Complement factor I knockdown inhibits colon cancer development by affecting Wnt/ß-catenin/c-Myc signaling pathway and glycolysis.

BACKGROUND: Colon cancer (CC) occurrence and progression are considerably influenced by the tumor microenvironment. However, the exact underlying regulatory mechanisms remain unclear. AIM: To investigate immune infiltration-related differentially expressed genes (DEGs) in CC and specifically explored the role and potential molecular mechanisms of complement factor I (CFI). METHODS: Immune infiltration-associated DEGs were screened for CC using bioinformatics. Quantitative reverse transcription polymerase chain reaction was used to examine hub DEGs expression in the CC cell lines. Stable CFI-knockdown HT29 and HCT116 cell lines were constructed, and the diverse roles of CFI in vitro were assessed using CCK-8, 5-ethynyl-2'-deoxyuridine, wound healing, and transwell assays. Hematoxylin and eosin staining and immunohistochemistry staining were employed to evaluate the influence of CFI on the tumorigenesis of CC xenograft models constructed using BALB/c male nude mice. Key proteins associated with glycolysis and the Wnt pathway were measured using western blotting. RESULTS: Six key immune infiltration-related DEGs were screened, among which the expression of CFI, complement factor B, lymphoid enhancer binding factor 1, and SRY-related high-mobility-group box 4 was upregulated, whereas that of fatty acid-binding protein 1, and bone morphogenic protein-2 was downregulated. Furthermore, CFI could be used as a diagnostic biomarker for CC. Functionally, CFI silencing inhibited CC cell proliferation, migration, invasion, and tumor growth. Mechanistically, CFI knockdown downregulated the expression of key glycolysis-related proteins (glucose transporter type 1, hexokinase 2, lactate dehydrogenase A, and pyruvate kinase M2) and the Wnt pathway-related proteins (ß-catenin and c-Myc). Further investigation indicated that CFI knockdown inhibited glycolysis in CC by blocking the Wnt/ß-catenin/c-Myc pathway. CONCLUSION: The findings of the present study demonstrate that CFI plays a crucial role in CC development by influencing glycolysis and the Wnt/ß-catenin/c-Myc pathway, indicating that it could serve as a promising target for therapeutic intervention in CC.

Serum C-reactive protein to albumin ratio as a potential risk indicator of pneumonia caused by Chlamydia psittaci: a multicenter retrospective study.

Introduction: The aim of the study was to describe psittacosis pneumonia and to assess the predictive value of the C-reactive protein/albumin ratio in psittacosis pneumonia for severity. Methods: Data on psittacosis pneumonia cases diagnosed using metagenomic sequencing were collected from three hospitals in Shanghai, China from Oct. 2019 to Oct. 2022. Serum levels of C-reactive protein and albumin were measured and the C-reactive protein to albumin ratio (CAR) was calculated. Spearman's correlation analysis, ordered logistic regression analysis, and receiver operating characteristic curve analysis were conducted to examine the correlation and predictive ability of the three indicators on the severity of the disease. Results: A total of 27 patients with psittacosis pneumonia were enrolled, with an average age of 62 years and 70.4% being male. 44.4% of patients had a clear history of contact with poultry or birds. The predominant symptom was fever (100%). Patients treated in the respiratory intensive care unit (RICU) had a higher likelihood of experiencing wheezing (88.9% versus 33.3%, P=0.013) and chest tightness (88.9% vs. 33.3%, P=0.013) than those in the general ward (Non-RICU). The proportion of patients with pleural effusion was significantly higher in the RICU compared to the Non-RICU (88.9% vs. 38.9%, P=0.019). The RICU group had a significantly higher CAR than the Non-RICU group (9.41 vs. 4.05, P=0.017). This result was accompanied by higher intubation and ventilator support (33.3% vs. 0.0%, P=0.029), higher PCT and CRP levels and lower albumin and PaCO2 levels in the RICU than in the Non-RICU. Logistic regression analysis indicated that CAR (OR 1.49; 95% CI 1.07-2.06, P=0.017) was risk factor for prolonged hospitalization (> 14 days). Discussion: Elevated serum CAR levels were found to be associated with a greater risk of severe psittacosis pneumonia. Consequently, it may serve as an uncomplicated and useful diagnostic tool for clinicians to promptly and precisely ascertain the severity of psittacosis pneumonia, ultimately aiding them in devising the most optimal therapeutic plan.

Optimizing Fatigue Performance in Gradient Structural Steels by Manipulating the Grain Size Gradient Rate.

As a new type of high-performance material, gradient structural steel is widely used in engineering fields due to its unique microstructure and excellent mechanical properties. For the prevalent fatigue failure problem, the rate of change in the local grain size gradients along the structure (referred to as the gradient rate) is a key parameter in the design of gradient structures, which significantly affects the fatigue performance of gradient structural steel. In this study, a new method of 'Voronoi primary + secondary modeling' is adopted to successfully establish three typical high-strength steel models corresponding to the convex-, linear-, and concave-type gradient rates for gradient structures, focusing on the stress-strain response and crack propagation in structural steel with different gradient rates under cyclic loading. It was found that the concave gradient rate structural model is dominated by finer grains with larger volume fraction, which is conducive to hindering fatigue crack propagation and has the longest fatigue life, which is 16.16% longer than that of the linear gradient rate structure and 23.66% longer than that of the convex gradient rate structure. The simulation results in this study are consistent with the relevant experimental phenomena. Therefore, when regulating the gradient rate, priority should be given to increasing the volume fraction of fine grains and designing a gradient rate structure dominated by fine grains to improve the fatigue life of the material. This study presents a new strategy for designing engineering materials with better service performance.

Chemical Compositions before and after Lactic Acid Fermentation of Isoflavone-Enriched Soybean Leaves and Their Anti-Obesity and Gut Microbiota Distribution Effects.

In this study, we prepared fermented products of isoflavone-enriched soybean leaves (IESLs) and analyzed their nutrients, isoflavones, anti-obesity efficacy, and effects on gut microbiota. Fermented IESLs (FIESLs) were found to be rich in nutrients, especially lauric acid, oleic acid, and linoleic acid. In addition, the concentrations of most essential free amino acids were increased compared to those of IESLs. The contents of bioactive compounds, such as total phenolic, total flavonoid, daidzein, and genistein, significantly increased as well. In addition, FIESLs administration in a high-fat diet (HFD) animal model improved the final body weight, epididymal fat, total lipid, triglyceride, total cholesterol, blood glucose, and leptin levels, as well as reverting microbiota dysbiosis. In conclusion, these findings indicate that FIESLs have the potential to inhibit obesity caused by HFDs and serve as a modulator of gut microbiota, offering the prevention of diet-induced gut dysbiosis and metabolite diseases associated with obesity.

Self-Illuminating Nanoagonist Simultaneously Induces Dual Cell Death Pathways via Death Receptor Clustering for Cancer Therapy.

Inducing death receptor 5 (DR5) clustering holds particular promise in tumor-specific therapeutics because it could trigger an apoptotic cascade in cancerous cells. Herein, we present a tumor microenvironment H2O2-responsive self-illuminating nanoagonist, which could induce dual tumor cell death pathways through enhancing DR5 clustering. By conjugating DR5 ligand peptides onto the surfaces of self-illuminating nanoparticles with cross-linking capacity, this strategy not only provides scaffolds for ligands to bind receptors but also cross-links them through photo-cross-linking. This strategy allows for efficient activation of DR5 downstream signaling, initiating the extrinsic apoptosis pathway and immunogenic cell death of tumor cells, and contributes to improved tumor-specific immune responses, resulting in enhanced antitumor efficacy and minimized systemic adverse effects.

Transient spectroscopic insights into nitroindole's T1 state: Elucidating its intermediates and unique photochemical properties.

Indoles are notable for their distinct photophysical and photochemical properties, making them useful indicators in biological systems and promising candidates for a variety of pharmaceutical applications. While some indoles exhibit room temperature phosphorescence, such a phenomenon has not been observed in nitroindoles. Typically, adding of a nitro group into aromatic compounds promotes ultrafast intersystem crossing and increases the formation quantum yield of the lowest excited triplet (T1). Therefore, understanding the reactivity of nitroindoles' T1 states is imperative. This study investigated the physical properties and chemical reactivities of the T1 state of 6-nitroindole (3HN-6NO2) in both polar aprotic and protic solvents, using transient absorption spectroscopy. Our results demonstrate the basicity and acidity of 3HN-6NO2, emphasizing its potential for protonation and dissociation in mildly acidic and basic conditions, respectively. Furthermore, 3HN-6NO2 has a high oxidizing capacity, participating in electron transfer reactions and proton-coupled electron transfer to produce radicals. Interestingly, in protic solvents like alcohols, 3HN-6NO2 dissociates at the -NH group and forms N-H…O hydrogen-bonded complexes with the nitro group. By identifying transient absorption spectra of intermediates and quantifying kinetic reaction rate constants, we illuminate the unique properties of the T1 state nitroindoles, enriching our understanding of their photophysical and photochemical behaviors. The results of this study have significant implications for their potential application in both biological systems and materials science.

Understanding the electrochemical properties of Mg-doped Li2MnO3: first-principles calculations.

Non-transition metal doping, especially for Mg, has been gradually employed to optimize the electrochemical performance of Li-rich cathode material Li2MnO3. However, the effects of Mg doping on the electrochemical behavior of Li2MnO3 have not been studied extensively. In this work, we investigate the effect of Mg doping at both the 2b (in the Li/Mn mixed layer) and 4h (in the Li layer) Li sites on the electrochemical properties of Li2MnO3 through first-principles calculations and ab initio molecular dynamics simulations. The local lattice structure, electronic density of states, Bader charge, delithiation voltage, lattice oxygen stability and Li diffusion kinetics are examined. Electronic structure analysis shows that Mg can activate the electrochemical activity of surrounding Mn by charge transfer, making Mn participate in charge compensation at the initial delithiation stage. Mg doping can also cause an increase in the average oxygen vacancy formation energy and hence depress the oxygen release during the delithiation process. Molecular dynamics simulations show that the diffusion kinetics of Li ions in Mg2b-Li2MnO3 is enhanced with respect to the undoped one, whereas Mg doped at the 4h site cannot improve the diffusion kinetics of Li ions. Further studies found that Mg doped at the 2b site results in a decrease in the energy barrier for the intra-layer diffusion and an increase in the energy barrier for the inter-layer diffusion of the nearby Li vacancies.

Diabetes-related amputations in Germany: analysis of time trend from 2015 to 2022 and differences by area-level socioeconomic deprivation.

Background: Diabetes-related amputations reduce health-related quality of life and are an indicator of the quality of care of diabetes. Methods: Population-based age-standardized rates for diabetes-related cases of major and minor amputation were calculated and reported for the years 2015 - 2022 using the Diagnosis-related groups statistics. For 2022 these rates were also reported according to area-level socioeconomic deprivation. Results: Diabetes-related major amputations decreased from 6.8 to 5.2 per 100,000 residents in women and from 18.6 to 17.5 per 100,000 residents in men between 2015 and 2022. In 2021 and 2022, there was no further decrease in men compared to the previous year. Diabetes-related minor amputations decreased in women between 2015 and 2022, but increased in men. Amputation rates were higher in regions with high deprivation than in regions with low deprivation. Conclusions: Diabetes care should consider socioeconomic differences into account. The monitoring of the trends in amputations needs to be continued.

A Possibilistic Formulation of Autonomous Search for Targets.

Autonomous search is an ongoing cycle of sensing, statistical estimation, and motion control with the objective to find and localise targets in a designated search area. Traditionally, the theoretical framework for autonomous search combines sequential Bayesian estimation with information theoretic motion control. This paper formulates autonomous search in the framework of possibility theory. Although the possibilistic formulation is slightly more involved than the traditional method, it provides a means for quantitative modelling and reasoning in the presence of epistemic uncertainty. This feature is demonstrated in the paper in the context of partially known probability of detection, expressed as an interval value. The paper presents an elegant Bayes-like solution to sequential estimation, with the reward function for motion control defined to take into account the epistemic uncertainty. The advantages of the proposed search algorithm are demonstrated by numerical simulations.

Preoperative prediction of perineural invasion of rectal cancer based on a magnetic resonance imaging radiomics model: A dual-center study.

BACKGROUND: Perineural invasion (PNI) has been used as an important pathological indicator and independent prognostic factor for patients with rectal cancer (RC). Preoperative prediction of PNI status is helpful for individualized treatment of RC. Recently, several radiomics studies have been used to predict the PNI status in RC, demonstrating a good predictive effect, but the results lacked generalizability. The preoperative prediction of PNI status is still challenging and needs further study. AIM: To establish and validate an optimal radiomics model for predicting PNI status preoperatively in RC patients. METHODS: This retrospective study enrolled 244 postoperative patients with pathologically confirmed RC from two independent centers. The patients underwent pre-operative high-resolution magnetic resonance imaging (MRI) between May 2019 and August 2022. Quantitative radiomics features were extracted and selected from oblique axial T2-weighted imaging (T2WI) and contrast-enhanced T1WI (T1CE) sequences. The radiomics signatures were constructed using logistic regression analysis and the predictive potential of various sequences was compared (T2WI, T1CE and T2WI + T1CE fusion sequences). A clinical-radiomics (CR) model was established by combining the radiomics features and clinical risk factors. The internal and external validation groups were used to validate the proposed models. The area under the receiver operating characteristic curve (AUC), DeLong test, net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA) were used to evaluate the model performance. RESULTS: Among the radiomics models, the T2WI + T1CE fusion sequences model showed the best predictive performance, in the training and internal validation groups, the AUCs of the fusion sequence model were 0.839 [95% confidence interval (CI): 0.757-0.921] and 0.787 (95%CI: 0.650-0.923), which were higher than those of the T2WI and T1CE sequence models. The CR model constructed by combining clinical risk factors had the best predictive performance. In the training and internal and external validation groups, the AUCs of the CR model were 0.889 (95%CI: 0.824-0.954), 0.889 (95%CI: 0.803-0.976) and 0.894 (95%CI: 0.814-0.974). Delong test, NRI, and IDI showed that the CR model had significant differences from other models (P < 0.05). Calibration curves demonstrated good agreement, and DCA revealed significant benefits of the CR model. CONCLUSION: The CR model based on preoperative MRI radiomics features and clinical risk factors can preoperatively predict the PNI status of RC noninvasively, which facilitates individualized treatment of RC patients.

Preparation and epitope analysis of monoclonal antibodies against African swine fever virus DP96R protein.

BACKGROUND: Many proteins of African swine fever virus (ASFV, such as p72, p54, p30, CD2v, K205R) have been successfully expressed and characterized. However, there are few reports on the DP96R protein of ASFV, which is the virulence protein of ASFV and plays an important role in the process of host infection and invasion of ASFV. RESULTS: Firstly, the prokaryotic expression vector of DP96R gene was constructed, the prokaryotic system was used to induce the expression of DP96R protein, and monoclonal antibody was prepared by immunizing mice. Four monoclonal cells of DP96R protein were obtained by three ELISA screening and two sub-cloning; the titer of ascites antibody was up to 1:500,000, and the monoclonal antibody could specifically recognize DP96R protein. Finally, the subtypes of the four strains of monoclonal antibodies were identified and the minimum epitopes recognized by them were determined. CONCLUSION: Monoclonal antibody against ASFV DP96R protein was successfully prepared and identified, which lays a foundation for further exploration of the structure and function of DP96R protein and ASFV diagnostic technology.

[Subjective health in the early phase of the COVID-19 pandemic-a comparison of socio-demographic groups and pandemic-related risk factors]. / Subjektive Gesundheit in der Frühphase der COVID-19-Pandemie ­ ein Vergleich von soziodemografischen Gruppen und pandemiebezogenen Risikofaktoren.

BACKGROUND: In the early stages of the COVID-19 pandemic in 2020, daily life was significantly restricted due to the containment measures of the initial lockdown while SARS-CoV­2 incidences remained relatively low. This study analyses socio-demographic and socio-economic groups in terms of changes in their subjective health during this phase. METHODS: Data from the Socio-Economic Panel (n = 14,856, March-July 2020) were used to estimate the relative frequency of self-reported good health, great worries about one's own health, and high life satisfaction of men and women stratified by age, education, income, migration history, pre-existing medical conditions, and high-risk occupation. The results were mutually adjusted using logistic regression, displayed on a monthly basis, and compared with the pre-pandemic period. RESULTS: Individuals of higher age, with lower education or income, and with pre-existing medical conditions reported positive health outcomes less frequently and worries more often. The differences between the subgroups remained largely stable compared to the pre-pandemic period. During the period of strongest restrictions due to infection-control measures, good health was reported less frequently by individuals with lower education or income compared to individuals with higher education or income. DISCUSSION: The impact of the early phase of the pandemic on subjective health and life satisfaction was low for the majority of the examined groups. Relative impairments were only identified for women in low socio-economic positions.

Examining the Alterations in Metabolite Constituents and Antioxidant Properties in Mountain-Cultivated Ginseng (Panax ginseng C.A. Meyer) Organs during a Two-Month Maturation Period.

The current research was the first to prove the existence of fluctuations in the metabolite constituents and antioxidant properties in different organs (leaves, stems, and roots) of the mountain-cultivated ginseng (MCG) plant during a two-month maturation period. Four metabolites, including fatty acids, amino acids, ginsenosides, and phenolic phytochemicals, exhibited considerable differences in organs and maturation times with the following order: leaves > stems > roots. The predominant metabolite contents were found in leaves, with fatty acid (1057.9 mg/100 g) on 31 May, amino acid (1989.2 mg/100 g) on 13 July, ginsenosides (88.7 mg/g) on 31 May, and phenolic phytochemical (638.3 µg/g) on 31 May. Interestingly, ginsenoside content in leaves were highest, with 84.8 → 88.7 → 82.2 → 78.3 mg/g. Specifically, ginsenosides Re, Rd, and F2 showed abundant content ranging from 19.1 to 16.9 mg/g, 8.5 to 14.8 mg/g, and 9.5 to 13.1 mg/g, respectively. Phenolic phytochemicals exhibited remarkable differences in organs compared to maturation periods, with the highest total phenolic content and total flavonoid content recorded at 9.48 GAE and 1.30 RE mg/g in leaves on 31 May. The antioxidant capacities on radical, FRAP, and DNA protection differed significantly, with leaves on 31 May exhibiting the highest values: 88.4% (DPPH), 89.5% (ABTS), 0.84 OD593 nm (FRAP) at 500 µg/mL, and 100% DNA protection at 50 µg/mL. Furthermore, principal cluster analysis revealed metabolite variability as follows: ginsenoside (83.3%) > amino acid (71.8%) > phenolic phytochemical (61.1%) > fatty acid (58.8%). A clustering heatmap highlighted significant changes in metabolite components under the maturation times for each organ. Our findings suggest that MCG leaves on 31 May may be a potential source for developing nutraceuticals, offering highly beneficial components and strong antioxidants.

CMOS Scaling for the 5 nm Node and Beyond: Device, Process and Technology.

After more than five decades, Moore's Law for transistors is approaching the end of the international technology roadmap of semiconductors (ITRS). The fate of complementary metal oxide semiconductor (CMOS) architecture has become increasingly unknown. In this era, 3D transistors in the form of gate-all-around (GAA) transistors are being considered as an excellent solution to scaling down beyond the 5 nm technology node, which solves the difficulties of carrier transport in the channel region which are mainly rooted in short channel effects (SCEs). In parallel to Moore, during the last two decades, transistors with a fully depleted SOI (FDSOI) design have also been processed for low-power electronics. Among all the possible designs, there are also tunneling field-effect transistors (TFETs), which offer very low power consumption and decent electrical characteristics. This review article presents new transistor designs, along with the integration of electronics and photonics, simulation methods, and continuation of CMOS process technology to the 5 nm technology node and beyond. The content highlights the innovative methods, challenges, and difficulties in device processing and design, as well as how to apply suitable metrology techniques as a tool to find out the imperfections and lattice distortions, strain status, and composition in the device structures.

Probing Chemical Equilibrium in Frozen Sodium Phosphate Buffer Solution by 31P Solid-State NMR.

Phosphate buffers are crucial for cryopreservative stability in pharmaceuticals, food processing, biomedical sciences, and biology. However, their freeze concentrates lack quantitative characterization, especially regarding the physicochemical properties of phosphate salt species in equilibrium at subzero temperatures. This study employs 31P solid-state NMR (ssNMR) to analyze frozen sodium phosphate (NaP) solutions, providing insights into phase composition, ionic strength, and pH. For the first time, we have directly quantified phosphate species in frozen NaP buffer, including crystallized disodium phosphate dodecahydrate (Na2HPO4·12H2O) content and the concentrations of H2PO4- and HPO42- in the freeze concentrate. This enabled the calculation of the pH as well as the ionic strength in the freeze concentrate. Trehalose effectively mitigated pH shifts in buffer solutions by preventing the selective crystallization of salt, a spectroscopic phenomenon not previously observed experimentally.

Investigating the impact of various sorghum types on the key aroma compounds of Sichuan Xiaoqu Baijiu through application of the sensomics approach.

The aroma of Sichuan Xiaoqu Baijiu (SXB) greatly benefits from the use of sorghum as its primary brewing ingredient. Nevertheless, the impact of different sorghum variety on the primary aroma compounds of SXB has not been thoroughly investigated. Gas chromatography-mass spectrometry (GC-MS) in conjunction with headspace solid phase microextraction (HS-SPME) and liquid-liquid extraction (LLE) were employed in this investigation. Using 5 sorghum varieties as raw materials, five different types of SXB were analysed for their aroma compounds using GC-MS, GC-O, AEDA, aroma recombination, and aroma omission. Key aroma compounds of SXB were successfully identified as ethyl acetate, ethyl 2-methylbutyrate, isoamyl acetate, ethyl hexanoate, ethyl heptanoate, ethyl lactate, ethyl octanoate, ethyl decanoate, phenylethyl acetate, ethyl laurate, ethyl palmitate, isoamyl alcohol, phenylethanol, 1,1-diethoxyethane, 3-hydroxy-2- butanone, furfural, and glacial acetic acid. Glacial acetic acid, ethyl acetate, ethyl lactate, phenylethyl acetate, acetoin, phenylethanol, and ethyl caproate were found to be the seven major aroma compounds that had the biggest impact on the variations of the five SXB aroma properties, according to partial least squares regression (PLS-R) analysis. The collinear network analysis also revealed that the largest positive correlation weight was discovered between the protein and furfural content, tannin content and cereal-like aroma profile while the highest negative correlation weight was found between the moisture and acetoin content. This study is a valuable resource for understanding how raw materials control the directional regulation of the sensory quality of the SXB liquor body.

Quantification of Residual Water in Pharmaceutical Frozen Solutions Via 1H Solid-State NMR.

Freezing is essential for the stability of biological drug substances and products, particularly in frozen solution formulations and during the primary drying of lyophilized preparations. However, the unfrozen segment within the frozen matrix can alter solute concentration, ionic strength, and stabilizer crystallization, posing risks of increased biophysical instability and faster chemical degradation. While quantifying the unfrozen water content is important for designing stable biopharmaceuticals, there is a lack of analytical techniques for in situ quantitative measurements. In this study, we introduce a 1H magic angle spinning NMR technique to identify the freezing point (Tice) and quantify mobile water content in frozen biologics, applying this method to analyze the freezing of a commercial high-concentration drug product, Dupixent®. Our results demonstrate that water freezing is influenced by buffer salt properties and formulation composition, including the presence of sugar cryoprotectants and protein concentration. Additionally, the 1H chemical shift can probe pH in the unfrozen phase, potentially predicting the microenvironmental acidity in the frozen state. Our proposed methodology provides fresh insights into the analysis of freeze-concentrated solutions, enhancing our understanding of the stability of frozen and lyophilized biopharmaceuticals.

Loss of TRIM29 mitigates viral myocarditis by attenuating PERK-driven ER stress response in male mice.

Viral myocarditis, an inflammatory disease of the myocardium, is a significant cause of sudden death in children and young adults. The current coronavirus disease 19 pandemic emphasizes the need to understand the pathogenesis mechanisms and potential treatment strategies for viral myocarditis. Here, we found that TRIM29 was highly induced by cardiotropic viruses and promoted protein kinase RNA-like endoplasmic reticulum kinase (PERK)-mediated endoplasmic reticulum (ER) stress, apoptosis, and reactive oxygen species (ROS) responses that promote viral replication in cardiomyocytes in vitro. TRIM29 deficiency protected mice from viral myocarditis by promoting cardiac antiviral functions and reducing PERK-mediated inflammation and immunosuppressive monocytic myeloid-derived suppressor cells (mMDSC) in vivo. Mechanistically, TRIM29 interacted with PERK to promote SUMOylation of PERK to maintain its stability, thereby promoting PERK-mediated signaling pathways. Finally, we demonstrated that the PERK inhibitor GSK2656157 mitigated viral myocarditis by disrupting the TRIM29-PERK connection, thereby bolstering cardiac function, enhancing cardiac antiviral responses, and curbing inflammation and immunosuppressive mMDSC in vivo. Our findings offer insight into how cardiotropic viruses exploit TRIM29-regulated PERK signaling pathways to instigate viral myocarditis, suggesting that targeting the TRIM29-PERK axis could mitigate disease severity.

Linewidth compression of a single longitudinal mode ytterbium-doped fiber laser based on femtosecond laser fabricated fiber Bragg gratings.

We demonstrate a single longitudinal mode distributed Bragg reflection (DBR) fiber laser by directly fabricating fiber Bragg gratings (FBGs) on an ytterbium-doped fiber (YDF) using a femtosecond laser. A simple optical self-injection feedback method was used to effectively compress the linewidth and reduce relative intensity noise (RIN) of a single longitudinal mode DBR fiber laser. Further, we investigated the effect of self-injection feedback cavity length and reflectivity on linewidth compression and determined that the linewidth tends to decrease with the increase of the external cavity photon lifetime. By a self-injection feedback, the laser linewidth was compressed from 31.8 kHz to 1.4 kHz. Meanwhile, the relaxation oscillation peak from -103.2d B/H z at 1.51 MHz was suppressed to -122.3d B/H z at 0.16 MHz. This low-noise narrow linewidth single longitudinal mode fiber laser is expected to be a promising candidate for applications such as active detection of neutral atmosphere and distributed fiber sensing.

An Automated Deep Learning-Based Framework for Uptake Segmentation and Classification on PSMA PET/CT Imaging of Patients with Prostate Cancer.

Uptake segmentation and classification on PSMA PET/CT are important for automating whole-body tumor burden determinations. We developed and evaluated an automated deep learning (DL)-based framework that segments and classifies uptake on PSMA PET/CT. We identified 193 [18F] DCFPyL PET/CT scans of patients with biochemically recurrent prostate cancer from two institutions, including 137 [18F] DCFPyL PET/CT scans for training and internally testing, and 56 scans from another institution for external testing. Two radiologists segmented and labelled foci as suspicious or non-suspicious for malignancy. A DL-based segmentation was developed with two independent CNNs. An anatomical prior guidance was applied to make the DL framework focus on PSMA-avid lesions. Segmentation performance was evaluated by Dice, IoU, precision, and recall. Classification model was constructed with multi-modal decision fusion framework evaluated by accuracy, AUC, F1 score, precision, and recall. Automatic segmentation of suspicious lesions was improved under prior guidance, with mean Dice, IoU, precision, and recall of 0.700, 0.566, 0.809, and 0.660 on the internal test set and 0.680, 0.548, 0.749, and 0.740 on the external test set. Our multi-modal decision fusion framework outperformed single-modal and multi-modal CNNs with accuracy, AUC, F1 score, precision, and recall of 0.764, 0.863, 0.844, 0.841, and 0.847 in distinguishing suspicious and non-suspicious foci on the internal test set and 0.796, 0.851, 0.865, 0.814, and 0.923 on the external test set. DL-based lesion segmentation on PSMA PET is facilitated through our anatomical prior guidance strategy. Our classification framework differentiates suspicious foci from those not suspicious for cancer with good accuracy.