Cross-site validation of lung cancer diagnosis by electronic nose with deep learning: a multicenter prospective study.

BACKGROUND: Although electronic nose (eNose) has been intensively investigated for diagnosing lung cancer, cross-site validation remains a major obstacle to be overcome and no studies have yet been performed. METHODS: Patients with lung cancer, as well as healthy control and diseased control groups, were prospectively recruited from two referral centers between 2019 and 2022. Deep learning models for detecting lung cancer with eNose breathprint were developed using training cohort from one site and then tested on cohort from the other site. Semi-Supervised Domain-Generalized (Semi-DG) Augmentation (SDA) and Noise-Shift Augmentation (NSA) methods with or without fine-tuning was applied to improve performance. RESULTS: In this study, 231 participants were enrolled, comprising a training/validation cohort of 168 individuals (90 with lung cancer, 16 healthy controls, and 62 diseased controls) and a test cohort of 63 individuals (28 with lung cancer, 10 healthy controls, and 25 diseased controls). The model has satisfactory results in the validation cohort from the same hospital while directly applying the trained model to the test cohort yielded suboptimal results (AUC, 0.61, 95% CI: 0.47─0.76). The performance improved after applying data augmentation methods in the training cohort (SDA, AUC: 0.89 [0.81─0.97]; NSA, AUC:0.90 [0.89─1.00]). Additionally, after applying fine-tuning methods, the performance further improved (SDA plus fine-tuning, AUC:0.95 [0.89─1.00]; NSA plus fine-tuning, AUC:0.95 [0.90─1.00]). CONCLUSION: Our study revealed that deep learning models developed for eNose breathprint can achieve cross-site validation with data augmentation and fine-tuning. Accordingly, eNose breathprints emerge as a convenient, non-invasive, and potentially generalizable solution for lung cancer detection. CLINICAL TRIAL REGISTRATION: This study is not a clinical trial and was therefore not registered.

Physiomimetic Fluidic Culture Platform on Microwell-Patterned Porous Collagen Scaffold for Human Pancreatic Islets.

Pancreatic islet transplantation is one of the clinical options for certain types of diabetes. However, difficulty in maintaining islets prior to transplantation limits the clinical expansion of islet transplantations. Our study introduces a dynamic culture platform developed specifically for primary human islets by mimicking the physiological microenvironment, including tissue fluidics and extracellular matrix support. We engineered the dynamic culture system by incorporating our distinctive microwell-patterned porous collagen scaffolds for loading isolated human islets, enabling vertical medium flow through the scaffolds. The dynamic culture system featured four 12 mm diameter islet culture chambers, each capable of accommodating 500 islet equivalents (IEQ) per chamber. This configuration calculates > five-fold higher seeding density than the conventional islet culture in flasks prior to the clinical transplantations (442 vs 86 IEQ/cm2). We tested our culture platform with three separate batches of human islets isolated from deceased donors for an extended period of 2 weeks, exceeding the limits of conventional culture methods for preserving islet quality. Static cultures served as controls. The computational simulation revealed that the dynamic culture reduced the islet volume exposed to the lethal hypoxia (< 10 mmHg) to ~1/3 of the static culture. Dynamic culture ameliorated the morphological islet degradation in long-term culture and maintained islet viability, with reduced expressions of hypoxia markers. Furthermore, dynamic culture maintained the islet metabolism and insulin-secreting function over static culture in a long-term culture. Collectively, the physiological microenvironment-mimetic culture platform supported the viability and quality of isolated human islets at high-seeding density. Such a platform has a high potential for broad applications in cell therapies and tissue engineering, including extended islet culture prior to clinical islet transplantations and extended culture of stem cell-derived islets for maturation.

Real-world osimertinib pretreatment experience in patients with epidermal growth factor receptor T790M mutation-positive locally advanced or metastatic non-small cell lung cancer.

Osimertinib has demonstrated efficacy in patients with epidermal growth factor receptor (EGFR) T790M-positive non-small cell lung cancer (NSCLC) in clinical trials. However, real-world data on its effectiveness remain scarce. Taiwanese patients with T790M-positive locally advanced or metastatic NSCLC and progressive disease following treatment with at least one EGFR tyrosine kinase inhibitor (TKI) were enrolled from the osimertinib early access program. Of the 419 patients (mean age, 63 years; female, 67%), 53% were heavily pretreated (≥ third-line [3L]), making osimertinib a fourth-line (4L) intervention. The median progression-free survival (PFS) was 10.5 months (95% confidence interval [CI]: 8.95-11.41); the 18-month PFS rate was 26.5%. The median overall survival (OS) was 19.0 months (95% CI: 16.30-20.95); the 24-month OS rate was 40.9%. The objective response rate was 32.46%, and the disease control rate was 86.38%. The median time to treatment discontinuation of osimertinib monotherapy was 11.9 months (95% CI: 10.49-13.11). Subgroup analyses of median PFS and OS in the chemotherapy combination group vs. the osimertinib monotherapy group yielded no difference. Central nervous system (CNS) metastasis, number of prior lines of therapy, and types of initial EGFR-TKIs did not significantly impact outcomes. The median PFS values were 9.0 (95% CI: 5.18-11.34) and 10.9 (95% CI: 9.18-11.90) months with and without CNS metastasis, respectively, and 10.8 (95% CI: 8.59-12.69), 13.6 (95% CI: 10.89-16.3), and 9.2 (95% CI: 7.8-10.62) months for second-line (2L), 3L, and ≥4L therapy, respectively. In patients who received osimertinib as 2L therapy, the median PFS values in response to prior afatinib, erlotinib and gefitinib treatment were 11.2 (95% CI: 4.85-4.79), 10.5 (95% CI: 8.59-20.26) and 8.7 (95% CI: 7.21-16.79) months, respectively. Overall, real-world data from Taiwan support the clinical benefits of osimertinib in EGFR T790M -positive NSCLC.

Integrative metagenomic analysis reveals distinct gut microbial signatures related to obesity.

Obesity is a metabolic disorder closely associated with profound alterations in gut microbial composition. However, the dynamics of species composition and functional changes in the gut microbiome in obesity remain to be comprehensively investigated. In this study, we conducted a meta-analysis of metagenomic sequencing data from both obese and non-obese individuals across multiple cohorts, totaling 1351 fecal metagenomes. Our results demonstrate a significant decrease in both the richness and diversity of the gut bacteriome and virome in obese patients. We identified 38 bacterial species including Eubacterium sp. CAG:274, Ruminococcus gnavus, Eubacterium eligens and Akkermansia muciniphila, and 1 archaeal species, Methanobrevibacter smithii, that were significantly altered in obesity. Additionally, we observed altered abundance of five viral families: Mesyanzhinovviridae, Chaseviridae, Salasmaviridae, Drexlerviridae, and Casjensviridae. Functional analysis of the gut microbiome indicated distinct signatures associated to obesity and identified Ruminococcus gnavus as the primary driver for function enrichment in obesity, and Methanobrevibacter smithii, Akkermansia muciniphila, Ruminococcus bicirculans, and Eubacterium siraeum as functional drivers in the healthy control group. Additionally, our results suggest that antibiotic resistance genes and bacterial virulence factors may influence the development of obesity. Finally, we demonstrated that gut vOTUs achieved a diagnostic accuracy with an optimal area under the curve of 0.766 for distinguishing obesity from healthy controls. Our findings offer comprehensive and generalizable insights into the gut bacteriome and virome features associated with obesity, with the potential to guide the development of microbiome-based diagnostics.

Communication-Efficient Hybrid Federated Learning for E-Health With Horizontal and Vertical Data Partitioning.

Electronic healthcare (e-health) allows smart devices and medical institutions to collaboratively collect patients' data, which is trained by artificial intelligence (AI) technologies to help doctors make diagnosis. By allowing multiple devices to train models collaboratively, federated learning is a promising solution to address the communication and privacy issues in e-health. However, applying federated learning in e-health faces many challenges. First, medical data are both horizontally and vertically partitioned. Since single horizontal federated learning (HFL) or vertical federated learning (VFL) techniques cannot deal with both types of data partitioning, directly applying them may consume excessive communication cost due to transmitting a part of raw data when requiring high modeling accuracy. Second, a naive combination of HFL and VFL has limitations including low training efficiency, unsound convergence analysis, and lack of parameter tuning strategies. In this article, we provide a thorough study on an effective integration of HFL and VFL, to achieve communication efficiency and overcome the above limitations when data are both horizontally and vertically partitioned. Specifically, we propose a hybrid federated learning framework with one intermediate result exchange and two aggregation phases. Based on this framework, we develop a hybrid stochastic gradient descent (HSGD) algorithm to train models. Then, we theoretically analyze the convergence upper bound of the proposed algorithm. Using the convergence results, we design adaptive strategies to adjust the training parameters and shrink the size of transmitted data. The experimental results validate that the proposed HSGD algorithm can achieve the desired accuracy while reducing communication cost, and they also verify the effectiveness of the adaptive strategies.

Study on the Equivalence Transformation between Blasting Vibration Velocity and Acceleration.

The evaluation of blasting vibrations primarily hinges on two physical quantities: velocity and acceleration. A significant challenge arises when attempting to reference the two types of vibration data in relation to one another, such as different types of seismometers, noise, etc., necessitating a method for their equivalent transformation. To address this, a transformation method is discussed in detail with a case study, and equations for the ratio (Ra) of the particle peak velocity (PPV) to the particle peak acceleration (PPA) are proposed. The findings are twofold: (1) The conventional data conversion processes often suffer from low accuracy due to the presence of trend terms and noise in the signal. To mitigate this, the built-in MATLAB function is used for trend term elimination, complemented by a combined approach that integrates CEEMDAN with WD/WDP for noise reduction. These significantly enhance the accuracy of the transformation. (2) This analysis reveals a positive power function correlation between Ra and the propagation distance of the blast vibrations, contrasted by a negative correlation with the maximum charge per delay. Intriguingly, the Ra values observed in pre-splitting blasting operations are consistently lower than those in bench blasting. The established Ra equations offer a rapid, direct method for assessing the transformation between the PPV and PPA, providing valuable insights for the optimization of blasting design.

A novel approach to determine the critical survival threshold of cellular oxygen within spheroids via integrating live/dead cell imaging with oxygen modeling.

Defining the oxygen level that induces cell death within 3-D tissues is vital for understanding tissue hypoxia; however, obtaining accurate measurements has been technically challenging. In this study, we introduce a noninvasive, high-throughput methodology to quantify critical survival partial oxygen pressure (pO2) with high spatial resolution within spheroids by using a combination of controlled hypoxic conditions, semiautomated live/dead cell imaging, and computational oxygen modeling. The oxygen-permeable, micropyramid patterned culture plates created a precisely controlled oxygen condition around the individual spheroid. Live/dead cell imaging provided the geometric information of the live/dead boundary within spheroids. Finally, computational oxygen modeling calculated the pO2 at the live/dead boundary within spheroids. As proof of concept, we determined the critical survival pO2 in two types of spheroids: isolated primary pancreatic islets and tumor-derived pseudoislets (2.43 ± 0.08 vs. 0.84 ± 0.04 mmHg), indicating higher hypoxia tolerance in pseudoislets due to their tumorigenic origin. We also applied this method for evaluating graft survival in cell transplantations for diabetes therapy, where hypoxia is a critical barrier to successful transplantation outcomes; thus, designing oxygenation strategies is required. Based on the elucidated critical survival pO2, 100% viability could be maintained in a typically sized primary islet under the tissue pO2 above 14.5 mmHg. This work presents a valuable tool that is potentially instrumental for fundamental hypoxia research. It offers insights into physiological responses to hypoxia among different cell types and may refine translational research in cell therapies.NEW & NOTEWORTHY Our study introduces an innovative combinatory approach for noninvasively determining the critical survival oxygen level of cells within small cell spheroids, which replicates a 3-D tissue environment, by seamlessly integrating three pivotal techniques: cell death induction under controlled oxygen conditions, semiautomated imaging that precisely identifies live/dead cells, and computational modeling of oxygen distribution. Notably, our method ensures high-throughput analysis applicable to various cell types, offering a versatile solution for researchers in diverse fields.

Immunometabolic features of natural killer cells are associated with infection outcomes in critical illness.

Immunosuppression increases the risk of nosocomial infection in patients with chronic critical illness. This exploratory study aimed to determine the immunometabolic signature associated with nosocomial infection during chronic critical illness. We prospectively recruited patients who were admitted to the respiratory care center and who had received mechanical ventilator support for more than 10 days in the intensive care unit. The study subjects were followed for the occurrence of nosocomial infection until 6 weeks after admission, hospital discharge, or death. The cytokine levels in the plasma samples were measured. Single-cell immunometabolic regulome profiling by mass cytometry, which analyzed 16 metabolic regulators in 21 immune subsets, was performed to identify immunometabolic features associated with the risk of nosocomial infection. During the study period, 37 patients were enrolled, and 16 patients (43.2%) developed nosocomial infection. Unsupervised immunologic clustering using multidimensional scaling and logistic regression analyses revealed that expression of nuclear respiratory factor 1 (NRF1) and carnitine palmitoyltransferase 1a (CPT1a), key regulators of mitochondrial biogenesis and fatty acid transport, respectively, in natural killer (NK) cells was significantly associated with nosocomial infection. Downregulated NRF1 and upregulated CPT1a were found in all subsets of NK cells from patients who developed a nosocomial infection. The risk of nosocomial infection is significantly correlated with the predictive score developed by selecting NK cell-specific features using an elastic net algorithm. Findings were further examined in an independent cohort of COVID-19-infected patients, and the results confirm that COVID-19-related mortality is significantly associated with mitochondria biogenesis and fatty acid oxidation pathways in NK cells. In conclusion, this study uncovers that NK cell-specific immunometabolic features are significantly associated with the occurrence and fatal outcomes of infection in critically ill population, and provides mechanistic insights into NK cell-specific immunity against microbial invasion in critical illness.

Regulation effect of magnetic field combined with low temperature storage on postharvest quality and cell wall pectic-polysaccharide degradation of Clausena lansium (Lour.) Skeels.

This study investigated the regulation effect of magnetic field combined with low temperature storage on postharvest quality and cell wall pectic-polysaccharide degradation of wampee stored for 15 d at 4 °C and 15 °C. Results showed that magnetic field combined with low temperature storage reduced browning rate of fruit after 15 d storage, but its effect on weight loss rate and total soluble solids (TSS) did not surpass that of storage temperature. Interestingly, contents of flavonoid, total phenols and malondialdehyde (MDA) were also lowered at varying degrees by combined treatment. Furthermore, molecular weight distribution and monosaccharide compositions of cell wall pectic-polysaccharides were also affected, which resulted from the coordinated action of cell wall pectin-degrading enzymes. The activities of these enzymes during storage, including polygalacturonase (PG), pectin methylesterase (PME) and ß-galactosidase (ß-Gal) in treated wampee decreased. These findings suggested that magnetic field combined with low temperature storage was an effective technology and had great potential in preservation of postharvest wampee in future.

Application of Laennec extrathecal blockade combined with indocyanine green fluorescence imaging in laparoscopic anatomic hepatectomy.

OBJECTIVE: To investigate the safety and application value of combining Laennec extracapsular occlusion with ICG fluorescence imaging in laparoscopic anatomic hepatectomy. METHODS: Complete laparoscopic dissection was performed outside the Laennec sheath, blocking Glisson's pedicle of the corresponding liver segment or lobe. An appropriate amount of indocyanine green (ICG) dye was intravenously injected, and the boundary line between the pre-cut liver segment and liver lobe was identified using fluorescence laparoscopy. Complete resection of the liver segment or lobe was performed based on anatomical markers. Clinical data, including operation time, intraoperative blood loss, postoperative hospital stay, and postoperative complications, were collected. RESULTS: A total of 14 cases were included in the study, including seven cases of primary liver cancer, three cases of metastatic liver cancer, three cases of intrahepatic bile duct calculi, and one case of hepatic hemangioma. All 14 patients underwent anatomic hepatectomy under fluorescent laparoscopy, with four cases involving the right liver, seven cases involving the left liver, two cases involving the right anterior lobe, and one case involving the right posterior lobe. CONCLUSION: Combining laparoscopic follow-up of the Laennec membrane with Glisson outer sheath block and intraoperative ICG fluorescence imaging provides real-time guidance for locating the resection boundaries during anatomic hepatectomy. This approach helps in controlling intraoperative bleeding, reducing operation time, and ensuring high safety. It holds significant value in clinical application.

Penthorum chinense Pursh inhibits ferroptosis in cellular and Caenorhabditis elegans models of Alzheimer's disease.

BACKGROUND: Ferroptosis, a unique type of cell death triggered by iron-dependent lipid peroxidation, plays a critical role in the pathogenesis of Alzheimer's disease (AD), a debilitating condition marked by memory loss and cognitive impairment due to the accumulation of beta-amyloid (Aß) and hyperphosphorylated Tau protein. Increasing evidence suggests that inhibitors of ferroptosis could be groundbreaking in the treatment of AD. METHOD: In this study, we established in vitro ferroptosis using erastin-, RSL-3-, hemin-, and iFSP1-induced PC-12 cells. Using MTT along with Hoechst/PI staining, we assessed cell viability and death. To determine various aspects of ferroptosis, we employed fluorescence probes, including DCFDA, JC-1, C11 BODIPY, Mito-Tracker, and PGSK, to measure ROS production, mitochondrial membrane potential, lipid peroxidation, mitochondrial morphology, and intracellular iron levels. Additionally, Western blotting, biolayer interferometry technology, and shRNA were utilized to investigate the underlying molecular mechanisms. Furthermore, p-CAX APP Swe/Ind- and pRK5-EGFP-Tau P301L overexpressing PC-12 cells, along with Caenorhabditis elegans (C. elegans) strains CL4176, CL2331, and BR5270, were employed to examine ferroptosis in AD models. RESULTS: Here, we conducted a screening of our natural medicine libraries and identified the ethanol extract of Penthorum chinense Pursh (PEE), particularly its ethyl acetate fraction (PEF), displayed inhibitory effects on ferroptosis in cells. Specifically, PEF inhibited the generation of ROS, lipid peroxidation, and intracellular iron levels. Furthermore, PEF demonstrated protective effects against H2O2-induced cell death, ROS production, and mitochondrial damage. Mechanistic investigations unveiled PEF's modulation of intracellular iron accumulation, GPX4 expression and activity, and FSP1 expression. In p-CAX APP Swe/Ind and pRK5-EGFP-Tau P301L overexpressing PC-12 cells, PEF significantly reduced cell death, as well as ROS and lipid peroxidase production. Moreover, PEF ameliorated paralysis and slowing rate in Aß and Tau transgenic C. elegans models, while inhibiting ferroptosis, as evidenced by decreased DHE intensity, lipid peroxidation levels, iron accumulation, and expression of SOD-3 and gst-4. CONCLUSION: Our findings highlight the suppressive effects of PEF on ferroptosis in AD cellular and C. elegans models. This study helps us better understand how ferroptosis affects AD and emphasizes the potential of PCP as a candidate for AD intervention.

Lung fluid content during 6MWT in patients with COPD with and without comorbid heart failure.

BACKGROUND: Impact of lung fluid content changing during exercise has not been investigated in chronic obstructive pulmonary disease (COPD). Using a novel point-of-care measurement system (remote dielectric sensing (ReDS) system), we aimed to investigate changes in lung fluid content before and after 6-minute walk test (6MWT); especially, differences between patients with and without comorbid heart failure (HF) were evaluated. METHODS: From June 2021 to July 2022, patients with COPD referred for 6MWT were prospectively enrolled. Measurements of lung fluid content by ReDS were conducted before and after 6MWT. Data on demographics, exacerbation history, spirometry and 6MWT were collected. Patients were also assessed for comorbid HF by cardiovascular evaluation. The main variables of interest were pre-6MWT ReDS, post-6MWT ReDS and post-pre ∆ReDS. RESULTS: In total, 133 patients with COPD were included. Comparisons between patients with COPD with and without HF indicated similar pre-6MWT ReDS (26.9%±5.9% vs 26.5%±4.7%; p=0.751), but a significant difference in post-6MWT ReDS (29.7%±6.3% vs 25.7%±5.3%; p=0.002). Patients with COPD without HF exhibited a significant decrease in post-6MWT ReDS (from 26.5% to 25.7%; paired t-test p=0.001); conversely, those with HF displayed a remarkable increase in post-6MWT ReDS (from 26.9% to 29.7%; paired t-test p<0.001). Receiver operating characteristic curve analysis showed an area under the curve of 0.82 (95% CI 0.71 to 0.93) for post-pre ∆ReDS in differentiating between patients with COPD with and without HF. CONCLUSIONS: Dynamic changes in lung fluid content prior to and following 6MWT significantly differed between patients with COPD with and without HF. Measurements of lung fluid content by ReDS during exercise testing may be of merit to identify patients with COPD with unrecognised HF.

A Bibliometric Analysis of Global Research Trends in Psoriasis and Metabolic Syndrome.

Background: Psoriasis is a frequent form of chronic inflammation in dermatology that is unmistakably linked to the metabolic syndrome (MetS) and its elements. This study was to explore the current status and new developments in the global research, and the holistic landscape of this field more intuitively through bibliometric analysis of scientific output and activity. Methods: Publications regarding psoriasis and MetS were searched and chosen from the database of the Web of Science Core Collection. Excel 2019, VOSviewer, and CiteSpace software were utilized to conduct bibliometric analysis. Results: There were 1096 publications included. The scientific outputs in this field had increased from 2004 to 2022, and the expansion could continue in the following years. The United States contributed the most publications (241, 21.99%) and had the most citation frequency (13,489 times). The University of California System was the most productive affiliation. Girolomoni G., Armstrong A.W., Gisondi P. and Gelfand J.M. were key and influential researchers. Journal of the European Academy of Dermatology and Venereology published the greatest number of articles (65 articles). By analyzing keyword frequency and clustering, we have identified the following areas of research interest and frontiers: prevalence, risk, association, gene expression, waist circumference, adipose tissue inflammation, vascular inflammation, cardiovascular disease, psoriatic arthritis, and fibrosis. Conclusion: This bibliometric analysis elucidates research domain of psoriasis and MetS, portraying present hotspots and future emerging trends. This field has generated significant interest and displays potential for further growth. The United States has made distinguished contributions, and currently dominates this field.

Traditional Chinese medicine Zhusha Anshen Wan: protective effects on liver, kidney, and intestine of the individual drugs using 1H NMR metabolomics.

Introduction: Zhusha Anshen Wan (ZSASW) is a traditional Chinese medicine compound mainly composed of mineral drugs. In clinical practice, ZSASW did not show the toxicity of administering equal doses of cinnabar alone, suggesting that the four combination herbs in ZSASW can alleviate the damage of cinnabar. The effect of each herb on reducing the toxicity of cinnabar has not been fully explained. Methods: In our study, we utilized a metabonomics approach based on high-resolution 1H nuclear magnetic resonance spectroscopy to investigate the reduction of toxicity by each herb in ZSASW. Liver, kidney and intestinal histopathology examinations and biochemical analysis of the serum were also performed. Results: Partial least squares-discriminant analysis (PLS-DA) was conducted to distinct different metabolic profiles in the urine and serum from the rats. Liver and kidney histopathology examinations, as well as analysis of serum clinical chemistry analysis, were also carried out. The metabolic profiles of the urine and serum of the rats in the CGU (treated with cinnabar and Glycyrrhiza uralensis Fisch) and CCC (treated with cinnabar and Coptis chinensis French) groups were remarkably similar to those of the control group, while those of the CRG (treated with cinnabar and Rehmannia glutinosa Libosch) and CAS (treated with cinnabar and Angelica sinensis) groups were close to those of the cinnabar group. The metabolic profiles of the urine and serum of the rats in the CGU and CCC groups were remarkably similar to those of the control group, while those of the CRG and CAS groups were close to those of the cinnabar group. Changes in endogenous metabolites associated with toxicity were identified. Rehmannia glutinosa, Rhizoma Coptidis and Glycyrrhiza uralensis Fisch could maintain the dynamic balance of the intestinal flora. These results were also verified by liver, kidney and intestinal histopathology examinations and biochemical analysis of the serum. The results suggested that Discussion: The metabolic mechanism of single drug detoxification in compound prescriptions has been elucidated. Coptis chinensis and Glycyrrhiza uralensis serve as the primary detoxification agents within ZSASW for mitigating liver, kidney, and intestinal damage caused by cinnabar. Detoxification can be observed through changes in the levels of various endogenous metabolites and related metabolic pathways.

The long-term outcome of chronic thromboembolic pulmonary hypertension: Pulmonary endarterectomy and balloon pulmonary angioplasty.

BACKGROUND: The long-term outcome on patients with chronic thromboembolic pulmonary hypertension (CTEPH) has not been ideal after standard medical treatment. However, good outcome for patients with CTEPH after interventions such as pulmonary endarterectomy (PEA) and balloon pulmonary angioplasty (BPA) has been reported recently. The aim of this study was to evaluate the impact of PEA or BPA on long-term outcomes for CTEPH patients in Han-Chinese population. METHODS: This was a multicenter, prospective case-control study. Patients with CTEPH were enrolled between January, 2018 and March, 2020. They were divided into two groups, including intervention (PEA or BPA) and conservative groups. The followed-up period was 26 months after treatment. The endpoints were all-cause mortality and CTEPH mortality. RESULTS: A total of 129 patients were enrolled and assigned to receive PEA/BPA (N = 73), or conservative therapy (N = 56). Overall, the 26-month survival rate of all-cause mortality was significantly higher in intervention group compared to that in conservative group (95.89% vs 80.36%; log-rank p = 0.0164). The similar trend was observed in the 26-month survival rate of CTEPH mortality (97.26% vs 85.71%; log-rank p = 0.0355). Regarding Cox proportional-hazard regression analysis, the hazard ratios (HRs) on patients with CTEPH receiving intervention in the outcome of all-cause mortality and CTEPH mortality were statistically significant (HR = 0.07 and p = 0.0141 in all-cause mortality; HR = 0.11 and p = 0.0461 in CTEPH mortality). CONCLUSION: This multicenter prospective case-control study demonstrated that intervention such as PEA and BPA increased the long-term survival rate for patient with CTEPH significantly. Intervention was an independent factor in long-term outcome for patients with CTEPH, including all-cause mortality and CTEPH mortality.

Comprehensive Genomic Analysis of Patients With Non-Small-Cell Lung Cancer Using Blood-Based Circulating Tumor DNA Assay: Findings From the BFAST Database of a Single Center in Taiwan.

PURPOSE: The Blood First Assay Screening Trial (BFAST) is a prospective study using next-generation sequencing (NGS) of circulating tumor DNA (ctDNA) in treatment-naïve advanced/metastatic non-small-cell lung cancer (NSCLC). We compared liquid biopsy to tissue testing and analyzed genomic alterations in Taiwanese patients with NSCLC using the BFAST database. MATERIALS AND METHODS: A total of 269 patients underwent FoundationOne Liquid Companion Diagnostic (F1LCDx) assay at the National Taiwan University Hospital, of whom 264 underwent tissue-based genetic testing also. We analyzed the actionable mutations and the concordance between tissue-based genetic testing, which was limited to EGFR, ALK, ROS1, and BRAF, in a real-life clinical setting and blood-based NGS in the clinical trial. Additionally, we analyzed the co-occurring genomic alterations from the blood-based ctDNA assay. RESULTS: A total of 76.2% patients showed actionable mutations. Standard tissue testing did not detect known driver alterations in about 22.7% of the patients (sensitivity, 70.24%). Liquid NGS detected additional mutations (RET, KRAS, MET, and ErbB2) in 14% of the patients, which went undetected by the standard-of-care testing. The complementary use of ctDNA NGS increased the detection rate by 42%. The F1LCDx assay had a sensitivity of 83.41%. Lower tumor and metastasis stages predicted nondetected blood-based NGS ctDNA results. Common co-occurring mutations in the blood-based NGS ctDNA assay were TP53, DNMT3A, TET2, PIK3CA, CTNNB1, and RB1. Among the patients with EGFR-mutated NSCLC, TET2 co-occurring alterations correlated with shorter progression-free survival of EGFR tyrosine kinase inhibitor treatment. CONCLUSION: NGS ctDNA analysis in comprehensive genetic testing improves actionable mutation identification, vital for treating Asian NSCLC cases with high actionable mutation rates. Lower stages correlated with undetected blood-based NGS ctDNA assay results.

Machine learning-directed electrical impedance tomography to predict metabolically vulnerable plaques.

The characterization of atherosclerotic plaques to predict their vulnerability to rupture remains a diagnostic challenge. Despite existing imaging modalities, none have proven their abilities to identify metabolically active oxidized low-density lipoprotein (oxLDL), a marker of plaque vulnerability. To this end, we developed a machine learning-directed electrochemical impedance spectroscopy (EIS) platform to analyze oxLDL-rich plaques, with immunohistology serving as the ground truth. We fabricated the EIS sensor by affixing a six-point microelectrode configuration onto a silicone balloon catheter and electroplating the surface with platinum black (PtB) to improve the charge transfer efficiency at the electrochemical interface. To demonstrate clinical translation, we deployed the EIS sensor to the coronary arteries of an explanted human heart from a patient undergoing heart transplant and interrogated the atherosclerotic lesions to reconstruct the 3D EIS profiles of oxLDL-rich atherosclerotic plaques in both right coronary and left descending coronary arteries. To establish effective generalization of our methods, we repeated the reconstruction and training process on the common carotid arteries of an unembalmed human cadaver specimen. Our findings indicated that our DenseNet model achieves the most reliable predictions for metabolically vulnerable plaque, yielding an accuracy of 92.59% after 100 epochs of training.

Phages modified hydrogel pellet assembled in 3D printed both-in-one device for detecting Pseudomonas aeruginosa based on colorimetric and pressure readout modes.

Pseudomonas aeruginosa (P. aeruginosa) with noticeable drug-resistance profile is one of the most pernicious pathogens that attracts major public health concerns. Herein, a 3D printed device combined with hydrogel pellet modified with phages was designed for point-of-care testing (POCT) of this pathogen with both colorimetric and pressure readout modes. A P. aeruginosa phage belonging to the family of Podoviridae was isolated from river water and noted as vB_PaeP-JZ1 (JZ1). Due to its host specificity, phage JZ1 was used as a recognizing agent for modifying the hydrogel pellet, and the modified hydrogel pellet was assembled into the 3D printed device to act as the sensing interface. Polymyxin B (PMB) was tagged with Pd@Pt core-shell nanodendrites (Pd@PtNDs) showing excellent peroxidase-like activity to act as the colorimetric and pressure signal tracer. P. aeruginosa can be quantified within the concentration ranges of 2.6 × 103 cfu mL-1 - 2.6 × 108 cfu mL-1 and 2.6 × 102 cfu mL-1 - 2.6 × 107 cfu mL-1 with colorimetric and pressure readout modes, respectively. The both modes can achieve quantitation of P. aeruginosa within 25 min. Thus the "both-in-one" 3D printed device with dual-mode readout function offers a rapid, sensitive, and specific platform for POCT of pathogenic bacteria.