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.

Complex heterozygous mutations in hereditary spherocytosis: A case report.

BACKGROUND: The aim of this study was to investigate the complex heterozygous mutations of ANK1 and SPTA1 in the same individual and improve our understanding of hereditary spherocytosis (HS) in children. We also hope to promote the application of gene detection technology in children with HS, with the goals of identifying more related gene mutations, supporting the acquisition of improved molecular genetic information to further reveal the pathogenesis of HS in children, and providing important guidance for the diagnosis, treatment, and prevention of HS in children. CASE SUMMARY: A 1-year and 5-month-old patient presented jaundice during the neonatal period, mild anemia 8 months later, splenic enlargement at 1 year and 5 months, and brittle red blood cell permeability. Genetic testing was performed on the patient, their parents, and sister. Swiss Model software was used to predict the protein structure of complex heterozygous mutations in ANK1 and SPTA1. Genetic testing revealed that the patient harbored a new mutation in the ANK1 gene from the father and a mutation in the SPTA1 gene from the mother. Combined with the clinical symptoms of the children, it is suggested that the newly discovered complex heterozygous mutations of ANK1 and SPTA1 may be the cause, providing important guidance for revealing the pathogenesis, diagnosis, treatment, and promotion of gene detection technology in children with HS. CONCLUSION: This case involves an unreported complex heterozygous mutation of ANK1 and SPTA1, which provides a reference for exploring HS.

Enhanced Pressure Response of Edge-Deposited Graphene Nanomechanical Resonators.

Nanomechanical resonators made of suspended graphene exhibit high sensitivity to pressure changes. Nevertheless, the graphene resonator pressure performance is affected owing to the gas permeation problem between the graphene film and the substrate. Therefore, we prepared edge-deposited graphene resonators by focused ion beam (FIB) deposition of SiO2, and their gas leakage velocities and pressure-sensing ability were demonstrated. In this paper, we characterize the pressure-sensing response and gas leakage velocities of graphene membranes using an all-optical actuation system. The gas leakage velocities of graphene resonators with diameters of 10, 20, and 40 µm are reduced by 5.0 × 106, 2.0 × 107, and 8.1 × 107 atoms/s, respectively, which demonstrates that the edge deposition structure can reduce the gas leakage of the resonator. Furthermore, the pressure-sensing performance of three graphene resonators with different diameters was evaluated, and their average pressure sensitivities were calculated to be 3.4, 2.4, and 1.9 kHz/kPa, with the largest full-range hysteresis errors of 0.6, 0.7, and 1.0%, respectively. The temperature stabilities of the three sizes of resonators in the temperature range of 300-400 K are 0.016, 0.015, and 0.016%/K, and the maximum resonance frequency drift over 1 h is 0.0058, 0.0048, and 0.0112%, respectively. This work has great significance for the improvement of gas leakage velocity characterization of graphene membrane and graphene resonant pressure sensor performance optimization.

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.

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-.

Current application and future perspective of CRISPR/cas9 gene editing system mediated immune checkpoint for liver cancer treatment.

Liver cancer, which is well-known to us as one of human most prevalent malignancies across the globe, poses a significant risk to live condition and life safety of individuals in every region of the planet. It has been shown that immune checkpoint treatment may enhance survival benefits and make a significant contribution to patient prognosis, which makes it a promising and popular therapeutic option for treating liver cancer at the current time. However, there are only a very few numbers of patients who can benefit from the treatment and there also exist adverse events such as toxic effects and so on, which is still required further research and discussion. Fortunately, the clustered regularly interspaced short palindromic repeat/CRISPR-associated nuclease 9 (CRISPR/Cas9) provides a potential strategy for immunotherapy and immune checkpoint therapy of liver cancer. In this review, we focus on elucidating the fundamentals of the recently developed CRISPR/Cas9 technology as well as the present-day landscape of immune checkpoint treatment which pertains to liver cancer. What's more, we aim to explore the molecular mechanism of immune checkpoint treatment in liver cancer based on CRISPR/Cas9 technology. At last, its encouraging and powerful potential in the future application of the clinic is discussed, along with the issues that already exist and the difficulties that must be overcome. To sum it all up, our ultimate goal is to create a fresh knowledge that we can utilize this new CRISPR/Cas9 technology for the current popular immune checkpoint therapy to overcome the treatment issues of liver cancer. .

The application of nanomaterials in tumor therapy based on the regulation of mechanical properties.

Mechanical properties, as crucial physical properties, have a significant impact on the occurrence, development, and metastasis of tumors. Regulating the mechanical properties of tumors to enhance their sensitivity to radiotherapy and chemotherapy has become an important strategy in the field of cancer treatment. Over the past few decades, nanomaterials have made remarkable progress in cancer therapy, either based on their intrinsic properties or as drug delivery carriers. However, the investigation of nanomaterials of mechanical regulation in tumor therapy is currently in its initial stages. The mechanical properties of nanomaterials themselves, drug carrier targeting, and regulation of the mechanical environment of tumor tissue have far-reaching effects on the efficient uptake of drugs and clinical tumor treatment. Therefore, this review aims to comprehensively summarize the applications and research progress of nanomaterials in tumor therapy based on the regulation of mechanical properties, in order to provide strong support for further research and the development of treatment strategies in this field.

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.

Brain-targeted drug delivery by in vivo functionalized liposome with stable D-peptide ligand.

Brain-targeted drug delivery poses a great challenge due to the blood-brain barrier (BBB). In a previous study, we have developed a peptide-modified stealth liposome (SP-sLip) to enhance BBB penetration via the adsorption of apolipoproteins in plasma. SP is an 11-amino acid peptide derived from 25 to 35 of the Amyloid ß peptide (Aß1-42), which is the nature ligand of apolipoproteins. Although SP-sLip exhibited efficient brain targeting performance, self-aggregation and instability of storage limited its further application. In this study, we developed a D-peptide ligand according to the reverse sequence of SP with D-amino acids, known as DSP, to solve the problems. Notably, DSP exhibited a reduced tendency for self-aggregation and exceptional stability compared to the SP peptide. Furthermore, compared to SP-sLip, DSP-modified sLip (DSP-sLip) demonstrated enhanced stability (>2 weeks), prolonged blood circulation (AUC increased 44.4%), reduced liver and spleen accumulation (reduced by 2.23 times and 1.86 times) with comparable brain-targeting efficiency. Similar to SP-sLip, DSP-sLip selectively adsorbed apolipoprotein A1, E, and J in the blood to form functionalized protein corona, thus crossing BBB via apolipoprotein receptor-mediated transcytosis. These findings underscored the importance of ligand stability in the in vitro and in vivo performance of brain-targeted liposomes, therefore paving the way for the design and optimization of efficient and stable nanocarriers.

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.

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.

The effectiveness of live music intervention on psychological distress among adolescent and young adult patients undergoing hematopoietic stem cell transplantation.

OBJECTIVE: To explore the effects of live music to decrease psychological distress in adolescent and young adult (AYA) patients undergoing hematopoietic stem cell transplantation (HSCT). METHOD: A quasi-experimental study was conducted. Sixty patients undergoing HSCT were divided into two groups, receiving either 4 week of live music (n = 31) or standard care (n = 29). Psychological distress, anxiety, the severity of symptom clusters and symptom interference were measured. RESULTS: When compared with the immediately and 1 month after intervention, patients in LM intervention group had significantly lower psychological distress and anxiety level than wait-list group. AYA undergoing HSCT reported significantly milder general symptom cluster and neurological symptom cluster at T3 than at baseline. CONCLUSIONS: Live music intervention showed a positive effect on relieving psychological distress and anxiety in AYA patients undergoing HSCT. However, further researches are warranted to explore the effects of live music intervention on symptom cluster.

Interactions of traditional and biodegradable microplastics with neonicotinoid pesticides.

Neonicotinoid pesticides (NNPs) and microplastics (MPs) are two emerging contaminants in agricultural environment. However, the interaction between MPs (especially biodegradable plastics) and NNPs is currently unclear. Therefore, taking thiacloprid (THI) as an example of NNPs, this study explores the adsorption-desorption process and mechanism of NNPs on MPs (traditional and biodegradable plastics), and analyzed the main factors affecting the adsorption (pH, salinity and dissolved organic matter). In addition, by using diffusive gradients in thin-films device, this study assessed the impact of MPs on the bioavailability of NNPs in soil. The results showed that the maximum adsorption capacity of polyamide 6 (96.49 µg g-1) for THI was greater than that of poly (butylene adipate co-terephthalate) (88.78 µg g-1). Aging increased the adsorption amount of THI (5.53 %-15.8 %) due to the higher specific surface area and reduced contact angle of MPs, but the adsorption mechanism remained unchanged. The desorption amount of THI from MPs in simulated intestinal fluid is 1.30-1.36 times. The MPs in soil alter the distribution of THI in the soil, increasing the bioavailability of THI while inhibiting its degradation. The results highlighted the significance of examining the combined pollution caused by MPs and NNPs.

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.

Unilateral boundary time series forecasting.

Time series forecasting is an essential tool across numerous domains, yet traditional models often falter when faced with unilateral boundary conditions, where data is systematically overestimated or underestimated. This paper introduces a novel approach to the task of unilateral boundary time series forecasting. Our research bridges the gap in existing methods by proposing a specialized framework to accurately forecast within these skewed datasets. The cornerstone of our approach is the unilateral mean square error (UMSE), an asymmetric loss function that strategically addresses underestimation biases in training data, improving the precision of forecasts. We further enhance model performance through the implementation of a dual model structure that processes underestimated and accurately estimated data points separately, allowing for a nuanced analysis of the data trends. Additionally, feature reconstruction is employed to recapture obscured dynamics, ensuring a comprehensive understanding of the data. We demonstrate the effectiveness of our methods through extensive experimentation with LightGBM and GRU models across diverse datasets, showcasing superior accuracy and robustness in comparison to traditional models and existing methods. Our findings not only validate the efficacy of our approach but also reveal its model-independence and broad applicability. This work lays the groundwork for future research in this domain, opening new avenues for sophisticated analytical models in various industries where precise time series forecasting is crucial.