Thalamocortical dysconnectivity is associated with pain in patients with knee osteoarthritis.

Previous studies have suggested that the morphology and function of the thalamus and cortex are abnormal in patients with knee osteoarthritis (KOA). However, whether the thalamocortical network is differentially affected in this disorder is unknown. In this study, we examined functional and effective connectivity between the thalamus and major divisions of the cortex in 27 healthy controls and 27 KOA patients using functional magnetic resonance imaging. We also explored the topological features of the brain via graph theory analysis. The results suggested that patients with KOA had significantly reduced resting-state functional connectivity (rsFC) of the thalamo-sensorimotor pathway; enhanced rsFC of the thalamo-medial/lateral frontal cortex (mFC/LFC), parietal, temporal and occipital pathways; reduced effective connectivity of the left sensorimotor-to-thalamus pathway; and enhanced effective connectivity of the right thalamus-to-sensorimotor pathway compared with healthy controls. The functional connectivity of the thalamo-sensorimotor and thalamo-mFC pathways was enhanced when patients performed the multisource interference task. Moreover, patients with KOA presented altered nodal properties associated with thalamocortical circuits, including the thalamus, amygdala, and regions in default mode networks, compared with healthy controls. The correlation analysis suggested a significant negative correlation between thalamo-mFC rsFC and pain intensity, between thalamo-sensorimotor task-related connectivity and disease duration/depression scores, and a positive correlation between right frontal nodal properties and pain intensity in KOA patients. Taken together, these findings establish abnormal and differential alterations in the thalamocortical network associated with pain characteristics in KOA patients, which extends our understanding of their role in the pathophysiology of KOA.

Hypothesis paper: GDF15 demonstrated promising potential in Cancer diagnosis and correlated with cardiac biomarkers.

BACKGROUND: Cardiovascular toxicity represents a significant adverse consequence of cancer therapies, yet there remains a paucity of effective biomarkers for its timely monitoring and diagnosis. To give a first evidence able to elucidate the role of Growth Differentiation Factor 15 (GDF15) in the context of cancer diagnosis and its specific association with cardiac indicators in cancer patients, thereby testing its potential in predicting the risk of CTRCD (cancer therapy related cardiac dysfunction). METHODS: Analysis of differentially expressed genes (DEGs), including GDF15, was performed by utilizing data from the public repositories of the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Cardiomyopathy is the most common heart disease and its main clinical manifestations, such as heart failure and arrhythmia, are similar to those of CTRCD. Examination of GDF15 expression was conducted in various normal and cancerous tissues or sera, using available database and serum samples. The study further explored the correlation between GDF15 expression and the combined detection of cardiac troponin-T (c-TnT) and N-terminal prohormone of brain natriuretic peptide (NT-proBNP), assessing the combined diagnostic utility of these markers in predicting risk of CTRCD through longitudinal electrocardiograms (ECG). RESULTS: GDF15 emerged as a significant DEG in both cancer and cardiomyopathy disease models, demonstrating good diagnostic efficacy across multiple cancer types compared to healthy controls. GDF15 levels in cancer patients correlated with the established cardiac biomarkers c-TnT and NT-proBNP. Moreover, higher GDF15 levels correlated with an increased risk of ECG changes in the cancer cohort. CONCLUSION: GDF15 demonstrated promising diagnostic potential in cancer identification; higher GDF15, combined with elevated cardiac markers, may play a role in the monitoring and prediction of CTRCD risk.

Disrupted Resting-State Functional Connectivity and Effective Connectivity of the Nucleus Accumbens in Chronic Low Back Pain: A Cross-Sectional Study.

Purpose: Chronic low back pain (cLBP) is a recurring and intractable disease that is often accompanied by emotional and cognitive disorders such as depression and anxiety. The nucleus accumbens (NAc) plays an important role in mediating emotional and cognitive processes and analgesia. This study investigated the resting-state functional connectivity (rsFC) and effective connectivity (EC) of NAc and its subregions in cLBP. Methods: Thirty-four cLBP patients and 34 age- and sex-matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Seed-based rsFC and Dynamic Causal Modelling (DCM) were used to examine the alteration of the rsFC and EC of the NAc. Results: Our results showed that the cLBP group had increased rsFC of the bilateral NAc-left superior frontal cortex (SFC), orbital frontal cortex (OFC), left angular gyrus, the left NAc-bilateral middle temporal gyrus, as well as decreased rsFC of left NAc-left supramarginal gyrus, right precentral gyrus, left cerebellum, brainstem (medulla oblongata), and right insula pathways compared with the HC; the results of the subregions were largely consistent with the whole NAc. In addition, the rsFC of the left NAc-left SFC was negatively correlated with Hamilton's Depression Scale (HAMD) scores (r = -0.402, p = 0.018), and the rsFC of left NAc-OFC was positively correlated with present pain intensity scores (r = 0.406, p = 0.017) in the cLBP group. DCM showed that the cLBP group showed significantly increased EC from the left cerebellum to the right NAc (p = 0.012) as compared with HC. Conclusion: Overall, our findings demonstrate aberrant rsFC and EC between NAc and regions that are associated with emotional regulation and cognitive processing in individuals with cLBP, underscoring the pivotal roles of emotion and cognition in cLBP.

RLAD: A Reliable Hippo-guided Multi-task Model for Alzheimer's Disease Diagnosis.

Early diagnosis of Alzheimer's disease (AD) is crucial for its prevention, and hippocampal atrophy is a significant lesion for early diagnosis. The current DL-based AD diagnosis methods only focus on either AD classification or hippocampus segmentation independently, neglecting the correlation between the two tasks and lacking pathological interpretability. To address this issue, we propose a Reliable Hippo-guided Learning model for Alzheimer's Disease diagnosis (RLAD), which employs multi-task learning for AD classification as a main task supplemented by hippocampus segmentation. More specifically, our model consists of 1) a hybrid shared features encoder that encodes local and global information in MRI to enhance the model's ability to learn discriminative features; 2) Task Specific Decoders to accomplish AD classification and hippocampus segmentation; and 3) Task Coordination module to correlate the two tasks and guide the classification task to focus on the hippocampus area. Our proposed RLAD model is evaluated on MRI scans of 1631 subjects from three independent datasets, including ADNI-1, ADNI-2, and HarP. Our extensive experimental results demonstrate that the proposed model significantly improves the performance of AD classification and hippocampus segmentation with strong generalization capabilities. Our implementation and model are available at https://github.com/LeoLjl/Explainable-Alzheimer-s-Disease-Diagnosis.

Dual Functional Ultrasensitive Point-of-Care Clinical Diagnosis Using Metal-Organic Frameworks-Based Immunobeads.

Sepsis is an acute systemic infectious syndrome with high fatality. Fast and accurate diagnosis, monitoring, and medication of sepsis are essential. We exploited the fluorescent metal-AIEgen frameworks (MAFs) and demonstrated the dual functions of protein detection and bacteria identification: (i) ultrasensitive point-of-care (POC) detection of sepsis biomarkers (100 times enhanced sensitivity); (ii) rapid POC identification of Gram-negative/positive bacteria (selective aggregation within 20 min). Fluorescent lateral flow immunoassays (LFAs) are convenient and inexpensive for POC tests. MAFs possess a large surface area, excellent photostability, high quantum yield (∼80%), and multiple active sites serving as protein binding domains for ultrasensitive detection of sepsis biomarkers (IL-6/PCT) on LFAs. The limit of detection (LOD) for IL-6/PCT is 0.252/0.333 pg/mL. Rapid appraisal of infectious bacteria is vital to guide the use of medicines. The dual-functional fluorescent MAFs have great potential in POC tests for the clinical diagnosis of bacterial infections.

Predicting isocitrate dehydrogenase genotype, histological phenotype, and Ki-67 expression level in diffuse gliomas with an advanced contrast analysis of magnetic resonance imaging sequences.

Background: The present study aimed to establish a robust predictive model based on a machine learning (ML) algorithm providing preoperative noninvasive diagnosis and to further explore the contribution of each magnetic resonance imaging (MRI) sequence to the classification to help select images for future model development. Methods: This was a retrospective cross-sectional study, and consecutive patients with histologically confirmed diffuse gliomas in our hospital from November 2015 to October 2019 were recruited. The participants were grouped into a training and testing set based on a ratio of 8:2. Five MRI sequences were employed to develop the support vector machine (SVM) classification model. An advanced contrast analysis of single-sequence-based classifiers was performed, according to which different sequence combinations were tested, and the best one was selected to form an ultimate classifier. Patients whose MRIs were acquired with other types of scanners formed an additional, independent validation set. Results: A total of 150 patients with gliomas were used in the present study. Contrast analysis revealed that the contribution of the apparent diffusion coefficient (ADC) was the most significant [accuracies were as follows: histological phenotype, 0.640; isocitrate dehydrogenase (IDH) status, 0.656; and Ki-67 expression, 0.699] and that of T1 weighted imaging was limited (accuracies were as follows: histological phenotype, 0.521; IDH status, 0.492; and Ki-67 expression, 0.556). The ultimate classifiers for IDH status, histological phenotype, and Ki-67 expression achieved promising performances with area under the curve (AUC) values of 0.88, 0.93, and 0.93, respectively. The classifiers for the histological phenotype, IDH status, and Ki-67 expression correctly predicted 3 of 5 subjects, 6 of 7 subjects, and 9 of 13 subjects in the additional validation set, respectively. Conclusions: The present study showed satisfactory performance in predicting the IDH genotype, histological phenotype, and Ki-67 expression level. The contrast analysis revealed the contribution of different MRI sequences and suggested that the combination of all the acquired sequences was not the optimal strategy to build the radiogenomics-based classifier.

Parasellar epidermoid cyst with unique radiological features: A case report and review of the literature.

Intracranial epidermoid cysts (ECs) are encapsulated lesions lined by squamous cell epithelium and the most location is the cerebellopontine angle and appears with cerebrospinal fluid-like irregular mass. Occasionally, ECs present as high-density masses on computed tomography and atypical features in magnetic resonance images in the unusual area, which makes the diagnosis difficult. Here, we report a case of a female subject who complained of episodic left facial convulsions for more than 3 months. Computed tomography plain scan revealed a large hyperdense parasellar mass with atypical magnetic resonance findings. In this report, we analyzed retrospectively the radiological characteristics and histopathology of the parasellar EC, thus increasing awareness about this unusual image features.

Development of Spectral Nano-Flow Cytometry for High-Throughput Multiparameter Analysis of Individual Biological Nanoparticles.

Correlated analysis of multiple biochemical parameters at the single-particle level and in a high-throughput manner is essential for insights into the diversity and functions of biological nanoparticles (BNPs), such as bacteria and subcellular organelles. To meet this challenge, we developed a highly sensitive spectral nano-flow cytometer (S-nFCM) by integrating a spectral recording module to a laboratory-built nFCM that is 4-6 orders of magnitude more sensitive in side scattering detection and 1-2 orders of magnitude more sensitive in fluorescence detection than conventional flow cytometers. An electron-multiplying charge-coupled device (EMCCD) was used to acquire the full fluorescence spectra of single BNPs upon holographic grating dispersion. Up to 10,000 spectra can be collected in 1 min with 2.1 nm resolution. The precision, linearity, and sensitivity were examined. Complete discernment of single influenza viruses against the background signal, discrimination of different strains of marine cyanobacteria in a mixed sample based on their spectral properties of natural fluorescence, classification of bacterial categories exhibiting different patterns of antigen expression, and multiparameter analysis of single mitochondria for drug discovery were successfully demonstrated.

Metal-Organic Frameworks in Microfluidics Enable Fast Encapsulation/Extraction of DNA for Automated and Integrated Data Storage.

DNA as an exceptional data storage medium offers high information density. However, DNA storage requires specialized equipment and tightly controlled environments for storage. Fast encapsulation within minutes for enhanced DNA stability to do away with specialized equipment and fast DNA extraction remain a challenge. Here, we report a DNA microlibrary that can be encapsulated by metal-organic frameworks (MOFs) within 10 min and extracted (5 min) in a single microfluidic chip for automated and integrated DNA-based data storage. The DNA microlibrary@MOFs enhances the stability of data-encoded DNA against harsh environments. The encoded information can be read out perfectly after accelerated aging, equivalent to being readable after 10 years of storage at 25 °C, 50% relative humidity, and 10 000 lx sunlight radiation. Moreover, the library enables fast retrieval of target data via flow cytometry and can be reproduced after each access.

Diffusion-weighted imaging and arterial spin labeling radiomics features may improve differentiation between radiation-induced brain injury and glioma recurrence.

OBJECTIVES: To determine whether radiomics features derived from diffusion-weighted imaging (DWI) and arterial spin labeling (ASL) can improve the differentiation between radiation-induced brain injury (RIBI) and tumor recurrence (TR) in glioma patients. METHODS: A total of 4199 radiomics features were extracted from conventional MRI, apparent diffusion coefficient (ADC), and cerebral blood flow (CBF) maps, obtained from 96 pathologically confirmed WHO grade 2~4 gliomas with enhancement after standard treatment. The intraclass correlation coefficient (ICC) was used to test segmentation stability between two doctors. Radiomics features were selected using the Mann-Whitney U test, LASSO regression, and RFE algorithms. Four machine learning classifiers were adopted to establish radiomics models. The diagnostic performance of multiparameter, conventional, and single-parameter MRI radiomics models was compared using the area under the curve (AUC). The models were evaluated in the subsequent independent validation set (n = 30). RESULTS: Eight important radiomics features (3 from conventional MRI, 1 from ADC, and 4 from CBF) were selected. Support vector machine (SVM) was chosen as the optimal classifier. The diagnostic performance of the multiparameter MRI radiomics model (AUC 0.96) was higher than that of the conventional MRI (AUC 0.88), ADC (AUC 0.91), and CBF (AUC 0.95) radiomics models. For subgroup analysis, the multiparameter MRI radiomics model showed similar performance, with AUCs of 0.98 in WHO grade 2~3 and 0.96 in WHO grade 4. CONCLUSION: The incorporation of noninvasive DWI and ASL into the MRI radiomics model improved the diagnostic performance in differentiating RIBI from TR; ASL, especially, played a significant role. KEY POINTS: • The multiparameter MRI radiomics model was superior to the conventional MRI radiomics model in differentiating glioma recurrence from radiation-induced brain injury. • Diffusion and perfusion MRI could improve the ability of the radiomics model in predicting the progression in patients with glioma. • Arterial spin labeling played an important role in predicting glioma progression using radiomics models.

Integrated Microfluidic DNA Storage Platform with Automated Sample Handling and Physical Data Partitioning.

Biopolymers are considered a promising alternative for information storage, and the most successful implementation has been using chemically synthesized DNA to represent binary data, which has achieved tremendous progress at multiple fronts bridging biotechnology with digital information. Currently, a majority of these systems are lacking the system integration and process automation expected by users of digital data and overly use tubes/vials for DNA storage. Herein, we present a microfluidic platform for automated storage and retrieval of data-encoding oligonucleotide samples enabled by a microvalve network architecture. Our platform, equipped with individually addressable compartments, offers an orthogonal strategy of data partitioning and file indexing with respect to the molecular-based random access implementation, with each partition amounting to an equivalence of 9.5 TB data within a 4 × 2 mm2 area. We examined the functionality of the presented platform and its compatibility with the DNA storage workflow coupled with nanopore sequencing to fully recover the stored files, demonstrating a significantly enhanced degree of function integration and process automation compared to that of the existing microfluidic approach.

Author Correction: Distinct thalamocortical network dynamics are associated with the pathophysiology of chronic low back pain.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Distinct thalamocortical network dynamics are associated with the pathophysiology of chronic low back pain.

Thalamocortical dysrhythmia is a key pathology of chronic neuropathic pain, but few studies have investigated thalamocortical networks in chronic low back pain (cLBP) given its non-specific etiology and complexity. Using fMRI, we propose an analytical pipeline to identify abnormal thalamocortical network dynamics in cLBP patients and validate the findings in two independent cohorts. We first identify two reoccurring dynamic connectivity states and their associations with chronic and temporary pain. Further analyses show that cLBP patients have abnormal connectivity between the ventral lateral/posterolateral nucleus (VL/VPL) and postcentral gyrus (PoCG) and between the dorsal/ventral medial nucleus and insula in the less frequent connectivity state, and temporary pain exacerbation alters connectivity between the VL/VPL and PoCG and the default mode network in the more frequent connectivity state. These results extend current findings on thalamocortical dysfunction and dysrhythmia in chronic pain and demonstrate that cLBP pathophysiology and clinical pain intensity are associated with distinct thalamocortical network dynamics.

Rapid quantification of pathogenic Salmonella Typhimurium and total bacteria in eggs by nano-flow cytometry.

Rapid quantification of pathogenic Salmonella Typhimurium (S. Typhimurium) and total bacteria in eggs is highly desired for food safety control. However, the complexity of egg matrix presents a significant challenge for sensitive detection of bacteria. In this study, a sample pretreatment protocol, including dilution, fat dissolution, protein degradation, filtration, and washing was developed to circumvent this challenge. A laboratory-built nano-flow cytometer (nFCM) that is hundreds of fold more sensitive than the conventional flow cytometer was employed to analyze individual bacteria upon nucleic acid and immunofluorescent staining. Eggs spiked with pathogenic S. Typhimurium and harmless Escherichia coli K12 (E. coli K12) were used as the model system to optimize the sample pretreatment protocol. S. Typhimurium and total bacteria in eggs can be quantified without cultural enrichment, and the whole process of sample pretreatment, staining, and instrument analysis can be accomplished within 1.5 h. The bacterial recovery rate upon sample pretreatment, detection limit, and dynamic range for S. Typhimurium in eggs were 92%, 2 × 103 cells/mL, and from 2 × 103 to 4 × 108 cells/mL, respectively. The as-developed approach can specifically distinguish S. Typhimurium from other bacteria and successful application to bacterial detection in eggs freshly purchased from supermarket and spoiled eggs upon inappropriate storage was demonstrated.

Brain gray matter alterations in Chinese patients with chronic knee osteoarthritis pain based on voxel-based morphometry.

Altered cerebral gray matter volume (GMV) is commonly found in patients with chronic pain. Chronic pain is the prominent characteristic of knee osteoarthritis (KOA), yet little is known about its morphological changes in the brain. Here an MRI study was performed to examine the structural brain abnormalities in 30 KOA patients with knee pain and age-matched healthy subjects. We detected that the patients exhibited significant almost 2-fold age-related decreases of GMV compared to healthy controls. Moreover, KOA patients also had significant loss of regional GMV including in the bilateral orbital frontal cortex (OFC), the right lateral prefrontal cortex (lPFC), and precentral and postcentral cortices. In addition, a high proportion of KOA patients exerted abnormal scores of Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Scale (HAMA), Mini Mental State examination (MMSE), and Montreal Cognitive Assessment (MoCA) compare to controls. Our results imply that chronic pain conditions which preferentially involve PFC might consider as a "cognitive state." And emotion and cognitive function about chronic pain should be highly regarded.

Porous carbon derived from Sunflower as a host matrix for ultra-stable lithium-selenium battery.

A novel porous carbon material using the spongy tissue of sunflower as raw material is reported for the first time. The obtained porous carbon has an extremely high surface area of 2493.0m2g-1, which is beneficial to focus on encapsulating selenium in it and have an inhibiting effect about diffusion of polyselenides over the charge/discharge processes used as the host matrix for Li-Se battery. The porous carbon/Se composite electrode with 63wt% selenium delivers a high specific capacitance of 319mAhg-1 of the initial capacity, and maintains 290mAhg-1, representing an extremely high capacity retention of 90.9% after 840 cycles with the rate of 1C.

[Brain gray matter abnormalities revealed by voxel-based morphometry in patients with chronic low back pain].

OBJECTIVE: To explore the morphometric abnormalities of brain gray matter (GM) in patients with chronic low back pain (CLBP). METHODS: Thirty patients with CLBP and 30 healthy individuals were enrolled and examined with a 3.0 T magnetic resonance (MR) scanner. High-resolution T1 structural MR data were acquired and data analysis was performed using voxel-based morphometry (VBM) in FMRIB Software Library. The morphological differences were compared between the two groups. RESULTS: s Compared with the healthy control subjects, patients with CLBP showed decreased GM volumes in several brain cortical areas including the bilateral superior frontal gyrus, right frontal pole, left insular cortex, left middle and left inferior temporal gyrus (P<0.05, after TFCE correction). Increased GM volumes were found in the patients in the subcortical structures including the left thalamus, bilateral putamen, bilateral nucleus accumben and right caudate nucleus (P<0.05, after TFCE correction). CONCLUSION: Patients with CLBP have different patterns of GM abnormalities in different brain regions, characterized by reduced GM volume in cerebral cortical regions and increased GM volume in the subcortical nuclei. Such changes might be associated with the maladaptation of the brain in chronic pain state.

Ferric ion-assisted in situ synthesis of silver nanoplates on polydopamine-coated silk.

In the present study, a ferric ion (Fe(3+))-assisted in situ synthesis approach was developed to grow silver (Ag) nanoplates on the polydopamine (PDA)-coated silk without the use of additional reductants. The essential role of Fe(3+) in the formation of Ag nanoplates is revealed by comparing the morphologies of Ag nanostructures prepared on the silk-coated PDA film with/without Fe(3+) doping. Scanning electron micrographs show that high-density Ag nanoplates could be synthesized in the reaction system containing 50µg/mL FeCl3 and 50mM AgNO3. The size of the Ag nanoplate could be tuned by adjusting the reaction duration. Based on the data, a mechanism involving the Fe(3+)-selected growth of Ag atoms along the certain crystal faces was proposed to explain the fabrication process. Transmission electron microscopy and X-ray diffractometry indicate that the Ag nanoplates possess good crystalline structures. Raman spectra demonstrate that the nanoplates could strongly enhance the Raman scattering of the PDA molecules. The Ag nanoplate-coated silk could be utilized as a flexible substrate for the development of surface-enhanced Raman scattering biosensors.

Aspergillus flavus Conidia-derived Carbon/Sulfur Composite as a Cathode Material for High Performance Lithium-Sulfur Battery.

A novel approach was developed to prepare porous carbon materials with an extremely high surface area of 2459.6 m(2)g(-1) by using Aspergillus flavus conidia as precursors. The porous carbon serves as a superior cathode material to anchor sulfur due to its uniform and tortuous morphology, enabling high capacity and good cycle lifetime in lithium sulfur-batteries. Under a current rate of 0.2 C, the carbon-sulfur composites with 56.7 wt% sulfur loading deliver an initial capacity of 1625 mAh g(-1), which is almost equal to the theoretical capacity of sulfur. The good performance may be ascribed to excellent electronic networks constructed by the high-surface-area carbon species. Moreover, the semi-closed architecture of derived carbons can effectively retard the polysulfides dissolution during charge/discharge, resulting in a capacity of 940 mAh g(-1) after 120 charge/discharge cycles.

Facile Synthesis of Novel Networked Ultralong Cobalt Sulfide Nanotubes and Its Application in Supercapacitors.

Ultralong cobalt sulfide (CoS(1.097)) nanotube networks are synthesized by a simple one-step solvothermal method without any surfactant or template. A possible formation mechanism for the growth processes is proposed. Owing to the hollow structure and large specific area, the novel CoS(1.097) materials present outstanding electrochemical properties. Electrochemical measurements for supercapacitors show that the as-prepared ultralong CoS(1.097) nanotube networks exhibit high specific capacity, good capacity retention, and excellent Coulombic efficiency.