Radiograph-based rheumatoid arthritis diagnosis via convolutional neural network.

OBJECTIVES: Rheumatoid arthritis (RA) is a severe and common autoimmune disease. Conventional diagnostic methods are often subjective, error-prone, and repetitive works. There is an urgent need for a method to detect RA accurately. Therefore, this study aims to develop an automatic diagnostic system based on deep learning for recognizing and staging RA from radiographs to assist physicians in diagnosing RA quickly and accurately. METHODS: We develop a CNN-based fully automated RA diagnostic model, exploring five popular CNN architectures on two clinical applications. The model is trained on a radiograph dataset containing 240 hand radiographs, of which 39 are normal and 201 are RA with five stages. For evaluation, we use 104 hand radiographs, of which 13 are normal and 91 RA with five stages. RESULTS: The CNN model achieves good performance in RA diagnosis based on hand radiographs. For the RA recognition, all models achieve an AUC above 90% with a sensitivity over 98%. In particular, the AUC of the GoogLeNet-based model is 97.80%, and the sensitivity is 100.0%. For the RA staging, all models achieve over 77% AUC with a sensitivity over 80%. Specifically, the VGG16-based model achieves 83.36% AUC with 92.67% sensitivity. CONCLUSION: The presented GoogLeNet-based model and VGG16-based model have the best AUC and sensitivity for RA recognition and staging, respectively. The experimental results demonstrate the feasibility and applicability of CNN in radiograph-based RA diagnosis. Therefore, this model has important clinical significance, especially for resource-limited areas and inexperienced physicians.

True or false? Alzheimer's disease is type 3 diabetes: Evidences from bench to bedside.

Globally, Alzheimer's disease (AD) is the most widespread chronic neurodegenerative disorder, leading to cognitive impairment, such as aphasia and agnosia, as well as mental symptoms, like behavioral abnormalities, that place a heavy psychological and financial burden on the families of the afflicted. Unfortunately, no particular medications exist to treat AD, as the current treatments only impede its progression.The link between AD and type 2 diabetes (T2D) has been increasingly revealed by research; the danger of developing both AD and T2D rises exponentially with age, with T2D being especially prone to AD. This has propelled researchers to investigate the mechanism(s) underlying this connection. A critical review of the relationship between insulin resistance, Aß, oxidative stress, mitochondrial hypothesis, abnormal phosphorylation of Tau protein, inflammatory response, high blood glucose levels, neurotransmitters and signaling pathways, vascular issues in AD and diabetes, and the similarities between the two diseases, is presented in this review. Grasping the essential mechanisms behind this detrimental interaction may offer chances to devise successful therapeutic strategies.

An Improved Ordinary State-Based Peridynamic Model for Granular Fractures in Cubic Crystals and the Effects of Crystal Orientations on Crack Propagation.

Material anisotropy caused by crystal orientation is an essential factor affecting the mechanical and fracture properties of crystal materials. This paper proposes an improved ordinary state-based peridynamic (OSB-PD) model to study the effect of arbitrary crystal orientation on the granular fracture in cubic crystals. Based on the periodicity of the equivalent elastic modulus of a cubic crystal, a periodic function regarding the crystal orientation is introduced into peridynamic material parameters, and a complete derivation process and expressions of correction factors are given. In addition, the derived parameters do not require additional coordinate transformation, simplifying the simulation process. Through convergence analysis, a regulating strategy to obtain the converged and accurate results of crack propagation paths is proposed. The effects of crystal orientations on crack initiation and propagation paths of single-crystal materials with different notch shapes (square, equilateral triangle, semi-circle) and sizes were studied. The results show that variations in crystal orientation can change the bifurcation, the number, and the propagation path direction of cracks. Under biaxial tensile loading, single crystals with semi-circular notches have the slowest crack initiation time and average propagation speed in most cases and are more resistant to fracture. Finally, the effects of grain anisotropy on dynamic fractures in polycrystalline materials under different grain boundary coefficients were studied. The decrease in grain anisotropy degree can reduce the microcracks in intergranular fracture and the crack propagation speed in transgranular fracture, respectively.

Novel separate aeration self-circulating technology for continuous aerobic granular sludge process: Performance evaluation, hydrodynamic simulation and control strategy.

The continuous aerobic granular sludge (AGS) process is promising for upgrading existing wastewater treatment facilities. However, this approach is still challenging because of its complicated structure and operation. To address this issue, a novel separate aeration self-circulating technology (abbreviated as Zier) was proposed, which is promising for cultivating AGS by its outstanding upflow velocity and circulation multiplier (more than 30 m/h and 200, respectively). This study elaborated on the Zier reactor's feasibility, optimization, and control strategy through computational fluid dynamics simulations, theoretical calculations, and experiments. An appropriate flow regime for efficient removal of pollutant and granulation of sludge was attained at a superficial gas velocity of 1.3 cm/s. Moreover, optimizing the aeration column diameter to half of the reaction column and increasing the height/diameter ratio to 20 dramatically boosted the nitrogen removal capacity over 1.6 kg N/m3/d. Utilizing a smaller circulation pipe diameter ensured granulation under a consistent flow regime. By judiciously regulating, multiple CSTRs and PFRs seamlessly integrated within the Zier reactor across a broad spectrum of particle sludge. The validity of these findings was further substantiated through experimental and theoretical validations. Drawing from these findings, a multi-scenario control strategy was proposed as Zier's map. With all the superiorities shown by the Zier reactor, this study could offer new insights into an efficient continuous AGS process.

Patient-Specific Factors Predicting Renal Denervation Response in Patients With Hypertension: A Systematic Review and Meta-Analysis.

BACKGROUND: The accurate selection of patients likely to respond to renal denervation (RDN) is crucial for optimizing treatment outcomes in patients with hypertension. This systematic review was designed to evaluate patient-specific factors predicting the RDN response. METHODS AND RESULTS: We focused on individuals with hypertension who underwent RDN. Patients were categorized based on their baseline characteristics. The primary outcome was blood pressure (BP) reduction after RDN. Both randomized controlled trials and nonrandomized studies were included. We assessed the risk of bias using corresponding tools and further employed the Grading of Recommendations Assessment, Development, and Evaluation approach to assess the overall quality of evidence. A total of 50 studies were ultimately included in this systematic review, among which 17 studies were for meta-analysis. Higher baseline heart rate and lower pulse wave velocity were shown to be associated with significant antihypertensive efficacy of RDN on 24-hour systolic BP reduction (weighted mean difference, -4.05 [95% CI, -7.33 to -0.77]; weighted mean difference, -7.20 [95% CI, -9.79 to -4.62], respectively). In addition, based on qualitative analysis, higher baseline BP, orthostatic hypertension, impaired baroreflex sensitivity, and several biomarkers are also reported to be associated with significant BP reduction after RDN. CONCLUSIONS: In patients with hypertension treated with the RDN, higher heart rate, and lower pulse wave velocity were associated with significant BP reduction after RDN. Other factors, including higher baseline BP, hypertensive patients with orthostatic hypertension, BP variability, impaired cardiac baroreflex sensitivity, and some biomarkers are also reported to be associated with a better BP response to RDN.

Reliability and validity of "My Jump 2" application for countermovement jump free arm and interlimb jump symmetry in different sports of professional athletes.

Background: Vertical jumping is an important evaluation tool to measure muscle strength and power as well as lower limb symmetry. It is of practical importance and value to develop and utilize a portable and low-cost mobile application (APP) to evaluate jumping. The "My Jump 2" app is an iPhone camera-based application for measuring jumping movements, which is applied to the countermovement jump (CMJ) vertical jumps of the lower limbs of athletes in different sports. The validity of this application and previous versions applied to different forms of vertical jump tests has been preliminarily demonstrated in different population, which has an obvious progress in research. Therefore, the reliability and validity of the jump height, time of flight parameters and symmetry of the CMJ vertical jump of athletes in different sports are needed to be verified by more experiments. Purpose: The purpose of this study is to verify whether "My Jump 2" can effectively and reliably assess jump height, flight practice and lower limb symmetry in CMJAM (countermovement jump free arm) tests in fencing, swimming and diving athletes. Methods: Seventy-nine fencers, swimmers and divers with training experience participated in this study. They completed a total of three CMJAM vertical jump and lower limb symmetry tests in 1 day, while being assessed by using the "My Jump 2" application and a force platform. The intra-group correlation coefficient (ICC) was used to verify reliability, while the Cronbach's alpha and coefficient of variation (CV%) was used to analyze the stability of the CMJAM vertical jump test over three jumps. The Pearson correlation coefficient was used to verify the strength of the relationship between methods (i.e., concurrent validity), and the Bland-Altman plot was used to represent consistency, meanwhile, the t-test was used to determine the systematic bias between methods. Results: Compared with the force platform, the cumulative height values of the total number of jumps (r = 0.999; p = 0.000), the cumulative time to vacate (r = 0.999; p = 0.000) for the CMJAM test obtained by the "My Jump 2" application, the height (ICC = 0.999-1, p = 0.000), the time to vacate flight (ICC = 0.999-1, p = 0.000), contact time symmetry (ICC = 0.976-0.994, p = 0.000), and flight time symmetry (ICC = 0.921-0.982, p = 0.000), respectively. Showed high correlation between the results of "my jump 2" app and the force platform. Conclusion: The "My Jump 2" application is a valid tool to assess CMJAM vertical jump and lower limb symmetry in fencing, swimming and diving athletes with training experience.

Sex Differences in the Relationship Between Self-Reporting of Snoring and Cardiovascular Risk:An Analysis of NHANES.

Background: Identifying risk factors for cardiovascular disease (CVD) is critical for effective prevention and management. While classic CVD risk factors have been extensively studied, there is a scarcity of research on the association between snoring and CVD risk, particularly in the context of sex differences. Methods: This study utilized data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2015 and 2020. Participants were initially categorized based on the severity of snoring or the presence of snoring.Within the snoring group, they were further classified by sex. Analysis was carried out using multivariate logistic regression. Results: Our study included 12,681 participants aged 18 years or older. When compared to the non-snoring group, individuals in the moderate snoring group had a higher odds ratio (OR) of 1.418 (95% CI 1.083 to 1.857, p = 0.011), while those in the severe snoring group had a higher OR of 1.882 (95% CI 1.468 to 2.409, p < 0.001). In the snoring group, individuals were further categorized by gender: 4527 males and 4131 females. Importantly, male patients showed a higher OR for atrial fibrillation (4.945, 95% CI 1.187 to 20.598, p = 0.028) compared to females. Additionally, male patients had a higher OR for coronary heart disease (2.002, 95% CI 1.152 to 3.479, p = 0.014) compared to females. Conclusion: Sex plays a significant role in the relationship between snoring and CVD risk. Males with snoring have a higher risk of developing CVD compared to females. In particular, male snorers are nearly five times more likely to develop atrial fibrillation and about twice as likely to experience coronary artery disease in comparison to female snorers. It is recommended that healthcare providers and public health officials prioritize cardiovascular risk assessments for male individuals who exhibit symptoms of snoring.

Heterogeneous body compositions and all-cause mortality in acute coronary syndrome patients: a ten-year retrospective cohort study.

BACKGROUND: The association of different body components, including lean mass and body fat, with the risk of death in acute coronary syndrome (ACS) patients are unclear. METHODS: We enrolled adults diagnosed with ACS at our center between January 2011 and December 2012 and obtained follow-up outcomes via telephone questionnaires. We used restricted cubic splines (RCS) with the Cox proportional hazards model to analyze the associations between body mass index (BMI), predicted lean mass index (LMI), predicted body fat percentage (BF), and the value of LMI/BF with 10-year mortality. We also examined the secondary outcome of death during hospitalization. RESULTS: During the maximum 10-year follow-up of 1398 patients, 331 deaths (23.6%) occurred, and a U-shaped relationship was found between BMI and death risk (P nonlinearity = 0.03). After adjusting for age and history of diabetes, the overweight group (24 ≤ BMI < 28 kg/m2) had the lowest mortality (HR = 0.53, 95% CI: 0.29-0.99). Predicted LMI and LMI/BF had an inverse linear relationship with a 10-year death risk (P nonlinearity = 0.24 and P nonlinearity = 0.38, respectively), while an increase in BF was associated with increased mortality (P nonlinearity = 0.64). During hospitalization, 31 deaths (2.2%) were recorded, and the associations of the indicators with in-hospital mortality were consistent with the long-term outcome analyses. CONCLUSION: Our study provides new insight into the "obesity paradox" in ACS patients, highlighting the importance of considering body composition heterogeneity. Predicted LMI and BF may serve as useful tools for assessing nutritional status and predicting the prognosis of ACS, based on their linear associations with all-cause mortality.

AgriGAN: unpaired image dehazing via a cycle-consistent generative adversarial network for the agricultural plant phenotype.

Artificially extracted agricultural phenotype information exhibits high subjectivity and low accuracy, while the utilization of image extraction information is susceptible to interference from haze. Furthermore, the effectiveness of the agricultural image dehazing method used for extracting such information is limited due to unclear texture details and color representation in the images. To address these limitations, we propose AgriGAN (unpaired image dehazing via a cycle-consistent generative adversarial network) for enhancing the dehazing performance in agricultural plant phenotyping. The algorithm incorporates an atmospheric scattering model to improve the discriminator model and employs a whole-detail consistent discrimination approach to enhance discriminator efficiency, thereby accelerating convergence towards Nash equilibrium state within the adversarial network. Finally, by training with network adversarial loss + cycle consistent loss, clear images are obtained after dehazing process. Experimental evaluations and comparative analysis were conducted to assess this algorithm's performance, demonstrating improved accuracy in dehazing agricultural images while preserving detailed texture information and mitigating color deviation issues.

Innovation for continuous aerobic granular sludge process in actual municipal sewage treatment: Self-circulating up-flow fluidized bed process.

Aerobic granular sludge (AGS) capable of nitrogen and phosphorus removal is mainly limited to the applications in sequencing batch reactors. This study introduced an innovative continuous self-circulating up-flow fluidized bed process (Zier process) using separate aeration. The process was composed of an anoxic column (Zier-A), aeration column (Zier-OO) and aerobic column (Zier-O), and was used to treat actual municipal sewage continuously for 170 days. The process achieved self-circulation of 20-32 times and an up-flow velocity within the reactor of 7-16 m/h which were accurately controlled with only separate aeration. The larger proportion of self-circulating multiple times contributed to particle formation and stability, providing hydraulic shear conditions, and screened the precipitation performance of the granular sludge (GS). Meanwhile, the dissolved oxygen (DO) of Zier-O was controlled at 0.1-0.3 mg/L, and the DO of Zier-A input water was zero. The accurate oxygen supply enhanced simultaneous nitrification and denitrification (SND) as well as short-cut nitrification and denitrification in Zier-O and improved the COD utilization rate and the nitrogen removal rate in Zier-A. The COD treatment capacity reached 2.46 kg-COD/(m³·d). With a hydraulic retention time of 10 h, the process consistently ensured that the average concentrations of ammonia nitrogen and total nitrogen in the effluent were maintained below 5 and 15 mg/L, respectively. Moreover, the process maintained the shape and stability of GS, the median diameter of GS ranged between 300-1210 µm, the percentage of mass with particle size distribution < 200 µm at a height of 150 cm within Zier-A and Zier-O accounted for as low as 0.04%-0.05%, and showed good settling performance. The suspended solids in effluent can be maintained at 50-80 mg/L. Overall, the unique structural setting and control method of the Zier process provide another approach for the application of continuous AGS treatment for municipal sewage.

Advances in spatial transcriptomics and its applications in cancer research.

Malignant tumors have increasing morbidity and high mortality, and their occurrence and development is a complicate process. The development of sequencing technologies enabled us to gain a better understanding of the underlying genetic and molecular mechanisms in tumors. In recent years, the spatial transcriptomics sequencing technologies have been developed rapidly and allow the quantification and illustration of gene expression in the spatial context of tissues. Compared with the traditional transcriptomics technologies, spatial transcriptomics technologies not only detect gene expression levels in cells, but also inform the spatial location of genes within tissues, cell composition of biological tissues, and interaction between cells. Here we summarize the development of spatial transcriptomics technologies, spatial transcriptomics tools and its application in cancer research. We also discuss the limitations and challenges of current spatial transcriptomics approaches, as well as future development and prospects.

DeepCBA: A deep learning framework for gene expression prediction in maize based on DNA sequences and chromatin interactions.

Chromatin interactions create spatial proximity between distal regulatory elements and target genes in the genome, which has an important impact on gene expression, transcriptional regulation, and phenotypic traits. To date, several methods have been developed for predicting gene expression. However, existing methods do not take into consideration the effect of chromatin interactions on target gene expression, thus potentially reducing the accuracy of gene expression prediction and mining of important regulatory elements. In this study, we developed a highly accurate deep learning-based gene expression prediction model (DeepCBA) based on maize chromatin interaction data. Compared with existing models, DeepCBA exhibits higher accuracy in expression classification and expression value prediction. The average Pearson correlation coefficients (PCCs) for predicting gene expression using gene promoter proximal interactions, proximal-distal interactions, and both proximal and distal interactions were 0.818, 0.625, and 0.929, respectively, representing an increase of 0.357, 0.16, and 0.469 over the PCCs obtained with traditional methods that use only gene proximal sequences. Some important motifs were identified through DeepCBA; they were enriched in open chromatin regions and expression quantitative trait loci and showed clear tissue specificity. Importantly, experimental results for the maize flowering-related gene ZmRap2.7 and the tillering-related gene ZmTb1 demonstrated the feasibility of DeepCBA for exploration of regulatory elements that affect gene expression. Moreover, promoter editing and verification of two reported genes (ZmCLE7 and ZmVTE4) demonstrated the utility of DeepCBA for the precise design of gene expression and even for future intelligent breeding. DeepCBA is available at http://www.deepcba.com/ or http://124.220.197.196/.

Overview of Functionalized Porous Materials for Rare-Earth Element Separation and Recovery.

The exceptional photoelectromagnetic characteristics of rare-earth elements contribute significantly to their indispensable position in the high-tech industry. The exponential expansion of the demand for high-purity rare earth and related compounds can be attributed to the swift advancement of contemporary technology. Nevertheless, rare-earth elements are finite and limited resources, and their excessive mining unavoidably results in resource depletion and environmental degradation. Hence, it is crucial to establish a highly effective approach for the extraction and reclamation of rare-earth elements. Adsorption is regarded as a promising technique for the recovery of rare-earth elements owing to its simplicity, environmentally friendly nature, and cost-effectiveness. The efficacy of adsorption is contingent upon the performance characteristics of the adsorbent material. Presently, there is a prevalent utilization of porous adsorbent materials with substantial specific surface areas and plentiful surface functional groups in the realm of selectively separating and recovering rare-earth elements. This paper presents a thorough examination of porous inorganic carbon materials, porous inorganic silicon materials, porous organic polymers, and metal-organic framework materials. The adsorption performance and processes for rare-earth elements are the focal points of discussion about these materials. Furthermore, this work investigates the potential applications of porous materials in the domain of the adsorption of rare-earth elements.

Discovery of Novel Receptor Tyrosine Kinase-like Orphan Receptor 1 (ROR1) Inhibitors for Cancer Treatment.

Receptor tyrosine kinase-like orphan receptor 1 (ROR1) is an oncogenic membrane protein in several malignancies and has been considered an attractive target for the treatment of human cancers. In this study, structure-based virtual screening and structure optimization were conducted to identify novel ROR1 inhibitors. Based on hit compound 2, 45 novel ROR1 inhibitors were designed and synthesized, and the detailed structure-activity relationship was investigated. Representative compound 19h potently binds ROR1 with a KD value of 0.10 µM, exhibiting antitumor activity in lung cancer and breast cancer cell lines (IC50: 0.36-1.37 µM). Additionally, a mechanism investigation demonstrated that compound 19h induces the apoptosis of tumor cells. Importantly, compound 19h significantly suppressed tumor growth in a mouse model without obvious toxicity. Overall, this work identified compound 19h as a new ROR1 inhibitor, providing a novel lead compound for the treatment of lung cancer and breast cancer.

SRSF9 promotes cell proliferation and migration of glioblastoma through enhancing CDK1 expression.

BACKGROUND: Glioblastoma (GBM) is a highly aggressive and prevalent brain tumor that poses significant challenges in treatment. SRSF9, an RNA-binding protein, is essential for cellular processes and implicated in cancer progression. Yet, its function and mechanism in GBM need clarification. METHODS: Bioinformatics analysis was performed to explore differential expression of SRSF9 in GBM and its prognostic relevance to glioma patients. SRSF9 and CDK1 expression in GBM cell lines and patients' tissues were quantified by RT-qPCR, Western blot or immunofluorescence assay. The role of SRSF9 in GBM cell proliferation and migration was assessed by MTT, Transwell and colony formation assays. Additionally, transcriptional regulation of CDK1 by SRSF9 was investigated using ChIP-PCR and dual-luciferase assays. RESULTS: The elevated SRSF9 expression correlates to GBM stages and poor survival of glioma patients. Through gain-of-function and loss-of-function strategies, SRSF9 was demonstrated to promote proliferation and migration of GBM cells. Bioinformatics analysis showed that SRSF9 has an impact on cell growth pathways including cell cycle checkpoints and E2F targets. Mechanistically, SRSF9 appears to bind to the promoter of CDK1 gene and increase its transcription level, thus promoting GBM cell proliferation. CONCLUSIONS: These findings uncover the cellular function of SRSF9 in GBM and highlight its therapeutic potential for GBM.

U-Shaped Relationship Between Fibrinogen Level and 10-year Mortality in Patients With Acute Coronary Syndrome: Prospective Cohort Study.

This study demonstrated that fibrinogen is an independent risk factor for 10-year mortality in patients with acute coronary syndrome (ACS), with a U-shaped nonlinear relationship observed between the two. These findings underscore the importance of monitoring fibrinogen levels and the consideration of long-term anti-inflammatory treatment in the clinical management of patients with ACS.

TSFAN: tensorized spatial-frequency attention network with domain adaptation for cross-session EEG-based biometric recognition.

Objective.Electroencephalogram (EEG) signals are promising biometrics owning to their invisibility, adapting to the application scenarios with high-security requirements. However, It is challenging to explore EEG identity features without the interference of device and state differences of the subject across sessions. Existing methods treat training sessions as a single domain, affected by the different data distribution among sessions. Although most multi-source unsupervised domain adaptation (MUDA) methods bridge the domain gap between multiple source and target domains individually, relationships among the domain-invariant features of each distribution alignment are neglected.Approach.In this paper, we propose a MUDA method, Tensorized Spatial-Frequency Attention Network (TSFAN), to assist the performance of the target domain for EEG-based biometric recognition. Specifically, significant relationships of domain-invariant features are modeled via a tensorized attention mechanism. It jointly incorporates appropriate common spatial-frequency representations of pairwise source and target but also cross-source domains, without the effect of distribution discrepancy among source domains. Additionally, considering the curse of dimensionality, our TSFAN is approximately represented in Tucker format. Benefiting the low-rank Tucker Network, the TSFAN can scale linearly in the number of domains, providing us the great flexibility to extend TSFAN to the case associated with an arbitrary number of sessions.Main results.Extensive experiments on the representative benchmarks demonstrate the effectiveness of TSFAN in EEG-based biometric recognition, outperforming state-of-the-art approaches, as verified by cross-session validation.Significance.The proposed TSFAN aims to investigate the presence of consistent EEG identity features across sessions. It is achieved by utilizing a novel tensorized attention mechanism that collaborates intra-source transferable information with inter-source interactions, while remaining unaffected by domain shifts in multiple source domains. Furthermore, the electrode selection shows that EEG-based identity features across sessions are distributed across brain regions, and 20 electrodes based on 10-20 standard system are able to extract stable identity information.

Transcriptomic and metabolomic profiles of Pirata subpiraticus in response to copper exposure.

Copper (Cu) contamination represents a persistent and significant form of heavy metal pollution in agricultural ecosystems, posing serious threats to organisms in current society. Spiders serve as crucial biological indicators for assessing the impact of heavy metals-induced toxicity. However, the specific molecular responses of spiders to Cu exposure and the mechanisms involved are not well understood. In our study, the wolf pond spiders, Pirata subpiraticus, were exposed to Cu for 21 d, resulting in a notable decline in survival rates compared with the control (n = 50, p < 0.05). We observed an increased expression of enzymes like glutathione peroxidase and superoxide dismutase (p < 0.05), signaling a strong oxidative stress response crucial for counteracting the harmful effects of reactive oxygen species. This response was corroborated by a rise in malondialdehyde levels (p < 0.05), a marker of lipid peroxidation and oxidative damage. Transcriptomic and metabolomic analyses revealed 2004 differentially expressed genes (DEGs) and 220 metabolites (DEMs). A significant number of these DEGs were involved in the glutathione biosynthetic process and antioxidant activity. A conjoint analysis revealed that under the Cu stress, several important enzymes and metabolites were altered (e.g., cathepsin A, legumain, and lysosomal acid lipase), affecting the activities of key biological processes and components, such as lysosome and insect hormone biosynthesis. Additionally, the protein interaction network analysis showed an up-regulation of processes like the apoptotic process, glutamate synthase activity, and peroxisome, suggesting that spiders activate cellular protective strategies to cope with stress and maintain homeostasis. This study not only deepens our understanding of spider biology in the context of environmental stress but also makes a significant contribution to the field of environmental stress biology.

Correction: Single molecule magnet features in luminescent lanthanide coordination polymers with heptacoordinate Dy/Yb(III) ions as nodes.

Correction for 'Single molecule magnet features in luminescent lanthanide coordination polymers with heptacoordinate Dy/Yb(III) ions as nodes' by Xiang-Tao Dong et al., Dalton Trans., 2023, 52, 12686-12694, https://doi.org/10.1039/D3DT02106H.

Topology Reconfiguration of Anion-Pillared Metal-Organic Framework from Flexibility to Rigidity for Enhanced Acetylene Separation.

Flexible metal-organic framework (MOF) adsorbents commonly encounter limitations in removing trace impurities below gate-opening threshold pressures. Topology reconfiguration can fundamentally eliminate intrinsic structural flexibility, yet remains a formidable challenge and is rarely achieved in practical applications. Herein, a solvent-mediated approach is presented to regulate the flexible CuSnF6-dpds-sql (dpds = 4,4''-dipyridyldisulfide) with sql topology into rigid CuSnF6-dpds-cds with cds topology. Notably, the cds topology is unprecedented and first obtained in anion-pillared MOF materials. As a result, rigid CuSnF6-dpds-cds exhibits enhanced C2H2 adsorption capacity of 48.61 cm3 g-1 at 0.01 bar compared to flexible CuSnF6-dpds-sql (21.06 cm3 g-1). The topology transformation also facilitates the adsorption kinetics for C2H2, exhibiting a 6.5-fold enhanced diffusion time constant (D/r2) of 1.71 × 10-3 s-1 on CuSnF6-dpds-cds than that of CuSnF6-dpds-sql (2.64 × 10-4 s-1). Multiple computational simulations reveal the structural transformations and guest-host interactions in both adsorbents. Furthermore, dynamic breakthrough experiments demonstrate that high-purity C2H4 (>99.996%) effluent with a productivity of 93.9 mmol g-1 can be directly collected from C2H2/C2H4 (1/99, v/v) gas-mixture in a single CuSnF6-dpds-cds column.