Fully Automatic Deep Learning Model for Spine Refracture in Patients with OVCF: A Multi-Center Study.

BACKGROUND: The reaserch of artificial intelligence (AI) model for predicting spinal refracture is limited to bone mineral density, X-ray and some conventional laboratory indicators, which has its own limitations. Besides, it lacks specific indicators related to osteoporosis and imaging factors that can better reflect bone quality, such as computed tomography (CT). OBJECTIVE: To construct a novel predicting model based on bone turn-over markers and CT to identify patients who were more inclined to suffer spine refracture. METHODS: CT images and clinical information of 383 patients (training set = 240 cases of osteoporotic vertebral compression fractures (OVCF), validation set = 63, test set = 80) were retrospectively collected from January 2015 to October 2022 at three medical centers. The U-net model was adopted to automatically segment ROI. Three-dimensional (3D) cropping of all spine regions was used to achieve the final ROI regions including 3D_Full and 3D_RoiOnly. We used the Densenet 121-3D model to model the cropped region and simultaneously build a T-NIPT prediction model. Diagnostics of deep learning models were assessed by constructing ROC curves. We generated calibration curves to assess the calibration performance. Additionally, decision curve analysis (DCA) was used to assess the clinical utility of the predictive models. RESULTS: The performance of the test model is comparable to its performance on the training set (dice coefficients of 0.798, an mIOU of 0.755, an SA of 0.767, and an OS of 0.017). Univariable and multivariable analysis indicate that T_P1NT was an independent risk factor for refracture. The performance of predicting refractures in different ROI regions showed that 3D_Full model exhibits the highest calibration performance, with a Hosmer-Lemeshow goodness-of-fit (HL) test statistic exceeding 0.05. The analysis of the training and test sets showed that the 3D_Full model, which integrates clinical and deep learning results, demonstrated superior performance with significant improvement (p-value < 0.05) compared to using clinical features independently or using only 3D_RoiOnly. CONCLUSION: T_P1NT was an independent risk factor of refracture. Our 3D-FULL model showed better performance in predicting high-risk population of spine refracture than other models and junior doctors do. This model can be applicable to real-world translation due to its automatic segmentation and detection.

Associations of ambient air pollution exposure and lifestyle factors with incident dementia in the elderly: A prospective study in the UK Biobank.

OBJECTIVE: Dementia is an important disease burden among the elderly, and its occurrence may be profoundly affected by environmental factors. Evidence of the relationship between air pollution and dementia is emerging, but the extent to which this can be offset by lifestyle factors remains ambiguous. METHODS: This study comprised 155,828 elder adults aged 60 years and above in the UK Biobank who were dementia-free at baseline. Cox proportional hazard models were conducted to examine the associations of annual average levels of air pollutants in 2010, including nitrogen dioxide (NO2), nitrogen oxides (NOX), particulate matter (PM2.5, PM10, and PMcoarse) and lifestyle factors recorded at baseline [physical activity (PA), sleep patterns, or smoking status] with incident risk of dementia, and their interactions on both multiplicative and additive scales. RESULTS: During a 12-year period of follow-up, 4,389 incidents of all-cause dementia were identified. For each standarddeviationincrease in ambient NO2, NOX or PM2.5, all-cause dementia risk increases by 1.07-fold [hazard ratio (HR) and 95 % confidence interval (CI) = 1.07 (1.04, 1.10)], 1.05-fold (95 % CI: 1.02, 1.08) and 1.07-fold (95 % CI: 1.04, 1.10), whereas low levels of PA, poor sleep patterns, and smoking are associated with an elevated risk of dementia [HR (95 % CI) = 1.17 (1.09, 1.26), 1.13 (1.00, 1.27), and 1.14 (1.07, 1.21), respectively]. Furthermore, these air pollutants show joint effects with low PA, poor sleep patterns, and smoking on the onset of dementia. The moderate to high levels of PA could significantly or marginally significantly modify the associations between NO2, NOX or PM2.5 (P-int = 0.067, 0.036, and 0.067, respectively) and Alzheimer's disease (AD), but no significant modification effects are found for sleep patterns or smoking status. CONCLUSION: The increased exposures of NO2, NOX, or PM2.5 are associated with elevated risk of dementia among elderly UK Biobank population. These air pollutants take joint effects with low PA, poor sleep patterns, and smoking on the development of dementia. In addition, moderate to high levels of PA could attenuate the incident risk of AD caused by air pollution. Further prospective researches among other cohort populations are warranted to validate these findings.

Health-related quality of life in children with childhood acute myeloid leukemia in China: A five-year prospective study.

Purpose: This study aims to identify the key factors influencing health-related quality of life (HRQoL) of pediatric acute myeloid leukemia (AML) patients following their initial diagnosis and examine their impact on the five-year survival prognosis. Methods: A chart review and follow-up were conducted for children with AML who participated in a prospective cohort study between 2017 and 2020. We identified factors influencing HRQoL through Pediatric Quality of Life Inventory™ (PedsQL™ 4.0), PedsQL™ Cancer Module 3.0 (CM 3.0) and PedsQL™ Family Impact Module 2.0 (FIM 2.0), as well as assessed the impact of impaired HRQoL on the overall outcomes of patients. Results: Sixty-four subjects enrolled in the study had complete HRQoL outcome data, and 61 of them completed the 5-year follow-up. In CM 3.0, age was positively associated with parental proxy reports (p = 0.040), whereas divorced families were negatively associated with child self-reports (p = 0.045). A positive medical history correlates with FIM 2.0 (p = 0.025). Residence (p = 0.046), the occupation of caregivers (p = 0.014), disease severity (p = 0.024), and the only child (p = 0.029) exhibited statistically significant associations with the impairment of HRQoL. Impaired HRQoL scores shown by the PedsQL™4.0 parent proxy report (p = 0.013) and FIM 2.0 (p = 0.011) were associated with a reduced 5-year survival rate. Conclusions: This study demonstrated that early impairment of HRQoL in pediatric acute myeloid leukemia patients has predictive value for long-term prognosis. Once validated, these findings may provide some guidance to clinicians treating children with AML.

Organic solid-electrolyte interface layers for Zn metal anodes.

Zinc ion batteries (ZIBs) have emerged as promising candidates for renewable energy storage owing to their affordability, safety, and sustainability. However, issues with Zn metal anodes, such as dendrite growth, hydrogen evolution reaction (HER), and corrosion, significantly hinder the practical application of ZIBs. To address these issues, organic solid electrolyte interface (SEI) layers have gained traction in the ZIB community as they can, for instance, help achieve uniform Zn plating/stripping and suppress side reactions. This article summarizes recent advances in organic artificial SEI layers for ZIB anodes, including their fabrication methods, electrochemical performance, and degradation suppression mechanisms.

Dependence of evolution of Cyanobacteria superiority on temperature and nutrient use efficiency in a meso-eutrophic plateau lake.

Algal blooms in lakes have been a challenging environmental issue globally under the dual influence of human activity and climate change. Considerable progress has been made in the study of phytoplankton dynamics in lakes; The long-term in situ evolution of dominant bloom-forming cyanobacteria in meso-eutrophic plateau lakes, however, lacks systematic research. Here, the monthly parameters from 12 sampling sites during the period of 1997-2022 were utilized to investigate the underlying mechanisms driving the superiority of bloom-forming cyanobacteria in Erhai, a representative meso-eutrophic plateau lake. The findings indicate that global warming will intensify the risk of cynaobacteria blooms, prolong Microcystis blooms in autumn to winter or even into the following year, and increase the superiority of filamentous Planktothrix and Cylindrospermum in summer and autumn. High RUETN (1.52 Biomass/TN, 0.95-3.04 times higher than other species) under N limitation (TN < 0.5 mg/L, TN/TP < 22.6) in the meso-eutrophic Lake Erhai facilitates the superiority of Dolichospermum. High RUETP (43.8 Biomass/TP, 2.1-10.2 times higher than others) in TP of 0.03-0.05 mg/L promotes the superiority of Planktothrix and Cylindrospermum. We provided a novel insight into the formation of Planktothrix and Cylindrospermum superiority in meso-eutrophic plateau lake with low TP (0.005-0.07 mg/L), which is mainly influenced by warming, high RUETP and their vertical migration characteristics. Therefore, we posit that although the obvious improvement of lake water quality is not directly proportional to the control efficacy of cyanobacterial blooms, the evolutionary shift in cyanobacteria population structure from Microcystis, which thrives under high nitrogen and phosphorus conditions, to filamentous cyanobacteria adapted to low nitrogen and phosphorus levels may serve as a significant indicator of water quality amelioration. Therefore, we suggest that the risk of filamentous cyanobacteria blooms in the meso-eutrophic plateau lake should be given attention, particularly in light of improving water quality and global warming, to ensure drinking water safety.

Small object detection algorithm incorporating swin transformer for tea buds.

Accurate identification of small tea buds is a key technology for tea harvesting robots, which directly affects tea quality and yield. However, due to the complexity of the tea plantation environment and the diversity of tea buds, accurate identification remains an enormous challenge. Current methods based on traditional image processing and machine learning fail to effectively extract subtle features and morphology of small tea buds, resulting in low accuracy and robustness. To achieve accurate identification, this paper proposes a small object detection algorithm called STF-YOLO (Small Target Detection with Swin Transformer and Focused YOLO), which integrates the Swin Transformer module and the YOLOv8 network to improve the detection ability of small objects. The Swin Transformer module extracts visual features based on a self-attention mechanism, which captures global and local context information of small objects to enhance feature representation. The YOLOv8 network is an object detector based on deep convolutional neural networks, offering high speed and precision. Based on the YOLOv8 network, modules including Focus and Depthwise Convolution are introduced to reduce computation and parameters, increase receptive field and feature channels, and improve feature fusion and transmission. Additionally, the Wise Intersection over Union loss is utilized to optimize the network. Experiments conducted on a self-created dataset of tea buds demonstrate that the STF-YOLO model achieves outstanding results, with an accuracy of 91.5% and a mean Average Precision of 89.4%. These results are significantly better than other detectors. Results show that, compared to mainstream algorithms (YOLOv8, YOLOv7, YOLOv5, and YOLOx), the model improves accuracy and F1 score by 5-20.22 percentage points and 0.03-0.13, respectively, proving its effectiveness in enhancing small object detection performance. This research provides technical means for the accurate identification of small tea buds in complex environments and offers insights into small object detection. Future research can further optimize model structures and parameters for more scenarios and tasks, as well as explore data augmentation and model fusion methods to improve generalization ability and robustness.

Hand skeletal features of children and adolescents with different growth statuses and periods.

Background: The hand skeletal features of children and adolescents at different growth statuses and development periods, and the correlation between these skeletal features and hand asymmetric force are currently unclear. Thus, this study sought to investigate the hand skeletal features of children and adolescents at different growth statuses and at different periods of development, and the correlation between these skeletal features and asymmetric force in hands. Methods: A retrospective study was performed on subjects aged 4-20 years with good growth status (group A) or short stature (group B). Additional subjects aged 4-20, 21-40, and >40 years were enrolled in groups C, D, and E, respectively. All the subjects underwent left-hand posteroanterior X-ray radiography. Brachymesophalangia-V (BMP-V), conical epiphysis, epiphysis/metaphysis symmetry of the proximal phalanx (ESP), and the angle of the metacarpal-phalangeal axis were analyzed. Results: Of the 654 children and teenagers aged 4-20 years (median: 11 years) enrolled in the study, 432 were allocated to group A, of whom 237 (54.9%) were male and 195 (45.1%) were female, and 222 matched cases were allocated to group B, of whom 112 (50.5%) were male and 110 (49.5%) were female. The first to third ESPs were significantly (P<0.05) greater in group A than in group B, while the first to third angles of the metacarpal-phalangeal axis were significantly (P<0.05) smaller in group A than in group B. The correlation analysis revealed a highly significant (P<0.01) negative correlation between the ESP and angle of the metacarpal-phalangeal axis (r=-0.948, -0.926, -0.940, -0.885, and -0.848, respectively). The incidence of BMP-V was 15.4% in all patients, while that of conical epiphysis was 19.5%. The incidence of BMP-V and conical epiphysis was significantly (P<0.05) smaller in group A than in group B (11.1% vs. 23.8% for BMP-V and 16.6% vs. 25.2% for conical epiphysis, respectively). Additionally, 216 subjects were enrolled in group C (108 male and 108 female), 185 subjects were enrolled in in group D (93 male and 92 female), and 176 subjects were enrolled in in group E (104 male and 72 female). The second to fifth ESPs in group C were significantly (P<0.05) smaller than those in both groups D and E, while the second to fifth angles of the metacarpal-phalangeal axis were significantly (P<0.05) larger in group C than in both groups D and E. A BMP-V was present in 35 (16.2%) patients in group C, 8 (4.3%) in group D, and 2 (1.1%) in group E, and the difference among the three groups was statistically significant (P<0.05). Conclusions: The epiphyseal symmetry of the proximal phalanges is poor in short stature children and adolescents, and the angle between the metacarpal and phalangeal axes is larger in children and adolescents with short stature than those with normal height and good growth status. A negative correlation was found between the epiphyseal symmetry of the proximal phalanges and asymmetrical stress.

Mediation of association between benzo[a]pyrene exposure and lung cancer risk by plasma microRNAs: A Chinese case-control study.

Epidemiologic studies have reported the positive relationship of benzo[a]pyrene (BaP) exposure with the risk of lung cancer. However, the mechanisms underlying the relationship is still unclear. Plasma microRNA (miRNA) is a typical epigenetic biomarker that was linked to environment exposure and lung cancer development. We aimed to reveal the mediation effect of plasma miRNAs on BaP-related lung cancer. We designed a lung cancer case-control study including 136 lung cancer patients and 136 controls, and measured the adducts of benzo[a]pyrene diol epoxide-albumin (BPDE-Alb) and sequenced miRNA profiles in plasma. The relationships between BPDE-Alb adducts, normalized miRNA levels and the risk of lung cancer were assessed by linear regression models. The mediation effects of miRNAs on BaP-related lung cancer were investigated. A total of 190 plasma miRNAs were significantly related to lung cancer status at Bonferroni adjusted P < 0.05, among which 57 miRNAs showed different levels with |fold change| > 2 between plasma samples before and after tumor resection surgery at Bonferroni adjusted P < 0.05. Especially, among the 57 lung cancer-associated miRNAs, BPDE-Alb adducts were significantly related to miR-17-3p, miR-20a-3p, miR-135a-5p, miR-374a-5p, miR-374b-5p, miR-423-5p and miR-664a-5p, which could in turn mediate a separate 42.2%, 33.0%, 57.5%, 36.4%, 48.8%, 32.5% and 38.2% of the relationship of BPDE-Alb adducts with the risk of lung cancer. Our results provide non-invasion biomarker candidates for lung cancer, and highlight miRNAs dysregulation as a potential intermediate mechanism by which BaP exposure lead to lung tumorigenesis.

Force-induced Caspase-1-dependent pyroptosis regulates orthodontic tooth movement.

Pyroptosis, an inflammatory caspase-dependent programmed cell death, plays a vital role in maintaining tissue homeostasis and activating inflammatory responses. Orthodontic tooth movement (OTM) is an aseptic force-induced inflammatory bone remodeling process mediated by the activation of periodontal ligament (PDL) progenitor cells. However, whether and how force induces PDL progenitor cell pyroptosis, thereby influencing OTM and alveolar bone remodeling remains unknown. In this study, we found that mechanical force induced the expression of pyroptosis-related markers in rat OTM and alveolar bone remodeling process. Blocking or enhancing pyroptosis level could suppress or promote OTM and alveolar bone remodeling respectively. Using Caspase-1-/- mice, we further demonstrated that the functional role of the force-induced pyroptosis in PDL progenitor cells depended on Caspase-1. Moreover, mechanical force could also induce pyroptosis in human ex-vivo force-treated PDL progenitor cells and in compressive force-loaded PDL progenitor cells in vitro, which influenced osteoclastogenesis. Mechanistically, transient receptor potential subfamily V member 4 signaling was involved in force-induced Caspase-1-dependent pyroptosis in PDL progenitor cells. Overall, this study suggested a novel mechanism contributing to the modulation of osteoclastogenesis and alveolar bone remodeling under mechanical stimuli, indicating a promising approach to accelerate OTM by targeting Caspase-1.

DNA methylation aging signatures of multiple metals exposure and their mediation effects in metal-associated mortality: Evidence from the Dongfeng-Tongji cohort study.

Humans were exposed to multiple metals, but the impact of metals on DNA methylation-age (DNAm-age), a well-recognized aging measure, remains inconclusive. This study included 2942 participants from the Dongfeng-Tongji cohort. We detected their plasma concentrations of 23 metals and determined their genome-wide DNA methylation using the Illumina Human-MethylationEPIC BeadChip. Five DNAm-age acceleration indexes (DAIs), including HannumAge-Accel, HorvathAge-Accel, PhenoAge-Accel, GrimAge-Accel (residual from regressing corresponding DNAm-age on chronological age) and DNAm-mortality score (DNAm-MS), were separately calculated. We found that each 1-unit increase in ln-transformed copper (Cu) was associated with a separate 1.02-, 0.83- and 0.07-unit increase in PhenoAge-Accel, GrimAge-Accel, and DNAm-MS (all FDR<0.05). Each 1-unit increase in ln-transformed nickel (Ni) was associated with a 0.34-year increase in PhenoAge-Accel, while each 1-unit increase in ln-transformed strontium (Sr) was associated with a 0.05-unit increase in DNAm-MS. The Cu, Ni and Sr showed joint positive effects on above three DAIs. PhenoAge-Accel, GrimAge-Accel, and DNAm-MS mediated a separate 6.5%, 12.3%, 6.0% of the positive association between Cu and all-cause mortality; GrimAge-Accel mediated 14.3% of the inverse association of selenium with all-cause mortality. Our findings revealed the effects of Cu, Ni, Sr and their co-exposure on accelerated aging and highlighted mediation roles of DNAm-age on metal-associated mortality.

Application of machine learning standardized integral area algorithm in measuring the scoliosis.

This study was to develop a computer vision evaluation method to automatically measure the degree of scoliosis based on the machine learning algorithm. For the X-ray images of 204 patients with idiopathic scoliosis who underwent full-spine radiography, histogram equalization of original image was performed before a flipping method was used to magnify asymmetric elements, search for the global maximum pixel value in each line, and scan local maximal pixel value, with the intersection set of two point sets being regarded as candidate anchor points. All fine anchors were fitted with cubic spline algorithm to obtain the approximate curve of the spine, and the degree of scoliosis was measured by the standardized integral area. All measured data were analyzed. In manual measurement, the Cobb angle was 11.70-25.00 (20.15 ± 3.60), 25.20-44.70 (33.89 ± 5.41), and 45.10-49.40 (46.98 ± 1.25) in the mild, moderate and severe scoliosis group, respectively, whereas the value for the standardized integral area algorithm was 0.072-0.298 (0.185 ± 0.040), 0.100-0.399 (0.245 ± 0.050), and 0.246-0.901 (0.349 ± 0.181) in the mild, moderate and severe scoliosis group, respectively. Correlation analysis between the manual measurement of the Cobb angle and the evaluation of the standardized integral area algorithm demonstrated the Spearman correlation coefficient r = 0.643 (P < 0.001). There was a positive correlation between the manual measurement of the Cobb angle and the measurement of the standardized integral area value. Two methods had good consistency in evaluating the degree of scoliosis. ROC curve analysis of the standardized integral area algorithm to measure the degree of scoliosis showed he cutoff value of the standardized integral area algorithm was 0.20 for the moderate scoliosis with an AUC of 0.865, sensitivity 0.907, specificity 0.635, accuracy 0.779, positive prediction value 0.737 and negative prediction value 0.859, and the cutoff value of the standardized integral area algorithm was 0.40 for the severe scoliosis with an AUC of 0.873, sensitivity 0.188, specificity 1.00, accuracy 0.936, positive prediction value 1 and a negative prediction value 0.935. Using the standardized integral area as an independent variable and the Cobb angle as a dependent variable, a linear regression equation was established as Cobb angle = 13.36 + 70.54 × Standardized area, the model has statistical significance. In conclusion, the integrated area algorithm method of machine learning can quickly and efficiently assess the degree of scoliosis and is suitable for screening the degree of scoliosis in a large dataset as a useful supplement to the fine measurement of scoliosis Cobb angle.

Self-promoted electroactive biomimetic mineralized scaffolds for bacteria-infected bone regeneration.

Infected bone defects are a major challenge in orthopedic treatment. Native bone tissue possesses an endogenous electroactive interface that induces stem cell differentiation and inhibits bacterial adhesion and activity. However, traditional bone substitutes have difficulty in reconstructing the electrical environment of bone. In this study, we develop a self-promoted electroactive mineralized scaffold (sp-EMS) that generates weak currents via spontaneous electrochemical reactions to activate voltage-gated Ca2+ channels, enhance adenosine triphosphate-induced actin remodeling, and ultimately achieve osteogenic differentiation of mesenchymal stem cells by activating the BMP2/Smad5 pathway. Furthermore, we show that the electroactive interface provided by the sp-EMS inhibits bacterial adhesion and activity via electrochemical products and concomitantly generated reactive oxygen species. We find that the osteogenic and antibacterial dual functions of the sp-EMS depend on its self-promoting electrical stimulation. We demonstrate that in vivo, the sp-EMS achieves complete or nearly complete in situ infected bone healing, from a rat calvarial defect model with single bacterial infection, to a rabbit open alveolar bone defect model and a beagle dog vertical bone defect model with the complex oral bacterial microenvironment. This translational study demonstrates that the electroactive bone graft presents a promising therapeutic platform for complex defect repair.

Deep Learning-Predicted Dihydroartemisinin Rescues Osteoporosis by Maintaining Mesenchymal Stem Cell Stemness through Activating Histone 3 Lys 9 Acetylation.

Maintaining the stemness of bone marrow mesenchymal stem cells (BMMSCs) is crucial for bone homeostasis and regeneration. However, in vitro expansion and bone diseases impair BMMSC stemness, limiting its functionality in bone tissue engineering. Using a deep learning-based efficacy prediction system and bone tissue sequencing, we identify a natural small-molecule compound, dihydroartemisinin (DHA), that maintains BMMSC stemness and enhances bone regeneration. During long-term in vitro expansion, DHA preserves BMMSC stemness characteristics, including its self-renewal ability and unbiased differentiation. In an osteoporosis mouse model, oral administration of DHA restores the femur trabecular structure, bone density, and BMMSC stemness in situ. Mechanistically, DHA maintains BMMSC stemness by promoting histone 3 lysine 9 acetylation via GCN5 activation both in vivo and in vitro. Furthermore, the bone-targeted delivery of DHA by mesoporous silica nanoparticles improves its therapeutic efficacy in osteoporosis. Collectively, DHA could be a promising therapeutic agent for treating osteoporosis by maintaining BMMSC stemness.

Prim-O-glucosylcimifugin ameliorates aging-impaired endogenous tendon regeneration by rejuvenating senescent tendon stem/progenitor cells.

Adult tendon stem/progenitor cells (TSPCs) are essential for tendon maintenance, regeneration, and repair, yet they become susceptible to senescence with age, impairing the self-healing capacity of tendons. In this study, we employ a recently developed deep-learning-based efficacy prediction system to screen potential stemness-promoting and senescence-inhibiting drugs from natural products using the transcriptional signatures of stemness. The top-ranked candidate, prim-O-glucosylcimifugin (POG), a saposhnikovia root extract, could ameliorate TPSC senescent phenotypes caused by long-term passage and natural aging in rats and humans, as well as restore the self-renewal and proliferative capacities and tenogenic potential of aged TSPCs. In vivo, the systematic administration of POG or the local delivery of POG nanoparticles functionally rescued endogenous tendon regeneration and repair in aged rats to levels similar to those of normal animals. Mechanistically, POG protects TSPCs against functional impairment during both passage-induced and natural aging by simultaneously suppressing nuclear factor-κB and decreasing mTOR signaling with the induction of autophagy. Thus, the strategy of pharmacological intervention with the deep learning-predicted compound POG could rejuvenate aged TSPCs and improve the regenerative capacity of aged tendons.

Copper isotope evidence for sulfide fractionation and lower crustal foundering in making continental crust.

The continental crust is strongly depleted in copper compared with its building blocks-primary arc magmas-and this depletion is intrinsically associated with continental crust formation. However, the process by which Cu removal occurs remains enigmatic. Here we show, using Cu isotopes, that subduction-zone processes and mantle melting produce limited fractionation of Cu isotopes in arc magmas, and, instead, the heterogeneous Cu isotopic compositions of lower crustal rocks, which negatively correlate with Cu contents, suggest segregation or accumulation of isotopically light sulfides during intracrustal differentiation of arc magmas. This is supported by the extremely light Cu isotopic compositions of lower crustal mafic cumulates and heavy Cu isotopic compositions of differentiated magmas in thick continental arcs. Intracrustal differentiation of mantle-derived magmas and subsequent foundering of sulfide-rich mafic cumulates preferentially removes isotopically light Cu, leaving a Cu-depleted and isotopically heavy continental crust.

High-precision zinc isotope measurement of chemically different geostandards by multicollector inductively coupled plasma mass spectrometry.

RATIONALE: Zinc isotopes are becoming increasingly applicable in high-temperature geochemistry, for example in crust-mantle interaction and volatilization-related processes. The published zinc isotope data for some commonly used reference materials, however, show large interlaboratory offsets. In addition, there is still limited data for zinc isotope compositions of many widely used geological reference materials. METHODS: For precise and accurate zinc isotopic ratio analysis of chemically diverse geostandards, including ultramafic to felsic igneous rocks, carbonatites, sediments and soils, an improved procedure for chemical purification of zinc was introduced in this study. The factors potentially affecting zinc isotopic ratio measurement were assessed. The accuracy and long-term reproducibility were obtained by measurements on both synthetic solutions and well-characterized geostandards. RESULTS: Purification of geologic samples with different zinc concentrations and matrix compositions yields consistent elution curves with nearly 100% recovery. Acidity and concentration mismatches and the presence of some matrix elements (e.g., Mg, Ti and Cr) have significant impacts on the precision and accuracy of zinc isotopic ratio measurement. The zinc isotope compositions of a suite of reference materials were measured using this method. CONCLUSIONS: The present study describes methods for the chemical purification of zinc and high-precision and accurate zinc isotopic ratio measurements using multicollector inductively coupled plasma mass spectrometer (MC-ICP-MS). The long-term external reproducibility for δ66 Zn values is ±0.04‰ (2SD). High-quality zinc isotope data of chemically different geostandards were reported to stimulate future interlaboratory calibrations.

Insight into the Mechanisms of Nitride Films with Excellent Hardness and Lubricating Performance: A Review.

Transition metal nitride (TMN) films with excellent hardness and lubricating performance are versatile low dimension materials, which are widely used in various fields including industries, transportation, aerospace, and so on. This paper introduces one film design strategy and provides a review of the mechanisms for strengthening and lubricating nitride films. The design strategy refers to two aspects which determine the structures, the performance, the components, and the chemical constitutions of nitride films The strengthening mechanisms of nitride films are then illuminated in detail, including the solid solution effect, the grain size effect, the secondary phase effect, the stress or stress field effect, the template effect, and the valence electron concentration effect. Five lubricating mechanisms are next summarized, including the easy-shear nature, the tribo-chemical reactions, the lubricious fluorides, the textured contact surface, and the synergistic effect. This paper aims to give a comprehensive introduction for understanding the mechanisms of strengthening and lubrication of nitride films for students and researchers, as well as to understand the current research progress in nitride films for exploring research gaps.

Structure transformation from Sierpinski triangles to chains assisted by gas molecules.

Reversible transformations between fractals and periodic structures are of fundamental importance for understanding the formation mechanism of fractals. Currently, it is still a challenge to controllably achieve such a transformation. We investigate the effect of CO and CO2 molecules on Sierpinski triangles (STs) assembled from Fe atoms and 4,4″-dicyano-1,1':3',1″-terphenyl (C3PC) molecules on Au surfaces. Using scanning tunneling microscopy, we discover that the gas molecules induce a transition from STs into 1D chains. Based on density functional theory modeling, we propose that the atomistic mechanism involves the transformation of a stable 3-fold coordination Fe(C3PC)3 motif to Fe(C3PC)4 with an axially bonded CO molecule. CO2 causes the structural transformation through a molecular catassembly process.

The Diagnostic Value of miR-124a Expression in Peripheral Blood and Synovial Fluid of Patients with Rheumatoid Arthritis.

INTRODUCTION: Rheumatoid arthritis (RA), a chronic autoimmune disorder, is currently a severe health threat. Previous studies have documented the altered expression of various miRNAs in RA patients. This study determined the expression of miR-124a in RA patients and estimated its diagnostic value for RA. METHODS: A total of 80 RA patients were enrolled as the study subjects, and 36 patients with osteoarthritis were included, with another 36 healthy people as the controls. miR-124a expression levels in peripheral blood plasma, peripheral blood mononuclear cells (PBMCs), and synovial fluid were measured using reverse transcription quantitative polymerase chain reaction, followed by Pearson correlation analysis. Additionally, the association between miR-124a and major clinical indicators was assessed, such as rheumatoid factor (RF), erythrocyte sedimentation rate (ESR), and disease activity score of 28 joints (DAS28). The diagnostic efficacy of miR-124a expression in plasma, PBMCs, and synovial fluid for RA was evaluated by the receiver operating characteristic curve, and the difference in the area under the curve (AUC) was analyzed. RESULTS: miR-124a was downregulated in RA patients, and the expression levels of miR-124a in plasma, PBMCs, and synovial fluid showed a certain degree of positive correlation. miR-124a was inversely linked with RF, ESR, and DAS28. For the diagnosis of RA patients, the AUC of plasma miR-124a was 0.899 and the cut-off value was 0.800, with 68.75% sensitivity and 94.44% specificity; the AUC of miR-124a in PBMCs was 0.937 and the cut-off value was 0.805, with 82.50% sensitivity and 91.67% specificity; the AUC of miR-124a in plasma combined with PBMCs was 0.961, with a higher diagnostic value than independent plasma or PBMCs; the AUC of miR-124a in synovial fluid was 0.929 and the cut-off value was 0.835, with 80.00% sensitivity and 88.89% specificity. CONCLUSION: miR-124a expression is downregulated in the plasma, PBMCs, and synovial fluid of RA patients and has a high diagnostic value for RA.