Analysis of the epidemiological situation of influenza in Guangzhou under the prevention and control of COVID-19 in June 2022.

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.

A deep learning-based automatic image quality assessment method for respiratory phase on computed tomography chest images.

Background: Computed tomography (CT) chest scans have become commonly used in clinical diagnosis. Image quality assessment (IQA) for CT images plays an important role in CT examination. It is worth noting that IQA is still a manual and subjective process, and even experienced radiologists make mistakes due to human limitations (fatigue, perceptual biases, and cognitive biases). There are also kinds of biases because of poor consensus among radiologists. Excellent IQA methods can reliably give an objective evaluation result and also reduce the workload of radiologists. This study proposes a deep learning (DL)-based automatic IQA method, to assess whether the image quality of respiratory phase on CT chest images are optimal or not, so that the CT chest images can be used in the patient's physical condition assessment. Methods: This retrospective study analysed 212 patients' chest CT images, with 188 patients allocated to a training set (150 patients), validation set (18 patients), and a test set (20 patients). The remaining 24 patients were used for the observer study. Data augmentation methods were applied to address the problem of insufficient data. The DL-based IQA method combines image selection, tracheal carina segmentation, and bronchial beam detection. To automatically select the CT image containing the tracheal carina, an image selection model was employed. Afterward, the area-based approach and score-based approach were proposed and used to further optimize the tracheal carina segmentation and bronchial beam detection results, respectively. Finally, the score about the image quality of the patient's respiratory phase images given by the DL-based automatic IQA method was compared with the mean opinion score (MOS) given in the observer study, in which four blinded experienced radiologists took part. Results: The DL-based automatic IQA method achieved good performance in assessing the image quality of the respiratory phase images. For the CT sequence of the same patient, the DL-based IQA method had an accuracy of 92% in the assessment score, while the radiologists had an accuracy of 88%. The Kappa value of the assessment score between the DL-based IQA method and radiologists was 0.75, with a sensitivity of 85%, specificity of 91%, positive predictive value (PPV) of 92%, negative predictive value (NPV) of 93%, and accuracy of 88%. Conclusions: This study develops and validates a DL-based automatic IQA method for the respiratory phase on CT chest images. The performance of this method surpassed that of the experienced radiologists on the independent test set used in this study. In clinical practice, it is possible to reduce the workload of radiologists and minimize errors caused by human limitations.

Injectable and Conductive Nanomicelle Hydrogel with α-Tocopherol Encapsulation for Enhanced Myocardial Infarction Repair.

Substantial advancements have been achieved in the realm of cardiac tissue repair utilizing functional hydrogel materials. Additionally, drug-loaded hydrogels have emerged as a research hotspot for modulating adverse microenvironments and preventing left ventricular remodeling after myocardial infarction (MI), thereby fostering improved reparative outcomes. In this study, diacrylated Pluronic F127 micelles were used as macro-cross-linkers for the hydrogel, and the hydrophobic drug α-tocopherol (α-TOH) was loaded. Through the in situ synthesis of polydopamine (PDA) and the incorporation of conductive components, an injectable and highly compliant antioxidant/conductive composite FPDA hydrogel was constructed. The hydrogel exhibited exceptional stretchability, high toughness, good conductivity, cell affinity, and tissue adhesion. In a rabbit model, the material was surgically implanted onto the myocardial tissue, subsequent to the ligation of the left anterior descending coronary artery. Four weeks postimplantation, there was discernible functional recovery, manifesting as augmented fractional shortening and ejection fraction, alongside reduced infarcted areas. The findings of this investigation underscore the substantial utility of FPDA hydrogels given their proactive capacity to modulate the post-MI infarct microenvironment and thereby enhance the therapeutic outcomes of myocardial infarction.

Super-resolution algorithm for the characterization of sweat glands in fingerprint OCT images.

Optical coherence tomography (OCT) is a noninvasive optical imaging technique that can be used to produce three-dimensional images of fingerprints. However, the low quality and poor resolution of the regions of interest (ROIs) in OCT images make it challenging to segment small tissues accurately. To address this issue, a super-resolution (SR) network called ESRNet has been developed to enhance the quality of OCT images, facilitating their applications in research. Firstly, the performance of the SR images produced by ESRNet is evaluated by comparing it to those generated by five other SR methods. Specifically, the SR performance is evaluated using three upscale factors (2×, 3×, and 4×) to assess the quality of the enhanced images. Based on the results obtained from the three datasets, it is evident that ESRNet outperforms current advanced networks in terms of SR performance. Furthermore, the segmentation accuracy of sweat glands has been significantly improved by the SR images. The number of sweat glands in the top view increased from 102 to 117, further substantiating the performance of the ESRNet network. The spiral structure of sweat glands is clear to human eyes and has been verified by showing similar left-right-handed spiral numbers. Finally, a sweat gland recognition method for the SR 3D images is proposed.

Deep learning-driven multi-view multi-task image quality assessment method for chest CT image.

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[Formula: see text]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[Formula: see text]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[Formula: see text]IQA method. RESULTS: In the additional test set, the M[Formula: see text]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[Formula: see text]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.

A computer-aided determining method for the myometrial infiltration depth of early endometrial cancer on MRI images.

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.

Distribution of common and rare drug resistance patterns in Mycobacterium tuberculosis clinical isolates revealed by GenoType MTBDRplus and MTBDRsl assay.

Background: Tuberculosis (TB) remains a significant global health emergency caused by Mycobacterium tuberculosis (Mtb). The epidemiology, transmission, genotypes, mutational patterns, and clinical consequences of TB have been extensively studied worldwide, however, there is a lack of information regarding the epidemiology and mutational patterns of Mtb in Pakistan, specifically concerning the prevalence of multi-drug resistant TB (MDR-TB). Methods: This study aimed to investigate the incidence of Mtb and associated mutational patterns using the line probe assay (LPA). Previous studies have reported a high frequency of mutations in the rpoB, inhA, and katG genes, which are associated with resistance to rifampicin (RIF) and isoniazid (INH). Therefore, the current study utilized LPA to detect mutations in the rpoB, katG, and inhA genes to identify multi-drug resistant Mtb. Results: LPA analysis of a large pool of Mtb isolates, including samples from 241 sputum-positive patients, revealed that 34.85% of isolates were identified as MDR-TB, consistent with reports from various regions worldwide. The most prevalent mutations observed were rpoB S531L and inhA promoter C15T, which were associated with resistance to RIF and INH, respectively. Conclusions: This study highlights the effectiveness of GenoType MTBDRplus and MTBDRsl assays as valuable tools for TB management. These assays enable rapid detection of resistance to RIF, INH, and fluoroquinolones (FQs) in Mtb clinical isolates, surpassing the limitations of solid and liquid media-based methods. The findings contribute to our understanding of MDR-TB epidemiology and provide insights into the genetic profiles of Mtb in Pakistan, which are essential for effective TB control strategies.

Metagenomic next-generation sequencing of bronchoalveolar lavage fluid assists in the diagnosis of pathogens associated with lower respiratory tract infections in children.

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.

Amino acid 17 in QRDR of Gyrase A plays a key role in fluoroquinolones susceptibility in mycobacteria.

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.

Clinical impact of human parainfluenza virus infections before and during the COVID-19 pandemic in Southern China.

Human parainfluenza viruses (HPIVs) are a leading cause of acute respiratory tract infections (ARTIs). Non-pharmaceutical interventions (NPIs) were widely administered to combat the pandemic of the coronavirus disease 2019 (COVID-19). Respiratory specimens were obtained from 10,454 hospitalized children with ARTIs to detect HPIV. We investigated differences in epidemiological and clinical characteristics of HPIV infections before (2017-2019) and during the COVID-19 pandemic (2020-2022). HPIVs were detected in 392 (3.75%, 392/10,454) patients, of whom 70 (17.86%), 48 (12.24%), and 274 (69.90%) were positive for HPIV1, HPIV2, and HPIV3, respectively. Detection rates of HPIV3 were higher in 2020-2022 than in 2017-2019 (3.38% vs. 2.24%). The seasonal distribution of HPIV1 showed no difference, but HPIV3 peaked between September and December during the COVID-19 pandemic, which differed from previous epidemiological patterns. Compared to the period before the COVID-19 pandemic, there has been a noticeable decrease in the incidence of asthma, moist rales, and emesis in patients infected with HPIV1 and in asthma, expectoration, and severe pneumonia in patients infected with HPIV3 during 2020-2022. The detection rates of HPIV increased in Southern China during the COVID-19 outbreak, which underlines the importance of continuous surveillance of HPIV in the next epidemic season.

Comprehensive analysis of the expression, prognosis and biological significance of FSCN family in clear cell renal cell carcinoma.

Fascin (FSCN) is an actin-binding protein that serves a critical role in cell migration and invasion, contributing to tumor metastasis. However, there is little known about the function of FSCN family in kidney renal clear cell carcinoma (KIRC). The present study used the UALCAN, gene expression profiling interactive analysis, The Cancer Genome Atlas, cBioPortal, STRING and The Tumor Immune Estimation Resource databases to investigate the transcription level, genetic alteration and biological function of FSCNs in KIRC and their association with the prognosis value and immune cell infiltration in patients with KIRC. Results showed that the expression of FSCN1 and FSCN3 was markedly upregulated in patients with KIRC, while the expression of FSCN2 showed an opposite trend, which was the same as the experiments. Furthermore, the expression levels of FSCNs were associated with pathological stage, molecular subtypes and tumor grade. The expression levels of FSCNs were statistically correlated with the immune cell infiltration in KIRC. Higher expression levels of FSCN1 and FSCN3 were associated with worse overall survival (OS) and progression-free interval of patients bearing KIRC. Univariate and multivariate analysis demonstrated that FSCN2 was an independent risk factor for OS time in KIRC. Furthermore, mutations in FSCNs were significantly associated with poor OS and progression-free survival in patients with KIRC. The FSCNs were involved in pathways including focal adhesion, endocytosis, hypertrophic cardiomyopathy, regulation of actin cytoskeleton. The results indicated that FSCN2 might serve as an independent prognostic factor for OS of KIRC and that FSCN1 and FSCN3 can be used as favorable biomarkers for predicting clinical outcomes in KIRC.

Construction of a virtual simulation laboratory for gene detection.

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.

Chain hybridization-based CRISPR-lateral flow assay enables accurate gene visual detection.

Visualized gene detection based on the CRISPR-Cas12/CRISPR-Cas13 technology and lateral flow assay device (CRISPR-LFA) has shown great potential in point-of-care testing sector. Current CRISPR-LFA methodology mainly utilizes conventional immuno-based LFA test strips, which could visualize whether the reporter probe is trans-cleaved by Cas protein, indicating the target positive detection. However, conventional CRISPR-LFA usually produces false-positive results in target negative assay. Herein, a nucleic acid Chain Hybridization-based Lateral Flow Assay platform, named CHLFA, has been developed to achieve the CRISPR-CHLFA concept. Different from the conventional CRISPR-LFA, the proposed CRISPR-CHLFA system was established based on the nucleic acid hybridization between the GNP-probe embedded in test strips and ssDNA (or ssRNA) reporter from CRISPR (LbaCas12a or LbuCas13a) reaction, which eliminated the requirement of immunoreaction in conventional immuno-based LFA. The assay realized the detection of 1-10 copy of target gene per reaction within 50 min. The CRISPR-CHLFA system achieved highly accurate visual detection of target negative samples, thus overcoming the false-positive problem that often produced in assays using conventional CRISPR-LFA. The CRISPR-CHLFA platform was further adopted for the visual detection of marker gene from SASR-CoV-2 Omicron variant and Mycobacterium tuberculosis (MTB), respectively, and 100% accuracy for the analysis of clinical specimens (45 SASR-CoV-2 specimens and 20 MTB specimens) was obtained. The proposed CRISPR-CHLFA system could provide an alternative platform for the development of POCT biosensors and can be widely adopted in accurate and visualized gene detection.

Continuous contractile force and electrical signal recordings of 3D cardiac tissue utilizing conductive hydrogel pillars on a chip.

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.

Molecular Epidemiology and Antibiotic Resistance Analysis of Non-Typeable Haemophilus influenzae (NTHi) in Guangzhou: A Representative City of Southern China.

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.

Laboratory blood test profiling reveals distinct biochemical and hemocyte features of KRAS mutated non-small cell lung cancer.

Background: The testing for capability of some routine blood test parameters to reflect the biology of non-small cell lung carcinoma with different driver mutations is of great interest and practice significance. We aim to screen these variables and, if allowed, develop a novel predictive model based on results of these routine blood tests commonly performed in clinical practice to inform which can help doctors assess the patient's genetic mutation status as early as possible before surgery. Methods: For the exploration cohort, we included 1,595 patients who were diagnosed with non-small cell lung cancer (NSCLC) and genetically profiled by a next-generation sequencing panel in the First Affiliated Hospital of Guangzhou Medical University. The external validation cohort, which consists of 197 NSCLC cancer patients from Sun Yat-sen University Cancer Hospital, was subsequently established. Results: We analyzed the association between 46 frequently tested laboratory variables and different genetic mutation types. KRAS mutation was found to be a unique subtype that exclusively correlated with several blood parameters in our study. Least absolute shrinkage and selection operator (LASSO) regression was performed, and the following parameters were found to be significantly associated with KRAS mutation: triglycerides [odds ratio (OR) =1.63], arterial oxygen partial pressure (OR =0.97), uric acid (OR =1.01), basophil count (OR =1.41), eosinophil count (OR =1.146), fibrinogen (OR =1.42), standard bicarbonate (OR =0.85), high-density lipoprotein cholesterol (OR =0.18), alpha-L-fucosidase (OR =1.07). The areas under the receiver-operator characteristic curve in the training set and the external validation set were 0.85 [95% confidence interval (CI): 0.81-0.88] and 0.81 (95% CI: 0.71-0.91), respectively. Conclusions: We developed a non-invasive, more cost-effective predictive model of NSCLC based on routinely available variables, with practical predictive power. This model can be used as a practical screening tool to guide the use of more specialized and expensive molecular assays for KRAS mutation in NSCLC. However, further studies are warranted to investigate the mechanism underlying such association between KRAS mutations and the related parameters of blood tests.

The value of folate receptor-positive circulating tumor cells in the diagnosis of lung cancer and its correlation with clinical characteristics.

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 < 0.0001). In a receiver operating characteristic analysis to distinguish the two groups, the area under curve of FR+CTC was 0.7457 (95% CI 0.6893-0.8021; P < 0.0001) using a cutoff of 8.65 FU/3 mL. The sensitivity was 86.37%, and the specificity was 74.19%. Combined with conventional serum tumor biomarkers, the area under curve was 0.922 (0.499-0.963). The sensitivity was 92.20%, and the specificity was 83.05%. FR+CTC levels were related to tumor staging (P4 < 0.001), the degree of tumor invasion both in single (P = 0.011) and multiple lesions (P = 0.022), pathological subtypes (P = 0.013), and maximum tumor diameter (P = 0.014). CONCLUSIONS: FR+CTC is an effective and reliable biomarker for the diagnosis of lung cancer. Further, FR+CTC level is correlated with tumor staging, degree of invasion, pathological subtypes, and tumor size.

Binary Colloidal Crystals Promote Cardiac Differentiation of Human Pluripotent Stem Cells via Nuclear Accumulation of SETDB1.

Biophysical cues can facilitate the cardiac differentiation of human pluripotent stem cells (hPSCs), yet the mechanism is far from established. One of the binary colloidal crystals, composed of 5 µm Si and 400 nm poly(methyl methacrylate) particles named 5PM, has been applied as a substrate for hPSCs cultivation and cardiac differentiation. In this study, cell nucleus, cytoskeleton, and epigenetic states of human induced pluripotent stem cells on the 5PM were analyzed using atomic force microscopy, molecular biology assays, and the assay for transposase-accessible chromatin sequencing (ATAC-seq). Cells were more spherical with stiffer cell nuclei on the 5PM compared to the flat control. ATAC-seq revealed that chromatin accessibility decreased on the 5PM, caused by the increased entry of histone lysine methyltransferase SETDB1 into the cell nuclei and the amplified level of histone H3K9me3 modification. Reducing cytoskeleton tension using a ROCK inhibitor attenuated the nuclear accumulation of SETDB1 on the 5PM, indicating that the effect is cytoskeleton-dependent. In addition, the knockdown of SETDB1 reversed the promotive effects of the 5PM on cardiac differentiation, demonstrating that biophysical cue-induced cytoskeletal tension, cell nucleus deformation, and then SETDB1 accumulation are critical outside-in signal transformations in cardiac differentiation. Human embryonic stem cells showed similar results, indicating that the biophysical impact of the 5PM surfaces on cardiac differentiation could be universal. These findings contribute to our understanding of material-assistant hPSC differentiation, which benefits materiobiology and stem cell bioengineering.

Characterization of Genetic Variants Associated with Rifampicin Resistance Level in Mycobacterium tuberculosis Clinical Isolates Collected in Guangzhou Chest Hospital, China.

Objective: Rifampicin (RIF)-resistance, a surrogate marker for multidrug-resistant tuberculosis (TB), is mediated by mutations in the rpoB gene. We aimed to investigate the prevalence of mutations pattern in the entire rpoB gene of Mycobacterium tuberculosis clinical isolates and their association with resistance level to RIF. Methods: Among 465 clinical isolates collected from the Guangzhou Chest Hospital, drug-susceptibility of 175 confirmed Mtb strains was performed via the proportion method and Bactec MGIT 960 system. GeneXpert MTB/RIF and sanger sequencing facilitated in genetic characterization, whereas the MICs of RIF were determined by Alamar blue assay. Results: We found 150/175 (85.71%) RIF-resistant strains (MIC: 4 to >64 µg/mL) of which 57 were MDR and 81 pre-XDR TB. Genetic analysis identified 17 types of mutations 146/150 (97.33%) within RRDR (codons 426-452) of rpoB, mainly at L430 (P), D435 (V, E, G, N), H445 (N, D, Y, R, L), S450 (L, F) and L452 (P). D435V 12/146 (8.2%), H445N 16/146 (10.9%), and S450L 70/146 (47.94%) were the most frequently encountered mutations. Mutations Q432K, M434V, and N437D are rarely identified in RRDR. Deletions at (1284-1289 CCAGCT), (1295-1303 AATTCATGG), and insertion at (1300-1302 TTC) were detected within RRDR of three RIFR strains for the first time. We detected 47 types of mutations and insertions/deletions (indels) outside the RRDR. Four RIFR strains were detected with only novel mutations/indels outside the RRDR. Two of the four had (K274Q + C897 del + I491M) and (A286V + L494P), respectively. The other two had (G1687del + P454L) and (TT1835-6 ins + I491L) individually. Compared with phenotypic characterization, diagnostic sensitivities of GeneXpert MTB/RIF and sequencing analysis were 95.33% (143/150), and 100% (150/150) respectively. Conclusion: Our findings underscore the key role of RRDR mutations and the contribution of non-RRDR mutations in rapid molecular diagnosis of RIFR clinical isolates. Such insights will support early detection of disease and recommend the appropriate anti-TB regimens in high-burden settings.

Intratumor heterogeneity of driver mutations and TMB distribution in 30 early-stage LUAD patients with multiple lesions.

Background: Differentiating 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. Methods: Sixty-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). Results: The 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). Conclusions: Comprehensive genomic profiling should be applied to distinguishing the nature of multiple lung lesions irrespective of radiologic and histologic diagnoses.