A Scoping Review of Factors Influencing Smoking Cessation in Patients with Chronic Obstructive Pulmonary Disease.

To provide a scoping review of studies on factors affecting smoking cessation in patients with chronic obstructive pulmonary disease (COPD), so as to provide a basis for healthcare professionals to intervene early in the process of cessation of smoking in patients with COPD, and to formulate personalized interventions for smoking cessation. Arksey and O'Malley's scoping review methodology as a framework, searched databases including CNKI, Wanfang Data, VIP, China Biomedical Database, PubMed, Web of Science, Embase, ProQuest, CINAHL, and Cochrane Library to collect literature on factors influencing smoking cessation among COPD patients. The literature was screened, data extracted, and summarized accordingly. A total of 28 papers were included. The socio-demographic related factors affecting smoking cessation in patients with COPD were age, educational level, residence, marital status, occupational status, economic status, race, and sex; tobacco related factors included smoking index, smoking duration (years), cumulative smoking (packs/year), smoking intensity (packs/day), and tobacco addiction; disease related factors included mMRC score, GOLD level, severity of airflow restrictions, symptom, activity limitation due to lung problems, history of deterioration in outpatient care, receipt of COPD medication, receipt of lung CT, receipt of pulmonary function tests, receipt of surgery, and comorbid comorbidities; psychologically related factors included mental health status, quit smoking health beliefs, smoking cessation self-efficacy, motivation to quit smoking, stress, and adverse emotions; environmental/Interpersonal network related factors-included environmental impacts, social support, family support, tobacco control policies, and satisfaction with cessation care; and behavior related factors included alcohol consumption, coffee consumption, eating, physical activity, and have a hobby. Healthcare professionals should avoid critical education of COPD patients in the process of smoking cessation management, pay attention to the adverse effects of medication side effects on patients, emphasize the improvement of patients' health beliefs and self-efficacy in smoking cessation, and help patients to establish a correct cognition of smoking cessation.

Fully automated hybrid approach on conventional MRI for triaging clinically significant liver fibrosis: A multi-center cohort study.

Establishing reliable noninvasive tools to precisely diagnose clinically significant liver fibrosis (SF, ≥F2) remains an unmet need. We aimed to build a combined radiomics-clinic (CoRC) model for triaging SF and explore the additive value of the CoRC model to transient elastography-based liver stiffness measurement (FibroScan, TE-LSM). This retrospective study recruited 595 patients with biopsy-proven liver fibrosis at two centers between January 2015 and December 2021. At Center 1, the patients before December 2018 were randomly split into training (276) and internal test (118) sets, the remaining were time-independent as a temporal test set (96). Another data set (105) from Center 2 was collected for external testing. Radiomics scores were built with selected features from Deep learning-based (ResUNet) automated whole liver segmentations on MRI (T2FS and delayed enhanced-T1WI). The CoRC model incorporated radiomics scores and relevant clinical variables with logistic regression, comparing routine approaches. Diagnostic performance was evaluated by the area under the receiver operating characteristic curve (AUC). The additive value of the CoRC model to TE-LSM was investigated, considering necroinflammation. The CoRC model achieved AUCs of 0.79 (0.70, 0.86), 0.82 (0.73, 0.89), and 0.81 (0.72-0.91), outperformed FIB-4, APRI (all p < 0.05) in the internal, temporal, and external test sets and maintained the discriminatory power in G0-1 subgroups (AUCs range, 0.85-0.86; all p < 0.05). The AUCs of joint CoRC-LSM model were 0.86 (0.79-0.94), and 0.81 (0.72-0.90) in the internal and temporal sets (p = 0.01). The CoRC model was useful for triaging SF, and may add value to TE-LSM.

Development of an hollow fiber solid phase microextraction method for the analysis of unbound fraction of imatinib and N-desmethyl imatinib in human plasma.

Therapeutic drug monitoring (TDM) of imatinib (IM) in cancer therapy offers the potential to improve treatment efficacy while minimizing toxicity. There was a significant correlation between unbound concentration and clinical response and toxicity, compared with total plasma concentrations, and the quantification of unbound IM and its metabolite, N-desmethyl imatinib (NDI) are of interest for TDM. However, traditional unbound drug separation methods have shortcomings, especially are susceptible to non-specific binding (NSB) of drugs to the polymer-constructed components of filter membranes, which are difficult to avoid at present. Hence it is necessary to developed a reliable separation method for the analysis of the unbound fraction of IM and NDI in TDM. We developed and validated an hollow fiber solid phase microextraction (HF-SPME) method coupled with high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) that to measure unbound IM and NDI concentration in human plasma. It used the NSB phenomenon and solve the NSB problem. The preparation procedure only involves a common vortex and ultrasonication without dilution of samples and modification of membrane. A total of 50 chronic myeloid leukemia (CML) patients were enrolled in our study. The relationship between the unbound and total concentrations for IM and NDI, as well as the concentration ratios of NDI to IM in 50 clinical plasma samples were investigated. The extraction recovery is high to 95.5-106 % with validation parameters for the methodological results were all excellent. There were both a poor linear relationship between the unbound and total concentrations for IM (r2=0.504) and NDI (r2=0.201) in 50 clinical plasma samples. The unbound concentration ratios of NDI to IM varied widely in CML patients. The determination of unbound IM and NDI concentration is meaningful and necessary. The developed HF-SPME method is simple, accurate and precise that could be used to measure unbound IM and NDI concentration in clinical TDM.

The effect of airborne particulate matter 2.5 (PM2.5) on meibomian gland.

Exposure to particulate matters in air pollution of 2.5 µm or less (PM2.5) was associated with loss of meibomian glands. The aim of this study was to verify that PM2.5 could directly impact meibomian gland epithelial cells and damage their function. To investigate the impact of PM2.5 on meibomian gland, immortalized human meibomian gland epithelial cells were treated with various concentrations of PM2.5in vitro. Meibomian gland cell microstructure, cell viability, expression of proliferating cell nuclear antigen and IL-1ß, and intracellular accumulation of acidic vesicles were measured by transmission electron microscopy, cell counting, Western blot and LysoTracker staining, respectively. To further study the effect of PM2.5in vivo, male C57BL/6J mice were treated with 5 mg/ml PM2.5 or vehicle for 3 months. Corneal fluorescein staining and ocular examinations were done before and after the treatment. Eyelids tissues were processed for morphological studies, immunostaining and Oil Red O staining. Our data suggest that exposure to PM2.5 caused significant meibomian gland dropout, clogged gland orifice and increased corneal fluorescein staining that were consistent with the clinical presentations of meibomian gland dysfunction. Prominent changes in the morphology and ultrastructure of meibomian glands was observed with PM2.5 treatment. PM2.5 promoted ductal keratinization, inhibited cell proliferation, induced cell apoptosis and increased Interleukin-1ß production in meibomian gland epithelial cells. This study may explain the association between PM2.5 exposure and meibomian gland dropout observed in clinic. PM2.5 resuspension instillation could be used to induce a meibomian gland dysfunction animal model.

Development and validation of radiomics nomogram for metastatic status of epithelial ovarian cancer.

To develop and validate an enhanced CT-based radiomics nomogram for evaluating preoperative metastasis risk of epithelial ovarian cancer (EOC). One hundred and nine patients with histologically confirmed EOC were retrospectively enrolled. The volume of interest (VOI) was delineated in preoperative enhanced CT images, and 851 radiomics features were extracted. The radiomics features were selected by the least absolute shrinkage and selection operator (LASSO), and the rad-score was calculated using the formula of the radiomics label. A clinical model, radiomics model, and combined model were constructed using the logistic regression classification algorithm. Receiver operating characteristic (ROC) curve analysis and decision curve analysis (DCA) were used to evaluate the diagnostic performance of the models. Seventy-five patients (68.8%) were histologically confirmed to have metastasis. Eleven optimal radiomics features were retained by the LASSO algorithm to develop the radiomic model. The combined model for evaluating metastasis of EOC achieved area under the curve (AUC) values of 0.929 (95% CI 0.8593-0.9996) in the training cohort and 0.909 (95% CI 0.7921-1.0000) in the test cohort. To facilitate clinical use, a radiomic nomogram was built by combining the clinical characteristics with rad-score. The DCA indicated that the nomogram had the most significant net benefit when the threshold probability exceeded 15%, surpassing the benefits of both the treat-all and treat-none strategies. Compared with clinical model and radiomics model, the radiomics nomogram has the best diagnostic performance in evaluating EOC metastasis. The nomogram is a useful and convenient tool for clinical doctors to develop personalized treatment plans for EOC patients.

Effects of long-term no-tillage and different stover mulching amounts on soil carbon and nitrogen contents and enzyme activities of carbon and nitrogen cycle in Mollisols.

To understand the effects of different stover mulching amounts in no-tillage on soil carbon and nitrogen contents and enzyme activities, finding a stover mulching amount which can meet the requirement of soil carbon and nitrogen accumulation while maximizing economic benefits, we conducted a long-term conservation tillage field experiment since 2007 in Mollisols area of Northeast China. We analyzed soil carbon and nitrogen contents, enzyme activities and economic benefits under conventional tillage (Control, CT), no-tillage without stover mulching (NT0), no-tillage with 33% stover mulching (NT33), no-tillage with 67% stover mulching (NT67), and no-tillage with 100% stover mulching (NT100) before planting in May 2020. The results showed that compared with CT, NT0 did not affect soil organic carbon (SOC) and total nitrogen (TN) contents, but increased soil organic carbon recalcitrance and decreased the availability of dissolved organic nitrogen (DON) and ammonium nitrogen. Compared with NT0, no-tillage with stover mulching significantly increased SOC contents in 0-10 cm layer and increased with the amounts of stover. In addition, NT67 and NT100 significantly increased SOC stocks, facilitating the accumulation of soil organic matter. The effects of different stover mulching amounts on soil nitrogen content in 0-10 cm layer were different. Specifically, NT33 increased DON content and DON/TN, NT67 increased DON content, while NT100 increased TN content. Compared with CT, NT0 decreased peroxidase (POD) activity in 0-10 cm layer. Compared with NT0, NT33 increased ß-glucosidase (ßG), cellobiase (CB), 1,4-ß-N-acetylglucosaminidase (NAG), polyphenol oxidase (PPO) and POD activities, while NT67 only increased CB, NAG and POD activities in 0-10 cm soil layer, both alleviated microbial nutrient limitation. NT100 increased PPO activity in 10-20 cm layer. NT33 increased carbon conversion efficiency of stover compared with NT100, and had the highest economic benefit. In all, no-tillage with 33% stover mulching was the optimal strategy, which could promote nutrient circulation, boost stover utilization efficiency, improve the quality of Mollisols, and maximize guaranteed income.

Bioactive 5/5/5/6 Four-Ring System Iridoids from Plumeria alba L.

Two rare 5/5/5/6 four-ring system iridoids, allamancins A and B (1 and 2) together with one known biogenetically related iridoid derivative, 3-O-methyallamancin (3) were isolated from the flowers of Plumeria alba L. The structures of these iridoid derivatives were determined by comprehensive spectroscopic analyses. The absolute configuration of 1 was confirmed by X-ray crystallographic analysis. The inhibitory activities of compounds 1-3 against nitric oxide (NO) production induced and three cancer cell lines were evaluated in vitro. Compounds 1 and 3 showed inhibitory activities on NO production with IC50 values of 18.3±0.12 and 22.1±0.14 µM, respectively. Compounds 1-3 showed moderate inhibitory activities against cancer cell lines of A549, Hela and MCF-7.

Metformin Overcomes the Consequences of NKX3.1 Loss to Suppress Prostate Cancer Progression.

BACKGROUND: The antidiabetic drug metformin has known anticancer effects related to its antioxidant activity; however, its clinical benefit for prostate cancer (PCa) has thus far been inconclusive. Here, we investigate whether the efficacy of metformin in PCa is related to the expression status of NKX3.1, a prostate-specific homeobox gene that functions in mitochondria to protect the prostate from aberrant oxidative stress. OBJECTIVE: To investigate the relationship of NKX3.1 expression and metformin efficacy in PCa. DESIGN, SETTING, AND PARTICIPANTS: Functional studies were performed in vivo and in vitro in genetically engineered mouse models and human LNCaP cells, and organotypic cultures having normal or reduced/absent levels of NKX3.1. Correlative studies were performed using two independent retrospective tissue microarray cohorts of radical prostatectomies and a retrospective cohort of prostate biopsies from patients on active surveillance. INTERVENTION: Metformin was administered before or after the induction of oxidative stress by treatment with paraquat. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Functional endpoints included analyses of histopathology, tumorigenicity, and mitochondrial function. Correlative endpoints include Kaplan-Meier curves and Cox proportional hazard regression models. RESULTS AND LIMITATIONS: Metformin reversed the adverse consequences of NKX3.1 deficiency following oxidative stress in vivo and in vitro, as evident by reduced tumorigenicity and restored mitochondrial function. Patients with low NKX3.1 expression showed a significant clinical benefit from taking metformin. CONCLUSIONS: Metformin can overcome the adverse consequences of NKX3.1 loss for PCa progression by protecting against oxidative stress and promoting normal mitochondrial function. These functional activities and clinical correlates were observed only with low NKX3.1 expression. Thus, the clinical benefit of metformin in PCa may depend on the status of NKX3.1 expression. PATIENT SUMMARY: Prostate cancer patients with low NKX3.1 are likely to benefit most from metformin treatment to delay disease progression in a precision interception paradigm.

RBMX involves in telomere stability maintenance by regulating TERRA expression.

Telomeric repeat-containing RNA (TERRA) is a class of long noncoding RNAs (lncRNAs) that are transcribed from subtelomeric to telomeric region of chromosome ends. TERRA is prone to form R-loop structures at telomeres by invading into telomeric DNA. Excessive telomere R-loops result in telomere instability, so the TERRA level needs to be delicately modulated. However, the molecular mechanisms and factors controlling TERRA level are still largely unknown. In this study, we report that the RNA binding protein RBMX is a novel regulator of TERRA level and telomere integrity. The expression level of TERRA is significantly elevated in RBMX depleted cells, leading to enhanced telomere R-loop formation, replication stress, and telomere instability. We also found that RBMX binds to TERRA and the nuclear exosome targeting protein ZCCHC8 simultaneously, and that TERRA degradation slows down upon RBMX depletion, implying that RBMX promotes TERRA degradation by regulating its transportation to the nuclear exosome, which decays nuclear RNAs. Altogether, these findings uncover a new role of RBMX in TERRA expression regulation and telomere integrity maintenance, and raising RBMX as a potential target of cancer therapy.

LEARN algorithm: a novel option for predicting non-alcoholic steatohepatitis.

Background: There is an unmet need for accurate non-invasive methods to diagnose non-alcoholic steatohepatitis (NASH). Since impedance-based measurements of body composition are simple, repeatable and have a strong association with non-alcoholic fatty liver disease (NAFLD) severity, we aimed to develop a novel and fully automatic machine learning algorithm, consisting of a deep neural network based on impedance-based measurements of body composition to identify NASH [the bioeLectrical impEdance Analysis foR Nash (LEARN) algorithm]. Methods: A total of 1,259 consecutive subjects with suspected NAFLD were screened from six medical centers across China, of which 766 patients with biopsy-proven NAFLD were included in final analysis. These patients were randomly subdivided into the training and validation groups, in a ratio of 4:1. The LEARN algorithm was developed in the training group to identify NASH, and subsequently, tested in the validation group. Results: The LEARN algorithm utilizing impedance-based measurements of body composition along with age, sex, pre-existing hypertension and diabetes, was able to predict the likelihood of having NASH. This algorithm showed good discriminatory ability for identifying NASH in both the training and validation groups [area under the receiver operating characteristics (AUROC): 0.81, 95% CI: 0.77-0.84 and AUROC: 0.80, 95% CI: 0.73-0.87, respectively]. This algorithm also performed better than serum cytokeratin-18 neoepitope M30 (CK-18 M30) level or other non-invasive NASH scores (including HAIR, ION, NICE) for identifying NASH (P value <0.001). Additionally, the LEARN algorithm performed well in identifying NASH in different patient subgroups, as well as in subjects with partial missing body composition data. Conclusions: The LEARN algorithm, utilizing simple easily obtained measures, provides a fully automated, simple, non-invasive method for identifying NASH.

Lipotoxicity-polarised macrophage-derived exosomes regulate mitochondrial fitness through Miro1-mediated mitophagy inhibition and contribute to type 2 diabetes development in mice.

AIMS/HYPOTHESIS: Insulin resistance is a major pathophysiological defect in type 2 diabetes and obesity. Numerous experimental and clinical studies have provided evidence that sustained lipotoxicity-induced mitophagy deficiency can exacerbate insulin resistance, leading to a vicious cycle between mitophagy dysfunction and insulin resistance, and thereby the onset of type 2 diabetes. Emerging evidence suggests that exosomes (Exos) from M2 macrophages play an essential role in modulating metabolic homeostasis. However, how macrophages are affected by lipotoxicity and the role of lipotoxicity in promoting macrophage activation to the M1 state have not been determined. The objective of this study was to determine whether M1 macrophage-derived Exos polarised by lipopolysaccharide (LPS) + palmitic acid (PA)-induced lipotoxicity contribute to metabolic homeostasis and impact the development of insulin resistance in type 2 diabetes. METHODS: Lipotoxicity-polarised macrophage-derived M1 Exos were isolated from bone marrow (C57BL/6J mouse)-derived macrophages treated with LPS+PA. Exos were characterised by transmission electron microscopy, nanoparticle tracking analysis and western blotting. Flow cytometry, H&E staining, quantitative real-time PCR, immunofluorescence, glucose uptake and output assays, confocal microscopy imaging, western blotting, GTTs and ITTs were conducted to investigate tissue inflammation, mitochondrial function and insulin resistance in vitro and in vivo. The roles of miR-27-3p and its target gene Miro1 (also known as Rhot1, encoding mitochondrial rho GTPase 1) and relevant pathways were predicted and assessed in vitro and in vivo using specific miRNA mimic, miRNA inhibitor, miRNA antagomir and siRNA. RESULTS: miR-27-3p was highly expressed in M1 Exos and functioned as a Miro1-inactivating miRNA through the miR-27-3p-Miro1 axis, leading to mitochondria fission rather than fusion as well as mitophagy impairment, resulting in NOD-like receptor 3 inflammatory activation and development of insulin resistance both in vivo and in vitro. Inactivation of miR-27-3p induced by M1 Exos prevented type 2 diabetes development in high-fat-diet-fed mice. CONCLUSIONS/INTERPRETATION: These findings suggest that the miR-27-3p-Miro1 axis, as a novel regulatory mechanism for mitophagy, could be considered as a new therapeutic target for lipotoxicity-related type 2 diabetes disease development.

2D Amorphous Iron Selenide Sulfide Nanosheets for Stable and Rapid Sodium-Ion Storage.

Sodium ion batteries (SIBs) suffer from large electrode volume change and sluggish redox kinetics for the relatively large ionic radius of sodium ions, raising a significant challenge to improve their long-term cyclability and rate capacity. Here, it is proposed to apply 2D amorphous iron selenide sulfide nanosheets (a-FeSeS NSs) as an anode material for SIBs and demonstrate that they exhibit remarkable rate capability of 528.7 mAh g-1 at 1 A g-1 and long-life cycle (10 000 cycles) performance (300.4 mAh g-1 ). This performance is much more superior to that of the previously reported Fe-based anode materials, which is attributed to their amorphous structure that alleviates volume expansion of electrode, 2D nature that facilitates electrons/ions transfer, and the S/Se double anions that offer more reaction sites and stabilize the amorphous structure. Such a 2D amorphous strategy provides a fertile platform for structural engineering of other electrode materials, making a more secure energy prospect closer to a reality.

Pigtail catheter exchange technique for the Simmons catheter formation in transradial cerebral angiography.

BACKGROUND: The transradial approach (TRA) has become popular for diagnostic cerebral angiography. However, this approach is still used less often because of problematic formation of the Simmons catheter. The purpose of this study was to introduce a pigtail catheter exchange technique for Simmons catheter formation to improve the success rates with a shorter operation time and without increasing complications. METHODS: This retrospective study included consecutive patients eligible for right TRA cerebral angiography at our institution from 2021. To introduce the technique, the cerebral angiogram of formation of the Simmons catheter in the type II aortic arch was constructed. Patient demographic and angiographic data were collected. RESULTS: In total, 295 cerebral angiographies were evaluated. There were 155 (52.5 %), 83 (28.1 %), 39 (13.2 %), and 18 (6.1 %) patients with types I, II, and III aortic arches and bovine arch, respectively. The total fluoroscopy time, operation time and radiation exposure were 6.3 ± 4.4 min, 17.7 ± 8.3 min and 559.2 ± 197.3 mGy, respectively. The Simmons catheter was successfully formed in 294 of 295 patients, with a success rate of 99.6 %, confirming an effective technique for right TRA cerebral angiography. No severe complications were observed in any patient. CONCLUSIONS: Pigtail catheter exchange may be an effective and safe technique for right TRA cerebral angiography. The findings of this report prompted institutions to apply this technique clinically and can serve as a basis for future trials focused on TRA cerebral angiography.

Hepatocytic ballooning in non-alcoholic steatohepatitis: Dilemmas and future directions.

Hepatocytic ballooning is a key histological feature in the diagnosis of non-alcoholic steatohepatitis (NASH) and is an essential component of the two most widely used histological scoring systems for diagnosing and staging non-alcoholic fatty liver disease (NAFLD) [namely, the NAFLD activity score (NAS), and the steatosis, activity and fibrosis (SAF) scoring system]. As a result of the increasing incidence of NASH globally, the diagnostic challenges of hepatocytic ballooning are unprecedented. Despite the clear pathological concept of hepatocytic ballooning, there are still challenges in assessing hepatocytic ballooning in 'real life' situations. Hepatocytic ballooning can be confused with cellular oedema and microvesicular steatosis. Significant inter-observer variability does exist in assessing the presence and severity of hepatocytic ballooning. In this review article, we describe the underlying mechanisms associated with hepatocytic ballooning. Specifically, we discuss the increased endoplasmic reticulum stress and the unfolded protein response, as well as the rearrangement of the intermediate filament cytoskeleton, the appearance of Mallory-Denk bodies and activation of the sonic Hedgehog pathway. We also discuss the use of artificial intelligence in the detection and interpretation of hepatocytic ballooning, which may provide new possibilities for future diagnosis and treatment.

Novel urinary protein panels for the non-invasive diagnosis of non-alcoholic fatty liver disease and fibrosis stages.

BACKGROUND & AIMS: There is an unmet clinical need for non-invasive tests to diagnose non-alcoholic fatty liver disease (NAFLD) and individual fibrosis stages. We aimed to test whether urine protein panels could be used to identify NAFLD, NAFLD with fibrosis (stage F ≥ 1) and NAFLD with significant fibrosis (stage F ≥ 2). METHODS: We collected urine samples from 100 patients with biopsy-confirmed NAFLD and 40 healthy volunteers, and proteomics and bioinformatics analyses were performed in this derivation cohort. Diagnostic models were developed for detecting NAFLD (UPNAFLD model), NAFLD with fibrosis (UPfibrosis model), or NAFLD with significant fibrosis (UPsignificant fibrosis model). Subsequently, the derivation cohort was divided into training and testing sets to evaluate the efficacy of these diagnostic models. Finally, in a separate independent validation cohort of 100 patients with biopsy-confirmed NAFLD and 45 healthy controls, urinary enzyme-linked immunosorbent assay analyses were undertaken to validate the accuracy of these new diagnostic models. RESULTS: The UPfibrosis model and the UPsignificant fibrosis model showed an AUROC of .863 (95% CI: .725-1.000) and 0.858 (95% CI: .712-1.000) in the training set; and .837 (95% CI: .711-.963) and .916 (95% CI: .825-1.000) in the testing set respectively. The UPNAFLD model showed an excellent diagnostic performance and the area under the receiver operator characteristic curve (AUROC) exceeded .90 in the derivation cohort. In the independent validation cohort, the AUROC for all three of the above diagnostic models exceeded .80. CONCLUSIONS: Our newly developed models constructed from urine protein biomarkers have good accuracy for non-invasively diagnosing liver fibrosis in NAFLD.

Fully connected neural network-based serum surface-enhanced Raman spectroscopy accurately identifies non-alcoholic steatohepatitis.

BACKGROUND/PURPOSE OF THE STUDY: There is a need to find a standardized and low-risk diagnostic tool that can non-invasively detect non-alcoholic steatohepatitis (NASH). Surface enhanced Raman spectroscopy (SERS), which is a technique combining Raman spectroscopy (RS) with nanotechnology, has recently received considerable attention due to its potential for improving medical diagnostics. We aimed to investigate combining SERS and neural network approaches, using a liver biopsy dataset to develop and validate a new diagnostic model for non-invasively identifying NASH. METHODS: Silver nanoparticles as the SERS-active nanostructures were mixed with blood serum to enhance the Raman scattering signals. The spectral data set was used to train the NASH classification model by a neural network primarily consisting of a fully connected residual module. RESULTS: Data on 261 Chinese individuals with biopsy-proven NAFLD were included and a prediction model for NASH was built based on SERS spectra and neural network approaches. The model yielded an AUROC of 0.83 (95% confidence interval [CI] 0.70-0.92) in the validation set, which was better than AUROCs of both serum CK-18-M30 levels (AUROC 0.63, 95% CI 0.48-0.76, p = 0.044) and the HAIR score (AUROC 0.65, 95% CI 0.51-0.77, p = 0.040). Subgroup analyses showed that the model performed well in different patient subgroups. CONCLUSIONS: Fully connected neural network-based serum SERS analysis is a rapid and practical tool for the non-invasive identification of NASH. The online calculator website for the estimated risk of NASH is freely available to healthcare providers and researchers ( http://www.pan-chess.cn/calculator/RAMAN_score ).

TLsub: A transfer learning based enhancement to accurately detect mutations with wide-spectrum sub-clonal proportion.

Mutation detecting is a routine work for sequencing data analysis and the trading of existing tools often involves the combinations of signals on a set of overlapped sequencing reads. However, the subclonal mutations, which are reported to contribute to tumor recurrence and metastasis, are sometimes eliminated by existing signals. When the clonal proportion decreases, signals often present ambiguous, while complicated interactions among signals break the IID assumption for most of the machine learning models. Although the mutation callers could lower the thresholds, false positives are significantly introduced. The main aim here was to detect the subclonal mutations with high specificity from the scenario of ambiguous sample purities or clonal proportions. We proposed a novel machine learning approach for filtering false positive calls to accurately detect mutations with wide spectrum subclonal proportion. We have carried out a series of experiments on both simulated and real datasets, and compared to several state-of-art approaches, including freebayes, MuTect2, Sentieon and SiNVICT. The results demonstrated that the proposed method adapts well to different diluted sequencing signals and can significantly reduce the false positive when detecting subclonal mutations. The codes have been uploaded at https://github.com/TrinaZ/TL-fpFilter for academic usage only.

DETexT: An SNV detection enhancement for low read depth by integrating mutational signatures into TextCNN.

Detecting SNV at very low read depths helps to reduce sequencing requirements, lowers sequencing costs, and aids in the early screening, diagnosis, and treatment of cancer. However, the accuracy of SNV detection is significantly reduced at read depths below ×34 due to the lack of a sufficient number of read pairs to help filter out false positives. Many recent studies have revealed the potential of mutational signature (MS) in detecting true SNV, understanding the mutational processes that lead to the development of human cancers, and analyzing the endogenous and exogenous causes. Here, we present DETexT, an SNV detection method better suited to low read depths, which classifies false positive variants by combining MS with deep learning algorithms to mine correlation information around bases in individual reads without relying on the support of duplicate read pairs. We have validated the effectiveness of DETexT on simulated and real datasets and conducted comparative experiments. The source code has been uploaded to https://github.com/TrinaZ/extra-lowRD for academic use only.

Technological innovation and clinical application of direct percutaneous computed tomography-guided enterostomy vs other enterostomy techniques.

BACKGROUND: To investigate the technological innovation, safety, operational advantages, and clinical application value of direct percutaneous computed tomography (CT)-guided enterostomy. METHODS: This retrospective study included patients who underwent direct percutaneous CT-guided enterostomy (n = 52), percutaneous endoscopic gastrojejunostomy (PEG-J, n = 39), or laparoscopic jejunostomy (n = 68) at Fujian Provincial Hospital between October 2019 and July 2021. The study indices included stoma surgery success rate, operation time, complication rate, and postoperative pain score. We concurrently analyzed the technological innovation of direct percutaneous CT-guided enterostomy and the changes in body mass index (BMI), serum albumin, prealbumin, and C-reactive protein (CRP) levels and patient-generated subjective global assessment (PG-SGA) scores after patients received 2 months of nutritional support. RESULTS: Direct percutaneous CT-guided enterostomy had a high success rate (100%) and low postoperative complication rate (5.77%). Compared to laparoscopic jejunostomy, direct percutaneous CT-guided enterostomy had a shorter operation time (36.92 ± 10.60) minutes, lower postoperative pain score (4.06 ± 2.02), lower anesthesia risk, and lower operative cost. The anesthetic risk for direct percutaneous CT-guided enterostomy is lower than that for PEG-J and has wider applications. After 2 months of postoperative nutritional support, patients had increased BMI, serum albumin level, and serum prealbumin level and decreased PG-SGA scores and CRP level with statistically significant differences compared to the preoperative state ( p < 0.05). CONCLUSION: Direct percutaneous CT-guided enterostomy is an important method of establishing an enteral nutrition therapy pathway, especially when endoscopic jejunostomy is not possible. It has a high safety profile and few complications, has unique advantages, and deserves further promotion of its application in clinical practice.