The adaptive evolution of Quercus section Ilex using the chloroplast genomes of two threatened species.

Chloroplast (cp) genome sequences have been extensively used for phylogenetic and evolutionary analyses, as many have been sequenced in recent years. Identification of Quercus is challenging because many species overlap phenotypically owing to interspecific hybridization, introgression, and incomplete lineage sorting. Therefore, we wanted to gain a better understanding of this genus at the level of the maternally inherited chloroplast genome. Here, we sequenced, assembled, and annotated the cp genomes of the threatened Quercus marlipoensis (160,995 bp) and Q. kingiana (161,167 bp), and mined these genomes for repeat sequences and codon usage bias. Comparative genomic analyses, phylogenomics, and selection pressure analysis were also performed in these two threatened species along with other species of Quercus. We found that the guanine and cytosine content of the two cp genomes were similar. All 131 annotated genes, including 86 protein-coding genes, 37 transfer RNA genes, and 8 ribosomal RNA genes, had the same order in the two species. A strong A/T bias was detected in the base composition of simple sequence repeats. Among the 59 synonymous codons, the codon usage pattern of the cp genomes in these two species was more inclined toward the A/U ending. Comparative genomic analyses indicated that the cp genomes of Quercus section Ilex are highly conserved. We detected eight highly variable regions that could be used as molecular markers for species identification. The cp genome structure was consistent and different within and among the sections of Quercus. The phylogenetic analysis showed that section Ilex was not monophyletic and was divided into two groups, which were respectively nested with section Cerris and section Cyclobalanopsis. The two threatened species sequenced in this study were grouped into the section Cyclobalanopsis. In conclusion, the analyses of cp genomes of Q. marlipoensis and Q. kingiana promote further study of the taxonomy, phylogeny and evolution of these two threatened species and Quercus.

Automated valvular heart disease detection using heart sound with a deep learning algorithm.

Background: Insufficient clinicians' auscultation ability delays the diagnosis and treatment of valvular heart disease (VHD); artificial intelligence provides a solution to compensate for the insufficiency in auscultation ability by distinguishing between heart murmurs and normal heart sounds. However, whether artificial intelligence can automatically diagnose VHD remains unknown. Our objective was to use deep learning to process and compare raw heart sound data to identify patients with VHD requiring intervention. Methods: Heart sounds from patients with VHD and healthy controls were collected using an electronic stethoscope. Echocardiographic findings were used as the gold standard for this study. According to the chronological order of enrollment, the early-enrolled samples were used to train the deep learning model, and the late-enrollment samples were used to validate the results. Results: The final study population comprised 499 patients (354 in the algorithm training group and 145 in the result validation group). The sensitivity, specificity, and accuracy of the deep-learning model for identifying various VHDs ranged from 71.4 to 100.0%, 83.5-100.0%, and 84.1-100.0%, respectively; the best diagnostic performance was observed for mitral stenosis, with a sensitivity of 100.0% (31.0-100.0%), a specificity of 100% (96.7-100.0%), and an accuracy of 100% (97.5-100.0%). Conclusions: Based on raw heart sound data, the deep learning model effectively identifies patients with various types of VHD who require intervention and assists in the screening, diagnosis, and follow-up of VHD.

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.

Oral uracil-tegafur compared with intravenous chemotherapy as adjuvant therapy for resected early-stage non-small cell lung cancer patients.

BACKGROUND: Studies comparing the effectiveness of either adjuvant oral uracil-tegafur (UFT) or intravenous chemotherapy on early-stage (stage I and II) non-small cell lung cancer (NSCLC) patients treated with complete surgical treatment remain limited. METHODS: From January 2011 to December 2017, patients with early-stage NSCLC (defined as tumor size >3 cm without mediastinal lymph node involvement or any distant metastasis) receiving either adjuvant oral UFT or intravenous chemotherapy after surgical resection were identified from the Taiwan Cancer Registry. Overall survival (OS) and relapse-free survival (RFS) were the primary and secondary outcomes, respectively. Propensity matching was used for controlling confounders. RESULTS: A total of 840 patients receiving adjuvant therapy after surgery (including 595 oral UFT and 245 intravenous chemotherapy) were enrolled. Before matching, patients using oral UFT had significantly longer OS (HR: 0.69, 95% CI: 0.49-0.98, p = 0.0387) and RFS (HR: 0.79, 95% CI: 0.61-0.97, p = 0.0392) than those with intravenous chemotherapy. A matched cohort of 352 patients was created using 1:1 propensity score-matching. In the Cox regression analysis, the UFT and the matched chemotherapy groups had similar OS (HR: 0.80, 95% CI: 0.48-1.32, p = 0.3753) and RFS (HR: 0.98, 95% CI: 0.72-1.34, p = 0.9149). Among subgroup analysis, oral UFT use was associated with longer RFS among the subgroups of non-drinker (HR: 0.66, 95% CI: 0.34-0.99, p = 0.0478) and patients with stage IB disease (HR: 0.67, 95% CI: 0.42-0.97, p = 0.0341). CONCLUSIONS: This population-based study in the real-world setting of Taiwan demonstrates comparable effectiveness between oral UFT and intravenous chemotherapy in terms of clinical outcomes for early-stage NSCLC patients after surgery.

Cyclist Orientation Estimation Using LiDAR Data.

It is crucial for an autonomous vehicle to predict cyclist behavior before decision-making. When a cyclist is on real traffic roads, his or her body orientation indicates the current moving directions, and his or her head orientation indicates his or her intention for checking the road situation before making next movement. Therefore, estimating the orientation of cyclist's body and head is an important factor of cyclist behavior prediction for autonomous driving. This research proposes to estimate cyclist orientation including both body and head orientation using deep neural network with the data from Light Detection and Ranging (LiDAR) sensor. In this research, two different methods are proposed for cyclist orientation estimation. The first method uses 2D images to represent the reflectivity, ambient and range information collected by LiDAR sensor. At the same time, the second method uses 3D point cloud data to represent the information collected from LiDAR sensor. The two proposed methods adopt a model ResNet50, which is a 50-layer convolutional neural network, for orientation classification. Hence, the performances of two methods are compared to achieve the most effective usage of LiDAR sensor data in cyclist orientation estimation. This research developed a cyclist dataset, which includes multiple cyclists with different body and head orientations. The experimental results showed that a model that uses 3D point cloud data has better performance for cyclist orientation estimation compared to the model that uses 2D images. Moreover, in the 3D point cloud data-based method, using reflectivity information has a more accurate estimation result than using ambient information.

Incidence of and Risk Factors for Acute Kidney Injury During Antituberculosis Treatment: A Prospective Cohort Study and Literature Review.

INTRODUCTION: Acute kidney injury (AKI) is occasionally detected in patients receiving anti-tuberculosis (TB) treatment. This prospective cohort study is the first to investigate the incidence, risk factors, and renal outcomes of AKI during anti-TB treatment. METHODS: This study was conducted from January 1, 2016, to May 31, 2018. Patients with a new diagnosis of TB and on standard anti-TB treatment were enrolled, and the patients received regular laboratory monitoring. AKI was defined according to the Kidney Disease: Improving Global Outcome (KDIGO) criteria. Urinalysis, renal ultrasonography, blood erythrocyte morphology, and fractional excretion of sodium were performed at AKI onset. The TB treatment regimen was adjusted by the primary physician if necessary. Risk factors for AKI were identified through Cox regression. RESULTS: In total, 106 patients were recruited (mean age 52.6 years, 71.7% men). Eleven (10.3%) patients experienced AKI. Increased serum uric acid and hemoglobin levels were noted at AKI onset. All patients with AKI achieved renal recovery and completed anti-TB treatment containing rifampin. Age [hazard ratio (HR) 1.06 (1.02-1.11)], a higher baseline estimated glomerular filtration rate [eGFR; HR 1.04 (1.02-1.06)], and a blood eosinophil count > 350 (109/L) [HR 10.99 (2.28-53.02)] were associated with a higher risk of AKI during TB treatment. CONCLUSION: Regular pharmacovigilant monitoring revealed an incidence of renal impairment during anti-TB treatment that was higher than expected. AKI was more common in older patients with a higher eGFR and blood eosinophil count. However, the complications had no influence on TB treatment completion, and no permanent renal impairment occurred.

Impact of the COVID-19 pandemic on treatment for mental health needs: a perspective on service use patterns and expenditures from commercial medical claims data.

OBJECTIVE: To examine changes in use patterns, cost of healthcare services before and after the outbreak of the COVID-19 pandemic, and their impacts on expenditures for patients receiving treatment for depression, anxiety, eating disorders, and substance use. METHODS: This cross-sectional study employed statistical tests to analyze claims in MarketScan® Commercial Database in March 2020-February 2021 and quarterly from March 2020 to August 2021, compared to respective pre-pandemic periods. The analysis is based on medical episodes created by the Merative™ Medical Episode Grouper (MEG). MEG is a methodology that groups medical and prescription drug claims to create clinically relevant episodes of care. RESULTS: Comparing year-over-year changes, proportion of patients receiving anxiety treatment among all individuals obtaining healthcare services grew 13.7% in the first year of the pandemic (3/2020-2/2021) versus 10.0% in the year before the pandemic (3/2019-2/2020). This, along with a higher growth in price per episode (5.5% versus 4.3%) resulted in a greater increase in per claimant expenditure ($0.61 versus $0.41 per month). In the same periods, proportion of patients receiving treatment for depression grew 3.7% versus 6.9%, but per claimant expenditure grew by same amount due to an increase in price per episode (4.8%). Proportion of patients receiving treatment for anorexia started to increase 21.1% or more in the fall of 2020. Patient proportion of alcohol use in age group 18-34 decreased 17.9% during the pandemic but price per episode increased 26.3%. Patient proportion of opioid use increased 11.5% in March-May 2020 but decreased or had no significant changes in subsequent periods. CONCLUSIONS: We investigated the changes in use patterns and expenditures of mental health patients before and after the outbreak of the COVID-19 pandemic using claims data in MarketScan®. We found that the changes and their financial impacts vary across mental health conditions, age groups, and periods of the pandemic. Some changes are unexpected from previously reported prevalence increases among the general population and could underlie unmet treatment needs. Therefore, mental health providers should anticipate the use pattern changes in services with similar COVID-19 pandemic disruptions and payers should anticipate cost increases due, in part, to increased price and/or service use.

Impact of ventilator settings during venovenous extracorporeal membrane oxygenation on clinical outcomes in influenza-associated acute respiratory distress syndrome: a multicenter retrospective cohort study.

Background: Patients with influenza-associated acute respiratory distress syndrome (ARDS) requiring venovenous extracorporeal membrane oxygenation (vv-ECMO) support have a high mortality rate. Ventilator settings have been known to have a substantial impact on outcomes. However, the optimal settings of mechanical ventilation during vv-ECMO are still unknown. Methods: This multicenter retrospective cohort study was conducted in the intensive care units (ICUs) of three tertiary referral hospitals in Taiwan between July 2009 and December 2019. It aims to describe the effect of ventilator settings during vv-ECMO on patient outcomes. Results: A total of 93 patients with influenza receiving ECMO were screened. Patients were excluded if they: were receiving venoarterial ECMO, died within three days of vv-ECMO initiation, or were transferred to the tertiary referral hospital >24 hours after vv-ECMO initiation. A total of 62 patients were included in the study, and 24 (39%) died within six months. During the first three days of ECMO, there were no differences in tidal volume (5.1 vs. 5.2 mL/kg, p = 0.833), dynamic driving pressure (15 vs. 14 cmH2O, p = 0.146), and mechanical power (11.3 vs. 11.8 J/min, p = 0.352) between survivors and non-survivors. However, respiratory rates were significantly higher in non-survivors compared with survivors (15 vs. 12 breaths/min, p = 0.013). After adjustment for important confounders, a higher mean respiratory rate of >12 breaths/min was still associated with higher mortality (adjusted hazard ratio = 3.31, 95% confidence interval = 1.10-9.97, p = 0.034). Conclusions: In patients with influenza-associated ARDS receiving vv-ECMO support, we found that a higher respiratory rate was associated with higher mortality. Respiratory rate might be a modifiable factor to improve outcomes in this patient population.

Real-Time Loosely Coupled 3DMA GNSS/Doppler Measurements Integration Using a Graph Optimization and Its Performance Assessments in Urban Canyons of New York.

Smart health applications have received significant attention in recent years. Novel applications hold significant promise to overcome many of the inconveniences faced by persons with disabilities throughout daily living. For people with blindness and low vision (BLV), environmental perception is compromised, creating myriad difficulties. Precise localization is still a gap in the field and is critical to safe navigation. Conventional GNSS positioning cannot provide satisfactory performance in urban canyons. 3D mapping-aided (3DMA) GNSS may serve as an urban GNSS solution, since the availability of 3D city models has widely increased. As a result, this study developed a real-time 3DMA GNSS-positioning system based on state-of-the-art 3DMA GNSS algorithms. Shadow matching was integrated with likelihood-based ranging 3DMA GNSS, generating positioning hypothesis candidates. To increase robustness, the 3DMA GNSS solution was then optimized with Doppler measurements using factor graph optimization (FGO) in a loosely-coupled fashion. This study also evaluated positioning performance using an advanced wearable system's recorded data in New York City. The real-time forward-processed FGO can provide a root-mean-square error (RMSE) of about 21 m. The RMSE drops to 16 m when the data is post-processed with FGO in a combined direction. Overall results show that the proposed loosely-coupled 3DMA FGO algorithm can provide a better and more robust positioning performance for the multi-sensor integration approach used by this wearable for persons with BLV.

Complete Chloroplast Genome of an Endangered Species Quercus litseoides, and Its Comparative, Evolutionary, and Phylogenetic Study with Other Quercus Section Cyclobalanopsis Species.

Quercus litseoides, an endangered montane cloud forest species, is endemic to southern China. To understand the genomic features, phylogenetic relationships, and molecular evolution of Q. litseoides, the complete chloroplast (cp) genome was analyzed and compared in Quercus section Cyclobalanopsis. The cp genome of Q. litseoides was 160,782 bp in length, with an overall guanine and cytosine (GC) content of 36.9%. It contained 131 genes, including 86 protein-coding genes, eight ribosomal RNA genes, and 37 transfer RNA genes. A total of 165 simple sequence repeats (SSRs) and 48 long sequence repeats with A/T bias were identified in the Q. litseoides cp genome, which were mainly distributed in the large single copy region (LSC) and intergenic spacer regions. The Q. litseoides cp genome was similar in size, gene composition, and linearity of the structural region to those of Quercus species. The non-coding regions were more divergent than the coding regions, and the LSC region and small single copy region (SSC) were more divergent than the inverted repeat regions (IRs). Among the 13 divergent regions, 11 were in the LSC region, and only two were in the SSC region. Moreover, the coding sequence (CDS) of the six protein-coding genes (rps12, matK, atpF, rpoC2, rpoC1, and ndhK) were subjected to positive selection pressure when pairwise comparison of 16 species of Quercus section Cyclobalanopsis. A close relationship between Q. litseoides and Quercus edithiae was found in the phylogenetic analysis of cp genomes. Our study provided highly effective molecular markers for subsequent phylogenetic analysis, species identification, and biogeographic analysis of Quercus.

Effectiveness of Endobronchial Ultrasound-Guided Transbronchial Biopsy Combined With Tissue Culture for the Diagnosis of Sputum Smear-Negative Pulmonary Tuberculosis.

Background: Microorganisms of tuberculosis (TB) are frequently difficult to identify from the airway specimen; therefore, lung biopsy for further histologic and microbiologic study is required. Endobronchial ultrasound-guided transbronchial biopsy (EBUS-TBB) is used for the diagnosis of pulmonary malignancy, but is rarely in the TB population. The purpose of this study was to verify the effectiveness and safety of EBUS-TBB with histologic study and tissue culture in the diagnosis of sputum smear-negative pulmonary TB. Methods: Patients who underwent EBUS-TBB with histologic study and TB tissue culture for clinically suspected, but sputum smear-negative pulmonary TB from January 2016 to December 2018, were included. The accuracy of each diagnostic modality was calculated, respectively. Factors that might influence the positive rate of TB culture (washing fluid and tissue specimen) were also evaluated. Results: One hundred sixty-one patients who underwent EBUS-TBB for clinically suspected, but sputum smear-negative pulmonary TB, were enrolled, and 43 of them were finally diagnosed as having pulmonary TB. The sensitivity of washing fluid (a combination of smear, culture, and polymerase chain reaction for TB) and tissue specimen (a combination of pathology and tissue culture) via EBUS-TBB for TB diagnosis were 48.8 and 55.8%, respectively. The sensitivity for TB diagnosis would be elevated to 67.4% when both washing fluid and tissue specimens are used. The positive TB culture rate would not statistically increase with a combination of tissue specimens and washing fluid. Univariate analysis revealed that TB microorganisms would be more easily cultivated when lesions had an abscess or cavity on the computed tomography (CT) image (presence vs. absence; 62.5 vs. 26.3%, p = 0.022), heterogeneous echogenicity on the EBUS finding (heterogeneous vs. homogeneous; 93.3 vs. 21.4%, p = 0.001), or a necrotic pattern via histologic study (presence vs. absence; 70.6 vs. 30.8%, p = 0.013). Heterogeneous echogenicity in the EBUS finding was the independent predictor according to the results of multivariate analysis. None of our patients encountered major adverse events or received further intensive care after EBUS-TBB. Conclusion: Endobronchial ultrasound-guided transbronchial biopsy is safe and effective for use in diagnosing sputum smear-negative pulmonary TB. EBUS echoic feature is also a predictor of the positive TB culture rate in pulmonary TB. However, tissue culture via EBUS-TBB has little effect in improving the positive TB culture rate.

The Role of High-Density Lipoprotein in Lowering Risk of Dementia in the Elderly: A Review.

Dementia is one of the major causes of disability and hospitalization in the elderly. As far as non-invasive markers of dementia are concerned, we only have age and Apolipoprotein-E (Apo-E) gene, which can be considered as clinically relevant. Modifiable risk factors have been found to be the cause in one-third of the patients who develop dementia. The compatible data supporting the same, in particular for dyslipidemia, is limited, which in turn makes it difficult to devise prevention and interventional methods for both dementia and mild cognitive impairment. Hence, the objective of the review is to summarize the findings on the relation established between the high-density lipoprotein type C( HDL-C) levels and lower the chance of dementia in the elderly, and the possible role of HDL-C as a potential predictive biomarker for cases of dementia in elderly people. Dyslipidemia, a known risk factor for the occurrence of cardiovascular diseases, seems to be linked to Alzheimer's disease. Elevated levels of serum cholesterol in mid-adult life increases the risk of dementia in older age. But elevated high-density lipoprotein (HDL) level and its principal apolipoprotein A-I (ApoA-I ) equates with a low risk of dementia in the elderly population HDL cholesterol has been found to promote endothelial nitric oxide synthase activity which in turn reduces the neural and vascular inflammation and suppresses vascular adhesion thereby exhibiting its vasoprotective function. It has been believed that all these factors have a role to play in the pathogenesis of dementia. The relation between the higher levels of HDL cholesterol or its key protein component ApoA-I and the lower dementia prevalence in the elderly had been documented in numerous observational studies. Some studies have reported conflicting results. Yet, observational studies measuring the baseline HDL level in middle age found a significant association between HDL level and dementia risk in the elderly, whereas those studies measuring HDL cholesterol level only in old age found no association. Likewise, a significant association between HDL cholesterol and dementia risk has been reported with studies that carry through to 10 years or longer. However, the studies with follow-up of fewer than 10 years had failed to document any such association between HDL cholesterol and dementia.  HDL assays may also be used as a predictive biomarker for dementia patients to target the interventions. Although statins do not target HDL directly but can be an area of interest for dementia.

An Instrumental Measure of Hand and Facial Movement Abnormalities in Patients With Schizophrenia.

Introduction: Movement disorders have been suggested to be a cardinal component of schizophrenia. With increased research interests in this area, instrumental measures are needed. This study was to examine if the motion capture system was reliable in measuring hand and facial bradykinesia and dyskinesia and more sensitive to detecting movement differences between schizophrenia patients and healthy people than traditional rating scales. Methods: Sixteen schizophrenia patients and 20 control subjects were recruited. Hand and facial bradykinesia and dyskinesia were measured using the motion capture system and rated using the Extrapyramidal Symptom Rating Scale and the Abnormal Involuntary Movement Scale. Results: The system showed strong test-retest reliability and generated larger effect sizes of group differences than did the rating scales. Conclusions: The results may support researchers and clinical practitioners to apply the system to sensitively measuring the hand and facial movement symptoms in schizophrenia patients, which contributes to gaining a deep understanding of movement issues in schizophrenia.

Outcomes of daytime nurse practitioner-staffed versus resident-staffed nonsurgical intensive care units: A retrospective observational study.

BACKGROUND: Rapid developments in medical care-such as monitoring devices, medications, and working hours restrictions for intensive care personnel-have dramatically increased the demand for intensive care physicians. Therefore, nurse practitioner (NP)-staffed care is becoming increasingly important. This study was aimed to compare the outcomes of daytime NP-staffed and daytime resident-staffed nonsurgical intensive care units (ICU). METHODS: We retrospectively assessed patients admitted to a nonsurgical ICU from March 2017 to December 2017. We collected basic patient data, including age, sex, admission diagnosis, transferring unit, and Acute Physiology and Chronic Health Evaluation II (APACHE II) score. Primary endpoints were ICU mortality, hospital mortality, and 30-day mortality. Secondary endpoints were 48-h readmission, discharge to nonhome locations, and lengths of ICU and hospital stay. RESULTS: A total of 838 subjects were analysed: 334 subjects in the NP-staffed group and 504 in the resident-staffed group. The NP-staffed group was more likely to come from inpatient units (38.3% vs 16.5% for resident-staffed group; p < 0.001) and had lower disease severity (APACHE II score, 13.9 ± 8.4 vs 15.1 ± 8.2 for resident-staffed group; p = 0.047). After adjusting for age, sex, location before ICU admission, APACHE II score, and significantly different basic characteristics, there were no differences in ICU mortality, hospital mortality, or 30-day mortality between the two groups. Secondary analysis showed the NP-staffed group had a lower discharge rate to nonhome locations (2.1% vs 6.3%; p = 0.023) and shorter hospital stay (12.1 ± 14.1 vs 14.2 ± 14.3 days; p = 0.015). CONCLUSIONS: We observed no difference in mortality between daytime NP-staffed and resident-staffed nonsurgical ICUs. Daytime NP-staffed care is an effective, safe, feasible method for staffing nonsurgical ICUs.

Semantic VPS for Smartphone Localization in Challenging Urban Environments.

Accurate smartphone-based outdoor localization systems in deep urban canyons are increasingly needed for various IoT applications. As smart cities have developed, building information modeling (BIM) has become widely available. This article, for the first time, presents a semantic Visual Positioning System (VPS) for accurate and robust position estimation in urban canyons where the global navigation satellite system (GNSS) tends to fail. In the offline stage, a material segmented BIM is used to generate segmented images. In the online stage, an image is taken with a smartphone camera that provides textual information about the surrounding environment. The approach utilizes computer vision algorithms to segment between the different types of material class identified in the smartphone image. A semantic VPS method is then used to match the segmented generated images with the segmented smartphone image. Each generated image contains position information in terms of latitude, longitude, altitude, yaw, pitch, and roll. The candidate with the maximum likelihood is regarded as the precise position of the user. The positioning result achieved an accuracy of 2.0 m among high-rise buildings on a street, 5.5 m in a dense foliage environment, and 15.7 m in an alleyway. This represents an improvement in positioning of 45% compared to the current state-of-the-art method. The estimation of yaw achieved accuracy of 2.3°, an eight-fold improvement compared to the smartphone IMU.

Establishing Aspergillus-Specific IgG Cut-Off Level for Chronic Pulmonary Aspergillosis Diagnosis: Multicenter Prospective Cohort Study.

OBJECTIVES: Aspergillus-specific IgG (Asp-IgG) cut-off level in diagnosing chronic pulmonary aspergillosis (CPA) remains unknown. METHODS: We prospectively recruited participants with clinical suspicion of CPA in three centers in Taiwan during 2019 June to 2020 August. Serum Aspergillus fumigatus-specific IgG (Asp-IgG) (Phadia, Uppsala, UPPS, Sweden) was examined. Optimal cut-off level was determined by Youden's index and validated. RESULTS: A total of 373 participants were recruited. In the derivation cohort (n = 262), Asp-IgG had an area under the receiver-operating-characteristic curve (AUC) of 0.832. The optimal cut-off level was 40.5 mgA/L. While applying this cut-off level to the validation cohort (n = 111), the sensitivity and specificity were 86.7% and 80.2%. Lowering the cut-off level from 40.5 to 27 mgA/L, the sensitivity was steady (30/36, 83.3% to 31/36, 86.1%) while specificity dropped from 81.9% (276/337) to 63.5% (214/337). Restricting CPA diagnosis to only chronic cavitary pulmonary aspergillosis (CCPA) and chronic fibrosing pulmonary aspergillosis (CFPA) yielded a cut-off level of 42.3 mgA/L in the derivation cohort with a sensitivity of 100% and specificity of 84.4% in the validation cohort. CONCLUSIONS: Serum Asp-IgG performs well for CPA diagnosis and provides a low false-positive rate when using a higher cut-off level (preferably around 40 mgA/L).