Recent symptomatic Omicron infection reduced COVID-19 pneumonia risk during reinfection: A computed tomography-based cohort study.

OBJECTIVES: SARS-CoV-2 infection could cause persistent lung injury or indicate potential genetic susceptibilities. Although infection-elicited hybrid immunity could protect against severe COVID-19, it remains unknown whether recent infection could reduce pneumonia risk during reinfection due to insufficient viral and chest computed tomography (CT) screening. METHODS: A total of 15,598 patients, 96% fully vaccinated and 52% boosted, from Xiangyang, China, who had symptomatic COVID-19 and chest CT scans during the first Omicron BF.7 wave in December 2022 to January 2023, were followed through the second Omicron XBB.1.5 wave between May and August 2023. A total of 17,968 second-wave patients with COVID-19 with chest CT scans but without previous symptomatic COVID-19 were enrolled as first-time infection controls. RESULTS: A total of 19.6% (3,061 of 15,598) first-wave patients were diagnosed with pneumonia. Among second-wave reinfected patients, only 0.2% (four of 2202) developed pneumonia, which was lower than the 1.7% (311 of 17,968) pneumonia prevalence among the second-wave first-time patients, with an adjusted relative risk of 0.11 (95% confidence interval: 0.04-0.29). A total of 1.3% (40 of 3,039) first-wave pneumonia survivors showed residual abnormal patterns in follow-up CT scans within 8 months after pneumonia diagnosis. CONCLUSIONS: In a highly vaccinated population, previous symptomatic Omicron infection within 8 months reduced pneumonia risk during reinfection. Uninfected individuals might need up-to-date vaccination to reduce pneumonia risk.

Deep learning models for thyroid nodules diagnosis of fine-needle aspiration biopsy: a retrospective, prospective, multicentre study in China.

BACKGROUND: Accurately distinguishing between malignant and benign thyroid nodules through fine-needle aspiration cytopathology is crucial for appropriate therapeutic intervention. However, cytopathologic diagnosis is time consuming and hindered by the shortage of experienced cytopathologists. Reliable assistive tools could improve cytopathologic diagnosis efficiency and accuracy. We aimed to develop and test an artificial intelligence (AI)-assistive system for thyroid cytopathologic diagnosis according to the Thyroid Bethesda Reporting System. METHODS: 11 254 whole-slide images (WSIs) from 4037 patients were used to train deep learning models. Among the selected WSIs, cell level was manually annotated by cytopathologists according to The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) guidelines of the second edition (2017 version). A retrospective dataset of 5638 WSIs of 2914 patients from four medical centres was used for validation. 469 patients were recruited for the prospective study of the performance of AI models and their 537 thyroid nodule samples were used. Cohorts for training and validation were enrolled between Jan 1, 2016, and Aug 1, 2022, and the prospective dataset was recruited between Aug 1, 2022, and Jan 1, 2023. The performance of our AI models was estimated as the area under the receiver operating characteristic (AUROC), sensitivity, specificity, accuracy, positive predictive value, and negative predictive value. The primary outcomes were the prediction sensitivity and specificity of the model to assist cyto-diagnosis of thyroid nodules. FINDINGS: The AUROC of TBSRTC III+ (which distinguishes benign from TBSRTC classes III, IV, V, and VI) was 0·930 (95% CI 0·921-0·939) for Sun Yat-sen Memorial Hospital of Sun Yat-sen University (SYSMH) internal validation and 0·944 (0·929 - 0·959), 0·939 (0·924-0·955), 0·971 (0·938-1·000) for The First People's Hospital of Foshan (FPHF), Sichuan Cancer Hospital & Institute (SCHI), and The Third Affiliated Hospital of Guangzhou Medical University (TAHGMU) medical centres, respectively. The AUROC of TBSRTC V+ (which distinguishes benign from TBSRTC classes V and VI) was 0·990 (95% CI 0·986-0·995) for SYSMH internal validation and 0·988 (0·980-0·995), 0·965 (0·953-0·977), and 0·991 (0·972-1·000) for FPHF, SCHI, and TAHGMU medical centres, respectively. For the prospective study at SYSMH, the AUROC of TBSRTC III+ and TBSRTC V+ was 0·977 and 0·981, respectively. With the assistance of AI, the specificity of junior cytopathologists was boosted from 0·887 (95% CI 0·8440-0·922) to 0·993 (0·974-0·999) and the accuracy was improved from 0·877 (0·846-0·904) to 0·948 (0·926-0·965). 186 atypia of undetermined significance samples from 186 patients with BRAF mutation information were collected; 43 of them harbour the BRAFV600E mutation. 91% (39/43) of BRAFV600E-positive atypia of undetermined significance samples were identified as malignant by the AI models. INTERPRETATION: In this study, we developed an AI-assisted model named the Thyroid Patch-Oriented WSI Ensemble Recognition (ThyroPower) system, which facilitates rapid and robust cyto-diagnosis of thyroid nodules, potentially enhancing the diagnostic capabilities of cytopathologists. Moreover, it serves as a potential solution to mitigate the scarcity of cytopathologists. FUNDING: Guangdong Science and Technology Department. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Predicting preoperative muscle invasion status for bladder cancer using computed tomography-based radiomics nomogram.

OBJECTIVES: The aim of the study is to assess the efficacy of the established computed tomography (CT)-based radiomics nomogram combined with radiomics and clinical features for predicting muscle invasion status in bladder cancer (BCa). METHODS: A retrospective analysis was conducted using data from patients who underwent CT urography at our institution between May 2018 and April 2023 with urothelial carcinoma of the bladder confirmed by postoperative histology. There were 196 patients enrolled in all, and each was randomized at random to either the training cohort (n = 137) or the test cohort (n = 59). Eight hundred fifty-one radiomics features in all were retrieved. For feature selection, the significance test and least absolute shrinkage and selection operator (LASSO) approaches were utilized. Subsequently, the radiomics score (Radscore) was obtained by applying linear weighting based on the selected features. The clinical and radiomics model, as well as radiomics-clinical nomogram were all established using logistic regression. Three models were evaluated using analysis of the receiver operating characteristic curve. An area under the curve (AUC) and 95% confidence intervals (CI) as well as specificity, sensitivity, accuracy, negative predictive value, and positive predictive value were included in the analysis. Radiomics-clinical nomogram's performance was assessed based on discrimination, calibration, and clinical utility. RESULTS: After obtaining 851 radiomics features, 12 features were ultimately selected. Histopathological grading and tortuous blood vessels were included in the clinical model. The Radscore and clinical histopathology grading were among the final predictors in the unique nomogram. The three models had an AUC of 0.811 (95% CI, 0.742-0.880), 0.845 (95% CI, 0.781-0.908), and 0.896 (95% CI, 0.846-0.947) in the training cohort and in the test cohort they were 0.808 (95% CI, 0.703-0.913), 0.847 (95% CI, 0.739-0.954), and 0.887 (95% CI, 0.803-0.971). According to the DeLong test, the radiomics-clinical nomogram's AUC in the training cohort substantially differed from that of the clinical model (AUC: 0.896 versus 0.845, p = 0.015) and the radiomics model (AUC: 0.896 versus 0.811, p = 0.002). The Delong test in the test cohort revealed no significant difference among the three models. CONCLUSIONS: CT-based radiomics-clinical nomogram can be a useful tool for quantitatively predicting the status of muscle invasion in BCa.

Potential diagnostic value of quantitative superb microvascular imaging in premalignant and malignant cervical lesions.

Objective: The purpose of this study was to assess the diagnostic efficacy of the vascular index (VI) on superb microvascular imaging (SMI) in distinguishing normal uterine cervical epithelium, high-grade cervical intraepithelial neoplasia (CIN), and cervical cancer. Methods: The retrospective study included women with pathology-confirmed CIN or cervical cancer, who underwent transvaginal ultrasound and SMI between April 2021 and October 2022. The SIM manifestations of normal cervix and cervical lesions were reviewed. SIM were measured and converted into vascular index (VI) which compared between cervical lesions and control groups. We have retrospectively compared ultrasound features of cervical lesions and characteristics of patients. Measurement reliability was evaluated by intra class correlation coefficient (ICC). Results: A total of 235 consecutive females were enrolled, comprising 38 with high-grade CIN, 96 with cervical cancer, and 101 with a normal uterine cervix. The microvascular architecture exhibited significant variations between premalignant and malignant cervical lesions. Branch-like patterns were predominantly observed in high-grade CIN, while crab claw-like and fireball-like patterns were more commonly associated with cervical cancer. The median VI of cervical cancer (34.7 ± 10.3) was significantly higher than that of high-grade CIN (17.6 ± 4.2) (P < 0.001). Moreover, the VI values of cervical cancer differed significantly among different FIGO stages and pathological types (P < 0.001 and P = 0.003, respectively). The VI demonstrated superior diagnostic performance for cervical lesions compared to vascular patterns (AUC = 0.974 and 0.969, respectively). Using a cut-off value of 25.5, the VI yielded a sensitivity of 82.3% and a specificity of 99.3% for cervical lesion detection. Conclusions: The SMI parameter (VI) exhibited a significantly higher value in cervical cancer compared to high-grade CIN, with a high level of agreement among observers. These findings suggest that quantitative SMI holds promise as an imaging technique for the detection and characterization of cervical lesions.

The Novel Role of Cytomorphology from Ultrasound-Guided Fine Needle Aspiration Cytology in Evaluating the Status of Prognostic Factors including Estrogen Receptor, Progesterone Receptor and HER2 in Breast Cancer.

It is well established that estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2) could be regarded as prognostic factors in breast cancer. Ultrasound-guided fine needle aspiration cytology (FNAC) has revolutionized the management of cancers, providing less invasive and quick diagnostic method. There are hardly any studies on the correlation between cytomorphology and prognostic biomarkers. We retrospectively analyzed the immunohistochemistry and the fluorescence in situ hybridization of breast cancer specimens from 252 patients, who have been diagnosed as breast cancer at our hospital. Morphological features of cytology smears were scored. The relationship between cytological features and three biomarkers were analyzed. Based on this, we developed a system to predict the status of biomarkers. The results indicated that some cytological parameters, especially the features of nucleoli, were distinctively related to the makers' expression. In the novel scoring system, a cutoff of 12.0 provided a statistical discrimination for cytological grading. We concluded that cytomorphological features were associated with prognostic factors. The HR+ neoplasms showed scattered micronucleoli, while HER2+ neoplasms demonstrated centered macronucleoli. We summarized a scoring system to predict the status of three factors. This may help us to broaden the application of breast cancer cytology.

SARS-CoV-2 immunity and functional recovery of COVID-19 patients 1-year after infection.

The long-term immunity and functional recovery after SARS-CoV-2 infection have implications in preventive measures and patient quality of life. Here we analyzed a prospective cohort of 121 recovered COVID-19 patients from Xiangyang, China at 1-year after diagnosis. Among them, chemiluminescence immunoassay-based screening showed 99% (95% CI, 98-100%) seroprevalence 10-12 months after infection, comparing to 0.8% (95% CI, 0.7-0.9%) in the general population. Total anti-receptor-binding domain (RBD) antibodies remained stable since discharge, while anti-RBD IgG and neutralization levels decreased over time. A predictive model estimates 17% (95% CI, 11-24%) and 87% (95% CI, 80-92%) participants were still 50% protected against detectable and severe re-infection of WT SARS-CoV-2, respectively, while neutralization levels against B.1.1.7 and B.1.351 variants were significantly reduced. All non-severe patients showed normal chest CT and 21% reported COVID-19-related symptoms. In contrast, 53% severe patients had abnormal chest CT, decreased pulmonary function or cardiac involvement and 79% were still symptomatic. Our findings suggest long-lasting immune protection after SARS-CoV-2 infection, while also highlight the risk of immune evasive variants and long-term consequences for COVID-19 survivors.

Deep neural networks could differentiate Bethesda class III versus class IV/V/VI.

BACKGROUND: Ultrasound (US) is the most commonly used radiologic modality to identify and characterize thyroid nodules. Many nodules subsequently undergo fine needle aspiration to further characterize the nodule and determine appropriate treatment. The fine needle aspirate is most commonly classified using the Bethesda System for Reporting Thyroid Cytology (TBSRTC). It can sometimes be difficult to differentiate Bethesda class III lesions (atypia of undetermined significance/follicular lesion of undetermined significance) from Bethesda class IV, V and VI (malignant nodules). However, differentiation is important as clinical management differs between the two groups. The purpose of this study was to introduce machine learning methods to help radiologists differentiate Bethesda class III from Bethesda class VI, V and VI lesions. METHODS: The authors collected 467 thyroid nodules with cytopathology results. US features were summarized using the 2017 ACR (American College of Radiology) Thyroid Imaging Reporting And Data System (TIRADS). Machine learning models [logistic regression, gradient boost, support vector machine (SVM), random forest and deep neural networks (DNN)] were created to classify Bethesda class III vs class IV/V/VI. RESULTS: DNN outperformed other machine learning classifiers and obtained the highest accuracy and specificity to classify thyroid nodules as either Bethesda III or IV/V/VI nodules using multiple US features. CONCLUSIONS: Machine learning/deep learning approaches could help differentiate Bethesda III nodules from IV/V/VI using US features which may benefit treatment decisions.

ErbB3 Ligand Heregulin1 Is a Major Mitogenic Factor for Uncontrolled Lung Cancer Cell Proliferation.

There are seven ligands for the epidermal growth factor receptor (EGFR) ErbB1 and two ligands for ErbB3. EGFR can form a homodimer or a heterodimer with ErbB3. In this study, we investigated whether homodimers or heterodimers, and which ligand, play a major role in cancer development, with the goal of ultimately identifying therapeutic targets. We demonstrated that the ErbB3 ligand heregulin1 is the strongest mitogenic factor for non-small cell lung cancer cells and is more potent in activating EGFRmut-ErbB3 heterodimers than EGFRwt-ErbB3 heterodimers. We discovered that four of the seven EGFR ligands inhibited heregulin1-induced EGFRwt-ErbB3 activation and cell proliferation by promoting dephosphorylation of heregulin1-induced ErbB3 phosphorylation, whereas the other three did not exhibit such inhibition. Importantly, those four EGFR ligands did not inhibit heregulin1-induced EGFRmut-ErbB3 activation and proliferation of cells with EGFR mutants. We demonstrated that ErbB3 was overexpressed in the lung cancer cells but not in the adjacent normal alveoli or stromal tissue. EGFR and heregulin1 were also highly expressed in lung cancer cells. We conclude that the overexpression of heregulin1, ErbB3, and EGFR mutant renders uncontrolled cell proliferation.

Perineural invasion in early-stage cervical cancer and its relevance following surgery.

Perineural invasion (PNI) is the neoplastic invasion of nerves by cancer cells, a process that has attracted attention as a novel prognostic factor for cancer. The present study aimed to investigate the prognostic value of PNI in patients with early-stage cervical cancer (International Federation of Gynecology and Obstetrics stage IA2-IIA). A total of 210 patients who underwent radical hysterectomy and pelvic lymphadenectomy between 2007 and 2012 were included in the current study, of whom 8.57% (18/210) exhibited PNI. Patients with PNI were more likely to exhibit adverse histopathological features, such as increased tumor size, depth of stromal invasion, parametrial invasion, lymphovascular space invasion and lymph nodes metastases (all P<0.05). Patients with PNI exhibited shorter disease-free and overall survival (P=0.002 and P=0.017, respectively). However, PNI was not identified as an independent risk factor for either recurrence or death by multivariate analysis. Furthermore, 88.9% (16/18) of patients with PNI received adjuvant therapy following surgery. PNI was significantly associated with well-established indicators for adjuvant therapy. In conclusion, PNI was associated with multiple high-risk factors and its presence was indicative of a poor outcome in patients with early-stage cervical cancer, which may influence management decisions regarding adjuvant therapy.

Papillary thyroid cancer located in malignant struma ovarii with omentum metastasis: a case report and review of the literature.

BACKGROUND: The present of malignant transformation in struma ovarii is exceedingly rare. Malignant struma ovarii is usually asymptomatic and infrequently diagnosed preoperatively. Because of its rarity, there is no consensus about diagnosis and management in the literature. CASE PRESENTATION: A 40-year-old female presented for her obstetric examination with an incidental finding of a pelvic mass. Patient was asymptomatic at presentation. A follow-up ultrasound confirmed the presence of a 3-cm mass in the left adnexa. Patient underwent a cytoreductive surgery (hysterectomy, bilateral salpingectomy and oophorectomy, omentectomy, appendectomy, and pelvic lymphadenectomy). Histopathology revealed a malignant struma ovarii with a focus of papillary thyroid carcinoma and the omentum metastasis. The patient with stage FIGO IIIc received 6 cycles of paclitaxel/carboplatin regimen after surgery. The patient subsequently had a thyroid scan that was normal with normal thyroid function. At a follow-up of 12 months, she is alive, in good clinical condition, and disease-free. CONCLUSIONS: Because of the rarity of these tumors and their lack of firm prognostic factors, treatment decisions should be made individually, based on pathologic and clinical parameters.

[Evidence of perineural invasion on early-stage cervical cancer and prognostic significance].

OBJECTIVE: To evaluate the incidence and significance of perineural invasion (PNI) in cervical cancer. METHODS: Retrospective chart review of patients with cervical cancer (stages Ia2-IIb) who underwent radical hysterectomy and pelvic lymphadenectomy from 2007 to 2012. To evaluate the incidence and significance of PNI in cervical and uterine tissues by microscopic examination. RESULTS: A total of 238 patients were included, 9.2% (22/238) patients with PNI in the cervical stroma. Patients with PNI were more likely to have adverse histopathologic features, including lymphoma vascular space invasion, parametrical invasion, depth of invasion, tomor size and lymph nodes metastases (all P < 0.05). PNI were independent of age, international federation of gynecology and obstetrics (FIGO) stage, histopathology type and grade, and positive vaginal margin (all P > 0.05). Patients with PNI had shorter disease-free and overall survival (P = 0.002 and P = 0.008, respectively). On multivariate analysis, risk factors for recurrence and death included parametrical invasion and depth of invasion (P < 0.05). Similarly, risk factors for recurrence included lymph nodes metastases (P = 0.024). However, PNI was not identified as an independent risk factor for either recurrence or death (P > 0.05). CONCLUSIONS: PNI exists in early cervical cancer. PNI is associated with tumor size, depth of invasion, parametrical invasion, lymphoma vascular space invasion and lymph nodes metastases. PNI represente a decreasing disease-free and overall survival in patients with early-stage cervical cancer, and is independently associated with multiple high-risk factors, which be informed management decisions regarding adjuvant therapy.

Polymer-fullerene bulk-heterojunction solar cells.

Solution-processed bulk heterojunction organic photovoltaic (OPV) devices have gained serious attention during the last few years and are established as one of the leading next generation photovoltaic technologies for low cost power production. This article reviews the OPV development highlights of the last two decades, and summarizes the key milestones that have brought the technology to today's efficiency performance of over 7%. An outlook is presented on what will be required to drive this young photovoltaic technology towards the next major milestone, a 10% power conversion efficiency, considered by many to represent the efficiency at which OPV can be adopted in wide-spread applications. With first products already entering the market, sufficient lifetime for the intended application becomes more and more critical, and the status of OPV stability as well as the current understanding of degradation mechanisms will be reviewed in the second part of this article.

Nanostructure dependence of field-effect mobility in regioregular poly(3-hexylthiophene) thin film field effect transistors.

Low polydispersity regioregular polythiophenes with number average molecular weights ranging from 2 to 13 kDa were cast under the same conditions from solution to form a series of field effect transistors (FETs). Tapping mode AFM and grazing incidence small-angle X-ray scattering revealed that in all cases the polymers formed regular nanofibrillar morphologies with the width of nanofibrils proportional to the weight average contour length of polymer chains, indicating that conjugated backbones were oriented perpendicular to the nanofibril axes. FET charge carrier mobilities exhibited exponential dependence on nanofibril width, pointing to the decisive role of extended conjugated pathways in charge transport.

Self-assembly of pODMA-b-ptBA-b-pODMA triblock copolymers in bulk and on surfaces. A quantitative SAXS/AFM comparison.

The phase state of a series of poly(n-octadecyl methacrylate)-b-poly(tert-butyl acrylate)-b-poly(n-octadecyl methacrylate) (pODMA-b-ptBA-b-pODMA) triblock copolymers, synthesized through atom transfer radical polymerization, has been investigated in bulk and on surfaces using small-angle X-ray scattering and atomic force microscopy, respectively. The mean-field theory was employed to construct the bulk phase diagram. Excellent agreement was found between the bulk and surface morphologies as well as for the domain spacing (domain spacing scaled as d approximately equal to N(0.64)), suggesting that the strong polymer-polymer interactions in bulk are also the dominant interactions on surfaces.