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Abstract The Mg–9Gd–3Y–2Zn–0.5Zr alloy was studied for its long-term corrosion behavior in a simulated coastal storage environment. The results show that the Mg12 (Y, Gd) Zn phase in the Mg–9Gd–3Y–2Zn–0.5Zr alloy forms a galvanic couple with α-Mg, and the Mg12 (Y, Gd) Zn phase acts as a cathode to accelerate α-Mg during the corrosion initiation period. The corrosion of the anode is subsequently transformed into corrosive dissolution of the anode. With the dissolution of the Mg12 (Y, Gd) Zn phase, elements such as Gd and Y are gradually distributed into the entire corrosion product layer, improving the protective performance of the corrosion product layer by forming dense Gd2O3 and Y2O3.

Epigenetic pathways play a critical role in the initiation, progression, and metastasis of cancer. Over the past few decades, significant progress has been made in the development of targeted epigenetic modulators (e.g., inhibitors). However, epigenetic inhibitors have faced multiple challenges, including limited clinical efficacy, toxicities, lack of subtype selectivity, and drug resistance. As a result, the design of new epigenetic modulators (e.g., degraders) such as PROTACs, molecular glue, and hydrophobic tagging (HyT) degraders has garnered significant attention from both academia and pharmaceutical industry, and numerous epigenetic degraders have been discovered in the past decade. In this review, we aim to provide an in-depth illustration of new degrading strategies (2017–2023) targeting epigenetic proteins for cancer therapy, focusing on the rational design, pharmacodynamics, pharmacokinetics, clinical status, and crystal structure information of these degraders. Importantly, we also provide deep insights into the potential challenges and corresponding remedies of this approach to drug design and development. Overall, we hope this review will offer a better mechanistic understanding and serve as a useful guide for the development of emerging epigenetic-targeting degraders.

As people’s material quality of life continues to improve, water resources become subjected to varying degrees of contamination. As one of the most commonly utilised agents in water treatment, a flocculant exhibits a diverse range of forms and a vast scope of applications. However, the application of flocculants gives rise to a series of issues, including the use of large doses, the formation of sludge, the difficulty of recycling flocculants, and other concerns. The development of new flocculation technology has become a crucial step in enhancing the purification of wastewater and reducing environmental pollution. Magnetic flocculation can be classified into two main categories: magnetic seeds flocculation and magnetic flocculation. This paper presents an overview of the factors influencing magnetic flocculation, including the type of magnetic seeds, magnetic seeds particle size, and other pertinent considerations. Furthermore, the classification of magnetic flocculants in the process of magnetic flocculation is discussed. This includes the types of magnetic flocculant, namely, inorganic composite magnetic flocculants, organic composite magnetic flocculants, and biological composite magnetic flocculants. Inorganic composite magnetic flocculants are inexpensive and simple to produce; however, their dosage is considerable, and the resulting floc is not tightly formed, which impairs the efficacy of flocculation. The use of organic composite magnetic flocculants requires a smaller dosage and exhibits a strong flocculating ability; however, it may possess toxic properties and potentially cause harm to the water body. The biological composite magnetic flocculant exhibits high efficiency and no pollution, yet it is subject to stringent environmental conditions, displays poor stability, and is applicable to a relatively limited range of treatment scenarios. Furthermore, the integration of magnetic flocculation technology with other techniques is classified and summarised in diverse contexts, and the prospective research focus and direction of magnetic flocculants are proposed.

Abstract Revealing the electrocatalytic microstructure is the basis for finding more efficient and stable electrode materials for clean energy conversion devices. However, there is still a lack of direct understanding of the phase transition process of the sample during heating, which makes the synthesis conditions of the catalyst often rely on experienced guidance. Herein, ZIF‐8@α‐Co(OH)2 core‐shell structure and uniformly coated α‐Co(OH)2 nanosheets on the surface of ZIF‐8 are synthesized. The effect of temperature on microstructure evolution is studied by in situ heating technique with high‐resolution transmission electron microscopy. Based on understanding the relationship between temperature, microstructure, and OER properties, a simple annealing synthesis strategy is designed effectively. During the annealing process, ZnO@CoO heterogeneous structure is formed at 400 °C, and the material reached a stable hydroxyl oxide structure after electrochemical cycle voltammetry in an alkaline solution. The OER performance test shows that the commercial IrO2 catalyst has comparable catalytic performance.

The regional distribution of neurofibrillary tangles of hyperphosphorylated tau aggregates is associated with the progression of Alzheimer’s disease (AD). Misfolded proteopathic tau recruits naïve tau and templates its misfolding and aggregation in a prion-like fashion, which is believed to be the molecular basis of propagation of tau pathology. A practical way to assess tau seeding activity is to measure its ability to recruit/bind other tau molecules and to induce tau aggregation. Based on the properties of proteopathic tau, here we report the development of two simple assays to assess tau seeding activity ----- capture assay in vitro and seeded-tau aggregation assay in cultured cells. In the capture assay, proteopathic tau was applied onto a nitrocellulose membrane and the membrane was incubated with cell lysate containing HA-tagged tau151-391 (HA-tau151-391). The captured tau on the membrane was determined by immuno-blots developed with anti-HA. For the seeded-tau aggregation assay, HEK-293FT cells transiently expressing HA-tau151-391 were treated with proteopathic tau in the presence of Lipofectamine 2000 and then lysed with RIPA buffer. RIPA-insoluble fraction containing aggregated tau was obtained by ultracentrifugation and analyzed by immuno-blot developed with anti-HA. To validate these two assays, we assessed the seeding activity of tau in the middle frontal gyrus, middle temporal gyrus and basal forebrain of AD and control brains and found that AD, but not control, brain extracts effectively captured and seeded tau151-391 aggregation. Basal forebrain contained less phospho-tau and tau seeding activity. The levels of captured tau or seeded-tau aggregates were positively correlated to the levels of phospho-tau, Braak stages and tangle sores. These two assays are specific and sensitive and can be carried out in a regular biomedical laboratory setting by using routine biochemical techniques.

Abstract Freezing fraction and collision coefficient are the key parameters in the ice accretion model, which should be calculated to predict the icing trend for transmission lines. Here a mathematical relation between freezing fraction and collision coefficient was derived using the simplified head balance model of transmission lines icing. Combined with the empirical formula of the liquid water content in air, a calculation method of the freezing fraction and collision coefficient was proposed using the ice surface temperature of transmission lines and the icing mass growth rate. The method to measure the icing mass growth rate based on online monitoring data and icing experiments was proposed. The icing experiments were carried out in the low‐temperature ice chamber with the same parameters as the online monitoring environmental parameters. The values of the freezing fraction and collision coefficient were calculated by using the online monitoring data and icing experiments data respectively, the calculation results were compared. The maximum relative differences between the calculation results from the online monitoring data and the icing experiments data do not exceed 18%, which proves the validity of the calculation method of the freezing fraction and collision coefficient in ice accretion model of transmission lines.

An approach to optimize the sensitivity and the limit of detection of on-chip refractive index sensor is proposed and demonstrated based on sub-wavelength grating racetrack microring resonator and Vernier effect. The sub-wavelength grating waveguide can reduce the structure limitation of the light field, which is beneficial to enhancing the interaction between the photon and analyte. By optimizing the parameters of the sub-wavelength grating racetrack microring resonator, the sensitivity of the sensor could be significantly improved to 664 nm/RIU. Subsequently, capitalizing the Vernier effect, a two cascaded microring-based refractive index sensor is designed. Owing to the Vernier effect, the wavelength spacings among the overlapped peaks could be effectively amplified more than ten times, leading to a high performance. The results demonstrate that an ultra-high sensitivity of 7061 nm/RIU and a low limit of detection of 1.74 × 10−5 RIU. With the advantages of ultra-high sensitivity and low limit of detection, the integrated device has important value in the fields of environmental monitoring and biosensors.

The impact of Pulsed Electric Field (PEF) processing pre-treatment on the texture and kinetics of in vitro starch digestibility of French fries made from two potato cultivars (Solanum tuberosum L.) containing dry matter content ranging from 19 to 22% was investigated. Whole and steam-peeled potato tubers were treated with a pilot scale PEF unit (electric field strength of 1.1 and 1.9 kV/cm with energy input 21%) tubers pretreated with PEF at electric field strength of 1.9 kV/cm. The findings generated in this study demonstrate PEF pretreatment may influence the texture of French fries and the extent of starch digestion that occurs.

To date, the underlying mechanisms involved intervertebral disc degeneration (IDD) remain unclear, which has hindered the development of molecular biological therapy for IDD. Autophagy is vital for intracellular quality control and metabolic balance in intervertebral disc cells. Hence, autophagy homeostasis is important. Emerging evidence has implicated vitamin D (VD) and the vitamin D receptor (VDR) in IDD progression because of their effects on different autophagy steps. However, the results of clinical trials in which VD supplementation was assessed as a treatment for IDD are controversial. Furthermore, experimental studies on the interplay between VD/VDR and autophagy are still in their infancy. In view of the significance of the crosstalk between VD/VDR and autophagy components, this review focuses on the latest research on VD/VDR modulation in autophagy and investigates the possible regulatory mechanisms. This article will deepen our understanding of the relationship between VD/VDR and autophagy and suggests novel strategies for IDD prevention and treatment.

Introduction: LncRNA (Long non-coding RNA) ZFAS1 (zinc finger antisense 1) functions as the oncogene in multiple cancers, including gastric cancer. However, its function and underlying mechanism in the GCA (gastric cardia adenocarcinoma), the most aggressive type of gastric cancer, remain unknown. Objective: In the current study, the expression level of LncRNA ZFAS1 was quantified in 762 GCA tissues and the paired adjacent non-tumor tissues. The expression level of LncRNA ZFAS1 was quantified in 762 GCA tissues and the paired adjacent non-tumor tissues, and further confirmed using in vitro cell and animal model based assays. Conclusion: We demonstrated here that the LncRNA ZFAS1 was up-regulated in GCA tissues. Furthermore, the elevated level of ZFAS1 was significantly associated with the GCA metastasis and cancer recurrence. It was also demonstrated to be an independent prognostic indicator of disease-free survival and overall survival for GCA patients. RNA sequencing showed that the up-regulated ZFAS1 was tightly associated with the down-regulated hypoxia inducible factor 1 (HIF1) and up-regulated EPAS1 (Endothelial PAS domain protein 1, also known as HIF2). In vitro studies showed that the ZFAS1 could bind to EPAS1, enhance its abilities to epigenetically silence the HIF1, and promote its own expression in GCA cell lines. In the animal model, codelivering the EPAS1 and the ZFAS1 antisense oligos could significantly boost up their therapeutic effects on tumor growth. Thus, targeting ZFAS1 and EPAS1 might be an alternative therapeutic option in GCA.

Stateful network protocol fuzzing is one of the essential means for ensuring network communication security. However, the existing methods have problems, including frequent auxiliary message interaction, no in-depth state-space exploration, and high shares of invalid interaction time. To this end, we propose SATFuzz, a stateful network protocol fuzzing framework. SATFuzz first prioritizes the states identified by the status codes in response messages, then randomly selects a state to test among the high-priority states, and determines its corresponding optimal test sequence, which is composed of the minimum pre-lead sequence, the test case, and the fittest post-end sequence. Finally, SATFuzz uses a quasi-recurrent neural network (QRNN) to filter the test cases before performing interaction, and only the optimal test sequence, including the valid test case, can be fed to the protocol entity. To verify the proposed framework, we conduct extensive experiments with the state-of-the-art fuzzer on two popular protocols. The results show that the vulnerability discovery efficiency of the proposed approach increases by at least 1.48 times (at most by 3.06 times), making it superior to the rival methods. This not only confirms the effectiveness of SATFuzz in terms of improving the vulnerability discovery efficiency but also shows that SATFuzz has significant advantages.

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

Based on various carbon nano materials, the ternary composite functionalized carbon nanotubes (FMWCNTs) @ carbon quantum dots (CQDs) @ polyaniline (PANI) was prepared by in-situ polymerization and hydrothermal method. The carbon-based material was made into an electrode sheet. The morphology and microscopic nanostructures were characterized by FTIR, field emission scanning electron microscopy and field emission transmission electron microscopy. Cyclic voltammetry and the galvanostatic charge discharge method was adapted to study the electrochemical properties of these active materials. Our results showed that the specific capacitance of FMWCNTs @ CQDs @ PANI was as high as 534 F/g, while it was 362 F/g, 319 F/g and 279 F/g for PANI @ FMWCNTs, PANI @ CQDs and polyaniline. This means that the specific capacitance of FMWCNTs @ CQDs @ PANI is increased by 47.5%, 67.4% and 91.4% comparing with the capacitance of PANI @ FMWCNTs, PANI @ CQDs and polyaniline, respectively. Moreover, the specific capacitance retention rate of the ternary active electrode after 1000 times of constant current charge and discharge cycle reached 86%, while it was 60% for PANI @ FMWCNTs, 72% for PANI @ CQDs and 65% for polyaniline.

This paper studies the influence of salience on nominal and real yield curves by introducing the salience effect in the Piazzesi and Schneider model (hereafter PS). We construct the salience values based on the expected consumption growth using U.S. data. We find that salience values are negatively correlated with the expected consumption growth rates. Based on U.S. data from 1960q1 to 2020q4, we find that the salience model can generate upward nominal and real yield curves within reasonable risk aversion coefficients (less than 10), as well as well-fitted average yields with actual data. The salience model compensates for the PS or recursive preference model’s inability to generate an upward nominal or real yield curve within reasonable risk aversion. Furthermore, we provide empirical support for model implications. [ABSTRACT FROM AUTHOR]

Abstract Background This study investigates the molecular mechanisms of CC@AC&SF@PP NPs loaded with AC099850.3 siRNA and sorafenib (SF) for improving hepatitis B virus-related hepatocellular carcinoma (HBV-HCC). Methods A dataset of 44 HBV-HCC patients and their survival information was selected from the TCGA database. Immune genes related to survival status were identified using the ImmPort database and WGCNA analysis. A prognostic risk model was constructed and analyzed using Lasso regression. Differential analysis was performed to screen key genes, and their significance and predictive accuracy for HBV-HCC were validated using Kaplan–Meier survival curves, ROC analysis, CIBERSORT analysis, and correlation analysis. The correlation between AC099850.3 and the gene expression matrix was calculated, followed by GO and KEGG enrichment analysis using AC099850.3 and its co-expressed genes. HepG2.2.15 cells were selected for in vitro validation, and lentivirus interference, cell cycle determination, CCK-8 experiments, colony formation assays, Transwell experiments, scratch experiments, and flow cytometry were performed to investigate the effects of key genes on HepG2.2.15 cells. A subcutaneous transplanted tumor model in mice was constructed to verify the inhibitory effect of key genes on HBV-HCC tumors. Subsequently, pH-triggered drug release NPs (CC@AC&SF@PP) were prepared, and their therapeutic effects on HBV-HCC in situ tumor mice were studied. Results A prognostic risk model (AC012313.9, MIR210HG, AC099850.3, AL645933.2, C6orf223, GDF10) was constructed through bioinformatics analysis, showing good sensitivity and specificity in diagnostic prediction. AC099850.3 was identified as a key gene, and enrichment analysis revealed its impact on cell cycle pathways. In vitro cell experiments demonstrated that AC099850.3 promotes HepG2.2.15 cell proliferation and invasion by regulating immune checkpoint CD276 expression and cell cycle progression. In vivo, subcutaneously transplanted tumor experiments showed that AC099850.3 promotes the growth of HBV-HCC tumors in nude mice. Furthermore, pH-triggered drug release NPs (CC@AC&SF@PP) loaded with AC099850.3 siRNA and SF were successfully prepared and delivered to the in situ HBV-HCC, enhancing the effectiveness of combined therapy for HBV-HCC. Conclusions AC099850.3 accelerates the cell cycle progression and promotes the occurrence and development of HBV-HCC by upregulating immune checkpoint CD276 expression. CC@AC&SF@PP NPs loaded with AC099850.3 siRNA and SF improve the effectiveness of combined therapy for HBV-HCC.

Abstract Myopia is a growing concern worldwide, especially among adolescents. This study aimed to investigate the prevalence and associated factors of myopia in adolescents aged 12–15 in Shandong Province, China. This cross-sectional study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines and involved stratified random cluster sampling of 128,678 students from 186 middle schools across 17 cities in Shandong Province. Data collection was conducted from March to April 2024. We excluded students with organic eye diseases, abnormal binocular vision functions, or a history of eye injuries or surgeries. Myopia was assessed using the standard logarithmic visual acuity chart and autorefractor without inducing ciliary muscle paralysis. A comprehensive questionnaire survey was conducted to gather demographic characteristics and daily life behaviors. With the chi-squared test for univariable analysis and multivariable logistic regression for identifying significant factors. This study included 126,375 participants, with a gender distribution of 51.02% male and 48.98% female. The overall prevalence of myopia was 71.34%. Higher prevalence was observed in girls (72.26%) compared to boys (70.45%), and the prevalence increased with age, peaking at 73.12% in 15-year-olds. Urban residents had a higher prevalence (71.86%) than rural (70.39%). Factors such as increased frequency of eye usage while lying down or leaning forward, frequent use of eyes while walking or riding in a car, prolonged screen time, and extended homework duration were associated with higher odds of developing myopia. Conversely, higher frequency of outdoor exercise, maintaining proper posture during reading and writing, greater distance from eyes to screen, and longer sleep duration were associated with lower odds. Additionally, female gender, older age, urban residence, and parental history of myopia increased the risk. The high prevalence of myopia among adolescents in Shandong Province was influenced by a combination of demographic, behavioral, and environmental factors. The study highlighted the importance of lifestyle modifications, such as increasing outdoor activities and maintaining proper visual habits, limiting the duration of screen exposure and homework sessions, and extending sleep duration, to mitigate the risk of developing myopia. These findings underscored the need for targeted public health interventions and educational campaigns to address this significant public health issue.

Abstract With the rapid proliferation of climate policies in both number and scope, there is an increasing demand for a global-level dataset that provides multi-indicator information on policy elements and their implementation contexts. To address this need, we developed the Global Climate Change Mitigation Policy Dataset (GCCMPD) using a semisupervised hybrid machine learning approach, drawing upon policy information from global, regional, and sector-specific sources. Differing from existing climate policy datasets, the GCCMPD covers a large range of policies, amounting to 73,625 policies of 216 entities. Through the integration of expert knowledge-based dictionary mapping, probability statistics methods, and advanced natural language processing technology, the GCCMPD offers detailed classification of multiple indicators and consistent information on sectoral policy instruments. This includes insights into objectives, target sectors, instruments, legal compulsion, administrative entities, etc. By aligning with the sector classification of the Intergovernmental Panel on Climate Change (IPCC) emission datasets, the GCCMPD serves to help policy-makers, researchers, and social organizations gain a deeper understanding of the similarities and distinctions among climate activities across countries, sectors, and entities.

Summary: Metal halide perovskite nanomaterials (PeNMs) are among the next generation of optoelectronic materials due to their unique crystal structure and diverse phase change behaviors, which have the potential to dynamically tune the device performances. In this review, the research progress on the phase change of PeNMs is comprehensively reviewed and summarized. First, the basic structure and composition, as well as the phase change mechanism are introduced. Then, the influence of the phase change on the optoelectronic properties of PeNMs is discussed in detail, including the regulation of the energy band structure, carrier transport properties, lattice strain and distortion, and the evolution of the photoexcited state. Finally, current challenges and future development trends are projected. This review promotes the understanding of the phase change of PeNMs, which will be useful for the innovative design and application of related optoelectronic devices.

Overweight/obesity among adolescents in Shandong Province, China, has been rising, posing significant public health challenge. Comprehensive investigation is needed to develop effective interventions. Following the Strengthening the Reporting of Observational Studies in Epidemiology guidelines, a stratified random cluster sampling approach was used from September to October 2023 across 17 cities in Shandong Province. The study included 165 middle schools, surveying 99,638 students aged 12 ∼ 15. After applying exclusion criteria, 97,356 students (97.71% effective rate) completed anthropometric measurements and questionnaires. Overweight/obesity were assessed based on national and international standards. Univariable chi-square test and multivariable logistic regression were used to analyze factors influencing overweight/obesity. In 2023, the overweight/obesity rate among 12 ∼ 15-year-olds in Shandong was 19.75%. Significant factors included sex, age, residence, family income, parental weight status and activity, mother’s gestational diabetes history, birth weight, physical activity, sleep, screen time, homework, and diet. Girls, older adolescents, and those with physically active parents or who themselves engaged in over 1.5 hours of daily physical activity had lower odds of being overweight/obese. Adequate sleep and frequent consumption of vegetable and fruit were also protective. Higher odds were associated with urban residence, high family income, overweight/obese parents, maternal gestational diabetes, high birth weight, excessive screen time, extensive homework, and frequent fast food consumption. Overweight/obesity in Shandong adolescents is influenced by multiple determinants. Holistic interventions addressing genetic, behavioral, and environmental factors are essential for promoting healthier lifestyles and reducing the prevalence in this demographic.

IntroductionTo explore the distribution of Isthmin-1 (ISM1) level and its association with isolated post-challenge hyperglycemia (IPH).MethodsA total of 522 participants without a history of diabetes were invited to attend a standard 75g 2-h oral glucose tolerance test (OGTT), and 71 subjects were further invited for a 3-h oral minimal model test. Insulin sensitivity and β-cell function were evaluated using both HOMA and estimated from OGTT. Circulating ISM1 levels were determined by a commercially available ELISA kit.ResultsA total of 76 (14.6%) participants were diagnosed as IPH, accounting for 61.3% of the newly diagnosed diabetes. ISM1 levels were significantly higher in men than in women (1.74 ng/mL versus 0.88 ng/mL). The inverse correlation between ISM1 and β-cell function and IPH was only significant in men. After multivariate adjustment, per unit increment in ISM1 was associated with 0.68-fold (95% CI: 0.49-0.90) reduced odds ratio (OR) of IPH in men. Compared to men with the lowest ISM1 levels, the adjusted OR of IPH with the highest ISM1 levels decreased by 73% (95% CI: 0.11-0.61). Moreover, incorporation of ISM1 into the New Chinese Diabetes Risk Score (NCDRS) model yielded a substantial improvement in net reclassification improvement of 58% (95% CI: 27%-89%) and integrated discrimination improvement of 6.4% (95% CI: 2.7%-10.2%) for IPH.ConclusionsISM1 was significantly and independently associated with IPH, and serves as a feasible biomarker for the early identification of men with high risk of IPH.

Abstract Background Relationship between serum phosphorus time in range and mortality risk in peritoneal dialysis (PD) patients remains uncertain. We aimed to evaluate the association between serum phosphorus time in range and all-cause mortality in Chinese PD population. Methods This was a multicenter, retrospective, cohort study of 1,915 patients collected from January 2008 to October 2020 in 4 Chinese centers. Serum phosphorus time in range was estimated as the months during the first year that a patient’s serum phosphorus level was within the target range (defined as 1.13–1.78 mmol/L). The primary outcome was all-cause mortality. The secondary outcomes were cardiovascular (CV) mortality and PD withdrawal. Cox proportional hazards regression model with comprehensive adjustments was used to assess the association. Results The primary outcome occurred in 249 (13.0%) PD patients over a median follow-up of 28 months. Overall, the serum phosphorus time in range was negatively associated with all-cause mortality (per 3-month increments, adjusted HR [aHR], 0.83; 95%CI: 0.75–0.92), CV mortality (per 3-month increments, aHR, 0.87; 95%CI: 0.77–0.99), and PD withdrawal (per 3-month increments, aHR, 0.89; 95%CI: 0.83–0.95). Competing-risk model showed that the relationship of serum phosphorus time in range with all-cause mortality remained stable. None of the variables including demographics, history of diabetes and CV disease, as well as several PD-related and clinical indicators modified this association. Conclusions PD patients with longer serum phosphorus time in range in the first year was negatively associated with all-cause mortality and CV mortality. Our findings highlight the importance of maintaining serum phosphorus levels within 1.13–1.78 mmol/L for PD patients.

Objective To compare the clinical outcomes and biomechanical characteristics of 1-, 2-, and 3-level pedicle subtraction osteotomy (PSO), and establish selection criteria based on preoperative radiographic parameters. Methods Patients undergone PSO to treat ankylosing spondylitis from February 2009 to May 2019 in Sun Yat-sen Memorial Hospital of Sun Yat-sen University were enrolled. According to the quantity of osteotomy performed, the participants were divided into group A (1-level PSO, n = 24), group B (2-level PSO, n = 19), and group C (3-level PSO, n = 11). Clinical outcomes were assessed before surgery and at the final follow-up. Comparisons of the radiographic parameters and quality-of-life indicators were performed among and within these groups, and the selection criteria were established by regression. Finite element analysis was conducted to compare the biomechanical characteristics of the spine treated with different quantity of osteotomies under different working conditions. Results Three-level PSO improved the sagittal parameters more significantly, but resulted in longer operative time and greater blood loss (p < 0.05). Greater stress was found in the proximal screws and proximal junction area of the vertebra in the model simulating 1-level PSO. Larger stress of screws and vertebra was observed at the distal end in the model simulating 3-level PSO. Conclusion Multilevel PSO works better for larger deformity correction than single-level PSO by allowing greater sagittal parameter correction and obtaining a better distribution of stress in the hardware construct, although with longer operation time and greater blood loss. Three-level osteotomy is recommended for the patients with preoperative of global kyphosis > 85.95°, T1 pelvic angle > 62.3°, sagittal vertical alignment > 299.55 mm, and pelvic tilt+ chin-brow vertical angle > 109.6°.

Abstract Objective To systematically review the effects of intermittent hypoxic training on the aerobic capacity of exercisers. Methods PubMed, Embase, The Cochrane Library, and Web of Science databases were electronically searched to collect studies on the effects of intermittent hypoxic training on the aerobic capacity of exercisers from January 1, 2000, to January 12, 2023. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias of the included studies. Then, meta-analysis was performed by using Stata SE 16.0 software. Results A total of 19 articles from 27 studies were included. The results of the meta-analysis showed that compared with the control group, the intermittent hypoxic training group had significantly increased maximal oxygen uptake [weighted mean difference = 3.20 (95%CI: 1.33 ~ 5.08)] and hemoglobin [weighted mean difference = 0.25 (95%CI: 0.04 ~ 0.45)]. Conclusion Intermittent hypoxic training can significantly improve the aerobic capacity of exercisers. Due to the limited quantity and quality of the included studies, more high-quality studies are needed to verify the above conclusion.

This study explores the potential of biosilica including diatom and diatomaceous earth as alternative silica sources for metakaolin-based geopolymers. Diatomaceous earth, composed of fossilised diatom frustules rich in amorphous silica, and diatoms, a sustainable source of renewable biosilica, are investigated for their effectiveness in enhancing geopolymer properties. Through detailed analyses including FTIR, XRD, and SEM, the study evaluates the impact of these biosilica sources on geopolymer compressive strength and microstructure, comparing them with conventional sodium silicate. Results show that diatoms exhibit significant promise, achieving 28-day strength up to 17.9 MPa at a 30% mass fraction, while diatomaceous earth reaches 26.2 MPa at a 50% addition rate, demonstrating their potential as active silica sources. Furthermore, the study elucidates the role of organic matter in biosilica on geopolymerisation, highlighting its influence on active silica release and the strength performance of products. This study proposes a novel pathway to enhance the sustainability of geopolymers through the utilisation of biosilica from diatoms, contributing to advancements in eco-efficient construction materials.

Diatomite, a natural adsorbent rich in active silica, serves as a valuable precursor for geopolymer synthesis. The safe disposal of diatomite as a failed lead (Pb(II)) adsorbent is critical to prevent secondary contamination. This study investigated the immobilisation efficiency of geopolymerisation for Pb(II)-rich diatomite sludge. Low-grade diatomite with high ignition loss was utilised in the synthesis of alkali-activated geopolymers. It was demonstrated that the geopolymers achieved a compressive strength of 28.3 MPa with a 50% replacement rate of metakaolin by diatomite sludge, which was not a compromise in strength compared to that of the geopolymer with no Pb(II) (26.2 MPa). The leaching behaviour of Pb(II) was evaluated using water and acetic acid, yielding concentrations below 3 mg/L and immobilisation efficiencies of 95% in both scenarios. Analytical techniques including Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) elucidated the mineral composition and chemical environment of the geopolymers. These analyses revealed that Pb(II) migrated from diatomite pores, potentially forming soluble hydroxides under sufficient hydroxide, which then participated in condensation with silicon and aluminium monomers, effectively immobilising Pb(II) within amorphous aluminosilicate gels. Furthermore, the formation of the amorphous gels within diatomite pores hindered Pb(II) leaching, encapsulating Pb(II) effectively. This study presents a novel approach to immobilising heavy metals within building materials, enhancing mineral resource utilisation efficiency while addressing environmental contamination concerns.

The use of Red/ET recombination to generate a large number of shuttle plasmids from a diverse library of chimeric domains for directed evolution of the pikromycin polyketide synthase (PKS) is reported. Red/ET recombination technology is adopted for generating new polyketide as it overcame some of the limitations of traditional approaches for PKS engineering.

Background:In recent years, diabetic kidney disease (DKD) has emerged as a prominent factor contributing to end-stage renal disease. Tubulointerstitial inflammation and lipid accumulation have been identified as key factors in the development of DKD. Earlier research indicated that Astragaloside IV (AS-IV) reduces inflammation and oxidative stress, controls lipid accumulation, and provides protection to the kidneys. Nevertheless, the mechanisms responsible for its protective effects against DKD have not yet been completely elucidated.Purpose:The primary objective of this research was to examine the protective properties of AS-IV against DKD and investigate the underlying mechanism, which involves CD36, reactive oxygen species (ROS), NLR family pyrin domain containing 3 (NLRP3), and interleukin-1β (IL-1β).Methods:The DKD rat model was created by administering streptozotocin along with a high-fat diet. Subsequently, the DKD rats and palmitic acid (PA)-induced HK-2 cells were treated with AS-IV. Atorvastatin was used as the positive control. To assess the therapeutic effects of AS-IV on DKD, various tests including blood sugar levels, the lipid profile, renal function, and histopathological examinations were conducted. The levels of CD36, ROS, NLRP3, Caspase-1, and IL-1β were detected using western blot analysis, PCR, and flow cytometry. Furthermore, adenovirus-mediated CD36 overexpression was applied to explore the underlying mechanisms through in vitro experiments.Results:In vivo experiments demonstrated that AS-IV significantly reduced hyperglycemia, dyslipidemia, urinary albumin excretion, and serum creatinine levels in DKD rats. Additionally, it improved renal structural abnormalities and suppressed the expression of CD36, NLRP3, IL-1β, TNF-α, and MCP-1. In vitro experiments showed that AS-IV decreased CD36 expression, lipid accumulation, and lipid ROS production while inhibiting NLRP3 activation and IL-1β secretion in PA-induced HK-2 cells.Conclusion:AS-IV alleviated renal tubule interstitial inflammation and tubule epithelial cell apoptosis in DKD rats by inhibiting CD36-mediated lipid accumulation and NLRP3 inflammasome activation.

IntroductionTrophoblast cell surface antigen 2 (TROP2; EpCAM2) is a transmembrane glycoprotein which is closely related to EpCAM (EpCAM; EpCAM1). Both proteins share partial overlapping functions in epithelial development and EpCAM expression but have not been comparatively analyzed together in bladder carcinomas. TROP2 constitutes the target for the antibody-drug conjugate Sacituzumab govitecan (SG; TrodelvyTM) which has been approved for treatment of metastatic urothelial carcinoma by the United States Food and Drug administration (FDA) irrespective of its TROP2 expression status. MethodsTo evaluate the potential clinical significance of subtle differences in TROP2 and EpCAM expression in urothelial bladder cancer, both proteins were analyzed by multiplex fluorescence immunohistochemistry in combination with a deep-learning based algorithm for automated cell detection on more than 2,700 urothelial bladder carcinomas in a tissue microarray (TMA) format. ResultsThe staining pattern of TROP2 and EpCAM were highly similar. For both proteins, the staining intensity gradually decreased from pTa G2 low grade (TROP2: 68.8±36.1; EpCAM: 21.5±11.7) to pTa G2 high grade (64.6±38.0; 19.3±12.2) and pTa G3 (52.1±38.7; 16.0±13.0, p

Abstract Background The application of molecular targeting therapy and immunotherapy has notably prolonged the survival of patients with hepatocellular carcinoma (HCC). However, multidrug resistance and high molecular heterogeneity of HCC still prevent the further improvement of clinical benefits. Dysfunction of tumor-infiltrating natural killer (NK) cells was strongly related to HCC progression and survival benefits of HCC patients. Hence, an NK cell-related prognostic signature was built up to predict HCC patients’ prognosis and immunotherapeutic response. Methods NK cell markers were selected from scRNA-Seq data obtained from GSE162616 data set. A consensus machine learning framework including a total of 77 algorithms was developed to establish the gene signature in TCGA–LIHC data set, GSE14520 data set, GSE76427 data set and ICGC–LIRI–JP data set. Moreover, the predictive efficacy on ICI response was externally validated by GSE91061 data set and PRJEB23709 data set. Results With the highest C-index among 77 algorithms, a 11-gene signature was established by the combination of LASSO and CoxBoost algorithm, which classified patients into high- and low-risk group. The prognostic signature displayed a good predictive performance for overall survival rate, moderate to high predictive accuracy and was an independent risk factor for HCC patients’ prognosis in TCGA, GEO and ICGC cohorts. Compared with high-risk group, low-risk patients showed higher IPS–PD1 blocker, IPS–CTLA4 blocker, common immune checkpoints expression but lower TIDE score, which indicated low-risk patients might be prone to benefiting from ICI treatment. Moreover, a real-world cohort, PRJEB23709, also revealed better immunotherapeutic response in low-risk group. Conclusions Overall, the present study developed a gene signature based on NK cell-related genes, which offered a novel platform for prognosis and immunotherapeutic response evaluation of HCC patients.