Experimental Test of Tracking the King Problem

In quantum theory, the retrodiction problem is not as clear as its classical counterpart because of the uncertainty principle of quantum mechanics. In classical physics, the measurement outcomes of the present state can be used directly for predicting the future events and inferring the past events which is known as retrodiction. However, as a probabilistic theory, quantum-mechanical retrodiction is a nontrivial problem that has been investigated for a long time, of which the Mean King Problem is one of the most extensively studied issues. Here, we present the first experimental test of a variant of the Mean King Problem, which has a more stringent regulation and is termed "Tracking the King". We demonstrate that Alice, by harnessing the shared entanglement and controlled-not gate, can successfully retrodict the choice of King's measurement without knowing any measurement outcome. Our results also provide a counterintuitive quantum communication to deliver information hidden in the choice of measurement.Comment: 16 pages, 5 figures, 2 table

An innovative EEG-based emotion recognition using a single channel-specific feature from the brain rhythm code method.

Efficiently recognizing emotions is a critical pursuit in brain–computer interface (BCI), as it has many applications for intelligent healthcare services. In this work, an innovative approach inspired by the genetic code in bioinformatics, which utilizes brain rhythm code features consisting of δ, θ, α, β, or γ, is proposed for electroencephalography (EEG)-based emotion recognition. These features are first extracted from the sequencing technique. After evaluating them using four conventional machine learning classifiers, an optimal channel-specific feature that produces the highest accuracy in each emotional case is identified, so emotion recognition through minimal data is realized. By doing so, the complexity of emotion recognition can be significantly reduced, making it more achievable for practical hardware setups. The best classification accuracies achieved for the DEAP and MAHNOB datasets range from 83–92%, and for the SEED dataset, it is 78%. The experimental results are impressive, considering the minimal data employed. Further investigation of the optimal features shows that their representative channels are primarily on the frontal region, and associated rhythmic characteristics are typical of multiple kinds. Additionally, individual differences are found, as the optimal feature varies with subjects. Compared to previous studies, this work provides insights into designing portable devices, as only one electrode is appropriate to generate satisfactory performances. Consequently, it would advance the understanding of brain rhythms, which offers an innovative solution for classifying EEG signals in diverse BCI applications, including emotion recognition

Compare Deep Learning Model and Conventional Logistic Regression Model for the Identification of Unstable Saccular Intracranial Aneurysms in Computed Tomography Angiography

BACKGROUND: It is crucial to distinguish unstable from stable intracranial aneurysms (IAs) as early as possible to derive optimal clinical decision-making for further treatment or follow-up. The aim of this study was to investigate the value of a deep learning model (DLM) in identifying unstable IAs from computed tomography angiography (CTA) images and to compare its discriminatory ability with that of a conventional logistic regression model (LRM). METHODS: From August 2011 to May 2021, a total of 1,049 patients with 681 unstable IAs and 556 stable IAs were retrospectively analyzed. IAs were randomly divided into training (64%), internal validation (16%), and test sets (20%). Convolutional neural network (CNN) analysis and conventional logistic regression (LR) were used to predict which IAs were unstable. The area under the curve (AUC), sensitivity, specificity and accuracy were calculated to evaluate the discriminating ability of the models. One hundred and ninety-seven patients with 229 IAs from Banan Hospital were used for external validation sets. RESULTS: The conventional LRM showed 11 unstable risk factors, including clinical and IA characteristics. The LRM had an AUC of 0.963 [95% confidence interval (CI): 0.941-0.986], a sensitivity, specificity and accuracy on the external validation set of 0.922, 0.906, and 0.913, respectively, in predicting unstable IAs. In predicting unstable IAs, the DLM had an AUC of 0.771 (95% CI: 0.582-0.960), a sensitivity, specificity and accuracy on the external validation set of 0.694, 0.929, and 0.782, respectively. CONCLUSIONS: The CNN-based DLM applied to CTA images did not outperform the conventional LRM in predicting unstable IAs. The patient clinical and IA morphological parameters remain critical factors for ensuring IA stability. Further studies are needed to enhance the diagnostic accuracy

Effect of Prunella vulgaris L extract on hyperprolactinemia in vitro and in vivo

Purpose: To investigate the anti-hyperprolactinemic activity of Prunella vulgaris L. extract (PVE) in vivo and in vitro.Methods: Rats were given intraperitoneal (i. p.) metoclopramide (MCP, 150 mg/kg daily) for 10 days to prepare hyperprolactinemia (hyperPRL) model. Bromocriptine was used as positive control drug. High (5.6 g/kg), medium (2.8 g/kg) and low (1.4 g/kg) doses of PVE were administered to hyperPRL rats. The effect of PVE on serum prolactin (PRL), estradiol (E2), progesterone (PGN), follicle stimulating hormone (FSH) and luteinizing hormone (LH) levels were investigated in the rats. MMQ cells derived from rat pituitary adenoma cells and GH3 cells from rat pituitary lactotropictumoral cells were used for in vitro experiments. The effect of PVE on PRL secretion were studied in MMQ cells and GH3 cells respectively.Results: Compared with the control group (446.21 ± 32.43 pg/mL), high (219.23 ± 10.62 pg/mL) and medium (245.47 ± 13.52 pg/mL) reduced PRL level of hyperPRL rats significantly (p 0.05). In MMQ cells, treatment with 5 mg/mL PVE or 10 mg/mL PVE) significantly suppressed PRL secretion and synthesis at 24h compared with controls (p < 0.01). Consistent with D2- action, PVE did not affect PRL in rat pituitary lactotropic tumor-derived GH3 cells that lack the D2 receptor expression, compared with controls.Conclusion: PVE showed anti-hyperPRL activity and can potentially be used for the treatment of hyperprolactinemi, but further studies are required to ascertain this.Keywords: Prunella vulgaris, Hyperprolactinemia, Prolactin, Bromocriptin

Involvement and repair of epithelial barrier dysfunction in allergic diseases

The epithelial barrier serves as a critical defense mechanism separating the human body from the external environment, fulfilling both physical and immune functions. This barrier plays a pivotal role in shielding the body from environmental risk factors such as allergens, pathogens, and pollutants. However, since the 19th century, the escalating threats posed by environmental pollution, global warming, heightened usage of industrial chemical products, and alterations in biodiversity have contributed to a noteworthy surge in allergic disease incidences. Notably, allergic diseases frequently exhibit dysfunction in the epithelial barrier. The proposed epithelial barrier hypothesis introduces a novel avenue for the prevention and treatment of allergic diseases. Despite increased attention to the role of barrier dysfunction in allergic disease development, numerous questions persist regarding the mechanisms underlying the disruption of normal barrier function. Consequently, this review aims to provide a comprehensive overview of the epithelial barrier’s role in allergic diseases, encompassing influencing factors, assessment techniques, and repair methodologies. By doing so, it seeks to present innovative strategies for the prevention and treatment of allergic diseases

Quality of reporting of systematic reviews published in “evidence-based” Chinese journals

BACKGROUND: The number of systematic reviews (SRs)/meta-analyses (MAs) has increased dramatically in China over the past decades. However, evaluation of quality of reporting of systematic reviews published has not been undertaken. The objective of this study is to evaluate the quality of reporting of SRs/MAs assessing efficacy and/or harms of clinical interventions published in “evidence-based” Chinese journals. METHODS: Web-based database searches were conducted for the Chinese Journal of Evidence-based Medicine, the Journal of Evidence-Based Medicine, the Chinese Journal of Evidence Based Pediatrics, and the Chinese Journal of Evidence-Based Cardiovascular Medicine. SRs/MAs assessing efficacy and/or harms of clinical interventions were included. The cut-off was December 31st 2011. The PRISMA statement was applied to assess the quality of reporting. Each item was assessed as follows: ‘Yes’ for total compliance, scored ‘1’; ‘partial’ for partial compliance, scored ‘0.5’; and ‘No’ for non-compliance, scored ‘0’. The review was considered to have major flaws if it received a total score of ≤15.0, minor flaws if it received a total score of 15.5 to 21.0, and minimal flaws if it received a total score 21.5 to 27.0. Odds ratios were used for binary variables, and the mean difference was used for continuous variables. Analyses were performed using RevMan 5.0 software. RESULTS: Overall, 487 SRs/MAs were identified and assessed. The included reviews had medium quality with minor flaws based on PRISMA total scores (range: 8.5–26.0; mean: 19.6 ± 3.3). The stratified analysis showed that SRs/MAs with more than 3 authors, from a university, hospital + university cooperation, multiple affiliations (≥2), and funding have significantly higher quality of reporting of SRs/MAs; 58% of the included reviews were considered to have minor flaws (total score of 15.6 to 21.0). Only 9.6% of reviews were considered to have major flaws. Specific areas needing improvement in reporting include the abstract, protocol and registration, and characteristics of the search. CONCLUSIONS: The reporting of SRs published in “evidence-based” Chinese journals is poor and needs to be improved in order for reviews to be useful. SR authors should use the PRISMA checklist to ensure complete and accurate accounts of their SRs