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Abstract Objectives To develop an innovative magnetic resonance imaging (MRI)-based PUMCH (Peking Union Medical College Hospital) classification system aimed at standardising the diagnosis of congenital cervical malformations (CCMs) by identifying their distinctive MRI features. Methods Seventy-nine consecutive patients with CCM underwent pre-treatment pelvic MRI; three experienced gynaecological radiologists retrospectively analysed these images. Qualitative assessments included Rock et al’s classification; PUMCH classification; haematometra; cervical signal features; ovarian endometriosis; haematosalpinx; and uterine, vaginal, urinary, and musculoskeletal malformations. Quantitative assessments involved the uterine volume, sagittal cervical length, and maximum ovarian cross-sectional area. The surgical treatment types were also recorded. Statistical methods were used to incorporate differences in clinical features and surgical methods into our classification. Results Morphologically, CCMs were categorised into three types: type I (53%) was characterised by the presence of a cervix with visible cervical canals; type II (23%) featured an existing cervix with concealed cervical canals; and type III (24%) indicated cervical aplasia, which involves a blind end in the lower part of the uterine corpus. Haematometra was significantly more prevalent in patients with type I CCM than in those with type II (p

Abstract With the flourishing of spatial omics technologies, alignment and stitching of slices becomes indispensable to decipher a holistic view of 3D molecular profile. However, existing alignment and stitching methods are unpractical to process large-scale and image-based spatial omics dataset due to extreme time consumption and unsatisfactory accuracy. Here we propose SANTO, a coarse-to-fine method targeting alignment and stitching tasks for spatial omics. SANTO firstly rapidly supplies reasonable spatial positions of two slices and identifies the overlap region. Then, SANTO refines the positions of two slices by considering spatial and omics patterns. Comprehensive experiments demonstrate the superior performance of SANTO over existing methods. Specifically, SANTO stitches cross-platform slices for breast cancer samples, enabling integration of complementary features to synergistically explore tumor microenvironment. SANTO is then applied to 3D-to-3D spatiotemporal alignment to study development of mouse embryo. Furthermore, SANTO enables cross-modality alignment of spatial transcriptomic and epigenomic data to understand complementary interactions.

Abstract We study a nearly critical superfluid system from two complementary approaches. Within the first approach, we formulate a Schwinger-Keldysh effective field theory (EFT) for the system when it is located slightly above the critical temperature. The dynamical variables in the EFT construction are two scalars: a neutral scalar associated with the conserved U(1) charge, and a complex scalar describing the order parameter. The set of symmetries, particularly the dynamical Kubo-Martin-Schwinger (KMS) symmetry and chemical shift symmetry, strictly constrains the form of EFT action. Within the second approach, using the holographic Schwinger-Keldysh technique, we derive the effective action for a “microscopic” holographic superfluid, confirming the EFT construction. A systematic inclusion of non-Gaussianity is one highlight of present study.

In order to establish the standard preparation methodology for bioactive polysaccharide of fucoidan, this study carried out the research of preparation method of fucoidan from Saccharina japonica. Three extraction methods, high temperature pressure extraction (HPE), acid extraction (AE), and microwave extraction at 400 W (M400 W), 500 W (M500 W), and 600 W (M600 W) were selected. Subsequently, two precipitation methods, calcium chloride precipitation (CP) and ethanol precipitation (GAP) were used to remove alginate followed by finally precipitation of fucoidan with high concentration ethanol. Fucoidan extracts prepared in totally ten different conditions were collected, of which the contents of total sugar, total phenols, protein, uronic acid, and sulfate groups were analyzed. Meanwhile their antioxidant activities including Fe3+ reduction ability, ABTS+ and DPPH free radical scavenging ability were determined. The correlation analysis was conducted based on the above determined results to discover the relationship between preparation methods and fucoidan qualities. Accordingly, the preparation methods for fucoidan of high yield, high purity, and excellent antioxidant activities were selected. Results showed that the yields of fucoidan by acid extraction with calcium precipitation (AE-CP) and microwave extraction with calcium precipitation (M400 W-CP, M500 W-CP, M600 W-CP) were 3.821%, 3.516%, 3.376%, and 2.998%, respectively. Meanwhile, the sulfate content was 17.734%, 23.872%, 23.376%, and 22.149%, respectively. Their protein and total phenol content were below 1%, the uronic acid content was below 10%, and the Trolox equivalent (ABTS+ radical scavenging ability) was 5.637, 5.336, 6.567, and 5.616 μg/mg, respectively. Thus, the above four preparation conditions were ideal for processing of fucoidan, among which the method of microwave extraction followed by calcium precipitation showed advantages of short processing time and low solvent consumption that met the requirement of the environmental-friendly processing. This study systematically investigated the effects of preparation methods on the yield and quality of fucoidan, which provided a practical preparation methodology for fucoidan from Saccharina japonica with high yield, purity and antioxidant activity.

Abstract Recent advancements in genome assembly have greatly improved the prospects for comprehensive annotation of Transposable Elements (TEs). However, existing methods for TE annotation using genome assemblies suffer from limited accuracy and robustness, requiring extensive manual editing. In addition, the currently available gold-standard TE databases are not comprehensive, even for extensively studied species, highlighting the critical need for an automated TE detection method to supplement existing repositories. In this study, we introduce HiTE, a fast and accurate dynamic boundary adjustment approach designed to detect full-length TEs. The experimental results demonstrate that HiTE outperforms RepeatModeler2, the state-of-the-art tool, across various species. Furthermore, HiTE has identified numerous novel transposons with well-defined structures containing protein-coding domains, some of which are directly inserted within crucial genes, leading to direct alterations in gene expression. A Nextflow version of HiTE is also available, with enhanced parallelism, reproducibility, and portability.

Abstract Hybrid mapping is a powerful approach to efficiently identify and characterize genes regulated through mechanisms in cis. In this study, using reciprocal crosses of the phenotypically divergent Duroc and Lulai pig breeds, we perform a comprehensive multi-omic characterization of regulatory variation across the brain, liver, muscle, and placenta through four developmental stages. We produce one of the largest multi-omic datasets in pigs to date, including 16 whole genome sequenced individuals, as well as 48 whole genome bisulfite sequencing, 168 ATAC-Seq and 168 RNA-Seq samples. We develop a read count-based method to reliably assess allele-specific methylation, chromatin accessibility, and RNA expression. We show that tissue specificity was much stronger than developmental stage specificity in all of DNA methylation, chromatin accessibility, and gene expression. We identify 573 genes showing allele specific expression, including those influenced by parent-of-origin as well as allele genotype effects. We integrate methylation, chromatin accessibility, and gene expression data to show that allele specific expression can be explained in great part by allele specific methylation and/or chromatin accessibility. This study provides a comprehensive characterization of regulatory variation across multiple tissues and developmental stages in pigs.

Abstract The dynamics of proteins are crucial for understanding their mechanisms. However, computationally predicting protein dynamic information has proven challenging. Here, we propose a neural network model, RMSF-net, which outperforms previous methods and produces the best results in a large-scale protein dynamics dataset; this model can accurately infer the dynamic information of a protein in only a few seconds. By learning effectively from experimental protein structure data and cryo-electron microscopy (cryo-EM) data integration, our approach is able to accurately identify the interactive bidirectional constraints and supervision between cryo-EM maps and PDB models in maximizing the dynamic prediction efficacy. Rigorous 5-fold cross-validation on the dataset demonstrates that RMSF-net achieves test correlation coefficients of 0.746 ± 0.127 at the voxel level and 0.765 ± 0.109 at the residue level, showcasing its ability to deliver dynamic predictions closely approximating molecular dynamics simulations. Additionally, it offers real-time dynamic inference with minimal storage overhead on the order of megabytes. RMSF-net is a freely accessible tool and is anticipated to play an essential role in the study of protein dynamics.

Abstract Large language models (LLMs) are seen to have tremendous potential in advancing medical diagnosis recently, particularly in dermatological diagnosis, which is a very important task as skin and subcutaneous diseases rank high among the leading contributors to the global burden of nonfatal diseases. Here we present SkinGPT-4, which is an interactive dermatology diagnostic system based on multimodal large language models. We have aligned a pre-trained vision transformer with an LLM named Llama-2-13b-chat by collecting an extensive collection of skin disease images (comprising 52,929 publicly available and proprietary images) along with clinical concepts and doctors’ notes, and designing a two-step training strategy. We have quantitatively evaluated SkinGPT-4 on 150 real-life cases with board-certified dermatologists. With SkinGPT-4, users could upload their own skin photos for diagnosis, and the system could autonomously evaluate the images, identify the characteristics and categories of the skin conditions, perform in-depth analysis, and provide interactive treatment recommendations.

Abstract During early embryonic development, the transition from totipotency to pluripotency is a fundamental and critical process for proper development. However, the regulatory mechanisms governing this transition remain elusive. Here, we conducted a comprehensive genome-wide CRISPR/Cas9 screen to investigate the 2-cell-like cells (2CLCs) phenotype in mouse embryonic stem cells (mESCs). This effort led to the identification of ten regulators that play a pivotal role in determining cell fate during this transition. Notably, our study revealed Mdm2 as a significant negative regulator of 2CLCs, as perturbation of Mdm2 resulted in a higher proportion of 2CLCs. Mdm2 appears to influence cell fate through its impact on cell cycle progression and H3K27me3 epigenetic modifications. In summary, the results of our CRISPR/Cas9 screen have uncovered several genes with distinct functions in regulating totipotency and pluripotency at various levels, offering a valuable resource for potential targets in future molecular studies.

Objective: To improve the contents of various hypoglycemic components in natural mulberry leaves, different fermentation-promoting substances were added to mulberry leaf shoots during their fermentation by means of that drawn on the experience of traditional black tea fermentation process. Method: Based on the single factor experiments, orthogonal optimization test was carried out to determine the optimal addition amount using cellulase, pectinase and tea polyphenols as influencing factors, and the contents of total alkaloids, total flavonoids and total polysaccharides in mulberry leaves as comprehensive evaluation indicators. Results: Compared with natural fermentation, the contents of total alkaloids, total flavonoids and total polysaccharides in mulberry leaves fermented by additives were increased by 61.84%, 45.02% and 28.68%, when the addition amounts of cellulase, pectinase and tea polyphenols were 0.6%, 0.8% and 0.9%, respectively. And their contents were 115.12%, 80.19% and 54.81% higher than those in natural mulberry leaves, respectively. Conclusion: The contents of hypoglycemic components in natural mulberry leaves can be improved by adding substances that promote fermentation, which lays a foundation for its subsequent effective utilization in hypoglycemia.

Excessive underground train-induced vibration becomes a serious environmental problem in cities. To investigate the vibration transfer from an underground train to a building nearby, an explicit-integration time-domain, three-dimensional finite element model is developed. The underground train, track, tunnel, soil layers and a typical multi-story building nearby are all fully coupled in this model. The complex geometries involving the track components and the building are all modelled in detail, which makes the simulation of vibration transfer more realistic from the underground train to the building. The model is validated with in-situ tests data and good agreements have been achieved between the numerical results and the experimental results both in time domain and frequency domain. The proposed model is applied to investigate the vibration transfer along the floors in the building and the influences of the soil stiffness on the vibration characteristics of the track-tunnel-soil-building system. It is found that the building vibration induced by an underground train is dominant at the frequency determined by the P2 resonance and influenced by the vibration modes of the building. The vertical vibration in the building decreases in a fluctuant pattern from the foundation to the top floor due to loss of high frequency contents and local modes. The vibration levels in different rooms at a same floor can be different due to the different local stiffness. A room with larger space thus smaller local stiffness usually has higher vibration level. Softer soil layers make the tunnel lining and the building have more low frequency vibration. The influence of the soil stiffness on the amplification scale along the floors of the building is found to be nonlinear and frequency-dependent, which needs to be further investigated.

Abstract Ulcerative colitis (UC) is characterized by an abnormal immune response, and the pathogenesis lacks clear understanding. The cGAS-STING pathway is an innate immune signaling pathway that plays a significant role in various pathophysiological processes. However, the role of the cGAS-STING pathway in UC remains largely unclear. In this study, we obtained transcriptome sequencing data from multiple publicly available databases. cGAS-STING related genes were obtained through literature search, and differentially expressed genes (DEGs) were analyzed using R package limma. Hub genes were identified through protein–protein interaction (PPI) network analysis and module construction. The ConsensuClusterPlus package was utilized to identify molecular subtypes based on hub genes. The therapeutic response, immune microenvironment, and biological pathways of subtypes were further investigated. A total of 18 DEGs were found in UC patients. We further identified IFI16, MB21D1 (CGAS), TMEM173 (STING) and TBK1 as the hub genes. These genes are highly expressed in UC. IFI16 exhibited the highest diagnostic value and predictive value for response to anti-TNF therapy. The expression level of IFI16 was higher in non-responders to anti-TNF therapy. Furthermore, a cluster analysis based on genes related to the cGAS-STING pathway revealed that patients with higher gene expression exhibited elevated immune burden and inflammation levels. This study is a pioneering analysis of cGAS-STING pathway-related genes in UC. These findings provide new insights for the diagnosis of UC and the prediction of therapeutic response.

Phenotypic differences between diploid parents and their allotriploid offspring are common in aquaculture breeding. Some allotriploid populations exhibit rapid growth rates and increased body weight, which are significant for supporting fisheries development. Understanding the genetic mechanisms underlying these traits is crucial for implementing diverse breeding strategies to achieve high production in fish farming. Here, we collected the following fish species for our study: red crucian carp (Carassius auratus red var., 2nRR), common carp (Cyprinus carpio L., 2nCC), and two allotriploids (3nR2C and 3 nRC2). These allotriploids were obtained through backcrossing an allotetraploid of C. auratus red var. × C. carpio L. (4nR2C2, ♂) with C. auratus red var. and C. carpio L. (♀), respectively. These allotriploids demonstrated faster growth rates compared to their diploid inbred parents, contributing to the Chinese fisheries industry for several decades. We conducted a systematic comparison of mitochondrial DNA (mtDNA) copy numbers in the liver and muscle tissues of 2nRR, 2nCC, 3nR2C, and 3 nRC2 under different seasons. When entering winter (low water temperature: 13 °C), the triploid fish (3nR2C and 3 nRC2) exhibited lower mtDNA copy numbers in the muscle, indicating a reduction in individual activity and energy expenditure to facilitate weight maintenance when food availability is limited. Furthermore, we analysed the expression levels of three nuclear-regulated mitochondrial genes (tfam, tfb1m, and tfb2m) and observed an imbalance of allelic expression in tfam and tfb1m in the two triploid fish. These findings enhance our understanding of the molecular regulatory mechanisms underlying growth trait differences among fish with different ploidy levels.

The Dongsheng Coalfield in Ordos is a Jurassic coal bearing formation, and the 2-2 and 3-1 coal seams in many deep mining areas can be mined in the whole area, and the spacing of coal seams is small. This paper takes Yingpanhao Coal Mine as a geological prototype, and constructs a numerical model of the research area through FLAC3D and UDEC numerical simulation software to study the surface movement deformation and the evolution law of stress field caused by mining coal seams 2-2 and 3-1. The results show that repeated mining in multiple coal seams will cause the central projection of the subsidence basin to move toward the direction of lower coal seam, and then approach the central projection of the initial mining of the upper coal seam, and ultimately cross it; after the two coal seams were continuously mined, the maximum subsidence value of the surface is less than the sum of the maximum subsidence values caused by mining the two coal seams separately, and the subsidence coefficient of the coal seam repeated mining is less than the initial mining subsidence coefficient; coal pillar dislocation is closely related to surface movement parameters, the staggered coefficient is related to the surface subsidence coefficient, horizontal movement coefficient, and the tangent of the main influencing angle in a logarithmic normal function, concave parabolic function, and convex parabolic function, respectively; as common factors, pillar staggered distance and width-depth ratio have coupling effects on the ratio of characteristic parameters of primary mining and repeated mining in coal seam; in addition, with the increase of pillar staggered distance, the surface subsidence basin area decreases first and then increases, and the contours of horizontal movement near the basin evolve from ellipse to shuttle; the optimal staggered distance of multi-coal seam mining in this study area is 30 m based on the empirical formula of pressure relief distance, the surface damage degree and the relief effect of staggered mining.

Abstract Background Obesity is a global public health concern linked to chronic diseases such as cardiovascular disease and type 2 diabetes (T2D). Emerging evidence suggests that epigenetic modifications, particularly DNA methylation, may contribute to obesity. However, the molecular mechanism underlying the longitudinal change of BMI has not been well-explored, especially in East Asian populations. Methods This study performed a longitudinal epigenome-wide association analysis of DNA methylation to uncover novel loci associated with BMI change in 533 individuals across two Chinese cohorts with repeated DNA methylation and BMI measurements over four years. Results We identified three novel CpG sites (cg14671384, cg25540824, and cg10848724) significantly associated with BMI change. Two of the identified CpG sites were located in regions previously associated with body shape and basal metabolic rate. Annotation of the top 20 BMI change-associated CpGs revealed strong connections to obesity and T2D. Notably, these CpGs exhibited active regulatory roles and located in genes with high expression in the liver and digestive tract, suggesting a potential regulatory pathway from genome to phenotypes of energy metabolism and absorption via DNA methylation. Cross-sectional and longitudinal EWAS comparisons indicated different mechanisms between CpGs related to BMI and BMI change. Conclusion This study enhances our understanding of the epigenetic dynamics underlying BMI change and emphasizes the value of longitudinal analyses in deciphering the complex interplay between epigenetics and obesity.

Abstract Background Aldehyde dehydrogenases (ALDHs) are a family of enzymes that catalyze the oxidation of aldehyde molecules into the corresponding carboxylic acid, regulate the balance of aldehydes and protect plants from the poisoning caused by excessive accumulation of aldehydes; however, this gene family has rarely been studied in cotton. Results In the present study, genome-wide identification was performed, and a total of 114 ALDH family members were found in three cotton species, Gossypium hirsutum, Gossypium arboreum and Gossypium raimondii. The ALDH genes were divided into six subgroups by evolutionary analysis. ALDH genes in the same subgroup showed similar gene structures and conserved motifs, but some genes showed significant differences, which may result in functional differences. Chromosomal location analysis and selective pressure analysis revealed that the ALDH gene family had experienced many fragment duplication events. Cis-acting element analysis revealed that this gene family may be involved in the response to various biotic and abiotic stresses. The RT‒qPCR results showed that the expression levels of some members of this gene family were significantly increased under salt stress conditions. Gohir.A11G040800 and Gohir.D06G046200 were subjected to virus-induced gene silencing (VIGS) experiments, and the sensitivity of the silenced plants to salt stress was significantly greater than that of the negative control plants, suggesting that Gohir.A11G040800 and Gohir.D06G046200 may be involved in the response of cotton to salt stress. Conclusions In total, 114 ALDH genes were identified in three Gossypium species by a series of bioinformatics analysis. Gene silencing of the ALDH genes of G. hirsutum revealed that ALDH plays an important role in the response of cotton to salt stress.

Abstract Wind is the most important external force in shaping aeolian landforms. Yet, it remains unclear what role the strong-wind events will play in the development of aeolian landforms compared with the effect of regular winds. A fundamental question is, what are the contributions of different wind speed levels to the deformation of aeolian landforms. Here, through in situ measurements of high-sampling-rate wind data and high-resolution topographic data, we analyzed short-term strong-wind events at different levels and monitored the rapid migration of barchan dunes, enabling us to provide a first report on the contribution rate of short-term strong winds to dune migration. Leveraging the linear relationship between sand flux and the migration distance of barchans, we found that the ratio of sand flux generated by short-term strong winds to the total sand flux is equal to the ratio of barchan migration distance caused by strong winds to the total migration distance in the same period. Moreover, a global analysis of three typical barchan fields confirmed the relationship. This study suggests that the development of aeolian landforms is dominantly controlled by the short-term strong-wind events rather than the previously reported time-averaging wind.

Many different factors, such as species traits, socio-economic factors, geographical and environmental factors, can lead to specimen collection preference. This study aims to determine whether grassland specimen collection in China is preferred by species traits (i.e., plant height, flowering and fruiting period), environmental range (i.e., the temperature and precipitation range) and geographical range (i.e., distribution range and altitudinal range). Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables. Random Forest models were then used to find the most parsimonious multivariate model. The results showed that interannual variation in specimen number between 1900 and 2020 was considerable. Specimen number of these species in southeast China was notably lower than that in northwest China. Environmental range and geographical range of species had significant positive correlations with specimen number. In addition, there were relatively weak but significant associations between specimen number and species trait (i.e., plant height and flowering and fruiting period). Random Forest models indicated that distribution range was the most important variable, followed by flowering and fruiting period, and altitudinal range. These findings suggest that future floristic surveys should pay more attention to species with small geographical range, narrow environmental range, short plant height, and short flowering and fruiting period. The correction of specimen collection preference will also make the results of species distribution model, species evolution and other works based on specimen data more accurate.

Abstract Optimizing short‐term load forecasting performance is a challenge due to the randomness of nonlinear power load and variability of system operation mode. The existing methods generally ignore how to reasonably and effectively combine the complementary advantages among them and fail to capture enough internal information from load data, resulting in accuracy reduction. To achieve accurate and efficient short‐term load forecasting, an integral implementation framework is proposed based on convolutional neural network (CNN), gated recurrent unit (GRU) and channel attention mechanism. CNN and GRU are first combined to fully extract the highly complicated dynamic characteristics and learn time compliance relationships of load sequence. Based on CNN‐GRU network, the channel attention mechanism is introduced to further reduce the loss of historical information and enhance the impact of important characteristics. Then, the overall framework of short‐term load forecasting based on CNN‐GRU‐Attention network is proposed, and the coupling relationship between each stage is revealed. Finally, the developed framework is implemented on realistic load dataset of distribution networks, and the experimental results verify the effectiveness of the proposed method. Compared with the state‐of‐the‐art models, the CNN‐GRU‐Attention model outperforms in different evaluation metrics.

Abstract Graphene photodetectors have exhibited high bandwidth and capability of being integrated with silicon photonics (SiPh), holding promise for future optical communication devices. However, they usually suffer from a low photoresponsivity due to weak optical absorption. In this work, we have implemented SiPh-integrated twisted bilayer graphene (tBLG) detectors and reported a responsivity of 0.65 A W–1 for telecom wavelength 1,550 nm. The high responsivity enables a 3-dB bandwidth of >65 GHz and a high data stream rate of 50 Gbit s–1. Such high responsivity is attributed to the enhanced optical absorption, which is facilitated by van Hove singularities in the band structure of high-mobility tBLG with 4.1o twist angle. The uniform performance of the fabricated photodetector arrays demonstrates a fascinating prospect of large-area tBLG as a material candidate for heterogeneous integration with SiPh.

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has severely impacted public health. In 2022, the Omicron variant of SARS-CoV-2 rapidly became the dominant circulating variant in the local COVID-19 outbreaks in Tianjin Municipality, China. To gain a deeper understanding of the genetic variations of the Omicron variant in Tianjin, specimens from individuals who tested positive for SARS-CoV-2 between December 2021 and November 2022 were used for virus whole genome sequencing and phylogenetic analysis. A total of 1,674 high-quality Omicron sequences were obtained, consisting of 1,339 sequences from local cases belonging to 20 Phylogenetic Assignment of Named Global Outbreak (PANGO) lineages and 335 sequences from imported cases belonging to 70 lineages. Tianjin experienced five waves of local outbreaks, accompanied by multiple substitutions among subvariants, ranging from the initial BA.1.1 lineage to the subsequent BA.2, BF.7, and BA.5.2 lineages. The evolutionary rate of local strains, estimated to be 28.999 substitutions per year, and the evolutionary rate of imported strains, estimated to be 24.946 substitutions per year, were lower than that of the strains circulating globally. The additional substitutions and deletions of local strains have been used to identify and disrupt the virus transmission chains. The subvariants such as BA.5.2.48, BA.5.2.49, BF.7.14, and XBB.1 circulating in the fifth epidemic wave presented criterial immune escape mutations including S: R346T, S: L452R and S: F486V. It is essential to implement genomic surveillance strategies to investigate further the development of genomic mutation characteristics in the SARS-CoV-2 variant. This ongoing monitoring will contribute to a better understanding of the virus's genetic changes and aid in effective control measures.

Abstract Background Nutritional deficiencies (ND) continue to threaten the lives of millions of people around the world, with children being the worst hit. Nevertheless, no systematic study of the epidemiological features of child ND has been conducted so far. Therefore, we aimed to comprehensively assess the burden of pediatric ND. Methods We analyzed data on pediatric ND between 1990 and 2019 from the Global Burden of Disease study (GBD) 2019 at the global, regional, and national levels. In addition, joinpoint regression models were used to assess temporal trends. Results In 2019, the number of prevalent cases of childhood malnutrition increased to 435,071,628 globally. The global age-standardized incidence, prevalence, and DALY rates showed an increasing trend between 1990 and 2019. Meanwhile, the burden of child malnutrition was negatively correlated with sociodemographic index (SDI). Asia and Africa still carried the heaviest burden. The burden and trends of child malnutrition varied considerably across countries and regions. At the age level, we found that malnutrition was significantly more prevalent among children

Abstract Background Analysis of patient-reported outcomes (PROs) offers valuable insights into distinguishing the effects of closely related medical procedures from the patient’s perspective. In this study we compared symptom burden in patients undergoing uniportal thoracoscopic segmentectomy and wedge resection for peripheral small-sized non-small cell lung cancer (NSCLC). Methods This study included patients with peripheral NSCLC from an ongoing longitudinal prospective cohort study (CN-PRO-Lung 3) who underwent segmentectomy or wedge resection with tumor diameter ≤ 2 cm and consolidation tumor ratio (CTR) ≤ 0.5. PROs data were collected using the Perioperative Symptom Assessment for Lung Surgery questionnaire pre-operatively, daily post-surgery up to the fourth hospitalization day, and weekly post-discharge up to the fourth week. Propensity score matching and a generalized estimation equation model were employed to compare symptom severity. In addition, short-term clinical outcomes were compared. Results In total, data of 286 patients (82.4%) undergoing segmentectomy and 61 patients (17.6%) undergoing wedge resection were extracted from the cohort. No statistically significant differences were found in the proportion of moderate-to-severe symptoms and mean scores for pain, cough, shortness of breath, disturbed sleep, fatigue, drowsiness, and distress during the 4-day postoperative hospitalization or the 4-week post-discharge period before or after matching (all p > 0.05). Compared with segmentectomy, wedge resection showed better short-term clinical outcomes, including shorter operative time (p = 0.001), less intraoperative bleeding (p = 0.046), and lower total hospital costs (p = 0.002). Conclusions The study findings indicate that uniportal thoracoscopic segmentectomy and wedge resection exert similar early postoperative symptom burden in patients with peripheral NSCLC (tumor diameter ≤ 2 cm and CTR ≤ 0.5). Clinical trial registration Not applicable.

Abstract Background Exosomes assume a pivotal role as essential mediators of intercellular communication within tumor microenvironments. Within this context, long noncoding RNAs (LncRNAs) have been observed to be preferentially sorted into exosomes, thus exerting regulatory control over the initiation and progression of cancer through diverse mechanisms. Results Exosomes were successfully isolated from cholangiocarcinoma (CCA) CTCs organoid and healthy human serum. Notably, the LncRNA titin-antisense RNA1 (TTN-AS1) exhibited a conspicuous up-regulation within CCA CTCs organoid derived exosomes. Furthermore, a significant elevation of TTN-AS1 expression was observed in tumor tissues, as well as in blood and serum exosomes from patients afflicted with CCA. Importantly, this hightened TTN-AS1 expression in serum exosomes of CCA patients manifested a strong correlation with both lymph node metastasis and TNM staging. Remarkably, both CCA CTCs organoid-derived exosomes and CCA cells-derived exosomes featuring pronounced TTN-AS1 expression demonstrated the capability to the proliferation and migratory potential of CCA cells. Validation of these outcomes was conducted in vivo experiments. Conclusions In conclusion, our study elucidating that CCA CTCs-derived exosomes possess the capacity to bolster the metastasis tendencies of CCA cells by transporting TTN-AS1. These observations underscore the potential of TTN-AS1 within CTCs-derived exosomes to serve as a promising biomarker for the diagnosis and therapeutic management of CCA.

Abstract ETV6::RUNX1 is the most common fusion gene in childhood acute lymphoblastic leukaemia (ALL) and is associated with favorable outcomes, especially in low‐risk children. However, as many as 10% of children relapse within 3 years, and such early relapses have poor survival. Identifying children at risk for early relapse is an important challenge. We interrogated data from 87 children with low‐risk ETV6::RUNX1‐positive B‐cell ALL and with available preserved bone marrow samples (discovery cohort). We profiled somatic point mutations in a panel of 559 genes and genome‐wide transcriptome and single‐nucleotide variants. We found high TIMD4 expression (> 85th‐percentile value) at diagnosis was the most important independent prognostic factor of early relapse (hazard ratio [HR] = 5.07 [1.76, 14.62]; p = 0.03). In an independent validation cohort of low‐risk ETV6::RUNX1‐positive B‐cell ALL (N = 68) high TIMD4 expression at diagnosis had an HR = 4.78 [1.07, 21.36] (p = 0.04) for early relapse. In another validation cohort including 78 children with low‐risk ETV6::RUNX1‐negative B‐cell ALL, high TIMD4 expression at diagnosis had an HR = 3.93 [1.31, 11.79] (p = 0.01). Our results suggest high TIMD4 expression at diagnosis in low‐risk B‐cell ALL in children might be associated with high risk for early relapse.

Abstract The rapid increase in biomedical publications necessitates efficient systems to automatically handle Biomedical Named Entity Recognition (BioNER) tasks in unstructured text. However, accurately detecting biomedical entities is quite challenging due to the complexity of their names and the frequent use of abbreviations. In this paper, we propose BioBBC, a deep learning (DL) model that utilizes multi-feature embeddings and is constructed based on the BERT-BiLSTM-CRF to address the BioNER task. BioBBC consists of three main layers; an embedding layer, a Long Short-Term Memory (Bi-LSTM) layer, and a Conditional Random Fields (CRF) layer. BioBBC takes sentences from the biomedical domain as input and identifies the biomedical entities mentioned within the text. The embedding layer generates enriched contextual representation vectors of the input by learning the text through four types of embeddings: part-of-speech tags (POS tags) embedding, char-level embedding, BERT embedding, and data-specific embedding. The BiLSTM layer produces additional syntactic and semantic feature representations. Finally, the CRF layer identifies the best possible tag sequence for the input sentence. Our model is well-constructed and well-optimized for detecting different types of biomedical entities. Based on experimental results, our model outperformed state-of-the-art (SOTA) models with significant improvements based on six benchmark BioNER datasets.

Abstract Metabolic dysfunction-associated steatotic liver disease (MASLD) is the leading cause of chronic liver disease that affects over 30% of the world’s population. For decades, the heterogeneity of non-alcoholic fatty liver disease (NAFLD) has impeded our understanding of the disease mechanism and the development of effective medications. However, a recent change in the nomenclature from NAFLD to MASLD emphasizes the critical role of systemic metabolic dysfunction in the pathophysiology of this disease and therefore promotes the progress in the pharmaceutical treatment of MASLD. In this review, we focus on the mechanism underlying the abnormality of hepatic lipid metabolism in patients with MASLD, and summarize the latest progress in the therapeutic medications of MASLD that target metabolic disorders.

For receiving-end power systems with multi-infeed HVDCs and large-scale renewable energy generation, the challenges of weak reactive power support and limited anti-interference capacity pose a threat to the power system voltage stability. To enhance the voltage stability under large disturbances, this paper proposes a data-driven method for coordinated emergency control strategy against voltage instability in multi-infeed hybrid AC/DC systems based on the squeeze and excitation (SE) module and convolutional neural network (CNN). Firstly, the SE module and CNN are integrated to intuitively capture correlations among various feature channels and extract key features related to voltage stability levels. Secondly, a voltage stability evaluation method is proposed based on the SE-CNN model, utilizing a dual channel structure to unveil the quantitative relationship between key response characteristics and voltage stability margin. Finally, regarding the control measures containing load shedding and DC modulation, the emergency control sensitivity index is proposed to assess the stability margin improvement effect of various control objects, and the optimal emergency control strategy is formulated to coordinate multiple voltage stability emergency control measures. Case studies were conducted on a typical China local region receiving-end power grid test system with voltage instability problems, and the simulation results verified the effectiveness of the proposed method. © 2017 Elsevier Inc. All rights reserved.

Regular recreational activities in urban park green spaces are beneficial to the physical and mental health of residents. The supply capacity of, the residents’ demand for, and the actual flow of recreational services must be distinguished and evaluated to promote the fair and reasonable layout of urban park green spaces. However, the unit dimensions of the supply, demand, and flow indexes of recreational services are often inconsistent or only in simple semiquantitative forms, which cannot be directly compared and analyzed. Thus, this study constructed a research framework of “potential supply/demand–pressure/accessibility–actual supply/demand” for recreational services, and the framework was tested using the central urban area of Xuchang as the experimental area. Results show the following: (1) A spatial mismatch exists in the supply–demand relationship of recreational services in the study area; this relationship is reflected in the semicircular layer structure from the central and southern areas to the periphery, changing from shortage of supply to oversupply. (2) The actual supply of recreational services is highly correlated with the number of people served, which can explain 50.38% of the change in the actual supply. (3) The potential demand for recreational services is highly correlated with the actual demand. It can explain 78.96% of the change in the actual demand. (4) Accessibility is a non-critical factor affecting the travel rate of residential quarters, while supply pressure is a key factor affecting the utilization rate of park green space. The framework can effectively identify important or low-utilization service-providing areas, unmet service-demanding areas, and important service-connecting areas. It is suitable for the study of the relationship between the supply, demand, and flow of user movement-related services.

Formic acid is regarded to be one of the most prospective hydrogen carriers. Effective screening of the fitting non-noble-metal-based heterogeneous catalysts to substitute the expensive noble-metal-based ones for FA dehydrogenation is considered as a key to the commercial application for hydrogen economics. Herein, dehydrogenation of liquid neat FA achieved a gas production value of 1753.5 mL/gcat./h at 94 °C by using a biomass-derived γ-Mo2N based catalyst synthesized from the earth-abundant molybdenum and soybean with a facile pyrolysis process. The effect of material ratio, pyrolysis temperature on the catalytic performance of FA dehydrogenation were studied in details. In particular, the catalyst obtained at a pyrolysis temperature of 700 °C, weight ratios of ammonium molybdate to soybean of 0.2/1 exhibited the highest activity. In addition, the catalytic activity increased with the increase of FA concentration, but conversely, the dehydrogenation selectivity decreased with the increasing FA concentration. Moreover, it was found that the Bio-Mo2N catalyst was rather stable over the 40 h continuous reaction period.

Summary: Acute myeloid leukemia (AML) is highly heterogeneous, necessitating personalized prognosis prediction and treatment strategies. Many of the current patient classifications are based on molecular features. Here, we classified the primary AML patients by predicted death risk curves and investigated the survival-directly-related molecular features. We developed a deep learning model to predict 5-year continuous-time survival probabilities for each patient and converted them to death risk curves. This method captured disease progression dynamics with high temporal resolution and identified seven patient groups with distinct risk peak timing. Based on clusters of death risk curves, we identified two robust AML prognostic biomarkers and discovered a subgroup within the European LeukemiaNet (ELN) 2017 Favorable category with an extremely poor prognosis. Additionally, we developed a web tool, De novo AML Prognostic Prediction (DAPP), for individualized prognosis prediction and expression perturbation simulation. This study utilized deep learning-based continuous-time risk modeling coupled with clustering-predicted risk distributions, facilitating dissecting time-specific molecular features of disease progression.

BackgroundDespite the potential demonstrated by targeted plasma metabolite modulators in halting the progression of chronic kidney disease (CKD), a lingering uncertainty persists concerning the causal relationship between distinct plasma metabolites and the onset and progression of CKD.MethodsA genome-wide association study was conducted on 1,091 metabolites and 309 metabolite ratios derived from a cohort of 8,299 unrelated individuals of European descent. Employing a bidirectional two-sample Mendelian randomization (MR) analysis in conjunction with colocalization analysis, we systematically investigated the associations between these metabolites and three phenotypes: CKD, creatinine-estimated glomerular filtration rate (creatinine-eGFR), and urine albumin creatinine ratio (UACR). In the MR analysis, the primary analytical approach employed was inverse variance weighting (IVW), and sensitivity analysis was executed utilizing the MR-Egger method and MR-pleiotropy residual sum and outlier (MR-PRESSO). Heterogeneity was carefully evaluated through Cochrane’s Q test. To ensure the robustness of our MR results, the leave-one-out method was implemented, and the strength of causal relationships was subjected to scrutiny via Bonferroni correction.ResultsOur thorough MR analysis involving 1,400 plasma metabolites and three clinical phenotypes yielded a discerning identification of 21 plasma metabolites significantly associated with diverse outcomes. Specifically, in the forward MR analysis, 6 plasma metabolites were determined to be causally associated with CKD, 16 with creatinine-eGFR, and 7 with UACR. Substantiated by robust evidence from colocalization analysis, 6 plasma metabolites shared causal variants with CKD, 16 with creatinine-eGFR, and 7 with UACR. In the reverse analysis, a diminished creatinine-eGFR was linked to elevated levels of nine plasma metabolites. Notably, no discernible associations were observed between other plasma metabolites and CKD, creatinine-eGFR, and UACR. Importantly, our analysis detected no evidence of horizontal pleiotropy.ConclusionThis study elucidates specific plasma metabolites causally associated with CKD and renal functions, providing potential targets for intervention. These findings contribute to an enriched understanding of the genetic underpinnings of CKD and renal functions, paving the way for precision medicine applications and therapeutic strategies aimed at impeding disease progression.

BackgroundHaemaphysalis flava is a notorious parasite for humans and animals worldwide. The organs of H. flava are bathed in hemolymph, which is a freely circulating fluid. Nutrients, immune factors, and waste can be transported to any part of the body via hemolymph. The main soluble components in hemolymph are proteins. However, knowledge of the H. flava proteome is limited.MethodsThe hemolymph was collected from fully engorged H. flava ticks by leg amputation. Hemolymph proteins were examined by both blue native polyacrylamide gel electrophoresis (BN-PAGE) and sodium dodecyl sulfate PAGE (SDS-PAGE). Proteins extracted from the gels were further identified by liquid chromatography–tandem mass spectrometry (LC–MS/MS).ResultsTwo bands (380 and 520 kDa) were separated from tick hemolymph by BN-PAGE and were further separated into four bands (105, 120, 130, and 360 kDa) by SDS-PAGE. LC–MS/MS revealed that seven tick proteins and 13 host proteins were present in the four bands. These tick proteins mainly belonged to the vitellogenin (Vg) family and the α-macroglobulin family members. In silico structural analysis showed that these Vg family members all had common conserved domains, including the N-terminus lipid binding domain (LPD-N), the C-terminus von Willebrand type D domain (vWD), and the domain of unknown function (DUF). Additionally, two of the Vg family proteins were determined to belong to the carrier protein (CP) by analyzing the unique N-terminal amino acid sequences and the cleaving sites.ConclusionThese findings suggest that the Vg family proteins and α-macroglobulin are the primary constituents of the hemolymph in the form of protein complexes. Our results provide a valuable resource for further functional investigations of H. flava hemolymph effectors and may be useful in tick management.

Acute large hemispheric infarction (ALHI) is an overwhelming emergency with a great challenge of gastrointestinal dysfunction clinically. Here, we initially proposed delayed bowel movements as the clinical phenotype of strike to gut-brain axis (GBA) in ALHI patients by epidemiological analysis of 499 acute ischemic stroke (AIS) patients. 1H NMR-based metabolomics revealed that AIS markedly altered plasma global metabolic profiling of patients compared with healthy controls. Risk factors of strike on GBA were the National Institutes of Health Stroke Scale (NIHSS) score ≥ 5 and stroke onset time ≤ 24 h. As a result, first defecating time after admission to the hospital ≥2 days could be considered as a potential risk factor for strike on GBA. Subsequently, the ALHI Bama miniature (BM) pig model with acute symptomatic seizure was successfully established by ligation of the left ascending pharyngeal artery combined with local air injection. Clinical phenotypes of brain necrosis such as hemiplegia were examined with brain diffusion-weighted imaging (DWI) and pathological diagnosis. In addition to global brain injury and inflammation, we also found that ALHI induced marked alterations of intestinal barrier integrity, the gut microbial community, and microbiota-derived metabolites including serotonin and neurotransmitters in both plasma and multiple brain tissues of BM pigs. These findings revealed that microbiota-gut-brain axis highly contributed to the occurrence and development of ALHI.

Abstract Self‐assembling peptides have numerous applications in medicine, food chemistry, and nanotechnology. However, their discovery has traditionally been serendipitous rather than driven by rational design. Here, HydrogelFinder, a foundation model is developed for the rational design of self‐assembling peptides from scratch. This model explores the self‐assembly properties by molecular structure, leveraging 1,377 self‐assembling non‐peptidal small molecules to navigate chemical space and improve structural diversity. Utilizing HydrogelFinder, 111 peptide candidates are generated and synthesized 17 peptides, subsequently experimentally validating the self‐assembly and biophysical characteristics of nine peptides ranging from 1–10 amino acids—all achieved within a 19‐day workflow. Notably, the two de novo‐designed self‐assembling peptides demonstrated low cytotoxicity and biocompatibility, as confirmed by live/dead assays. This work highlights the capacity of HydrogelFinder to diversify the design of self‐assembling peptides through non‐peptidal small molecules, offering a powerful toolkit and paradigm for future peptide discovery endeavors.

We investigate the effect of ultrasound on the evaporation and crystallization of sessile NaCl solution droplets which were positioned in traveling or standing wave ultrasound field. The experimental results indicated that the ultrasound field can significantly accelerate the evaporation rate of the sessile droplets and refine the crystal grains. By adjusting the distance between the sessile droplets and the ultrasound emitter, it is found that, in traveling wave ultrasound field, the sessile droplet evaporation time and the time for the appearance of NaCl grains exhibited a fluctuating increase as the droplet-emitter distance increased. While in the standing wave ultrasound, the sessile droplet evaporation rate increases with the increasing droplet-emitter distance. Overall, the traveling wave ultrasound field has a stronger effect on grain refinement of the sessile droplets than the standing wave ultrasound field. The grain refinement is attributed to the decrease of critical nucleation radius caused by ultrasound energy and the increase of the nucleation rate caused by the accelerated evaporation rate. In addition, the breakage of grains caused by ultrasonic cavitation would also lead to grain refinement.

Abstract Objective To systematically analyze the accuracy of ultrasonic techniques in assessing the nature of gastric contents and their volume. Methods English-language articles that used ultrasonic techniques to assess the nature of gastric contents and their volume in patients were selected. In eligible studies, data were recalculated and analyzed for forest plots and subject summary curves of operating characteristics (SROC). Study quality was assessed using the diagnostic accuracy study quality assessment tool QUADAS-2. Publication bias was tested using funnel plots. Results Nine articles with a total of 523 study subjects were identified for this review. All studies were feasibility studies. The sensitivity of ultrasound assessment of gastric contents ranged from 53 to 100% and the specificity from 48 to 99%. The combined analysis yielded an area under the working characteristic curve for subjects of 97% (95% confidence interval (CI), 95–98%), a sensitivity of 95% (95% CI, 84–99%), and a specificity of 88% (95% CI, 72–95%). There was a high degree of heterogeneity among the studies due to inter-operator differences and small sample sizes. Conclusion Ultrasound techniques have high diagnostic accuracy in assessing the nature of gastric contents and their volume in patients. However, most of the studies were feasibility studies with small sample sizes, lacked standardization, and had high risk of bias. More studies are needed in the future to investigate the diagnostic performance of gastric ultrasound assessment techniques. Critical relevance statement Ultrasonography can be used to assess gastric contents, but standardized data integration and reporting are needed to account for the diagnostic capabilities of this technology. Key points • Ultrasound is a safe and feasible tool for assessing gastric contents. • Ultrasound has good diagnostic performance for gastric contents. • There is still a certain heterogeneity within our analysis process; more research is needed in the future to improve our results. Graphical Abstract

Abstract Scanning electron microscopy (SEM) is a crucial tool for analyzing submicron-scale structures. However, the attainment of high-quality SEM images is contingent upon the high conductivity of the material due to constraints imposed by its imaging principles. For weakly conductive materials or structures induced by intrinsic properties or organic doping, the SEM imaging quality is significantly compromised, thereby impeding the accuracy of subsequent structure-related analyses. Moreover, the unavailability of paired high–low quality images in this context renders the supervised-based image processing methods ineffective in addressing this challenge. Here, an unsupervised method based on Cycle-consistent Generative Adversarial Network (CycleGAN) was proposed to enhance the quality of SEM images for weakly conductive samples. The unsupervised model can perform end-to-end learning using unpaired blurred and clear SEM images from weakly and well-conductive samples, respectively. To address the requirements of material structure analysis, an edge loss function was further introduced to recover finer details in the network-generated images. Various quantitative evaluations substantiate the efficacy of the proposed method in SEM image quality improvement with better performance than the traditional methods. Our framework broadens the application of artificial intelligence in materials analysis, holding significant implications in fields such as materials science and image restoration.

Abstract Background Pulmonary sarcomatoid carcinoma (PSC) is a rare and highly malignant type of non-small cell lung cancer (NSCLC), for which the treatment of choice is surgery. For peripheral PSC growing outward and invading the chest wall, a complete resection of the affected lung lobes and the invaded chest wall can improve long-term prognosis. However, when the extent of the resected chest wall is large, reconstruction is often required to reduce the risk of postoperative complications. Here, we present a case of PSC invading the chest wall treated with successful extended radical resection for lung cancer and chest wall reconstruction. Case presentation A 58-year-old male patient with a nodule in the right upper lobe that had been identified on physical examination 2 years before presentation presented to our hospital with a recent cough, expectoration, and chest pain. Imaging revealed a mass in the right upper lobe that had invaded the chest wall. Preoperative puncture pathology revealed poorly differentiated NSCLC. We performed extended radical resection for lung cancer under open surgery and reconstructed the chest wall using stainless steel wire and polypropylene meshes. The procedure was uneventful, and the patient was discharged 7 days postoperatively. Furthermore, the final pathology revealed PSC. Conclusions This case underscores the feasibility of surgical R0 resection in patients with PSC with chest wall invasion and no lymph node metastasis, potentially enhancing long-term outcomes. The novel aspect of this case lies in the individualized chest wall reconstruction for a large defect, using cost-effective materials that offered satisfactory structural support and postoperative recovery, thereby providing a valuable reference for similar future surgical interventions.

Abstract Metastatic prostate cancer (PCa) poses a significant therapeutic challenge with high mortality rates. Utilizing CRISPR-Cas9 in vivo, we target five potential tumor suppressor genes (Pten, Trp53, Rb1, Stk11, and RnaseL) in the mouse prostate, reaching humane endpoint after eight weeks without metastasis. By further depleting three epigenetic factors (Kmt2c, Kmt2d, and Zbtb16), lung metastases are present in all mice. While whole genome sequencing reveals few mutations in coding sequence, RNA sequencing shows significant dysregulation, especially in a conserved genomic region at chr5qE1 regulated by KMT2C. Depleting Odam and Cabs1 in this region prevents metastasis. Notably, the gene expression signatures, resulting from our study, predict progression-free and overall survival and distinguish primary and metastatic human prostate cancer. This study emphasizes positive genetic interactions between classical tumor suppressor genes and epigenetic modulators in metastatic PCa progression, offering insights into potential treatments.

Abstract Background The global prevalence of VCI has increased steadily in recent years, but diagnostic biomarkers for VCI in patients with non-disabling ischemic cerebrovascular incidents (NICE) remain indefinite. The primary objective of this research was to investigate the relationship between peripheral serological markers, white matter damage, and cognitive function in individuals with NICE. Methods We collected clinical data, demographic information, and medical history from 257 patients with NICE. Using the MoCA upon admission, patients were categorized into either normal cognitive function (NCF) or VCI groups. Furthermore, they were classified as having mild white matter hyperintensity (mWMH) or severe WMH based on Fazekas scores. We then compared the levels of serological markers between the cognitive function groups and the WMH groups. Results Among 257 patients with NICE, 165 were male and 92 were female. Lymphocyte count (OR = 0.448, P

Abstract Background Severe asthma places a large burden on patients and society. The characteristics of patients with severe asthma in the Chinese population remain unclear. Methods A retrospective review was conducted in patients with severe asthma. Demographic and clinical data were collected. Patients were grouped according to phenotypes in terms of exacerbations, body mass index (BMI) and fixed airway obstruction (FAO) status, and the characteristics of different groups were compared. Comorbidities, factors that influence asthma phenotypes, were also analyzed in the study. Results A total of 228 patients with severe asthma were included in our study. They were more likely to be overweight or obese. A total of 41.7% of the patients received GINA step 5 therapy, and 43.4% had a history of receiving regular or intermittent oral corticosteroids (OCS). Severe asthmatic patients with comorbidities were prone to have more asthma symptoms and decreased quality of life than patients without comorbidities. Patients with exacerbations were characterized by longer duration of asthma, poorer lung function, and worse asthma control. Overweight or obese patients tended to have more asthma symptoms, poorer lung function and more asthma-related comorbidities. Compared to patients without FAO, those in the FAO group were older, with longer duration of asthma and more exacerbations. Conclusion The existence of comorbidities in patients with severe asthma could result in more asthma symptoms and decreased quality of life. Patients with exacerbations or with overweight or obese phenotypes were characterized by poorer lung function and worse asthma control. Patients with FAO phenotype tended to have more exacerbations.

Abstract This study aims to test the effects of the parent-implemented interventions (PIIs) on children with autism spectrum disorder (ASD) in China and to explore the effects of PIIs on the family quality of life of families of children with ASD in China. This study adopted a randomized controlled trial (RCT) design based on PIIs. Participants is divided into intervention group (N(parents) = 35, Age(M ± SD) = 35.69 ± 3.45; N(children) = 35, Age(M ± SD) = 5.49 ± 2.74) and control group (N(parents) = 35, Age(M ± SD) = 36.06 ± 4.28; N(children) = 35, Age(M ± SD) = 5.71 ± 3.25); parents in intervention group were trained with PIIs and required to implement family interventions for their children with ASD as they learned. This study will provide data to support the development and improvement of PIIs, and will also benefit the well-being and sustainability of children with ASD and their families. Compared to control group, the children in intervention group had a significant improvement in social communication ability (p

Abstract To evaluate the association of uric acid (UA) with adverse outcomes and its potential mediator in patients with left ventricular diastolic dysfunction (LVDD) and pulmonary hypertension (PH). We retrospectively analyzed 234 patients with LVDD and PH. The baseline characteristics of patients with low UA (≤ 330 µmol/L) group were compared with high UA (> 330 µmol/L) group. Adverse outcomes included all-cause mortality, cardiac death and heart failure (HF) hospitalization. Their association with UA and the mediator were evaluated using Cox regression and mediation analysis. The mediation proportion was further quantified by the R mediation package. During a mean follow-up of 50 ± 18 months, there were 27 all-cause deaths, 18 cardiovascular deaths and 41 incidents of HF hospitalization. Multivariable Cox regression analysis showed UA was an independent risk factor of adverse outcomes in LVDD and PH patients, even after adjusting for age, sex, body mass index, medical histories, systolic blood pressure, fasting blood glucose, total cholesterol, triglyceride, eGFR, BNP and medications. The hazard ratios (HRs) for UA (per 10 µmol/L increase) were as below: for all-cause mortality, HR 1.143, 95% CI 1.069–1.221, P

Abstract Advances in cryo-electron microscopy (cryo-EM) imaging technologies have led to a rapidly increasing number of cryo-EM density maps. Alignment and comparison of density maps play a crucial role in interpreting structural information, such as conformational heterogeneity analysis using global alignment and atomic model assembly through local alignment. Here, we present a fast and accurate global and local cryo-EM density map alignment method called CryoAlign, that leverages local density feature descriptors to capture spatial structure similarities. CryoAlign is a feature-based cryo-EM map alignment tool, in which the employment of feature-based architecture enables the rapid establishment of point pair correspondences and robust estimation of alignment parameters. Extensive experimental evaluations demonstrate the superiority of CryoAlign over the existing methods in terms of both alignment accuracy and speed.

Abstract The Li-S battery is a promising next-generation battery chemistry that offers high energy density and low cost. The Li-S battery has a unique chemistry with intermediate sulphur species readily solvated in electrolytes, and understanding their implications is important from both practical and fundamental perspectives. In this study, we utilise the solvation free energy of electrolytes as a metric to formulate solvation-property relationships in various electrolytes and investigate their impact on the solvated lithium polysulphides. We find that solvation free energy influences Li-S battery voltage profile, lithium polysulphide solubility, Li-S battery cyclability and the Li metal anode; weaker solvation leads to lower 1st plateau voltage, higher 2nd plateau voltage, lower lithium polysulphide solubility, and superior cyclability of Li-S full cells and Li metal anodes. We believe that relationships delineated in this study can guide the design of high-performance electrolytes for Li-S batteries.

Abstract Extracting rare earth elements (REEs) from wastewater is essential for the growth and an eco-friendly sustainable economy. However, it is a daunting challenge to separate individual rare earth elements by their subtle differences. To overcome this difficulty, we report a unique REE nanotrap that features dense uncoordinated carboxyl groups and triazole N atoms in a two-fold interpenetrated metal-organic framework (named NCU-1). Notably, the synergistic effect of suitable pore sizes and REE nanotraps in NCU-1 is highly responsive to the size variation of rare-earth ions and shows high selectivity toward light REE. As a proof of concept, Pr/Lu and Nd/Er are used as binary models, which give a high separation factor of SF Pr/Lu = 796 and SF Nd/Er = 273, demonstrating highly efficient separation over a single step. This ability achieves efficient and selective extraction and separation of REEs from mine tailings, establishing this platform as an important advance for sustainable obtaining high-purity REEs.