Disorder-tuned conductivity in amorphous monolayer carbon.

Correlating atomic configurations-specifically, degree of disorder (DOD)-of an amorphous solid with properties is a long-standing riddle in materials science and condensed matter physics, owing to difficulties in determining precise atomic positions in 3D structures1-5. To this end, 2D systems provide insight to the puzzle by allowing straightforward imaging of all atoms6,7. Direct imaging of amorphous monolayer carbon (AMC) grown by laser-assisted depositions has resolved atomic configurations, supporting the modern crystallite view of vitreous solids over random network theory8. Nevertheless, a causal link between atomic-scale structures and macroscopic properties remains elusive. Here we report facile tuning of DOD and electrical conductivity in AMC films by varying growth temperatures. Specifically, the pyrolysis threshold temperature is the key to growing variable-range-hopping conductive AMC with medium-range order (MRO), whereas increasing the temperature by 25 °C results in AMC losing MRO and becoming electrically insulating, with an increase in sheet resistance of 109 times. Beyond visualizing highly distorted nanocrystallites embedded in a continuous random network, atomic-resolution electron microscopy shows the absence/presence of MRO and temperature-dependent densities of nanocrystallites, two order parameters proposed to fully describe DOD. Numerical calculations establish the conductivity diagram as a function of these two parameters, directly linking microstructures to electrical properties. Our work represents an important step towards understanding the structure-property relationship of amorphous materials at the fundamental level and paves the way to electronic devices using 2D amorphous materials.

Manipulating 2D Materials through Strain Engineering.

This review explores the growing interest in 2D layered materials, such as graphene, h-BN, transition metal dichalcogenides (TMDs), and black phosphorus (BP), with a specific focus on recent advances in strain engineering. Both experimental and theoretical results are delved into, highlighting the potential of strain to modulate physical properties, thereby enhancing device performance. Various strain engineering methods are summarized, and the impact of strain on the electrical, optical, magnetic, thermal, and valleytronic properties of 2D materials is thoroughly examined. Finally, the review concludes by addressing potential applications and challenges in utilizing strain engineering for functional devices, offering valuable insights for further research and applications in optoelectronics, thermionics, and spintronics.

Associations of rumination with suicidal ideation and suicide attempts amongst individuals with major depressive disorder: A 12-month longitudinal study in China.

BACKGROUND: This study aimed to explore the longitudinal associations of rumination with suicidal ideation and suicide attempts in individuals with major depressive disorder (MDD). METHODS: Participants were derived from the Depression Cohort in China study (DCC). Those who completed at least one follow-up visit during the 12 months were included in the analysis. Dimensions of rumination including brooding and reflection were each measured using five items of the Ruminative Responses Scale. Suicidal ideation was assessed using the Beck Scale for Suicide Ideation. Suicide attempts were also assessed and all were analyzed with generalized estimating equations. RESULTS: Our final sample included 532 participants aged 18 to 59 years (mean [SD], 26.91 [6.94] years) consisting of 148 (27.8%) males and 384 (72.2%) females. After adjusting for temporal trend and potential confounders, individuals with higher levels of reflection were more likely to report suicidal ideation (AOR =1.11, 95% CI:1.01-1.22). However, no statistically significant association was found between brooding and suicidal ideation (AOR =1.06, 95% CI:0.96-1.17). Conversely, individuals with higher levels of brooding were more likely to report suicide attempts (AOR =1.13, 95% CI:1.02-1.24), while no statistically significant association was observed between reflection and suicide attempts (AOR =0.91, 95% CI:0.82-1.01). CONCLUSION: Rumination reflects a disturbance in cognitive emotional processing and manifests in different dimensions. Our findings suggest that high levels of reflection and brooding may be associated with a higher likelihood of having suicidal ideation and suicide attempts, respectively. However, it should be interpreted with caution, given that effect sizes are small.

Developing hydrogels for gene therapy and tissue engineering.

Hydrogels are a class of highly absorbent and easily modified polymer materials suitable for use as slow-release carriers for drugs. Gene therapy is highly specific and can overcome the limitations of traditional tissue engineering techniques and has significant advantages in tissue repair. However, therapeutic genes are often affected by cellular barriers and enzyme sensitivity, and carrier loading of therapeutic genes is essential. Therapeutic gene hydrogels can well overcome these difficulties. Moreover, gene-therapeutic hydrogels have made considerable progress. This review summarizes the recent research on carrier gene hydrogels for the treatment of tissue damage through a summary of the most current research frontiers. We initially introduce the classification of hydrogels and their cross-linking methods, followed by a detailed overview of the types and modifications of therapeutic genes, a detailed discussion on the loading of therapeutic genes in hydrogels and their characterization features, a summary of the design of hydrogels for therapeutic gene release, and an overview of their applications in tissue engineering. Finally, we provide comments and look forward to the shortcomings and future directions of hydrogels for gene therapy. We hope that this article will provide researchers in related fields with more comprehensive and systematic strategies for tissue engineering repair and further promote the development of the field of hydrogels for gene therapy.

Prevalence of Parkinson's disease among adults aged 45 years and older in China: a cross-sectional study based on the China health and retirement longitudinal study.

BACKGROUND: In recent decades, China has experienced a rapid increase in the number of elderly individuals and life expectancy, as well as industrialization, which is associated with an increased prevalence of Parkinson's disease (PD). However, inconsistent results have recently been reported. Therefore, this study aimed to investigate the prevalence and distribution characteristics of PD among individuals aged 45 years and older. METHODS: Using data from the China Health and Retirement Longitudinal Study (CHARLS), we attempted to estimate the prevalence of PD and its distribution characteristics among 19,034 individuals aged 45 years and older residing in 446 communities/villages within 27 provinces/autonomous regions/municipalities in mainland China. Cases were established based on a doctor's previous diagnosis. Crude and age-adjusted prevalence rates were calculated and stratified by age, sex, area of residence, education level, marital status, and geographic region. Logistic regression models were used to identify risk factors associated with PD. RESULTS: We identified 178 patients with PD among 19,034 residents aged 45 years and older. The crude prevalence was 0.94%, and the age-adjusted prevalence was 0.82% for individuals aged 45 years and older. The prevalence of PD increased with age (P < 0.001). No significant differences were found in terms of sex, area of residence, or education level. Stratified by geographic region, the prevalence of PD was greater in North and Northwest China and lower in southern China (p < 0.001). Multiple regression analyses showed that age was a significant risk factor for PD. CONCLUSION: The prevalence of PD increased with age in the Chinese population.

Portable electrochemical sensing platform based on amidated GO-MOF and PEDOT:PSS for high-efficient detection of ponceau 4R.

A promising electrochemical sensing platform for the detection of ponceau 4R in food has been fabricated based on the carboxylated graphene oxide (GO-COOH), metal-organic framework (MOF) UIO-66-NH2, and poly (3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS). To this end GO-COOH was covalently coupled with UIO-66-NH2 through amide reaction, endowing the material (GO-CONH-UIO-66) unique hierarchical pores and high chemical stability and as a result improving the conductivity of MOF and the dispersion of GO. After the addition of PEDOT:PSS into GO-CONH-UIO-66, the continuity and conductivity of the composite (PEDOT:PSS/GO-CONH-UIO-66) have been further enhanced, due to the high conductivity, favorable film-forming, and hydrophilic properties of PEDOT:PSS. Systematic electrochemical experiments confirm that the PEDOT:PSS/GO-CONH-UIO-66/GCE shows satisfactory electrochemical sensing properties towards the detection of ponceau 4R, with a wide linear detection range of 0.01-30 µM, a low limit of detection of 3.33 nM, and a high sensitivity of 0.606 µA µM-1 cm-2. The PEDOT:PSS/GO-CONH-UIO-66 sensing platform was successfully used to detect ponceau 4R in beverage, and the detection results were compared with  high-performance liquid chromatography. As a result, the PEDOT:PSS/GO-CONH-UIO-66 composite shows a promising application prospect for rapid detection of ponceau 4R in food and will play significant role in food safety detection and supervision.

2D van der Waals Vertical Heterojunction Transistors for Ternary Neural Networks.

Compared with binary systems, ternary computing systems can utilize fewer devices to realize the same information density. However, most ternary computing systems based on binary CMOS circuits require additional devices to bridge binary processing and ternary computing. Exploring new device architectures for direct ternary processing and computing becomes the key to promoting ternary computing systems. Here, we demonstrated a 2D van der Waals vertical heterojunction transistor (V-HTR) with three flat conductance states, which can be the basic cell in ternary circuits to perform ternary processing and computing, without additional devices. A ternary neural network (TNN) and a ternary inverter were demonstrated based on the V-HTRs. The TNN can eliminate fuzzy data and output only clear data by building a ternary quantization function. By demonstrating both ternary logic and a TNN on the same device architecture, the 2D V-HTR shows potential as a basic hardware unit for future ternary computing systems.

PIDNET: Polar Transformation Based Implicit Disentanglement Network for Truncation Artifacts.

The interior problem, a persistent ill-posed challenge in CT imaging, gives rise to truncation artifacts capable of distorting CT values, thereby significantly impacting clinical diagnoses. Traditional methods have long struggled to effectively solve this issue until the advent of supervised models built on deep neural networks. However, supervised models are constrained by the need for paired data, limiting their practical application. Therefore, we propose a simple and efficient unsupervised method based on the Cycle-GAN framework. Introducing an implicit disentanglement strategy, we aim to separate truncation artifacts from content information. The separated artifact features serve as complementary constraints and the source of generating simulated paired data to enhance the training of the sub-network dedicated to removing truncation artifacts. Additionally, we incorporate polar transformation and an innovative constraint tailored specifically for truncation artifact features, further contributing to the effectiveness of our approach. Experiments conducted on multiple datasets demonstrate that our unsupervised network outperforms the traditional Cycle-GAN model significantly. When compared to state-of-the-art supervised models trained on paired datasets, our model achieves comparable visual results and closely aligns with quantitative evaluation metrics.

[Research progress of traditional Chinese medicine intervention for ulcerative colitis based on Notch1 signaling pathway].

Ulcerative colitis(UC) is one of the common gastrointestinal diseases worldwide. In recent years, the incidence of UC has been continuously increasing, seriously threatening the health of people globally. It thus has become an urgent problem that needs to be addressed. There is research evidence that intestinal mucosal barrier dysfunction, including changes in intestinal stem cell secretion lineage, mucosal layer damage, disruption of cell junctions, overactive immune function, and imbalanced gut microbiota, is an important pathogenic factor and molecular basis of UC. The Notch signaling pathway is a highly conserved signaling pathway in eukaryotes during evolution, which transmits signals through cell connections between adjacent cells, affecting a series of processes such as cell proliferation, differentiation, development, migration, and apoptosis. Therefore, the Notch signaling pathway can regulate intestinal stem cells, CD4~+T cells, innate lymphoid cells(ILCs), macrophages(MØ), and intestinal microbiota and thus affect the chemical, physical, immune, and biological mucosal barriers of the intestinal mucosa. Its function is extensive and unique, different from those signaling pathways that mainly focus on anti-inflammatory and antioxidant stress. It can explain the therapeutic effects of traditional Chinese medicine from different perspectives. This article reviewed the role of the Notch1 signaling pathway in the pathogenesis of UC and the relevant literature on the targeted prevention and treatment of UC with traditional Chinese medicine, so as to provide new targets and theoretical support for further research on the effective prevention and treatment of UC.

Robust Behavior of Charge Density Wave Quantum Motif Star-of-David in 2D NbSe2 Nanocrystals.

Charge density wave (CDW) is a typical collective phenomenon, and the phase change is generally accompanied by electronic transition with potential device applications. For the continuous miniaturization of devices, it is important to investigate the size effect down to the nanoscale. In this work, single-layer (SL) 1T-NbSe2 islands provide an ideal research platform to investigate the size effect on CDW arrangement and electronic states. The CDW motifs (Star-of-David [SOD]) at the island border are along the edge, and those at the interior tend to arrange in a triangular lattice for islands as small as 5 nm. Interestingly, in some small islands, the SOD clusters rearrange into a square-like lattice, and each SOD cluster remains robust as a quantum motif, both in the sense of geometry and electronic structures. Moreover, the electronic structure at the center of the small islands is downwards shifted compared to the big islands, explained by the spatial extension of the band bending originating from the edge of the islands. These findings reveal the robust behavior of CDW motifs down to the nanoscale and provide new insights into the size-limiting effect on 2D2D CDW ordering and electronic states down to a few nanometer extremes.

Initial experience of visualized biliary cannulation during ERCP.

BACKGROUND : Selective biliary cannulation is the most challenging step in endoscopic retrograde cholangiopancreatography (ERCP) because only indirect radiographic images can be obtained. Therefore, we developed a novel endoscopic retrograde direct cholangioscopy (ERDC) technology to facilitate visible biliary cannulation. METHODS : In this case series, we used ERDC to treat 21 patients with common bile duct stones who were enrolled consecutively between July 2022 and December 2022. The procedure details and complications were recorded, and all patients were followed up for 3 months after the procedure. The learning curve effect was analyzed by comparing the early and later cases. RESULTS : Biliary cannulation was successful in all patients, and the stones were removed completely. The median (interquartile range [IQR]) time for cholangioscopy-guided biliary cannulation was 240.0 (10.0-430.0) seconds, and the median (IQR) number of cannulation procedures was 2 (1-5). Despite there being one episode of post-ERCP pancreatitis, one of cholangitis, and three patients developing asymptomatic hyperamylasemia, all of the patients recovered after symptomatic treatment, being discharged and with no serious adverse events occurring during the 3-month follow-up period. Compared with the early cases, the number of intubations and the use of guidewire guidance decreased in later cases. CONCLUSION : Our research confirms that ERDC is a feasible technology for biliary cannulation under direct vision.

hENT1's role in adjuvant intra-arterial gemcitabine-based chemotherapy for resectable pancreatic cancer patients.

BACKGROUND: We aimed to verify the role of hENT1 as a prognostic predictor for patients with resectable pancreatic ductal adenocarcinoma (PDAC) who underwent radical resection followed by intra-arterial infusion of gemcitabine-based regimen. METHODS: We collected surgical samples from 102 patients with resectable PDAC who received radical resection followed by intra-arterial infusion of gemcitabine-based regimen. The hENT1 expression with the help of immunohistochemistry was conducted using formalin-fixed and paraffin embedded tissues. The Kaplan-Meier analyses and Cox regression were used to evaluate the mortality hazard associated with the discrepancy between strong and weak of hENT1 expression. Patients' clinical and pathological characteristics were compared between the two groups, then the role of hENT1 as a prognostic predictor was further explored. RESULTS: A total of 102 patients were included to assess the hENT1 expression. 50 patients were classified into high hENT1 expression group, the other 52 patients were attributed into low hENT1 expression group. High hENT1 expression was related to a significantly improved overall survival (OS) (p = 0.014) and disease-free survival (DFS) (p = 0.004). Both univariate (p = 0.001) and multivariate analyses (p < 0.001) indicated that high hENT1 expression was related to a decreased mortality. CONCLUSIONS: High expression of hENT1 is positive prognostic factor for adjuvant intra-arterial gemcitabine-based chemotherapy in resectable PDAC.

A clinically feasible circulating tumor cell sorting system for monitoring the progression of advanced hepatocellular carcinoma.

BACKGROUND: Hematogenous metastasis is essential for the progression of advanced hepatocellular carcinoma (HCC) and can occur even after patients receive multidisciplinary therapies, including immunotherapy and hepatectomy; circulating tumor cells (CTCs) are one of the dominant components of the metastatic cascade. However, the CTC capture efficiency for HCC is low due to the low sensitivity of the detection method. In this study, epithelial cell adhesion molecule (EpCAM)/vimentin/Glypican-3 (GPC3) antibody-modified lipid magnetic spheres (LMS) were used to capture tumor cells with epithelial phenotype, mesenchymal phenotype and GPC3 phenotype, respectively, in order to capture more CTCs with a more comprehensive phenotype for monitoring tumor metastasis. RESULTS: The novel CTC detection system of Ep-LMS/Vi-LMS/GPC3-LMS was characterized by low toxicity, strong specificity (96.94%), high sensitivity (98.12%) and high capture efficiency (98.64%) in vitro. A sudden increase in CTC counts accompanied by the occurrence of lung metastasis was found in vivo, which was further validated by a clinical study. During follow-up, the rapid increase in CTCs predicted tumor progression in HCC patients. Additionally, genetic testing results showed common genetic alterations in primary tumors, CTCs and metastatic tissues. The proportion of patients predicted to benefit from immunotherapy with the CTC detection method was higher than that for the tissue detection method (76.47% vs. 41.18%, P = 0.037), guiding the application of clinical individualized therapy. CONCLUSIONS: The Ep-LMS/Vi-LMS/GPC3-LMS sequential CTC capture system is convenient and feasible for the clinical prediction of HCC progression. CTCs captured by this system could be used as a suitable alternative to HCC tissue detection in guiding immunotherapy, supporting the clinical application of CTC liquid biopsy.

Advanced porous organic materials for sample preparation in pharmaceutical analysis.

The development of novel sample preparation media plays a crucial role in pharmaceutical analysis. To facilitate the extraction and enrichment of pharmaceutical molecules in complex samples, various functionalized materials have been developed and prepared as adsorbents. Recently, some functionalized porous organic materials have become adsorbents for pharmaceutical analysis due to their unique properties of adsorption and recognition. These advanced porous organic materials, combined with consequent analytical techniques, have been successfully used for pharmaceutical analysis in complex samples such as environmental and biological samples. This review encapsulates the progress of advanced porous materials for pharmaceutical analysis including pesticides, antibiotics, chiral drugs, and other compounds in the past decade. In addition, we also address the limitations and future trends of these porous organic materials in pharmaceutical analysis.

The role of main pancreatic duct stent in the enucleation of benign/borderline pancreatic head tumors: a cohort study.

PURPOSE: This study aimed to reveal the role of preoperative main pancreatic duct (MPD) stent placement in reducing the intraoperative main pancreatic duct injury rate and the incidence of postoperative pancreatic leakage following pancreatic tumor enucleation. METHODS: A retrospective cohort analysis was performed for all patients with benign/borderline pancreatic head tumors who were treated with enucleation. The patients were divided into two groups (standard vs. stent) depending on whether they underwent main pancreatic duct stent placement prior to surgery. RESULTS: Thirty-three patients were finally included in the analytical cohort. Compared with the standard group, patients in the stent group had a shorter distance between tumors and main pancreatic duct (p=0.01) and presented with larger tumors (p<0.01). The rates of POPF (grade B&C) were 39.1% (9/23) and 20% (2/10) in the standard and stent groups, respectively (p<0.01). Major postoperative complications occurred more frequently in the standard group than in the stent group (14 versus 2; p<0.01). No significant differences in mortality, in-hospital stay or medical cost were observed between the two groups (p>0.05). CONCLUSIONS: MPD stent placement prior to surgery may facilitate pancreatic tumor enucleation, minimize MPD injury and decrease the occurrence of postoperative fistula.

Resource Allocation and Data Offloading Strategy for Edge-Computing-Assisted Intelligent Telemedicine System.

Intelligent telemedicine technology has been widely applied due to the quick development of the Internet of Things (IoT). The edge-computing scheme can be regarded as a feasible solution to reduce energy consumption and enhance the computing capabilities for the Wireless Body Area Network (WBAN). For an edge-computing-assisted intelligent telemedicine system, a two-layer network architecture composed of WBAN and Edge-Computing Network (ECN) was considered in this paper. Moreover, the age of information (AoI) was adopted to describe the time cost for the TDMA transmission mechanism in WBAN. According to the theoretical analysis, the strategy for resource allocation and data offloading in edge-computing-assisted intelligent telemedicine systems can be expressed as a system utility function optimizing problem. To maximize the system utility, an incentive mechanism based on contract theory (CT) was considered to motivate edge servers (ESs) to participate in system cooperation. To minimize the system cost, a cooperative game was developed to address the slot allocation in WBAN, while a bilateral matching game was utilized to optimize the data offloading problem in ECN. Simulation results have verified the effectiveness of the strategy proposed in terms of the system utility.

Joint User Clustering and Graph Coloring Based Pilot Assignment for Cell-Free Massive MIMO Systems.

Pilot contamination due to pilot reuse seriously mitigates the performance of the cell-free massive multiple-input multiple-output (MIMO) systems. In this paper, we propose a joint pilot assignment scheme that employs user clustering and graph coloring (UC-GC) to reduce pilot contamination. The proposed method consists of two steps: firstly, we utilize AP selection to classify all users; secondly, we assign pilots to users with more severe pilot contamination using the graph coloring algorithm and then assign pilots to the remaining users. The numerical simulation results show that the proposed scheme outperforms existing pilot assignment schemes and significantly improves throughout with low complexity.

A Hierarchical Multitask Learning Approach for the Recognition of Activities of Daily Living Using Data from Wearable Sensors.

Machine learning with deep neural networks (DNNs) is widely used for human activity recognition (HAR) to automatically learn features, identify and analyze activities, and to produce a consequential outcome in numerous applications. However, learning robust features requires an enormous number of labeled data. Therefore, implementing a DNN either requires creating a large dataset or needs to use the pre-trained models on different datasets. Multitask learning (MTL) is a machine learning paradigm where a model is trained to perform multiple tasks simultaneously, with the idea that sharing information between tasks can lead to improved performance on each individual task. This paper presents a novel MTL approach that employs combined training for human activities with different temporal scales of atomic and composite activities. Atomic activities are basic, indivisible actions that are readily identifiable and classifiable. Composite activities are complex actions that comprise a sequence or combination of atomic activities. The proposed MTL approach can help in addressing challenges related to recognizing and predicting both atomic and composite activities. It can also help in providing a solution to the data scarcity problem by simultaneously learning multiple related tasks so that knowledge from each task can be reused by the others. The proposed approach offers advantages like improved data efficiency, reduced overfitting due to shared representations, and fast learning through the use of auxiliary information. The proposed approach exploits the similarities and differences between multiple tasks so that these tasks can share the parameter structure, which improves model performance. The paper also figures out which tasks should be learned together and which tasks should be learned separately. If the tasks are properly selected, the shared structure of each task can help it learn more from other tasks.

Sleep Stage Classification in Children Using Self-Attention and Gaussian Noise Data Augmentation.

The analysis of sleep stages for children plays an important role in early diagnosis and treatment. This paper introduces our sleep stage classification method addressing the following two challenges: the first is the data imbalance problem, i.e., the highly skewed class distribution with underrepresented minority classes. For this, a Gaussian Noise Data Augmentation (GNDA) algorithm was applied to polysomnography recordings to seek the balance of data sizes for different sleep stages. The second challenge is the difficulty in identifying a minority class of sleep stages, given their short sleep duration and similarities to other stages in terms of EEG characteristics. To overcome this, we developed a DeConvolution- and Self-Attention-based Model (DCSAM) which can inverse the feature map of a hidden layer to the input space to extract local features and extract the correlations between all possible pairs of features to distinguish sleep stages. The results on our dataset show that DCSAM based on GNDA obtains an accuracy of 90.26% and a macro F1-score of 86.51% which are higher than those of our previous method. We also tested DCSAM on a well-known public dataset-Sleep-EDFX-to prove whether it is applicable to sleep data from adults. It achieves a comparable performance to state-of-the-art methods, especially accuracies of 91.77%, 92.54%, 94.73%, and 95.30% for six-stage, five-stage, four-stage, and three-stage classification, respectively. These results imply that our DCSAM based on GNDA has a great potential to offer performance improvements in various medical domains by considering the data imbalance problems and correlations among features in time series data.

Axial-Bonding-Driven Dimensionality Effect on the Charge-Density Wave in NbSe2.

2H-NbSe2 is a prototypical charge-density-wave (CDW) system, exhibiting such a symmetry-breaking quantum ground state in its bulk and down to a single-atomic-layer limit. However, how this state depends on dimensionality and what governs the dimensionality effect remain controversial. Here, we experimentally demonstrate a robust 3 × 3 CDW phase in both freestanding and substrate-supported bilayer NbSe2, far above the bulk transition temperature. We exclude environmental effects and reveal a strong temperature and thickness dependence of Raman intensity from an axially vibrating A1g phonon mode, involving Se ions. Using first-principles calculations, we show that these result from a delicate but profound competition between the intra- and interlayer bonding formed between Se-pz orbitals. Our results suggest the crucial role of Se out-of-plane displacement in driving the CDW distortion, revealing the Se-dominated dimensionality effect and establishing a new perspective on the chemical bonding and mechanical stability in layered CDW materials.