On spectra and Brown's spectral measures of elements in free products of matrix algebras

We compute spectra and Brown measures of some non self-adjoint operators in (M_2(\cc), {1/2}Tr)*(M_2(\cc), {1/2}Tr), the reduced free product von Neumann algebra of M_2(\cc) with M_2(\cc). Examples include $AB$ and $A+B$, where A and B are matrices in (M_2(\cc), {1/2}Tr)*1 and 1*(M_2(\cc), {1/2}Tr), respectively. We prove that AB is an R-diagonal operator (in the sense of Nica and Speicher \cite{N-S1}) if and only if Tr(A)=Tr(B)=0. We show that if X=AB or X=A+B and A,B are not scalar matrices, then the Brown measure of X is not concentrated on a single point. By a theorem of Haagerup and Schultz \cite{H-S1}, we obtain that if X=AB or X=A+B and $X\neq \lambda 1$, then X has a nontrivial hyperinvariant subspace affiliated with (M_2(\cc), {1/2}Tr)*(M_2(\cc), {1/2}Tr).Comment: final version. to appear on Math. Sca

Discovery of Novel Insulin Sensitizers: Promising Approaches and Targets

Insulin resistance is the undisputed root cause of type 2 diabetes mellitus (T2DM). There is currently an unmet demand for safe and effective insulin sensitizers, owing to the restricted prescription or removal from market of certain approved insulin sensitizers, such as thiazolidinediones (TZDs), because of safety concerns. Effective insulin sensitizers without TZD-like side effects will therefore be invaluable to diabetic patients. The specific focus on peroxisome proliferator-activated receptor γ- (PPARγ-) based agents in the past decades may have impeded the search for novel and safer insulin sensitizers. This review discusses possible directions and promising strategies for future research and development of novel insulin sensitizers and describes the potential targets of these agents. Direct PPARγ agonists, selective PPARγ modulators (sPPARγMs), PPARγ-sparing compounds (including ligands of the mitochondrial target of TZDs), agents that target the downstream effectors of PPARγ, along with agents, such as heat shock protein (HSP) inducers, 5′-adenosine monophosphate-activated protein kinase (AMPK) activators, 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) selective inhibitors, biguanides, and chloroquines, which may be safer than traditional TZDs, have been described. This minireview thus aims to provide fresh perspectives for the development of a new generation of safe insulin sensitizers

Effect of amber powder on endometrial ultrastructure and MAPK pathway in endometriosis model rats

Purpose: To explore the therapeutic role of amber powder in endometriosis by investigating its effect on endometrial ultrastructure, ERK1/2, p38MAPK, and NF-κB mRNA pathways and CSRC/EFR/ERK1/2 proteins. Methods: Sprague Dawley (SD) rats were randomly divided into blank group, disease model group (untreated), amber powder high-dose group, amber powder medium-dose group, amber powder lowdose group and danazol group. Morphological changes in endometrial cells were studied using transmission electron microscopy. The expression of ERK1/2, p38MAPK, and NF-κB mRNA in endometrial tissues of each group was determined using quantitative real-time polymerase chain reaction (qRT-PCR). Immunohistochemistry was utilized for the measurement of C-SRC/EFR/ERK1/2 pathway protein expression. Results: The endometriosis rats treated with a high-, medium- and low-dose amber powder showed a decrease in the volume of ectopic lesions, compared with the untreated disease model group. The expressions of ERK1/2, p38MAPK, NF-κB mRNA, and C-SRC/EFR/ERK1/2 protein were higher in the eutopic and ectopic endometrial tissues in untreated disease group than those in normal control group. Moreover, treatment of endometriosis rats with amber powder revealed a reduction in the expressions of ERK1/2, p38MAPK, NF-κB mRNA and C-SRC/EFR/ERK1/2 proteins in eutopic and ectopic endometrium tissues. Conclusion: Amber powder reduces ectopic lesions and slows down the development of endometriosis, probably via inhibition of MAPK pathway genes in eutopic and ectopic endometrial tissues

Performance of artificial intelligence in predicting the prognossis of severe COVID-19: a systematic review and meta-analysis

BackgroundCOVID-19-induced pneumonia has become a persistent health concern, with severe cases posing a significant threat to patient lives. However, the potential of artificial intelligence (AI) in assisting physicians in predicting the prognosis of severe COVID-19 patients remains unclear.MethodsTo obtain relevant studies, two researchers conducted a comprehensive search of the PubMed, Web of Science, and Embase databases, including all studies published up to October 31, 2023, that utilized AI to predict mortality rates in severe COVID-19 patients. The PROBAST 2019 tool was employed to assess the potential bias in the included studies, and Stata 16 was used for meta-analysis, publication bias assessment, and sensitivity analysis.ResultsA total of 19 studies, comprising 26 models, were included in the analysis. Among them, the models that incorporated both clinical and radiological data demonstrated the highest performance. These models achieved an overall sensitivity of 0.81 (0.64–0.91), specificity of 0.77 (0.71–0.82), and an overall area under the curve (AUC) of 0.88 (0.85–0.90). Subgroup analysis revealed notable findings. Studies conducted in developed countries exhibited significantly higher predictive specificity for both radiological and combined models (p < 0.05). Additionally, investigations involving non-intensive care unit patients demonstrated significantly greater predictive specificity (p < 0.001).ConclusionThe current evidence suggests that artificial intelligence prediction models show promising performance in predicting the prognosis of severe COVID-19 patients. However, due to variations in the suitability of different models for specific populations, it is not yet certain whether they can be fully applied in clinical practice. There is still room for improvement in their predictive capabilities, and future research and development efforts are needed.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/ with the Unique Identifier CRD42023431537

Franck-Condon Factors and Radiative Lifetime of the A^{2}\Pi_{1/2} - X^{2}\Sigma^{+} Transition of Ytterbium Monoflouride, YbF

The fluorescence spectrum resulting from laser excitation of the A^{2}\Pi_{1/2} - X^{2}\Sigma^{+} (0,0) band of ytterbium monofluoride, YbF, has been recorded and analyzed to determine the Franck-Condon factors. The measured values are compared with those predicted from Rydberg-Klein-Rees (RKR) potential energy curves. From the fluorescence decay curve the radiative lifetime of the A^{2}\Pi_{1/2} state is measured to be 28\pm2 ns, and the corresponding transition dipole moment is 4.39\pm0.16 D. The implications for laser cooling YbF are discussed.Comment: 5 pages, 5 figure

SIRT1 Activation by Resveratrol Alleviates Cardiac Dysfunction via Mitochondrial Regulation in Diabetic Cardiomyopathy Mice

Background. Diabetic cardiomyopathy (DCM) is a major threat for diabetic patients. Silent information regulator 1 (SIRT1) has a regulatory effect on mitochondrial dynamics, which is associated with DCM pathological changes. Our study aims to investigate whether resveratrol, a SRIT1 activator, could exert a protective effect against DCM. Methods and Results. Cardiac-specific SIRT1 knockout (SIRT1KO) mice were generated using Cre-loxP system. SIRT1KO mice displayed symptoms of DCM, including cardiac hypertrophy and dysfunction, insulin resistance, and abnormal glucose metabolism. DCM and SIRT1KO hearts showed impaired mitochondrial biogenesis and function, while SIRT1 activation by resveratrol reversed this in DCM mice. High glucose caused increased apoptosis, impaired mitochondrial biogenesis, and function in cardiomyocytes, which was alleviated by resveratrol. SIRT1 deletion by both SIRT1KO and shRNA abolished the beneficial effects of resveratrol. Furthermore, the function of SIRT1 is mediated via the deacetylation effect on peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), thus inducing increased expression of nuclear respiratory factor 1 (NRF-1), NRF-2, estrogen-related receptor-α (ERR-α), and mitochondrial transcription factor A (TFAM). Conclusions. Cardiac deletion of SIRT1 caused phenotypes resembling DCM. Activation of SIRT1 by resveratrol ameliorated cardiac injuries in DCM through PGC-1α-mediated mitochondrial regulation. Collectively, SIRT1 may serve as a potential therapeutic target for DCM

Manganese oxide electrode with excellent electrochemical performance for sodium ion batteries by pre-intercalation of K and Na ions

Materials with a layered structure have attracted tremendous attention because of their unique properties. The ultrathin nanosheet structure can result in extremely rapid intercalation/de-intercalation of Na ions in the charge-discharge progress. Herein, we report a manganese oxide with pre-intercalated K and Na ions and having flower-like ultrathin layered structure, which was synthesized by a facile but efficient hydrothermal method under mild condition. The pre-intercalation of Na and K ions facilitates the access of electrolyte ions and shortens the ion diffusion pathways. The layered manganese oxide shows ultrahigh specific capacity when it is used as cathode material for sodium-ion batteries. It also exhibits excellent stability and reversibility. It was found that the amount of intercalated Na ions is approximately 71% of the total charge. The prominent electrochemical performance of the manganese oxide demonstrates the importance of design and synthesis of pre-intercalated ultrathin layered materials

Rapid determination of 103 common veterinary drug residues in milk and dairy products by ultra performance liquid chromatography tandem mass spectrometry

A multi-residue method has been developed for the identification and quantification of 103 common veterinary drug residues in milk and dairy Products. This method was based on QuEChERS with dispersive solid-phase where C18 sorbent and anhydrous sodium sulfate were used to sample purification. After evaporation and reconstitution, the samples were analyzed by ultra-performance liquid chromatography-tandem mass spectrometry. The mean recovery results were all higher than 60% except ampicillin, pipemidic acid, enoxacin, and estriol, and the relative standard deviation was <20.0%. The limit of quantification ranged between 0.1 and 5 μg/kg for milk and between 0.5 and 25 μg/kg for milk powder. It was successfully used to detect residues of veterinary drug in real samples. This study proposes a simple and fast analytical method for monitoring multi-class veterinary drug residues to ensure food safety