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Droplet-based single-cell sequencing techniques rely on the fundamental assumption that each droplet encapsulates a single cell, enabling individual cell omics profiling. However, the inevitable issue of multiplets, where two or more cells are encapsulated within a single droplet, can lead to spurious cell type annotations and obscure true biological findings. The issue of multiplets is exacerbated in single-cell multiomics settings, where integrating cross-modality information for clustering can inadvertently promote the aggregation of multiplet clusters and increase the risk of erroneous cell type annotations. Here, we propose a compound Poisson model-based framework for multiplet detection in single-cell multiomics data. Leveraging experimental cell hashing results as the ground truth for multiplet status, we conducted trimodal DOGMA-seq experiments and generated 17 benchmarking datasets from two tissues, involving a total of 280,123 droplets. We demonstrated that the proposed method is an essential tool for integrating cross-modality multiplet signals, effectively eliminating multiplet clusters in single-cell multiomics data-a task at which the benchmarked single-omics methods proved inadequate.
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Análisis de la Célula Individual , Análisis de la Célula Individual/métodos , Humanos , Animales , Análisis por Conglomerados , Algoritmos , Ratones , Distribución de Poisson , MultiómicaRESUMEN
Heart failure (HF) is a significant global public health concern with a high readmission rate, posing a serious threat to the health of the elderly population. While several studies have used machine learning (ML) to develop all-cause readmission risk prediction models for elderly patients with HF, few have integrated ML-selected features with those chosen by human experts to assess HF patients readmission. A retrospective analysis of 8396 elderly HF patients hospitalized at the Affiliated Hospital of North Sichuan Medical College from January 1, 2018 to December 31, 2021 was conducted. Variables selected by XGBoost, LASSO regression, and random forest constituted the machine group, while the human expert group comprised variables chosen by two experienced cardiovascular professors. The variables selected by both groups were combined to form a human-machine collaboration group. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) method was used to elucidate the importance of each predictive feature, explain the impact of individual features on the model, and provide visual representation. A total of 73 features were included for model development. The human-machine collaboration model, utilizing CatBoost, achieved an AUC of 0.83617, an F1-score of 0.73521, and a Brier score of 0.16536 on the validation set. This model demonstrated superior predictive performance compared to those created solely by human experts or machine. The SHAP plot was then used to visually display the feature analysis of the human-machine collaboration model, revealing HGB, NT-proBNP, smoking history, NYHA classification, and LVEF as the 5 most important features. This study indicate that the human-machine collaboration model outperforms those relying solely on human expert selection or machine algorithm at predicting all-cause readmission in elderly HF patients. The application of the SHAP method enhanced the interpretability of the model outcomes, aiding clinicians in accurately pinpointing risk factors associated with HF readmission. This advancement enables the formulation of tailored treatment strategies, offering a more personalized approach to patient care.
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Insuficiencia Cardíaca , Aprendizaje Automático , Readmisión del Paciente , Humanos , Insuficiencia Cardíaca/epidemiología , Readmisión del Paciente/estadística & datos numéricos , Anciano , Femenino , Masculino , Estudios Retrospectivos , Anciano de 80 o más Años , Factores de Riesgo , Medición de Riesgo/métodos , Curva ROCRESUMEN
To investigate the factors that influence readmissions in patients with acute non-ST elevation myocardial infarction (NSTEMI) after percutaneous coronary intervention (PCI) by using multiple machine learning (ML) methods to establish a predictive model. In this study, 1576 NSTEMI patients who were hospitalized at the Affiliated Hospital of North Sichuan Medical College were selected as the research subjects. They were divided into two groups: the readmitted group and the non-readmitted group. The division was based on whether the patients experienced complications or another incident of myocardial infarction within one year after undergoing PCI. Common variables selected by univariate and multivariate logistic regression, LASSO regression, and random forest were used as independent influencing factors for NSTEMI patients' readmissions after PCI. Six different ML models were constructed using these common variables. The area under the ROC curve, accuracy, sensitivity, and specificity were used to evaluate the performance of the six ML models. Finally, the optimal model was selected, and a nomogram was created to visually represent its clinical effectiveness. Three different methods were used to select seven representative common variables. These variables were then utilized to construct six different ML models, which were subsequently compared. The findings indicated that the LR model exhibited the most optimal performance in terms of AUC, accuracy, sensitivity, and specificity. The outcome, admission mode (walking and non-walking), communication ability, CRP, TC, HDL, and LDL were identified as independent predicators of readmissions in NSTEMI patients after PCI. The prediction model constructed by the LR algorithm was the best. The established column graph model established proved to be effective in identifying high-risk groups with high accuracy and differentiation. It holds a specific predictive value for the occurrence of readmissions after direct PCI in NSTEMI patients.
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Aprendizaje Automático , Infarto del Miocardio sin Elevación del ST , Readmisión del Paciente , Intervención Coronaria Percutánea , Humanos , Intervención Coronaria Percutánea/efectos adversos , Intervención Coronaria Percutánea/métodos , Readmisión del Paciente/estadística & datos numéricos , Masculino , Femenino , Infarto del Miocardio sin Elevación del ST/cirugía , Persona de Mediana Edad , Anciano , Factores de Riesgo , Medición de Riesgo/métodos , Curva ROCRESUMEN
The metapopulation network model is a mathematical framework used to study the spatial spread of epidemics with individuals' mobility. In this paper, we develop a time-varying network model in which the activity of a population is correlated with its attractiveness in mobility. By studying the spreading dynamics of the SIR (susceptible-infectious-recovered)-type disease in different correlated networks based on the proposed model, we theoretically derive the mobility threshold and numerically observe that increasing the correction between activity and attractiveness results in a reduced mobility threshold but suppresses the fraction of infected subpopulations. It also introduces greater heterogeneity in the spatial distribution of infected individuals. Additionally, we investigate the impact of nonpharmaceutical interventions on the spread of epidemics in different correlation networks. Our results show that the simultaneous implementation of self-isolation and self-protection is more effective in negatively correlated networks than that in positively correlated or non-correlated networks. Both self-isolation and self-protection strategies enhance the mobility threshold and, thus, slow down the spread of the epidemic. However, the effectiveness of each strategy in reducing the fraction of infected subpopulations varies in different correlated networks. Self-protection is more effective in positively correlated networks, whereas self-isolation is more effective in negatively correlated networks. Our study will provide insights into epidemic prevention and control in large-scale time-varying metapopulation networks.
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Epidemias , Humanos , Enfermedades Transmisibles/epidemiología , Enfermedades Transmisibles/transmisión , Factores de Tiempo , Dinámica PoblacionalRESUMEN
Ischemic stroke is a common type of stroke that significantly affects human well-being and quality of life. In order to further characterize the pathophysiology of ischemic stroke and develop new treatment strategies, ischemic stroke models with controllable and consistent response to potential clinical treatments are urgently needed. The middle cerebral artery occlusion (MCAO) model is currently the most widely used animal model of ischemic stroke. This review discusses various methods for constructing the MCAO model and compares their advantages and disadvantages in order to provide better approaches for studying ischemic stroke.
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Intracranial aneurysms (IAs) are highly prevalent in the population, and their rupture poses a significant risk of death or disability. However, the treatment of aneurysms, whether through interventional embolization or craniotomy clipping surgery, is not always safe and carries a certain proportion of morbidity and mortality. Therefore, early detection and prompt intervention of IAs with a high risk of rupture is of notable clinical significance. Moreover, accurately predicting aneurysms that are likely to remain stable can help avoid the risks and costs of over-intervention, which also has considerable social significance. Recent advances in artificial intelligence (AI) technology offer promising strategies to assist clinical trials. This review will discuss the state-of-the-art AI applications for assessing the rupture risk of IAs, with a focus on achievements, challenges, and potential opportunities.
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Early brain injury (EBI) subsequent to subarachnoid hemorrhage (SAH) is strongly associated with delayed cerebral ischemia and poor patient prognosis. Based on investigations into the molecular mechanisms underlying EBI, neurovascular dysfunction resulting from SAH can be attributed to a range of pathological processes, such as microvascular alterations in brain tissue, ionic imbalances, blood-brain barrier disruption, immune-inflammatory responses, oxidative stress, and activation of cell death pathways. Research progress presents a variety of promising therapeutic approaches for the preservation of neurological function following SAH, including calcium channel antagonists, endothelin-1 receptor blockers, antiplatelet agents, anti-inflammatory agents, and anti-oxidative stress agents. EBI can be mitigated following SAH through neuroprotective measures. To enhance our comprehension of the relevant molecular pathways involved in brain injury, including brain ischemia-hypoxic injury, neuroimmune inflammation activation, and the activation of various cell-signaling pathways, following SAH, it is essential to investigate the evolution of these multifaceted pathophysiological processes. Facilitating neural repair following a brain injury is critical for improving patient survival rates and quality of life.
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Psychotic symptoms are reported as one of the most common complications of Alzheimer's disease (AD), in whom they are associated with more rapid deterioration and increased mortality. Empiric treatments, namely first and second-generation antipsychotics, confer modest efficacy in patients with AD and with psychosis (AD+P) and themselves increase mortality. Recent studies suggested the use and beneficial effects of antidepressants among patients with AD+P. This motivates our rationale for exploring their potential as a novel combination therapy option among these patients. We included electronic medical records of 10,260 patients with AD in our study. Survival analysis was performed to assess the effects of the combination of antipsychotics and antidepressants on the mortality of these patients. A protein-protein interaction network representing AD+P was built, and network analysis methods were used to quantify the efficacy of these drugs on AD+P. A combined score was developed to measure the potential synergetic effect against AD+P. Our survival analyses showed that the co-administration of antidepressants with antipsychotics have a significant beneficial effect in reducing mortality. Our network analysis showed that the targets of antipsychotics and antidepressants are well-separated, and antipsychotics and antidepressants have similar Signed Jaccard Index (SJI) scores to AD+P. Eight drug pairs, including some popular recommendations like aripiprazole/sertraline, showed higher than average scores which suggest their potential in treating AD+P via strong synergetic effects. Our proposed combinations of antipsychotic and antidepressant therapy showed a strong superiority over current antipsychotics treatment for AD+P. The observed beneficial effects can be further strengthened by optimizing drug-pair selection based on our systems pharmacology analysis.
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Enfermedad de Alzheimer , Antipsicóticos , Trastornos Psicóticos , Humanos , Antipsicóticos/uso terapéutico , Enfermedad de Alzheimer/tratamiento farmacológico , Trastornos Psicóticos/tratamiento farmacológico , Trastornos Psicóticos/etiología , Antidepresivos/uso terapéuticoRESUMEN
BACKGROUND: Antibiotic resistance has become a global concern. Vancomycin is known as the last line of antibiotics, but its treatment index is narrow. Therefore, clinical dosing decisions must be made with the utmost care; such decisions are said to be "suitable" only when both "efficacy" and "safety" are considered. This study presents a model, namely the "ensemble strategy model," to predict the suitability of vancomycin regimens. The experimental data consisted of 2141 "suitable" and "unsuitable" patients tagged with a vancomycin regimen, including six diagnostic input attributes (sex, age, weight, serum creatinine, dosing interval, and total daily dose), and the dataset was normalized into a training dataset, a validation dataset, and a test dataset. AdaBoost.M1, Bagging, fastAdaboost, Neyman-Pearson, and Stacking were used for model training. The "ensemble strategy concept" was then used to arrive at the final decision by voting to build a model for predicting the suitability of vancomycin treatment regimens. RESULTS: The results of the tenfold cross-validation showed that the average accuracy of the proposed "ensemble strategy model" was 86.51% with a standard deviation of 0.006, and it was robust. In addition, the experimental results of the test dataset revealed that the accuracy, sensitivity, and specificity of the proposed method were 87.54%, 89.25%, and 85.19%, respectively. The accuracy of the five algorithms ranged from 81 to 86%, the sensitivity from 81 to 92%, and the specificity from 77 to 88%. Thus, the experimental results suggest that the model proposed in this study has high accuracy, high sensitivity, and high specificity. CONCLUSIONS: The "ensemble strategy model" can be used as a reference for the determination of vancomycin doses in clinical treatment.
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Inteligencia Artificial , Vancomicina , Humanos , Antibacterianos , Algoritmos , CreatininaRESUMEN
Background: Psychotic symptoms are reported as one of the most common complications of Alzheimer's disease (AD), affecting approximately half of AD patients, in whom they are associated with more rapid deterioration and increased mortality. Empiric treatments, namely first and second-generation antipsychotics, confer modest efficacy in AD patients with psychosis (AD+P) and themselves increase mortality. A recent genome-wide meta-analysis and early clinical trials suggest the use and beneficial effects of antidepressants among AD+P patients. This motivates our rationale for exploring their potential as a novel combination therapy option amongst these patients. Methods: We included University of Pittsburgh Medical Center (UPMC) electronic medical records (EMRs) of 10,260 AD patients from January 2004 and October 2019 in our study. Survival analysis was performed to assess the effects of the combination of antipsychotics and antidepressants on the mortality of these patients. To provide more valuable insights on the hidden mechanisms of the combinatorial therapy, a protein-protein interaction (PPI) network representing AD+P was built, and network analysis methods were used to quantify the efficacy of these drugs on AD+P. An indicator score combining the measurements on the separation between drugs and the proximity between the drugs and AD+P was used to measure the effect of an antipsychotic-antidepressant drug pair against AD+P. Results: Our survival analyses replicated that antipsychotic usage is strongly associated with increased mortality in AD patients while the co-administration of antidepressants with antipsychotics showed a significant beneficial effect in reducing mortality. Our network analysis showed that the targets of antipsychotics and antidepressants are well-separated, and antipsychotics and antidepressants have similar proximity scores to AD+P. Eight drug pairs, including some popular recommendations like Aripiprazole/Sertraline and other pairs not reported previously like Iloperidone/Maprotiline showed higher than average indicator scores which suggest their potential in treating AD+P via strong synergetic effects as seen in our study. Conclusion: Our proposed combinations of antipsychotics and antidepressants therapy showed a strong superiority over current antipsychotics treatment for AD+P. The observed beneficial effects can be further strengthened by optimizing drug-pair selection based on our systems pharmacology analysis.
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Aim: Since tissue inhibitors of matrix metalloproteinase 3 (TIMP-3) was reported to be a potential risk factor of atherosclerosis, aneurysm, hypertension, and post-ischaemic neuronal injury, it may also be a candidate risk factor of stress. Therefore, this study was designed to explore the causal role of TIMP-3 in the risk of ischaemic stroke (IS) and intracerebral haemorrhage (ICH), which are the two main causes of stress via this Mendelian Randomisation (MR) study. Methods: The summarised data of TIMP-3 level in circulation was acquired from the Cooperative Health Research in the Region of Augsburg public database and the outcome of IS and ICH was obtained from genome-wide association studies conducted by MEGASTROKE and the International Stroke Genetics Consortium, respectively. Five statistical methods including inverse-variance weighting, weighted-median analysis, MR-Egger regression, MR Pleiotropy RESidual Sum and Outlier test, and MR-Robust Adjusted Profile Score were applied to evaluate the causal role of TIMP-3 in the occurrence of IS and ICH. Inverse-variance weighting was applied for assessing causality. Furthermore, heterogeneity and pleiotropic tests were utilised to confirm the reliability of this study. Results: We found that TIMP-3 could be a positively causal relationship with the incidence of IS (OR = 1.026, 95% CI: 1.007-1.046, p = 0.0067), especially for the occurrence of small vessel stroke (SVS; OR = 1.045, 95% CI: 1.016-1.076, p = 0.0024). However, the causal effects of TIMP-3 on another IS subtype cardioembolic stroke (CES; OR = 1.049, 95% CI: 1.006-1.094, p = 0.024), large artery stroke (LAS; OR = 1.0027, 95% CI: 0.9755-1.0306, p = 0.849) and ICH (OR = 0.9900, 95% CI: 0.9403-1.0423, p = 0.701), as well as ICH subtypes were not observed after Bonferroni corrections (p = 0.00714). Conclusion: Our results revealed that high levels of circulating TIMP-3 causally increased the risk of developing IS and SVS, but not CES, LAS, ICH, and all ICH subtypes. Further investigation is required to elucidate the underlying mechanism.
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One critical problem inhibiting the application of MoS2 field-effect transistors (FETs) is the hysteresis in their transfer characteristics, which is typically associated with charge trapping (CT) and charge detrapping (CDT) induced by atomic defects at the MoS2-dielectric interface. Here, we propose a novel atomistic framework to simulate electronic processes across the MoS2-SiO2 interface, demonstrating the distinct CT/CDT behavior of different types of atomic defects and further revealing the defect type(s) that most likely cause hysteresis. An anharmonic approximation of the classical Marcus theory is developed and combined with state-of-the-art density functional theory to calculate the gate bias-dependent CT/CDT rates. All the key electronic quantities are calculated with Heyd-Scuseria-Ernzerhof hybrid functionals. The results show that single Si-dangling bond defects are active electron trapping centers. Single O-dangling bond defects are active hole trapping centers, which are more likely to be responsible for the hysteresis phenomenon due to their significant CT rate and apparent threshold voltage shift. In contrast, double Si-dangling bond defects are not active trap centers. These findings provide fundamental physical insights for understanding the hysteresis behavior of MoS2 FETs and provide vital support for understanding and solving the reliability of nanoscale devices.
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Clustering cells and depicting the lineage relationship among cell subpopulations are fundamental tasks in single-cell omics studies. However, existing analytical methods face challenges in stratifying cells, tracking cellular trajectories, and identifying critical points of cell transitions. To overcome these, we proposed a novel Markov hierarchical clustering algorithm (MarkovHC), a topological clustering method that leverages the metastability of exponentially perturbed Markov chains for systematically reconstructing the cellular landscape. Briefly, MarkovHC starts with local connectivity and density derived from the input and outputs a hierarchical structure for the data. We firstly benchmarked MarkovHC on five simulated datasets and ten public single-cell datasets with known labels. Then, we used MarkovHC to investigate the multi-level architectures and transition processes during human embryo preimplantation development and gastric cancer procession. MarkovHC found heterogeneous cell states and sub-cell types in lineage-specific progenitor cells and revealed the most possible transition paths and critical points in the cellular processes. These results demonstrated MarkovHC's effectiveness in facilitating the stratification of cells, identification of cell populations, and characterization of cellular trajectories and critical points.
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Biología Computacional/métodos , Análisis de la Célula Individual/métodos , Blastocisto/citología , Blastocisto/metabolismo , Carcinogénesis/genética , Carcinogénesis/metabolismo , Linaje de la Célula , Humanos , Cadenas de MarkovRESUMEN
Background: Previous studies on the management of chronic subdural hematoma (cSDH) mainly focused on the risk of postoperative recurrence and measures to prevent it. In this study, we propose the use of a non-invasive postoperative treatment method, the modified Valsalva maneuver (MVM), as a means of reducing the recurrence of cSDH. This study aims to clarify the effects of MVM on functional outcomes and recurrence rates. Methods: A prospective study was conducted at the Department of Neurosurgery, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from November 2016 to December 2020. The study included 285 adult patients who underwent burr-hole drainage for the treatment of cSDH and received subdural drains. These patients were divided into two groups: the MVM group (n = 117) and the control group (n = 98). In the MVM group, patients received treatment with a customized MVM device for at least 10 times per hour, 12 h per day. The study's primary endpoint was the recurrence rate of SDH, while functional outcomes and morbidity 3 months after surgery were the secondary outcomes. Results: In the current study, 9 out of 117 patients (7.7%) in the MVM group experienced a recurrence of SDH, while 19 out of 98 patients (19.4%, p < 0.05) in the HC group experienced a recurrence of SDH. Additionally, the infection rate of diseases such as pneumonia (1.7%) was significantly lower in the MVM group compared to the HC group (9.2%, p < 0.001, odds ratio (OR = 0.1). After 3 months of the surgery, 109 out of 117 patients (93.2%) in the MVM group achieved a favorable prognosis, compared to 80 out of 98 patients (81.6%) in the HC group (p = 0.008, with an OR of 2.9). Additionally, infection rate (with an OR of 0.2) and age (with an OR of 0.9) are independent predictors of a favorable prognosis at the follow-up stage. Conclusions: The use of MVM in the postoperative management of cSDHs has been shown to be safe and effective, resulting in reduced rates of cSDH recurrence and infection following burr-hole drainage. These findings suggest that MVM treatment may lead to a more favorable prognosis at the follow-up stage.
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BACKGROUND: Although various implants exist for the fixation of isolated greater tuberosity fractures, few implants are specifically designed for such fractures. The purpose of this study was to investigate the clinical and radiologic outcomes of open reduction-internal fixation with a low-profile anatomic locking plate for comminuted greater tuberosity fractures of the proximal humerus. METHODS: From November 2012 to February 2018, 24 patients with displaced and comminuted isolated greater tuberosity fractures were treated with the new low-profile anatomic locking plate. To determine clinical outcomes, we evaluated active range of motion; the visual analog scale pain score; the Constant-Murley score; the Disabilities of the Arm, Shoulder and Hand score; radiographs; and complications. RESULTS: In all cases, a mean follow-up period of 29.3 months (range, 18-48 months) was completed. All patients achieved bone union with a mean healing time of 11.3 weeks (range, 8-16 weeks). The mean Constant-Murley score was 91.1 points (range, 69-100 points), with a rate of good to excellent results of 95.8%. The average Disabilities of the Arm, Shoulder and Hand score was 9.9 points (range, 2-25 points), and the mean visual analog scale pain score was 1.1 points (range, 0-4 points). Mean active forward flexion, abduction, external rotation, and internal rotation (level) were 157°, 152°, and 40°, and T11, respectively. Postoperatively, 1 patient had persistent shoulder stiffness, and 1 patient had recurrence of shoulder dislocation because of a falling injury during badminton. No serious complications such as subacromial impingement, malunion, nonunion, loss of reduction, or implant failure occurred. CONCLUSIONS: The new low-profile anatomic locking plate was useful for the treatment of comminuted isolated greater tuberosity fractures as it provided reliable stability and satisfactory radiographic and functional results. The described technique is a simple and effective method and provides a new reliable option for the treatment of isolated greater tuberosity fractures.
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Fracturas Conminutas , Fracturas del Hombro , Placas Óseas , Fijación Interna de Fracturas , Curación de Fractura , Fracturas Conminutas/diagnóstico por imagen , Fracturas Conminutas/cirugía , Humanos , Húmero , Rango del Movimiento Articular , Estudios Retrospectivos , Hombro , Fracturas del Hombro/diagnóstico por imagen , Fracturas del Hombro/cirugía , Resultado del TratamientoRESUMEN
BACKGROUND: Over the past decade, the endoscopic transnasal transsphenoidal approach for pituitary adenomas has been widely adopted among neurosurgeons. However, olfactory disturbances have been observed after this procedure, and few studies on long-term (>6 mo) olfactory disturbance after endoscopic transnasal transsphenoidal pituitary adenoma surgery have been conducted. Although we perform minimally invasive endoscopic surgery, some patients continue to experience hyposmia, with some even experience long-term hyposmia. This impairment results in a considerable loss in quality of life. We present a series of patients who underwent minimally invasive single-nostril TSS for pituitary adenoma, including evaluation of their olfactory function. We further investigated the related risk factors for long-term olfactory dysfunction. METHODS: One hundred sixty-one consecutive patients who met the study criteria underwent the single-nostril endoscopic transsphenoidal approach by the senior author. The Smell Diskettes Olfaction Test was used to evaluate olfactory function. RESULTS: Postoperative olfactory disturbance in patients treated with endoscopic transnasal TSS is frequent. Of the study population, 67.1% of the patients were hyposmic or anosmic and 14.9% had long-term olfactory dysfunction. We also performed multivariate logistic regression analysis to compare the characteristics of patients with long-term olfactory dysfunction. Nasal symptoms (odds ratio [OR], 6.77) and smoking (OR, 14.77) were associated with long-term olfactory dysfunction after transnasal TSS. CONCLUSIONS: Significant disturbances in olfactory performance occur after single-nostril transnasal TSS for pituitary adenoma. Furthermore, preoperative nasal disease and smoking appear to be risk factors for long-term olfactory dysfunction. Physicians should address clinical findings related to olfactory function and provide appropriate care.
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Adenoma/cirugía , Endoscopía/efectos adversos , Trastornos del Olfato/etiología , Neoplasias Hipofisarias/cirugía , Adulto , Anciano , Femenino , Humanos , Masculino , Persona de Mediana Edad , Periodo Posoperatorio , Calidad de Vida , Olfato , Resultado del TratamientoRESUMEN
The spin torque nano-oscillator (STNO) is a very promising candidate for next generation telecommunication systems due to its small size ~100 nm and high output frequency range. However, it still suffers low output power, usually smaller than µW, and very high phase noise. Also, the modulation method for the STNO should be further developed. The frequency modulation and amplitude modulation method for STNO can be easily applied because of the non-linear nature of STNO, yet it is very rare to see the proposal of a phase modulation method. In this work, we propose a robust phase shift keying modulation method for STNO. Its feasibility is demonstrated with both theoretical and numerical analysis, and its robustness is investigated under room temperature thermal noise. It is shown that our proposed phase modulation method can tune the phase arbitrarily, while the modulation speed can be as fast as 10 ns at room temperature. Comparing with the other phase modulation method, our approach has advantages of larger phase tuning range and stronger robustness against thermal noise.
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BACKGROUND: Technical aspects of the correct placement of medial support locking screws in the locking plate for proximal humerus fractures remain incompletely understood. This study was to evaluate the clinical relationship between the number of medial support screws and the maintenance of fracture reduction after locked plating of proximal humerus fractures. METHODS: We retrospectively evaluated 181 patients who had been surgically treated for proximal humeral fractures (PHFs) with a locking plate between September 2007 and June 2013. All cases were then subdivided into one of four groups as follows: 75 patients in the medial cortical support (MCS) group, 26 patients in the medial multiscrew support (MMSS) group, 29 patients in the medial single screw support (MSSS) group, and 51 patients in the no medial support (NMS) group. Clinical and radiographic evaluations included the Constant-Murley score (CM), visual analogue scale (VAS), complications, and revision surgeries. The neck-shaft angle (NSA) was measured in a true anteroposterior radiograph immediately postoperation and at final follow-up. One-way analysis of variance or Kruskal-Wallis test was used for statistical analysis of measurement data, and Chi-square test or Fisher's exact test was used for categorical data. RESULTS: The mean postoperative NSAs were 133.46° ± 6.01°, 132.39° ± 7.77°, 135.17° ± 10.15°, and 132.41° ± 7.16° in the MCS, MMSS, MSSS, and NMS groups, respectively, and no significant differences were found (F = 1.02, P = 0.387). In the final follow-up, the NSAs were 132.79° ± 6.02°, 130.19° ± 9.25°, 131.28° ± 12.85°, and 127.35° ± 8.50° in the MCS, MMSS, MSSS, and NMS groups, respectively (F = 4.40, P = 0.008). There were marked differences in the NSA at the final follow-up between the MCS and NMS groups (P = 0.004). The median (interquartile range [IQR]) NSA losses were 0.0° (0.0-1.0)°, 1.3° (0.0-3.1)°, 1.5° (1.0-5.2)°, and 4.0° (1.2-7.1)° in the MCS, MMSS, MSSS, and NMS groups, respectively (H = 60.66, P < 0.001). There were marked differences in NSA loss between the MCS and the other three groups (MCS vs. MMSS, Z = 3.16, P = 0.002; MCS vs. MSSS, Z = 4.78, P < 0.001; and MCS vs. NMS, Z = 7.34, P < 0.001). There was also significantly less NSA loss observed in the MMSS group compared to the NMS group (Z = -3.16, P = 0.002). However, there were no significant differences between the MMSS and MSSS groups (Z = -1.65, P = 0.225) or the MSSS and NMS groups (Z = -1.21, P = 0.099). The average CM scores were 81.35 ± 9.79, 78.04 ± 8.97, 72.76 ± 10.98, and 67.33 ± 12.31 points in the MCS, MMSS, MSSS, and NMS groups, respectively (F = 18.68, P < 0.001). The rates of excellent and good CM scores were 86.67%, 80.77%, 65.52%, and 43.14% in the MCS, MMSS, MSSS, and NMS groups, respectively (χ2 = 29.25, P < 0.001). The median (IQR) VAS scores were 1 (0-2), 1 (0-2), 2 (1-3), and 3 (1-5) points in the MCS, MMSS, MSSS, and NMS groups, respectively (H = 27.80, P < 0.001). Functional recovery was markedly better and VAS values were lower in the MCS and MMSS groups (for CM scores: MCS vs. MSSS, P < 0.001; MCS vs. NMS, P < 0.001; MMSS vs. MSSS, P = 0.031; and MMSS vs. NMS, P < 0.001 and for VAS values: MCS vs. MSSS, Z = 3.31, P = 0.001; MCS vs. NMS, Z = 4.64, P < 0.001; MMSS vs. MSSS, Z = -2.09, P = 0.037; and MMSS vs. NMS, Z = -3.16, P = 0.003). CONCLUSIONS: Medial support screws might help enhance mechanical stability and maintain fracture reduction when used to treat PHFs with medial metaphyseal comminution or malreduction.
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Placas Óseas , Tornillos Óseos , Fijación Interna de Fracturas/métodos , Fracturas del Hombro/cirugía , Anciano , Femenino , Humanos , Húmero , Masculino , Persona de Mediana Edad , Estudios Retrospectivos , Resultado del TratamientoRESUMEN
Artificial synaptic devices implemented by emerging post-CMOS non-volatile memory technologies such as Resistive RAM (RRAM) have made great progress recently. However, it is still a big challenge to fabricate stable and controllable multilevel RRAM. Benefitting from the control of electron spin instead of electron charge, spintronic devices, e.g., magnetic tunnel junction (MTJ) as a binary device, have been explored for neuromorphic computing with low power dissipation. In this paper, a compound spintronic device consisting of multiple vertically stacked MTJs is proposed to jointly behave as a synaptic device, termed as compound spintronic synapse (CSS). Based on our theoretical and experimental work, it has been demonstrated that the proposed compound spintronic device can achieve designable and stable multiple resistance states by interfacial and materials engineering of its components. Additionally, a compound spintronic neuron (CSN) circuit based on the proposed compound spintronic device is presented, enabling a multi-step transfer function. Then, an All Spin Artificial Neural Network (ASANN) is constructed with the CSS and CSN circuit. By conducting system-level simulations on the MNIST database for handwritten digital recognition, the performance of such ASANN has been investigated. Moreover, the impact of the resolution of both the CSS and CSN and device variation on the system performance are discussed in this work.
Asunto(s)
Redes Neurales de la Computación , Magnetismo , Memoria , Neuronas/química , Semiconductores , Sinapsis/químicaRESUMEN
Spin-transfer-torque magnetic random access memory (STT-MRAM) attracts extensive attentions due to its non-volatility, high density and low power consumption. The core device in STT-MRAM is CoFeB/MgO-based magnetic tunnel junction (MTJ), which possesses a high tunnel magnetoresistance ratio as well as a large value of perpendicular magnetic anisotropy (PMA). It has been experimentally proven that a capping layer coating on CoFeB layer is essential to obtain a strong PMA. However, the physical mechanism of such effect remains unclear. In this paper, we investigate the origin of the PMA in MgO/CoFe/metallic capping layer structures by using a first-principles computation scheme. The trend of PMA variation with different capping materials agrees well with experimental results. We find that interfacial PMA in the three-layer structures comes from both the MgO/CoFe and CoFe/capping layer interfaces, which can be analyzed separately. Furthermore, the PMAs in the CoFe/capping layer interfaces are analyzed through resolving the magnetic anisotropy energy by layer and orbital. The variation of PMA with different capping materials is attributed to the different hybridizations of both d and p orbitals via spin-orbit coupling. This work can significantly benefit the research and development of nanoscale STT-MRAM.