Development of a luciferase-based Gram-positive bacterial reporter system for the characterization of antimicrobial agents.

Mechanistic investigations are of paramount importance in elucidating the modes of action of antibiotics and facilitating the discovery of novel drugs. We reported a luciferase-based reporter system using bacterial cells to unveil mechanisms of antimicrobials targeting transcription and translation. The reporter gene Nluc encoding NanoLuciferase (NanoLuc) was integrated into the genome of the Gram-positive model organism, Bacillus subtilis, to generate a reporter strain BS2019. Cellular transcription and translation levels were assessed by quantifying the amount of Nluc mRNA as well as the luminescence catalyzed by the enzyme NanoLuc. We validated this system using three known inhibitors of transcription (rifampicin), translation (chloramphenicol), and cell wall synthesis (ampicillin). The B. subtilis reporter strain BS2019 successfully revealed a decline in Nluc expression by rifampicin and NanoLuc enzyme activity by chloramphenicol, while ampicillin produced no observable effect. The assay was employed to characterize a previously discovered bacterial transcription inhibitor, CUHK242, with known antimicrobial activity against drug-resistant Staphylococcus aureus. Production of Nluc mRNA in our reporter BS2019 was suppressed in the presence of CUHK242, demonstrating the usefulness of the construct, which provides a simple way to study the mechanism of potential antibiotic candidates at early stages of drug discovery. The reporter system can also be modified by adopting different promoters and reporter genes to extend its scope of contribution to other fields of work. IMPORTANCE: Discovering new classes of antibiotics is desperately needed to combat the emergence of multidrug-resistant pathogens. To facilitate the drug discovery process, a simple cell-based assay for mechanistic studies is essential to characterize antimicrobial candidates. In this work, we developed a luciferase-based reporter system to quantify the transcriptional and translational effects of potential compounds and validated our system using two currently marketed drugs. Reporter strains generated in this study provide readily available means for identifying bacterial transcription inhibitors as prospective novel antibacterials. We also provided a series of plasmids for characterizing promoters under various conditions such as stress.

Development and validation of 10-year risk prediction models of cardiovascular disease in Chinese type 2 diabetes mellitus patients in primary care using interpretable machine learning-based methods.

AIM: To develop 10-year cardiovascular disease (CVD) risk prediction models in Chinese patients with type 2 diabetes mellitus (T2DM) managed in primary care using machine learning (ML) methods. METHODS: In this 10-year population-based retrospective cohort study, 141 516 Chinese T2DM patients aged 18 years or above, without history of CVD or end-stage renal disease and managed in public primary care clinics in 2008, were included and followed up until December 2017. Two-thirds of the patients were randomly selected to develop sex-specific CVD risk prediction models. The remaining one-third of patients were used as the validation sample to evaluate the discrimination and calibration of the models. ML-based methods were applied to missing data imputation, predictor selection, risk prediction modelling, model interpretation, and model evaluation. Cox regression was used to develop the statistical models in parallel for comparison. RESULTS: During a median follow-up of 9.75 years, 32 445 patients (22.9%) developed CVD. Age, T2DM duration, urine albumin-to-creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), systolic blood pressure variability and glycated haemoglobin (HbA1c) variability were the most important predictors. ML models also identified nonlinear effects of several predictors, particularly the U-shaped effects of eGFR and body mass index. The ML models showed a Harrell's C statistic of >0.80 and good calibration. The ML models performed significantly better than the Cox regression models in CVD risk prediction and achieved better risk stratification for individual patients. CONCLUSION: Using routinely available predictors and ML-based algorithms, this study established 10-year CVD risk prediction models for Chinese T2DM patients in primary care. The findings highlight the importance of renal function indicators, and variability in both blood pressure and HbA1c as CVD predictors, which deserve more clinical attention. The derived risk prediction tools have the potential to support clinical decision making and encourage patients towards self-care, subject to further research confirming the models' feasibility, acceptability and applicability at the point of care.

Rewiring of RNA methylation by the oncometabolite fumarate in renal cell carcinoma.

Metabolic reprogramming is a hallmark of cancer that facilitates changes in many adaptive biological processes. Mutations in the tricarboxylic acid cycle enzyme fumarate hydratase (FH) lead to fumarate accumulation and cause hereditary leiomyomatosis and renal cell cancer (HLRCC). HLRCC is a rare, inherited disease characterized by the development of non-cancerous smooth muscle tumors of the uterus and skin, and an increased risk of an aggressive form of kidney cancer. Fumarate has been shown to inhibit 2-oxoglutarate-dependent dioxygenases (2OGDDs) involved in the hydroxylation of HIF1α, as well as in DNA and histone demethylation. However, the link between fumarate accumulation and changes in RNA post-transcriptional modifications has not been defined. Here, we determine the consequences of fumarate accumulation on the activity of different members of the 2OGDD family targeting RNA modifications. By evaluating multiple RNA modifications in patient-derived HLRCC cell lines, we show that mutation of FH selectively affects the levels of N6-methyladenosine (m6A), while the levels of 5-formylcytosine (f5C) in mitochondrial tRNA are unaffected. This supports the hypothesis of a differential impact of fumarate accumulation on distinct RNA demethylases. The observation that metabolites modulate specific subsets of RNA-modifying enzymes offers new insights into the intersection between metabolism and the epitranscriptome.

Sulfonamidyl derivatives of sigmacidin: Protein-protein interaction inhibitors targeting bacterial RNA polymerase and sigma factor interaction exhibiting antimicrobial activity against antibiotic-resistant bacteria.

RNA polymerase is an essential enzyme involved in bacterial transcription, playing a crucial role in RNA synthesis. However, it requires the association with sigma factors to initiate this process. In our previous work, we utilized a structure-based drug discovery approach to create benzoyl and benzyl benzoic acid compounds. These compounds were designed based on the amino acid residues within the key binding site of sigma factors, which are crucial for their interaction with RNA polymerase. By inhibiting bacterial transcription, these compounds exhibited notable antimicrobial activity, and we coined them as sigmacidins to highlight their resemblance to sigma factors and the benzoic acid structure. In this study, we further modified the compound scaffolds and developed a series of sulfonamidyl benzoic acid derivatives. These derivatives displayed potent antimicrobial activity, with minimum inhibitory concentrations (MICs) as low as 1 µg/mL, demonstrating their efficacy against bacteria. Furthermore, these compounds demonstrated low cytotoxicity, indicating their potential as safe antimicrobial agents. To ascertain their mechanism of action in interfering with bacterial transcription, we conducted biochemical and cellular assays. Overall, this study showcases the effectiveness of sulfonamidyl benzoic acid derivatives as antimicrobial agents by targeting protein-protein interactions involving RNA polymerase and sigma factors. Their strong antimicrobial activity and low cytotoxicity implicate their potential in combating antibiotic-resistant bacteria.

Cell cycle regulation of the psoriasis associated gene CCHCR1 by transcription factor E2F1.

The coiled-coil alpha-helical rod protein 1 (CCHCR1) was first identified as a candidate gene in psoriasis and has lately been found to be associated with a wide range of clinical conditions including COVID-19. CCHCR1 is located within P-bodies and centrosomes, but its exact role in these two subcellular structures and its transcriptional control remain largely unknown. Here, we showed that CCHCR1 shares a bidirectional promoter with its neighboring gene, TCF19. This bidirectional promoter is activated by the G1/S-regulatory transcription factor E2F1, and both genes are co-induced during the G1/S transition of the cell cycle. A luciferase reporter assay suggests that the short intergenic sequence, only 287 bp in length, is sufficient for the G1/S induction of both genes, but the expression of CCHCR1 is further enhanced by the presence of exon 1 from both TCF19 and CCHCR1. This research uncovers the transcriptional regulation of the CCHCR1 gene, offering new perspectives on its function. These findings contribute to the broader understanding of diseases associated with CCHCR1 and may serve as a foundational benchmark for future research in these vital medical fields.

A novel retinoic acid receptor-γ agonist antagonizes immune checkpoint resistance in lung cancers by altering the tumor immune microenvironment.

All-trans-retinoic acid (ATRA), the retinoic acid receptors (RARs) agonist, regulates cell growth, differentiation, immunity, and survival. We report that ATRA-treatment repressed cancer growth in syngeneic immunocompetent, but not immunodeficient mice. The tumor microenvironment was implicated: CD8+ T cell depletion antagonized ATRA's anti-tumorigenic effects in syngeneic mice. ATRA-treatment with checkpoint blockade did not cooperatively inhibit murine lung cancer growth. To augment ATRA's anti-tumorigenicity without promoting its pro-tumorigenic potential, an RARγ agonist (IRX4647) was used since it regulates T cell biology. Treating with IRX4647 in combination with an immune checkpoint (anti-PD-L1) inhibitor resulted in a statistically significant suppression of syngeneic 344SQ lung cancers in mice-a model known for its resistance to checkpoints and characterized by low basal T cell and PD-L1 expression. This combined treatment notably elevated CD4+ T-cell presence within the tumor microenvironment and increased IL-5 and IL-13 tumor levels, while simultaneously decreasing CD38 in the tumor stroma. IL-5 and/or IL-13 treatments increased CD4+ more than CD8+ T-cells in mice. IRX4647-treatment did not appreciably affect in vitro lung cancer growth, despite RARγ expression. Pharmacokinetic analysis found IRX4647 plasma half-life was 6 h in mice. Yet, RARα antagonist (IRX6696)-treatment with anti-PD-L1 did not repress syngeneic lung cancer growth. Together, these findings provide a rationale for a clinical trial investigating an RARγ agonist to augment check point blockade response in cancers.

Comparison of COVID-19 with influenza A in the ICU: a territory-wide, retrospective, propensity matched cohort on mortality and length of stay.

OBJECTIVES: Direct comparisons between COVID-19 and influenza A in the critical care setting are limited. The objective of this study was to compare their outcomes and identify risk factors for hospital mortality. DESIGN AND SETTING: This was a territory-wide, retrospective study on all adult (≥18 years old) patients admitted to public hospital intensive care units in Hong Kong. We compared COVID-19 patients admitted between 27 January 2020 and 26 January 2021 with a propensity-matched historical cohort of influenza A patients admitted between 27 January 2015 and 26 January 2020. We reported outcomes of hospital mortality and time to death or discharge. Multivariate analysis using Poisson regression and relative risk (RR) was used to identify risk factors for hospital mortality. RESULTS: After propensity matching, 373 COVID-19 and 373 influenza A patients were evenly matched for baseline characteristics. COVID-19 patients had higher unadjusted hospital mortality than influenza A patients (17.5% vs 7.5%, p<0.001). The Acute Physiology and Chronic Health Evaluation IV (APACHE IV) adjusted standardised mortality ratio was also higher for COVID-19 than influenza A patients ((0.79 (95% CI 0.61 to 1.00) vs 0.42 (95% CI 0.28 to 0.60)), p<0.001). Adjusting for age, PaO2/FiO2, Charlson Comorbidity Index and APACHE IV, COVID-19 (adjusted RR 2.26 (95% CI 1.52 to 3.36)) and early bacterial-viral coinfection (adjusted RR 1.66 (95% CI 1.17 to 2.37)) were directly associated with hospital mortality. CONCLUSIONS: Critically ill patients with COVID-19 had substantially higher hospital mortality when compared with propensity-matched patients with influenza A.

Changes in Etiology and Clinical Outcomes of Pleural empyema during the COVID-19 Pandemic.

Healthcare-seeking behavior changed during the COVID-19 pandemic and might alter the epidemiology of pleural empyema. In this study, the incidence, etiology and outcomes of patients admitted for pleural empyema in Hong Kong in the pre-COVID-19 (January 2015-December 2019) and post-COVID-19 (January 2020-June 2022) periods were compared. Overall, Streptococcus pneumoniae was the predominant organism in <18-year-old patients, while Streptococcus anginosus, anaerobes and polymicrobial infections were more frequent in adults. In the post-COVID-19 period, a marked decline in the incidence of pleural empyema in children was observed (pre-COVID-19, 18.4 ± 4.8 vs. post-COVID-19, 2.0 ± 2.9 cases per year, p = 0.036), while the incidence in adults remained similar (pre-COVID-19, 189.0 ± 17.2 vs. post-COVID-19, 198.4 ± 5.0 cases per year; p = 0.23). In the post-COVID-19 period, polymicrobial etiology increased (OR 11.37, p < 0.0001), while S. pneumoniae etiology decreased (OR 0.073, p < 0.001). In multivariate analysis, clinical outcomes (length of stay, ICU admission, use of intrapleural fibrinolytic therapy, surgical intervention, death) were not significantly different in pre- and post-COVID-19 periods. In conclusion, an increase in polymicrobial pleural empyema was observed during the pandemic. We postulate that this is related to the delayed presentation of pneumonia to hospitals.

CDK5RAP2 is a Wnt target gene and promotes stemness and progression of oral squamous cell carcinoma.

In oral squamous cell carcinoma (OSCC), a highly aggressive and frequently lethal malignancy, the role and action mechanism of the microtubule regulatory protein CDK5RAP2 have not been fully understood. Here, we show that CDK5RAP2 is highly expressed in OSCC and its expression correlates with clinical stage and lymph node metastasis of the disease. The expression of CDK5RAP2 is regulated by the Wnt signaling pathway. Depletion of CDK5RAP2 inhibits the tumorigenesis and migration of OSCC cells and alters the OSCC cancer stem (-like) cell (CSC) signature. Notably, suppression of CDK5RAP2 expression disrupts spindle orientation during mitosis. Collectively, these results identify CDK5RAP2 as a potential CSC marker and reveal a mechanism that controls the CSC population in OSCC.

Worsening of asthma control after recovery from mild to moderate COVID-19 in patients from Hong Kong.

BACKGROUND: While there are postulations that asthma is potentially associated with severe coronavirus disease 2019 (COVID-19), there has been conflicting results from studies on the impact mild-to-moderate COVID-19 on asthma control after recovery. METHODS: A case control study on the association between mild-to-moderate COVID-19 and asthma control post infection was conducted. The primary outcome was a reduction in Asthma Control Test (ACT) score by ≥ 3 points post-COVID infection. The secondary outcomes included the change in ACT score, the proportion of patient with ACT score who dropped to ≤ 15 on enrolment visit and the need for escalation of asthma maintenance therapy. RESULTS: Out of the total of 221 adult patients with asthma recruited, 111 had mild-to-moderate COVID-19 within 30 to 270 days prior to study enrolment. The adjusted odds ratio (aOR) for a reduction in ACT score by ≥ 3 points after COVID-19 was 3.105 (95% CI = 1.385-6.959, p = 0.006). The odds of escalation of asthma maintenance therapy by at least 1 Global Initiative for Asthma (GINA) step was 4.733 (95% CI = 1.151-19.467, p = 0.031) and asthma patient are more likely to become uncontrolled after COVID-19 [aOR = 5.509 (95% CI = 1.061-28.600, p = 0.042)]. CONCLUSION: Mild-to-moderate COVID-19 among asthma patients, upon recovery, was associated with worsening of asthma symptom, lower ACT score, a higher need for escalation of asthma maintenance therapy and more uncontrolled asthma.

Deep learning attention-guided radiomics for COVID-19 chest radiograph classification.

Background: Accurate assessment of coronavirus disease 2019 (COVID-19) lung involvement through chest radiograph plays an important role in effective management of the infection. This study aims to develop a two-step feature merging method to integrate image features from deep learning and radiomics to differentiate COVID-19, non-COVID-19 pneumonia and normal chest radiographs (CXR). Methods: In this study, a deformable convolutional neural network (deformable CNN) was developed and used as a feature extractor to obtain 1,024-dimensional deep learning latent representation (DLR) features. Then 1,069-dimensional radiomics features were extracted from the region of interest (ROI) guided by deformable CNN's attention. The two feature sets were concatenated to generate a merged feature set for classification. For comparative experiments, the same process has been applied to the DLR-only feature set for verifying the effectiveness of feature concatenation. Results: Using the merged feature set resulted in an overall average accuracy of 91.0% for three-class classification, representing a statistically significant improvement of 0.6% compared to the DLR-only classification. The recall and precision of classification into the COVID-19 class were 0.926 and 0.976, respectively. The feature merging method was shown to significantly improve the classification performance as compared to using only deep learning features, regardless of choice of classifier (P value <0.0001). Three classes' F1-score were 0.892, 0.890, and 0.950 correspondingly (i.e., normal, non-COVID-19 pneumonia, COVID-19). Conclusions: A two-step COVID-19 classification framework integrating information from both DLR and radiomics features (guided by deep learning attention mechanism) has been developed. The proposed feature merging method has been shown to improve the performance of chest radiograph classification as compared to the case of using only deep learning features.

Artificial intelligence-assisted multistrategy image enhancement of chest X-rays for COVID-19 classification.

Background: The coronavirus disease 2019 (COVID-19) led to a dramatic increase in the number of cases of patients with pneumonia worldwide. In this study, we aimed to develop an AI-assisted multistrategy image enhancement technique for chest X-ray (CXR) images to improve the accuracy of COVID-19 classification. Methods: Our new classification strategy consisted of 3 parts. First, the improved U-Net model with a variational encoder segmented the lung region in the CXR images processed by histogram equalization. Second, the residual net (ResNet) model with multidilated-rate convolution layers was used to suppress the bone signals in the 217 lung-only CXR images. A total of 80% of the available data were allocated for training and validation. The other 20% of the remaining data were used for testing. The enhanced CXR images containing only soft tissue information were obtained. Third, the neural network model with a residual cascade was used for the super-resolution reconstruction of low-resolution bone-suppressed CXR images. The training and testing data consisted of 1,200 and 100 CXR images, respectively. To evaluate the new strategy, improved visual geometry group (VGG)-16 and ResNet-18 models were used for the COVID-19 classification task of 2,767 CXR images. The accuracy of the multistrategy enhanced CXR images was verified through comparative experiments with various enhancement images. In terms of quantitative verification, 8-fold cross-validation was performed on the bone suppression model. In terms of evaluating the COVID-19 classification, the CXR images obtained by the improved method were used to train 2 classification models. Results: Compared with other methods, the CXR images obtained based on the proposed model had better performance in the metrics of peak signal-to-noise ratio and root mean square error. The super-resolution CXR images of bone suppression obtained based on the neural network model were also anatomically close to the real CXR images. Compared with the initial CXR images, the classification accuracy rates of the internal and external testing data on the VGG-16 model increased by 5.09% and 12.81%, respectively, while the values increased by 3.51% and 18.20%, respectively, for the ResNet-18 model. The numerical results were better than those of the single-enhancement, double-enhancement, and no-enhancement CXR images. Conclusions: The multistrategy enhanced CXR images can help to classify COVID-19 more accurately than the other existing methods.

A Phase II Trial of Guadecitabine in Children and Adults with SDH-Deficient GIST, Pheochromocytoma, Paraganglioma, and HLRCC-Associated Renal Cell Carcinoma.

PURPOSE: Succinate dehydrogenase (dSDH)-deficient tumors, including pheochromocytoma/paraganglioma, hereditary leiomyomatosis and renal cell cancer-associated renal cell carcinoma (HLRCC-RCC), and gastrointestinal stromal tumors (GIST) without KIT or platelet-derived growth factor receptor alpha mutations are often resistant to cytotoxic chemotherapy, radiotherapy, and many targeted therapies. We evaluated guadecitabine, a dinucleotide containing the DNA methyltransferase inhibitor decitabine, in these patient populations. PATIENTS AND METHODS: Phase II study of guadecitabine (subcutaneously, 45 mg/m2/day for 5 consecutive days, planned 28-day cycle) to assess clinical activity (according to RECISTv.1.1) across three strata of patients with dSDH GIST, pheochromocytoma/paraganglioma, or HLRCC-RCC. A Simon optimal two-stage design (target response rate 30% rule out 5%) was used. Biologic correlates (methylation and metabolites) from peripheral blood mononuclear cells (PBMC), serum, and urine were analyzed. RESULTS: Nine patients (7 with dSDH GIST, 1 each with paraganglioma and HLRCC-RCC, 6 females and 3 males, age range 18-57 years) were enrolled. Two patients developed treatment-limiting neutropenia. No partial or complete responses were observed (range 1-17 cycles of therapy). Biologic activity assessed as global demethylation in PBMCs was observed. No clear changes in metabolite concentrations were observed. CONCLUSIONS: Guadecitabine was tolerated in patients with dSDH tumors with manageable toxicity. Although 4 of 9 patients had prolonged stable disease, there were no objective responses. Thus, guadecitabine did not meet the target of 30% response rate across dSDH tumors at this dose, although signs of biologic activity were noted.

Restrictive and liberal transfusion strategies in extracorporeal membrane oxygenation: A retrospective observational study.

BACKGROUND: To compare the outcomes of patients requiring extracorporeal membrane oxygenation (ECMO) support who had a restrictive transfusion strategy with those who had a liberal strategy. STUDY DESIGN AND METHODS: We retrospectively reviewed all adult patients from 2010 to 2019 who received a minimum of one packed red blood cell (pRBC) during ECMO. Hemoglobin values before each transfusion were retrieved. Restrictive transfusion strategy was defined as a transfusion threshold ≤8.5 g/dl in all transfusion episodes for a single patient, while liberal transfusion strategy was defined as a transfusion threshold >8.5 g/dl in any transfusion episode. RESULTS: The analysis included 763 patients, with 138 (18.1%) patients in the restrictive and 625 (81.9%) in the liberal transfusion strategy group. The median hemoglobin level, taking into account all measured hemoglobin values, during ECMO support was 8.3 and 9.9 g/dl, and the average units of pRBC received per day were 0.7 (0.3-1.8) and 1.2 (0.6-2.3), respectively. There were no significant differences in intensive care unit (ICU) mortality (adjusted odds ratio (OR), 0.86; 95% CI 0.56-1.30; p = .47), hospital mortality (adjusted OR, 0.79; 95% CI 0.52-1.21; p = .28), and 90-day mortality (adjusted OR, 0.84; 95% CI 0.55-1.28; p = .42) between the two groups. Among subgroup analyses, a restrictive transfusion strategy was associated with decreased risk of ICU mortality in patients on veno-venous ECMO (adjusted OR, 0.36; 95% CI 0.17-0.73; p = .005). There was no heterogeneity on outcomes across patients stratified by age, APACHE IV score, or need for large volume transfusion. DISCUSSION: Our data suggested it may be safe to adopt a restrictive red cell transfusion threshold of 8.5 g/dl in patients on ECMO, and highlighted the need for prospective trials in this heavily-transfused population.

Genome of the sea anemone Exaiptasia pallida and transcriptome profiles during tentacle regeneration.

Cnidarians including sea anemones, corals, hydra, and jellyfishes are a group of animals well known for their regeneration capacity. However, how non-coding RNAs such as microRNAs (also known as miRNAs) contribute to cnidarian tissue regeneration is poorly understood. Here, we sequenced and assembled the genome of the sea anemone Exaiptasia pallida collected in Hong Kong waters. The assembled genome size of E. pallida is 229.21 Mb with a scaffold N50 of 10.58 Mb and BUSCO completeness of 91.1%, representing a significantly improved genome assembly of this species. The organization of ANTP-class homeobox genes in this anthozoan further supported the previous findings in jellyfishes, where most of these genes are mainly located on three scaffolds. Tentacles of E. pallida were excised, and both mRNA and miRNA were sequenced at 9 time points (0 h, 6 h, 12 h, 18 h, 1 day, 2, 3, 6, and 8 days) from regenerating tentacles. In addition to the Wnt signaling pathway and homeobox genes that are shown to be likely involved in tissue regeneration as in other cnidarians, we have shown that GLWamide neuropeptides, and for the first time sesquiterpenoid pathway genes could potentially be involved in the late phase of cnidarian tissue regeneration. The established sea anemone model will be useful for further investigation of biology and evolution in, and the effect of climate change on this important group of animals.

Computed tomographic imaging features of maxillary and mandibular melanotic neuroectodermal tumor of infancy: Report of 2 cases and systematic review.

OBJECTIVE: The aim of this systematic review was to determine the computed tomographic (CT) imaging characteristics of maxillary and mandibular melanotic neuroectodermal tumor of infancy (MNTI). Two cases from our institution were also presented. STUDY DESIGN: Full-text case reports and case series of histopathologically proven gnathic MNTI with CT figures of diagnostic quality were searched in PubMed, Scopus, Web of Science, Ovid, and Google Scholar databases from July 2021 to February 2022. Descriptive statistics were used to determine the frequency of each CT feature of gnathic MNTI. RESULTS: Fifty-two published studies met the eligibility criteria, providing a total of 53 maxillary and mandibular MNTIs for analysis. In order of frequency, the CT features of gnathic MNTI that were present in over half of the study sample were bone expansion (53, 100%), a well-defined periphery (49, 92.5%), tooth displacement (45, 84.9%), and a bilocular radiolucent internal pattern (32, 60.4%). CONCLUSIONS: The bilocular radiolucent internal pattern has not been recognized as a common CT feature of gnathic MNTI. When associated with a well-defined, expansile mass in the infantile maxilla or mandible, this imaging characteristic can support a radiologic interpretation of MNTI.

Development and validation of bone-suppressed deep learning classification of COVID-19 presentation in chest radiographs.

Background: Coronavirus disease 2019 (COVID-19) is a pandemic disease. Fast and accurate diagnosis of COVID-19 from chest radiography may enable more efficient allocation of scarce medical resources and hence improved patient outcomes. Deep learning classification of chest radiographs may be a plausible step towards this. We hypothesize that bone suppression of chest radiographs may improve the performance of deep learning classification of COVID-19 phenomena in chest radiographs. Methods: Two bone suppression methods (Gusarev et al. and Rajaraman et al.) were implemented. The Gusarev and Rajaraman methods were trained on 217 pairs of normal and bone-suppressed chest radiographs from the X-ray Bone Shadow Suppression dataset (https://www.kaggle.com/hmchuong/xray-bone-shadow-supression). Two classifier methods with different network architectures were implemented. Binary classifier models were trained on the public RICORD-1c and RSNA Pneumonia Challenge datasets. An external test dataset was created retrospectively from a set of 320 COVID-19 positive patients from Queen Elizabeth Hospital (Hong Kong, China) and a set of 518 non-COVID-19 patients from Pamela Youde Nethersole Eastern Hospital (Hong Kong, China), and used to evaluate the effect of bone suppression on classifier performance. Classification performance, quantified by sensitivity, specificity, negative predictive value (NPV), accuracy and area under the receiver operating curve (AUC), for non-suppressed radiographs was compared to that for bone suppressed radiographs. Some of the pre-trained models used in this study are published at (https://github.com/danielnflam). Results: Bone suppression of external test data was found to significantly (P<0.05) improve AUC for one classifier architecture [from 0.698 (non-suppressed) to 0.732 (Rajaraman-suppressed)]. For the other classifier architecture, suppression did not significantly (P>0.05) improve or worsen classifier performance. Conclusions: Rajaraman suppression significantly improved classification performance in one classification architecture, and did not significantly worsen classifier performance in the other classifier architecture. This research could be extended to explore the impact of bone suppression on classification of different lung pathologies, and the effect of other image enhancement techniques on classifier performance.

Effect of hospital case volume on clinical outcomes of patients requiring extracorporeal membrane oxygenation: a territory-wide longitudinal observational study.

Background: The utilization of extracorporeal membrane oxygenation (ECMO) has increased rapidly around the world. Being an overall low-volume high-cost form of therapy, the effectiveness of having care delivered in segregated units across a geographical locality is debatable. Methods: All adult extracorporeal membrane oxygenation cases admitted to public hospitals in Hong Kong between 2010 and 2019 were included. "High-volume" centers were defined as those with >20 extracorporeal membrane oxygenation cases in the respective calendar year, while "low-volume" centers were those with ≤20. Clinical outcomes of patients who received extracorporeal membrane oxygenation care in high-volume centers were compared with those in low-volume centers. Results: A total of 911 patients received extracorporeal membrane oxygenation-297 (32.6%) veno-arterial extracorporeal membrane oxygenation, 450 (49.4%) veno-venous extracorporeal membrane oxygenation, and 164 (18.0%) extracorporeal membrane oxygenation-cardiopulmonary resuscitation. The overall hospital mortality was 456 (50.1%). The annual number of extracorporeal membrane oxygenation cases in high- and low-volume centers were 29 and 11, respectively. Management in a high-volume center was not significantly associated with hospital mortality (adjusted odds ratio (OR) 0.86, 95% confidence interval (CI): 0.61-1.21, P=0.38), or with intensive care unit mortality (adjusted OR 0.76, 95% CI: 0.54-1.06, P=0.10) compared with a low-volume center. Over the 10-year period, the overall observed mortality was similar to the Acute Physiology And Chronic Health Evaluation IV-predicted mortality, with no significant difference in the standardized mortality ratios between high- and low-volume centers (P=0.46). Conclusions: In a territory-wide observational study, we observed that case volumes in extracorporeal membrane oxygenation centers were not associated with hospital mortality. Maintaining standards of care in low-volume centers is important and improves preparedness for surges in demand.

Adenoidal-Nasopharyngeal Ratio in Healthy Adults on Cone Beam Computed Tomography.

OBJECTIVE: This study aimed to quantify the adenoidal-nasopharyngeal ratio (ANR) in a cohort of healthy adults on cone beam computed tomography (CT) using the Fujioka method, which is a reproducible measure of adenoid size and nasopharyngeal patency. METHODS: Electronic health records and maxillofacial cone beam CT in 202 consecutive patients aged 16 years and older were retrospectively reviewed. Patients with a history of adenoidectomy, sinonasal disease, lymphoproliferative disorders, and cleft palate were excluded from the study. The midsagittal reconstructed cone beam CT image was used to determine the ANR. Statistical analysis was conducted using 1-way analysis of variance. RESULTS: Of the 202 subjects, 131 were female and 71 were male. The mean ± SD subject age was 45.43 ± 20.79 years (range, 16-91 years). The mean ± SD ANR in all subjects was 0.22 ± 0.13 (range, 0.03-0.75) and in each decade of adult life was as follows: younger than 21 years, 0.39 ± 0.12; 21 to 30 years, 0.29 ± 0.11; 31 to 40 years, 0.21 ± 0.09; 41 to 50 years, 0.20 ± 0.07; 51 to 60 years, 0.16 ± 0.10; 61 to 70 years, 0.13 ± 0.05; 71 to 80 years, 0.12 ± 0.05; 81 to 90 years, 0.11 ± 0.04; and 91 years or older, 0.10 ± 0. The differences in mean ANR among the age subgroups were statistically significant ( P < 0.001). CONCLUSIONS: The mean ANR gradually decreased from 0.39 in the second decade of life to 0.16 in the sixth decade of life and plateaued at approximately 0.10 thereafter.