Selective Oxidation of Vitamin D3 Enhanced by Long-Range Effects of a Substrate Channel Mutation in Cytochrome P450BM3 (CYP102A1).

Vitamin D deficiency affects nearly half the population, with many requiring or opting for supplements with vitamin D3(VD3), the precursor of vitamin D (1α,25-dihydroxyVD3). 25-HydroxyVD3, the circulating form of vitamin D, is a more effective supplement than VD3 but its synthesis is complex. We report here the engineering of cytochrome P450BM3(CYP102A1) for the selective oxidation of VD3 to 25-hydroxyVD3. Long-range effects of the substrate-channel mutation Glu435Ile promoted binding of the VD3 side chain close to the heme, enhancing VD3 oxidation activity that reached 6.62 g of 25-hydroxyVD3 isolated from a 1-litre scale reaction (69.1% yield; space-time-yield 331 mg/L/h).

Development and validation of a model for predicting the early occurrence of RF in ICU-admitted AECOPD patients: a retrospective analysis based on the MIMIC-IV database.

BACKGROUND: This study aims to construct a model predicting the probability of RF in AECOPD patients upon hospital admission. METHODS: This study retrospectively extracted data from MIMIC-IV database, ultimately including 3776 AECOPD patients. The patients were randomly divided into a training set (n = 2643) and a validation set (n = 1133) in a 7:3 ratio. First, LASSO regression analysis was used to optimize variable selection by running a tenfold k-cyclic coordinate descent. Subsequently, a multifactorial Cox regression analysis was employed to establish a predictive model. Thirdly, the model was validated using ROC curves, Harrell's C-index, calibration plots, DCA, and K-M curve. RESULT: Eight predictive indicators were selected, including blood urea nitrogen, prothrombin time, white blood cell count, heart rate, the presence of comorbid interstitial lung disease, heart failure, and the use of antibiotics and bronchodilators. The model constructed with these 8 predictors demonstrated good predictive capabilities, with ROC curve areas under the curve (AUC) of 0.858 (0.836-0.881), 0.773 (0.746-0.799), 0.736 (0.701-0.771) within 3, 7, and 14 days in the training set, respectively and the C-index was 0.743 (0.723-0.763). Additionally, calibration plots indicated strong consistency between predicted and observed values. DCA analysis demonstrated favorable clinical utility. The K-M curve indicated the model's good reliability, revealed a significantly higher RF occurrence probability in the high-risk group than that in the low-risk group (P < 0.0001). CONCLUSION: The nomogram can provide valuable guidance for clinical practitioners to early predict the probability of RF occurrence in AECOPD patients, take relevant measures, prevent RF, and improve patient outcomes.

Elastic-Plastic Fully π-Conjugated Polymer with Excellent Energy Dissipation Capacity for Ultra-Deep-Blue Flexible Polymer Light-Emitting Diodes with CIEy = 0.04.

Emerging intrinsically flexible fully π-conjugated polymers (FπCPs) are a promising functional material for flexible optoelectronics, attributed to their potential interchain interpenetration and entanglement. However, the challenge remains in obtaining elastic-plastic FπCPs with intrinsic robust optoelectronic property and excellent long-term and cycling deformation stability simultaneously for applications in deep-blue flexible polymer light-emitting diodes (PLEDs). This study, demonstrates a series of elastic-plastic FπCPs (P1-P4) with an excellent energy dissipation capacity via side-chain internal plasticization for the ultra-deep-blue flexible PLEDs. First, the freestanding P1 film exhibited a maximum fracture strain of 34.6%. More interestingly, the elastic behavior is observed with a low strain (≤10%), and the stretched film with a high deformation (>10%) attributed to plastic processing revealed the robust capacity to realize energy absorption and release. The elastic-plastic P1 film exhibits outstanding ultra-deep-blue emission, with an efficiency of 56.38%. Subsequently, efficient PLEDs are fabricated with an ultra-deep-blue emission of CIE (0.16, 0.04) and a maximum external quantum efficiency of 1.73%. Finally, stable and efficient ultra-deep-blue electroluminescence are obtained from PLEDs based on stretchable films with different strains and cycling deformations, suggesting excellent elastic-plastic behavior and deformation stability for flexible electronics.

Inflammation-Responsive Mesoporous Silica Nanoparticles with Synergistic Anti-inflammatory and Joint Protection Effects for Rheumatoid Arthritis Treatment.

PURPOSE: Joint destruction is a major burden and an unsolved problem in rheumatoid arthritis (RA) patients. We designed an intra-articular mesoporous silica nanosystem (MSN-TP@PDA-GlcN) with anti-inflammatory and joint protection effects. The nanosystem was synthesized by encapsulating triptolide (TP) in mesoporous silica nanoparticles and coating it with pH-sensitive polydopamine (PDA) and glucosamine (GlcN) grafting on the PDA. The nano-drug delivery system with anti-inflammatory and joint protection effects should have good potency against RA. METHODS: A template method was used to synthesize mesoporous silica (MSN). MSN-TP@PDA-GlcN was synthesized via MSN loading with TP, coating with PDA and grafting of GlcN on PDA. The drug release behavior was tested. A cellular inflammatory model and a rat RA model were used to evaluate the effects on RA. In vivo imaging and microdialysis (MD) system were used to analyze the sustained release and pharmacokinetics in RA rats. RESULTS: TMSN-TP@PDA-GlcN was stable, had good biocompatibility, and exhibited sustained release of drugs in acidic environments. It had excellent anti-inflammatory effects in vitro and in vivo. It also effectively repaired joint destruction in vivo without causing any tissue toxicity. In vivo imaging and pharmacokinetics experiments showed that the nanosystem prolonged the residence time, lowered the Cmax value and enhanced the relative bioavailability of TP. CONCLUSIONS: These results demonstrated that MSN-TP@PDA-GlcN sustained the release of drugs in inflammatory joints and produced effective anti-inflammatory and joint protection effects on RA. This study provides a new strategy for the treatment of RA.

Commonly used software tools produce conflicting and overly-optimistic AUPRC values.

The precision-recall curve (PRC) and the area under the precision-recall curve (AUPRC) are useful for quantifying classification performance. They are commonly used in situations with imbalanced classes, such as cancer diagnosis and cell type annotation. We evaluate 10 popular tools for plotting PRC and computing AUPRC, which were collectively used in more than 3000 published studies. We find the AUPRC values computed by the tools rank classifiers differently and some tools produce overly-optimistic results.

A target-triggered strand displacement-assisted target recycling based on carbon dots-based fluorescent probe and MSNs@PDA nanoparticles for miRNA amplified detection and fluorescence imaging.

A target-triggered strand displacement-assisted target recycling based on carbon dots-based fluorescent probe and mesoporous silica nanoparticles@polydopamine (MSNs@PDA) was established to detect miRNA. The surface of MSNs rich in mesopores was coated with a layer of PDA, which can adsorb and quench the fluorescence of single-stranded Fuel DNA with fluorescent carbon dots (CDs) modified at the end through fluorescence resonance energy transfer (FRET). After adding double-stranded DNA-gold nanoparticles (dsDNA-AuNPs) and target let-7a, it will trigger two toehold-mediated strand displacement reactions (TSDR), leading to the recovery of fluorescence and the recycling of target let-7a (excitation wavelength: 380 nm; emission wavelength: 458 nm). The recovery value of fluorescence is proportional to the logarithm of the target microRNA let-7a concentration, thus realizing the sensitivity amplification detection of disease markers. The MSNs@PDA@Fuel DNA-CDs/dsDNA-AuNPs nanoplatform based on the strategy of "on-off-on" and TSDR cyclic amplification may hold great potential as an effective and safe nanoprobe for accurate fluorescence imaging of diseases related to miRNA with low abundances.

N-ethyl-N-nitrosourea (ENU)-induced C-terminal truncation of Runx3 results in autoimmune colitis associated with Th17/Treg imbalance.

Inflammatory bowel disease (IBD) is a chronic and progressive inflammatory intestinal disease that affects people around the world. The primary cause of IBD is an imbalance in the host immune response to intestinal flora. Several human genes, including IL10, STAT3, IRGM, ATG16L1, NOD2 and RUNX3, are associated with inappropriate immune responses in IBD. It has been reported that homozygous Runx3-knockout (ko) mice spontaneously develop colitis. However, the high mortality rate in these mice within the first two weeks makes it challenging to study the role of Runx3 in colitis. To address this issue, a spontaneous colitis (SC) mouse model carrying a C-terminal truncated form of Runx3 with Tyr319stop point mutation has been generated. After weaning, SC mice developed spontaneous diarrhea and exhibited prominent enlargement of the colon, accompanied by severe inflammatory cell infiltration. Results of immunofluorescence staining showed massive CD4+ T cell infiltration in the inflammatory colon of SC mice. Colonic IL-17A mRNA expression and serum IL-17A level were increased in SC mice. CD4+ T cells from SC mice produced stronger IL-17A than those from wildtype mice in Th17-skewing conditions in vitro. In addition, the percentages of Foxp3+ Treg cells as well as the RORγt+Foxp3+ Treg subset, known for its role in suppressing Th17 response in the gut, were notably lower in colon lamina propria of SC mice than those in WT mice. Furthermore, transfer of total CD4+ T cells from SC mice, but not from wildtype mice, into Rag1-ko host mice resulted in severe autoimmune colitis. In conclusion, the C-terminal truncated Runx3 caused autoimmune colitis associated with Th17/Treg imbalance. The SC mouse model is a feasible approach to investigate the effect of immune response on spontaneous colitis.

A nomogram to predict cryptococcal meningitis in patients with pulmonary cryptococcosis.

Background: The most serious manifestation of pulmonary cryptococcosis is complicated with cryptococcal meningitis, while its clinical manifestations lack specificity with delayed diagnosis and high mortality. The early prediction of this complication can assist doctors to carry out clinical interventions in time, thus improving the cure rate. This study aimed to construct a nomogram to predict the risk of cryptococcal meningitis in patients with pulmonary cryptococcosis through a scoring system. Methods: The clinical data of 525 patients with pulmonary cryptococcosis were retrospectively analyzed, including 317 cases (60.38 %) with cryptococcal meningitis and 208 cases (39.62 %) without cryptococcal meningitis. The risk factors of cryptococcal meningitis were screened by univariate analysis, LASSO regression analysis and multivariate logistic regression analysis. Then the risk factors were incorporated into the nomogram scoring system to establish a prediction model. The model was validated by receiver operating characteristic (ROC) curve, decision curve analysis (DCA) and clinical impact curve. Results: Fourteen risk factors for cryptococcal meningitis in patients with pulmonary cryptococcosis were screened out by statistical method, including 6 clinical manifestations (fever, headache, nausea, psychiatric symptoms, tuberculosis, hematologic malignancy) and 8 clinical indicators (neutrophils, lymphocytes, glutamic oxaloacetic transaminase, T cells, helper T cells, killer T cells, NK cells and B cells). The AUC value was 0.978 (CI 96.2 %∼98.9 %), indicating the nomogram was well verified. Conclusion: The nomogram scoring system constructed in this study can accurately predict the risk of cryptococcal meningitis in patients with pulmonary cryptococcosis, which may provide a reference for clinical diagnosis and treatment of patients with cryptococcal meningitis.

The association between ultra-processed food intake and age-related hearing loss: a cross-sectional study.

OBJECTIVES: This study aimed to explore the association between ultra-processed foods and age-related hearing loss. METHODS: Cross-sectional analyses based on data from a nationally representative sample of 1075 adults aged over 50 in the US was performed. The odds ratios (ORs) and 95% confidence intervals (CIs) for hearing loss according to ultra-processed foods intake quartiles were calculated using a multiple adjusted logistic regression model. Restricted cubic spline model was used to flexibly model potential nonlinear relations between ultra-processed foods intake and possibility of hearing loss. We also explored statistical interactions and conducted subgroup analyses where they were found to be significant. RESULTS: Ultra-processed foods intake was significantly correlated with high-frequency hearing loss. After controlling for all covariables, individuals in the fourth quartile of Ultra-processed foods consumption had a 2.8 times higher chance of developing high-frequency hearing loss than individuals in the first quartile of Ultra-processed foods consumption. We also found that the association was more significant in non-Hispanic whites. CONCLUSIONS: This study discovered an association between Ultra-processed foods intake and the incidence of high-frequency hearing loss, which was more significant in non-Hispanic whites.

Construction and validation of a nomogram model to predict the poor prognosis in patients with pulmonary cryptococcosis.

Background: Patients with poor prognosis of pulmonary cryptococcosis (PC) are prone to other complications such as meningeal infection, recurrence or even death. Therefore, this study aims to analyze the influencing factors in the poor prognosis of patients with PC, so as to build a predictive nomograph model of poor prognosis of PC, and verify the predictive performance of the model. Methods: This retrospective study included 410 patients (78.1%) with improved prognosis of PC and 115 patients (21.9%) with poor prognosis of PC. The 525 patients with PC were randomly divided into the training set and validation set according to the ratio of 7:3. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm was used to screen the demographic information, including clinical characteristics, laboratory test indicators, comorbidity and treatment methods of patients, and other independent factors that affect the prognosis of PC. These factors were included in the multivariable logistic regression model to build a predictive nomograph. The receiver operating characteristic curve (ROC), calibration curve and decision curve analysis (DCA) were used to verify the accuracy and application value of the model. Results: It was finally confirmed that psychological symptoms, cytotoxic drugs, white blood cell count, hematocrit, platelet count, CRP, PCT, albumin, and CD4/CD8 were independent predictors of poor prognosis of PC patients. The area under the curve (AUC) of the predictive model for poor prognosis in the training set and validation set were 0.851 (95% CI: 0.818-0.881) and 0.949, respectively. At the same time, calibration curve and DCA results confirmed the excellent performance of the nomogram in predicting poor prognosis of PC. Conclusion: The nomograph model for predicting the poor prognosis of PC constructed in this study has good prediction ability, which is helpful for improving the prognosis of PC and further optimizing the clinical management strategy.

The Effect of Colloidal Nanoparticles on Phase Separation of Block and Heteroarm Star Copolymers Confined between Polymer Brushes.

The effect of colloidal nanoparticles on the phase changes of the amphiphilic AB linear diblock, A1A2B, and A2B heteroarm star copolymers confined between two polymer brush substrates was investigated by using a real-space self-consistent field theory. By changing the concentrations of nanoparticles and polymer brushes, the phase structure of the amphiphilic AB copolymer transforms from lamellar to core-shell hexagonal phase to cylinder phase. The pattern of A2B heteroarm star copolymer changes from core-shell hexagonal phases to lamellar phases and the layer decreases when increasing the density of the polymer brushes. The results showed that the phase behavior of the system is strongly influenced by the polymer brush architecture and the colloidal nanoparticle numbers. The colloidal nanoparticles and the soft confined surface of polymer brushes make amphiphilic AB copolymers easier to form ordered structures. The dispersion of the nanoparticles was also investigated in detail. The soft surfaces of polymer brushes and the conformation of the block copolymers work together to force the nanoparticles to disperse evenly. It will give helpful guidance for making some new functional materials by nano etching technology, nano photoresist, and nanoprinting.

Relationship Between Systemic Immune-Inflammation Index and Risk of Respiratory Failure and Death in COPD: A Retrospective Cohort Study Based on the MIMIC-IV Database.

Purpose: Chronic obstructive pulmonary disease (COPD) concurrent with respiratory failure (RF) is devastating, and may result in death and disability. Systemic immune-inflammation index (SII) is a new prognostic biomarker linked to unfavorable outcomes of acute coronary syndrome, ischemic stroke, and heart failure. Nonetheless, its role in COPD is rarely investigated. Consequently, this study intends to assess the accuracy of SII in predicting the prognosis of COPD. Patients and Methods: The clinical information was retrospectively acquired from the Medical Information Mart for Intensive Care-IV database. The outcomes encompassed the incidence of RF and mortality. The relationship between different SII and outcomes was examined utilizing the Cox proportional-hazards model and restricted cubic splines. Kaplan-Meier analysis was employed for all-cause mortality. Results: The present study incorporated 1653 patients. During hospitalization, 697 patients (42.2%) developed RF, and 169 patients (10.2%) died. And 637 patients (38.5%) died during long-term follow-up. Higher SII increased the risk of RF (RF: HR: 1.19, 95% CI 1.12-1.28, P<0.001), in-hospital mortality (HR: 1.22, 95% CI 1.07-1.39, P=0.003), and long-term follow-up mortality (HR: 1.12, 95% CI 1.05-1.19, P<0.001). Kaplan-Meier analysis suggested a significantly elevated risk of all-cause death (log-rank P<0.001) in patients with higher SII, especially during the short-term follow-up period of 21 days. Conclusion: SII is closely linked to an elevated risk of RF and death in COPD patients. It appears to be a potential predictor of the prognosis of COPD patients, which is helpful for the risk stratification of this population. However, more prospective studies are warranted to consolidate our conclusion.

Commonly used software tools produce conflicting and overly-optimistic AUPRC values.

The precision-recall curve (PRC) and the area under it (AUPRC) are useful for quantifying classification performance. They are commonly used in situations with imbalanced classes, such as cancer diagnosis and cell type annotation. We evaluated 10 popular tools for plotting PRC and computing AUPRC, which were collectively used in >3,000 published studies. We found the AUPRC values computed by the tools rank classifiers differently and some tools produce overly-optimistic results.

Triphenylamine Spirofunctionalized Light-Emitting Conjugated Polymer with an Ultradeep-Blue Narrowband Emission for Large-Area Printed Display.

Emerging printed large-area polymer light-emitting diodes (PLEDs) are essential for manufacturing flat-panel displays and solid lighting devices. However, it is challenging to obtain large-area and stable ultradeep-blue PLEDs because of the lack of light-emitting conjugated polymers (LCPs) with robust deep-blue emissions, excellent morphological stabilities, and high charging abilities. Here, a novel unsymmetrically substituted polydiarylfluorene (POPSAF) is obtained with stable narrowband emission for large-area printed displays via triphenylamine (TPA) spirofunctionalization of LCPs. POPSAF films show narrowband and stable ultradeep-blue emission with a full width at half maximum (FWHM) of 36 nm, associated with their intrachain excitonic behavior without obvious polaron formation. Compared to controlled poly[4-(octyloxy)-9,9-diphenylfluoren-2,7-diyl]-co-[5-(octyloxy)-9,9-diphenylfluoren-2,7-diyl] (PODPF), excellent charge transport is observed in the POPSAF films because of the intrinsic hole transport ability of the TPA units. Large-area PLEDs are fabricated via blade-coating with an emission area of 9 cm2, which exhibit uniform ultradeep-blue emission with an FWHM of 36 nm and corresponding Commission internationale de l'éclairage (CIE) coordinates of (0.155, 0.072). These findings are attributed to the synergistic effects of robust emission, stable morphology, and printing capacity. Finally, preliminary printed passive matrix (PM) PLED displays with 20 × 20 pixels monochromes are fabricated, confirmed the effectiveness of spirofunctionalization in optoelectronics.

Hypoxia and Singlet Oxygen Dual-Responsive Micelles for Photodynamic and Chemotherapy Therapy Featured with Enhanced Cellular Uptake and Triggered Cargo Delivery.

Introduction: Combination therapy provides better outcomes than a single therapy and becomes an efficient strategy for cancer treatment. In this study, we designed a hypoxia- and singlet oxygen-responsive polymeric micelles which contain azo and nitroimidazole groups for enhanced cellular uptake, repaid cargo release, and codelivery of photosensitizer Ce6 and hypoxia-activated prodrug tirapazamine TPZ (DHM-Ce6@TPZ), which could be used for combining Ce6-mediated photodynamic therapy (PDT) and PDT-activated chemotherapy to enhance the therapy effect of cancer. Methods: The hypoxia- and singlet oxygen-responsive polymeric micelles DHM-Ce6@TPZ were prepared by film hydration method. The morphology, physicochemical properties, stimuli responsiveness, in vitro singlet oxygen production, cellular uptake, and cell viability were evaluated. In addition, the in vivo therapeutic effects of the micelles were verified using a tumor xenograft mice model. Results: The resulting dual-responsive micelles not only increased the concentration of intracellular photosensitizer and TPZ, but also facilitated photosensitizer and TPZ release for enhanced integration of photodynamic and chemotherapy therapy. As a photosensitizer, Ce6 induced PDT by generating toxic singlet reactive oxygen species (ROS), resulting in a hypoxic tumor environment to activate the prodrug TPZ to achieve efficient chemotherapy, thereby evoking a synergistic photodynamic and chemotherapy therapeutic effect. The cascade synergistic therapeutic effect of DHM-Ce6@TPZ was effectively evaluated both in vitro and in vivo to inhibit tumor growth in a breast cancer mice model. Conclusion: The designed multifunctional micellar nano platform could be a convenient and powerful vehicle for the efficient co-delivery of photosensitizers and chemical drugs for enhanced synergistic photodynamic and chemotherapy therapeutic effect of cancer.

Investigating alcohol consumption in China via wastewater-based epidemiology.

Alcohol abuse and addiction is a public health issue of global concern. Wastewater-based epidemiology (WBE) is a forceful and effective complementary tool for investigating chemical consumption. This study examined alcohol consumption in major cities of China via WBE and compared WBE estimates with other data sources. A simple and valid ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed for the determination of two alcohol metabolites, ethyl glucuronide (EtG) and ethyl sulfate (EtS) in wastewater. The optimized method was applied to 62 sewage samples collected from wastewater treatment plants (WWTPs) in 31 provincial capital cities across China in the fourth quarter of 2020. The methodology established in this study was validated with the lower limit of quantification (LLOQ) up to 0.1 µg/L, good linearity in the range of 0.1-50 µg/L, intra-day and inter-day precision less than 5.58% and 5.55%, respectively, and the recoveries of the extracts were higher than 97.14%. The consumption range of alcohol estimated via WBE was 6.09 ± 4.56 ethanol/person/day (EPD) in the capital cities of China. Alcohol consumption varies significantly between cities in China, with WBE estimating lower alcohol consumption than WHO and lower than foreign countries. Investing in alcohol consumption based on WBE has great potential to accurately and efficiently estimate alcohol consumption.

LncRNA HCG11 enhances the chemosensitivity of non-small cell lung cancer cells to Gemcitabine via miR-17-5p/p21 axis.

BACKGROUND: This study investigated the inhibitory effects of lncRNA HLA Complex Group 11 (HCG11) on non-small cell lung cancer (NSCLC) and the molecular mechanisms. RESEARCH DESIGN AND METHODS: Bioinformatics analysis was conducted to determine the downstream targeted gene miR-17-5p/p21 and predict their binding sites. qRT-PCR and Western blot were used to detect expression levels, and dual luciferase and RIP assays were adopted to verify binding relationship. RESULTS: The lncRNA HCG11/miR-17-5p/p21 axis was found to regulate drug resistance, proliferation, apoptosis, and cell cycle of A549 and A549-Gemcitabine (GEM) cells. HCG11 acted as a ceRNA binding to miR-17-5p, which repressed p21 expression in turn. In vivo experiments demonstrated that HCG11 hindered tumor growth. Therefore, lncRNA HCG11, by targeting the miR-17-5p/p21 axis, suppressed GEM resistance and malignant progression of NSCLC cells. CONCLUSIONS: This study provides a reference for investigating the potential value of lncRNA HCG11 in the diagnosis of NSCLC and finding potential targets against clinical chemotherapeutic resistance in NSCLC.

The application of nanopore targeted sequencing for pathogen diagnosis in bronchoalveolar lavage fluid of patients with pneumonia: a prospective multicenter study.

OBJECTIVE: To evaluate the value of nanopore targeted sequencing in diagnosing pneumonia pathogens. METHODS: This large-scale multicentre prospective study performed in 8 hospitals across China from April to October 2022. Hospitalised patients with a diagnosis of pneumonia at admission were included. Complete clinical data were collected, and bronchoalveolar lavage fluid were obtained from each patient. These samples underwent simultaneous testing using conventional microbial testing, metagenomic next-generation sequencing, and nanopore targeted sequencing. RESULTS: A total of 218 patients were included. Among the 168 cases of pulmonary infection, 246 strains of pathogens were confirmed. Nanopore targeted sequencing outperformed conventional microbial testing, identifying more pathogens with a sensitivity increase of 47.9% (77.2% vs. 29.3%). Metagenomic next-generation sequencing had a sensitivity of 82.9%. Total of 70.1% patients had consistent results in both metagenomic next-generation sequencing and nanopore targeted sequencing. Nanopore targeted sequencing exhibited significantly higher sensitivity in detecting Pneumocystis jiroveci, cytomegalovirus, Mycobacterium tuberculosis, Nontuberculous mycobacteria, Streptococcus pneumoniae, and Mycoplasma pneumoniae compared to conventional microbial testing. However, metagenomic next-generation sequencing demonstrated higher sensitivity than nanopore targeted sequencing for Aspergillus (88.5% vs. 53.8%). Regarding the detection of co-infections, nanopore targeted sequencing displayed significantly higher sensitivity than conventional microbial testing (76.7% vs. 28.7%) and was on par with metagenomic next-generation sequencing (76.7% vs. 82.9%). CONCLUSION: Nanopore targeted sequencing performs equally well as metagenomic next-generation sequencing in bronchoalveolar lavage fluid for pathogen diagnosis in pneumonia, both methods showing higher sensitivity than conventional microbial testing. Nanopore targeted sequencing can be considered a reliable method for diagnosing pathogens in pneumonia.

Multi-feature concatenation and multi-classifier stacking: An interpretable and generalizable machine learning method for MDD discrimination with rsfMRI.

Major depressive disorder (MDD) is a serious and heterogeneous psychiatric disorder that needs accurate diagnosis. Resting-state functional MRI (rsfMRI), which captures multiple perspectives on brain structure, function, and connectivity, is increasingly applied in the diagnosis and pathological research of MDD. Different machine learning algorithms are then developed to exploit the rich information in rsfMRI and discriminate MDD patients from normal controls. Despite recent advances reported, the MDD discrimination accuracy has room for further improvement. The generalizability and interpretability of the discrimination method are not sufficiently addressed either. Here, we propose a machine learning method (MFMC) for MDD discrimination by concatenating multiple features and stacking multiple classifiers. MFMC is tested on the REST-meta-MDD data set that contains 2428 subjects collected from 25 different sites. MFMC yields 96.9% MDD discrimination accuracy, demonstrating a significant improvement over existing methods. In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites. The use of XGBoost as the meta classifier allows us to probe the decision process of MFMC. We identify 13 feature values related to 9 brain regions including the posterior cingulate gyrus, superior frontal gyrus orbital part, and angular gyrus, which contribute most to the classification and also demonstrate significant differences at the group level. The use of these 13 feature values alone can reach 87% of MFMC's full performance when taking all feature values. These features may serve as clinically useful diagnostic and prognostic biomarkers for MDD in the future.

Large-scale group-hierarchical DEMATEL method for complex systems.

Existing Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods are mostly suitable for simple systems with fewer factors, and lack effective integration of expert knowledge and experience from large-scale group populations, resulting in a potential compromise of the quality of the initial direct relation (IDR) matrix. To make DEMATEL better suited for the identification of critical factors in complex systems, this paper proposes a hierarchical DEMATEL method for large-scale group decision-making. Considering the limitations of expert knowledge and experience, a method based on expert consistency network for constructing the expert weight matrix is designed. The expert consistency network is constructed for different elements, and the weights of experts in different elements are determined using the clustering coefficient. Following the principles of the classic DEMATEL method, the steps for identifying key elements in complex systems using the large-scale group-hierarchical DEMATEL method are summarized. To objectively test the effectiveness and superiority of the decision algorithm, the robustness of the algorithm is analyzed in an interference environment. Finally, the superiority of the proposed method and algorithm is verified through a case study, which demonstrating that the proposed decision-making method is suitable for group decision-making in complex systems, with high algorithm stability and low algorithm deviation.