Search

Abstract Background To construct a CT-based radiomics nomogram, enabling the estimation of overall survival (OS) in small cell lung cancer (SCLC) patients and facilitating the identification of prophylactic cranial irradiation (PCI) beneficiaries through risk stratification using the radiomics score (RS). Methods A retrospective recruitment of 375 patients with pathologically confirmed SCLC was conducted across three medical centers, followed by their division into different cohorts. To generate the RS, a series of analyses were performed, including Pearson correlation analysis, univariate Cox analysis, and least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Subsequently, patients were stratified into either the low RS or high RS group, determined by identifying the optimal RS cutoff value. Subsequently, a radiomics nomogram was constructed using the RS, followed by assessments of its discrimination, calibration, clinical utility and reclassification. Moreover, we evaluated the potential benefits of PCI following stratification by RS. Results For the internal and external validation cohorts, the radiomics nomogram (concordance index [C-index]: 0.770, 0.763) outperformed clinical nomogram (C-index: 0.625, 0.570) in predicting OS. Besides, patients with high RS had survival benefit from PCI in both the limited and extensive stage (hazard ratio [HR]: 0.304, 95% confidence interval [CI]: 0.087–1.065, P = 0.003; HR: 0.481, 95% CI: 0.270–0.860, P = 0.019, respectively), while no significant association were observed in patients with low RS. Conclusion A radiomics nomogram based on CT shows potential in predicting OS for individuals with SCLC. The RS could assist in tailoring treatment plans to identify patients likely to benefit from PCI.

Abstract The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has evolved many high‐risk variants, resulting in repeated COVID‐19 waves over the past years. Therefore, accurate early warning of high‐risk variants is vital for epidemic prevention and control. However, detecting high‐risk variants through experimental and epidemiological research is time‐consuming and often lags behind the emergence and spread of these variants. In this study, HiRisk‐Detector a machine learning algorithm based on haplotype network, is developed for computationally early detecting high‐risk SARS‐CoV‐2 variants. Leveraging over 7.6 million high‐quality and complete SARS‐CoV‐2 genomes and metadata, the effectiveness, robustness, and generalizability of HiRisk‐Detector are validated. First, HiRisk‐Detector is evaluated on actual empirical data, successfully detecting all 13 high‐risk variants, preceding World Health Organization announcements by 27 days on average. Second, its robustness is tested by reducing sequencing intensity to one‐fourth, noting only a minimal delay of 3.8 days, demonstrating its effectiveness. Third, HiRisk‐Detector is applied to detect risks among SARS‐CoV‐2 Omicron variant sub‐lineages, confirming its broad applicability and high ROC‐AUC and PR‐AUC performance. Overall, HiRisk‐Detector features powerful capacity for early detection of high‐risk variants, bearing great utility for any public emergency caused by infectious diseases or viruses.

Further development of direct-acting antiviral agents against human SARS-CoV-2 infections remains a public health priority. Here, we report that an antisense peptide-conjugated morpholino oligomer (PPMO) named 5′END-2, targeting a highly conserved sequence in the 5′ UTR of SARS-CoV-2 genomic RNA, potently suppressed SARS-CoV-2 growth in vitro and in vivo. In HeLa-ACE 2 cells, 5′END-2 produced IC50 values of between 40 nM and 1.15 μM in challenges using six genetically disparate strains of SARS-CoV-2, including JN.1. In vivo, using K18-hACE2 mice and the WA-1/2020 virus isolate, two doses of 5′END-2 at 10 mg/kg, administered intranasally on the day before and the day after infection, produced approximately 1.4 log10 virus titer reduction in lung tissue at 3 days post-infection. Under a similar dosing schedule, intratracheal administration of 1.0–2.0 mg/kg 5′END-2 produced over 3.5 log10 virus growth suppression in mouse lungs. Electrophoretic mobility shift assays characterized specific binding of 5′END-2 to its complementary target RNA. Furthermore, using reporter constructs containing SARS-CoV-2 5′ UTR leader sequence, in an in-cell system, we observed that 5′END-2 could interfere with translation in a sequence-specific manner. The results demonstrate that direct pulmonary delivery of 5′END-2 PPMO is a promising antiviral strategy against SARS-CoV-2 infections and warrants further development.

In promoting the large-scale application of Hydrogen Storage Power Stations (HSPS), challenges are encountered. These challenges include economic inefficiencies during peak shaving participation and low operational efficiency caused by improper power distribution among units. To address these issues, the revenue generated from HSPS participation in peak shaving is examined. A model is established to analyze the economic benefits associated with this participation. An operational strategy is proposed to optimize the role of HSPS in peak shaving. Additionally, the necessary power instructions are derived to ensure the effective operation of these stations. The influence of power output and temperature on the charging and discharging efficiency of storage units is also investigated. The optimal model is constructed to outline the efficiency of hydrogen storage units, and the power allocation strategy for multiple storage units is proposed to maximize system efficiency. The peak shifting capability, operational revenue, and overall operational efficiency of HSPS are improved by the strategy presented in this paper. The degradation impact on the lifespan of the storage units is minimized. The effectiveness of the proposed strategy is validated through simulation analysis. Comparisons with alternative scenarios show that significant advantages are provided by our approach in increasing revenue from peak shifting. Overall peak shifting effectiveness, operational efficiency of storage units, and the operational lifespan of these units are improved.

Drug conjugates are obtained from tumor-located vectors connected to cytotoxic agents via linkers, which are designed to deliver hyper-toxic payloads directly to targeted cancer cells. These drug conjugates include antibody-drug conjugates (ADCs), peptide-drug conjugates (PDCs), small molecule-drug conjugates (SMDCs), nucleic acid aptamer-drug conjugates (ApDCs), and virus-like drug conjugate (VDCs), which show great therapeutic value in the clinic. Drug conjugates consist of a targeting carrier, a linker, and a payload. Payloads are key therapy components. Cytotoxic molecules and their derivatives derived from natural products are commonly used in the payload portion of conjugates. The ideal payload should have sufficient toxicity, stability, coupling sites, and the ability to be released under specific conditions to kill tumor cells. Microtubule protein inhibitors, DNA damage agents, and RNA inhibitors are common cytotoxic molecules. Among these conjugates, cytotoxic molecules of natural origin are summarized based on their mechanism of action, conformational relationships, and the discovery of new derivatives. This paper also mentions some cytotoxic molecules that have the potential to be payloads. It also summarizes the latest technologies and novel conjugates developed in recent years to overcome the shortcomings of ADCs, PDCs, SMDCs, ApDCs, and VDCs. In addition, this paper summarizes the clinical trials conducted on conjugates of these cytotoxic molecules over the last five years. It provides a reference for designing and developing safer and more efficient conjugates.

Highlights The boosted heterogeneous interfaces in titanium nitride (TiN) nanotube/polydimethylsiloxane (PDMS) composite contributed to strong polarization loss relaxation ability. The TiN nanotubes/PDMS composite possessed both good impedance matching behavior and strong dielectric loss ability in wide temperature spectrum. The TiN nanotubes/PDMS composite exhibited excellent EMWA performances (effective absorption bandwidth value of 3.23 GHz and minimum reflection loss value of − 44.15 dB) at the varied temperature from 298 to 573 K.

ObjectiveThe purpose of this study is to investigate potential associations between osteopenia, osteosarcopenia, and postoperative outcomes in patients with hepatobiliary-pancreatic cancer (HBPC).MethodsThree online databases, including Embase, PubMed, and the Cochrane Library, were thoroughly searched for literature describing the relationship between osteopenia, osteosarcopenia, and outcomes of surgical treatment of HBPC patients from the start of each database to September 29, 2023. The Newcastle-Ottawa Scale was used to rate the quality of the studies.ResultsThis analysis included a total of 16 articles with a combined patient cohort of 2,599 individuals. The results demonstrated that HBPC patients with osteopenia had significantly inferior OS (HR: 2.27, 95% CI: 1.70-3.03, p < 0.001) and RFS (HR: 1.96, 95% CI: 1.42-2.71, p < 0.001) compared to those without osteopenia. Subgroup analysis demonstrated that these findings were consistent across univariate and multivariate analyses, as well as hepatocellular carcinoma, biliary tract cancer, and pancreatic cancer. The risk of postoperative major complications was significantly higher in patients with osteopenia compared to those without osteopenia (OR: 1.66, 95% CI: 1.19-2.33, p < 0.001). Besides, we also found that the presence of osteosarcopenia in HBPC patients was significantly related to poorer OS (HR: 3.31, 95% CI: 2.00-5.48, p < 0.001) and PFS (HR: 2.50, 95% CI: 1.62-3.84, p < 0.001) in comparison to those without osteosarcopenia.ConclusionPreoperative osteopenia and osteosarcopenia can predict poorer OS and RFS with HBPC after surgery.

Abstract Background Small (

Abstract With the rapid development of wind power, the pressure on peak regulation of the power grid is increased. Electrochemical energy storage is used on a large scale because of its high efficiency and good peak shaving and valley filling ability. The economic benefit evaluation of participating in power system auxiliary services has become the focus of attention since the development of grid-connected hundred megawatt-scale electrochemical energy storage systems (ESS). Based on the relationship between power and capacity in the process of peak shaving and valley filling, a dynamic economic benefit evaluation model of peak shaving assisted by hundred megawatt-scale electrochemical ESS considering the equivalent life of the battery is proposed. The model considers the investment cost of energy storage, power efficiency, and operation and maintenance costs, and analyzes the dynamic economic benefits of different energy storage technologies participating in the whole life cycle of the power grid. Then, according to the current ESS market environment, the auxiliary service compensation price, peak-valley price difference and energy storage cost unit price required to make the energy storage technology achieve the balance of payments are calculated, and the economic balance points of different energy storage types are clarified. Finally, based on the measured data of different provincial power grids, the economies of six energy storage types applied to three provincial power grids are compared and analyzed, and the rationality and effectiveness of the relevant models proposed are verified. The work has theoretical guiding significance for the economic benefit evaluation of hundred megawatt-scale electrochemical energy storage.

The Resource for Coronavirus 2019 (RCoV19) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19. The complete contents of RCoV19 are available to the public at https://ngdc.cncb.ac.cn/ncov/.

In this paper, we study a predator-prey system, the modified Holling-Tanner model with strong Allee effect. The existence and stability of the non-negative equilibria are discussed first. Several kinds of bifurcation phenomena, which the model may undergo, such as saddle-node bifurcation, Hopf bifurcation, and Bogdanov-Takens bifurcation, are studied second. Bifurcation diagram for Bogdanov-Takens bifurcation of codimension 2 is given. Then, possible dynamical behaviors of this model are illustrated by numerical simulations. This paper appears to be the first study of the modified Holling-Tanner model that includes the influence of a strong Allee effect.

Background: Metabolic dysfunction-associated fatty liver disease (MAFLD) is now the most prevalent chronic liver disease worldwide, with an increasing incidence rate. MAFLD is a heterogeneous disease that can have a low or high-risk profile for developing severe liver disease in its natural course. Recent evidence has highlighted the critical role of RNA methylation modification in the pathogenesis of various liver diseases. However, it remains unclear whether the RNA N1-methyladenosine (m1A) modification of immune cells could potentially contribute to the pathogenesis and heterogeneity of MAFLD. Materials and methods: To address this issue, we conducted an integrated bioinformatics analysis of MAFLD bulk and single-cell RNA sequencing (scRNA-seq) data to pinpoint m1A regulators in the network. This was followed by a description of the immune landscape, pathway enrichment analysis, and molecular subtyping. Results: The expression patterns of m1A regulatory genes stratify MAFLD into two molecular subtypes, Cluster 1 and Cluster 2. These subtypes demonstrate different immune cell infiltration with distinct inflammation characteristics, which suggest different immune-inflammatory responses in the liver. Notably, Cluster 2 is associated with pro-inflammation and may be more likely to lead to progressive stages of MAFLD. Through intersection analysis of weighted gene co-expression network analysis (WGCNA) and m1A regulatory genes, three true hub genes (ALKBH1, YTHDC1, and YTHDF3) were identified, all of which were strongly correlated with infiltrating immune cells. The specific signaling pathways involved in the three core genes were derived from genomic variation analysis. Furthermore, scRNA-seq data from 33,168 cells from six liver samples identified 26 cell clusters and eight cell types, with endothelial cells, macrophages, and monocytes showing the most significant differences between MAFLD and normal controls. The cell-cell communication network between immune cells and non-parenchymal cells was extremely sophisticated and changed significantly in MAFLD. Conclusions: In summary, these findings demonstrate the involvement of m1A in MAFLD heterogeneity and emphasize the crucial role of m1A modulation of immune cells in regulating inflammation in MAFLD. These results may suggest potential therapeutic strategies for MAFLD.

Abstract Objectives Mucosal healing (MH) is an important goal in the treatment of patients with Crohn’s disease (CD). Noninvasive assessment of MH with normalized iodine concentration (NIC) is unknown. Methods In this retrospective study, 94 patients with diagnosed CD underwent endoscopy and dual-energy CT enterography (DECTE) at the post-infliximab treatment review. Two radiologists reviewed DECTE images by consensus for assessing diseased bowel segments of the colon or terminal ileum, and the NIC was measured. Patients were divided into transmural healing (TH), MH and non-MH groups. The diagnostic performance of the MH and non-MH groups with clinical factors and NIC was assessed utilizing receiver operating characteristic (ROC) curve analysis. Results Of the 94 patients included in our study, 8 patients achieved TH, 34 patients achieved MH, and 52 patients did not achieve MH at the post-IFX treatment review. The area under the ROC curve (AUC), sensitivity, specificity, and accuracy values were 0.929 (95% confidence interval [CI] 0.883–0.967), 0.853, 0.827, and 0.837, respectively, for differentiating MHs from non-MHs, and the optimal NIC threshold was 0.448. The AUC of the combined model for distinguishing MHs from non-MHs in CD patients, which was based on the NIC and calprotectin, was 0.964 (95% CI 0.935–0.987). Conclusions The normalized iodine concentration measurement in DECTE has good performance in assessment MH in patients with CD. Iodine concentration from DECTE can be used as a radiologic marker for MH.

As a new technology in the field of food science, three-dimensional (3D) printing technology has tremendous development potential due to its rapid prototyping capabilities, suitability for complex structures, and customization. Proteins, lipids, and other edible substances are generally used as materials in 3D food printing, but not all ingredients can be printed or processed well. 3D food printing technology, the properties of 3D printing materials, common food additives and their effects on rheological properties, processing properties, and nutritional properties of print materials are reviewed in this paper. This study would provide a scientific basis for the application of 3D food printing technology in the food field and theoretical references.