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Abstract Periodontitis exacerbates Alzheimer’s disease (AD) through multiple pathways. Both periodontitis and AD are intricately correlated to intestinal homeostasis, yet there is still a lack of direct evidence regarding whether periodontitis can regulate the progression of AD by modulating intestinal homeostasis. The current study induced experimental periodontitis in AD mice by bilaterally ligating the maxillary second molars with silk and administering Pg-LPS injections in APPswe/PS1ΔE9 (APP/PS1) mice. Behavioral tests and histological analyses of brain tissue were conducted after 8 weeks. Gut microbiota was analyzed and colon tissue were also evaluated. Then, fecal microbiota from mice with periodontitis was transplanted into antibiotic-treated mice to confirm the effects of periodontitis on AD and the potential mechanism was explored. The results indicated periodontitis exacerbated cognitive impairment and anxious behaviour in APP/PS1 mice, with increased Aβ deposition, microglial overactivation and neuroinflammation in brain. Moreover, the intestinal homeostasis of AD mice was altered by periodontitis, including affecting gut microbiota composition, causing colon inflammation and destroyed intestinal epithelial barrier. Furthermore, AD mice that underwent fecal transplantation from mice with periodontitis exhibited worsened AD progression and disrupted intestinal homeostasis. It also impaired intestinal barrier function, elevated peripheral inflammation, damaged blood-brain barrier (BBB) and caused neuroinflammation and synapses impairment. Taken together, the current study demonstrated that periodontitis could disrupt intestinal homeostasis to exacerbate AD progression potential via causing gut microbial dysbiosis, intestinal inflammation and intestinal barrier impairment to induce peripheral inflammation and damage BBB, ultimately leading to neuroinflammation and synapse impairment. It underscores the importance of maintaining both periodontal health and intestinal homeostasis to reduce the risk of AD.

Abstract Governing equations are foundations for modelling, predicting, and understanding the Earth system. The Earth system is undergoing rapid change, and the conventional approaches for establishing governing equations, such as empirical generalisations, are becoming increasingly challenging to deal with the complexity and diversity of the geoscience processes we study today. In this Perspective, we explore data-driven equation discovery, a novel scientific artificial intelligence pathway, for advancing geosciences. Data-driven equation discovery identifies hidden patterns from data and transforms them into interpretable equation representations, automating and accelerating equation discovery processes. It provides a practical approach for geoscientists to model and understand complex geoscience processes based on big Earth data. The final vision is to uncover new clear, describable, and quantifiable equations in various geoscience disciplines. We summarize opportunities and highlight that challenges in this field should be addressed by interdisciplinary collaborations.

Abstract Background Children with chronic kidney disease (CKD) are at high risk of cardiovascular disease. Cardiovascular magnetic resonance (CMR) is the reference method for assessing cardiac remodeling. To our knowledge, no study has reported a comprehensive analysis of left ventricular(LV) cardiac remodeling using CMR in different stages of pediatric CKD. This prospective case-control study aimed to investigate cardiac remodeling in pediatric CKD, using CMR, and determine its relationship with risk factors. Method CMR was performed in 124 children with CKD and 50 controls. The cardiac remodeling parameters included left ventricular mass index (LVMI), LV remodeling index (LVRI), and LV wall thickness. Univariable and multivariable analyses were performed to assess the cardiac remodeling risk factors. Results Cardiac remodeling was observed in 35.5% (44/124) of children with CKD. The LVMI, LVRI, and LV wall thickness were higher in advanced stages of CKD (P

Abstract Radioresistance contributes to metastasis and recurrence in non-small cell lung cancer (NSCLC) patients. However, the underlying mechanism remains unclear. To provide novel clues, a complete multi-omics map of a radioresistant cancer cell line has been profiled. In this article, a lung adenocarcinoma cell line, radioresistant A549 (RA549), was generated by exposure to a series of irradiation. Subsequently, we adopted transcriptome, quantitative proteome and lysine 2-hydroxyisobutyrylome to construct a differential profile on the transcriptional to post-tanslational levels on A549 and RA549 cell lines, respectively. Our analysis revealed 920 significantly differentially expressed genes and 699 proteins. Furthermore, 2-hydroxyisobutyrylome identified 30,089 Khib modified sites on 4635 proteins, indicating that Khib modifications play vital role in regulating NSCLC radioresistance. Multi-omics combined analysis identified 19 significantly differentially expressed genes/proteins in total. Meanwhile, we found that EGFR, a well-known lung cancer-related receptor, was upregulated at both the protein and Khib modification levels in RA549. Further gain/loss of function experiments showed that Khib modified EGFR level positively correlates with NSCLC cell radioresistance. Taken together, our findings report that Khib-modified proteins enhanced resistance to radiation and represent promising therapeutic targets.

Abstract Background Cereal diseases caused by insect-transmitted viruses are challenging to forecast and control because of their intermittent outbreak patterns, which are usually attributed to increased population densities of vector insects due to cereal crop rotations and indiscriminate use of pesticides, and lack of resistance in commercial varieties. Root microbiomes are known to significantly affect plant health, but there are significant knowledge gaps concerning epidemics of cereal virus diseases at the microbiome-wide scale under a variety of environmental and biological factors. Results Here, we characterize the diversity and composition of rice (Oryza sativa) root-associated bacterial communities after infection by an insect-transmitted reovirus, rice black-streaked dwarf virus (RBSDV, genus Fijivirus, family Spinareoviridae), by sequencing the bacterial 16S rRNA gene amplified fragments from 1240 samples collected at a consecutive 3-year field experiment. The disease incidences gradually decreased from 2017 to 2019 in both Langfang (LF) and Kaifeng (KF). BRSDV infection significantly impacted the bacterial community in the rice rhizosphere, but this effect was highly susceptible to both the rice-intrinsic and external conditions. A greater correlation between the bacterial community in the rice rhizosphere and those in the root endosphere was found after virus infection, implying a potential relationship between the rice-intrinsic conditions and the rhizosphere bacterial community. The discrepant metabolites in rhizosphere soil were strongly and significantly correlated with the variation of rhizosphere bacterial communities. Glycerophosphates, amino acids, steroid esters, and triterpenoids were the metabolites most closely associated with the bacterial communities, and they mainly linked to the taxa of Proteobacteria, especially Rhodocyclaceae, Burkholderiaceae, and Xanthomonadales. In addition, the greenhouse pot experiments demonstrated that bulk soil microbiota significantly influenced the rhizosphere and endosphere communities and also regulated the RBSDV-mediated variation of rhizosphere bacterial communities. Conclusions Overall, this study reveals unprecedented spatiotemporal dynamics in rhizosphere bacterial communities triggered by RBSDV infection with potential implications for disease intermittent outbreaks. The finding has promising implications for future studies exploring virus-mediated plant-microbiome interactions. Video Abstract

Non-alcoholic fatty liver disease (NAFLD) is one abnormal buildup of fat within the liver, independent of excessive alcohol intake. In type 2 diabetes, the presence of NAFLD can exacerbate chronic kidney diseases and mortality in patients. Hepatocyte nuclear factor 1 homeobox A (HNF1A) predominantly expressed in the liver, owns one crucial role in liver development, function and tumorigenesis. However, the precise regulatory role of HNF1A on the progression of type 2 diabetes combined with NAFLD keep dimness. This investigation uncovered that HNF1A levels, both in protein and mRNA expressions, were elevated in high-fat diet plus hyperglycemia (HFG) mice. Furthermore, liver steatosis was strengthened in the HFG group, which was mitigated following the HNF1A inhibition. Knockdown of HNF1A ameliorated glucose and lipid metabolism disorders in HFG mice. Lastly, the study observed an stimulation of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway in HFG mice, but this change was neutralized uponHNF1A silencing. In conclusion, knockdown of HNF1A improved type 2 diabetes combined with NAFLD, as well as disorders in glucose and lipid metabolism, and retarded the PI3K/AKT/mTOR signaling pathway. These finding demonstrated that HNF1A may be one serviceable target for ameliorating type 2 diabetes combined with NAFLD.

Abstract Background Madhuca longifolia, the energy-producing and medicinal tropical tree originally from southern India, faces difficulties in adapting to the low temperatures of late autumn and early winter in subtropical southern China, impacting its usability. Therefore, understanding the molecular mechanisms controlling the ability of this species to adapt to environmental challenges is essential for optimising horticulture efforts. Accordingly, this study aimed to elucidate the molecular responses of M. longifolia to low-temperature stress through genomic and transcriptomic analyses to inform strategies for its effective cultivation and utilisation in colder climates. Results Herein, the high-quality reference genome and genomic assembly for M. longifolia are presented for the first time. Using Illumina sequencing, Hi-C technology, and PacBio HiFi sequencing, we assembled a chromosome-level genome approximately 737.92 Mb in size, investigated its genomic features, and conducted an evolutionary analysis of the genus Madhuca. Additionally, using transcriptome sequencing, we identified 17,941 differentially expressed genes related to low-temperature response. Through bioinformatics analysis of the WRKY gene family, 15 genes crucial for M. longifolia low-temperature resistance were identified. Conclusions This research not only lays the groundwork for the successful ecological adaptation and cultivation of M. longifolia in China’s southern subtropical regions but also offers valuable insights for the genetic enhancement of cold tolerance in tropical species, contributing to their sustainable horticulture and broader industrial, medicinal, and agricultural use.

Abstract Video Coding for Machines (VCM) is gaining momentum in applications like autonomous driving, industry manufacturing, and surveillance, where the robustness of machine learning algorithms against coding artifacts is one of the key success factors. This work complements the MPEG/JVET standardization efforts in improving the resilience of deep neural network (DNN)-based machine models against such coding artifacts by proposing the following three advanced fine-tuning procedures for their training: (1) the progressive increase of the distortion strength as the training proceeds; (2) the incorporation of a regularization term in the original loss function to minimize the distance between predictions on compressed and original content; and (3) a joint training procedure that combines the proposed two approaches. These proposals were evaluated against a conventional fine-tuning anchor on two different machine tasks and datasets: image classification on ImageNet and semantic segmentation on Cityscapes. Our joint training procedure is shown to reduce the training time in both cases and still obtain a 2.4% coding gain in image classification and 7.4% in semantic segmentation, whereas a slight increase in training time can bring up to 9.4% better coding efficiency for the segmentation. All these coding gains are obtained without any additional inference or encoding time. As these advanced fine-tuning procedures are standard-compliant, they offer the potential to have a significant impact on visual coding for machine applications.

The 3C-like protease (3CLpro) is a crucial target in anti-Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) drug design. Herein, we performed high-throughput synthesis of catechol derivatives from the bioactive catechol-terminal alkyne scaffold A4, by using modular click chemistry. Subsequently, we conducted two rounds of SARS-CoV-2 3CLpro inhibition screening and selected seven compounds for synthesis and further efficacy validation. Compound P1-E11 had potent inhibitory effects toward SARS-CoV-2 3CLpro (IC50 = 2.54 ± 0.46 μM); exhibited good selectivity toward the human cysteine proteases cathepsins B and L; and demonstrated superior anti-SARS-CoV-2 potency (EC50 = 4.66 ± 0.58 μM) with low cytotoxicity (CC50 > 100 μM) in A549-hACE2-TMPRSS2 cells. The irreversible covalent mechanism of P1-E11 was confirmed through time-dependent experiments, enzyme kinetic studies, and dilution and dialysis assays. The binding affinity between P1-E11 and SARS-CoV-2 3CLpro with a KD value of 0.57 μM was validated through surface plasmon resonance (SPR) experiments. Molecular docking provided insights into the binding mode of P1-E11 to the target protein. This study demonstrated the feasibility and efficacy of modular click reactions in natural-product-based structural modifications and presents a novel approach for leveraging this strategy in antiviral drug discovery.

Abstract Background Ambient particulate matter (PM) exposure is recognized as a risk factor for cardiovascular disease (CVD). However, the extent to which PM exposure is associated with CVD via triglyceride glucose (TyG)-related indicators remains unknown. This study examines the relationship between long-term PM exposure and CVD events, further assessing whether TyG-related indicators mediate this association. Methods This cohort study involved 7,532 individuals aged at least 45 years who were not diagnosed with CVD in 2011 from the China Longitudinal Study of Health and Retirement (CHARLS) and were followed up for the occurrence of CVD until 2020. The annual PM concentration data at the city level, with aerodynamic diameters ≤ 1 μm (PM1), ≤ 2.5 μm (PM2.5), and ≤ 10 μm (PM10), were obtained from the ChinaHighAirPollutants (CHAP). The average concentration of PM in the 3 years before the baseline survey in 2011 was defined as the long-term exposure level of the individual. The relationship between PM exposure and CVD incidence was examined via Cox proportional hazards models, with a focus on probing the role of TyG-related indicators through mediation analysis. Results A total of 1,865 individuals with CVD were diagnosed over the span of a 7.4-year follow-up period. The 3-year average concentrations before baseline were 31.29 µg/m³ for PM1, 56.03 µg/m³ for PM2.5, and 95.73 µg/m³ for PM10. In fully adjusted model, the Cox proportional hazards models revealed that an increase of 10 µg/m³ in the PM1, PM2.5, and PM10 exposure concentrations corresponded to elevated CVD risk, with HRs (95% CI) of 1.135 (1.078–1.195), 1.092 (1.062–1.123), and 1.075 (1.059–1.090), respectively. Mediation analyses further suggested that the correlation between PM exposure and CVD could be partly mediated via TyG-BMI, TyG-WC, and TyG-WHtR, with mediation proportions varying from 5.54 to 15.30%. Conclusion A significant correlation was observed between long-term PM exposure and increased CVD risk, with TyG-related indicators, such as TyG-BMI, TyG-WC, and TyG-WHtR, partially mediating this relationship.

Abstract Background Right aortic arch (RAA) is a common congenital aortic arch abnormality. Fetuses with RAA frequently have good outcomes after birth. However, chromosomal abnormalities and genetic syndromes suggest poor prognosis for these patients. So far the underlying genetic etiology is still not identified in most RAA patients based on traditional genetic techniques and a problem is still debated whether fetuses with isolated RAA should be referred for CMA. Our study aims to investigate the genetic etiology of fetuses with right aortic arch (RAA) by chromosomal microarray analysis (CMA) and whole exome sequencing (WES) and evaluate the efficacy of CMA in fetal isolated RAA. Results Among these 153 fetuses, 99 (64.7%) with isolated RAA and 54 (35.3%) with non-isolated RAA; 25.5% (39/153) with additional intracardiac anomalies (ICA), and 19.0% (29/153) with extracardiac anomalies (ECA). Tetralogy of Fallot (n = 10) and persistent left superior vena cava (n = 11) are the most common ICA and ECA, respectively. CMA detected 15 clinically significant copy number variations (CNVs) in 14 cases (9.2%); microdeletion of 22q11.21 was the most common pathogenic CNVs (7.8%). The chromosomal abnormalities rate was higher in non-isolated RAA and RAA with ICA groups than in isolated RAA group (16.7% vs. 5.1%; 20% vs. 5.1%, both p < 0.05). From five cases further undergoing WES, a diagnostic variant in MTOR gene (c.7255G > A, de novo) was first reported in prenatal, extending the prenatal manifestation of Smith–Kingsmore syndrome (OMIM: 616638); a clinically relevant variant c.3407A > T in STAG2 was identified, being inherited from the healthy mother. Moreover, the premature birth and termination rates were higher in non-isolated RAA group than in isolated RAA group (11.1% vs. 1.0%; 37.0% vs. 2.0%, both p < 0.01). Conclusions We demonstrate that CMA and WES are useful diagnostic tools for fetal RAA, particularly non-isolated RAA, and all fetuses with RAA should be referred for CMA. The data probably aids in prenatal diagnosis and prenatal counseling of fetal RAA.

In recent years, the issue of PM2.5-O3 compound pollution has become a significant global environmental concern. This study examines the spatial and temporal patterns of global PM2.5-O3 compound pollution and exposure risks, firstly at the global and urban scale, using spatial statistical regression, exposure risk assessment, and trend analyses based on the datasets of daily PM2.5 and surface O3 concentrations monitored in 120 cities around the world from 2019 to 2022. Additionally, on the basis of the common emission sources, spatial heterogeneity, interacting chemical mechanisms, and synergistic exposure risk levels between PM2.5 and O3 pollution, we proposed a synergistic PM2.5-O3 control framework for the joint control of PM2.5 and O3. The results indicated that: (1) Nearly 50% of cities worldwide were affected by PM2.5-O3 compound pollution, with China, South Korea, Japan, and India being the global hotspots for PM2.5-O3 compound pollution; (2) Cities with PM2.5-O3 compound pollution have exposure risk levels dominated by ST + ST (Stabilization) and ST + HR (High Risk). Exposure risk levels of compound pollution in developing countries are significantly higher than those in developed countries, with unequal exposure characteristics; (3) The selected cities showed significant positive spatial correlations between PM2.5 and O3 concentrations, which were consistent with the spatial distribution of the precursors NOx and VOCs; (4) During the study period, 52.5% of cities worldwide achieved synergistic reductions in annual average PM2.5 and O3 concentrations. The average PM2.5 concentration in these cities decreased by 13.97%, while the average O3 concentration decreased by 19.18%. This new solution offers the opportunity to construct intelligent and healthy cities in the upcoming low–carbon transition.

Abstract Ovarian cancer is an extremely malignant gynaecological tumour with a poor patient prognosis and is often associated with chemoresistance. Thus, exploring new therapeutic approaches to improving tumour chemosensitivity is important. The expression of transcription elongation factor B polypeptide 2 (TCEB2) gene is reportedly upregulated in ovarian cancer tumour tissues with acquired resistance, but the specific mechanism involved in tumour resistance remains unclear. In this study, we found that TCEB2 was abnormally highly expressed in cisplatin-resistant tumour tissues and cells. TCEB2 silencing also inhibited the growth and glycolysis of SKOV-3/cisplatin (DDP) and A2780/DDP cells. We further incubated human umbilical vein endothelial cells (HUVECs) with culture supernatants from cisplatin-resistant cells having TCEB2 knockdown. Results revealed that the migration, invasion, and angiogenesis of HUVECs were significantly inhibited. Online bioinformatics analysis revealed that the hypoxia-inducible factor-1A (HIF-1A) protein may bind to TCEB2, and TCEB2 silencing inhibited SKOV-3/DDP cell growth and glycolysis by downregulating HIF1A expression. Similarly, TCEB2 promoted HUVEC migration, invasion, and angiogenesis by upregulating HIF1A expression. In vivo experiments showed that TCEB2 silencing enhanced the sensitivity of ovarian cancer nude mice to cisplatin and that TCEB2 knockdown inhibited the glycolysis and angiogenesis of tumour cells. Our findings can serve as a reference for treating chemoresistant ovarian cancer.

Abstract Cis-dichlorodiammineplatinum(II) (CDDP), while widely utilized in tumor therapy, results in toxic side effects that patients find intolerable. The specific mechanism by which CDDP inflicts ovarian damage remains unclear. This study aimed to explore the involvement of ferrostatin-1 (FER-1) and ferroptosis in CDDP-induced ovarian toxicity. This study established models of CDDP-induced injury in granulosa cells (GCs) and rat model of premature ovarian failure (POF). CCK-8 assessed the effects of CDDP and FER-1 on GC viability. FerroOrange and Mito-FerroGreen, DCFH-DA and MitoSox-Red, Rhodamine 123 and Transmission electron microscopy (TEM) measured Fe2+, reactive oxygen species (ROS), mitochondrial membrane potential and the mitochondrial morphology in GC cells, respectively. Serum hormone levels; organ indices; malondialdehyde, superoxide dismutase, and glutathione analyses; and western blotting were performed to examine ferroptosis's role in vitro. Molecular docking simulation was evaluated the interaction between FER-1 and GPX4 or FER-1 and NRF2. Molecular docking simulations were conducted to evaluate the interactions between FER-1 and GPX4, as well as FER-1 and NRF2. The findings revealed that CDDP-induced ovarian toxicity involved iron accumulation, increased ROS accumulation, and mitochondrial dysfunction, leading to endocrine disruption and tissue damage in rats. These changes correlated with NRF2, HO-1, and GPX4 levels. However, FER-1 decreased the extent of ferroptosis. Thus, ferroptosis appears to be a crucial mechanism of CDDP-induced ovarian injury, with GPX4 as potential protective targets.

Abstract The large mid-infrared (MIR) spectral region, ranging from 2.5 µm to 25 µm, has remained under-exploited in the electromagnetic spectrum, primarily due to the absence of viable transceiver technologies. Notably, the 8–14 µm long-wave infrared (LWIR) atmospheric transmission window is particularly suitable for free-space optical (FSO) communication, owing to its combination of low atmospheric propagation loss and relatively high resilience to turbulence and other atmospheric disturbances. Here, we demonstrate a direct modulation and direct detection LWIR FSO communication system at 9.1 µm wavelength based on unipolar quantum optoelectronic devices with a unprecedented net bitrate exceeding 55 Gbit s−1. A directly modulated distributed feedback quantum cascade laser (DFB-QCL) with high modulation efficiency and improved RF-design was used as a transmitter while two high speed detectors utilizing meta-materials to enhance their responsivity are employed as receivers; a quantum cascade detector (QCD) and a quantum-well infrared photodetector (QWIP). We investigate system tradeoffs and constraints, and indicate pathways forward for this technology beyond 100 Gbit s−1 communication.

Abstract Background Exploring the physiological and molecular mechanisms underlying goat sexual maturation can enhance breeding practices and optimize reproductive efficiency and is therefore substantially important for practical breeding purposes. As an essential neuroendocrine organ in animals, the hypothalamus is involved in sexual development and other reproductive processes in female animals. Although microRNAs (miRNAs) have been identified as significant regulators of goat reproduction, there is a lack of research on the molecular regulatory mechanisms of hypothalamic miRNAs that are involved in the sexual development of goats. Therefore, we examined the dynamic changes in serum hormone profiles and hypothalamic miRNA expression profiles at four developmental stages (1 day (neonatal, D1, n = 5), 2 months (prepubertal, M2, n = 5), 4 months (sexual maturity, M4, n = 5), and 6 months (breeding period, M6, n = 5)) during sexual development in Jining grey goats. Results Transcriptome analysis revealed 95 differentially expressed miRNAs (DEMs) in the hypothalamus of goats across the four developmental stages. The target genes of these miRNAs were significantly enriched in the GnRH signalling pathway, the PI3K-Akt signalling pathway, and the Ras signalling pathway (P

Abstract The recent development of nanobiomaterials has shed some light on the field of periodontal tissue regeneration. Laponite (LAP), an artificially synthesized two-dimensional (2D) disk-shaped nanosilicate, has garnered substantial attention in regenerative biomedical applications owing to its distinctive structure, exceptional biocompatibility and bioactivity. This study endeavors to comprehensively evaluate the influence of LAP on periodontal regeneration. The effects of LAP on periodontal ligament cells (PDLCs) on osteogenesis, cementogenesis and angiogenesis were systematically assessed, and the potential mechanism was explored through RNA sequencing. The results indicated that LAP improved osteogenic and cementogenic differentiation of PDLCs, the regulatory effects of LAP on PDLCs were closely correlated with activation of PI3K-AKT signaling pathway. Moreover, LAP enhanced angiogenesis indirectly via manipulating paracrine of PDLCs. Then, LAP was implanted into rat periodontal defect to confirm its regenerative potential. Both micro-CT and histological analysis indicated that LAP could facilitate periodontal tissue regeneration in vivo. These findings provide insights into the bioactivity and underlying mechanism of LAP on PDLCs, highlighting it might be a potential therapeutic option in periodontal therapy.

Leaf economics spectrum (LES) describes the fundamental trade-offs between leaf structural, chemical, and physiological investments. Generally, structurally robust thick leaves with high leaf dry mass per unit area (LMA) exhibit lower photosynthetic capacity per dry mass (Amass). Paradoxically, “soft and thin-leaved” mosses and spikemosses have very low Amass, but due to minute-size foliage elements, their LMA and its components, leaf thickness (LT) and density (LD), have not been systematically estimated. Here, we characterized LES and associated traits in cryptogams in unprecedented details, covering five evolutionarily different lineages. We found that mosses and spikemosses had the lowest LMA and LT values ever measured for terrestrial plants. Across a broad range of species from different lineages, Amass and LD were negatively correlated. In contrast, Amass was only related to LMA when LMA was greater than 14 g cm−2. In fact, low Amass reflected high LD and cell wall thickness in the studied cryptogams. We conclude that evolutionarily old plant lineages attained poorly differentiated, ultrathin mesophyll by increasing LD. Across plant lineages, LD, not LMA, is the trait that represents the trade-off between leaf robustness and physiology in the LES.

Introduction: Sepsis-induced cardiac injury is the leading cause of death in patients. Recent studies have reported that reactive oxygen species (ROS)-mediated ferroptosis and macrophage-induced inflammation are the two main key roles in the process of cardiac injury. The combination of ferroptosis and inflammation inhibition is a feasible strategy in the treatment of sepsis-induced cardiac injury. Objectives: In the present study, ceria nanozyme coordination with curcumin (CeCH) was designed by a self-assembled method with human serum albumin (HSA) to inhibit ferroptosis and inflammation of sepsis-induced cardiac injury. Methods and results: The formed CeCH obtained the superoxide dismutase (SOD)-like and catalase (CAT)-like activities from ceria nanozyme to scavenge ROS, which showed a protective effect on cardiomyocytes in vitro. Furthermore, it also showed ferroptosis inhibition to reverse cell death from RSL3-induced cardiomyocytes, denoted from curcumin. Due to the combination therapy of ceria nanozyme and curcumin, the formed CeCH NPs could also promote M2 macrophage polarization to reduce inflammation in vitro. In the lipopolysaccharide (LPS)-induced sepsis model, the CeCH NPs could effectively inhibit ferroptosis, reverse inflammation, and reduce the release of pro-inflammatory factors, which markedly alleviated the myocardial injury and recover the cardiac function. Conclusion: Overall, the simple self-assembled strategy with ceria nanozyme and curcumin showed a promising clinical application for sepsis-induced cardiac injury by inhibiting ferroptosis and inflammation.

ABSTRACT: Objectives: The emergence of carbapenem-resistant Klebsiella pneumoniae presents significant health challenges. Here, we present the structural genome sequence of an NDM-5–producing K. pneumoniae (HZKP2) in China. Methods: Antimicrobial susceptibility tests were conducted via broth microdilution. Whole-genome sequencing was performed for genomic analysis. Wzi and capsular polysaccharide (KL) were analysed using Kaptive. Resistance genes, virulence factors, and comparative genomics analyses were also conducted. Multilocus sequence typing (MLST), replicons type, and core genome MLST analysis were further conducted using BacWGSTdb server. Results: HZKP2 was resistant to cefepime, ceftazidime, ciprofloxacin, ciprofloxacin, meropenem, and ertapenem. It harboured fosA, blaSHV-187, oqxA, oqxB, sul1, dfrA1, tet(A), floR, aph(6)-Id, aph(3′')-Ib, sul2, blaCTX-M-55, and blaNDM-5. Based on the RAST results, 5563 genes that belonged to 398 subsystems were annotated. The complete genome sequence of HZKP2 was characterized as ST1, wzi 19, and KL19, 5 five contigs totalling 5 654 446 bp, including one chromosome and four plasmids. Further analysis found that blaNDM-5 was located in a 46 161 bp IncX3 plasmid (pHZKP2-3). The genetic structure of blaNDM-5 gene was ISKox3-IS26-bleMBL-blaNDM-5-IS5-ISAb125-IS3000. Further analysis revealed that insertion sequences mediated the dissemination of blaNDM-5 from other species of Enterobacterales. Phylogenetic analysis showed that the closest relative was from a human stool specimen in China, which differed by 53 core genome MLST alleles. Conclusions: Our study provides the first structural perspective of the ST1 K. pneumoniae isolate producing NDM-5 in China. These results could provide valuable insights into the genetic characteristics, antimicrobial resistance mechanisms, and transmission dynamics of carbapenem-resistant K. pneumoniae in clinical settings.

Ecological restoration projects implemented over the past 20 years have substantially increased forest coverage in China, but the high tree mortality of new afforestation forest remains a challenging but unsolved problem. It is still not clear how much vegetation can be sustained by the forest lands with given water, energy and soil conditions, i.e., the carrying capacity for vegetation (CCV) of forest lands, which is the prerequisite for planning and implementing forest restoration projects. Here, we used a simplified method to evaluate the CCV across forest lands nationwide. Specifically, based on leaf area index (LAI) dataset, we use boosted regression tree and multiple linear regression model to analyze the CCV during 2001–2020 and 2021–2030 and explore the contribution of environmental factors. We find that there are three typical regions with lower CCV located in the Loess Plateau and the southern region of the Inner Mongolia Plateau, the Hengduan Mountain region, and the Tianshan Mountains. More importantly, the vegetation in the regions near the dry-wet climate transition zone show excess local carrying capacity for vegetation over the past two decades and they are more susceptible to potential climatic stress. In comparison, in the Greater Khingan Mountains and Hengduan Mountains, there is high potential to improve the forest growth. Temperature, precipitation and soil affects the CCV by shaping the vegetation in the optimal range. This indicates that more consideration should be given to restrictions of regional environmental constraints when planning afforestation and forest management. This study has important implications for guiding future forest scheme in China.

Pine Island Glacier (PIG), the largest glacier in the Amundsen Sea Embayment of West Antarctica, has contributed to over a quarter of the observed sea level rise around Antarctica. In recent years, multiple observations have confirmed its continuous retreat, ice flow acceleration and profound surface melt. Understanding these changes is crucial for accurately monitoring ice mass discharge and future Antarctic contributions to sea level rise. Therefore, it is essential to investigate the complex interactions between these variables to comprehend how they collectively affect the overall stability of the intricate PIG system. In this study, we utilized high-resolution remote sensing data and deep learning method to detect and analyze the spatio-temporal variations of surface melt, ice shelf calving, and ice flow velocity of the PIG from 2015 to 2023. We explored the correlations among these factors to understand their long-term impacts on the glacier's stability. Our findings reveal a retreat of 26.3 km and a mass loss of 1001.6 km2 during 2015–2023. Notably, extensive surface melting was observed, particularly in the 2016/2017 and 2019/2020 melting seasons. Satellite data vividly illustrate prolonged and intense melting periods, correlating with a significant retreat in the glacier's terminus position in 2019/2020. Furthermore, the comprehensive analysis of surface melting and the cumulative retreat of the ice shelf from 2017 to 2020 on the PIG shows a temporal relationship with subsequent significant changes in ice flow velocity, ranging from 10.9 to 12.2 m d−1, with an average acceleration rate of 12%. These empirical findings elucidate the intricate relationship among surface melt, ice flow velocity, and consequential glacier dynamics. A profound understanding of these interrelationships holds paramount importance in glacier dynamic changes and modeling, providing invaluable insights into potential glacier responses to global climate change.

Climatic factors are closely associated with the occurrence of vector-borne diseases, and they also influence the distribution of vectors. The occurrence of plague is closely related to the population dynamics of fleas and their host animals, as well as climatic conditions. This study focused on Xilingol League, utilizing climatic and flea index data from 2012 to 2021. Spearman correlation and ''Boruta'' importance analysis were conducted to screen for climatic variables. A generalized additive model (GAM) was employed to investigate the influence of climatic factors and rodent density on the flea index. GAM analysis revealed distinct trends in flea index among different rodent hosts. For Meriones unguiculatus, the flea index declined with increased density and with higher humidity, yet rose with greater lagged sunshine duration. For Spermophilus dauricus, an initial increase in flea index with density was observed, followed by a decrease, and a rise in the index was noted when ground temperatures were low. This study reveals the nonlinear interactions and lag effects among climatic factors, density, and flea index. Climatic factors and density variably influence the flea index of two Yersinia pestis hosts. This research advances the prediction and early warning efforts for plague control, providing a theoretical basis for rodent and flea eradication strategies.

Abstract Background Tuberculosis (TB) remains a serious global public health problem in China. The right knowledge, attitude, and practice (KAP) towards TB are indispensable to appropriate healthcare-seeking behaviors and treatment services timely. However, there are few studies that addressed the KAP towards TB in high-risk and under-developing regions in China. This study aims to evaluate the KAP towards TB in Ningxia Northwest, China, and identify factors that influence it. The findings can guide future health education and promotion interventions. Methods A stratified multistage random sampling method was used to conduct a face-to-face questionnaire survey with 33 items for selected residents. The composite score of Knowledge, Attitudes, and Practices (KAP) was divided into two groups, which are poor (scores below the average) and good (scores above the average). A two-level logistic model with a random intercept equation accounted for the similarity of residents within communities to examine the association between individual-level KAP and demographic and socioeconomic factors. Results A total of 2,341 residents were recruited, the mean age was 50, and 41.2% were female. The percentages of residents who were total awareness of TB knowledge and had positive attitudes and behavior toward TB were 51.9%, 75.3%, and 76.2%, respectively. The two-level logistic model demonstrated that residents with a high annual family income, urban living, primary school education or higher, occupation of teacher or doctor, a very good self-perceived status, medical insurance, knowing DOTS, and family members or friends with TB history had better knowledge of TB (P

Abstract Purpose To confirm which method provides lower rate of recurrent instability and superior clinical outcomes. Method We searched PubMed, Embase and Web of Science for the trials involving one intervention or both for patellar instability: medial patellofemoral ligament reconstruction (MPFLR) with and without tibial tubercle osteotomy (TTO). The postoperative Kujala score, Lysholm score, Tegner scores and the rate of recurrent instability (dislocation or subluxation) were analyzed as the primary clinical outcome parameters in a random or fixed effects meta-analysis. Results In total, 43 articles met inclusion criteria after full-text review. A total of 2046 patients were analyzed. The overall mean age was 20.3 years (range, 9.5–60.0 years), with a mean follow-up time of 3.2 years (range, 1–8 years). The mean Kujala scores in MPFLR and MPFLR + TTO were 89.04 and 84.44, respectively. There was significant difference in Kujala scores between MPFLR and MPFLR + TTO (MD = 4.60, 95%CI: 1.07–8.13; P = 0.01). The mean Lysholm scores in MPFLR and MPFLR + TTO were 90.59 and 88.14, respectively. There was no significant difference in Lysholm scores between MPFLR and MPFLR + TTO (MD = 2.45, 95%CI: -3.20-8.10; P = 0.40). The mean Tegner scores in MPFLR and MPFLR + TTO were 5.30 and 4.88, respectively. There was no significant difference in Tegner scores between MPFLR and MPFLR + TTO (MD = 0.42, 95%CI: -0.39-1.23; P = 0.31). At final follow-up, the rates of recurrent instability in MPFLR and MPFLR + TTO were 3% and 4%, respectively. There was no significant difference in the rates between MPFLR and MPFLR + TTO (OR = 0.99, 95%CI: 0.96–1.02; P = 0.4848). Conclusion MPFLR and MPFLR + TTO are effective and reliable treatments in the setting of patellofemoral instability. MPFLR seems to show a better performance in functional outcomes than MPFLR + TTO. Moreover, their rates of recurrent instability are very low, and no significant difference exists.

Abstract Deep learning models have been developed for various predictions in glioma; yet, they were constrained by manual segmentation, task-specific design, or a lack of biological interpretation. Herein, we aimed to develop an end-to-end multi-task deep learning (MDL) pipeline that can simultaneously predict molecular alterations and histological grade (auxiliary tasks), as well as prognosis (primary task) in gliomas. Further, we aimed to provide the biological mechanisms underlying the model’s predictions. We collected multiscale data including baseline MRI images from 2776 glioma patients across two private (FAHZU and HPPH, n = 1931) and three public datasets (TCGA, n = 213; UCSF, n = 410; and EGD, n = 222). We trained and internally validated the MDL model using our private datasets, and externally validated it using the three public datasets. We used the model-predicted deep prognosis score (DPS) to stratify patients into low-DPS and high-DPS subtypes. Additionally, a radio-multiomics analysis was conducted to elucidate the biological basis of the DPS. In the external validation cohorts, the MDL model achieved average areas under the curve of 0.892–0.903, 0.710–0.894, and 0.850–0.879 for predicting IDH mutation status, 1p/19q co-deletion status, and tumor grade, respectively. Moreover, the MDL model yielded a C-index of 0.723 in the TCGA and 0.671 in the UCSF for the prediction of overall survival. The DPS exhibits significant correlations with activated oncogenic pathways, immune infiltration patterns, specific protein expression, DNA methylation, tumor mutation burden, and tumor-stroma ratio. Accordingly, our work presents an accurate and biologically meaningful tool for predicting molecular subtypes, tumor grade, and survival outcomes in gliomas, which provides personalized clinical decision-making in a global and non-invasive manner.

Abstract Objective To develop and evaluate the predictive value of a simplified lung ultrasound (LUS) method for forecasting respiratory support in term infants. Methods This observational, prospective, diagnostic accuracy study was conducted in a tertiary academic hospital between June and December 2023. A total of 361 neonates underwent LUS examination within 1 h of birth. The proportion of each LUS sign was utilized to predict their respiratory outcomes and compared with the LUS score model. After identifying the best predictive LUS sign, simplified models were created based on different scan regions. The optimal simplified model was selected by comparing its accuracy with both the full model and the LUS score model. Results After three days of follow-up, 91 infants required respiratory support, while 270 remained healthy. The proportion of confluent B-lines demonstrated high predictive accuracy for respiratory support, with an area under the curve (AUC) of 89.1% (95% confidence interval [CI]: 84.5-93.7%). The optimal simplified model involved scanning the R/L 1–4 region, yielding an AUC of 87.5% (95% CI: 82.6-92.3%). Both the full model and the optimal simplified model exhibited higher predictive accuracy compared to the LUS score model. The optimal cut-off value for the simplified model was determined to be 15.9%, with a sensitivity of 76.9% and specificity of 91.9%. Conclusions The proportion of confluent B-lines in LUS can effectively predict the need for respiratory support in term infants shortly after birth and offers greater reliability than the LUS score model.

Abstract Background To explore the feasibility and effectiveness of a segmented sodium citrate solution anticoagulation strategy in patients receiving CRRT. Methods A prospective, randomized controlled study was conducted. Results According to the inclusion and exclusion criteria, 80 patients were included and randomly divided into two groups. Moreover, coagulation indices, liver function indices, renal function indices, and SOFA and APACHE II scores did not significantly differ between the two groups (P > 0.05). The coagulation grade of the venous ports in the experimental group was lower than that in the control group and the two groups of filters, but the difference was not statistically significant (P = 0.337). Both sodium citrate solution infusion methods maintained a low blood calcium concentration (0.25–0.45 mmol/L) in the peripheral circulation pathway, and no patient developed hypocalcaemia (

Abstract Many disease resistance genes have been introgressed into wheat from its wild relatives. However, reduced recombination within the introgressed segments hinders the cloning of the introgressed genes. Here, we have cloned the powdery mildew resistance gene Pm13, which is introgressed into wheat from Aegilops longissima, using a method that combines physical mapping with radiation-induced chromosomal aberrations and transcriptome sequencing analysis of ethyl methanesulfonate (EMS)-induced loss-of-function mutants. Pm13 encodes a kinase fusion protein, designated MLKL-K, with an N-terminal domain of mixed lineage kinase domain-like protein (MLKL_NTD domain) and a C-terminal serine/threonine kinase domain bridged by a brace. The resistance function of Pm13 is validated through transient and stable transgenic complementation assays. Transient over-expression analyses in Nicotiana benthamiana leaves and wheat protoplasts reveal that the fragment Brace-Kinase122-476 of MLKL-K is capable of inducing cell death, which is dependent on a functional kinase domain and the three α-helices in the brace region close to the N-terminus of the kinase domain.

Objective: To provide theoretical basis and basic research data for the technological development of inoculated Chinese traditional fermented fish, Mei yu, the effects of inoculated fermentation with Lactobacillus sake JXNU1-3 on the quality of Mei yu were investigated. Methods: The sensory evaluation, color, texture and composition of volatile flavor compounds of Mei yu prepared by traditional fermentation and inoculated fermentation with Lactobacillus sakei JXNU1-3 with different salt concentration during fermentation were compared by sensory evaluation, electronic nose, texture analyzer and solid phase micro-extraction and gas chromatography-mass spectrometry (SPEM/GC-MS). Result: It was showed that inoculated fermented Mei yu with a salt concentration of 2% and fermentation time of 3 days had better color, texture, and higher sensory score. The inoculated fermented Mei yu had lower response values to sulfides and methylated compounds compared with the traditional fermented Mei yu. Further, the main flavor substances and key flavor components of these two fermented fish samples were similar. However, compared with inoculated fermented Mei yu, isoamyl alcohol (sour odor) and 2-acetylpyrrole (musty odor) compounds were only detected in traditional fermented Mei yu. Conclusions: Compared with traditional fermentation, inoculated fermentation could reduce the corruption degree and improve the sensory quality of Mei yu, which indicated that Lactobacillus sakei JXNU1-3 could be used as a good starter culture for the development of inoculated fermentation technology of Mei yu.

Flood control operation, a non-engineering measure, can efficiently manage flood disasters within a river basin. However, numerous uncertainties exit in the real-time operation of flood control systems, creating risks in decision-making. As an efficient tool to mitigate these risks, risk management has garnered increasing attention in real-time flood control operation. This communication offers a series of suggestions for future research concerning risk management in real-time flood control operation, including risk assessment, risk diagnosis, and risk control methods.

Microfluidic technology utilizing the deterministic lateral displacement (DLD) method holds significant promise for efficiently separating micro-particles and biological cells. Despite the notable high throughput advantages associated with DLD chips, their widespread application is impeded by the substantial manufacturing costs of tens of thousands of micropillars. This study aims to explore the feasibility of employing the injection molding method for the mass production of DLD microfluidic chips. A multistage DLD chip with varied critical diameters was designed to isolate white blood cells from the human whole blood. The separation effectiveness was verified with the polydimethylsiloxane chip fabricated by standard soft lithography. Subsequently, nickel mold inserts were electroformed to fabricate thermoplastic DLD chips via the injection molding. The replication quality of micropillars under different molding parameters was studied. The capability of injection-molded chips to effectively achieve particle separation was validated. Results showed that thermoplastic chips with good replication quality were obtained, providing a scale-up production strategy for fabricating polymer-based microfluidic chips for disposable separation applications.

Objective: Distraction osteogenesis (DO) has been widely used to treat bone defects as its effectiveness in bone regeneration. Currently, distraction devices for establishing DO models are mainly developed for rats or large animals. However, a mouse DO model is in great need for in-depth mechanistic investigations using various transgenic mice. The current study reports the development of a reproducible murine DO model. Methods: A mini-titanium lengthener was designed and fabricated. The mini-lengthener was applied on the murine femur with four threaded pins using a designed clamp as the drilling and insertion guide. After transverse osteotomy using a Gigli saw, and after 5 days of latency, DO procedures started at 0.3 mm/day for 10 days, and the consolidation period was left for 28 days. The bone formation was monitored by radiography and histology. Potential effects on animal locomotion during DO were also measured by behavior tests. Results: Separated bone segments maintained good alignment during the entire DO phases. New bone formation was found as early as the end of the distraction phase. Active bone remodeling was found between the separated bone segments at late distraction and early consolidation phases. At the mature consolidation phase, bone remodeling was mainly observed in the contact cortical bone. Mice underwent DO procedure did not have significant impairment in their locomotion. Conclusion: We have successfully developed a murine femoral DO model, which may be used to study the biological processes of DO. We also developed the mini-lengthener and the guide clamp to ensure the standardization and reproducibility of the mouse DO model.The translational potential of this article: Current study reports the development of a murine femoral DO model. A well-established murine DO model will facilitate further investigations of the biological mechanisms of DO in various transgenic and normal mice.

Abstract Background The mortality rate and prognosis of short-term and long-term acute kidney injury (AKI) patients who undergo continuous renal replacement therapy (CRRT) are different. Setting up risk stratification tools for both short-term and long-term deaths is highly important for clinicians. Method A total of 1535 AKI patients receiving CRRT were included in this study, with 1144 from the training set (the Dryad database) and 391 from the validation set (MIMIC IV database). A model for predicting mortality within 10 and 90 days was built using nine different machine learning (ML) algorithms. AUROC, F1-score, accuracy, sensitivity, specificity, precision, and calibration curves were used to assess the predictive performance of various ML models. Results A total of 420 (31.1%) deaths occurred within 10 days, and 1080 (68.8%) deaths occurred within 90 days. The random forest (RF) model performed best in both predicting 10-day (AUROC: 0.80, 95% CI: 0.74–0.84; accuracy: 0.72, 95% CI: 0.67–0.76; F1-score: 0.59) and 90-day mortality (AUROC: 0.78, 95% CI: 0.73–0.83; accuracy: 0.73, 95% CI: 0.69–0.78; F1-score: 0.80). The importance of the feature shows that SOFA scores are rated as the most important risk factor for both 10-day and 90-day mortality. Conclusion Our study, utilizing multiple machine learning models, estimates the risk of short-term and long-term mortality among AKI patients who commence CRRT. The results demonstrated that the prognostic factors for short-term and long-term mortality are different. The RF model has the best prediction performance and has valuable potential for clinical application.

Abstract Background More and more studies showed that gut microbiota was closely related to the development of colorectal cancer (CRC). However, the specific pathway of gut microbiota regulating CRC development is still unknown. Methods We collected fecal samples from 14 CRC patients and 20 normal volunteers for 16 S sequencing analysis. At the same time, 14 CRC patients’ tumors and their adjacent tissues were collected for the detection of STING pathway related protein level. Mice were injected with azoxymethane (AOM) to establish an animal model of CRC, and antibiotics were given at the same time to evaluate the influence of gut microbiota on STING pathway and whether it was involved in regulating the tumor development of CRC mice. Results The sequencing results showed that compared with the normal group, the gut microbiota gut microbiota of CRC patients changed significantly at different species classification levels. At the level of genus, Akkermansia, Ligilactobacillus and Subdoligranulum increased the most in CRC patients, while Bacteroides and Dialister decreased sharply. The expression of STING-related protein was significantly down-regulated in CRC tumor tissues. Antibiotic treatment of CRC mice can promote the development of tumor and inhibit the activation of STING pathway. Conclusion Gut microbiota participates in CRC progress by mediating STING pathway activation.

Abstract Background Patients with chronic conditions need multiple medications daily to manage their condition. However, most patients have poor compliance, which affects the effectiveness of treatment. To address these challenges, we establish a medication reminder system for the intelligent generation of universal medication schedule (UMS) to remind patients with chronic diseases to take medication accurately and to improve safety of home medication. Methods To design medication time constraint with one drug (MTCOD) for each drug and medication time constraint with multi-drug (MTCMD) for each two drugs in order to better regulate the interval and time of patients’ medication. Establishment of a medication reminder system consisting of a cloud database of drug information, an operator terminal for medical staff and a patient terminal. Results The cloud database has a total of 153,916 pharmaceutical products, 496,708 drug interaction data, and 153,390 pharmaceutical product-ingredient pairs. The MTCOD data was 153,916, and the MTCMD data was 8,552,712. An intelligent UMS medication reminder system was constructed. The system can read the prescription information of patients and provide personalized medication guidance with medication timeline for chronic patients. At the same time, patients can query medication information and get remote pharmacy guidance in real time. Conclusions Overall, the medication reminder system provides intelligent medication reminders, automatic drug interaction identification, and monitoring system, which is helpful to monitor the entire process of treatment in patients with chronic diseases.

Abstract Microplastics (MPs) are defined as plastic particles smaller than 5 mm in size, and nanoplastics (NPs) are those MPs with a particle size of less than 1000 nm or 100 nm. The prevalence of MPs in the environment and human tissues has raised concerns about their potential negative effects on human health. Macrophages are the major defence against foreign substances in the intestine, and can be polarized into two types: the M1 phenotype and the M2 phenotype. However, the effect of NPs on the polarization of macrophages remains unclear. Herein, we selected polystyrene, one of the most plastics in the environment and controlled the particle sizes at 50 nm and 500 nm respectively to study the effects on the polarization of macrophages. We used mouse RAW264.7 cell line models in this macrophage-associated study. Experiments on cell absorption showed that macrophages could quickly ingest polystyrene nanoplastics of both diameters with time-dependent uptake. Compared to the untreated group and 10 μg/mL treatment group, macrophages exposed to 50 μg/mL groups (50 nm and 500 nm) had considerably higher levels of CD86, iNOS, and TNF-α, but decreased levels of aCD206, IL-10, and Arg-1. According to these findings, macrophage M1 and M2 polarization can both be induced and inhibited by 50 μg/mL 50 nm and 500 nm polystyrene nanoplastics. This work provided the first evidence of a possible MPs mode of action with appropriate concentration and size through the production of polarized M1, providing dietary and environmental recommendations for people, particularly those with autoimmune and autoinflammatory illnesses.

AIM: To describe the characteristics of peripapillary hyperreflective ovoid mass-like structure (PHOMS) in myopic children and to investigate factors associated with PHOMS. METHODS: This retrospective observational study included 101 eyes of 101 children (age ≤17y) with myopia. All included patients underwent comprehensive clinical examination. Optic nerve canal parameters, including disc diameter, optic nerve head (ONH) tilt angle, and border tissue angle were measured using serial enhanced-depth imaging spectral-domain optical coherence tomography (EDI-OCT). Based on the optic disc drusen consortium's definition of PHOMS, eyes were classified as PHOMS group and non-PHOMS group. PHOMS was categorized according to height. RESULTS: Sixty-seven (66.3%) eyes were found with PHOMS. Small PHOMS could only be detected by optical coherence tomography (OCT). Medium PHOMS could be seen with blurred optic disc borders corresponding to OCT. The most frequent location of PHOMS was at the nasosuperior (91%, 61 of 67 eyes) to ONH disc. The axial length and spherical equivalent were more myopic in the PHOMS group than in the non-PHOMS group (both P

Abstract Background Prostate cancer (PCa) is the second leading cause of tumor-related mortality in men. Metastasis from advanced tumors is the primary cause of death among patients. Identifying novel and effective biomarkers is essential for understanding the mechanisms of metastasis in PCa patients and developing successful interventions. Methods Using the GSE8511 and GSE27616 data sets, 21 metastasis-related genes were identified through the weighted gene co-expression network analysis (WGCNA) method. Subsequent functional analysis of these genes was conducted on the gene set cancer analysis (GSCA) website. Cluster analysis was utilized to explore the relationship between these genes, immune infiltration in PCa, and the efficacy of targeted drug IC50 scores. Machine learning algorithms were then employed to construct diagnostic and prognostic models, assessing their predictive accuracy. Additionally, multivariate COX regression analysis highlighted the significant role of POLD1 and examined its association with DNA methylation. Finally, molecular docking and immunohistochemistry experiments were carried out to assess the binding affinity of POLD1 to PCa drugs and its impact on PCa prognosis. Results The study identified 21 metastasis-related genes using the WGCNA method, which were found to be associated with DNA damage, hormone AR activation, and inhibition of the RTK pathway. Cluster analysis confirmed a significant correlation between these genes and PCa metastasis, particularly in the context of immunotherapy and targeted therapy drugs. A diagnostic model combining multiple machine learning algorithms showed strong predictive capabilities for PCa diagnosis, while a transfer model using the LASSO algorithm also yielded promising results. POLD1 emerged as a key prognostic gene among the metastatic genes, showing associations with DNA methylation. Molecular docking experiments supported its high affinity with PCa-targeted drugs. Immunohistochemistry experiments further validated that increased POLD1 expression is linked to poor prognosis in PCa patients. Conclusions The developed diagnostic and metastasis models provide substantial value for patients with prostate cancer. The discovery of POLD1 as a novel biomarker related to prostate cancer metastasis offers a promising avenue for enhancing treatment of prostate cancer metastasis.

Abstract Industrial The upgrading of industrial structure, as the main means of urban economic transformation, plays a crucial role in the process of achieving urban economic resilience construction. We conducted a study on the nonlinear impact mechanism of industrial structure upgrading on urban economic resilience based on panel data from 267 prefecture-level and above-level cities and above in China from 2008 to 2021, using globalization as a threshold variable. The obtained results demonstrated the following: (1) there existed a significant nonlinear relationship between industrial structure upgrading and rationalization and urban economic resilience, with a significant double threshold effect. (2) A robustness test was performed by removing extreme values from the sample, controlling for the time series and individual interaction terms while considering control variables, which did not change the basic conclusions based on the model. This demonstrated that the threshold regression model constructed in this study is robust and reliable. (3) From a regional heterogeneity perspective, the impact of industrial structure upgrading on urban economic resilience varied among different regions. Notably, industrial structure upgrading imposed a significant double threshold effect on urban economic resilience in the eastern and central regions, manifested as an inverted U-shaped trend. In the northeastern region, there was only a single threshold effect with globalization as the threshold variable, which still occurred on the left side of the inverted U-shaped curve, while no threshold effect was observed in the western region.

Abstract Objective To investigate the association between total sleep duration variability and stroke in the middle-aged and elderly population in China. Methods Data were collected from the 2011, 2013, 2015, and 2018 surveys of the China Health and Retirement Longitudinal Study (CHARLS). A total of 3485 participants, who had not experienced a stroke until 2015 and completed the follow-up in 2018, were enrolled to analyze the relationship between total sleep duration variability and new stroke. Total sleep duration was calculated by summing self-reported nocturnal sleep duration and daytime napping. The variability was determined by calculating the standard deviation (SD) of total sleep duration across the first three waves. A binary logistic regression model was utilized to analyze this association. Results Of the 3485 participants, 183 (5.25%) sustained a stroke event. A dose-response relationship was observed, indicating an increased stroke risk of 0.2 per unit (hours) increase in total sleep duration variability [OR (95% CI): 1.20 (1.01–1.42)]. Upon stratification by sex groups, this increased risk was significant only in men [OR (95% CI): 1.44 (1.12–1.83)]. Conclusion Increased total sleep duration variability was associated with an increased risk of stroke in the middle-aged and elderly, independent of factors such as age, nocturnal sleep duration, napping habits, region of residence, hypertension, diabetes mellitus, dyslipidemia, BMI, smoking, drinking habits, and marital status. However, a more notable correlation was observed in males.

Abstract Objectives This study was designed to explore and validate the value of different machine learning models based on ultrasound image-omics features in the preoperative diagnosis of lymph node metastasis in pancreatic cancer (PC). Methods This research involved 189 individuals diagnosed with PC confirmed by surgical pathology (training cohort: n = 151; test cohort: n = 38), including 50 cases of lymph node metastasis. Image-omics features were extracted from ultrasound images. After dimensionality reduction and screening, eight machine learning algorithms, including logistic regression (LR), support vector machine (SVM), K-nearest neighbors (KNN), random forest (RF), extra trees (ET), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multilayer perceptron (MLP), were used to establish image-omics models to predict lymph node metastasis in PC. The best omics prediction model was selected through ROC curve analysis. Machine learning models were used to analyze clinical features and determine variables to establish a clinical model. A combined model was constructed by combining ultrasound image-omics and clinical features. Decision curve analysis (DCA) and a nomogram were used to evaluate the clinical application value of the model. Results A total of 1561 image-omics features were extracted from ultrasound images. 15 valuable image-omics features were determined by regularization, dimension reduction, and algorithm selection. In the image-omics model, the LR model showed higher prediction efficiency and robustness, with an area under the ROC curve (AUC) of 0.773 in the training set and an AUC of 0.850 in the test set. The clinical model constructed by the boundary of lesions in ultrasound images and the clinical feature CA199 (AUC = 0.875). The combined model had the best prediction performance, with an AUC of 0.872 in the training set and 0.918 in the test set. The combined model showed better clinical benefit according to DCA, and the nomogram score provided clinical prediction solutions. Conclusion The combined model established with clinical features has good diagnostic ability and can be used to predict lymph node metastasis in patients with PC. It is expected to provide an effective noninvasive method for clinical decision-making, thereby improving the diagnosis and treatment of PC.

Abstract Climate change leads to permafrost thawing, accelerating carbon emissions increases, challenges the goal of climate change mitigation. However, it remains unknown whether implementing ecological restoration projects in Alpine areas can offset the adverse effects of permafrost thawing locally. Here we took the Qinghai‒Tibet Plateau as an example to explore this issue based on the improved Biome-BGCMuSo model. We found future climate change-induced permafrost thawing will decrease carbon sink. Projects’ carbon sink enhancement could fully counteract the permafrost thawing-induced carbon loss. Additionally, future warmer and wetter climates will enlarge the suitable area for restoration. If these areas are taken into account, carbon sink attributable to Projects will further increase. These results indicate that ERPs have the potential to combat future permafrost thawing-induced carbon loss, and their contribution will be further amplified by future climate change.

To explore the impact of ursodeoxycholic acid (UDCA) on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and clinical outcomes in patients with autoimmune liver disease (AILD). Patients diagnosed with AILD were enrolled and divided into a UDCA group and a non-UDCA group based on whether they received UDCA treatment. Relevant data were collected regarding AILD diagnosis, treatment, biochemical indicators, and imaging examination. The incidence of SARS-CoV-2 infection and the prognosis of AILD patients were observed. A total of 1,138 patients completed follow-up. The usage rate of hormone (P = 0.003) and immunosuppressant (P = 0.001) used for treating AILD in the non-UDCA group was markedly lower than in the UDCA group. The UDCA usage rate was markedly lower in SARS-CoV-2 infected patients than in uninfected patients (P = 0.003). The rate of SARS-CoV-2 infection in the non-UDCA group was significantly higher than in the UDCA group (P = 0.018). Logistic regression analysis showed that UDCA use (P = 0.003) was correlated to a lower incidence of SARS-CoV-2, while immunosuppressant use (P = 0.017) increased the incidence. Recovery time from SARS-CoV-2 infection was markedly longer for those receiving UDCA treatment than those in the non-UDCA group (P = 0.018). UDCA is associated with low SARS-CoV-2 incidence in AILD patients, while immunosuppressant increases its incidence instead. Patients receiving UDCA treatment have a longer recovery time after being infected.

Abstract Due to the limitations of single-model tumor therapeutic strategies, multimodal combination therapy have become a more favorable option to enhance efficacy by compensating for its deficiencies. However, in nanomaterial-based multimodal therapeutics for tumors, exploiting synergistic interactions and cascade relationships of materials to achieve more effective treatments is still a great challenge. Based on this, we constructed a nanoplatform with a “triple-linkage” effect by cleverly integrating polydopamine (PDA), silver nanoparticles (AgNPs), and glucose oxidase (GOx) to realize enhanced photothermal therapy (PTT) and activatable metal ion therapy (MIT) for hepatocellular carcinoma (HCC) treatment. First, the non-radiative conversion of PDA under light conditions was enhanced by AgNPs, which directly enhanced the photothermal conversion efficiency of PDA. In addition, GOx reduced the synthesis of cellular heat shock proteins by interfering with cellular energy metabolism, thereby enhancing cellular sensitivity to PTT. On the other hand, H2O2, a by-product of GOx-catalyzed glucose, could be used as an activation source to activate non-toxic AgNPs to release cytotoxic Ag+, achieving activatable Ag+-mediated MIT. In conclusion, this nanosystem achieved efficient PTT and MIT for HCC by exploiting the cascade effect among PDA, AgNPs, and GOx, providing a novel idea for the design of multimodal tumor therapeutic systems with cascade regulation. Graphical abstract

Abstract With the goal of achieving carbon neutrality, active distribution networks (DNs) with a high proportion of photovoltaics (PVs) are facing challenges in maintaining voltage stability and low‐carbon operation. Energy storage systems (ESSs), which have the ability to store and transfer energy temporarily, can be used as effective measures to enhance the capacity of consuming PVs and reduce carbon emissions in DNs. However, existing low‐carbon dispatch strategies for multiple sources, storages and loads fail to consider voltage violations, while the temporal carbon emission intensity of the upper‐level power grid is also often overlooked, which is an important factor that affects the dispatch strategy. Therefore, a two‐stage self‐adaptive dispatch strategy of ESSs that considers the temporal characteristics of slack nodal carbon emission intensity to minimise carbon emissions while maintaining voltage stability in DNs with high access to PVs is proposed. First, the framework of the proposed two‐stage self‐adaptive dispatch strategy of ESSs is established by taking into account the effects of ESSs on adjusting voltages and reducing carbon emissions, respectively, with the two‐stage switch principle of two operation modes being determined. On this basis, an optimization dispatch model is established to improve voltages and carbon emissions, and the optimal day‐ahead dispatch strategy of ESSs can be obtained by solving the model using genetic algorithm. Case studies of the modified 10 kV IEEE 33‐node DN and IEEE 123‐node DN verify the feasibility and superiority of the proposed two‐stage self‐adaptive security and low‐carbon day‐ahead dispatch strategy for ESSs, showing that the voltage stabilisation and lower carbon emissions of DNs are both improved.

Abstract The central nervous system (CNS) is the most delicate system in human body, with the most complex structure and function. It is vulnerable to trauma, infection, neurodegeneration and autoimmune diseases, and activates the immune system. An appropriate inflammatory response contributes to defence against invading microbes, whereas an excessive inflammatory response can aggravate tissue damage. The NLRP3 inflammasome was the first one studied in the brain. Once primed and activated, it completes the assembly of inflammasome (sensor NLRP3, adaptor ASC, and effector caspase-1), leading to caspase-1 activation and increased release of downstream inflammatory cytokines, as well as to pyroptosis. Cumulative studies have confirmed that NLRP3 plays an important role in regulating innate immunity and autoimmune diseases, and its inhibitors have shown good efficacy in animal models of various inflammatory diseases. In this review, we will briefly discuss the biological characteristics of NLRP3 inflammasome, summarize the recent advances and clinical impact of the NLRP3 inflammasome in infectious, inflammatory, immune, degenerative, genetic, and vascular diseases of CNS, and discuss the potential and challenges of NLRP3 as a therapeutic target for CNS diseases.

Background: Ischaemic stroke can lead to many complications, but treatment options are limited. Icariin is a traditional Chinese medicine with reported neuroprotective effects against ischaemic cerebral injury; however, the underlying mechanisms by which icariin ameliorates cell apoptosis require further study. Purpose: This study aimed to investigate the therapeutic potential of icariin after ischaemic stroke and the underlying molecular mechanisms. Methods: N2a neuronal cells were used to create an in vitro oxygen-glucose deprivation (OGD) model. The effects of icariin on OGD cells were assessed using the CCK-8 kit to detect the survival of cells and based on the concentration, apoptosis markers, inflammation markers, and M2 pyruvate kinase isoenzyme (PKM2) expression were detected using western blotting, RT-qPCR, and flow cytometry. To investigate the underlying molecular mechanisms, we used the PKM2 agonist TEPP-46 and detected apoptosis-related proteins. Results: We demonstrated that icariin alleviated OGD-induced apoptosis in vitro. The expression levels of the apoptosis marker proteins caspase-3 and Bax were upregulated and Bcl-2 was downregulated. Furthermore, icariin reduced inflammation and downregulated the expression of PKM2. Moreover, activation of the PKM2 by pretreatment with the PKM2 agonist TEPP-46 enhanced the effects on OGD induced cell apoptosis in vitro. Conclusion: This study elucidated the underlying mechanism of PKM2 in OGD-induced cell apoptosis and highlighted the potential of icariin in the treatment of ischaemic stroke.