Search

The lipid nanoparticle (LNP) has been so far proven as a strongly effective delivery system for mRNA and siRNA. However, the mechanisms of LNP's distribution, metabolism, and elimination are complicated, while the transportation and pharmacokinetics (PK) of LNP are just sparsely investigated and simply described. This study aimed to build a model for the transportation of RNA-LNP in Hela cells, rats, mice, and humans by physiologically based pharmacokinetic (PBPK) and quantum mechanics (QM) models with integrated multi-source data. LNPs with different ionizable lipids, particle sizes, and doses were modeled and compared by recognizing their critical parameters dominating PK. Some interesting results were found by the models. For example, the metabolism of ionizable lipids was first limited by the LNP disassembly rate instead of the hydrolyzation of ionizable lipids; the ability of RNA release from endosomes for three ionizable lipids was quantitively derived and can predict the probability of RNA release. Moreover, the biodegradability of three ionizable lipids was estimated by the QM method and the is generally consistent with the result of PBPK result. In summary, the transportation model of RNA LNP among various species for the first time was successfully constructed. Various in vitro and in vivo pieces of evidence were integrated through QM/PBPK multi-level modeling. The resulting new understandings are related to biodegradability, safety, and RNA release ability which are highly concerned issues of the formulation. This would benefit the design and research of RNA-LNP in the future.

In current practice of bolt reaming and anchoring of roadways in soft coal and rock mass, resin cartridges bend easily under the strong pushing and stirring of bolts, and the resin accumulates in the bolt-reamed area and does not participate in the stirring. As a result, bolts encounter high drilling resistance and cannot reach the bottom of drillholes. The effective anchorage length is far less than the actual anchorage length. Bolts are not centered, and the shear is misaligned at the joint surface in the reaming area, which leads to cracking of the whole anchoring solid and large shear deformation of bolts. This study systematically analyzes the characteristics of roadway bolt reaming and anchoring. The influences of resin stirring force, bolt pull-out force, and reaming–anchoring solid strength on reaming–anchoring performance were analyzed theoretically. The main purpose is to develop a device that enhances reaming and anchoring. The mechanism through which the device strengthens the reaming–anchoring solid was analyzed theoretically. Numerical simulation and experiments were carried out to verify the improved performance of the small-pore reaming and anchoring using the proposed technology. The results showed that the stirring migration rate of the resin cartridge is greatly improved by adding the device to bolts. The reaction rate of the anchoring mixture, stirring pressure, pull-out force of the reaming and anchoring system, bolt concentricity, and shear and compressive strengths of the anchoring solid are also enhanced in the reaming area. This ensures that the resin cartridge in the reaming area is completely stirred, which greatly improves the shear resistance of the reaming–anchoring solid. Meanwhile, the drilling performance, torsional force, and stirring efficiency of bolts are maximized and prevail over those of conventional bolts.

Background: Oxaliplatin is commonly used to treat gastrointestinal malignancies. However, its applications are limited due to potential adverse drug reactions (ADRs), particularly severe anaphylactic shock. There is no method to predict or prevent ADRs caused by oxaliplatin. Therefore, we aimed to investigate the genetic HLA predisposition and immune mechanism of oxaliplatin-induced ADRs. Methods: A retrospective review was performed for 154 patients with ADRs induced by oxaliplatin during 2016–2021 recorded in our ADR notification system. HLA genotyping was conducted for 47 patients with oxaliplatin-induced ADRs, 1100 general population controls, and 34 oxaliplatin-tolerant controls in 2019–2023. The in vitro basophil activation test (BAT) was performed and oxaliplatin-specific IgE levels were determined. Results: The incidence of oxaliplatin-induced ADRs and anaphylactic shock in our cohort was 7.1% and 0.15%, respectively. Of the 154 patients, 67.5% suffered rash/eruption; 26.0% of the patients who could not undergo oxaliplatin rechallenge were considered to show oxaliplatin-induced immune-mediated hypersensitivity reactions (HRs). The genetic study found that the HLA-DRB∗12:01 allele was associated with oxaliplatin-induced HRs compared to the general population controls (sensitivity = 42.9%; odds ratio [OR] = 3.4; 95% CI = 1.4–8.2; P = 0.008) and tolerant controls (OR = 12; 95% CI = 2.3–63.7; P = 0.001). The in vitro BAT showed higher activation of CD63+ basophils in patients with oxaliplatin-induced HRs compared to the tolerant controls (P

Utilizing first-order beam dynamics models is adequate for studying the beam properties during the conceptual design of a cyclotron-based proton therapy beamline. After finishing lattice design, particle-matter interaction simulations for passive elements (e.g., degrader, collimators, energy slit) are required. The cascade simulation is used for lattice updates in each iteration, which is complicated. In addition, when the models involve particle tracking and particle-matter interaction, their optimization process is time-consuming. Therefore, this study proposes a start-to-end modeling method using Monte Carlo Beam Delivery Simulation (BDSIM) software that considers more realistic factors, such as particle-matter interaction and the realistic vacuum chamber, to precisely evaluate working parameters, along with an efficient optimization method that utilizes multi-objective Bayesian optimization (MOBO) to improve transmission efficiency. Taking the Huazhong University of Science and Technology proton therapy facility (HUST-PTF) as an example, beam loss along the beamline is located, quantified, and subsequently reduced by tuning the quadrupole strengths based on MOBO. The results show that: (i) By considering the particle-matter interaction and the realistic vacuum chamber, the precision in the prediction of the beam properties is improved; (ii) After optimization, the transmission efficiency of the entire beamline is relatively increased by an average of 6.52 % under different energy settings, especially 11.39 % at 70 MeV.

Wampee (Clausena lansium) is an important evergreen fruit tree native to southern China that has a long history of use for medicinal purposes. Here, a chromosome-level genome of C. lansium was constructed with a genome size of 282.9 Mb and scaffold N50 of 30.75 Mb. The assembled genome contains 48.70% repetitive elements and 24,381 protein-coding genes. Comparative genomic analysis showed that C. lansium diverged from Aurantioideae 15.91–24.95 million years ago. Additionally, some expansive and specific gene families related to methyltransferase activity and S-adenosylmethionine-dependent methyltransferase activity were also identified. Further analysis indicated that N-methyltransferase (NMT) is mainly involved in alkaloid biosynthesis and O-methyltransferase (OMT) participates in the regulation of coumarin accumulation in wampee. This suggested that wampee's richness in alkaloids and coumarins might be due to the gene expansions of NMT and OMT. The tandem repeat event was one of the major reasons for the NMT expansion. Hence, the reference genome of C. lansium will facilitate the identification of some useful medicinal compounds from wampee resources and reveal their biosynthetic pathways.

Introduction: Posterior tibial slope (PTS) plays a vital role in knee stability. PTS of more than 12° may be considered with increased strain on the native anterior cruciate ligament (ACL) fibers. To handle the instability caused by changes in PTS degree, Proximal Tibial Anterior Closing Wedge Osteotomy (PT-ACWO) is adopted by surgeons. Methods: Between October 2015 and October 2019, our department conducted a retrospective analysis of patients who experienced anterior cruciate ligament reconstruction (ACLR) graft failures, with a particular focus on pathological PTS. The time from initial ACLR to revision ranged from 1 to 10 years, with a mean of 2.5 years. Radiological assessments of PTS were conducted, and outcomes were quantified using the International Knee Documentation Committee (IKDC) score, Lysholm score, and Tegner activity scale. The surgical technique and the use of 3D Patient-Specific Instrumentation (PSI) were outlined. Preoperative imaging included the use of Kirschner wires to establish tibial plateau reference points, and 3D-PSI was employed to guide the location and depth of the tibial osteotomy, which was performed obliquely. In a notable instance, a novel tibial tunnel was mapped out, and ortho-bridge system (OBS) fixation was utilized to ensure adequate space for the new tunnel. Results: In a cohort of seven patients with a mean follow-up of 28.1 months, a significant reduction in PTS was noted postoperatively (median [interquartile range, IQR], from 15.27° [13.46°, 16.60°] to 6.25° [5.89°, 6.78°]; P = 0.002). IKDC score improved to 85.10 (80.25, 88.10), P

The resource utilization of calcium carbide residue (CCR) and rice husk ash (RHA) is helpful to save resources and alleviate environmental pollution. In this research, CCR and RHA were used to modify soft clay, and the resonant column test was conducted to explore its small-strain dynamic characteristics. The micro-mechanism of CCR-RHA modified soft clay (CRSC) was investigated by using scanning electron microscopy, X-ray diffraction and mercury intrusion tests. The findings demonstrated that the dynamic shear modulus of the CRSC increased with the increase of RHA content and confining pressure, but decreased with the increase of shear strain. In contrast, the damping ratio presents the opposite change law. The Hardin-Drnevich (H-D) model was used to fit the dynamic shear modulus/maximum dynamic shear modulus (G/Gmax)-shear strain γ and the damping ratio D-shear strain γ. As confining pressure increased, Gmax increased but Dmax dropped in CRSC specimens with the same RHA content. The changes of the fitted G/Gmax-γ curve could be divided into progressively decrease stage and rapid decrease stage, while the changes of the fitted D-γ curve could be separated into linear stage and slow stage, with the same turning point γ = 10−4. Microscopic tests revealed that the incorporation of CCR and RHA helped to promote the hydration reaction, and the generated hydration products such as calcium silicate hydrate were able to enhance the integrity and compactness of the CRSC. The results of this research putfward solid foundation for the application of CCR-RHA in the modification of soft soil.

Heterogeneous grain structures with coherent L12 nanoprecipitates were constructed in a medium entropy alloy with chemical composition of Co34.5Cr32Ni27.5Al3Ti3 (at. %). The volume fraction and size of L12 nanoprecipitates are observed to become higher and larger, and the interspacing is found to become smaller with increasing aging time, resulting in a severer heterogeneity. The domain of tensile properties was expanded by varying the size and volume fraction of coherent L12 nanoprecipitates after aging treatment. The samples after longer-time aging treatment show stronger strain hardening as compared to those after shorter-time aging treatment. The hetero-deformation-induced (HDI) hardening plays a more vital role in the longer-time aged samples than the shorter-time aged samples, especially at the elasto-plastic transition stage. The dominant precipitation hardening mechanism is observed to transit from dislocation-cutting to Orowan dislocation-looping with increasing precipitation size, as predicted by a theoretical model and validated by experimental results. Multiple deformation defects, such as deformation twins, stacking faults and Lomer-Cottrell locks, are the dominant deformation mechanisms for all samples, while interactions between these defects and L12 nanoprecipitates were observed to be more intensive in the longer-time aged samples than in the shorter-time aged samples, resulting in stronger precipitation and HDI hardening.

Background: Tongue inspection, an essential diagnostic method in Traditional Chinese Medicine (TCM), has the potential for early-stage disease screening. This study aimed to evaluate the effectiveness of deep learning-based analysis of tongue images for hepatic fibrosis screening. Methods: A total of 1083 tongue images were collected from 741 patients and divided into training, validation, and test sets. DenseNet-201, a convolutional neural network, was employed to train the AI model using these tongue images. The predictive performance of AI was assessed and compared with that of FIB-4, using real-time two-dimensional shear wave elastography as the reference standard. Results: The proposed AI model achieved an accuracy of 0.845 (95% CI: 0.79–0.90) and 0.814 (95% CI: 0.76–0.87) in the validation and test sets, respectively, with negative predictive values (NPVs) exceeding 90% in both sets. The AI model outperformed FIB-4 in all aspects, and when combined with FIB-4, the NPV reached 94.4%. Conclusion: Tongue inspection, with the assistance of AI, could serve as a first-line screening method for hepatic fibrosis.

Cu pillar bump (CPB) technology as the representative advanced packaging technology possesses the characteristics of miniaturization and high density, thus playing an important role in the reliability of electronic devices. However, the brittle intermetallic compound (IMC) layer in the joints evidently affects the service performance and reliability of CPB joints. Thus, the influence of IMC layer thickness and microstructure needs to be carefully evaluated. In this study, the reliability of CPB joints with different IMC layer thickness under the condition of isothermal storage and room-temperature electromigration was tested, and the effect of initial IMC thickness of joints on the reliability was revealed. The full-IMC joints have the best isothermal storage reliability while the half-IMC joints perform the worst. Meanwhile, the thin-IMC joints own the best electromigration reliability but the full-IMC joints show the worst because that the initial voids in full-IMC joints accelerate the failure caused by electromigration.

Background: Lifestyle plays an important role in preventing and managing gastroesophageal reflux disease (GERD). In response to the conflicting results in previous studies, we performed a systematic review and meta-analysis to investigate this association. Methods: Relevant studies published until January 2023 were retrieved from 6 databases, and the prevalence of symptomatic gastroesophageal reflux (GER) or GERD was determined from the original studies. A random effects model was employed to meta-analyze the association by computing the pooled relative risk (RR) with 95% confidence intervals (95%CIs). Furthermore, subgroup and dose–response analyses were performed to explore subgroup differences and the association between cumulative physical activity (PA) time and GERD. Results: This meta-analysis included 33 studies comprising 242,850 participants. A significant negative association was observed between PA and the prevalence of symptomatic GER (RR = 0.74, 95%CI: 0.66–0.83; p < 0.01) or GERD (RR = 0.80, 95%CI: 0.76–0.84; p < 0.01), suggesting that engaging in PA might confer a protective benefit against GERD. Subgroup analyses consistently indicated the presence of this association across nearly all subgroups, particularly among the older individuals (RR

A novel small molecule depressant (M-DEP) was used to separate chalcopyrite and molybdenite via flotation. The results showed that M-DEP had an excellent selective depression on molybdenite, while had little effect on the flotation of chalcopyrite. The adsorption capacity of M-DEP on the surface of molybdenite was greater than that on chalcopyrite surface. The adsorption of M-DEP reduced the floatability of molybdenite and had less effect on the floatability of chalcopyrite, which was due to its different adsorption modes on the surface of the two minerals. Furthermore, the interaction between chalcopyrite and M-DEP was mainly chemical interaction, and almost all of the adsorbed M-DEP molecules were removed and replaced by sodium butyl xanthate (SBX). By contrast, hydrophobic interaction was the main way in which M-DEP was adsorbed on the molybdenite surface with little chemical interaction, which was less interfered by SBX addition. Therefore, M-DEP had a super selective depression on molybdenite. The study provided a novel depressant and approach for the deep separation of chalcopyrite and molybdenite via flotation.

Background: Osteoporosis is recognized as a skeletal disorder characterized by diminished bone tissue quality and density. Regular physical exercise is widely acknowledged to preserve and enhance bone health, but the detailed molecular mechanisms involved remain unclear. Irisin, a factor derived from muscle during exercise, influences bone and muscle. Since its discovery in 2012, irisin has been found to promote bone growth and reduce bone resorption, establishing a tangible link between muscle exertion and bone health. Consequently, the mechanism by which irisin prevents osteoporosis have attracted significant scientific interest. Aim of the review: This study aims to elucidate the multifaceted relationship between exercise, irisin, and bone health. Focusing on irisin, a muscle-derived factor released during exercise, we seek to understand its role in promoting bone growth and inhibiting resorption. Through a review of current research article on irisin in osteoporosis, Our review provides a deep dive into existing research on influence of irisin in osteoporosis, exploring its interaction with pivotal signaling pathways and its impact on various cell death mechanisms and inflammation. We aim to uncover the molecular underpinnings of how irisin, secreted during exercise, can serve as a therapeutic strategy for osteoporosis. Key scientific concepts of the review: Irisin, secreted during exercise, plays a vital role in bridging muscle function to bone health. It not only promotes bone growth but also inhibits bone resorption. Specifically, Irisin fosters osteoblast proliferation, differentiation, and mineralization predominantly through the ERK, p38, and AMPK signaling pathways. Concurrently, it regulates osteoclast differentiation and maturation via the JNK, Wnt/β-catenin and RANKL/RANK/OPG signaling pathways. This review further delves into the profound significance of irisin in osteoporosis and its involvement in diverse cellular death mechanisms, including apoptosis, autophagy, ferroptosis, and pyroptosis.

Variations in molecular evolutionary rate have been widely investigated among lineages and genes. However, it remains an open question whether fast rate of molecular evolution is driven by natural selection or random drift, and how the fast rate is linked to metabolic rate. Additionally, previous studies on fast molecular evolution have been largely restricted to concatenated matrix of genes or a few specifically selected genes, but less is known for individual genes at the genome-wide level. Here we addressed these questions using more than 5000 single-copy orthologous (SCO) genes through comparative genomic and phylogenetic analyses among fishes, with a special focus on a newly-sequenced clupeocephalan fish the Chinese hook snout carp Opsariichthys bidens. We showed O. bidens displays significantly higher mean substitution rate and more fast-evolving SCO genes (2172 genes) than most fishes studied here. The rapidly evolving genes are enriched in highly conserved and very basic functions such as translation and ribosome that are critical for biological fitness. We further revealed that ∼25 % of these fast-evolving genes exhibit a constant increase of substitution rate from the common ancestor down to the present, suggesting a neglected but important contribution from ancestral states. Model fitting showed that ∼85 % of fast-evolving genes exclusive to O. bidens and related species follow the adaptive evolutionary model rather than random-drift model, and 7.6 % of fast-evolving genes identified in O. bidens have experienced positive selection, both indicating the reflection of adaptive selection. Finally, metabolic rate was observed to be linked with substitution rate in a gene-specific manner. Overall, our findings reveal fast molecular evolution of SCO genes at genome-wide level in O. bidens, and uncover the evolutionary and ecological contributors to it.

Background: Mounting evidence underscores the importance of cell communication within the tumor microenvironment, which is pivotal in tumor proliferation, invasion, and metastasis. Exosomes play a crucial role in cell-to-cell communication. Although single-cell RNA sequencing (scRNA-seq) provides insights into individual cell transcriptional characteristics, it falls short of comprehensively capturing exosome-mediated intercellular communication. Method: We analyzed Pancreatic Ductal Adenocarcinoma (PDAC) tissues, separating supernatant and precipitate for exosome purification and single-cell nucleus suspension. We then constructed Single-nucleus RNA sequencing (snRNA-seq) and small RNA-seq libraries from these components. Our bioinformatic analysis integrated these sequences with ligand-receptor analysis and public miRNA data to map the cell communication network. Results: We established intercellular communication networks using bioinformatic analysis to track exosome miRNA effects and ligand-receptor pairs. Significantly, hsa-miR-1293 emerged as a prognostic biomarker for pancreatic cancer, linked to immune evasion, increased myeloid-derived suppressor cells, and poorer prognosis. Targeting this miRNA may enhance anti-tumor immunity and improve outcomes. Conclusion: Our study offers a novel approach to constructing intercellular communication networks using snRNA-seq and exosome-small RNA sequencing. By integrating miRNA tracing with ligand-receptor analysis, we illuminate the complex interactions in the pancreatic cancer microenvironment, highlighting the pivotal role of miRNAs and identifying potential biomarkers and therapeutic targets.

Q345B/2205 dissimilar steel multi-layer multi-pass welded joints were prepared using gas metal arc welding (GMAW). The effects of heat inputs on the microstructures and properties of welded joints were studied. The morphology and composition distribution of Q345B base metal near the fusion line were investigated. The results showed that the welded joints under different heat inputs were all present “carbon depleted zone” and “carburized zones” on both sides of the Q345B base metal and transition layer interface. The microstructure of the “carburized zones” was composed of martensite phase and granular bainite phase. It was found that only the welded joints with heat inputs of 1.765 kJ/mm and 2.860 kJ/mm met the usage requirements. The corrosion behavior and characteristics of the welded joint with a heat input of 1.765 kJ/mm in a 3.5 wt % NaCl solution were investigated intensively. During the soaked process of 14 days, the total impedance value of the welded joint showed first increasing and then decreasing. The maximum value of 8.7 kΩ cm2 was obtained on the 5th day. As the soaked time increased, the corrosion products of the welded joint underwent the formation, thickening, cracking and detachment, which was the main reason of the change in the corrosion resistance. The research results of this article have significant implications for the application of low-alloy steel and stainless steel welded joints in engineering.

Ultra-high strength steels with excellent strength, ductility and toughness have become one of indispensable high-performance structural materials. The development of ultra-high strength steels with higher performance has been widely concerned to break the strength-ductility trade-off. This study proposes a material inverse design strategy that combines material genetic design with thermodynamic calculation to search for new alloys with desirable microstructure and optimal strengthening contributions. Based on the advancement of the ‘Pareto Front’, a new steel with superior properties was successfully screened from 390,625 candidate individuals, which was verified by experiments. The experimental results show that a new steel Fe-0.25C-14.8Ni-17.0Co-2.54Mo-1.56Cr-0.53Al-1.06Cu-0.38V (wt. %) has been successfully developed. After quenching-cryogenic-aging process, the new steel achieved a superior combination of strength, ductility and toughness, with a yield strength of 2.2 GPa, an elongation-to-failure of 10% and a V-notch impact energy of 15 J. Multi-scale microstructure characterization indicates that such superior property synergy arises from the unique microstructure: lath martensite matrix with high-density dislocations and interstitial solid soluble carbon atoms, embedded fine M2C, NiAl and Cu-rich nanoprecipitates. We present an in-depth discussion on the origins of superior strength/ductility/toughness combinations of the new steel to validate the design strategy and provide an accessible pathway exploiting high-performance ultra-high strength steels.

Background/purpose: Periodontitis is associated with various systemic diseases, potentially facilitated by the passage of Porphyromonas gingivalis outer membrane vesicles (Pg-OMVs). Several recent studies have suggested a connection between Pg-OMVs and neuroinflammation and neurodegeneration, but the precise causal relationship remains unclear. This study aimed to investigate the mechanisms underlying these associations using in vitro models. Materials and methods: Isolated Pg-OMVs were characterized by morphology, size, and gingipain activity. We exposed SH-SY5Y neuroblastoma cells and BV-2 microglial cells to various concentrations of Pg-OMVs. Cell morphology, a 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, an enzyme-linked immunosorbent assay, and Western blot analysis were used to evaluate the cellular mechanism underlying Pg-OMV-induced neurotoxicity in neuronal cells and inflammatory responses in microglial cells. Results: Exposure to Pg-OMVs induced neurotoxicity in SH-SY5Y cells, as evidenced by cellular shrinkage, reduced viability, activation of apoptotic pathways, and diminished neuronal differentiation markers. Gingipain inhibition mitigated these effects, suggesting that gingipain mediates Pg-OMVs-induced neurotoxicity in SH-SY5Y cells. Our research on neuroinflammation suggests that upon endocytosis of Pg-OMVs by BV-2 cells, lipopolysaccharide (LPS) can modulate the production of inducible nitric oxide synthase and tumor necrosis factor-alpha by activating pathways that involve phosphorylated AKT and the phosphorylated JNK pathway. Conclusion: Our study demonstrated that following the endocytosis of Pg-OMVs, gingipain can induce neurotoxicity in SH-SY5Y cells. Furthermore, the Pg-OMVs-associated LPS can trigger neuroinflammation via AKT and JNK signaling pathways in BV-2 cells.

In order to better detect and identify the running state of the wind turbine equipment and its generator in the power system wind farm, and then improve the operation reliability of the wind turbine in the power system wind farm, the monitoring method of power system state operation based on Supervisory Control and Data Acquisition (SCADA) model was studied. The SCADA model pre installs different types of sensors on the units of the power system to collect, record and store the power data of the power system. The empirical wavelet transform method is selected to extract the signal characteristics from the state operation signals collected by the SCADA model. ReliefF algorithm is used to select features related to equipment status monitoring from the extracted status operation signal features. Fuzzy C-means clustering algorithm is used to analyze the correlation of feature selection results and identify power system operating conditions. According to the condition identification results of power system, support vector regression prediction algorithm is selected to output the monitoring results of power system state operation. The experimental results show that the monitoring time of the generator and other equipment is less than 100 ms, which provides a strong guarantee for the reliable operation of the power system. This result not only validates the validity of the monitoring and data acquisition model proposed in this paper, but also provides a new idea and method for the intelligent operation and safety management of power system.

Background: The paclitaxel liposome formulation, encapsulating paclitaxel within a phospholipid bilayer, addresses the insolubility of traditional paclitaxel formulations, thereby reducing toxicity without compromising its antitumor efficacy. Methods: This multicenter, open-label, non-inferiority randomized controlled trial (ChiCTR2000038555) evaluates the efficacy and safety of paclitaxel liposome in comparison to the standard regimen of paclitaxel combined with carboplatin (PLC vs. PC) as first-line therapy in patients with epithelial ovarian cancer. Results: An analysis of median progression-free survival (PFS) revealed non-inferior outcomes between 263 patients in the PLC group and 260 patients in the PC group (32.3 vs. 29.9 months, hazard ratio [HR], 0.89 [95% CI, 0.64−1.25]), using a non-inferior margin of 1.3. Although the overall incidence of treatment-related adverse events was comparable between groups, the PLC group experienced significantly fewer non-hematologic toxicities than those treated with the PC regimen. Conclusion: The findings affirm the non-inferiority of paclitaxel liposome compared to the combination of paclitaxel and carboplatin regarding therapeutic efficacy, with an enhanced safety profile marked by reduced non-hematologic toxicities.

Background: Alzheimer's disease (AD) is complicated by multiple environmental and polygenetic factors. The accuracy of artificial neural networks (ANNs) incorporating the common factors for identifying AD has not been evaluated. Methods: A total of 184 probable AD patients and 3773 healthy individuals aged 65 and over were enrolled. AD-related genes (51 SNPs) and 8 environmental factors were selected as features for multilayer ANN modeling. Random Forest (RF) and Support Vector Machine with RBF kernel (SVM) were also employed for comparison. Model results were verified using traditional statistics. Results: The ANN achieved high accuracy (0.98), sensitivity (0.95), and specificity (0.96) in the intrinsic test for AD classification. Excluding age and genetic data still yielded favorable results (accuracy: 0.97, sensitivity: 0.94, specificity: 0.96). The assigned weights to ANN features highlighted the importance of mental evaluation, years of education, and specific genetic variations (CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650) for AD classification. Receiver operating characteristic analysis revealed AUC values of 0.99 (intrinsic test), 0.60 (TWB-GWA), and 0.72 (CG-WGS), with slightly lower AUC values (0.96, 0.80, 0.52) when excluding age in ANN. The performance of the ANN model in AD classification was comparable to RF, SVM (linear kernel), and SVM (RBF kernel). Conclusion: The ANN model demonstrated good sensitivity, specificity, and accuracy in AD classification. The top-weighted SNPs for AD prediction were CASS4 rs7274581, PICALM rs3851179, and TOMM40 rs2075650. The ANN model performed similarly to RF and SVM, indicating its capability to handle the complexity of AD as a disease entity.

A novel alloy composition design (Fe–14Cr–13Co–5Mo–2Ni–1W–1V-0.16C-0.12Nb-0.074Si-0.027Mn, wt. %) was proposed for modification on that of the conventional CSS-42L stainless steel. The present homogeneous structure without carburizing displays an excellent synergy of yield strength and fracture toughness, which should improve the performance of the corresponding case-carburized steels under the contact/bending fatigue conditions. An ultrahigh surface hardness (71 HRC) and an excellent hardness gradient along the depth are achieved in the present case-carburized gradient structure. Higher surface hardness at a temperature range of 200–400 °C is also observed in the present case-carburized gradient structure, as compared to the other case-carburized advanced bearing/gear steels, such as the M50 steel, the M50NiL steel and the conventional CSS-42L steel. Besides the previously reported M6C carbides in the case-carburized conventional CSS-42L steel, M7C3 carbides are newly discovered in the present case-carburized gradient structure due to the novel chemical design. The ultrahigh surface hardness at both room and high temperatures and the excellent hardness gradient distribution in the present case-carburized gradient structure should be attributed to the increased amount of dual-carbides, as well as the ultrafine dual-carbides embedded in the ultrafine martensite matrix. The superior mechanical properties of the present case-carburized gradient structure should be desirable for real bearing/gear applications.

Background: Soil salinization threatens food security and ecosystem health, and is one of the important drivers to the degradation of many ecosystems around the world. Soil microorganisms have extremely high diversity and participate in a variety of key ecological processes. They are important guarantees for soil health and sustainable ecosystem development. However, our understanding of the diversity and function of soil microorganisms under the change of increased soil salinization is fragmented. Aim of Review: Here, we summarize the changes in soil microbial diversity and function under the influence of soil salinization in diverse natural ecosystems. We particularly focus on the diversity of soil bacteria and fungi under salt stress and the changes in their emerging functions (such as their mediated biogeochemical processes). This study also discusses how to use the soil microbiome in saline soils to deal with soil salinization for supporting sustainable ecosystems, and puts forward the knowledge gaps and the research directions that need to be strengthened in the future. Key Scientific Concepts of Review: Due to the rapid development of molecular-based biotechnology (especially high-throughput sequencing technology), the diversity and community composition and functional genes of soil microorganisms have been extensively characterized in different habitats. Clarifying the responding pattern of microbial-mediated nutrient cycling under salt stress and developing and utilizing microorganisms to weaken the adverse effects of salt stress on plants and soil, which are of guiding significance for agricultural production and ecosystem management in saline lands.

Straw mulching is a widespread practice for reducing the soil carbon loss caused by erosion. However, the effects of straw mulching on dissolved organic matter (DOM) runoff loss from black soil are not well studied. How straw mulching affects the composition and loss of runoff DOM by changing soil aggregates remains largely unclear. Here, a straw mulching treatment was compared to a no mulching treatment (as a control) on sloping farmland with black soil erosion in Northeast China. We divided the soil into large macroaggregates (>2 mm), small macroaggregates (0.25–2 mm), and microaggregates (

Hexavalent chromium [Cr(VI)], one common environmental contaminant, has long been recognized as a carcinogen associated with lung cancer, but roles and mechanisms of Cr(VI)-induced epigenetic dysregulations in carcinogenesis remain to be investigated. In this study, we identified that RNA m5C methyltransferase NSUN2 was significantly upregulated in Cr(VI)-transformed cells and lung tissues of Cr(VI)-exposed mice. Inhibition of NSUN2 reduced cell proliferation, migration, colony formation and tube formation abilities. We found NSUN2-mediated m5C modification induced metabolic reprogramming and cell cycle by promoting the mRNA stabilities of ME1, GLUT3 and CDK2. In addition, knockdown of NSUN2 attenuated tumorigenesis and angiogenesis in vivo. RNA m5C reader ALYREF was identified to be involved in NSUN2-mediated m5C modification in Cr (VI)-induced carcinogenesis. Further study showed that EP300 induced NSUN2 upregulation through transcriptional activation by inducing histone modification at H3K27ac site for regulating Cr(VI) carcinogenesis. Our findings demonstrated novel role and mechanism of NSUN2 and epigenetic changes by increasing the RNA m5C modification that are important for Cr (VI)-induced carcinogenesis through NSUN2/ALYREF pathway. NSUN2, ALYREF, ME1, GLUT3 or/and CDK2 may be used as potential new biomarkers or/and therapeutic target(s) in the future.

Background: To enhance the accuracy of hepatocellular carcinoma (HCC) diagnosis using contrast-enhanced (CE) US, the American College of Radiology developed the CEUS Liver Imaging Reporting and Data System (LI-RADS). However, the system still exhibits limitations in distinguishing between HCC and non-HCC lesions. Purpose: To investigate the viability of employing machine learning methods based on quantitative parameters of contrast-enhanced ultrasound for distinguishing HCC within LR-M nodules. Materials and methods: This retrospective analysis was conducted on pre-treatment CEUS data from liver nodule patients across multiple centers between January 2013 and June 2022. Quantitative analysis was performed using CEUS images, and the machine learning diagnostic models based on quantitative parameters were utilized for the classification diagnosis of LR-M nodules. The performance of the model was assessed using the area under the receiver operating characteristic curve (AUC) and compared with the performance of four radiologists. Results: The training and internal testing datasets comprised 168 patients (median age, 53 years [IQR, 18 years]), while the external testing datasets from two other centers included 110 patients (median age, 54 years [IQR, 16 years]). In the internal independent test set, the top-performing Random Forest model achieved an AUC of 0.796 (95%CI: 0.729–0.853) for diagnosing HCC. This model exhibited a sensitivity of 0.752 (95%CI: 0.750–0.755) and a specificity of 0.761 (95%CI: 0.758–0.764), outperforming junior radiologists who achieved an AUC of 0.619 (95%CI: 0.543–0.691, p

Background: Hypoxia caused by global climate change and human activities has become a growing concern eliciting serious effect and damages to aquatic animals. Hexagrammos otakii is usually a victim of hypoxia which caused by high density aquaculture and high nutrient input. The mechanism underlying ferroptosis regulation after hypoxia-stress in liver of H. otakii, however, remains elusive. Methods: For a duration of 15 days, expose the H. otakii to low concentrations of dissolved oxygen (3.4 ± 0.2 mg/L). Detecting alterations in the H. otakii liver tissue by chemical staining, immunohistochemistry, and electron microscopy. The expression variations of relevant genes in the liver of the H. otakii were simultaneously detected using Western blot and qPCR. A correlation analysis was performed between HIF-1α and iron ion expression in the liver of H. otakii following hypoxic stress. Results: In this study, we conducted the whole ferroptosis integrated analysis of H. otakii under chronic hypoxic condition. Reactive oxygen species (ROS) are highly accumulated under the hypoxia treatment (Superoxide Dismutase, SOD; Catalase, CAT), and which results in a significantly enhanced of lipid peroxidation (Lipid Peroxidation, LPO; Malondialdehyde, MDA; Aminotransferase, AST; Alanine aminotransferase, ALT) in liver tissue. The HIF-1α signaling is activated to cope with the hypoxia stress through strategies including changing iron ion concentration (Fe3+ and TFR1) to breaking the oxidation balance (GSH and GSH-Px), and enhancing ferroptosis gene expression (GPX4). The expression of genes related to ferroptosis pathway (DMT1, FTH1, STEAP3, ACSL4, γ-GCS, SLC7A11) is significantly upregulated and associated to the expression of iron and HIF-1α. Conclusions: It is demonstrated that the HIF-1α/Fe3+/ROS/GPX4 axis is involved in promoting ferroptosis in fat greening hepatocytes following hypoxia-stress. Ultimately, our findings unveil a process by which hypoxic stress strongly encourages ferroptosis by triggering HIF-1α and boosting iron synthesis.

The knowledge of gut microbial information helps evaluate the nutrition and health of the host and can be used as an important tool for improving wildlife conservation and management. Guizhou golden monkey (Rhinopithecus brelichi) is on the International Union for Conservation of Nature (IUCN 2023) Red List. The purpose of the current study was to investigate the difference of gut microbiome and resistome among three different groups of Guizhou golden monkeys using a metagenome approach, thus providing valuable insights and tools for management of captive golden monkeys. Fecal samples of Guizhou golden monkeys were collected from three places including Fanjingshan National Nature Reserve in Guizhou (n =3, Wild), Panxi wildlife rescue center in Guizhou (n=3, CapGZ), and Beijing Zoo (n=3, CapBJ). Fecal DNA was extracted and libraries were prepared and then were sequenced on Illumina PE150 platform with 2 × 150 bp paired reads. The results showed that wild Guizhou golden monkeys had lower abundance of Firmicutes, Uroviricota, Spirochaetes, Fibrobacterota, Campylobacterota, and Candidatus Melainabacteria and higher abundance Proteobacteria, Bacteroidetes and Actinobacteria than the two groups of captive monkeys. PCoA analysis showed that fecal samples from three groups could be distinctly separated. Wild monkeys had significantly higher abundance of genes associated with metabolic function, including carbohydrate metabolism, amino acid metabolism, energy metabolism, and metabolism of cofactors and vitamins. Among the top 20 ARGs analyzed, more ARGs were detected in the wild monkeys than the rest two groups. Overall, this study provides a comprehensive analysis of microbiomes and resistome in wild and captive Guizhou golden monkeys. The data is important for improving the health, management, and conservation of Guizhou golden monkeys based on the deviations in gut microbiome. It also establishes the scientific foundation for future comparative studies on the gut microbiome and resistome of Guizhou golden monkeys and other closely related Rhinopithecus species.

The development of highly effective bifunctional catalysts for n-hexadecane hydroisomerization is still essential to produce second-generation biodiesel. Herein, a Pt-Pd/ZSM-22-G (abbreviated as Pt-Pd/Z22-G) bimetallic catalyst was prepared by employing a room temperature electron reduction (RTER) method with glow discharge as the electron source. As a contrast, a series of Pt/Z22-H, Pd/Z22-H and Pt-Pd/Z22-H catalysts were prepared by the conventional hydrogen reduction method. The Pt-Pd/Z22-G catalyst reveals more exposed metal sites, larger CMe/CH+ values and an enhanced distribution of Pt-Pd(111) facets compared with the Pt/Z22-H, Pd/Z22-H and Pt-Pd/Z22-H catalysts. These modifications are originated from the stronger electron interactions and the smaller metal nanoparticles because of the effects of highly energetic reducing electrons. The n-hexadecane hydroisomerization results show that the iso-hexadecane yield over the Pt-Pd/Z22-G catalyst is 82.9%, which is the highest among four investigated catalysts in this work. This phenomenon occurs because more exposed Pt-Pd(111) facets and larger CMe/CH+ ratios are beneficial for the adsorption and hydrogenation of iso-alkene intermediates at metal sites to increase the iso-alkanes yield based on density functional theory (DFT) calculations. Furthermore, the iso-alkanes yield over the Pt-Pd/Z22-G catalyst also keeps steady after long-term tests for 120 h because of the limited metal aggregation and carbon deposition.

Tebuconazole (TEB), a prominent chiral triazole fungicide, has been extensively utilized for plant pathogen control globally. Despite experimental evidence of TEB metabolism in mammals, the enantioselectivity in the biotransformation of R- and S-TEB enantiomers by specific CYP450s remains elusive. In this work, integrated in silico simulations were employed to unveil the binding interactions and enantioselective metabolic fate of TEB enantiomers within human CYP1A2, 2B6, 2E1, and 3A4. Molecular dynamics (MD) simulations clearly delineated the binding specificity of R- and S-TEB to the four CYP450s, crucially determining their differences in metabolic activity and enantioselectivity. The primary driving force for robust ligand binding was identified as van der Waals interactions with CYP450s, particularly involving the hydrophobic residues. Mechanistic insights derived from quantum mechanics/molecular mechanics (QM/MM) calculations established C2-methyl hydroxylation as the predominant route of R-/S-TEB metabolism, while C6-hydroxylation and triazol epoxidation were deemed kinetically infeasible pathways. Specifically, the resulting hydroxy-R-TEB metabolite primarily originates from R-TEB biotransformation by 1A2, 2E1 and 3A4, whereas hydroxy-S-TEB is preferentially produced by 2B6. These findings significantly contribute to our comprehension of the binding specificity and enantioselective metabolic fate of chiral TEB by CYP450s, potentially informing further research on human health risk assessment associated with TEB exposure.

Background: Recent research highlights the importance of muscular strength as a key factor in physical fitness, a strong indicator of overall mortality risk, and a vital target for preventing chronic diseases. This study used a proteome-wide Mendelian randomization analysis plus colocalization analysis for low hand grip strength to explore potential therapeutic targets for muscle weakness. Methods: We conducted two two-sample Mendelian randomization analyses from four cohorts to identify and validate the causal relationship between plasma proteins and low grip strength. We also employed bidirectional Mendelian randomization analysis with Steiger filtering, Bayesian co-localization, and phenotype scanning to detect reverse causality, thereby consolidating our Mendelian randomization findings. Downstream analyses were also undertaken of identified proteins, including knockout models, enrichment analyses, and protein-protein interaction networks. Finally, we assessed the druggability of the identified proteins. Results: At Bonferroni significance (P

Understanding the spatial fishing activity distribution characteristics is important for the sustainable development of fisheries. Spatial nonstationarity is always present, especially in marine ecosystems. To explore how marine environmental factors affect the fishing effort of tuna purse seine vessels, data from 2015 to 2020 on the fishing activities of these fleets and environmental variables in the Western and Central Pacific Ocean (WCPO) were analyzed. A Generalized Additive Model (GAM), Geographically Weighted Regression model (GWR), and Multi-Scale Geographically Weighted Regression (MGWR) model were applied to explore the drivers of fishing activity and the impacts of environmental factors on spatial heterogeneity. The results indicate that: (1) The MGWR models has the highest prediction accuracy and effectively reflects the spatial heterogeneity and multi-scale effects of environmental factors in a year. (2) Environmental factors exhibit significant multi-scale effects and spatial heterogeneity on the fishing activities of purse seine tuna vessels. Sea floor depth, salinity at 200 m depth and sea surface temperature show the greatest spatial heterogeneity in their impact on fishing activities. (3) Sea surface temperature, distance to port, and primary productivity and salinity at 200 m depth are key variables influencing the fishing activities of purse seine tuna vessels. These findings are expected to provide scientific and effective guidance for fishery management and sustainable development by assessing the spatial variations in fishing activities at multiple scales.

Background: Intravenous immunoglobulin (IVIG)-resistant Kawasaki disease (KD) poses a considerable challenge to patients and their families due to its severe complications. Previous researches have highlighted the critical role of immune disorders in its pathogenesis. However, fragmented studies based on isolated cases hinder a comprehensive understanding of this deadly illness. This study aimed to explore the overall landscape of peripheral blood mononuclear cells (PBMCs) in IVIG-resistant KD patients using single-cell RNA sequencing (scRNA-seq). Methods: The scRNA-seq was used to characterize the transcriptomic profiles of IVIG-resistant KD patients, IVIG-responsive KD patients, and healthy controls. Data quality control (QC) and subsequent analysis were conducted using various R packages. These included DoubletFinder and Harmony for QC, Seurat and SingleR for identifying and annotating major cell types, ggpubr for calculating and visualizing the percentages of each cell type, Seurat for characterizing differentially expressed genes (DEGs) between groups, pheatmap for visualizing the DEGs, clusterProfiler for performing Gene Ontology (GO) enrichment analysis of DEGs, scRepertoire for TCR and BCR data analysis, Monocle for assessing cell differentiation trajectories, and CellChat for intercellular interaction evaluation. Results: High-quality single-cell transcriptome data from 12 participants were analyzed, including five with IVIG-resistant KD, four with IVIG-responsive KD, and three healthy controls. We identified 10 major cell types and observed that the differentiation of CD8+ effector T cells was impeded in IVIG-resistant KD patients with coronary artery lesion (CAL) according to cell differentiation trajectory analysis. Subsequent cell communication analysis demonstrated that myeloid cluster with high expression of LCN2, S100P, and LTF played a key role, potentially signaling through MIF-CD74/CXCR4 and MIF-CD74/CD44 ligand-receptor pairs. Conclusion: Complex immunopathological changes occur during the development of CAL in IVIG-resistant KD. Stunted differentiation of CD8+ effector T cells is noted in KD-CAL. Interactions between myeloid cells and T cells activates multiple inflammatory signaling pathways, with ligand-receptor pairs, including MIF-CD74/CXCR4 and MIF-CD74/CD44, potentially playing crucial roles.

Summary: Short-chain fatty acids (SCFAs) are immunomodulatory compounds produced by the microbiome through dietary fiber fermentation. Although generally considered beneficial for gut health, patients suffering from inflammatory bowel disease (IBD) display poor tolerance to fiber-rich diets, suggesting that SCFAs may have contrary effects under inflammatory conditions. To investigate this, we examined the effect of SCFAs on human macrophages in the presence of Toll-like receptor (TLR) agonists. In contrast to anti-inflammatory effects under steady-state conditions, we found that butyrate and propionate activated the NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome in the presence of TLR agonists. Mechanistically, these SCFAs prevented transcription of FLICE-like inhibitory protein (cFLIP) and interleukin-10 (IL-10) through histone deacetylase (HDAC) inhibition, triggering caspase-8-dependent NLRP3 inflammasome activation. SCFA-driven NLRP3 activation was potassium efflux independent and did not result in cell death but rather triggered hyperactivation and IL-1β release. Our findings demonstrate that butyrate and propionate are bacterially derived danger signals that regulate NLRP3 inflammasome activation through epigenetic modulation of the inflammatory response.

The minimum fire extinguishing concentration is a key index for the development of next generation chemical clean fire extinguishing gases, which is usually got by the cup-burner. The fire suppression performance of low concentration of chemical gas is hard to be understood by the available methods. In this work, the fundamental acknowledgement of steady flame surface attacking mechanism by halon functional group is newly discussed by conducting a series of bench scale tests with a cylindrical channel under a varied fluorinated gases. The characteristics of flame propagation under differentiated air atmosphere environmental conditions is obtained. The influence of fluorine-containing gas flow rate on flame propagation speed is clarified. A dimensionless relationship including atomic radius, bond length, polarization degree, molar mass and molar volume are proposed to describe the influence of low concentration of fluorine-containing gas on flame propagation speed. It provides an insight for the understanding of the flame inhibition performance of low concentration halogenated gas.

Background: An association between increased aortic root dimensions (ARD) and elevated risk of cardiovascular mortality has been reported in the general population. However, evidence regarding the association between ARD and mortality in patients with acute heart failure (AHF) is limited. Methods: In a nationwide prospective cohort of the China Patient-Centered Evaluative Assessment of Cardiac Events Prospective Heart Failure Study, ARD was measured during diastole using echocardiography and indexed to body mass index (BMI). Cox proportional hazard models were used to validate the association between BMI-indexed ARD and mortality. Additionally, the relationship between BMI-indexed ARD and mortality was presented using restricted cubic spline in all populations, and both sexes. Results: A total of 2125 participants with ARD were included in the final analysis, among of 38.4 % were women, with a median age of 67 years. Over a median follow-up period of 54.4 (interquartile range: 30.1 to 59.7) months, 895 deaths occurred, with 750 attributed to cardiovascular causes and 145 to non-cardiovascular causes. Compared to the highest tertile group of BMI-indexed ARD, the lowest tertile group had a lower risk of cardiovascular mortality (hazard ratio [HR], 0.71; 95 % confidence interval [CI], 0.58 to 0.87; P

Summary: Injury is common in the life of organisms. Because the extent of damage cannot be predicted, injured organisms must determine how much tissue needs to be restored. Although it is known that amputation position affects the regeneration speed of appendages, mechanisms conveying positional information remain unclear. We investigated tissue dynamics in regenerating caudal fins of the African killifish (Nothobranchius furzeri) and found position-specific, differential spatial distribution modulation, persistence, and magnitude of proliferation. Single-cell RNA sequencing revealed a transient regeneration-activated cell state (TRACS) in the basal epidermis that is amplified to match a given amputation position and expresses components and modifiers of the extracellular matrix (ECM). Notably, CRISPR-Cas9-mediated deletion of the ECM modifier sequestosome 1 (sqstm1) increased the regenerative capacity of distal injuries, suggesting that regeneration growth rate can be uncoupled from amputation position. We propose that basal epidermis TRACS transduce positional information to the regenerating blastema by remodeling the ECM.

Summary: Background: Early prediction of lymph node status after neoadjuvant chemotherapy (NAC) facilitates promptly optimization of treatment strategies. This study aimed to develop and validate a deep learning network (DLN) using baseline computed tomography images to predict lymph node metastasis (LNM) after NAC in patients with locally advanced gastric cancer (LAGC). Methods: A total of 1205 LAGC patients were retrospectively recruited from three hospitals between January 2013 and March 2023, constituting a training cohort, an internal validation cohort, and two external validation cohorts. A transformer-based DLN was developed using 3D tumor images to predict LNM after NAC. A clinical model was constructed through multivariate logistic regression analysis as a baseline for subsequent comparisons. The performance of the models was evaluated through discrimination, calibration, and clinical applicability. Furthermore, Kaplan–Meier survival analysis was conducted to assess overall survival (OS) of LAGC patients at two follow-up centers. Findings: The DLN outperformed the clinical model and demonstrated a robust performance for predicting LNM in the training and validation cohorts, with areas under the curve (AUCs) of 0.804 (95% confidence interval [CI], 0.752–0.849), 0.748 (95% CI, 0.660–0.830), 0.788 (95% CI, 0.735–0.835), and 0.766 (95% CI, 0.717–0.814), respectively. Decision curve analysis exhibited a high net clinical benefit of the DLN. Moreover, the DLN was significantly associated with the OS of LAGC patients [Center 1: hazard ratio (HR), 1.789, P

Summary: Obesity and fatty liver diseases—metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH)—affect over one-third of the global population and are exacerbated in individuals with reduced functional aldehyde dehydrogenase 2 (ALDH2), observed in approximately 560 million people. Current treatment to prevent disease progression to cancer remains inadequate, requiring innovative approaches. We observe that Aldh2−/− and Aldh2−/−Sptbn1+/− mice develop phenotypes of human metabolic syndrome (MetS) and MASH with accumulation of endogenous aldehydes such as 4-hydroxynonenal (4-HNE). Mechanistic studies demonstrate aberrant transforming growth factor β (TGF-β) signaling through 4-HNE modification of the SMAD3 adaptor SPTBN1 (β2-spectrin) to pro-fibrotic and pro-oncogenic phenotypes, which is restored to normal SMAD3 signaling by targeting SPTBN1 with small interfering RNA (siRNA). Significantly, therapeutic inhibition of SPTBN1 blocks MASH and fibrosis in a human model and, additionally, improves glucose handling in Aldh2−/− and Aldh2−/−Sptbn1+/− mice. This study identifies SPTBN1 as a critical regulator of the functional phenotype of toxic aldehyde-induced MASH and a potential therapeutic target.

Antioxidant and free radical resistance has been a key concern of tissue engineering. In this study, Hydroxyapatite (HAp) with osteogenic activity and Oligomeric Proantho Cyanidins (OPC) with antioxidant activity were chemically grafted to prepare gelatin-based biofunctional aerogel (GHPOS). SEM results confirmed that these aerogels exhibited obvious macroporous structure and could provide a suitable microenvironment for bone cell growth. The addition of HAP-PEI-OPC made it have good antioxidant activity, and the cell results proved that the aerogel prepared in this study had good cytocompatibility and did not produce cytotoxicity. The addition of nanoparticles played an important role in the activity of 3T3-E1. The results showed that these bioactive aerogel scaffolds have potential applications in bone tissue engineering.

ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis Fifth Generation) is a significant dataset in climate reanalysis. Conducting a global-scale accuracy assessment and spatiotemporal distribution characteristic study of its temperature and precipitation data is crucial for gaining in-depth understanding of extreme climate changes. This study, based on CRU TS v4.04 (Climatic Research Unit Time-Series version 4.04) gridded data, employs multiple statistical indicators and detection metrics to assess the accuracy of the ERA5 temperature and precipitation dataset at a monthly scale over the past 70 years. Additionally, it utilizes Empirical Orthogonal Functions (EOF) to explore its spatiotemporal distribution characteristics. The results indicate that: (1) ERA5 demonstrates good consistency in most regions globally; however, the influence of uneven station density distribution results in weaker correlation in areas with sparse station density. (2) The accuracy of ERA5 data exhibits certain differences between the two periods (1950–1979, 1979–2019); with the overall performance of ERA5 temperature data near the Earth’s surface being better than that of precipitation data. (3) ERA5 precipitation data in the mid and low latitudes of the Southern and Northern Hemispheres exhibit characteristics of positive–negative distribution, while temperature data show an opposite distribution in the Northern and Southern Hemispheres (with a predominant pattern of warmer temperatures in the north and colder temperatures in the south). Additionally, the typical patterns for both variables occur in January and July each year. The above study will provide reference and insights for future climate change prediction and adaptation efforts.

To explore how chemical, physical and biological process impact the adsorption capacity of biochar for cations and anions, five kinds of spent mushroom substrate biochars including PB (carbonized Auricularia auricula substrate at 600 °C for 6 h), NB (Aged PB at 25 °C and 40 % moisture for 12 mon), AB (PB treated with 20 % mixed acid solution at 70 °C for 6 h), FB (PB subjected to 16 freeze–thaw cycles between − 20 °C and 25 °C) and MB (PB incubated with microbes from contaminated soil for 15 cycles) were prepared under simulated conditions, the internal mechanisms were revealed. Results showed that all aging processes caused a variation in crystal quantity and structure on different biochar. AB, NB and MB had higher hydrophilicity and polarity, and more positive charges than PB. Moreover, AB and MB had a higher cation exchange capacity (CEC) (70.7 and 75.3 cmol/kg) and more oxygen-containing functional groups than PB. MB has the maximum adsorption capacity for Cd(II) (24.2 mg/g), followed by PB (23.5 mg/g), FB (22.7 mg/g), NB (22.2 mg/g), and AB (22.0 mg/g). Langmuir model better described the Cd(II) adsorption onto NB, FB, and PB, while Freundlich better described AB and MB. As for Cr(VI), the maximum adsorption capacity followed the order: MB (24.1 mg/g) > AB (23.7 mg/g) > FB (23.5 mg/g) > PB (23.0 mg/g) > NB (22.7 mg/g). Langmuir model was better for Cr(VI) adsorption onto FB and PB, while Freundlich was better for AB, NB and MB. The pseudo-first-order kinetic model fits for Cd adsorption by FB，while the pseudo-second-order kinetic model fit for the adsorption of Cd and Cr by other biochars. The adsorption of Cr by all biochars was significantly related to the content of lactone group. Acidification and organic acids from microorganisms increased the pHPZC values of AB and MB, which was not conducive to the adsorption of Cd. The surface fragmentation of FB caused by the freezing and thawing process promoted its adsorption of Cd.

Background: For locally advanced cervical cancer (LACC), treatment response to radiotherapy (RT) can vary significantly even among those with the same stage classification of International Federation of Gynecology and Obstetrics (FIGO). This study investigated the value of ADC metric for forecasting end-of-treatment outcomes in LACC patients referred for RT. Methods: Eighty patients with pathologically confirmed cervical squamous cell carcinoma with (SCC) were included in the research. Abdominal or pelvic MRI scans were conducted at least three times for all participants: before RT, three weeks after beginning of RT and approximately two months after RT was finalized. Calculated apparent diffusion coefficient (ADC) values of the LACC include: pre-ADC, interim-ADC, ΔADC and Δ%ADC. Based on Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, subjects were calculated and subsequently categorized into good responders group (complete response) and poor responders group (progressive disease, stable disease or partial response). Results: Compared to good-responders, subjects of poor-responder group showed significantly lower values of interim-ADC, ΔADC, and Δ%ADC (all P

Ecosystem services are crucial for human survival and development. Changes in land use can lead to alterations in ecosystem service functions. However, the mechanism of how land use changes resulting from underground coal mining affect ecosystem service remains unclear, especially in areas with high groundwater levels. To address this issue, we studied the spatiotemporal in land use change in Jining City from 2000 to 2020 and employed Markov-PIM (probability integration method)-PLUS (Patch-generate Land Use Simulation) model to simulate land use change and ecosystem service values (ESV) in Jining City by 2030 under four different scenarios. The results indicate that from 2000 to 2020, the area of ecological space increased by 169.99 km2, and the area of living space expanded by 775.28 km2, while the area of production space decreased by 945.27 km2, conversely. These changes led to a 3 million yuan increase in total ESV. From 2020 to 2030, there was a marked decline in ESV under both natural development (ND) and living space preference (LSP) scenarios, with decreases of 0.59 billion yuan and 1.38 billion yuan, respectively. In contrast, in production space preference (PSP) and ecological space preference (ESP) scenarios, ESV increase by 0.22 billion yuan and 0.34 billion yuan. The ESP scenario is an effective strategy to strengthen environmental protection, significantly improve the ESV level of Jining City and meet the development goals of Jining City. Finally, the study concludes with recommendations like comprehensive management, industrial upgrading, and collaborative development for optimizing Jining City's future land use and enhance ESV for urban development.

Summary: Background: Acute respiratory distress syndrome (ARDS) is a life-threatening condition with a high incidence and mortality rate in intensive care unit (ICU) admissions. Early identification of patients at high risk for developing ARDS is crucial for timely intervention and improved clinical outcomes. However, the complex pathophysiology of ARDS makes early prediction challenging. This study aimed to develop an artificial intelligence (AI) model for automated lung lesion segmentation and early prediction of ARDS to facilitate timely intervention in the intensive care unit. Methods: A total of 928 ICU patients with chest computed tomography (CT) scans were included from November 2018 to November 2021 at three centers in China. Patients were divided into a retrospective cohort for model development and internal validation, and three independent cohorts for external validation. A deep learning-based framework using the UNet Transformer (UNETR) model was developed to perform the segmentation of lung lesions and early prediction of ARDS. We employed various data augmentation techniques using the Medical Open Network for AI (MONAI) framework, enhancing the training sample diversity and improving the model's generalization capabilities. The performance of the deep learning-based framework was compared with a Densenet-based image classification network and evaluated in external and prospective validation cohorts. The segmentation performance was assessed using the Dice coefficient (DC), and the prediction performance was assessed using area under the receiver operating characteristic curve (AUC), sensitivity, and specificity. The contributions of different features to ARDS prediction were visualized using Shapley Explanation Plots. This study was registered with the China Clinical Trial Registration Centre (ChiCTR2200058700). Findings: The segmentation task using the deep learning framework achieved a DC of 0.734 ± 0.137 in the validation set. For the prediction task, the deep learning-based framework achieved AUCs of 0.916 [0.858–0.961], 0.865 [0.774–0.945], 0.901 [0.835–0.955], and 0.876 [0.804–0.936] in the internal validation cohort, external validation cohort I, external validation cohort II, and prospective validation cohort, respectively. It outperformed the Densenet-based image classification network in terms of prediction accuracy. Moreover, the ARDS prediction model identified lung lesion features and clinical parameters such as C-reactive protein, albumin, bilirubin, platelet count, and age as significant contributors to ARDS prediction. Interpretation: The deep learning-based framework using the UNETR model demonstrated high accuracy and robustness in lung lesion segmentation and early ARDS prediction, and had good generalization ability and clinical applicability. Funding: This study was supported by grants from the Shanghai Renji Hospital Clinical Research Innovation and Cultivation Fund (RJPY-DZX-008) and Shanghai Science and Technology Development Funds (22YF1423300).

Accurately predicting the concentration of fine particulate matter (PM2.5) is crucial for evaluating air pollution levels and public exposure. Recent advancements have seen a significant rise in using deep learning (DL) models for forecasting PM2.5 concentrations. Nonetheless, there is a lack of unified and standardized frameworks for assessing the performance of DL-based PM2.5 prediction models. Here we extensively reviewed those DL-based hybrid models for forecasting PM2.5 levels according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We examined the similarities and differences among various DL models in predicting PM2.5 by comparing their complexity and effectiveness. We categorized PM2.5 DL methodologies into seven types based on performance and application conditions, including four types of DL-based models and three types of hybrid learning models. Our research indicates that established deep learning architectures are commonly used and respected for their efficiency. However, many of these models often fall short in terms of innovation and interpretability. Conversely, models hybrid with traditional approaches, like deterministic and statistical models, exhibit high interpretability but compromise on accuracy and speed. Besides, hybrid DL models, representing the pinnacle of innovation among the studied models, encounter issues with interpretability. We introduce a novel three-dimensional evaluation framework, i.e., Dataset-Method-Experiment Standard (DMES) to unify and standardize the evaluation for PM2.5 predictions using DL models. This review provides a framework for future evaluations of DL-based models, which could inspire researchers to standardize DL model usage in PM2.5 prediction and improve the quality of related studies.

Objectives: We aimed to evaluate the analytical performance of second-trimester maternal serum screening in China, and to compare if there are differences in sigma levels across different methods and months. Methods: A retrospective study was conducted to assess the analytical quality levels of laboratories by calculating the Sigma metrics with prenatal screening biomarkers: AFP, Total β-hCG, free β-hCG, uE3. Data from 591 laboratories were selected. Sigma metrics were computed using the formula: Sigma metrics(σ) = (%TEa - |%Bias|)/%CV. The Friedman test and Mann-Whitney test were used to compare differences across various methods and different months. The Hodges–Lehmann was used for determining 95 % confidence intervals of pseudo-medians. Results: Only uE3 showed significant monthly variations in sigma calculations. However, around 8 % of laboratories across all four analytes demonstrated sigma levels both above 6 and below 3 in different months. Laboratories utilizing time-resolved fluorescence methods significantly outperformed those using chemiluminescence in sigma level. For AFP, the pseudo-median difference between these methods lies within a 95 % confidence interval of (−3.22, −1.93), while for uE3, it is at (−2.30, −1.40). Notably, the median sigma levels for all analytes reached the 4-sigma threshold, with free β-hCG even attaining the 6-sigma level. Conclusion: With current standards, China's second-trimester maternal serum screening is of relatively high analytical quality, and variations in sigma levels exist across different months and methods.

DC microgrids have the risk of wideband DC bus voltage ripples. The ripple frequency may vary with system operating conditions, increasing the difficulty in voltage ripple suppression. To this end, an adaptive virtual admittance control strategy of the existing bidirectional DC/DC converter (BDC) with active power filtering capability is proposed. A ripple detection method based on the windowed-interpolated discrete Fourier transform is integrated, which allows the working frequency band of virtual ripple admittance to be automatically tuned. The proposed strategy reduces the impedance of BDC at the ripple frequency, allowing it to provide the ripple compensation current. To achieve synergistic suppression of multiple BDCs considering compensation capabilities and avoid overcurrent, the adaptive virtual ripple admittance based on the remaining deliverable current is designed. According to the difference of voltage ripple distribution due to line impedances, the virtual ripple admittance can be further adjusted by the secondary adjustment of management system to enhance the ripple suppression effect. Further, the stability analysis of the proposed strategy and comparison with fixed virtual admittance control are conducted. Finally, the effectiveness of the proposed strategy in the DC bus voltage ripple suppression and ripple compensation current distribution is verified by experiments.