Differences in Genomic Alterations and Accumulations of Heavy Metals Between Advanced Non-small Cell Lung Cancer Patients with and without Bone Metastasis.

Purpose: Bone metastasis (BoM) has been closely associated with increased morbidity and poor survival outcomes in patients with non-small cell lung cancer (NSCLC). Given its significant implications, this study aimed to systematically compare the biological characteristics between advanced NSCLC patients with and without BoM. Methods: In this study, the genomic alterations from the tumor tissue DNA of 42 advanced NSCLC patients without BoM and 67 patients with BoM and were analyzed by a next-generation sequencing (NGS) panel. The serum concentrations of 18 heavy metals were detected by inductively coupled plasma emission spectrometry (ICP-MS). Results: A total of 157 somatic mutations across 18 mutated genes and 105 somatic mutations spanning 16 mutant genes were identified in 61 out of 67 (91.05%) patients with BoM and 37 of 42 (88.10%) patients without BoM, respectively. Among these mutated genes, NTRK1, FGFR1, ERBB4, NTRK3, and FGFR2 stood out exclusively in patients with BoM, whereas BRAF, GNAS, and AKT1 manifested solely in those without BoM. Moreover, both co-occurring sets of genes and mutually exclusive sets of genes in patients with BoM were different from those in patients without BoM. In addition, the serum concentrations of Cu and Sr in patients with BoM were significantly higher than in patients without BoM. One of our aims was to explore how these heavy metals associated with BoM interacted with other heavy metals, and significant positive correlations were observed between Cu and Co, between Cu and Cr, between Sr and Ba, and between Sr and Ni in patients with BoM. Given the significant impacts of molecular characteristics on patients' prognosis, we also observed a noteworthy negative correlation between EGFR mutations and Co, alongside a significant positive correlation between TP53 mutations and Cd. Conclusions: The genomic alterations, somatic interactions, key signaling pathways, functional biological information, and accumulations of serum heavy metals were markedly different between advanced NSCLC patients with and without BoM, and certain heavy metals (e.g., Cu, Sr) might have potentials to identify high-risk patients with BoM.

Study on the differences between Hoek-Brown parameters and equivalent Mohr-Coulomb parameters in the calculation slope critical acceleration and permanent displacement.

Mohr-Coulomb (MC) strength criterion has been widely used in many classical analytical expressions and numerical modeling due to its simple physical calculation, but the MC criterion is not suitable for describing the failure envelope of rock masses. In order to directly apply MC parameters to analytical expressions or numerical modeling in rock slope stability analysis, scholars established a criterion for converting Hoek-Brown (HB) parameters to equivalent MC parameters. However, the consistency of HB parameters and equivalent MC parameters in calculating critical acceleration of slope needs to be further explored and confirmed. Therefore, HB parameters are converted into equivalent MC parameters by considering the influence of slope angle (1# case and 2# case when slope angle is not considered and slope angle is considered respectively). Then, the lower-bound of finite element limit analysis is used for numerical modeling, and the results of calculating critical acceleration using HB parameters and equivalent MC parameters are compared, and the influence of related parameters on the calculation of critical acceleration is studied. Finally, the influence of different critical accelerations on the calculation of slope permanent displacement is further analyzed through numerical cases and engineering examples. The results show that: (1) In the 1# case, the critical acceleration obtained by the equivalent MC parameters are significantly larger than that obtained by the 2 #case and the HB parameters, and this difference becomes more obvious with the increase of slope angle. The critical acceleration obtained by the 2# case is very close to the HB parameters; (2) In the 1# case, slope height is inversely proportional to ΔAc (HB(Ac) - 1#(Ac)), and with the increase of slope height, ΔAc decreases, while in the 2# case, the difference of ΔAc (HB(Ac) - 2#(Ac)) is not significant; (3) In the 1# case, the sensitivity of the HB parameters to ΔAc is D > GSI > mi > σci, but in the 2# case, there is no sensitivity-related regularity; (4) The application of HB parameters and equivalent MC parameters in slope permanent displacement is studied through numerical cases and engineering examples, and the limitations of equivalent MC parameters in rock slope stability evaluation are revealed.

Thalamocortical functional connectivity and rapid antidepressant and antisuicidal effects of low-dose ketamine infusion among patients with treatment-resistant depression.

Previous studies have shown an association between the thalamocortical dysconnectivity and treatment-resistant depression (TRD). Whether a single subanesthetic dose of ketamine may change thalamocortical connectivity among patients with TRD is unclear. Whether these changes in thalamocortical connectivity is associated with the antidepressant and antisuicidal effects of ketamine treatment is also unclear. Two resting-state functional MRIs were collected in two clinical trials of 48 patients with TRD (clinical trial 1; 32 receiving ketamine, 16 receiving a normal saline placebo) and 48 patients with TRD and strong suicidal ideation (clinical trial 2; 24 receiving ketamine, 24 receiving midazolam), respectively. All participants underwent rs-fMRI before and 3 days after infusion. Seed-based functional connectivity (FC) was analyzed in the left/right thalamus. FCs between the bilateral thalamus and right middle frontal cortex (BA46) and between the left thalamus and left anterior paracingulate gyrus (BA8) increased among patients in the ketamine group in clinical trials 1 and 2, respectively. FCs between the right thalamus and bilateral frontal pole (BA9) and between the right thalamus and left rostral paracingulate gyrus (BA10) decreased among patients in the ketamine group in clinical trials 1 and 2, respectively. However, the associations between those FC changes and clinical symptom changes did not survive statistical significance after multiple comparison corrections. Whether ketamine-related changes in thalamocortical connectivity may be associated with ketamine's antidepressant and antisuicidal effects would need further investigation. Clinical trials registration: UMIN Clinical Trials Registry (UMIN-CTR): Registration number: UMIN000016985 and UMIN000033916.

Development and validation of a prediction model for mortality in critically ill COVID-19 patients.

Background: Early prediction of prognosis may help early treatment measures to reduce mortality in critically ill coronavirus disease (COVID-19) patients. The study aimed to develop a mortality prediction model for critically ill COVID-19 patients. Methods: This retrospective study analyzed the clinical data of critically ill COVID-19 patients in an intensive care unit between April and June 2022. Propensity matching scores were used to reduce the effect of confounding factors. A predictive model was built using logistic regression analysis and visualized using a nomogram. Calibration and receiver operating characteristic (ROC) curves were used to estimate the accuracy and predictive value of the model. Decision curve analysis (DCA) was used to examine the value of the model for clinical interventions. Results: In total, 137 critically ill COVID-19 patients were enrolled; 84 survived, and 53 died. Univariate and multivariate logistic regression analyses revealed that aspartate aminotransferase (AST), creatinine, and myoglobin levels were independent prognostic factors. We constructed logistic regression prediction models using the seven least absolute shrinkage and selection operator regression-selected variables (hematocrit, red blood cell distribution width-standard deviation, procalcitonin, AST, creatinine, potassium, and myoglobin; Model 1) and three independent factor variables (Model 2). The calibration curves suggested that the actual predictions of the two models were similar to the ideal predictions. The ROC curve indicated that both models had good predictive power, and Model 1 had better predictive power than Model 2. The DCA results suggested that the model intervention was beneficial to patients and patients benefited more from Model 1 than from Model 2. Conclusion: The predictive model constructed using characteristic variables screened using LASSO regression can accurately predict the prognosis of critically ill COVID-19 patients. This model can assist clinicians in implementing early interventions. External validation by prospective large-sample studies is required.

Assessing spatial heterogeneity of nutrient loads in a large shallow lake using a lattice Boltzmann water quality model.

Nutrient loads in lakes are spatially heterogeneous, but current spatial analysis method are mainly zonal, making them subjective and uncertain. This study proposes a high-resolution model for assessing spatial differences in nutrient loads based on the lattice Boltzmann method. The model was applied to Dongping Lake in China. Firstly, the contribution rates of four influencing factors, including water transfer, inflow, wind, and internal load, were calculated at different locations in the lake. Then, their proportionate contributions during different intervals to the whole lake area were calculated. Finally, the cumulative load could be calculated for any location within the lake. The validation showed that the model simulated hydrodynamics and water quality well, with relative errors between the simulated and measured water quality data smaller than 0.45. Wind increased the nutrient loads in most parts of the lake. The loads tended to accumulate in the east central area where high-frequency circulation patterns were present. Overall, the proposed water quality model based on the lattice Boltzmann method was able to simulate seven indexes. Therefore, this model represents a useful tool for thoroughly assessing nutrient load distributions in large shallow lakes and could help refine lake restoration management.

Hydrophobic Ion Barrier-Enabled Ultradurable Zn (002) Plane Orientation towards Long-Life Anode-Less Zn Batteries.

Gradual disability of Zn anode and high negative/positive electrode (N/P) ratio usually depreciate calendar life and energy density of aqueous Zn batteries (AZBs). Herein, within original Zn2+-free hydrated electrolytes, a steric hindrance/electric field shielding-driven "hydrophobic ion barrier" is engineered towards ultradurable (002) plane-exposed Zn stripping/plating to solve this issue. Guided by theoretical simulations, hydrophobic adiponitrile (ADN) is employed as a steric hindrance agent to ally with inert electric field shielding additive (Mn2+) for plane adsorption priority manipulation, thereby constructing the "hydrophobic ion barrier". This design robustly suppresses the (002) plane/dendrite growth, enabling ultradurable (002) plane-exposed dendrite-free Zn stripping/plating. Even being cycled in Zn‖Zn symmetric cell over 2150 h at 0.5 mA cm-2, the efficacy remains well-kept. Additionally, Zn‖Zn symmetric cells can be also stably cycled over 918 h at 1 mA cm-2, verifying uncompromised Zn stripping/plating kinetics. As-assembled anode-less Zn‖VOPO4·2H2O full cells with a low N/P ratio (2:1) show a high energy density of 75.2 Wh kg-1full electrode after 842 cycles at 1 A g-1, far surpassing counterparts with thick Zn anode and low cathode loading mass, featuring excellent practicality. This study opens a new avenue by robust "hydrophobic ion barrier" design to develop long-life anode-less Zn batteries.

Scavenging Radionuclide by Shapeable Porous Materials.

Nuclear energy is a competitive and environmentally friendly low-carbon energy source. It is seen as an important avenue for satisfying energy demands, responding to the energy crisis, and mitigating global climate change. However, much attention has been paid to achieving the effective treatment of radionuclide oxoanions produced in nuclear waste. Initially, advanced adsorbents were mainly available in powder form, which meant that additional purification processes were usually required for separation and recovery in industrial applications. Therefore, to meet the practical requirements of industrial applications, materials need to be molded and processed into forms such as beads, membranes, gels, and resins. Here, we summarize the fabrication of porous materials used for capturing typical radionuclide oxoanions, including UO22+, TcO4-, IO3-, SeO32-, and SeO4-.

Machine learning-based prediction of cadmium pollution in topsoil and identification of critical driving factors in a mining area.

Mining activities have resulted in a substantial accumulation of cadmium (Cd) in agricultural soils, particularly in southern China. Long-term Cd exposure can cause plant growth inhibition and various diseases. Rapid identification of the extent of soil Cd pollution and its driving factors are essential for soil management and risk assessment. However, traditional geostatistical methods are difficult to simulate the complex nonlinear relationships between soil Cd and potential features. In this study, sequential extraction and hotspot analyses indicated that Cd accumulation increased significantly near mining sites and exhibited high mobility. The concentration of Cd was estimated using three machine learning models based on 3169 topsoil samples, seven quantitative variables (soil pH, Fe, Ca, Mn, TOC, Al/Si and ba value) and three quantitative variables (soil parent rock, terrain and soil type). The random forest model achieved marginally better performance than the other models, with an R2 of 0.78. Importance analysis revealed that soil pH and Ca and Mn contents were the most significant factors affecting Cd accumulation and migration. Conversely, due to the essence of controlling Cd migration being soil property, soil type, terrain, and soil parent materials had little impact on the spatial distribution of soil Cd under the influence of mining activities. Our results provide a better understanding of the geochemical behavior of soil Cd in mining areas, which could be helpful for environmental management departments in controlling the diffusion of Cd pollution and capturing key targets for soil remediation.

In-depth metaproteomics analysis reveals the protein profile and metabolism characteristics in pork during refrigerated storage.

Alterations in microbiotas and endogenous enzymes have been implicated in meat deterioration. However, the factors that mediate the interactions between meat quality and microbiome profile were inadequately investigated. In this study, we collected pork samples throughout the refrigeration period and employed metaproteomics to characterize both the pork and microbial proteins. Our findings demonstrated that pork proteins associated with the catabolic process are upregulated during storage compared to the initial stage. Pseudomonas, Clostridium, Goodfellowiella, and Gonapodya contribute to the spoilage process. Notably, we observed an elevated abundance of microbial proteins related to glycolytic enzymes in refrigerated pork, identifying numerous proteins linked to biogenic amine production, thus highlighting their essential role in microbial decay. Further, we reveal that many of these microbial proteins from Pseudomonas are ribosomal proteins, promoting enzyme synthesis by enhancing transcription and translation. This study provides intrinsic insights into the underlying mechanisms by which microorganisms contribute to meat spoilage.

A systematic review and meta-analysis of canine enteric coronavirus prevalence in dogs of mainland China.

BACKGROUND: Canine enteric coronavirus (CECoV) is a prevalent infectious disease among dogs worldwide, yet its epidemiology in mainland China remains poorly understood. This systematic review and meta-analysis aimed to assess the prevalence of CECoV in mainland China and identify factors influencing its prevalence. METHODS: A comprehensive literature search was conducted across multiple databases for studies regarding CECoV epidemiology of China. PubMed, CNKI, Wanfang, and CQVIP were searched to obtain the studies. Eligible studies were selected based on predefined criteria, and data were extracted and synthesized. The quality the studies was assessed using the JBI assessment tool. Heterogeneity was checked using I2 test statistics followed by subgroup and sensitivity analysis. Subgroup analyses were performed to explore variations in CECoV prevalence by factors such as year, region, season, health status, social housing type, gender, age, and breed. Publication bias was assessed using a funnel plot and eggers test that was followed by trim and fill analysis. RESULTS: A total of 27 studies involving 21,034 samples were included in the meta-analysis. The overall pooled prevalence of CECoV in mainland China was estimated to be 0.30 (95% CI 0.24-0.37), indicating persistent circulation of the virus. Subgroup analyses revealed higher prevalence rates in younger dogs, multi-dog households, apparently healthy dogs, and certain regions such as southwest China. Seasonal variations were observed, with lower prevalence rates in summer. However, no significant differences in prevalence were found by gender. CONCLUSIONS: This study provides valuable insights into the epidemiology of CECoV in mainland China, highlighting the persistent circulation of the virus and identifying factors associated with higher prevalence rates. Continuous monitoring and surveillance efforts, along with research into accurate detection methods and preventive measures, are essential for the effective control of CECoV and mitigation of its potential impact on animal and human health.

Surface-Charge Tuned Polymeric Nanoemulsions for Carvacrol Delivery in Interkingdom Biofilms.

Biofilms, intricate microbial communities entrenched in extracellular polymeric substance (EPS) matrices, pose formidable challenges in infectious disease treatment, especially in the context of interkingdom biofilms prevalent in the oral environment. This study investigates the potential of carvacrol-loaded biodegradable nanoemulsions (NEs) with systematically varied surface charges─cationic guanidinium (GMT-NE) and anionic carboxylate (CMT-NE). Zeta potentials of +25 mV (GMT-NE) and -33 mV (CMT-NE) underscore successful nanoemulsion fabrication (∼250 nm). Fluorescent labeling and dynamic tracking across three dimensions expose GMT-NE's superior diffusion into oral biofilms, yielding a robust antimicrobial effect with 99.99% killing for both streptococcal and Candida species and marked reductions in bacterial cell viability compared to CMT-NE (∼4-log reduction). Oral mucosa tissue cultures affirm the biocompatibility of both NEs with no morphological or structural changes, showcasing their potential for combating intractable biofilm infections in oral environment. This study advances our understanding of NE surface charges and their interactions within interkingdom biofilms, providing insights crucial for addressing complex infections involving bacteria and fungi in the demanding oral context.

A comparative metabolomic analysis reveals the metabolic variations among cartilage of Kashin-Beck disease and osteoarthritis.

Aims: The metabolic variations between the cartilage of osteoarthritis (OA) and Kashin-Beck disease (KBD) remain largely unknown. Our study aimed to address this by conducting a comparative analysis of the metabolic profiles present in the cartilage of KBD and OA. Methods: Cartilage samples from patients with KBD (n = 10) and patients with OA (n = 10) were collected during total knee arthroplasty surgery. An untargeted metabolomics approach using liquid chromatography coupled with mass spectrometry (LC-MS) was conducted to investigate the metabolomics profiles of KBD and OA. LC-MS raw data files were converted into mzXML format and then processed by the XCMS, CAMERA, and metaX toolbox implemented with R software. The online Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate the metabolites by matching the exact molecular mass data of samples with those from the database. Results: A total of 807 ion features were identified for KBD and OA, including 577 positive (240 for upregulated and 337 for downregulated) and 230 negative (107 for upregulated and 123 for downregulated) ions. After annotation, LC-MS identified significant expressions of ten upregulated and eight downregulated second-level metabolites, and 183 upregulated and 162 downregulated first-level metabolites between KBD and OA. We identified differentially expressed second-level metabolites that are highly associated with cartilage damage, including dimethyl sulfoxide, uric acid, and betaine. These metabolites exist in sulphur metabolism, purine metabolism, and glycine, serine, and threonine metabolism. Conclusion: This comprehensive comparative analysis of metabolism in OA and KBD cartilage provides new evidence of differences in the pathogenetic mechanisms underlying cartilage damage in these two conditions.

Thermosensitive Polyhedral Oligomeric Silsesquioxane Hybrid Hydrogel Enhances the Antibacterial Efficiency of Erythromycin in Bacterial Keratitis.

Bacterial keratitis is a serious ocular infection that can impair vision or even cause blindness. The clinical use of antibiotics is limited due to their low bioavailability and drug resistance. Hence, there is a need to develop a novel drug delivery system for this infectious disease. In this study, erythromycin (EM) was encapsulated into a bifunctional polyhedral oligomeric silsesquioxane (BPOSS) with the backbone of the poly-PEG/PPG urethane (BPEP) hydrogel with the aim of improving the drug efficiency in treating bacterial keratitis. A comprehensive characterization of the BPEP hydrogel was performed, and its biocompatibility was assessed. Furthermore, we carried out the evaluation of the antimicrobial effect of the BPEP-EM hydrogel in S. aureus keratitis using in vivo mouse model. The BPEP hydrogel exhibited self-assembling and thermogelling properties, which assisted the drug loading of drug EM and improved its water solubility. Furthermore, the BPEP hydrogel could effectively bind with mucin on the ocular surface, thereby markedly prolonging the ocular residence time of EM. In vivo testing confirmed that the BPEP-EM hydrogel exerted a potent therapeutic action in the mouse model of bacterial keratitis. In addition, the hydrogel also exhibited an excellent biocompatibility. Our findings demonstrate that the BPEP-EM hydrogel showed a superior therapeutic effect in bacterial keratitis and demonstrated its potential as an ophthalmic formulation.

Generalizable Reconstruction for Accelerating MR Imaging via Federated Learning with Neural Architecture Search.

Heterogeneous data captured by different scanning devices and imaging protocols can affect the generalization performance of the deep learning magnetic resonance (MR) reconstruction model. While a centralized training model is effective in mitigating this problem, it raises concerns about privacy protection. Federated learning is a distributed training paradigm that can utilize multi-institutional data for collaborative training without sharing data. However, existing federated learning MR image reconstruction methods rely on models designed manually by experts, which are complex and computationally expensive, suffering from performance degradation when facing heterogeneous data distributions. In addition, these methods give inadequate consideration to fairness issues, namely ensuring that the model's training does not introduce bias towards any specific dataset's distribution. To this end, this paper proposes a generalizable federated neural architecture search framework for accelerating MR imaging (GAutoMRI). Specifically, automatic neural architecture search is investigated for effective and efficient neural network representation learning of MR images from different centers. Furthermore, we design a fairness adjustment approach that can enable the model to learn features fairly from inconsistent distributions of different devices and centers, and thus facilitate the model to generalize well to the unseen center. Extensive experiments show that our proposed GAutoMRI has better performances and generalization ability compared with seven state-of-the-art federated learning methods. Moreover, the GAutoMRI model is significantly more lightweight, making it an efficient choice for MR image reconstruction tasks. The code will be made available at https://github.com/ternencewu123/GAutoMRI.

LC-MS Characterization of N/O-Glycans of α- and ß-subunits of Chicken Ovomucin Separated by SDS-PAGE.

As the main active glycoprotein of egg white, the biological functions of chicken ovomucin α- and ß-subunit are closely related to the structure of glycans. However, the exact composition and structure of the subunit glycans are still unknown. We obtained highly pure chicken ovomucin α-subunit and ß-subunit protein bands by the strategy combined with two-step isoelectric precipitation and SDS-PAGE gel electrophoresis. The ammonia-catalyzed one-pot procedure was then used to release and capture α-and ß-subunit protein glycans with 1-phenyl- 3-Methyl-5-pyrazolone (PMP). The N/O-glycans of bis-PMP derivatives were purified and analyzed by LC-MS. More importantly, an effective dual modification was performed to accurately quantify neutral and sialylated O-glycans through methylamidation of sialic acid residues and simultaneously through carbonyl condensation reactions of reducing ends with PMP. We first showed that the α-subunit protein has only N-glycosylation modification, and the ß-subunit only O-glycosylation, a total of 22 N-glycans and 20 O-glycans were identified in the α- and ß-subunit, respectively. In addition, the complex N-glycan (47%) and the sialylated O-glycan (77%) are each major types of the above subunits. Such findings in this study provide a basis for studying the functional and biological activities of chicken ovomucin glycans.

Associations between maternal early pregnancy depression and longitudinal fetal growth.

BACKGROUND: The impacts of maternal depression during mid-to-late pregnancy on fetal growth have been extensively investigated. However, the association between maternal depression during early pregnancy and fetal intrauterine growth are less clear. METHODS: A prospective study comprised 23,465 eligible pregnant women and their offspring was conducted at a hospital-based center in Shanghai. Prenatal depression was assessed used using Patient Health Questionnaire (PHQ-9) before 14 gestational weeks. Differences in fetal growth trajectory of different maternal depressive statuses during three periods (16-23, 24-31, and 32-41 gestational weeks) were compared using a multilevel model with fractional polynomials. RESULTS: Women with depressive symptoms during early pregnancy had higher longitudinal fetal trajectories, with an estimated increase in fetal weight (ß = 0.33; 95 % CI, 0.06-0.61), compared to those without depressive symptoms. Increases in fetal abdominal circumference among women with depressive symptoms were observed before 23 gestational weeks. Offspring born to mothers with early pregnancy depression had a significantly higher birth weight of 14.13 g (95 % CI, 1.33-27.81 g) and an increased risk of severe large size for gestational age (adjusted odds ratio [aOR], 1.64; 95 % CI, 1.32-2.04) and macrosomia (aOR, 1.21; 95 % CI, 1.02-1.43). LIMITATIONS: Self-rated scale was used to assess depressive symptoms rather than clinical diagnosis. And Long-term effects of early pregnancy depression on offspring were not explored. CONCLUSIONS: The study revealed an association between maternal depression during early pregnancy and increased fetal biometrics, higher birth weight, and an elevated risk of severe large size for gestational age and macrosomia.