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Abstract This study aims to develop a super-resolution (SR) algorithm tailored specifically for enhancing the image quality and resolution of early cervical cancer (CC) magnetic resonance imaging (MRI) images. The proposed method is subjected to both qualitative and quantitative analyses, thoroughly investigating its performance across various upscaling factors and assessing its impact on medical image segmentation tasks. The innovative SR algorithm employed for reconstructing early CC MRI images integrates complex architectures and deep convolutional kernels. Training is conducted on matched pairs of input images through a multi-input model. The research findings highlight the significant advantages of the proposed SR method on two distinct datasets at different upscaling factors. Specifically, at a 2× upscaling factor, the sagittal test set outperforms the state-of-the-art methods in the PSNR index evaluation, second only to the hybrid attention transformer, while the axial test set outperforms the state-of-the-art methods in both PSNR and SSIM index evaluation. At a 4× upscaling factor, both the sagittal test set and the axial test set achieve the best results in the evaluation of PNSR and SSIM indicators. This method not only effectively enhances image quality, but also exhibits superior performance in medical segmentation tasks, thereby providing a more reliable foundation for clinical diagnosis and image analysis.

Abstract Backgrounds Mycoplasma pneumoniae (M. pneumoniae) is a common pathogen causing respiratory diseases in children. This study aimed to characterize epidemiological and disease severity shifts of M. pneumoniae: infections in Guangzhou, China during and after the coronavirus disease 2019 (COVID-19) pandemic. Methods Throat swab samples were obtained from 5405 hospitalized patients with symptoms of acute respiratory infections to detect M. pneumoniae. Differences in epidemiological and clinical characteristics of M. pneumoniae: infections were investigated during 2020–2022 and after COVID-19 pandemic (2023). Results M. pneumoniae were detected in 849 (15.6%, 849/5405) patients. The highest annual positive rate was 29.4% (754/2570) in 2023, followed by 5.3% (72/1367) in 2022, 1.2% (12/1015) in 2021, and 2.0% (11/553) in 2020, with significantly increasing annual prevalence from 2020 to 2023. M. pneumoniae incidence peaked between July and December post-COVID-19 pandemic in 2023, with the highest monthly positive rate (56.4%, 165/293). Clinical characteristics and outcomes of patients with M. pneumoniae did not vary between periods during and after COVID-19 pandemic except that patients with M. pneumoniae post-COVID-19 pandemic were more likely to develop fever. Patients with severe M. pneumoniae pneumonia (SMPP) were more likely to develop respiratory complications, myocardial damage, and gastrointestinal dysfunction than those with non-SMPP. Patients with SMPP had lower lymphocytes, CD3+ T cells, CD4+ T cells, CD8+ T cells, B cells, and higher IL-4, IL-6, IL-10 levels than those with non-SMPP. Bronchoalveolar lavage fluid specimens from infected patients were obtained to identify macrolide resistance mutations. Macrolide-resistant M. pneumoniae (MRMP) proportion in 2023 was 91.1% (215/236). Conclusion Outbreaks of M. pneumoniae: occurred in Guangzhou, China in 2023 upon Non-pharmaceutical interventions easing. Despite the increasing incidence of M. pneumoniae, the disease severity remained similar during and after the COVID-19 pandemic.

Epidermal Growth Factor Receptor-Tyrosine Kinase Inhibitors (EGFR-TKIs) are a class of oral targeted anticancer drugs that have been demonstrated to significantly inhibit tumor progression and improve clinical prognosis in patients diagnosed with EGFR-mutated tumors, particularly in those with non-small cell lung cancer. However, the sustained usage of EGFR-TKIs may cause potential cardiotoxicity, thus limiting their applicability. The primary objective of this review is to systematically analyze the evolving landscape of research pertaining to EGFR-TKI-induced cardiotoxicity and elucidate its underlying mechanisms, such as PI3K signaling pathway inhibition, ion channel blockade, oxidative stress, inflammatory responses, and apoptosis. Additionally, the review includes an exploration of risk assessment for cardiotoxicity induced by EGFR-TKIs, along with management and response strategies. Prospective research directions are outlined, emphasizing the need for more accurate predictors of cardiotoxicity and the development of innovative intervention strategies. In summation, this review consolidates recent research advances, illuminates the risks associated with EGFR-TKI-induced cardiac toxicity and presents crucial insights for refining clinical dosage protocols, optimizing patient management strategies, and unraveling the intricate mechanisms governing EGFR-TKI-induced cardiotoxicity.

Abstract Background Chest computed tomography (CT) image quality impacts radiologists’ diagnoses. Pre-diagnostic image quality assessment is essential but labor-intensive and may have human limitations (fatigue, perceptual biases, and cognitive biases). This study aims to develop and validate a deep learning (DL)-driven multi-view multi-task image quality assessment (M $$^2$$ 2 IQA) method for assessing the quality of chest CT images in patients, to determine if they are suitable for assessing the patient’s physical condition. Methods This retrospective study utilizes and analyzes chest CT images from 327 patients. Among them, 1613 images from 286 patients are used for model training and validation, while the remaining 41 patients are reserved as an additional test set for conducting ablation studies, comparative studies, and observer studies. The M $$^2$$ 2 IQA method is driven by DL technology and employs a multi-view fusion strategy, which incorporates three scanning planes (coronal, axial, and sagittal). It assesses image quality for multiple tasks, including inspiration evaluation, position evaluation, radiation protection evaluation, and artifact evaluation. Four algorithms (pixel threshold, neural statistics, region measurement, and distance measurement) have been proposed, each tailored for specific evaluation tasks, with the aim of optimizing the evaluation performance of the M $$^2$$ 2 IQA method. Results In the additional test set, the M $$^2$$ 2 IQA method achieved 87% precision, 93% sensitivity, 69% specificity, and a 0.90 F1-score. Extensive ablation and comparative studies have demonstrated the effectiveness of the proposed algorithms and the generalization performance of the proposed method across various assessment tasks. Conclusion This study develops and validates a DL-driven M $$^2$$ 2 IQA method, complemented by four proposed algorithms. It holds great promise in automating the assessment of chest CT image quality. The performance of this method, as well as the effectiveness of the four algorithms, is demonstrated on an additional test set.

Abstract Objective Under the prevention and control measures of COVID‐19, the epidemiological situation of respiratory pathogens is not well known. Understanding the patterns of respiratory pathogens epidemiology under the prevention and control measures of COVID‐19 is important to guide resource allocation for existing and future treatment and prevention strategies. Methods In total, 659 fever outpatients nasopharyngeal swabs were collected at fever illness onset during June in 2022 at the First Hospital of Guangzhou Medical University. Swabs were tested by real‐time fluorescent single‐tube multiplex polymerase chain reaction (PCR) for 12 respiratory pathogens. Moreover, 108 of the 659 swabs were tested for influenza virus antigen. Results At least one pathogen was detected in 477 (72.38%) of 659 fever outpatients with multiple pathogens identified in 25 (3.79%). The highest multiple infectious pattern is parainfluenza virus in combination with influenza (five cases). Influenza A virus (IFA), human rhinovirus (HRV), and parainfluenza virus are the three leading virus pathogens with proportions of 64.64%, 5.01%, and 2.88%. School‐age children and adult groups have the highest pathogens positivity rate of 81.28% and 83.87%. Conclusion A high proportion of adolescents and adults has respiratory pathogens detected during fever illnesses during June in 2022 under the prevention and control of COVID‐19. These data indicate that diagnosis, prevention, and control of respiratory tract infection should be paid attention under the prevention and control of COVID‐19.

Abstract To classify early endometrial cancer (EC) on sagittal T2-weighted images (T2WI) by determining the depth of myometrial infiltration (MI) using a computer-aided diagnosis (CAD) method based on a multi-stage deep learning (DL) model. This study retrospectively investigated 154 patients with pathologically proven early EC at the institution between January 1, 2018, and December 31, 2020. Of these patients, 75 were in the International Federation of Gynecology and Obstetrics (FIGO) stage IA and 79 were in FIGO stage IB. An SSD-based detection model and an Attention U-net-based segmentation model were trained to select, crop, and segment magnetic resonance imaging (MRl) images. Then, an ellipse fitting algorithm was used to generate a uterine cavity line (UCL) to obtain MI depth for classification. In the independent test datasets, the uterus and tumor detection model achieves an average precision rate of 98.70% and 87.93%, respectively. Selecting the optimal MRI slices method yields an accuracy of 97.83%. The uterus and tumor segmentation model with mean IOU of 0.738 and 0.655, mean PA of 0.867 and 0.749, and mean DSC of 0.845 and 0.779, respectively. Finally, the CAD method based on the calculated MI depth reaches an accuracy of 86.9%, a sensitivity of 81.8%, and a specificity of 91.7% for early EC classification. In this study, the CAD method implements an end-to-end early EC classification and is found to be on par with radiologists in terms of performance. It is more intuitive and interpretable than previous DL-based CAD methods.

ABSTRACT The polymorphism at amino acid 17 of quinolone resistance-determining region of GyrA has been stated with a potential role in fluoroquinolone susceptibility in different mycobacterial species. However, no study has provided dependable evidence so far. Here, we verified that gene-edited Mycobacterium abscessus mutants bearing Ser/Gly at this position were more susceptible to fluoroquinolones than their parent strain and the revertant that supports mycobacteria containing Ser/Gly at this position were more susceptible to fluoroquinolones than those containing Ala. IMPORTANCE Fluoroquinolones (FQs) play a key role in the treatment regimens against tuberculosis and non-tuberculous mycobacterial infections. However, there are significant differences in the sensitivities of different mycobacteria to FQs. In this study, we proved that this is associated with the polymorphism at amino acid 17 of quinolone resistance-determining region of Gyrase A by gene editing. This is the first study using CRISPR-associated recombination for gene editing in Mycobacterium abscessus to underscore the contribution of the amino acid substitutions in GyrA to FQ susceptibilities in mycobacteria.

Abstract Objective The current paper aims to discuss the development of a virtual simulation experiment teaching system and review its effectiveness in improving the teaching of clinical skills to college medical students. Methods Collaborators used 3D Studio Max, Unity 3D and Visual Studio to develop four modules: laboratory thinking training, biosafety training, gene testing and experimental assessment. Teaching was conducted and a virtual software program was used for evaluation of the students. Results The laboratory safety training system, virtual gene experiment system and experimental assessment system were developed. The results of the questionnaire survey show that the software provides good interactivity and guidance. The interest of medical students in study is improved and they received training in clinical experimental thinking. Student evaluation assists their scientific research practice, and can improve the awareness of biosafety. Conclusion The virtual simulation experiment teaching system, when applied in the teaching of undergraduate and postgraduate experiment courses, can bring about rapid improvements in the following areas: biosafety awareness, interest in learning about experiments and experimental skills, clinical experimental thinking, and comprehensive experimental ability.

Abstract Objective The aim of this research is to investigate the feasibility of folate receptor‐positive circulating tumor cells (FR+CTCs) as a biomarker for the diagnosis of malignant pulmonary nodules and the correlation between clinicopathological factors and FR+CTC levels. Methods Patients initially diagnosed with one or more pulmonary nodules from a computed tomography scan were prospectively included. Three milliliters of peripheral blood was collected from each participant for FR+CTC analysis prior to surgery. Clinical and pathological parameters and FR+CTC levels were compared between patients with lung cancer and benign diseases. Results Six hundred fifty‐three patients had lung cancer and the other 124 had benign lung diseases based on pathological examinations of the resected specimens. The median FR+CTC value of the lung cancer group was 12.0 (95% CI 9.6–16.2) FU/3 mL and that of the benign group was 7.2 (95% CI 5.78–11.2) FU/3 mL. The difference was statistically significant (P

Worldwide, lower respiratory tract infections (LRTI) are an important cause of hospitalization in children. Due to the relative limitations of traditional pathogen detection methods, new detection methods are needed. The purpose of this study was to evaluate the value of metagenomic next-generation sequencing (mNGS) of bronchoalveolar lavage fluid (BALF) samples for diagnosing children with LRTI based on the interpretation of sequencing results. A total of 211 children with LRTI admitted to the First Affiliated Hospital of Guangzhou Medical University from May 2019 to December 2020 were enrolled. The diagnostic performance of mNGS versus traditional methods for detecting pathogens was compared. The positive rate for the BALF mNGS analysis reached 95.48% (95% confidence interval [CI] 92.39% to 98.57%), which was superior to the culture method (44.07%, 95% CI 36.68% to 51.45%). For the detection of specific pathogens, mNGS showed similar diagnostic performance to PCR and antigen detection, except for Streptococcus pneumoniae, for which mNGS performed better than antigen detection. S. pneumoniae, cytomegalovirus and Candida albicans were the most common bacterial, viral and fungal pathogens. Common infections in children with LRTI were bacterial, viral and mixed bacterial-viral infections. Immunocompromised children with LRTI were highly susceptible to mixed and fungal infections. The initial diagnosis was modified based on mNGS in 29.6% (37/125) of patients. Receiver operating characteristic (ROC) curve analysis was performed to predict the relationship between inflammation indicators and the type of pathogen infection. BALF mNGS improves the sensitivity of pathogen detection and provides guidance in clinical practice for diagnosing LRTI in children.

Heart-on-chip emerged as a potential tool for cardiac tissue engineering, recapitulating key physiological cues in cardiac pathophysiology. Controlled electrical stimulation and the ability to provide directly analyzed functional readouts are essential to evaluate the physiology of cardiac tissues in the heart-on-chip platforms. In this scenario, a novel heart-on-chip platform integrating two soft conductive hydrogel pillar electrodes was presented here. Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and cardiac fibroblasts were seeded into the apparatus to create 3D human cardiac tissues. The application of electrical stimulation improved functional performance by altering the dynamics of tissue structure and contractile development. The contractile forces that cardiac tissues contract was accurately measured through optical tracking of hydrogel pillar displacement. Furthermore, the conductive properties of hydrogel pillars allowed direct and non-invasive electrophysiology studies, enabling continuous monitoring of signal changes in real-time while dynamically administering drugs to the cardiac tissues, as shown by a chronotropic reaction to isoprenaline and verapamil. Overall, the platform for acquiring contractile force and electrophysiological signals in situ allowed monitoring the tissue development trend without interrupting the culture process and could have diverse applications in preclinical drug testing, disease modeling, and therapeutic discovery.

Abstract The limited performance of guideline‐recommended abdominal ultrasound and serum alpha‐fetoprotein (AFP) highlights the urgent, unmet need for new biomarkers for more accurate detection of early hepatocellular carcinoma (HCC). To this end, we have conducted a prospective clinical validation study to evaluate the performance of the HelioLiver Test, a multi‐analyte blood test combining cell‐free DNA methylation patterns, clinical variables, and protein tumor markers. A blinded, multicenter validation study was performed with 247 subjects, including 122 subjects with HCC and 125 control subjects with chronic liver disease. The performance of the HelioLiver Test was compared with AFP and the GALAD score as established HCC surveillance blood tests. The performance of the HelioLiver Test (area under the receiver operating characteristic curve [AUROC] = 0.944) was superior to both AFP (AUROC = 0.851; p < 0.0001) and GALAD (AUROC = 0.899; p < 0.0001). Using a prespecified diagnostic algorithm, the HelioLiver Test showed sensitivities of 85% (95% confidence interval [CI], 78%–90%) for HCC of any stage and 76% (95% CI, 60%–87%) for early stage (American Joint Committee on Cancer [AJCC] I and II) HCC. In contrast, AFP (≥20 ng/mL) alone and the GALAD score (≥−0.63) showed lower sensitivities of 62% (95% CI, 54%–70%) and 75% (95% CI, 67%‐82%) for HCC overall, and 57% (95% CI, 40%–71%) and 65% (95% CI, 49%–79%) for early stage (AJCC I and II) HCC, respectively. The specificities of the HelioLiver Test (91%; 95% CI, 85%–95%), AFP (97%; 95% CI, 92%–99%), and the GALAD score (94%; 95% CI, 88%–97%) were similar for control subjects. The HelioLiver Test showed superior performance for HCC detection compared to with both AFP and the GALAD score and warrants further evaluation in HCC surveillance settings.

Abstract Dried blood samples (DBSs) have many advantages; yet, impediments have limited the clinical utilization of DBSs. We developed a novel volumetric sampling device that collects a precise volume of blood, which overcomes the heterogeneity and hematocrit issues commonly encountered in a traditional DBS card collection as well as allowing for more efficient extraction and processing procedures and thus, more efficient quantitation, by using the entire sample. We also provided a thorough procedure validation using this volumetric DBS collection device with an established quantitative proteomics analysis method, and then analyzed 1000 proteins using this approach in DBSs concomitantly with serum for future consideration of utility in clinical applications. Our data provide a first step in the establishment of a DBS database for the broad application of this sample type for widespread use in clinical proteomic and other analyses applications.

The iPSC line was generated from the peripheral blood mononuclear cells (PBMCs) from a 53-year-old female patient carrying the LMNA gene mutation (c.1304_1307dup) diagnosed with atrial fibrillation and paroxysmal ventricular tachycardia. Through comprehensive detection, it was verified that the cell line had the LMNA gene mutation, normal karyotype, and the potential to differentiate into the three germ layers. This cell line may reveal potential therapeutic targets for atrial and ventricular arrhythmias caused by LMNA mutations.

ABSTRACT Mycobacterium abscessus is an emerging human pathogen leading to significant morbidity and even mortality, intrinsically resistant to almost all the antibiotics available and so can be a nightmare. Mechanisms of its intrinsic resistance remain not fully understood. Here, we selected and confirmed an M. abscessus transposon mutant that is hypersensitive to multiple drugs including rifampin, rifabutin, vancomycin, clofazimine, linezolid, imipenem, levofloxacin, cefoxitin, and clarithromycin. The gene MAB_0189c encoding a putative arabinosyltransferase C was found to be disrupted, using a newly developed highly-efficient strategy combining next-generation sequencing and multiple PCR. Furthermore, selectable marker-free deletion of MAB_0189c recapitulated the hypersensitive phenotype. Disruption of MAB_0189c resulted in an inability to synthesize lipoarabinomannan and markedly enhanced its cell envelope permeability. Complementing MAB_0189c or M. tuberculosis embC restored the resistance phenotype. Importantly, treatment of M. abscessus with ethambutol, a first-line antituberculosis drug targeting arabinosyltransferases of M. tuberculosis, largely sensitized M. abscessus to multiple antibiotics in vitro. We finally tested activities of six selected drugs using a murine model of sustained M. abscessus infection and found that linezolid, rifabutin, and imipenem were active against the MAB_0189c deletion strain. These results identified MAB_0189 as a crucial determinant of intrinsic resistance of M. abscessus, and optimizing inhibitors targeting MAB_0189 might be a strategy to disarm the intrinsic multiple antibiotic resistance of M. abscessus. IMPORTANCE Mycobacterium abscessus is intrinsically resistant to most antibiotics, and treatment of its infections is highly challenging. The mechanisms of its intrinsic resistance remain not fully understood. Here we found a transposon mutant hypersensitive to a variety of drugs and identified the transposon inserted into the MAB_0189c (orthologous embC coding arabinosyltransferase, EmbC) gene by using a newly developed rapid and efficient approach. We further verified that the MAB_0189c gene played a significant role in its intrinsic resistance by decreasing the cell envelope permeability through affecting the production of lipoarabinomannan in its cell envelope. Lastly, we found the arabinosyltransferases inhibitor, ethambutol, increased activities of nine selected drugs in vitro. Knockout of MAB_0189c made M. abscessus become susceptible to 3 drugs in mice. These findings indicated that potential powerful M. abscessus EmbC inhibitor might be used to reverse the intrinsic resistance of M. abscessus to multiple drugs.

Early treatment increases the 5-year survival rate of patients with endometrial cancer (EC). Deep learning (DL) as a new computer-aided diagnosis method has been widely used in medical image processing which can reduce the misdiagnosis by radiologists. An automatic staging method based on DL for the early diagnosis of EC will benefit both radiologists and patients. To develop an effective and automatic prediction model for early EC diagnosis on magnetic resonance imaging (MRI) images, we retrospectively enrolled 117 patients (73 of stage IA, 44 of stage IB) with a pathological diagnosis of early EC confirmed by postoperative biopsy at our institution from 1 January 2018, to 31 December 2020. Axial T2-weighted image (T2WI), axial diffusion-weighted image (DWI) and sagittal T2WI images from 117 patients have been classified into stage IA and stage IB according to the patient’s pathological diagnosis. Firstly, a semantic segmentation model based on the U-net network is trained to segment the uterine region and the tumor region on the MRI images. Then, the area ratio of the tumor region to the uterine region (TUR) in the segmentation map is calculated. Finally, the receiver operating characteristic curves (ROCs) are plotted by the TUR and the results of the patient’s pathological diagnosis in the test set to find the optimal staging thresholds for stage IA and stage IB. In the test sets, the trained semantic segmentation model yields the average Dice similarity coefficients of uterus and tumor on axial T2WI, axial DWI, and sagittal T2WI were 0.958 and 0.917, 0.956 and 0.941, 0.972 and 0.910 respectively. With pathological diagnostic results as the gold standard, the classification model on axial T2WI, axial DWI, and sagittal T2WI yielded an area under the curve (AUC) of 0.86, 0.85 and 0.94, respectively. In this study, an automatic DL-based segmentation model combining the ROC analysis of TUR on MRI images presents an effective early EC staging method.

BackgroundDifferentiating multiple pulmonary lesions as multiple primary lung cancer (MLC) or intra-pulmonary metastasis (IPM) is critical. Lung cancer also has a high genetic heterogeneity, which influenced the treatment strategy. Genetic information may aid in tracing lineage information on multiple lung lesions. This study applied comprehensive genomic profiling to decipher the intrinsic genetics of multiple lung lesions.MethodsSixty-six lung adenocarcinomas (LUAD) tumor lesions (FFEP) archived from 30 patients were included in this study. The 508 cancer-related genes were evaluated by targeted next-generation sequencing (MGI-seq 2000).ResultsThe study included a total of 30 LUADs (66 samples). The majority of tumors demonstrated intra-tumoral heterogeneity. Two hundred twenty-four mutations were detected by sequencing the 66 samples. We investigated the driver gene mutations of NSCLC patients with multiple lesions. EGFR was the most frequently (48/198) mutated driver gene. The codons in EGFR mainly affected by mutations were p.L858R (18/66 [27.3%]) and exon 19del (8/66 [12.1%]). In addition, additional driver genes were found, including TP53, BRAF, ERBB2, MET, and PIK3CA. We also found that the inter-component heterogeneity of different lesions and more than two different mutation types of EGFR were detected in seven patients with two lesions (P3, P10, P24, P25, P28, P29, and P30). The TMB values of different lesions in each patient were different in 26 patients (except P4, P5, P14, and P30).ConclusionsComprehensive genomic profiling should be applied to distinguishing the nature of multiple lung lesions irrespective of radiologic and histologic diagnoses.

We generated an iPSCs line from the peripheral blood mononuclear cells (PBMCs) collected from a patient with long QT syndrome type 1 (LQT1) via a non-integrating system. We identified and verified a missense mutation in the KCNQ1 gene (c.773A > T) by whole-exome sequencing and Sanger sequencing. The established iPSC line was tested for pluripotency, differentiation potential, and karyotype. This cell-based model can help study the molecular mechanism and develop personalized drug therapies for LQT1.

This study aimed to investigate the molecular epidemiology and antibiotic resistance of Haemophilus influenzae in Guangzhou, China. A total of 80 H. influenzae isolates were collected from the First Affiliated Hospital of Guangzhou Medical University from January 2020 to April 2021. Species identification, antimicrobial susceptibility, molecular capsular typing, multilocus sequence typing and the clinical characteristics analysis of patients were performed. For all recruited isolates, the majority of H. influenzae strains from patients with respiratory symptoms were found to be non-typeable H. influenzae (NTHi). The isolates were relative susceptible to third- and fourth-generation cephalosporins, quinolones and chloramphenicol, despite having a high ampicillin resistance rate (>70%). The genotyping results reveal a total of 36 sequence types (STs), with ST12 being the most prevalent ST. Remarkably, the 36 STs identified from 80 NTHi isolates within a short period of 15 months and in a single medical setting have revealed a high genetic diversity in NTHi isolates. In comparison, it is noteworthy that the most prevalent STs found in the present study have rarely been found to overlap with those from previous studies. This is the first study on the molecular epidemiology of NTHi isolates in Guangzhou, a city that is representative of southern China.

PRKAG2 cardiomyopathy is a rare progressive disease characterized by increased ventricular wall thickness and preexcitation. Dysfunction of the protein 5′-AMP-activated protein kinase (AMPK) plays a decisive role in the progression of ventricular lesions. Although patients with the PRKAG2-R302Q mutation have a high incidence of atrial fibrillation (AF), the molecular mechanism contributing to the disease remains unclear. We carried out whole-genome sequencing with linkage analysis in three affected members of a family. Atrial samples were obtained from the proband via surgical intervention. Control atrium biopsies were obtained from patients with persistent AF. Pathological changes were analyzed using the hematoxylin and eosin (H&E), Masson, and periodic acid–Schiff (PAS) staining. The AMPK signaling pathway was investigated by western blot. A murine atrial cardiomyocyte cell line (HL-1) and human induced pluripotent stem derived atrial cardiomyocytes (hiPSC-ACMs) were transfected with an adenovirus carrying the same mutation. We used enzyme linked immunosorbent assay (ELISA) to determine the AMPK activity in HL-1 cells and hiPSC-ACMs overexpressing PRKAG2-R302Q. Pathological results showed a large quantity of glycogen accumulation and vacuolization in cardiomyocytes from the proband atrial tissue. Western blot analysis revealed that the AMPK activity was significantly downregulated compared with that of the controls. Furthermore, remarkable glycogen deposition and impairment of AMPK activity were reproduced in HL-1 cells overexpressing PRKAG2-R302Q. Taken together, PRKAG2-R302Q mutation directly impair atrial cardiomyocytes. PRKAG2-R302Q mutation lead to glycogen deposition and promote the growth of atrial lesions by disrupting the AMPK pathway.

The polarization states of scattered photons can be used to map or image the anisotropic features of a nanostructure. However, the scattering strength depends heavily on the refractivity contrast in the near field under measurement, which limits the imaging sensitivity for viral particles which have little refractivity contrast with their nano-ambientes. In this paper, we show the photon scattering signal strength can be magnified by introducing a more abrupt change of refractivity at the virus particle using antibody-conjugated gold nanoparticles (AuNPs), allowing the presence of such viruses to be detected. Using two different deep learning methods to minimize scattering noise, the photon states scattering signal of a AuNPs ligated virus is enhanced significantly compared to that of a bare virus particle. This is confirmed by Finite Difference Time Domain (FDTD) numerical simulations. The sensitivity of the polarization state scattering spectra from a virus-gold particle doublet is 5.4 times higher than that of a conventional microscope image.

Fast and accurate diagnosis and the immediate isolation of patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are regarded as the most effective measures to restrain the coronavirus disease 2019 (COVID-19) pandemic. Here, we present a high-throughput, multi-index nucleic acid isothermal amplification analyzer (RTisochip™-W) employing a centrifugal microfluidic chip to detect 19 common respiratory viruses, including SARS-CoV-2, from 16 samples in a single run within 90 min. The limits of detection of all the viruses analyzed by the RTisochip™-W system were equal to or less than 50 copies·μL−1, which is comparable to those of conventional reverse transcription polymerase chain reaction. We also demonstrate that the RTisochip™-W system possesses the advantages of good repeatability, strong robustness, and high specificity. Finally, we analyzed 201 cases of preclinical samples, 14 cases of COVID-19-positive samples, 25 cases of clinically diagnosed samples, and 614 cases of clinical samples from patients or suspected patients with respiratory tract infections using the RTisochip™-W system. The test results matched the referenced results well and reflected the epidemic characteristics of the respiratory infectious diseases. The coincidence rate of the RTisochip™-W with the referenced kits was 98.15% for the detection of SARS-CoV-2. Based on these extensive trials, we believe that the RTisochip™-W system provides a powerful platform for fighting the COVID-19 pandemic.

Egress of flaviviruses and involved host pathways are not well understood. Here, the authors show that Lyn is a critical host kinase for Dengue and Zika virus egress resulting in infectious virus progenies within autophagosome-derived vesicles, which might help the virus to evade antibody responses.

Background Dengue is a major public health issue worldwide and severe dengue (SD) is life threatening. It is critical to triage patients with dengue infection in the early stage. However, there is limited knowledge on early indicators of SD. The objective of this study is to identify risk factors for the prognosis of SD and try to find out some potential predictive factors for SD from dengue fever (DF) in the early of infection. Methods The PubMed, Cochrane Library and Web of Science databases were searched for relevant studies from June 1999 to December 2020. The pooled odds ratio (OR) or standardized mean difference (SMD) with 95% confidence intervals (CI) of identified factors was calculated using a fixed or random effect model in the meta-analysis. Tests for heterogeneity, publication bias, subgroup analyses, meta-regression, and a sensitivity analysis were further performed. Findings A total of 6,848 candidate articles were retrieved, 87 studies with 35,184 DF and 8,173 SD cases met the eligibility criteria. A total of 64 factors were identified, including population and virus characteristics, clinical symptoms and signs, laboratory biomarkers, cytokines, and chemokines; of these factors, 34 were found to be significantly different between DF and SD, while the other 30 factors were not significantly different between the two groups after pooling the data from the relevant studies. Additionally, 9 factors were positive associated with SD within 7 days after illness when the timing subgroup analysis were performed. Conclusions Practical factors and biomarkers for the identification of SD were established, which will be helpful for a prompt diagnosis and early effective treatment for those at greatest risk. These outcomes also enhance our knowledge of the clinical manifestations and pathogenesis of SD.

Peripheral blood mononuclear cells (PBMCs) were harvested and reprogramed to induced pluripotent stem cells (iPSCs) from a 46-year-old male patient with familial dilated cardiomyopathy and atrial fibrillation via a non-integrating system. A missense mutation in the LMNA gene (c.1003C > T) was identified by whole-exome sequencing and verified by Sanger sequencing. The pluripotency, differentiation potential, and karyotype of this cell line were also tested. This model is helpful to study the phenotype, mechanism, and therapy for laminopathy.

Tumor mutation burden (TMB) serves as an effective biomarker predicting efficacy of mono-immunotherapy for non-small cell lung cancer (NSCLC). Establishing a precise TMB predicting model is essential to select which populations are likely to respond to immunotherapy or prognosis and to maximize the benefits of treatment. In this study, available Formalin-fixed paraffin embedded tumor tissues were collected from 499 patients with NSCLC. Targeted sequencing of 636 cancer related genes was performed, and TMB was calculated. Distribution of TMB was significantly (p < 0.001) correlated with sex, clinical features (pathological/histological subtype, pathological stage, lymph node metastasis, and lympho-vascular invasion). It was also significantly (p < 0.001) associated with mutations in genes like TP53, EGFR, PIK3CA, KRAS, EPHA3, TSHZ3, FAT3, NAV3, KEAP1, NFE2L2, PTPRD, LRRK2, STK11, NF1, KMT2D, and GRIN2A. No significant correlations were found between TMB and age, neuro-invasion (p = 0.125), and tumor location (p = 0.696). Patients with KRAS p.G12 mutations and FAT3 missense mutations were associated (p < 0.001) with TMB. TP53 mutations also influence TMB distribution (P < 0.001). TMB was reversely related to EGFR mutations (P < 0.001) but did not differ by mutation types. According to multivariate logistic regression model, genomic parameters could effectively construct model predicting TMB, which may be improved by introducing clinical information. Our study demonstrates that genomic together with clinical features yielded a better reliable model predicting TMB-high status. A simplified model consisting of less than 20 genes and couples of clinical parameters were sought to be useful to provide TMB status with less cost and waiting time.

Abstract Background Fluoroquinolone-resistant Haemophilus influenzae (FRHI) has been reported worldwide but remain unclear in China. Methods A total of 402 H. influenzae isolates collected from 2016 to 2017 were included. Antimicrobial susceptibility on 10 antibiotics was performed, and minimum inhibitory concentration of ciprofloxacin- and nalidixic acid-resistant strains were further determined by E-test strips, with risk factors also evaluated. Strains with resistance or reduced susceptibility to ciprofloxacin were subjected to sequencing of the quinolone resistance-determining regions (QRDR) and plasmid-mediated quinolone resistance genes by sequencing, with multi-locus sequence typing. Results 2.2% of H. influenzae strains were non-susceptible (7/402, 1.7%) or susceptible (2/402, 0.5%) to ciprofloxacin but NAL-resistant by E-test, and multidrug resistance was more common in fluoroquinolones non-susceptible H. influenzae group (p = 0.000). Infection risk factors included invasive procedure (p = 0.011), catching cold/previous contact with someone who had a cold (p = 0.019), fluoroquinolones use during previous 3 months (p = 0.003). With none of mutations obtained in gyrB, parE and other plasmid-mediated quinolone resistance genes, 7 and 4 strains were found for Ser-84-Leu substitutions in gyrA and one amino acid substitution in the QRDR of gyrA linked with one amino acid substitution in the QRDR of parC, respectively. In addition, five sequence types (ST) were identified, with ST1719 firstly found. Conclusions For the first time, this study has reported the incidence, risk factors, molecular determinants on fluoroquinolones resistance and ST of FRHI strains in mainland China, representing the first evidence of mutation of gyrA and parC in China and the new ST1719 worldwide.

In this study, we proposed a method to measure the epidermal thickness (ET) of skin based on deep convolutional neural network, which was used to determine the boundaries of skin surface and the ridge portion in dermal–epidermis junction (DEJ) in cross-section optical coherence tomography (OCT) images of fingertip skin. The ET was calculated based on the row difference between the surface and the ridge top, which is determined by search the local maxima of boundary of the ridge portion. The results demonstrated that the region of ridge portion in DEJ was well determined and the ET measurement in this work can reduce the effect of the papillae valley in DEJ by 9.85%. It can be used for quantitative characterization of skin to differentiate the skin diseases.

In endometrial cancer, patients in early stages have a 91% 5-year survival chance. By contrast, patients in advanced stages have only 20% survival chance. Therefore, early diagnosis of endometrial cancer is very important. Photoacoustic imaging is able to distinguish benign from malignant tumors. However, the images acquired through photoacoustic imaging contain inherent artifacts, caused by imperfect reconstruction algorithms. In this paper, to improve the said images, a filtered delay-multiply-and-sum (F-DMAS) algorithm, which was proven to have an increased dynamic range and better quality of B-mode images was employed in the reconstruction process. First, the images of two blood vessel phantom experiments, acquired through photoacoustic imaging, were reconstructed by employing the F-DMAS algorithm. The results show the lateral resolutions of the system improving from 2.22 mm (with traditional photoacoustic imaging reconstruction algorithms) to 1.47 mm. Next, images of a pig uterus, filled with intralipid-20% emulsion, were also reconstructed by employing the F-DMAS algorithm. The average signal-to-noise ratio increased from 11.14 dB (with traditional photoacoustic imaging reconstruction algorithms) to 64.90 dB. In order to improve the continuity of the 3D PA image, F-DMAS with an adaptive coefficient was discussed to find the best balance between the signal-to-noise ratio and continuity. In conclusion, this paper demonstrates that the use of F-DMAS algorithms in the reconstruction of the images acquired through photoacoustic imaging in clinical investigations would improve the detection rate of early endometrial cancer.

In illuminating tissues, a cylindrical diffuser (CD) has an advantage over regular laser sources due to its ability to illuminate a larger volume of the target tissue. This paper presents a co-registered large volume photoacoustic (PA) and ultrasonic (US) imaging for early endometrial cancer (EEC) detection using CD. It has the advantage that the US imaging system is outside the body and only the PA excitation device is inside the body, which makes the system more efficient and less invasive for EEC detection. The paper reports on two sets of experiments. The first set produced real-time PA images of blood vessel phantom. The second set demonstrated the imaging of pig uterus ex vivo. The results show that the system has the potential for imaging and characterizing of EEC.