CK1α protects cardiomyocytes in sepsis-induced myocardial depression by repressing the interaction of ATG5 with myD88/NF-kappaB signaling

Purpose: To explore the effects of casein kinase 1α (CK1α) on cardiomyocytes in sepsis-induced myocardial depression.Methods: Colorectal ligation puncture (CLP) surgery was performed for the establishment of the mouse model. Total RNAs of the lungs, kidneys, liver tissues and alveolar macrophages were extracted using TRIzol™ reagent, while gene expression analysis was performed by quantitative polymerase chain reaction (qPCR) following reverse transcription. Western blot was employed to evaluate protein expression, and echocardiography was conducted to assess cardiac function. Immunofluorescent assay was performed to determine the expression of p-FOXO3a in primary cardiomyocytes.Results: Inhibition of CK1α impaired autophagy influx, and significantly increased inflammatory cytokines in H9C2 cells after lipopolysaccharide (LPS) treatment (p < 0.05). Moreover, aberrant activation of the Toll-like receptor 4(TLR4)/myD88/NF-kappaB pathway was observed in the H9C2 cell line after LPS treatment (p < 0.05). Immunoprecipitation analysis revealed an interaction between MyD88 and autophagy-related gene 5 (Atg5), and cardiac dysfunction in mice intravenously injectedwith an adenoviral vector containing shRNA (casein kinase 1 α) CSNK1A1 was suppressed (p < 0.05). In contrast, overexpression of CK1α remarkably improved cardiac systolic function (p < 0.05), the expression of inflammatory cytokines was repressed, and autophagy was enhanced in the hearts of mice with the specific overexpression of CSNK1A1 in cardiomyocytes (p < 0.05). In Atg5-deficient mice pretreated with DC661, the protective effect of adenoviral vector containing CK1α overexpression was eliminated.Conclusion: CK1α protects cardiomyocytes during sepsis after the inhibition of TLR/MyD88/NF-kappaBpathway via interaction of Atg5 with MyD88. The results of the current study may provide new insights into the treatment of sepsis-induced myocardial depression

Rethinking Learning Rate Tuning in the Era of Large Language Models

Large Language Models (LLMs) represent the recent success of deep learning in achieving remarkable human-like predictive performance. It has become a mainstream strategy to leverage fine-tuning to adapt LLMs for various real-world applications due to the prohibitive expenses associated with LLM training. The learning rate is one of the most important hyperparameters in LLM fine-tuning with direct impacts on both fine-tuning efficiency and fine-tuned LLM quality. Existing learning rate policies are primarily designed for training traditional deep neural networks (DNNs), which may not work well for LLM fine-tuning. We reassess the research challenges and opportunities of learning rate tuning in the coming era of Large Language Models. This paper makes three original contributions. First, we revisit existing learning rate policies to analyze the critical challenges of learning rate tuning in the era of LLMs. Second, we present LRBench++ to benchmark learning rate policies and facilitate learning rate tuning for both traditional DNNs and LLMs. Third, our experimental analysis with LRBench++ demonstrates the key differences between LLM fine-tuning and traditional DNN training and validates our analysis

Intrinsic Lithiophilicity of Li–Garnet Electrolytes Enabling High‐Rate Lithium Cycling

Solid‐state lithium batteries are widely considered as next‐generation lithium‐ion battery technology due to the potential advantages in safety and performance. Among the various solid electrolyte materials, Li–garnet electrolytes are promising due to their high ionic conductivity and good chemical and electrochemical stabilities. However, the high electrode/electrolyte interfacial impedance is one of the major challenges. Moreover, short circuiting caused by lithium dendrite formation is reported when using Li–garnet electrolytes. Here, it is demonstrated that Li–garnet electrolytes wet well with lithium metal by removing the intrinsic impurity layer on the surface of the lithium metal. The Li/garnet interfacial impedance is determined to be 6.95 Ω cm2 at room temperature. Lithium symmetric cells based on the Li–garnet electrolytes are cycled at room temperature for 950 h and current density as high as 13.3 mA cm−2 without showing signs of short circuiting. Experimental and computational results reveal that it is the surface oxide layer on the lithium metal together with the garnet surface that majorly determines the Li/garnet interfacial property. These findings suggest that removing the superficial impurity layer on the lithium metal can enhance the wettability, which may impact the manufacturing process of future high energy density garnet‐based solid‐state lithium batteries.By removing the impurity layer on the surface of the lithium metal, Li–garnet electrolytes are demonstrated to well wet the lithium metal, rendering a Li/garnet interfacial impedance of 6.95 Ω cm2, stable galvanostatic cycling for 950 h, and a current density as high as 13.3 mA cm−2 without showing any sign of short circuiting at room temperature.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154451/1/adfm201906189-sup-0001-SuppMat.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154451/2/adfm201906189.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154451/3/adfm201906189_am.pd

A Statistics-Based Study on Wood Presentation of Modern Wood Building Facades

Wood presentation of modern wood building facades relating to the expression of the essential characteristics of architecture, utilization efficiency of wood and acceptance of architectural image,etc. However, relevant studies are obviously insufficient. This paper makes a statistical analysis of outstanding wood structure space cases which be selected, tries to reveal the expression rule of major timber application variables of wood coverage, materials collocation, wood form and wood color under the limitation of the main influencing factors of building function, building form and building scale.The purpose of this study is to explore the wood presentation rule of modern wood building Facades under the influence of building factors

Detection of Flare-induced Plasma Flows in the Corona of EV Lac with X-ray Spectroscopy

Stellar flares are characterized by sudden enhancement of electromagnetic radiation from the atmospheres of stars. Compared to their solar counterparts, our knowledge on the coronal plasma dynamics of stellar flares and their connection to coronal mass ejections (CMEs) remains very limited. With time-resolved high-resolution spectroscopic observations from the \textit{Chandra} X-ray observatory, we detected noticeable coronal plasma flows during several stellar flares on a nearby dMe star EV Lac. In the observed spectra of O~{\sc{viii}} (3 MK), Fe~{\sc{xvii}} (6 MK), Mg~{\sc{xii}} (10 MK), and Si~{\sc{xiv}} (16 MK) lines, these flare-induced upflows/downflows appear as significant Doppler shifts of several tens to \speed{130}, and the upflow velocity generally increases with temperature. Variable line ratios of the Si~{\sc{xiii}} triplet reveal that these plasma flows in most flares are accompanied by an increase of the coronal plasma density and temperature. We interpret these results as X-ray evidences for chromospheric evaporation on EV Lac. In two successive flares, the plasma flow pattern and a sharp increase of the measured coronal density are highly suggestive of explosive evaporation. The transition from redshifts to blueshifts in such an explosive evaporation occurs at a temperature of at least 10 MK, much higher than that observed in solar flares ($\sim$1 MK). However, in one flare the cool and warm upflows appear to be accompanied by a decreasing plasma density, which might be explained by a stellar filament/prominence eruption coupled to this flare. These results provide important clues to understand the coronal plasma dynamics during flares on M dwarfs.Comment: accepted by Ap

Algorithmic discrimination: examining its types and regulatory measures with emphasis on US legal practices

IntroductionAlgorithmic decision-making systems are widely used in various sectors, including criminal justice, employment, and education. While these systems are celebrated for their potential to enhance efficiency and objectivity, they also pose risks of perpetuating and amplifying societal biases and discrimination. This paper aims to provide an indepth analysis of the types of algorithmic discrimination, exploring both the challenges and potential solutions.MethodsThe methodology includes a systematic literature review, analysis of legal documents, and comparative case studies across different geographic regions and sectors. This multifaceted approach allows for a thorough exploration of the complexity of algorithmic bias and its regulation.ResultsWe identify five primary types of algorithmic bias: bias by algorithmic agents, discrimination based on feature selection, proxy discrimination, disparate impact, and targeted advertising. The analysis of the U.S. legal and regulatory framework reveals a landscape of principled regulations, preventive controls, consequential liability, self-regulation, and heteronomy regulation. A comparative perspective is also provided by examining the status of algorithmic fairness in the EU, Canada, Australia, and Asia.ConclusionReal-world impacts are demonstrated through case studies focusing on criminal risk assessments and hiring algorithms, illustrating the tangible effects of algorithmic discrimination. The paper concludes with recommendations for interdisciplinary research, proactive policy development, public awareness, and ongoing monitoring to promote fairness and accountability in algorithmic decision-making. As the use of AI and automated systems expands globally, this work highlights the importance of developing comprehensive, adaptive approaches to combat algorithmic discrimination and ensure the socially responsible deployment of these powerful technologies

Systematic review and network meta-analysis of pre-emptive embolization of the aneurysm sac side branches and aneurysm sac coil embolization to improve the outcomes of endovascular aneurysm repair

ObjectivePrevious reports have revealed a high incidence of type II endoleak (T2EL) after endovascular aneurysm repair (EVAR). The incidence of T2EL after EVAR is reduced by pre-emptive embolization of aneurysm sac side branches (ASSB) and aneurysm sac coil embolization (ASCE). This study aimed to investigate whether different preventive interventions for T2EL were correlated with suppression of aneurysm sac expansion and reduction of the re-intervention rate.MethodsThe PubMed, Web of Science, MEDLINE and Embase databases, and conference proceedings were searched to identify articles on EVAR with or without embolization. The study was developed in line with the Participants, Interventions, Comparisons, Outcomes, and Study design principles and was conducted and reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines. We used network meta-analysis based on multivariate random-effects meta-analysis to indirectly compare outcomes of different strategies for embolization during EVAR.ResultsA total of 31 studies met all inclusion criteria and were included in the qualitative and quantitative syntheses. The included studies were published between 2001 and 2022 and analyzed a total of 18,542 patients, including 1,882 patients who received prophylactic embolization treatment during EVAR (experimental group) and 16,660 who did not receive prophylactic embolization during EVAR (control group). The effect of pre-emptive embolization of the inferior mesenteric artery (IMA) (IMA-ASSB) in preventing T2EL was similar (relative risk [RR] 1.01, 95% confidence interval [CI] 0.38–2.63) to the effects of non-selective embolization of ASSB (NS-ASSB) and ASCE (RR 0.88, 95% CI 0.40–1.96). IMA-ASSB showed a better clinical effect in suppressing the aneurysm sac expansion (RR 0.27, 95% CI 0.09–2.25 compared with NS-ASSB; RR 0.93, 95% CI 0.16–5.56 compared with ASCE) and reducing the re-intervention rate (RR 0.34, 95% CI 0.08–1.53 compared with NS-ASSB; RR 0.66, 95% CI 0.19–2.22 compared with ASCE). All prophylactic embolization strategies improved the clinical outcomes of EVAR.ConclusionProphylactic embolization during EVAR effectively prevents T2EL, suppresses the aneurysm sac expansion, and reduces the re-intervention rate. IMA embolization demonstrated benefits in achieving long-term aneurysm sac stability and lowering the risk of secondary surgery. NS-ASSB more effectively reduces the incidence of T2EL, while IMA embolization alone or in combination with ASCE enhances the clinical benefits of EVAR. In addition, as network meta-analysis is still an indirect method based on a refinement of existing data, more studies and evidence are still needed in the future to establish more credible conclusions

Digital intervention in improving the outcomes of mental health among LGBTQ+ youth: a systematic review

LGBTQ+ youth experience mental health disparities and higher rates of mental disorders due to barriers to accessing care, including insufficient services and the anticipated stigma of revealing their identities. This systematic review incorporated 15 empirical studies on digital interventions’ impact on LGBTQ+ youth mental health, examining their potential to address these inequities. This study innovatively categorized existing digital interventions into four streams: Structured Formal (telehealth, online programs), Structured Informal (serious games), Unstructured Formal (mobile applications), and Unstructured Informal (social media). We found that S&F and U&F effectively reduced symptoms. U&F showed potential but required enhancement, while U&I fostered resilience but posed risks. Further integration of emerging technologies like virtual reality may strengthen these interventions. This review identifies the characteristics of effective digital health interventions and evaluates the overall potential of digital technologies in improving LGBTQ+ youth mental health, uniquely contributing insights on digital solutions advancing LGBTQ+ youth mental healthcare

Highly sensitive and selective CO sensor using a 2.33 μm diode laser and wavelength modulation spectroscopy

A ppm-level CO sensor based on a 2f wavelength modulation spectroscopy (2f-WMS) technique was developed for the application of SF6 decomposition analysis in an electric power system. A detailed investigation of the optimum target line selection was carried out to avoid spectral interference from high purity SF6 in a wide wavelength range. A diode laser emitting at 2.33 μm and a 14.5-m multipass gas cell (MGC) was employed to target the R(6) line of the CO first overtone band and increase the optical path, respectively, thus resulting in a minimum detection sensitivity of 1 ppm. A Levenberg-Marquardt nonlinear least-squares fit algorithm makes full use of the information from all data points of the 2f spectrum and as a result, a measurement precision of ~40 ppb was achieved with a data update rate of 0.6 s. The sensor performance was also evaluated in terms of the gas flow rate, stability, and linearity. The results showed that the best operating condition with a precision of 6 ppb can be achieved by increasing the gas flow rate to the value that matches the optimum averaging time of 48 s

Beat frequency quartz-enhanced photoacoustic spectroscopy for fast and calibration-free continuous trace-gas monitoring

Quartz-enhanced photoacoustic spectroscopy (QEPAS) is a sensitive gas detection technique which requires frequent calibration and has a long response time. Here we report beat frequency (BF) QEPAS that can be used for ultra-sensitive calibration-free trace-gas detection and fast spectral scan applications. The resonance frequency and Q-factor of the quartz tuning fork (QTF) as well as the trace-gas concentration can be obtained simultaneously by detecting the beat frequency signal generated when the transient response signal of the QTF is demodulated at its non-resonance frequency. Hence, BF-QEPAS avoids a calibration process and permits continuous monitoring of a targeted trace gas. Three semiconductor lasers were selected as the excitation source to verify the performance of the BF-QEPAS technique. The BF-QEPAS method is capable of measuring lower trace-gas concentration levels with shorter averaging times as compared to conventional PAS and QEPAS techniques and determines the electrical QTF parameters precisely