Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma.

PURPOSE: To develop a non-invasive auxiliary assessment method based on CT-derived extracellular volume (ECV) to predict the pathological grading (PG) of hepatocellular carcinoma (HCC). METHODS: The study retrospectively analyzed 238 patients who underwent HCC resection surgery between January 2013 and April 2023. Six machine learning algorithms were employed to construct predictive models for HCC PG: logistic regression, extreme gradient boosting, Light Gradient Boosting Machine (LightGBM), random forest, adaptive boosting, and Gaussian naive Bayes. Model performance was evaluated using receiver operating characteristic curve analysis, including area under the curve (AUC), sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and F1 score. Calibration plots were used for visual evaluation of model calibration. Clinical decision curve analysis was performed to assess potential clinical utility by calculating net benefit. RESULTS: 166 patients from Hospital A were allocated to the training set, while 72 patients from Hospital B (constituting 30.25% of the total sample) were assigned to the test set. The model achieved an AUC of 1.000 (95%CI: 1.000-1.000) in the training set and 0.927 (95%CI: 0.837-0.999) in the validation set, respectively. Ultimately, the model achieved an AUC of 0.909 (95%CI: 0.837-0.980) in the test set, with an accuracy of 0.778, sensitivity of 0.906, specificity of 0.789, negative predictive value of 0.556, and F1 score of 0.908. CONCLUSION: This study successfully developed and validated a non-invasive auxiliary assessment method based on CT-derived ECV to predict the HCC PG, providing important supplementary information for clinical decision-making.

Mechanism of Astragalus mongholicus Bunge ameliorating cerebral ischemia-reperfusion injury: Based on network pharmacology analysis and experimental verification.

ETHNOPHARMACOLOGICAL RELEVANCE: Astragalus mongholicus Bunge (AMB) is a herb with wide application in traditional Chinese medicine, exerting a wealth of pharmacological effects. AMB has been proven to have an evident therapeutic effect on ischemic cerebrovascular diseases, including cerebral ischemia-reperfusion injury (CIRI). However, the specific mechanism underlying AMB in CIRI remains unclear. AIM OF THE STUDY: This study aimed to investigate the potential role of AMB in CIRI through a comprehensive approach of network pharmacology and in vivo experimental research. METHODS: The intersection genes of drugs and diseases were obtained through analysis of the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and Gene Expression Omnibus (GEO) database. The protein-protein interaction (PPI) network was created through the string website. Meanwhile, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was carried out using R studio, and thereafter the key genes were screened. Then, the molecular docking prediction was made between the main active ingredients and target genes, and hub genes with high binding energy were obtained. In addition, molecular dynamic (MD) simulation was used to validate the result of molecular docking. Based on the results of network pharmacology, we used animal experiments to verify the predicted hub genes. First, the rat middle cerebral artery occlusion and reperfusion (MACO/R) model was established and the effective dose of AMB in CIRI was determined by behavioral detection and 2,3,5-Triphenyltetrazolium chloride (TTC) staining. Then the target proteins corresponding to the hub genes were measured by Western blot. Moreover, the level of neuronal death was measured using hematoxylin and eosin (HE) and Nissl staining. RESULTS: Based on the analysis of the TCMSP database and GEO database, a total of 62 intersection target genes of diseases and drugs were obtained. The KEGG enrichment analysis showed that the therapeutic effect of AMB on CIRI might be realized through the advanced glycation endproduct-the receptor of advanced glycation endproduct (AGE-RAGE) signaling pathway in diabetic complications, nuclear factor kappa-B (NF-κB) signaling pathway and other pathways. Molecular docking results showed that the active ingredients of AMB had good binding potential with hub genes that included Prkcb, Ikbkb, Gsk3b, Fos and Rela. Animal experiments showed that AWE (60 g/kg) could alleviate CIRI by regulating the phosphorylation of PKCß, IKKß, GSK3ß, c-Fos and NF-κB p65 proteins. CONCLUSION: AMB exerts multi-target and multi-pathway effects against CIRI, and the underlying mechanism may be related to anti-apoptosis, anti-inflammation, anti-oxidative stress and inhibiting calcium overload.

Vaccine-elicited IL-1R signaling results in Th17 TRM-mediated immunity.

Lung tissue resident memory (TRM) cells are thought to play crucial roles in lung host defense. We have recently shown that immunization with the adjuvant LTA1 (derived from the A1 domain of E. coli heat labile toxin) admixed with OmpX from K. pneumoniae can elicit antigen specific lung Th17 TRM cells that provide serotype independent immunity to members of the Enterobacteriaceae family. However, the upstream requirements to generate these cells are unclear. Single-cell RNA-seq showed that vaccine-elicited Th17 TRM cells expressed high levels of IL-1R1, suggesting that IL-1 family members may be critical to generate these cells. Using a combination of genetic and antibody neutralization approaches, we show that Th17 TRM cells can be generated independent of caspase-1 but are compromised when IL-1α is neutralized. Moreover IL-1α could serve as a molecular adjuvant to generate lung Th17 TRM cells independent of LTA1. Taken together, these data suggest that IL-1α plays a major role in vaccine-mediated lung Th17 TRM generation.

Construction of a diagnostic model based on random forest and artificial neural network for peri-implantitis.

OBJECTIVES: This study aimed to reveal critical genes regulating peri-implantitis during its development and construct a diagnostic model by using random forest (RF) and artificial neural network (ANN). METHODS: GSE-33774, GSE106090, and GSE57631 datasets were obtained from the GEO database. The GSE33774 and GSE106090 datasets were analyzed for differential expression and functional enrichment. The protein-protein interaction networks (PPI) and RF screened vital genes. A diagnostic model for peri-implantitis was established using ANN and validated on the GSE33774 and GSE57631 datasets. A transcription factor-gene interaction network and a transcription factor-micro-RNA (miRNA) regulatory network were also established. RESULTS: A total of 124 differentially expressed genes (DEGs) involved in the regulation of peri-implantitis were screened. Enrichment analysis showed that DEGs were mainly associated with immune receptor activity and cytokine receptor activity and were mainly involved in processes such as leukocyte and neutrophil migration. The PPI and RF screened six essential genes, namely, CD38, CYBB, FCGR2A, SELL, TLR4, and CXCL8. The receiver operating characteristic curve (ROC) indicated that the ANN model had an excellent diagnostic performance. FOXC1, GATA2, and NF-κB1 may be essential transcription factors in peri-implantitis, and hsa-miR-204 may be a key miRNA. CONCLUSIONS: The diagnostic model of peri-implantitis constructed by RF and ANN has high confidence, and CD38, CYBB, FCGR2A, SELL, TLR4, and CXCL8 are potential diagnostic markers. FOXC1, GATA2, and NF-κB1 may be essential transcription factors in peri-implantitis, and hsa-miR-204 plays a vital role as a critical miRNA.

Development and validation of HPV-associated and HPV-independent penile squamous cell carcinoma prognostic nomogram.

OBJECTIVE: The aim of this study was to introduce HPV-associated and HPV-independent histologic classifications to analyze prognostic factors and develop a prognostic nomogram for patients with penile squamous cell carcinoma (PSCC). METHODS: Data of 1502 PSCC patients between 2010 and 2020 were accessed from the SEER database, and the patients were randomly divided into a training set and a validation set. Independent risk factors for PSCC patients prognosis were analyzed by using univariate and multivariate COX proportional hazards regression, and was used for the construction of the nomogram, and the predictive performance of the model was evaluated by C-index, calibration curve and ROC curve. Kaplan-Meier analysis was applied to explore the impact of HPV-related factors on patient survival, while propensity score matching (PSM) and inverse probability treatment weighting (IPTW) techniques were used to balance other confounding factors like individual clinical and pathological factors, and to evaluate the differences in overall survival (OS) and cause-specific survival (CSS) between subgroups. RESULT: The results indicated that histologic type, Grade classification, T/M stage, surgical methods and chemotherapy were independent risk factors affecting OS and CSS in PSCC patients. In addition, age and marital status were significantly associated with OS, while lymph node metastasis was an independent prognostic factor for CSS, the validation results of the model showed that the nomogram had a superior predictive performance compared with the American Joint Committee on Cancer staging system. In addition, subgroup analyses prior to and after IPTW and PSM adjustments showed that HPV-associated group had better OS and CSS than HPV-independent group. CONCLUSION: Our study developed and validated a nomogram using a novel histologic classification and achieved satisfactory results, which can better help clinicians to predict the prognosis of penile squamous cell carcinoma patients.

Natural Killer Cells Do Not Attenuate a Mouse-Adapted SARS-CoV-2-Induced Disease in Rag2-/- Mice.

This study investigates the roles of T, B, and Natural Killer (NK) cells in the pathogenesis of severe COVID-19, utilizing mouse-adapted SARS-CoV-2-MA30 (MA30). To evaluate this MA30 mouse model, we characterized MA30-infected C57BL/6 mice (B6) and compared them with SARS-CoV-2-WA1 (an original SARS-CoV-2 strain) infected K18-human ACE2 (K18-hACE2) mice. We found that the infected B6 mice developed severe peribronchial inflammation and rapid severe pulmonary edema, but less lung interstitial inflammation than the infected K18-hACE2 mice. These pathological findings recapitulate some pathological changes seen in severe COVID-19 patients. Using this MA30-infected mouse model, we further demonstrate that T and/or B cells are essential in mounting an effective immune response against SARS-CoV-2. This was evident as Rag2-/- showed heightened vulnerability to infection and inhibited viral clearance. Conversely, the depletion of NK cells did not significantly alter the disease course in Rag2-/- mice, underscoring the minimal role of NK cells in the acute phase of MA30-induced disease. Together, our results indicate that T and/or B cells, but not NK cells, mitigate MA30-induced disease in mice and the infected mouse model can be used for dissecting the pathogenesis and immunology of severe COVID-19.

Embigin Is Highly Expressed on CD4+ and CD8+ T Cells but Is Dispensable for Several T Cell Effector Responses.

T cell immunity, including CD4+ and CD8+ T cell immunity, is critical to host immune responses to infection. Transcriptomic analyses of both CD4+ and CD8+ T cells of C57BL/6 mice show high expression the gene encoding embigin, Emb, which encodes a transmembrane glycoprotein. Moreover, we found that lung CD4+ Th17 tissue-resident memory T cells of C57BL/6 mice also express high levels of Emb. However, deletion of Emb in αß T cells of C57BL/6 mice revealed that Emb is dispensable for thymic T cell development, generation of lung Th17 tissue-resident memory T cells, tissue-resident memory T cell homing to the lung, experimental autoimmune encephalitis, as well as clearance of pulmonary viral or fungal infection. Thus, based on this study, embigin appears to play a minor role if any in αß T cell development or αß T cell effector functions in C57BL/6 mice.

Exploring the potential link between MitoEVs and the immune microenvironment of periodontitis based on machine learning and bioinformatics methods.

BACKGROUND: Periodontitis is a chronic inflammatory condition triggered by immune system malfunction. Mitochondrial extracellular vesicles (MitoEVs) are a group of highly heterogeneous extracellular vesicles (EVs) enriched in mitochondrial fractions. The objective of this research was to examine the correlation between MitoEVs and the immune microenvironment of periodontitis. METHODS: Data from MitoCarta 3.0, GeneCards, and GEO databases were utilized to identify differentially expressed MitoEV-related genes (MERGs) and conduct functional enrichment and pathway analyses. The random forest and LASSO algorithms were employed to identify hub MERGs. Infiltration levels of immune cells in periodontitis and healthy groups were estimated using the CIBERSORT algorithm, and phenotypic subgroups of periodontitis based on hub MERG expression levels were explored using a consensus clustering method. RESULTS: A total of 44 differentially expressed MERGs were identified. The random forest and LASSO algorithms identified 9 hub MERGs (BCL2L11, GLDC, CYP24A1, COQ2, MTPAP, NIPSNAP3A, FAM162A, MYO19, and NDUFS1). ROC curve analysis showed that the hub gene and logistic regression model presented excellent diagnostic and discriminating abilities. Immune infiltration and consensus clustering analysis indicated that hub MERGs were highly correlated with various types of immune cells, and there were significant differences in immune cells and hub MERGs among different periodontitis subtypes. CONCLUSION: The periodontitis classification model based on MERGs shows excellent performance and can offer novel perspectives into the pathogenesis of periodontitis. The high correlation between MERGs and various immune cells and the significant differences between immune cells and MERGs in different periodontitis subtypes can clarify the regulatory roles of MitoEVs in the immune microenvironment of periodontitis. Future research should focus on elucidating the functional mechanisms of hub MERGs and exploring potential therapeutic interventions based on these findings.

Efficacy and safety of the Valsalva maneuver in relieving venipuncture pain in children and adults: A systematic review and meta-analysis.

Venipuncture is a common invasive clinical procedure, and pain management during puncture has been of interest to healthcare professionals. The purpose of this systematic review and meta-analysis was to evaluate the efficacy and safety of the Valsalva maneuver (VM) for the relief of venipuncture pain in children and adults. PubMed, Embase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP database, and CBM were searched from inception to December 2023 for all available randomized controlled trials (RCTs) that evaluated the impact of VM on venipuncture. Two reviewers independently performed study selection, data extraction, and risk of bias assessment. Continuous variables were analyzed by mean differences (MD) or standardized mean differences (SMD), whereas dichotomous variables were analyzed by risk ratios (RR). A total of 22 studies involving 1740 participants were included. The pooled results showed that VM relieved pain intensity during venipuncture in children (SMD = -0.89, 95% CI = -1.47 to -0.30, p = 0.003) and adults (SMD = -1.11, 95% CI = -1.46 to -0.77, p < 0.00001), reduced anxiety intensity (SMD = -1.07, 95% CI = -1.68 to -0.47, p = 0.0005), and shortened puncture time (MD = -13.52, 95% CI = -21.14 to -5.90, p = 0.0005). There was no significant difference in the success rate of venous cannulation, MAP, HR, or incidence of adverse events in subjects who performed VM compared to controls. VM was an effective and safe method of pain management that reduced pain intensity during venipuncture in children and adults without significant adverse effects. The results of this meta-analysis need to be further validated by more rigorous and larger RCTs.

Elucidating the mechanism and origin of stereoselectivity in the activation/transformation of an acetic ester catalyzed by an N-heterocyclic carbene.

The activation of an ester by N-heterocyclic carbene (NHC) organocatalysis is an efficient and important approach for generating an NHC-bound enolate intermediate, an important active intermediate in the transformation of carbonyl compounds. Herein, we perform a theoretical study on the NHC-catalyzed activation and transformation reaction of an acetic ester in which the NHC-bound enolate intermediate is a key intermediate. Multiple activation and transformation pathways are proposed and analyzed to identify an energetically favorable pathway. The use of different substrates for the reaction is considered. When a chalcone substrate is used, [4+2] cycloaddition between the enolate intermediate and the chalcone is identified to be both the rate- and stereoselectivity-determining step for the reaction, with the R-configured product being generated as the major isomer. Noncovalent interaction (NCI) and atoms-in-molecules (AIM) analyses are performed to identify the origin of the stereoselectivity of the reaction, and a local reactivity analysis is conducted to explore substrate and catalyst effects on the reaction.

An injectable collagen peptide-based hydrogel with desirable antibacterial, self-healing and wound-healing properties based on multiple-dynamic crosslinking.

Conventional collagen-based hydrogels as wound dressing materials are usually lack of antibacterial activity and easily broken when encountering external forces. In this work, we developed a collagen peptide-based hydrogel as a wound dressing, which was composed of adipic acid dihydrazide functionalized collagen peptide (Col-ADH), oxidized dextran (ODex), polyvinyl alcohol (PVA) and borax via multiple-dynamic reversible bonds (acylhydrazone, amine, borate ester and hydrogen bonds). The injectable hydrogel exhibited satisfactory self-healing ability, antibacterial activity, mechanical strength, as well as good biocompatibility and biodegradability. In vivo experiments demonstrated the rapid hemostasis, accelerated cell migration, and promoted wound healing capacities of the hydrogel. These results indicate that the multifunctional collagen peptide-based hydrogel has great potentials in the field of wound dressings.

Machine learning facilitated the conceptual design of an alum dosing system for phosphorus removal in a wastewater treatment plant.

Wastewater treatment plants (WWTPs) face challenges in controlling total phosphorus (TP), given more stringent regulations on TP discharging. In particular, WWTPs that operate at a small scale lack resources for real-time monitoring of effluent quality. This study aimed to develop a conceptual alum dosing system for reducing TP concentration, leveraging machine learning (ML) techniques and data from a full-scale WWTP containing incomplete TP information. The proposed system comprises two ML models in series: an Alert model based on LightGBM with an accuracy of 0.92, and a Dosage model employing a voting algorithm through combining three ML algorithms (LightGBM, SGD, and SVC) with an accuracy of 0.76. The proposed system has demonstrated the potential to ensure that 88.1% of the effluent remains below the TP discharge limit, which outperforms traditional dosing methods and could reduce overdosing from 61.3 to 12.1%. Furthermore, the SHapley Additive exPlanations (SHAP) analysis revealed that incorporating the output features from the previous cycle and utilizing the results of the Alert model as the input features for dosage prediction could be an effective method for data with limited information. The findings of this study have practical applications in improving the efficiency and effectiveness of TP control in small-scale WWTPs, providing a valuable solution for complying with stringent regulations and enhancing environmental sustainability.

Characterization of phosphate solubilizing bacteria in the sediments of eutrophic lakes and their potential for cyanobacterial recruitment.

Microbes may induce endogenous phosphorus (P) migration from lacustrine sediment. This study focused on the role of phosphate-solubilizing bacteria (PSB) disturbance in affecting the sediment P release and further contributing to cyanobacterial recruitment in Meiliang Bay, Lake Taihu. Gluconic acid was the main mechanism of phosphate solubilizing by PSB. The dominant PSB (Burkholderia) isolated from eutrophic lake sediments was used as a representative to investigate the effects of disturbance on endogenous P release using diffusive gradients in thin films (DGT) and high-resolution dialysis (HR-Peeper). The results show that soluble reactive phosphorus (SRP) and iron (Fe (II)) concentrations could reach 0.51 mg L-1 and 33.56 mg L-1 in pore water, respectively. And the sediment DGT-P and DGT-Fe were relatively reduced by PSB. Subsequent the chlorophyll a (Chl a) concentrations reached peaks of 344.8 µg L-1 in overlying water. The abundance of the dominant PSB (Burkholderia-Caballeronia-Paraburkholderia) were significantly associated with Chl a (P < 0.05) and algal effective state phosphorus (AAP) (P < 0.05), respectively. PSB mainly regulates AAP leaching to pore water and then diffusing across the sediment-water interface to the overlying water, producing the effect of cyanobacteria recruitment. The results provide new insights into early management of cyanobacterial resuscitation in a large eutrophic lake.

Fluctuation theorems and thermodynamic inequalities for nonequilibrium processes stopped at stochastic times.

We investigate the thermodynamics of general nonequilibrium processes stopped at stochastic times. We propose a systematic strategy for constructing fluctuation-theorem-like martingales for each thermodynamic functional, yielding a family of stopping-time fluctuation theorems. We derive second-law-like thermodynamic inequalities for the mean thermodynamic functional at stochastic stopping times, the bounds of which are even stronger than the thermodynamic inequalities resulting from the traditional fluctuation theorems when the stopping time is reduced to a deterministic one. Numerical verification is carried out for three well-known thermodynamic functionals, namely, entropy production, free energy dissipation, and dissipative work. These universal equalities and inequalities are valid for arbitrary stopping strategies, and thus provide a comprehensive framework with insights into the fundamental principles governing nonequilibrium systems.

Organocatalytic atroposelective synthesis of axially chiral N,N'-pyrrolylindoles via de novo indole formation.

The first organocatalytic atroposelective synthesis of axially chiral N,N'-pyrrolylindoles based on o-alkynylanilines was successfully established via de novo indole formation catalyzed by chiral phosphoric acid (CPA). This new synthetic strategy introduced CPA-catalyzed asymmetric 5-endo-dig cyclization of new well-designed o-alkynylanilines containing a pyrrolyl unit, resulting in a wide range of axially chiral N,N'-pyrrolylindoles in high yields with exclusive regioselectivity and excellent enantioselectivity (up to 99% yield, >20 : 1 rr, 95 : 5 er). Considering the potential biological significance of N-N atropisomers, preliminary biological activity studies were performed and revealed that these structurally important N,N'-pyrrolylindoles had a low IC50 value with promising impressive cytotoxicity against several kinds of cancer cell lines. DFT studies reveal that the N-nucleophilic cyclization mediated by CPA is the rate- and stereo-determining step, in which ligand-substrate dispersion interactions facilitate the axial chirality of the target products.

Outcomes Following Transcatheter Aortic Valve Replacement for Aortic Stenosis in Patients With Type 0 Bicuspid, Type 1 Bicuspid, and Tricuspid Aortic Valves.

BACKGROUND: Data concerning the outcomes of transcatheter aortic valve replacement in type 0 bicuspid aortic stenosis (AS) are scarce. The study aims to compare the outcomes of transcatheter aortic valve replacement for AS in patients with type 0 bicuspid, type 1 bicuspid, and tricuspid aortic valve anatomy. METHODS: We enrolled consecutive patients undergoing transcatheter aortic valve replacement for severe AS between 2012 and 2022 in this single-center retrospective cohort study. The primary outcome was mortality, while secondary outcomes included in-hospital complications such as stroke and pacemaker implantation and transcatheter heart valve hemodynamic performance. RESULTS: The number of patients with AS with type 0 bicuspid, type 1 bicuspid, and tricuspid aortic valve anatomy was 328, 302, and 642, respectively. Self-expanding transcatheter heart valves were used in the majority of patients (n=1160; 91.4%). In the matched population, differences in mortality (30 days: 4.2% versus 1.7% versus 1.7%, Poverall=0.522; 1 year: 10% versus 2.3% versus 6.2%, Poverall=0.099) and all stroke (30 days: 1.0% versus 0.9% versus 0.0%, Poverall=0.765; 1 year: 1.4% versus 1.6% versus 1.3%, Poverall=NS) were nonsignificant, and the incidence of overall in-hospital complications was comparable among groups. Ascending aortic diameter was the single predictor of 1-year mortality in type 0 bicuspid patients (hazard ratio, 1.59 [95% CI, 1.03-2.44]; P=0.035). The proportion of patients with a mean residual gradient ≥20 mm Hg was the highest in those with type 0 bicuspid anatomy, although the need for permanent pacemaker implantation was the lowest in this group. CONCLUSIONS: Major clinical outcomes of transcatheter aortic valve replacement for AS in patients with type 0 bicuspid, type 1 bicuspid, and tricuspid aortic valve anatomy are equivalent at short- and mid-term follow-up. These observations merit further exploration in prospective international registries and randomized controlled trials.

Slow Auger Recombination in Ag2Se Colloidal Quantum Dots.

Efficient Auger recombination (AR) presents a significant challenge for the advancement of colloidal quantum dot (QD)-based devices involving multiexcitons. Here, the AR dynamics of near-infrared Ag2Se QDs were studied through transient absorption experiments. As the QD radius increases from 0.9 to 2.5 nm, the biexciton lifetime (τ2) of Ag2Se QDs increases from 35 to 736 ps, which is approximately 10 times longer than that of comparable-sized CdSe and PbSe QDs. A qualitative analysis based on observables indicates that the slow Auger rate is primarily attributed to the low density of the final states. The biexciton lifetime and triexciton lifetime (τ3) of Ag2Se QDs follow R3 and R2.6 dependence, respectively. Moreover, the ratio of τ2/τ3 is ∼2.3-3.2, which is markedly lower than the value expected from statistical scaling (4.5). These findings suggest that environmentally friendly Ag2Se QDs can serve as excellent candidates for low-threshold lasers and third-generation photovoltaics utilizing carrier multiplication.

Interpretable machine-learning model for Predicting the Convalescent COVID-19 patients with pulmonary diffusing capacity impairment.

INTRODUCTION: The COVID-19 patients in the convalescent stage noticeably have pulmonary diffusing capacity impairment (PDCI). The pulmonary diffusing capacity is a frequently-used indicator of the COVID-19 survivors' prognosis of pulmonary function, but the current studies focusing on prediction of the pulmonary diffusing capacity of these people are limited. The aim of this study was to develop and validate a machine learning (ML) model for predicting PDCI in the COVID-19 patients using routinely available clinical data, thus assisting the clinical diagnosis. METHODS: Collected from a follow-up study from August to September 2021 of 221 hospitalized survivors of COVID-19 18 months after discharge from Wuhan, including the demographic characteristics and clinical examination, the data in this study were randomly separated into a training (80%) data set and a validation (20%) data set. Six popular machine learning models were developed to predict the pulmonary diffusing capacity of patients infected with COVID-19 in the recovery stage. The performance indicators of the model included area under the curve (AUC), Accuracy, Recall, Precision, Positive Predictive Value(PPV), Negative Predictive Value (NPV) and F1. The model with the optimum performance was defined as the optimal model, which was further employed in the interpretability analysis. The MAHAKIL method was utilized to balance the data and optimize the balance of sample distribution, while the RFECV method for feature selection was utilized to select combined features more favorable to machine learning. RESULTS: A total of 221 COVID-19 survivors were recruited in this study after discharge from hospitals in Wuhan. Of these participants, 117 (52.94%) were female, with a median age of 58.2 years (standard deviation (SD) = 12). After feature selection, 31 of the 37 clinical factors were finally selected for use in constructing the model. Among the six tested ML models, the best performance was accomplished in the XGBoost model, with an AUC of 0.755 and an accuracy of 78.01% after experimental verification. The SHAPELY Additive explanations (SHAP) summary analysis exhibited that hemoglobin (Hb), maximal voluntary ventilation (MVV), severity of illness, platelet (PLT), Uric Acid (UA) and blood urea nitrogen (BUN) were the top six most important factors affecting the XGBoost model decision-making. CONCLUSION: The XGBoost model reported here showed a good prognostic prediction ability for PDCI of COVID-19 survivors during the recovery period. Among the interpretation methods based on the importance of SHAP values, Hb and MVV contributed the most to the prediction of PDCI outcomes of COVID-19 survivors in the recovery period.

Bioelectret poly(lactic acid) membranes with simultaneously enhanced physical interception and electrostatic adsorption of airborne PM0.3.

Traditional polymeric fibrous membranes have been extensively used to reduce the health risks caused by airborne particulate matter (PM), leading to the dramatically increasing pollution of plastics and microplastics. Although great efforts have been made to develop poly(lactic acid) (PLA)-based membrane filters, they are frequently dwarfed by their relatively poor electret properties and electrostatic adsorptive mechanisms. To resolve this dilemma, a bioelectret approach was proposed in this work, strategically involving the bioinspired adhesion of dielectric hydroxyapatite nanowhiskers as a biodegradable electret to promote the polarization properties of PLA microfibrous membranes. In addition to significant improvements in tensile properties, the incorporation of hydroxyapatite bioelectret (HABE) enabled remarkable increase in the removal efficiencies of ultrafine PM0.3 in a high-voltage electrostatic field (10 and 25 kV). This was exemplified by the largely increased filtering performance (69.75%, 23.1 Pa) for PLA membranes loaded with 10 wt% HABE at the normal airflow rate (32 L/min) compared to the pristine PLA counterpart (32.89%, 7.2 Pa). Although the filtration efficiency of PM0.3 for the counterpart dramatically decreased to 21.6% at 85 L/min, the increment was maintained at nearly 196% for the bioelectret PLA, while an ultralow pressure drop (74.5 Pa) and high humidity resistance (RH 80%) were achieved. The unusual property combination were ascribed to the HABE-enabled realization of multiple filtration mechanisms, including the simultaneous enhancement of physical interception and electrostatic adsorption. The significant filtration applications, unattainable with conventional electret membranes, demonstrate the bioelectret PLA as a promising biodegradable platform that allows high filtration properties and humidity resistance.

A female of progressive familial intrahepatic cholestasis type 3 caused by heterozygous mutations of ABCB4 gene and her cirrhosis improved after treatment of ursodeoxycholic acid: a case report.

BACKGROUND: Progressive familial intrahepatic cholestasis (PFIC) is a group of rapidly progressive autosomal recessive disorders characterized by intrahepatic cholestasis. PFIC-3 is caused by mutations in the ATP-binding cassette subfamily B member 4 gene (ABCB4), which encodes multidrug resistance protein 3 (MDR3/ABCB4). Patients are usually in infancy or childhood, but cirrhosis and portal hypertension may be the first manifestation in older children or young adults. CASE PRESENTATION: A 25-year-old young woman with recurrent abnormal hepatic function was mainly characterized by increased gamma glutamyl transpeptidase (GGT) and bile acid with cryptogenic cirrhosis. After 7 months of treatment with ursodeoxycholic acid (UDCA), her hepatic pathology suggested there were also obvious widening and venous fibrosis around the portal vein, and slight bile duct hyperplasia at the edge of the portal area. Infiltration of inflammatory cells around the portal vein and hepatocyte ABCB4/MDR3 protein was basically normal. Sequencing indicated the patient had heterozygous mutations in the ABCB4 gene: c.2696C > G and wes [hg19]7q21.12(87032513-87033422) × 1. Through SWISS-MODEL Predict for protein structures, the missense mutation results in protein side chain missing a methyl group (-CH3), and the deletion mutation results in the serious damage to the structure of MDR3 protein which lead to phosphatidylcholine deficiency of bile in the capillary bile ducts. The toxic effect of bile salts then damages the bile ducts, causing cholestasis and cholangitis, which can then develop into biliary cirrhosis. Through the analysis of pathogenicity prediction software, the mutations led to PFIC3. After treatment of UDCA for 29 months, her cirrhosis was improved, hepatic function was close to normal. CONCLUSION: Novel heterozygous mutations are the molecular pathological cause of PFIC3 in this patient. All young adult patients with occult cirrhosis should be tested for ABCB4. Early diagnosis of PFIC3 and continued treatment with UDCA are key to improving prognosis and delaying the onset of end-stage liver disease.