96 research outputs found
Strong cosmic censorship for the massless Dirac field in the Reissner-Nordstrom-de Sitter spacetime
We present the Fermi story of strong cosmic censorship in the near-extremal
Reissner-Nordstrom-de Sitter black hole. To this end, we first derive from
scratch the criterion for the quasi-normal modes of Dirac field to violate
strong cosmic censorship in such a background, which turns out to be exactly
the same as those for Bose fields, although the involved energy momentum tensor
is qualitatively different from that for Bose fields. Then to extract the
low-lying quasi-normal modes by Prony method, we apply Crank-Nicolson method to
evolve our Dirac field in the double null coordinates. As a result, it shows
that for a fixed near-extremal black hole, strong cosmic censorship can be
recovered by the black hole family mode once the charge of our
Dirac field is greater than some critical value, which is increased as one
approaches the extremal black hole.Comment: JHEP published versio
RLogist: Fast Observation Strategy on Whole-slide Images with Deep Reinforcement Learning
Whole-slide images (WSI) in computational pathology have high resolution with
gigapixel size, but are generally with sparse regions of interest, which leads
to weak diagnostic relevance and data inefficiency for each area in the slide.
Most of the existing methods rely on a multiple instance learning framework
that requires densely sampling local patches at high magnification. The
limitation is evident in the application stage as the heavy computation for
extracting patch-level features is inevitable. In this paper, we develop
RLogist, a benchmarking deep reinforcement learning (DRL) method for fast
observation strategy on WSIs. Imitating the diagnostic logic of human
pathologists, our RL agent learns how to find regions of observation value and
obtain representative features across multiple resolution levels, without
having to analyze each part of the WSI at the high magnification. We benchmark
our method on two whole-slide level classification tasks, including detection
of metastases in WSIs of lymph node sections, and subtyping of lung cancer.
Experimental results demonstrate that RLogist achieves competitive
classification performance compared to typical multiple instance learning
algorithms, while having a significantly short observation path. In addition,
the observation path given by RLogist provides good decision-making
interpretability, and its ability of reading path navigation can potentially be
used by pathologists for educational/assistive purposes. Our code is available
at: \url{https://github.com/tencent-ailab/RLogist}.Comment: accepted by AAAI 202
Acupuncture treatment for post-stroke depression: Intestinal microbiota and its role
Stroke-induced depression is a common complication and an important risk factor for disability. Besides psychiatric symptoms, depressed patients may also exhibit a variety of gastrointestinal symptoms, and even take gastrointestinal symptoms as the primary reason for medical treatment. It is well documented that stress may disrupt the balance of the gut microbiome in patients suffering from post-stroke depression (PSD), and that disruption of the gut microbiome is closely related to the severity of the condition in depressed patients. Therefore, maintaining the balance of intestinal microbiota can be the focus of research on the mechanism of acupuncture in the treatment of PSD. Furthermore, stroke can be effectively treated with acupuncture at all stages and it may act as a special microecological regulator by regulating intestinal microbiota as well. In this article, we reviewed the studies on changing intestinal microbiota after acupuncture treatment and examined the existing problems and development prospects of acupuncture, microbiome, and poststroke depression, in order to provide new ideas for future acupuncture research
Acupuncture for insomnia symptoms in hypertensive patients: a systematic review and meta-analysis
PurposeIn the realm of pain management, traditional Chinese medicine, specifically acupuncture, has garnered increasing attention. This meta-analysis pioneers the evaluation of acupuncture’s effectiveness in treating insomnia among hypertensive patients.MethodsWe conducted a comprehensive search across several databases—PubMed, Web of Science, Cochrane Library, WANFANG, China National Knowledge Infrastructure (CNKI), Sinomed, and the Chinese Journal of Science and Technology (VIP). Additionally, forward and backward articles of studies published from the inception of these databases until 10 September 2023, were reviewed. This systematic review and meta-analysis included all randomized controlled trials (RCTs) focusing on acupuncture for insomnia in hypertensive patients, without imposing language or date restrictions. We rigorously assessed all outcome measures reported in these trials. The evidence was synthesized by calculating the difference between mean differences (MD) in symptom change. The quality of the evidence was determined using the Cochrane Risk of Bias tool. This study is registered with PROSPERO under number CRD42023461760.ResultsOur analysis included 16 RCTs, comprising 1,309 patients. The findings revealed that acupuncture was significantly more effective than the control group in reducing insomnia symptoms, as indicated by a greater decrease in the PSQI score (MD = −3.1, 95% CI [−3.77 to −2.62], p < 0.00001). Additionally, improvements in both systolic and diastolic blood pressure were more pronounced in the acupuncture group compared to the control group (SBP: MD = −10.31, 95% CI [−16.98 to −3.64], p = 0.002; DBP: MD = −5.71, 95% CI [−8.19 to −3.23], p < 0.00001). These results suggest that acupuncture not only improves sleep quality but also lowers blood pressure in patients suffering from hypertension and insomnia. Further research is warranted to elucidate optimal acupuncture points and the duration of treatment for maximized therapeutic effect.Systematic review registration:https://www.crd.york.ac.uk/prospero, CRD42023461760
Application of diffusion tensor imaging in the diagnosis of post-stroke aphasia: a meta-analysis and systematic review
IntroductionDiffusion Tensor Imaging (DTI) indicators of different white matter (WM) fibers and brain region lesions for post-stroke aphasia (PSA) are inconsistent in existing studies. Our study examines the consistency and differences between PSA tests performed with DTI. In addition, obtaining consistent and independent conclusions between studies was made possible by utilizing DTI in PSA assessment.MethodsIn order to gather relevant studies using DTI for diagnosing PSA, we searched the Web of Science, PubMed, Embase, and CNKI databases. Based on the screening and evaluation of the included studies, the meta-analysis was used to conduct a quantitative analysis. Narrative descriptions were provided for studies that met the inclusion criteria but lacked data.ResultsFirst, we reported on the left hemisphere. The meta-analysis showed that fractional anisotropy (FA) of the arcuate fasciculus (AF) and superior longitudinal fasciculus (SLF), inferior frontal-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), and uncinate fasciculus (UF) were decreased in the PSA group in comparison with the healthy controls (p < 0.00001). However, in the comparison of axial diffusivity (AD), there was no statistically significant difference in white matter fiber tracts in the dual-stream language model of the PSA group. Elevated radial diffusivity (RD) was seen only in the IFOF and ILF (PIFOF = 0.01; PILF = 0.05). In the classic Broca’s area, the FA of the PSA group was decreased (p < 0.00001) while the apparent diffusion coefficient was elevated (p = 0.03). Secondly, we evaluated the white matter fiber tracts in the dual-stream language model of the right hemisphere. The FA of the PSA group was decreased only in the IFOF (p = 0.001). AD was elevated in the AF and UF (PAF < 0.00001; PUF = 0.009). RD was elevated in the AF and UF (PAF = 0.01; PUF = 0.003). The other fiber tracts did not undergo similar alterations.ConclusionIn conclusion, DTI is vital for diagnosing PSA because it detects WM changes effectively, but it still has some limitations. Due to a lack of relevant language scales and clinical manifestations, diagnosing and differentiating PSA independently remain challenging.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=365897
Broadband nonlinear modulation of incoherent light using a transparent optoelectronic neuron array
Nonlinear optical processing of ambient natural light is highly desired in
computational imaging and sensing applications. A strong optical nonlinear
response that can work under weak broadband incoherent light is essential for
this purpose. Here we introduce an optoelectronic nonlinear filter array that
can address this emerging need. By merging 2D transparent phototransistors
(TPTs) with liquid crystal (LC) modulators, we create an optoelectronic neuron
array that allows self-amplitude modulation of spatially incoherent light,
achieving a large nonlinear contrast over a broad spectrum at
orders-of-magnitude lower intensity than what is achievable in most optical
nonlinear materials. For a proof-of-concept demonstration, we fabricated a
10,000-pixel array of optoelectronic neurons, each serving as a nonlinear
filter, and experimentally demonstrated an intelligent imaging system that uses
the nonlinear response to instantly reduce input glares while retaining the
weaker-intensity objects within the field of view of a cellphone camera. This
intelligent glare-reduction capability is important for various imaging
applications, including autonomous driving, machine vision, and security
cameras. Beyond imaging and sensing, this optoelectronic neuron array, with its
rapid nonlinear modulation for processing incoherent broadband light, might
also find applications in optical computing, where nonlinear activation
functions that can work under ambient light conditions are highly sought.Comment: 20 Pages, 5 Figure
Genetic analysis of chikungunya viruses imported to mainland China in 2008
<p>Abstract</p> <p>Background</p> <p>Chikungunya virus (CHIKV) has caused large outbreaks worldwide in recent years, especially on the islands of the Indian Ocean and India. The virus is transmitted by mosquitoes (<it>Aedes aegypti</it>), which are widespread in China, with an especially high population density in southern China. Analyses of full-length viral sequences revealed the acquisition of a single adaptive mutation providing a selective advantage for the transmission of CHIKV by this species. No outbreaks due to the local transmission of CHIKV have been reported in China, and no cases of importation were detected on mainland China before 2008. We followed the spread of imported CHIKV in southern China and analyzed the genetic character of the detected viruses to evaluate their potential for evolution.</p> <p>Results</p> <p>The importation of CHIKV to mainland China was first detected in 2008. The genomic sequences of four of the imported viruses were identified, and phylogenetic analysis demonstrated that the sequences were clustered in the Indian Ocean group; however, seven amino acid changes were detected in the nonstructural protein-coding region, and five amino acid changes were noted in the structural protein-coding regions. In particular, a novel substitution in E2 was detected (K252Q), which may impact the neurovirulence of CHIKV. The adaptive mutation A226V in E1 was observed in two imported cases of chikungunya disease.</p> <p>Conclusions</p> <p>Laboratory-confirmed CHIKV infections among travelers visiting China in 2008 were presented, new mutations in the viral nucleic acids and proteins may represent adaptive mutations for human or mosquito hosts.</p
Phase-transition-promoted thermoelectric textiles based on twin surface-modified CNT fibers
With the fast development of new science and technology, wearable devices are in great demand in modern human daily life. However, the energy problem is a long-lasting issue to achieve real smart, wearable, and portable devices. Flexible thermoelectric generators (TEGs) based on thermoelectric conversion systems can convert body waste heat into electricity with excellent flexibility and wearability, which shows a new direction to solving this issue. Here in this work, polyethylenimine (PEI) and gold nanoparticles (Au NPs) twin surface-modified carbon nanotube fibers (CNTFs) were designed and prepared to fabricate thermoelectric textiles (TET) with high performance, good air stability, and high-efficiency power generation. To better utilize the heat emitted by the human body, microencapsulated phase change materials (MPCM) were coated on the hot end of the TET to achieve the phase-transition-promoted TET. MPCM-coated TET device could generate 25.7% more energy than the untreated control device, which indicates the great potential of the phase-transition-promoted TET
The Prognostic Significance of NEK2 in Hepatocellular Carcinoma: Evidence from a Meta-Analysis and Retrospective Cohort Study
Background/Aims: Numerous studies have shown that NIMA-related kinase 2 (NEK2) expression in hepatocellular carcinoma (HCC) tissue is associated with survival and clinicopathological features; however, the evidence remains inconclusive. Thus, we aimed to further explore the prognostic and clinicopathological significance of NEK2 expression in HCC using a two-part study consisting of a retrospective cohort study and a meta-analysis. Methods: In the cohort study, NEK2 expression in 206 HCC samples and adjacent normal liver tissues was detected by immunohistochemistry (IHC). Patients were divided into a high NEK2 expression group and a low NEK2 expression group by the median value of the immunohistochemical scores. The Kaplan–Meier method with the log-rank test was used to analyze survival outcomes in the two groups, and multivariate analysis based on Cox proportional hazard regression models was applied to identify independent prognostic factors. In the meta-analysis, eligible studies were searched in PubMed, EMBASE, Web of Science, and CNKI databases. STATA version 12.0 (Stata Corporation, College Station, TX) was used for statistical analyses. Results: The IHC results of our cohort study showed higher NEK2 expression in HCC tissues compared with adjacent normal liver tissues. Multivariate analysis revealed that high NEK2 expression was an independent risk factor for poor overall survival (OS) [hazard ratio (HR) = 1.763; 95% CI, 1.060–2.935; P = 0.029] and disease-free survival (DFS) [hazard ratio (HR) = 1.687; 95% CI, 1.102–2.584; P = 0.016] in HCC patients. A total of 11 studies with 1,698 patients were enrolled in the meta-analysis, consisting of 10 studies from the database search and our cohort study. The pooled results revealed that high NEK2 expression correlated closely with poor OS among HCC patients (HR = 1.47; 95% CI, 1.21–1.80; P < 0.01), and DFS/recurrence-free survival (RFS) (HR = 1.92; 95% CI, 1.41–2.63; P < 0.01). Additionally, our meta-analysis also showed that the proportion of HCC patients with high NEK2 expression was greater in the group with larger tumors (> 5 cm) than in the group with smaller tumors (≤ 5 cm) [odds ratio (OR) = 2.02; 95% CI, 1.13–3.64; P < 0.01). Conclusion: Our study demonstrated that high NEK2 expression is a risk factor for poor survival in HCC patients. More prospective, homogeneous, and multiethnic studies are required to validate our findings
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