Entanglement Structure: Entanglement Partitioning in Multipartite Systems and Its Experimental Detection Using Optimizable Witnesses

Creating large-scale entanglement lies at the heart of many quantum information processing protocols and the investigation of fundamental physics. For multipartite quantum systems, it is crucial to identify not only the presence of entanglement but also its detailed structure. This is because in a generic experimental situation with sufficiently many subsystems involved, the production of so-called genuine multipartite entanglement remains a formidable challenge. Consequently, focusing exclusively on the identification of this strongest type of entanglement may result in an all or nothing situation where some inherently quantum aspects of the resource are overlooked. On the contrary, even if the system is not genuinely multipartite entangled, there may still be many-body entanglement present in the system. An identification of the entanglement structure may thus provide us with a hint about where imperfections in the setup may occur, as well as where we can identify groups of subsystems that can still exhibit strong quantum-information-processing capabilities. However, there is no known efficient methods to identify the underlying entanglement structure. Here, we propose two complementary families of witnesses for the identification of such structures. They are based on the detection of entanglement intactness and entanglement depth, each requires only the implementation of solely two local measurements. Our method is also robust against noises and other imperfections, as reflected by our experimental implementation of these tools to verify the entanglement structure of five different eight-photon entangled states. We demonstrate how their entanglement structure can be precisely and systematically inferred from the experimental data. In achieving this goal, we also illustrate how the same set of data can be classically postprocessed to learn the most about the measured system.Comment: 21 pages, 13 figure

Sialylation of vasorin by ST3Gal1 facilitates TGF-β1-mediated tumor angiogenesis and progression.

ST3Gal1 is a key sialyltransferase which adds α2,3-linked sialic acid to substrates and generates core 1 O-glycan structure. Upregulation of ST3Gal1 has been associated with worse prognosis of breast cancer patients. However, the protein substrates of ST3Gal1 implicated in tumor progression remain elusive. In our study, we demonstrated that ST3GAL1-silencing significantly reduced tumor growth along with a notable decrease in vascularity of MCF7 xenograft tumors. We identified vasorin (VASN) which was shown to bind TGF-β1, as a potential candidate that links ST3Gal1 to angiogenesis. LC-MS/MS analysis of VASN secreted from MCF7, revealed that more than 80% of its O-glycans are sialyl-3T and disialyl-T. ST3GAL1-silencing or desialylation of VASN by neuraminidase enhanced its binding to TGF-β1 by 2- to 3-fold and thereby dampening TGF-β1 signaling and angiogenesis, as indicated by impaired tube formation of HUVECs, suppressed angiogenesis gene expression and reduced activation of Smad2 and Smad3 in HUVEC cells. Examination of 114 fresh primary breast cancer and their adjacent normal tissues showed that the expression levels of ST3Gal1 and TGFB1 were high in tumor part and the expression of two genes was positively correlated. Kaplan Meier survival analysis showed a significantly shorter relapse-free survival for those with lower expression VASN, notably, the combination of low VASN with high ST3GAL1 yielded even higher risk of recurrence (p = 0.025, HR = 2.967, 95% CI = 1.14-7.67). Since TGF-β1 is known to transcriptionally activate ST3Gal1, our findings illustrated a feedback regulatory loop in which TGF-β1 upregulates ST3Gal1 to circumvent the negative impact of VASN

The significance of seizures and other predictive factors during the acute illness for the long-term outcome after bacterial meningitis

SummaryBackgroundSeizures are important neurological complications of bacterial meningitis, but no information about its epidemiology and the outcomes of seizures after community-acquired bacterial meningitis (CABM) in an adult population have been reported.AimsTo determine the frequency, clinical relevance, subtypes of seizures during the acute phase of bacterial meningitis, and the long-term outcomes of seizure complicating adult CABM.MethodsIn this 12-year retrospective study, 117 adult patients were identified with culture-proven CABM. A comparison was made between the clinical data of the patients with and without seizures during hospitalization.ResultsThirty-one patients had seizures during CABM, accounting for 27% (31/117) of the episodes. The time interval between the onset of bacterial meningitis and the seizures was 1–21 days (mean, 4 days). Furthermore, 80% (25/31) of the episodes occurred within 24h of presentation. Ten patients who had seizures progressed to status epilepticus. At follow-up after completing treatment, 10 patients completely recovered and were seizure-free, 19 died of meningitis during the acute stage and the other two progressed to chronic epilepsy.ConclusionA log-rank test demonstrated that the long-term outcome of adult CABM with acute seizures produced worse outcomes than for those who had no seizures, though no difference was noted between focal and generalized seizures. None of our patients without seizures in the acute phase of bacterial meningitis developed late seizures during the follow-up periods. Poor outcome in this study may attribute to neurological complications such as seizure, hydrocephalus, infection itself, or a combination of complications

Image operator learning coupled with CNN classification and its application to staff line removal

Many image transformations can be modeled by image operators that are characterized by pixel-wise local functions defined on a finite support window. In image operator learning, these functions are estimated from training data using machine learning techniques. Input size is usually a critical issue when using learning algorithms, and it limits the size of practicable windows. We propose the use of convolutional neural networks (CNNs) to overcome this limitation. The problem of removing staff-lines in music score images is chosen to evaluate the effects of window and convolutional mask sizes on the learned image operator performance. Results show that the CNN based solution outperforms previous ones obtained using conventional learning algorithms or heuristic algorithms, indicating the potential of CNNs as base classifiers in image operator learning. The implementations will be made available on the TRIOSlib project site.Comment: To appear in ICDAR 201

Whole-genome DNA methylome analysis of different developmental stages of the entomopathogenic fungus Beauveria bassiana NCHU-157 by nanopore sequencing

The entomopathogenic fungus (EPF), Beauveria bassiana, is an important and commonly used EPF for microbial control. However, the role of DNA methylation has not been thoroughly studied. Therefore, the whole genomic DNA methylome of one promising EPF isolate, B. bassiana NCHU-157 (Bb-NCHU-157), was investigated by Oxford Nanopore Technologies (ONT). First, the whole genome of Bb-NCHU-157 was sequenced by next-generation sequencing (NGS) and ONT. The genome of Bb-NCHU-157 contains 16 contigs with 34.19 Mb and 50% GC content, which are composed of 10,848 putative protein-coding genes. Two putative DNA methyltransferases (DNMTs) were found, including Dim-2 and C-5 cytosine-specific DNA methylases. Both DNMTs showed higher expression levels in the mycelium stage than in the conidia stage, indicating that development of DNA methylation in Bb-NCHU-157 might occur in the mycelium stage. The global methylation level of the mycelium stage (5 mC = 4.56%, CG = 3.33%, CHG = 0.74%, CHH = 0.49%) was higher than that of the conidial stage (5 mC = 2.99%, CG = 1.99%, CHG = 0.63%, CHH = 0.37%) in both the gene and transposable element (TE) regions. Furthermore, the TE regions showed higher methylation frequencies than the gene regions, especially for CHH site methylation, suggesting regulation of genomic stabilization during mycelium development. In the gene regions, high methylation frequencies were found around the transcription start site (TSS) and transcription end site (TES). Moreover, CG and CHG methylation mainly occur in the promoter and intergenic regions, while CHH methylation occurs in the TE region. Among the methylated regions, 371, 661, and 756 differentially DNA methylated regions (DMRs) were hypermethylated in the mycelium in CG, CHG, and CHH, while only 13 and 7 DMRs were hypomethylated in the mycelium in CHG, and CHH, respectively. Genes located in the DMR shared the GO terms, DNA binding (GO: 0003677), and sequence-specific DNA binding (GO: 0043565) for hypermethylation in the mycelium, suggesting that methylation might regulate gene expression from the initial process. Evaluation of the DNA methylome in Bb-NCHU-157 by ONT provided new insight into this field. These data will be further validated, and epigenetic regulation during the development of B. bassiana will be explored

Impact of cognitive behavior therapy on osteoarthritis-associated pain, insomnia, depression, fatigue, and physical function in patients with knee/hip osteoarthritis: A systematic review and meta-analysis of randomized controlled trials

BackgroundThis meta-analysis aimed at evaluating the efficacy of cognitive behavior therapy (CBT) against osteoarthritis-associated symptoms in patients with knee/hip osteoarthritis.MethodsMedline, PubMed, Cochrane Library, and EMBASE databases were searched from inception to July 2022 to identify randomized controlled trials (RCTs) comparing the efficacy of CBT with other treatment approaches in adults with confirmed knee/hip osteoarthritis. The pain intensity (primary outcome) and the secondary outcomes including insomnia severity, sleep efficiency, physical function as well as the severity of depression and fatigue were assessed at two time points (i.e., immediately after treatment and during the follow-up period). The effect size is expressed as standardized mean difference (SMD) with SMDs of < 0.2, 0.2–0.5, and 0.5–0.8, and > 0.8 representing negligible, small, medium, and large effect sizes, respectively.ResultsFifteen RCTs were included for analysis. Immediately after CBT intervention, meta-analysis showed similar treatment effect in pain severity [SMD = –0.46, 95% confidence interval (CI): –0.95 to 0.04, 11 studies, 1557 participants] and other symptoms including depression (SMD = –0.26, 95% CI: –0.58 to 0.06, five studies, 735 participants), fatigue (SMD = –2.44, 95% CI:–6.53 to 1.65, two RCTs, 511 participants), and physical function (SMD = –0.11, 95% CI:–0.25 to 0.02, five RCTs, 720 participants) between CBT and control groups, while there was an improvement in insomnia severity (SMD = –0.65, 95% CI: –1.06 to –0.24, four RCTs, 639 participants, medium treatment effect) and sleep efficiency (SMD = 0.32, 95% CI: 0.04 to 0.59, three RCTs, 352 patients, small treatment effect). During follow-up, CBT improved pain severity (SMD = –0.52, 95% CI: –1.03 to –0.01, eight studies, 1447 participants, medium treatment effect), insomnia (SMD = –0.43, 95% CI: –0.85 to –0.01, three RCTs, 571 participants, small treatment effect), and depression (SMD = –0.39, 95% CI: –0.59 to –0.18, four RCTs, 791 participants, small treatment effect). Nevertheless, sleep efficiency, fatigue, and physical function were not improved in the follow-up period.ConclusionOur results may suggest the durability of CBT-associated treatment benefits, supporting its role as a potential promising alternative or complementary intervention for patients with knee/hip osteoarthritis, especially against pain and insomnia. Future large-scale investigations are warranted to verify our findings.Systematic review registration[https://www.crd.york.ac.uk/prospero/], identifier [CRD42022331165]

Altered Striatocerebellar Metabolism and Systemic Inflammation in Parkinson’s Disease

Parkinson’s disease (PD) is the most second common neurodegenerative movement disorder. Neuroinflammation due to systemic inflammation and elevated oxidative stress is considered a major factor promoting the pathogenesis of PD, but the relationship of structural brain imaging parameters to clinical inflammatory markers has not been well studied. Our aim was to evaluate the association of magnetic resonance spectroscopy (MRS) measures with inflammatory markers. Blood samples were collected from 33 patients with newly diagnosed PD and 30 healthy volunteers. MRS data including levels of N-acetylaspartate (NAA), creatine (Cre), and choline (Cho) were measured in the bilateral basal ganglia and cerebellum. Inflammatory markers included plasma nuclear DNA, plasma mitochondrial DNA, and apoptotic leukocyte levels. The Cho/Cre ratio in the dominant basal ganglion, the dominant basal ganglia to cerebellum ratios of two MRS parameters NAA/Cre and Cho/Cre, and levels of nuclear DNA, mitochondrial DNA, and apoptotic leukocytes were significantly different between PD patients and normal healthy volunteers. Significant positive correlations were noted between MRS measures and inflammatory marker levels. In conclusion, patients with PD seem to have abnormal levels of inflammatory markers in the peripheral circulation and deficits in MRS measures in the dominant basal ganglion and cerebellum