo EGFR mutation tests. Moreover, it may help better plan of the follow-up treatment.

Hotspots and frontiers in PSMA research for prostate cancer: a bibliometric and visualization analysis over the past 20 years.

BACKGROUND: Prostate-specific membrane antigen (PSMA)-targeted imaging and therapy have significantly changed the management of patients with prostate cancer (PCa) at different disease stages. This advancement has attracted the attention of scholars, leading to a prolific output of scholarly publications. This study comprehensively outlines the knowledge framework associated with PSMA-based diagnosis and treatment of PCa through the application of bibliometric analysis, and discusses the potential research trends and foci. METHODS: Articles and reviews related to PSMA for prostate cancer from 2003 to 2022 were retrieved from Web of Science Core Collection. VOSviewer, Citespace, and R-bibliometrix were primarily employed to execute and visually represent co-authorship, co-citation, and co-occurrence analysis of countries, institutions, authors, references and keywords in this field. RESULTS: A total of 3830 papers were included. The papers on the field of PSMA-based PCa therapy and imaging had been continuously increased since 2003, but the rate has slowed from 2020. The United States made the largest contribution in this field, in terms of publications 997 (26.03%), H-index (110) and total citations (53,167 times). We identified the most productive institution were Technical University of Munich, and Australian institutions had become very active in recent years. Journal of Nuclear Medicine was the most prominent journal in this field. Professors Matthias Eiber and Martin G Pomper made great achievements, while Ali Afshar-Oromieh was the most co-cited author. According to the result of keywords and topics analysis, "ga-68 labeled psma ligand", "radiation dosimetry" and "HBED-CC" were major research areas in the near future, while "Extended pelvic lymph node dissection" was considered to be the future research foci. CONCLUSIONS: The field of psma-based PCa therapy and imaging is in the stage of vigorous development and has a bright prospect. The United States and Germany have achieved outstanding results in this area, while Australia has recently developed rapidly. It is foreseeable that more research foci will be lied in the early detection of pelvic lymph nodes and the multimodal imaging-guided surgery.

A novel technique to harvest bone autografts with mild local hyperthermia and enhanced osteogenic bone quality: a preclinical study in dogs.

BACKGROUND: Guided bone regeneration (GBR) involves collecting bone autografts with high bio-quality and efficiency. The current non-irrigated low-speed drilling has been limited for broader application in bone autograft harvest due to its low efficiency, inability to conduct buccal cortical perforation, and dependence on simultaneous implant placement. Increasing the drilling speed helps improve the efficiency but may incur thermal-mechanical bone damage. Most studies have addressed thermal reactions during bone drilling on non-vital models, which is irrelevant to clinical scenarios. Little has been known about bone's in vivo thermal profiles under non-irrigated higher-speed drilling and its influences on the resulting bone chips. AIM: A novel technique for bone harvest and cortical perforation via in-situ non-irrigated higher-speed drilling was proposed and investigated for the first time. METHODS: The third mandible premolars of eight beagles were extracted and healed for three months. Sixteen partial edentulous sites (left and right) were randomized into four groups for bone autograft harvest without irrigation: chisel, 50 rpm drilling, 500 rpm drilling, and 1000 rpm drilling. Bone chips were harvested on the buccal plates of the missing tooth. An infrared camera and an implantable thermocouple collaboratively monitored in vivo real-time bone temperature at the drilling sites. In vitro performances of cells from bone chips, including cell number, viability, proliferation, migration, ALP activity, in vitro mineralization, mRNA transcriptional level of osteogenic genes and heat shock protein 70 (HSP-70), and HSP-70 expression at the protein level were also studied. RESULTS: 500 rpm produced mild local hyperthermia with a 2-6 °C temperature rise both on the cortical surface and inside the cortical bone. It also held comparable or enhanced cell performances such as cell number, viability, proliferation, migration, ALP activity, in vitro mineralization, and osteogenic genes expression. CONCLUSIONS: In-situ non-irrigated higher-speed drilling at 500 rpm using a screw drill is versatile, efficient, and thermal friendly and improves the bio-quality of bone chips. Our novel technique holds clinical translational potential in GBR application.

Electrochemiluminescent CdS Quantum Dots Biosensor for Cancer Mutation Detection at Different Positions on Linear DNA Analytes.

PCR-based techniques routinely employed for the detection of mutated linear DNA molecules, including circulating tumor DNA (ctDNA), require large nucleotide sections on both sides of the mutation for primer annealing. This means that DNA fragments with a mutation positioned closer to the extremities are unlikely to be detected. Thus, sensors capable of recognizing linear DNA with characteristic mutations closer to the ends would be advantageous over the state-of-the-art approaches. Here, an electrochemiluminescence-resonance energy transfer (ECL-RET) biosensor comprising capped CdS quantum dots and hairpin DNA probes labeled with Au nanoparticles was developed for the detection of epidermal growth factor receptor (EGFR) ctDNA carrying the critical T790M lung cancer mutation. The ECL-RET system detected different DNA molecules including single-stranded 18-nucleotides (nt) and 40-nt as well as double-stranded 100-nt with the single nucleotide polymorphism (SNP) coding for T790M located either in the middle or only 7 nt from one end. For all target DNA, the sensor's limits of detection (LODs) were in the aM range, with excellent selectivity. It was the case of 100-nt target linear ctDNA fragments with LODs of 8.1 and 3.4 aM when the EGFR T790M SNP was either in the middle or at the end, respectively. These results show that ECL-RET systems can sense mutations in DNA fragments that would remain undetected by standard techniques.

Risk factors for air embolism following computed tomography-guided percutaneous transthoracic needle biopsy: a systematic review and meta-analysis

To quantitatively analyze the risk factors for air embolism following computed tomography (CT)-guided percutaneous transthoracic needle biopsy (PTNB) and qualitatively review their characteristics. The databases of PubMed, Embase, Web of Science, Wanfang Data, VIP information, and China National Knowledge Infrastructure were searched on January 4, 2021, for studies reporting the occurrence of air embolisms following CT-guided PTNB. After study selection, data extraction, and quality assessment, the characteristics of the included cases were qualitatively and quantitatively analyzed. A total of 154 cases of air embolism following CT-guided PTNB were reported. The reported incidence was 0.06% to 4.80%, and 35 (22.73%) patients were asymptomatic. An unconscious or unresponsive state was the most common symptom (29.87%). Air was most commonly found in the left ventricle (44.81%), and 104 (67.53%) patients recovered without sequelae. Air location (P < 0.001), emphysema (P = 0.061), and cough (P = 0.076) were associated with clinical symptoms. Air location (P = 0.015) and symptoms (P < 0.001) were significantly associated with prognosis. Lesion location [odds ratio (OR): 1.85, P = 0.017], lesion subtype (OR: 3.78, P = 0.01), pneumothorax (OR: 2.16, P = 0.003), hemorrhage (OR: 3.20, P < 0.001), and lesions located above the left atrium (OR: 4.35, P = 0.042) were significant risk factors for air embolism. Based on the current evidence, a subsolid lesion, being located in the lower lobe, the presence of pneumothorax or hemorrhage, and lesions located above the left atrium were significant risk factors for air embolism.

Global burden of prostate cancer attributable to smoking among males in 204 countries and territories, 1990-2019.

INTRODUCTION: Understanding the latest global spatio-temporal pattern of prostate cancer burden attributable to smoking can help guide effective global health policy. This study aims to elucidate the trends in smoking-related prostate cancer from 1990 to 2019 using Global Burden of Disease (GBD) 2019 study data. METHODS: Data on prostate cancer attributable to smoking were extracted from Global Burden of Disease Study (GBD) 2019. The numbers and age-standardized rates on smoking-related prostate cancer mortality (ASMR) and disability-adjusted life years (ASDR) were analyzed by year, age, region, country, and socio-demographic index (SDI) level. Estimated annual percentage change (EAPC) was calculated to evaluate the temporal trends of ASMR and ASDR from 1990 to 2019. RESULTS: Of all prostate cancer deaths and DALYs globally in 2019, 6% and 6.6% were attributable to smoking, which contributed to 29,298 (95% CI 12,789 to 46,609) deaths and 571,590 (95% CI 253,490 to 917,820) disability-adjusted life-years (DALYs) in 2019. The number of smoking-related deaths and DALYs showed an upward trend, increasing by half from 1990 to 2019, while ASMR and ASDR declined in five sociodemographic indexes (SDI) regions, with the fastest decline in high SDI regions. For geographical regions, Western Europe and East Asia were the high-risk areas of prostate cancer deaths and DALYs attributable to smoking, among which China and the United States were the countries with the heaviest burden. The ASMR has decreased in all age groups, with the fastest decrease occurring in 75-79 years old. The ASMR or ASDR tended to increase in countries with the lowest SDI, but declined in countries with the highest SDI. The EAPC in ASMR or ASDR was highly negatively correlated with Human Development Index (HDI) in 2019, with coefficients 0.46. CONCLUSION: The number of smoking-related prostate cancer deaths and DALYs continued to increase globally, whereas its ASMR and ASDR have been decreasing. This substantial progress is particularly significant in developed regions and vary across geographic regions. Medical strategies to prevent and reduce the burden should be adjusted and implemented based on country-specific disease prevalence.

Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell lung cancer (NSCLC) before surgery is crucial, while there is lack of corresponding method clinically. PURPOSE: To develop and validate a model to quantitively predict the N2 lymph node metastasis in presurgical clinical stage I-II NSCLC using multiview radiomics and deep learning method. METHODS: In this study, 140 NSCLC patients were enrolled and randomly divided into training and test sets. Univariate and multiple analysis method were used step by step to establish the clinical model; Then a multiview radiomics modeling scheme was designed, in which the optimal input feature set was determined by subcategorizing radiomics features (C1: original; C2: LoG and C3: wavelet) and comparison of corresponding radiomics model. The minimum-redundancy maximum-relevance (mRMR) selection and the least absolute shrinkage and selection operator (LASSO) algorithm were used for the feature selection and construction of each radiomics model (Rad). Next, an end-to-end ResNet18 architecture and transfer learning techniques were designed to construct a deep learning model (DL). Subsequently, the screened clinical risk factors and constructed Rad and DL models were combined and compared and a nomogram was constructed. Finally, the diagnostic performance of all constructed models were evaluated and compared using receiver operating characteristic curve (ROC) analysis, Delong test, Calibration analysis, Hosmer-Lemeshow test, and decision curves, respectively. RESULTS: Carcinoma embryonic antigen (CEA) level and spiculation were screened to make up the Clinical model, while seven radiomics features in the optimal input feature set C2 + C3 were selected to construct the Rad. DL was constructed by training on 1.8 million natural images and small sample data of our N2 lymph node volume of interest (VOI) images. Except for the Clinical model, all other models showed good predictive accuracy and consistency in both training set and test set. DL (area under curve (AUC): 0.83) was better than Rad (AUC: 0.76) in predictive accuracy, but their difference was not significant (p = 0.45). The combined models showed better diagnostic performance than the model only clinical or image risk factors were used (AUC for Clinical, Rad + DL, Rad + Clinical, DL + Clinical, and Rad + DL + Clinical were respectively 0.66, 0.86, 0.82, 0.86, and 0.88). Finally, the Rad + DL + Clinical model with the best diagnostic performance was selected to draw the final nomogram for clinical use. CONCLUSION: This study proposes a nomogram based on multiview radiomics, deep learning, and clinical features that can be efficiently used to quantitively predict presurgical N2 diseases in patients with clinical stage I-II NSCLC.

Artificial intelligence for the prediction of acute kidney injury during the perioperative period: systematic review and Meta-analysis of diagnostic test accuracy.

BACKGROUND: Acute kidney injury (AKI) is independently associated with morbidity and mortality in a wide range of surgical settings. Nowadays, with the increasing use of electronic health records (EHR), advances in patient information retrieval, and cost reduction in clinical informatics, artificial intelligence is increasingly being used to improve early recognition and management for perioperative AKI. However, there is no quantitative synthesis of the performance of these methods. We conducted this systematic review and meta-analysis to estimate the sensitivity and specificity of artificial intelligence for the prediction of acute kidney injury during the perioperative period. METHODS: Pubmed, Embase, and Cochrane Library were searched to 2nd October 2021. Studies presenting diagnostic performance of artificial intelligence in the early detection of perioperative acute kidney injury were included. True positives, false positives, true negatives and false negatives were pooled to collate specificity and sensitivity with 95% CIs and results were portrayed in forest plots. The risk of bias of eligible studies was assessed using the PROBAST tool. RESULTS: Nineteen studies involving 304,076 patients were included. Quantitative random-effects meta-analysis using the Rutter and Gatsonis hierarchical summary receiver operating characteristics (HSROC) model revealed pooled sensitivity, specificity, and diagnostic odds ratio of 0.77 (95% CI: 0.73 to 0.81),0.75 (95% CI: 0.71 to 0.80), and 10.7 (95% CI 8.5 to 13.5), respectively. Threshold effect was found to be the only source of heterogeneity, and there was no evidence of publication bias. CONCLUSIONS: Our review demonstrates the promising performance of artificial intelligence for early prediction of perioperative AKI. The limitations of lacking external validation performance and being conducted only at a single center should be overcome. TRIAL REGISTRATION: This study was not registered with PROSPERO.

Evaluation of volume changes following lateral window maxillary sinus floor elevation using Minics software.

Background: Significant volume changes at the site of lateral window maxillary sinus floor elevation have been reported 6 months postoperatively, with stabilization thereafter. However, at present, there is no consensus regarding the gold standard to assess the shape and volume of the bone graft site after implantation. This study aimed to analyze volume changes in the lateral window maxillary sinus floor elevation region using Minics software. Methods: We analyzed 40 patients who underwent lateral window maxillary sinus floor elevation surgery at the Stomatology Department of Binhaiwan Central Hospital, Dongguan, China between 2017 and 2020. Twenty patients underwent lateral window maxillary sinus floor elevation with simultaneous implantation, while 20 patients underwent lateral window maxillary sinus floor elevation with delayed implantation 6 months later. Minics software was used for three-dimensional analysis of the elevation site on the day after surgery (T1) and 6 months after surgery (T2) in both groups. Results: The elevation site volume was reduced 6 months after lateral window maxillary sinus floor elevation. The differences in the length, width, height from the tip, and volume of the implant between T1 and T2 were statistically significant. Conclusions: The length, width, height, and volume of the lateral window maxillary sinus floor elevation region were reduced using Minics software, suggesting that the volume of the elevation site should be enlarged as much as possible during the operation to prevent volume shrinkage.

A nomogram predicting the severity of COVID-19 based on initial clinical and radiologic characteristics.

Aim: This study aimed to build an easy-to-use nomogram to predict the severity of COVID-19. Patients & methods: From December 2019 to January 2020, patients confirmed with COVID-19 in our hospital were enrolled. The initial clinical and radiological characteristics were extracted. Univariate and multivariate logistic regression were used to identify variables for the nomogram. Results: In total, 104 patients were included. Based on statistical analysis, age, levels of neutrophil count, creatinine, procalcitonin and numbers of involved lung segments were identified for nomogram. The area under the curve was 0.939 (95% CI: 0.893-0.984). The calibration curve showed good agreement between prediction of nomogram and observation in the primary cohort. Conclusion: An easy-to-use nomogram with great discrimination was built to predict the severity of COVID-19.

CT-Guided Percutaneous Core Needle Biopsy in Typing and Subtyping Lung Cancer: A Comparison to Surgery.

Background: Lung cancer histologic types and subtypes are closely associated with treatment selection and prognosis prediction. In this study, we aim to evaluate the suitability of computed tomography-guided percutaneous core needle biopsy (CT-guided PCNB) in typing and subtyping lung cancer. Methods: From August 2007 to December 2015, the patients who underwent CT-guided PCNB and lung lesion resection were retrospectively collected and analyzed. All pathological sections were reassessed in consensus by 2 junior pathologists (group A) and 2 senior pathologists (group B), respectively. All cases were diagnosed on 3 levels: first, malignant and benign diagnosis; second, histologic types diagnosis; and third, histologic subtypes diagnosis and compared with surgery results. Pearson chi-square test was used to compare the differences of diagnostic accuracy between pathologists in group A and group B. Results: A cohort of 160 patients was included in this study. On the first level, the diagnostic accuracy was 90.63% (group A) and 94.38% (group B), (P = .20). On the second level, the diagnostic accuracy for malignant lesions, adenocarcinoma (ADC), and squamous cell carcinoma (SQC) were, respectively, 72.66%, 84.72%, and 69.05% (group A) and 76.98%, 90.28%, and 71.43% (group B) (P > .05). On the third level, the diagnostic accuracy for ADC subtypes were 26.39% (group A) and 55.56% (group B) (P < 0.01); for SQC subtypes were 28.57% (group A) and 38.10% (group B) (P = 0.36). Conclusion: Small specimens obtained by CT-guided PCNB were suitable for the diagnosis of lung cancer histologic types, which may contribute to the selection of a suitable treatment strategy for the unresectable lung cancers. While for the diagnosis of subtypes, discussion with experienced pathologists was recommended.

Comparison of CT-Guided Core Needle Biopsy in Pulmonary Ground-Glass and Solid Nodules Based on Propensity Score Matching Analysis.

Purpose: To compare the diagnostic accuracy and safety of computed tomography (CT)-guided core needle biopsy (CNB) between pulmonary ground-glass and solid nodules using propensity score matching (PSM) method and determine the relevant risk factors. Methods: This was a single-center retrospective cohort study using data from 665 patients who underwent CT-guided CNB of pulmonary nodules in our hospital between May 2019 and May 2021, including 39 ground-glass nodules (GGNs) and 626 solid nodules. We used a 1:4 PSM analysis to compared the diagnostic yields and complications rates of CT-guided CNB between 2 groups. Results: After PSM, 170 cases involved in the comparison (34 GGNs vs 136 solid nodules) were randomly matched (1:4) by patient demographics, clinical history, lesion characteristics, and procedure-related factors. There was no statistically significant difference in the diagnostic yields and complications rates between 2 groups. Significant pneumothorax incidence increase was noted at small lesion size, deep lesion location, and traversing interlobar fissure (P < .05). Post-biopsy hemorrhage was a protective factor for pneumothorax (P < .05). The size/proportion of consolidation of GGN did not influence the diagnostic accuracy and complication incidence (P > .05). Conclusions: The accuracy and safety of CT-guided CNB were comparable for ground-glass and solid nodules and the size/proportion of consolidation of GGN may be not a relevant risk factor. The biopsy should avoid traversing interlobar fissure as far as possible. Smaller lesion size and deeper lesion location may lead to higher pneumothorax rate and post-biopsy hemorrhage may be a protective factor for pneumothorax.

A Predictive Model to Differentiate Between Second Primary Lung Cancers and Pulmonary Metastasis.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram for differentiating second primary lung cancers (SPLCs) from pulmonary metastases (PMs). MATERIALS AND METHODS: A total of 261 lesions from 253 eligible patients were included in this study. Among them, 195 lesions (87 SPLCs and 108 PMs) were used in the training cohort to establish the diagnostic model. Twenty-one clinical or imaging features were used to derive the model. Sixty-six lesions (32 SPLCs and 34 PMs) were included in the validation set. RESULTS: After analysis, age, lesion distribution, type of lesion, air bronchogram, contour, spiculation, and vessel convergence sign were considered to be significant variables for distinguishing SPLCs from PMs. Subsequently, these variables were selected to establish a nomogram. The model showed good distinction in the training set (area under the curve = 0.97) and the validation set (area under the curve = 0.92). CONCLUSION: This study found that the nomogram calculated from clinical and radiological characteristics could accurately classify SPLCs and PMs.

An electrochemiluminescence resonance energy transfer biosensor for the detection of circulating tumor DNA from blood plasma.

A liquid biopsy is a noninvasive approach for detecting double-stranded circulating tumor DNA (ctDNA) of 90-320 nucleotides in blood plasma from patients with cancer. Most techniques employed for ctDNA detection are time consuming and require expensive DNA purification kits. Electrochemiluminescence resonance energy transfer (ECL-RET) biosensors exhibit high sensitivity, a wide response range, and are promising for straightforward sensing applications. Until now, ECL-RET biosensors have been designed for sensing short single-stranded oligonucleotides of less than 45 nucleotides. In this work, an ECL-RET biosensor comprising graphitic carbon nitride quantum dots was assessed for the amplification-free detection in the blood plasma of DNA molecules coding for the EGFR L858R mutation, which is associated with non-small-cell lung cancer. Following a low-cost pre-treatment, the highly specific ECL-RET biosensor quantified double-stranded EGFR L858R DNA of 159 nucleotides diluted into the blood within a linear range of 0.01 fM to 1 pM, demonstrating its potential for noninvasive biopsies.

Parentage Analysis in Giant Grouper (Epinephelus lanceolatus) Using Microsatellite and SNP Markers from Genotyping-by-Sequencing Data.

Pedigree information is necessary for the maintenance of diversity for wild and captive populations. Accurate pedigree is determined by molecular marker-based parentage analysis, which may be influenced by the polymorphism and number of markers, integrity of samples, relatedness of parents, or different analysis programs. Here, we described the first development of 208 single nucleotide polymorphisms (SNPs) and 11 microsatellites for giant grouper (Epinephelus lanceolatus) taking advantage of Genotyping-by-sequencing (GBS), and compared the power of SNPs and microsatellites for parentage and relatedness analysis, based on a mixed family composed of 4 candidate females, 4 candidate males and 289 offspring. CERVUS, PAPA and COLONY were used for mutually verification. We found that SNPs had a better potential for relatedness estimation, exclusion of non-parentage and individual identification than microsatellites, and > 98% accuracy of parentage assignment could be achieved by 100 polymorphic SNPs (MAF cut-off < 0.4) or 10 polymorphic microsatellites (mean Ho = 0.821, mean PIC = 0.651). This study provides a reference for the development of molecular markers for parentage analysis taking advantage of next-generation sequencing, and contributes to the molecular breeding, fishery management and population conservation.

Low-Intensity Focused Ultrasound-Augmented Multifunctional Nanoparticles for Integrating Ultrasound Imaging and Synergistic Therapy of Metastatic Breast Cancer.

The metastasis of breast cancer is believed to have a negative effect on its prognosis. Benefiting from the remarkable deep-penetrating and noninvasive characteristics, sonodynamic therapy (SDT) demonstrates a whole series of potential leading to cancer treatment. To relieve the limitation of monotherapy, a multifunctional nanoplatform has been explored to realize the synergistic treatment efficiency. Herein, we establish a novel multifunctional nano-system which encapsulates chlorin e6 (Ce6, for SDT), perfluoropentane (PFP, for ultrasound imaging), and docetaxel (DTX, for chemotherapy) in a well-designed PLGA core-shell structure. The synergistic Ce6/PFP/DTX/PLGA nanoparticles (CPDP NPs) featured with excellent biocompatibility and stability primarily enable its further application. Upon low-intensity focused ultrasound (LIFU) irradiation, the enhanced ultrasound imaging could be revealed both in vitro and in vivo. More importantly, combined with LIFU, the nanoparticles exhibit intriguing antitumor capability through Ce6-induced cytotoxic reactive oxygen species as well as DTX releasing to generate a concerted therapeutic efficiency. Furthermore, this treating strategy actives a strong anti-metastasis capability by which lung metastatic nodules have been significantly reduced. The results indicate that the SDT-oriented nanoplatform combined with chemotherapy could be provided as a promising approach in elevating effective synergistic therapy and suppressing lung metastasis of breast cancer.