Adsorption Behaviors and Mechanism of Phenol and Catechol in Wastewater by Magnetic Graphene Oxides: A Comprehensive Study Based on Adsorption Experiments, Mathematical Models, and Molecular Simulations.

This study provides a comprehensive analysis of the adsorption behaviors and mechanisms of phenol and catechol on magnetic graphene oxide (MGO) nanocomposites based on adsorption experiments, mathematical models, and molecular simulations. Through systematic experiments, the influence of various parameters, including contact time, pH conditions, and ionic strength, on the adsorption efficacy was comprehensively evaluated. The optimal contact time for adsorption was identified as 60 min, with the observation that an increase in inorganic salt concentration adversely affected the MGOs' adsorption capacity for both phenol and catechol. Specifically, MGOs exhibited a superior adsorption performance under mildly acidic conditions. The adsorption isotherm was well represented by the Langmuir model, suggesting monolayer coverage and finite adsorption sites for both pollutants. In terms of adsorption kinetics, a pseudo-first-order kinetic model was the most suitable for describing phenol adsorption, while catechol adsorption conformed more closely to a pseudo-second-order model, indicating distinct adsorption processes for these two similar compounds. Furthermore, this research utilized quantum chemical calculations to decipher the interaction mechanisms at the molecular level. Such calculations provided both a visual representation and a quantitative analysis of the interactions, elucidating the underlying physical and chemical forces governing the adsorption phenomena. The findings could not only offer crucial insights for the treatment of coal industrial wastewater containing phenolic compounds with bridging macroscopic observations with microscopic theoretical explanations but also advance the understanding of material-pollutant interactions in aqueous environments.

Multi-omics analysis of the gut microbiome and metabolites associated with the psychoneurological symptom cluster in children with cancer receiving chemotherapy.

BACKGROUND: Children with cancer receiving chemotherapy commonly report a cluster of psychoneurological symptoms (PNS), including pain, fatigue, anxiety, depression, and cognitive dysfunction. The role of the gut microbiome and its functional metabolites in PNS is rarely studied among children with cancer. This study investigated the associations between the gut microbiome-metabolome pathways and PNS in children with cancer across chemotherapy as compared to healthy children. METHODS: A case-control study was conducted. Cancer cases were recruited from Children's Healthcare of Atlanta and healthy controls were recruited via flyers. Participants reported PNS using the Pediatric Patient-Reported Outcomes Measurement Information System. Data for cases were collected pre-cycle two chemotherapy (T0) and post-chemotherapy (T1), whereas data for healthy controls were collected once. Gut microbiome and its metabolites were measured using fecal specimens. Gut microbiome profiling was performed using 16S rRNA V4 sequencing, and metabolome was performed using an untargeted liquid chromatography-mass spectrometry approach. A multi-omics network integration program analyzed microbiome-metabolome pathways of PNS. RESULTS: Cases (n = 21) and controls (n = 14) had mean ages of 13.2 and 13.1 years. For cases at T0, PNS were significantly associated with microbial genera (e.g., Ruminococcus, Megasphaera, and Prevotella), which were linked with carnitine shuttle (p = 0.0003), fatty acid metabolism (p = 0.001) and activation (p = 0.001), and tryptophan metabolism (p = 0.008). Megasphaera, clustered with aspartate and asparagine metabolism (p = 0.034), carnitine shuttle (p = 0.002), and tryptophan (p = 0.019), was associated with PNS for cases at T1. Gut bacteria with potential probiotic functions, along with fatty acid metabolism, tryptophan, and carnitine shuttle, were more clustered in cancer cases than the control network and this linkage with PNS needs further studies. CONCLUSIONS: Using multi-omics approaches, this study indicated specific microbiome-metabolome pathways linked with PNS in children with cancer across chemotherapy. Due to limitations such as antibiotic use in cancer cases, these findings need to be further confirmed in a larger cohort.

The Development of a Series of Genomic DNA Reference Materials with Specific Copy Number Ratios for The Detection of Genetically Modified Maize DBN9936.

The genetically modified (GM) maize DBN9936 with a biosafety certificate will soon undergo commercial application. To monitor the safety of DBN9936 maize, three genomic DNA (gDNA) reference materials (RMs) (DBN9936a, DBN9936b, and DBN9936c) were prepared with nominal copy number ratios of 100%, 3%, and 1% for the DBN9936 event, respectively. DBN9936a was prepared from the leaf tissue gDNA of DBN9936 homozygotes, while DBN9936b and DBN9936c were prepared by the quantitative mixing of gDNA from the leaf tissues of DBN9936 homozygotes and non-GM counterparts. Validated DBN9936/zSSIIb duplex droplet digital PCR was demonstrated to be an accurate reference method for conducting homogeneity study, stability study, and collaborative characterization. The minimum intake for one measurement was determined to be 2 µL, and the gDNA RMs were stable during transport at 37 °C for 14 days and storage at -20 °C for 18 months. Each gDNA RM was certified for three property values: DBN9936 event copy number concentration, zSSIIb reference gene copy number concentration, and DBN9936/zSSIIb copy number ratio. The measurement uncertainty of the certified values took the uncertainty components related to possible inhomogeneity, instability, and characterization into account. This batch of gDNA RMs can be used for calibration and quality control when quantifying DBN9936 events.

Performance evaluation of a deep learning-based cascaded HRNet model for automatic measurement of X-ray imaging parameters of lumbar sagittal curvature.

PURPOSE: To develop a deep learning-based cascaded HRNet model, in order to automatically measure X-ray imaging parameters of lumbar sagittal curvature and to evaluate its prediction performance. METHODS: A total of 3730 lumbar lateral digital radiography (DR) images were collected from picture archiving and communication system (PACS). Among them, 3150 images were randomly selected as the training dataset and validation dataset, and 580 images as the test dataset. The landmarks of the lumbar curve index (LCI), lumbar lordosis angle (LLA), sacral slope (SS), lumbar lordosis index (LLI), and the posterior edge tangent angle of the vertebral body (PTA) were identified and marked. The measured results of landmarks on the test dataset were compared with the mean values of manual measurement as the reference standard. Percentage of correct key-points (PCK), intra-class correlation coefficient (ICC), Pearson correlation coefficient (r), mean absolute error (MAE), mean square error (MSE), root-mean-square error (RMSE), and Bland-Altman plot were used to evaluate the performance of the cascade HRNet model. RESULTS: The PCK of the cascaded HRNet model was 97.9-100% in the 3 mm distance threshold. The mean differences between the reference standard and the predicted values for LCI, LLA, SS, LLI, and PTA were 0.43 mm, 0.99°, 1.11°, 0.01 mm, and 0.23°, respectively. There were strong correlation and consistency of the five parameters between the cascaded HRNet model and manual measurements (ICC = 0.989-0.999, R = 0.991-0.999, MAE = 0.63-1.65, MSE = 0.61-4.06, RMSE = 0.78-2.01). CONCLUSION: The cascaded HRNet model based on deep learning algorithm could accurately identify the sagittal curvature-related landmarks on lateral lumbar DR images and automatically measure the relevant parameters, which is of great significance in clinical application.

Immunotherapy efficacy predictive tool for lung adenocarcinoma based on neural network.

Background: Remarkably, the anti-cancer efficacy of immunotherapy in lung adenocarcinoma (LUAD) has been demonstrated. However, predicting the beneficiaries of this expensive treatment is still a challenge. Materials and methods: A group of patients (N = 250) diagnosed with LUAD and receiving immunotherapy were retrospectively studied. They were randomly divided into a training dataset (80%) and a test dataset (20%). The training dataset was utilized to train neural network models to predict patients' objective response rate (ORR), disease control rate (DCR), responders (progression-free survival time > 6 months), and overall survival (OS) possibility, which were validated by both the training and test datasets and packaged into a tool later. Results: In the training dataset, the tool scored 0.9016 area under the receiver operating characteristic (AUC) curve on ORR judgment, 0.8570 on DCR, and 0.8395 on responder prediction. In the test dataset, the tool scored 0.8173 AUC on ORR, 0.8244 on DCR, and 0.8214 on responder determination. As for OS prediction, the tool scored 0.6627 AUC in the training dataset and 0.6357 in the test dataset. Conclusions: This immunotherapy efficacy predictive tool for LUAD patients based on neural networks could predict their ORR, DCR, and responder well.

Continuous real-time monitoring of carbon dioxide emitted from human skin by quartz-enhanced photoacoustic spectroscopy.

In this study, a skin gas detection system based on quartz enhanced photoacoustic spectroscopy (QEPAS) with a constant temperature collection chamber and an automatic frequency adjustment function was used to collect and monitor carbon dioxide (CO2) emissions from human skin. The detection element of the system is an on-beam structure assembled by a 30.72 kHz quartz tuning fork (QTF). A laser with a wavelength of 4991.26 cm-1 is emitted (with a wavelength adjustment range of 10 cm-1) to excite the QTF. When the integration time is 365 s, the system can achieve a minimum detection limit (MDL) of 2.6 ppmv. The sensitivity of the system is 636.9 ppmv/V. The gas detection system is used to monitor the concentration of CO2 emissions from different parts of the skin and the same part covered by different cosmetics. The CO2 emission rate is defined as the ratio of the skin gas monitoring time of 25 min to the CO2 concentration variable in the gas chamber (volume of 8 mL). The results were collected from three healthy volunteers. Among the six different parts, the cheeks emitted the fastest rate (the average rate was 365.5 ppmv/min) of CO2, and the thighs emitted the slowest rate (the average rate was 56.4 ppmv/min) of CO2. Comparing the experimental results of the six sites at different times, the order of the CO2 emission rate is identical for all six sites. In the experiments with the three cosmetic products (experimental site: forearm), comparing the CO2 emission rate from clean skin with the CO2 emission rate from cosmetic-covered skin shows that sunscreen is the most breathable, followed by barrier cream, and foundation is the least breathable.

CRISPR/Cas12a-mediated Enzymatic recombinase amplification for rapid visual quantitative authentication of halal food.

Economically motivated adulteration (EMA) has become a concern in food safety. We propose a CRISPR/Cas12a Mediated Enzymatic Recombinase Amplification detection system (CAMERA) that integrates Enzymatic Recombinase Amplification (ERA) and Cas12a cleavage to detect halal food adulteration. We designed and screened crRNA targeting CLEC, a porcine-specific nuclear single-copy gene, and optimized the reagent concentrations and incubation times for the ERA and Cas12a cleavage steps. CAMERA was highly specific for pork ingredients detection. The DNA concentration and fluorescence signal intensity relationship was linear at DNA concentrations of 20-0.032 ng/µL. CAMERA detected as few as two CLEC copies and quantified samples with porcine DNA content as low as 5% within 25 min. The system could be operated in a miniaturized working mode that requires no technical expertise or professional equipment, making CAMERA a valuable tool in resource-limited areas for the qualitative and quantitative detection of pork ingredients in halal food.

BPOZ-2 is a negative regulator of the NLPR3 inflammasome contributing to SARS-CoV-2-induced hyperinflammation.

Introduction: Inflammation play important roles in the initiation and progression of acute lung injury (ALI), acute respiratory distress syndrome (ARDS), septic shock, clotting dysfunction, or even death associated with SARS-CoV-2 infection. However, the pathogenic mechanisms underlying SARS-CoV-2-induced hyperinflammation are still largely unknown. Methods: The animal model of septic shock and ALI was established after LPS intraperitoneal injection or intratracheal instillation. Bone marrow-derived macrophages (BMDMs) from WT and BPOZ-2 KO mouse strains were harvested from the femurs and tibias of mice. Immunohistology staining, ELISA assay, coimmunoprecipitation, and immunoblot analysis were used to detect the histopathological changes of lung tissues and the expression of inflammatory factors and protein interaction. Results and conclusions: We show a distinct mechanism by which the SARS-CoV-2 N (SARS-2-N) protein targets Bood POZ-containing gene type 2 (BPOZ-2), a scaffold protein for the E3 ubiquitin ligase Cullin 3 that we identified as a negative regulator of inflammatory responses, to promote NLRP3 inflammasome activation. We first demonstrated that BPOZ-2 knockout (BPOZ-2 KO) mice were more susceptible to lipopolysaccharide (LPS)-induced septic shock and ALI and showed increased serum IL-1ß levels. In addition, BMDMs isolated from BPOZ-2 KO mice showed increased IL-1ß production in response to NLRP3 stimuli. Mechanistically, BPOZ-2 interacted with NLRP3 and mediated its degradation by recruiting Cullin 3. In particular, the expression of BPOZ-2 was significantly reduced in lung tissues from mice infected with SARS-CoV-2 and in cells overexpressing SARS-2-N. Importantly, proinflammatory responses triggered by the SARS-2-N were significantly blocked by BPOZ-2 reintroduction. Thus, we concluded that BPOZ-2 is a negative regulator of the NLPR3 inflammasome that likely contributes to SARS-CoV-2-induced hyperinflammation.

On-Demand Portable Paper-Based Electrospray Ionization Mass Spectrometry for High-Sensitivity Analysis of Complex Samples.

Paper spray ionization has been demonstrated to be the most promising substrate-based source, but this technique suffers from the low desorption efficiency of target compounds and poor portability. In the current study, we describe a portable paper-based electrospray ionization (PPESI) in which a piece of triangle paper and adsorbent are packed sequentially into a modified disposable micropipette tip. This source not only captures the feature of paper spray and adsorbent for highly efficient suppression of sample matrixes for target compound analysis but also takes advantage of a micropipette tip to prevent spray solvent from rapid evaporation. The performance of developed PPESI depends on the type and amount of packed adsorbent, paper substrate, and spray solvent and applied voltage. Moreover, by contrast to other related sources, the analytical sensitivity and the spray duration of PPESI in tandem with MS have been improved by factors of 2.8-32.3 and 2.0-13.3, respectively. Based on its high accuracy (>96%) and precision (less than 3% relative standard deviation), the PPESI coupled to a mass spectrometer has been used to determine diverse therapeutic drugs and pesticides in complex biological (e.g., whole blood, serum, and urine) and food (e.g., milk and orange juice) matrixes, and the limits of detection and quantification were 2-4 pg mL-1 and 7-13 pg mL-1, respectively. Taking the portability, high sensitivity, and repeatability, the technique may be a promising alternative for complex sample analysis.

A visual CRISPR/dCas9-mediated enzyme-linked immunosorbent assay for nucleic acid detection with single-base specificity.

Specific and economical nucleic acid detection is crucial for molecular diagnoses in resource-limited settings. Various facile readout approaches have been developed for nucleic acid detection, but they have limited specificity. Herein, nuclease-dead Cas9 (dCas9)/sgRNA was used as an excellent DNA recognition probe system to develop a visual clustered regularly interspaced short palindromic repeats (CRISPR)/dCas9-mediated enzyme-linked immunosorbent assay (ELISA) for specific and sensitive detection of cauliflwer mosaic virus 35s (CaMV35S) promoter in genetically modified (GM) crops. In this work, the CaMV35S promoter was amplified with biotinylated primers, and then precisely bound with dCas9 in the presence of sgRNA. The formed complex was captured by antibody-coated microplate and bound to a streptavidin-labeled horseradish peroxidase probe for the visual detection. Under the optimal conditions, dCas9-ELISA could detect CaMV35s promoter as low as 12.5 copies µL-1. Moreover, the proposed method was capable to distinguish the target sequence with single-base specificity. Coupled with one-step extraction and recombinase polymerase amplification, dCas9-ELISA can identify actual GM rice seeds within 1.5 h from sampling to results without expensive equipment and technical expertise. Therefore, the proposed method offers a specific, sensitive, rapid and cost-effective detection platform for molecular diagnoses.

Assessing the efficacy of immunotherapy in lung squamous carcinoma using artificial intelligence neural network.

Background: At present, immunotherapy is a very promising treatment method for lung cancer patients, while the factors affecting response are still controversial. It is crucial to predict the efficacy of lung squamous carcinoma patients who received immunotherapy. Methods: In our retrospective study, we enrolled lung squamous carcinoma patients who received immunotherapy at Beijing Chest Hospital from January 2017 to November 2021. All patients were grouped into two cohorts randomly, the training cohort (80% of the total) and the test cohort (20% of the total). The training cohort was used to build neural network models to assess the efficacy and outcome of immunotherapy in lung squamous carcinoma based on clinical information. The main outcome was the disease control rate (DCR), and then the secondary outcomes were objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). Results: A total of 289 patients were included in this study. The DCR model had area under the receiver operating characteristic curve (AUC) value of 0.9526 (95%CI, 0.9088-0.9879) in internal validation and 0.9491 (95%CI, 0.8704-1.0000) in external validation. The ORR model had AUC of 0.8030 (95%CI, 0.7437-0.8545) in internal validation and 0.7040 (95%CI, 0.5457-0.8379) in external validation. The PFS model had AUC of 0.8531 (95%CI, 0.8024-0.8975) in internal validation and 0.7602 (95%CI, 0.6236-0.8733) in external validation. The OS model had AUC of 0.8006 (95%CI, 0.7995-0.8017) in internal validation and 0.7382 (95%CI, 0.7366-0.7398) in external validation. Conclusions: The neural network models show benefits in the efficacy evaluation of immunotherapy to lung squamous carcinoma patients, especially the DCR and ORR models. In our retrospective study, we found that neoadjuvant and adjuvant immunotherapy may bring greater efficacy benefits to patients.

Gray matter reduction in bilateral insula mediating adverse psychiatric effects of body mass index in schizophrenia.

BACKGROUND: Both schizophrenia (SZ) and overweight/obesity (OWB) have shown some structural alterations in similar brain regions. As higher body mass index (BMI) often contributes to worse psychiatric outcomes in SZ, this study was designed to examine the effects of OWB on gray matter volume (GMV) in patients with SZ. METHODS: Two hundred fifty subjects were included and stratified into four groups (n = 69, SZ patients with OWB, SZ-OWB; n = 74, SZ patients with normal weight, SZ-NW; n = 54, healthy controls with OWB, HC-OWB; and n = 53, HC with NW, HC-NW). All participants were scanned using high-resolution T1-weighted sequence. The whole-brain voxel-based morphometry was applied to examine the GMV alterations, and a 2 × 2 full factorial analysis of variance was performed to identify the main effects of diagnosis (SZ vs HC), BMI (NW vs OWB) factors, and their interactions. Further, the post hoc analysis was conducted to compare the pairwise differences in GMV alterations. RESULTS: The main effects of diagnosis were located in right hippocampus, bilateral insula, rectus, median cingulate/paracingulate gyri and thalamus (SZ < HC); while the main effects of BMI were displayed in right amygdala, left hippocampus, bilateral insula, left lingual gyrus, and right superior temporal gyrus (OWB < NW). There were no significant diagnosis-by-BMI interaction effects in the present study, but the results showed that both SZ and OWB were additively associated with lower GMV in bilateral insula. Moreover, mediation analyses revealed the indirect effect of BMI on negative symptom via GMV reduction in bilateral insula. CONCLUSION: This study further supports that higher BMI is associated with lower GMV, which may increase the risk of unfavourable disease courses in SZ.

Qualitative and Quantitative Real-Time PCR Methods for Assessing False-Positive Rates in Genetically Modified Organisms Based on the Microbial-Infection-Linked HPT Gene.

The hygromycin phosphotransferase (HPT) gene as a selective marker is normally used in screening tests as a first step in detecting and quantifying genetically modified organisms (GMOs) in seeds, food, and feed materials. Nevertheless, if researchers only focus on the HPT gene, it is difficult to distinguish genetically modified (GM) crops from microbial infection, leading to miscalculation of the rate of GM materials in a given sample set. Here, we cloned the 7259 bp sequence carrying the HPT gene from soybean sprouts using the genome walking strategy. BLAST analysis revealed that this sequence was derived from plasmids naturally occurring in microorganisms, such as Escherichia coli, Klebsiella pneumoniae or Salmonella sp. Using the reconstructed plasmid pFP-hpt, qualitative PCR and quantitative real-time PCR (qPCR) methods were established, and 261 bp and 156 bp products were produced. The specificity of these assays was assessed against related pFP-hpt plasmids, plant species with important agronomic traits, and GM crops containing the HPT gene. No unexpected results were observed between samples using these qualitative PCR and qPCR methods. The sensitivity of this qualitative PCR assay was determined at 20 copies, while the limit of detection (LOD) and limit of quantification (LOQ) of qPCR were both 5 copies per reaction. Our in-house validation indicated that the amplification efficiency, linearity, and repeatability of this qPCR assay were in line with performance requirements. Furthermore, a qualitative and quantitative duplex PCR showed high reliability for the simultaneous detection of the HPT gene in a plant sample and environmental micro-organisms harboring the HPT gene in one PCR reaction. These qualitative PCR and qPCR assays were able to differentiate between plants infected with E. coli harboring the HPT gene from GM plants, indicating that these two methods are broadly applicable for routine GMO testing.

Amplification of fluorescence polarization signal based on specific recognition of aptamers combined with quantum quenching effect for ultrasensitive and simple detection of PCB-77.

Here, we report a novel aptasensor based on decahedral silver nanoparticles (Ag10NPs) enhanced fluorescence polarization (FP) for detecting PCB-77. Using aptamer modified Ag10NPs hybridized with DNA sequence labeled fluorescent group as an analytical probe, polychlorinated biphenyls (PCB-77) could be detected with high sensitivity and selectivity. The linear range of determination was 0.02 ng/L to 390 ng/L and the limit of detection was 5 pg/L. In addition, through the optimization of the experiment condition and signal probe DNA (pDNA), we found that the maximum FP signal could be generated when the distance between fluorescein and the surface of Ag10NPs was 3 nm. When the aptamer was immobilized on the surface of Ag10NPs could be strengthened the anti-interference performance of aptamer nanoprobe and further improved the detection ability. At the same time, we also compared the detection performance of the traditional FP signal enhancer streptavidin (SA) analysis system. The fluorescence polarization aptasensor could detect PCB-77 samples efficiently in complex environmental water, which shows a good application prospect.

A label-free electrochemical impedimetric DNA biosensor for genetically modified soybean detection based on gold carbon dots.

A label-free electrochemical impedimetric biosensor was constructed based on gold carbon dots (GCDs) modified screen-printed carbon electrode for the detection of genetic modified (GM) soybean. The structure and property of GCDs were investigated. The GCDs can directly bind to single-stranded DNA probes through Au-thiol interaction and boost electric conductivity for the DNA sensor construction. The quantification of target DNA was monitored by the change of electron-transfer resistance (Ret) upon the DNA hybridization on sensor surface. Under the optimal conditions, the Ret response (vs. Ag reference electrode) increased with the logarithm of target DNA concentrations in a wide linear range of 1.0 × 10-7 - 1.0 × 10-13 M with a detection limit of 3.1 × 10-14 M (S/N = 3). It was also demonstrated that the proposed DNA sensor possessed high specificity for discriminating target DNA from mismatched sequences. Moreover, the developed biosensor was applied to detect SHZD32-1 in actual samples, and the results showed a good consistency with those obtained from the gel electrophoresis method. Compared with the previous reports for DNA detection, the label-free biosensor showed a comparatively simple platform due to elimination of complicated DNA labeling. Therefore, the proposed method showed great potential to be an alternative device for simple, sensitive, specific, and portable DNA sensor.

MiR-139-5p/ENAH Affects Progression of Hepatocellular Carcinoma Cells.

This study aims to investigate the specific mechanism of miR-139-5p regulating hepatocellular carcinoma (HCC). Bioinformatic approaches was utilized to observe miR-139-5p level in HCC and unearth its target mRNA. Next, miR-139-5p and enabled homolog (ENAH) levels in HCC cell lines and normal liver cell line were evaluated with qRT-PCR. ENAH protein level was assessed by Western blot. The cell viability, migratory and invasive capacities of HepG2 cells was observed by cell functional assays. The binding of these two genes was proved through dual-luciferase method. Xenograft nude mouse model was prepared to identify the role of miR-139-5p in vivo. Poorly expressed miR-139-5p in HCC hindered the phenotypes of cancer cells. ENAH was at high level in HCC and it is a downstream target of miR-139-5p. Additionally, ENAH could reverse the suppressive impacts of miR-139-5p on HCC cell behaviors. Likewise, miR-139-5p was determined to perform tumor-suppressing function in vivo. MiR-139-5p hampered HCC cell processes by mediating ENAH, and miR-139-5p/ENAH is hopefully to be the possible target for HCC patients.

Synthesis of thickness-controllable polydopamine modified halloysite nanotubes (HNTs@PDA) for uranium (VI) removal.

Halloysite nanotubes (HNTs) are considered structurally promising adsorption materials, but their application is limited due to their poor native adsorption properties. Improving the adsorption capacity of HNTs for radioactive U(VI) is of great significance. By controlling the mass ratio of HNTs and dopamine (DA), composite adsorbents (HNTs@PDA) with different polydopamine (PDA) layer thicknesses were synthesized. Characterization of HNTs@PDA demonstrated that the original structure of the HNTs was maintained. Adsorption experiments verified that the adsorption capacity of HNTs@PDA for U(VI) was significantly improved. The effects of solution pH, temperature, and coexisting ions on the adsorption process were investigated. The removal efficiency was observed to be 75% after five repeated uses. The adsorption mechanism of U(VI) by HNTs@PDA can be explained by considering electrostatic interactions and the complexation of C-O, -NH- and C-N/CN in the PDA layer. This study provides some basic information for the application of HNTs for U(VI) removal.

Application of ddPCR in detection of the status and abundance of EGFR T790M mutation in the plasma samples of non-small cell lung cancer patients.

Background/Objective: The third-generation epidermal growth factor receptor (EGFR) -tyrosine kinase inhibitor (TKIs), such as osimertinib, designed for targeting the acquired drug-resistant mutation of EGFR T790M, was approved as the first-line therapy for advanced EGFR-mutated non-small cell lung cancer (NSCLC). Thus, detection of the EGFR T790M mutation for NSCLC is crucial. However, tissue samples are often difficult to obtain, especially in patients at advanced stages. This study assessed the performances of droplet digital polymerase chain reaction (ddPCR) and next-generation sequencing (NGS) in detecting EGFR T790M status and abundance in the plasma ctDNA samples of patients with NSCLC. We also explored the association between T790M status and abundance and the response to third-generation EGFR-TKIs. Methods: A total of 201 plasma samples with matched tissues, 821 plasma samples, and 56 patients who received third-generation EGFR-TKIs with response evaluation were included in this study. ddPCR and NGS were used to detect the mutation status and abundance of T790M in the tissues and/or blood samples. Results: The results showed that the sensitivity and the specificity of EGFR T790M mutation status detected by ddPCR in plasma samples were 81.82% and 91.85%, respectively, compared with the tissue samples, with a consistency coefficient of 0.740. Among the 821 plasma samples, the positive rates of EGFR T790M detected by ddPCR and NGS were 34.2% (281/821) and 22.5% (185/821), respectively. With NGS results as the reference, the sensitivity and the specificity of ddPCR were 100% and 84.91%, respectively, and the consistency coefficient of the two methods was 0.717. In addition, we found that a higher EGFR T790M abundance was linked to a higher treatment response rate to the third-generation EGFR-TKIs regardless of the classification of the median value of 0.43% (P = 0.016) or average value of 3.16% (P = 0.010). Conclusion: Taking these data together, this study reveals that ddPCR is an alternatively potent method for the detection of EGFR T790M in the plasma samples of NSCLC patients.

Development and Validation of a Nomogram for Preoperative Prediction of Localization of Neonatal Gastrointestinal Perforation.

Background: Information regarding the localization of gastrointestinal perforation is crucial for the following surgical procedure. This study was to determine the key indicators and develop a prediction model for the localization in neonates with gastrointestinal perforation. Methods: A nomogram to predict the location of neonatal gastrointestinal perforation was developed using a cohort of patients who underwent surgery between July 2009 and May 2021. Baseline variables were analyzed using logistics regression and nomogram developed using significant predictors. The predictive performance of the nomogram was assessed by the concordance index (C-index), calibration curve, and area under the receiver operating characteristic (ROC) curve (AUC). The nomogram was further validated in an integrated external cohort. Results: We investigated the data of 201 patients, of which 65 (32.3%) were confirmed with upper gastrointestinal perforation by surgery. Multivariate logistic regression analysis identified the following as independent predictors: preterm [OR: 5.014 (1.492-18.922)], time of onset [OR: 0.705 (0.582-0.829)], preoperative hemoglobin [OR:1.017 (1.001-1.033)], bloody stool: No [OR: 4.860 (1.270-23.588)], shock [OR: 5.790 (1.683-22.455)] and sepsis: No [OR 3.044 (1.124-8.581)]. Furthermore, the nomogram was effective in predicting the perforation site, with an AUC of 0.876 [95% confidence interval (CI): 0.830-0.923]. Internal validation showed that the average AUC was 0.861. Additionally, the model achieved satisfactory discrimination (AUC, 0.900; 95% CI, 0.826-0.974) and calibration (Hosmer-Lemeshow test, P = 0.4802) in external validation. Conclusions: The nomogram based on the six factors revealed good discrimination and calibration, suggesting good clinical utility. The nomogram could help surgeons predict the location of gastrointestinal perforation before surgery to make a surgical plan.