Clinical Comparison between HD-tDCS and tDCS for Improving Upper Limb Motor Function: A Randomized, Double-Blinded, Sham-Controlled Trial.

Background: Stroke is a common and frequently occurring disease among middle-aged and elderly people, with approximately 55%-75% of patients remaining with upper limb dysfunction. How to promote the recovery of motor function at an early stage is crucial to the life of the patient. Objectives: This study aimed to investigate whether high-definition transcranial direct current stimulation (HD-tDCS) of the primary motor cortex (M1) functional area in poststroke patients in the subacute phase is more effective in improving upper limb function than conventional tDCS. Methods: This randomized, sham-controlled clinical trial included 69 patients with subcortical stroke. They were randomly divided into the HD-tDCS, anodal tDCS (a-tDCS), and sham groups. Each group received 20 sessions of stimulation. The patients were assessed using the Action Research Arm Test, Fugl-Meyer score for upper extremities, Motor Function Assessment Scale, and modified Barthel index (MBI) pretreatment and posttreatment. Results: The intragroup comparison scores improved after 4 weeks of treatment. The HD-tDCS group showed a slightly greater, but nonsignificant improvement as compared to a-tDCS group in terms of mean change observed in function of trained items. The MBI score of the HD-tDCS group was maintained up to 8 weeks of follow-up and was higher than that in the a-tDCS group. Conclusion: Both HD-tDCS and a-tDCS can improve upper limb motor function and daily activities of poststroke patients in the subacute stage. This trial is registered with ChiCTR2000031314.

Multiple semantic X-ray medical image retrieval using efficient feature vector extracted by FPN.

OBJECTIVE: Content-based medical image retrieval (CBMIR) has become an important part of computer-aided diagnostics (CAD) systems. The complex medical semantic information inherent in medical images is the most difficult part to improve the accuracy of image retrieval. Highly expressive feature vectors play a crucial role in the search process. In this paper, we propose an effective deep convolutional neural network (CNN) model to extract concise feature vectors for multiple semantic X-ray medical image retrieval. METHODS: We build a feature pyramid based CNN model with ResNet50V2 backbone to extract multi-level semantic information. And we use the well-known public multiple semantic annotated X-ray medical image data set IRMA to train and test the proposed model. RESULTS: Our method achieves an IRMA error of 32.2, which is the best score compared to the existing literature on this dataset. CONCLUSIONS: The proposed CNN model can effectively extract multi-level semantic information from X-ray medical images. The concise feature vectors can improve the retrieval accuracy of multi-semantic and unevenly distributed X-ray medical images.

[Simulation model of tumor-treating fields].

Tumor-treating fields (TTFields) is a novel treatment modality for malignant solid tumors, often employing electric field simulations to analyze the distribution of electric fields on the tumor under different parameters of TTFields. Due to the present difficulties and high costs associated with reproducing or implementing the simulation model construction techniques, this study used readily available open-source software tools to construct a highly accurate, easily implementable finite element simulation model for TTFields. The accuracy of the model is at a level of 1 mm 3. Using this simulation model, the study carried out analyses of different factors, such as tissue electrical parameters and electrode configurations. The results show that factors influncing the distribution of the internal electric field of the tumor include changes in scalp and skull conductivity (with a maximum variation of 21.0% in the treatment field of the tumor), changes in tumor conductivity (with a maximum variation of 157.8% in the treatment field of the tumor), and different electrode positions and combinations (with a maximum variation of 74.2% in the treatment field of the tumor). In summary, the results of this study validate the feasibility and effectiveness of the proposed modeling method, which can provide an important reference for future simulation analyses of TTFields and clinical applications.

A Dual-Branch Framework With Prior Knowledge for Precise Segmentation of Lung Nodules in Challenging CT Scans.

Lung cancer is one of the deadliest cancers globally, and early diagnosis is crucial for patient survival. Pulmonary nodules are the main manifestation of early lung cancer, usually assessed using CT scans. Nowadays, computer-aided diagnostic systems are widely used to assist physicians in disease diagnosis. The accurate segmentation of pulmonary nodules is affected by internal heterogeneity and external data factors. In order to overcome the segmentation challenges of subtle, mixed, adhesion-type, benign, and uncertain categories of nodules, a new mixed manual feature network that enhances sensitivity and accuracy is proposed. This method integrates feature information through a dual-branch network framework and multi-dimensional fusion module. By training and validating with multiple data sources and different data qualities, our method demonstrates leading performance on the LUNA16, Multi-thickness Slice Image dataset, LIDC, and UniToChest, with Dice similarity coefficients reaching 86.89%, 75.72%, 84.12%, and 80.74% respectively, surpassing most current methods for pulmonary nodule segmentation. Our method further improved the accuracy, reliability, and stability of lung nodule segmentation tasks even on challenging CT scans.

Magnetically Compatible Brain Electrode Arrays Based on Single-Walled Carbon Nanotubes for Long-Term Implantation.

Advancements in brain-machine interfaces and neurological treatments urgently require the development of improved brain electrodes applied for long-term implantation, where traditional and polymer options face challenges like size, tissue damage, and signal quality. Carbon nanotubes are emerging as a promising alternative, combining excellent electronic properties and biocompatibility, which ensure better neuron coupling and stable signal acquisition. In this study, a new flexible brain electrode array based on 99.99% purity of single-walled carbon nanotubes (SWCNTs) was developed, which has 30 um × 40 um size, about 5.1 kΩ impedance, and 14.01 dB signal-to-noise ratio (SNR). The long-term implantation experiment in vivo in mice shows the proposed brain electrode can maintain stable LFP signal acquisition over 12 weeks while still achieving an SNR of 3.52 dB. The histological analysis results show that SWCNT-based brain electrodes induced minimal tissue damage and showed significantly reduced glial cell responses compared to platinum wire electrodes. Long-term stability comes from SWCNT's biocompatibility and chemical inertness, the electrode's flexible and fine structure. Furthermore, the new brain electrode array can function effectively during 7-Tesla magnetic resonance imaging, enabling the collection of local field potential and even epileptic discharges during the magnetic scan. This study provides a comprehensive study of carbon nanotubes as invasive brain electrodes, providing a new path to address the challenge of long-term brain electrode implantation.

40 Hz light flickering promotes sleep through cortical adenosine signaling.

Flickering light stimulation has emerged as a promising non-invasive neuromodulation strategy to alleviate neuropsychiatric disorders. However, the lack of a neurochemical underpinning has hampered its therapeutic development. Here, we demonstrate that light flickering triggered an immediate and sustained increase (up to 3 h after flickering) in extracellular adenosine levels in the primary visual cortex (V1) and other brain regions, as a function of light frequency and intensity, with maximal effects observed at 40 Hz frequency and 4000 lux. We uncovered cortical (glutamatergic and GABAergic) neurons, rather than astrocytes, as the cellular source, the intracellular adenosine generation from AMPK-associated energy metabolism pathways (but not SAM-transmethylation or salvage purine pathways), and adenosine efflux mediated by equilibrative nucleoside transporter-2 (ENT2) as the molecular pathway responsible for extracellular adenosine generation. Importantly, 40 Hz (but not 20 and 80 Hz) light flickering for 30 min enhanced non-rapid eye movement (non-REM) and REM sleep for 2-3 h in mice. This somnogenic effect was abolished by ablation of V1 (but not superior colliculus) neurons and by genetic deletion of the gene encoding ENT2 (but not ENT1), but recaptured by chemogenetic inhibition of V1 neurons and by focal infusion of adenosine into V1 in a dose-dependent manner. Lastly, 40 Hz light flickering for 30 min also promoted sleep in children with insomnia by decreasing sleep onset latency, increasing total sleep time, and reducing waking after sleep onset. Collectively, our findings establish the ENT2-mediated adenosine signaling in V1 as the neurochemical basis for 40 Hz flickering-induced sleep and unravel a novel and non-invasive treatment for insomnia, a condition that affects 20% of the world population.

Hemorrhagic fever caused by a novel tick-borne Bunyavirus in Huaiyangshan,China / 中华流行病学杂志

Background:From April to July in 2009 and 2010,unexplained severe hemorrhagic fever-like illnesses occurred in farmers from the Huaiyangshan mountains range.Methods:Clinical specimens (blood,urine,feces,and throat swabs) from suspected patients were obtained and stored.Mosquitoes and ticks in affected regions were collected.Virus was isolated from 2 patients and characterized by whole genome sequencing.Virus detection in additional patients and arthropods was done by virus-specific reverse transcription (RT) PCR.Clinical and epidemiological data of RT-PCR confirmed patients were analyzed.Results:An unknown virus was isolated from blood of two patients and from Haemaphysalis ticks collected from dogs.Whole genome sequence analysis identified the virus as a novel member of the family Bunyaviridae,most closely related to the viruses of the genus Phlebovirus within which it forms a separate lineage.Subsequently,infection was confirmed by RT-PCR in 33 of 58 suspected patients.The illness in these patients was characterized by fever,severe malaise,nausea,vomiting,and diarrhea.Prominent laboratory findings included low white cell- and platelet counts,coagulation disturbances,and elevation of liver enzymes.Hemorrhagic complications were observed in 3 cases,5 (15%) patients died.Conclusions:A novel tick-borne Bunyavirus causing life-threatening hemorrhagic fever in humans has emerged in the Huaiyangshan mountain areas of China.Further studies are needed to determine the epidemiology,geographic distribution and vertebrate animal ecology of this virus.