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IntroductionThe significance of ligand-receptor (LR) pair interactions in the progression of acute myeloid leukemia (AML) has been the focus of numerous studies. However, the relationship between LR pairs and the prognosis of AML, as well as their impact on treatment outcomes, is not fully elucidated.MethodsLeveraging data from the TCGA-LAML cohort, we mapped out the LR pair interactions and distinguished specific molecular subtypes, with each displaying distinct biological characteristics. These subtypes exhibited varying mutation landscapes, pathway characteristics, and immune infiltration levels. Further insight into the immune microenvironment among these subtypes revealed disparities in immune cell abundance.ResultsNotably, one subtype showed a higher prevalence of CD8 T cells and plasma cells, suggesting increased adaptive immune activities. Leveraging a multivariate Lasso regression, we formulated an LR pair-based scoring model, termed “LR.score,” to classify patients based on prognostic risk. Our findings underscored the association between elevated LR scores and T-cell dysfunction in AML. This connection highlights the LR score’s potential as both a prognostic marker and a guide for personalized therapeutic interventions. Moreover, our LR.score revealed substantial survival prediction capacities in an independent AML cohort. We highlighted CLEC11A, ICAM4, ITGA4, and AVP as notably AML-specific.DiscussionqRT-PCR analysis on AML versus normal bone marrow samples confirmed the significant downregulation of CLEC11A, ITGA4, ICAM4, and AVP in AML, suggesting their inverse biomarker potential in AML. In summary, this study illuminates the significance of the LR pair network in predicting AML prognosis, offering avenues for more precise treatment strategies tailored to individual patient profiles.

The development of the Energy Internet has improved the efficiency of energy utilization and promoted sustainable development of power and energy systems. The multi-energy system modeling considering the dynamic process of transmission line is one of the key research points of Energy Internet operation control. Through the energy circuit theory, the lumped parameter model of natural gas pipelines is built and the dynamic characteristic parameters under the control instruction are extracted. Combined with dynamic characteristic parameters, the long short-term memory (LSTM) neural network is designed to fit the natural gas pipeline dynamic process into discrete linear time-varying (LTV) equations. Combined with the equations, an energy hub method is used to build a control model of industrial parks with multi-energy distribution system. Using the rolling optimal control strategy given in this paper, the model is solved by the Matlab-Yalmip solver and rolling control instructions of each energy conversion unit are obtained. Finally, the case study demonstrates that the LSTM neural network-based modeling method presented in this paper can accurately fit the dynamic process of a natural gas pipeline system. The rolling control model of the multi-energy system can improve the efficiency of energy utilization, exhibit the transmission line status constraints during the optimization control process and improve reliability of the multi-energy system operation.

Abstract Background Uric acid/high-density lipoprotein cholesterol ratio (UHR) is a novel index of inflammation and metabolism that has been investigated in various diseases. However, association between UHR and hypertension among reproductive-aged women is unclear. Methods In this cross-sectional study, we investigated the association between serum UHR and hypertension among 5485 women aged 20–44 years based on the National Health and Nutrition Examination Survey (NHANES) database using various methods, including univariate and multivariate logistic regression analysis, stratified analysis, and spline regression. P 1, P

Abstract The deformation potential plays an important role in electrical transport properties, but in the context of high-throughput searches requires a consistent and readily computable reference level. Here, we design a high-throughput method for calculating the deformation potential for semiconductors in the MatHub-3d database. The deformation potential is obtained from the volume-dependent band edge (valence band maximum and conduction band minimum) variations with respect to the reference level. In order to adapt the calculation of reference level to a high-throughput manner, the average value of the first valence electron energy band associated with each compound is used as the reference level. Deformation potentials for 11,993 materials are calculated using the above-mentioned method. By considering the calculated deformation potentials, electronic structures, and bulk moduli, 9957 compounds with converged electrical transport properties are obtained. 332 promising p-type thermoelectric materials, and 321 n-type entries are then proposed. Among them, 156 compounds are screened to having both potentially good n- and p-type thermoelectric transport properties. The band structures and chemical bonding information for several typical compounds are further presented to reveal favorable band and bonding features for thermoelectrics.

Cartilage, a flexible and smooth connective tissue that envelops the surfaces of synovial joints, relies on chondrocytes for extracellular matrix (ECM) production and the maintenance of its structural and functional integrity. Melatonin (MT), renowned for its anti-inflammatory and antioxidant properties, holds the potential to modulate cartilage regeneration and degradation. Therefore, the present study was devoted to elucidating the mechanism of MT on chondrocytes. The in vivo experiment consisted of three groups: Sham (only the skin tissue was incised), Model (using the anterior cruciate ligament transection (ACLT) method), and MT (30 mg/kg), with sample extraction following 12 weeks of administration. Pathological alterations in articular cartilage, synovium, and subchondral bone were evaluated using Safranin O-fast green staining. Immunohistochemistry (ICH) analysis was employed to assess the expression of matrix degradation-related markers. The levels of serum cytokines were quantified via Enzyme-linked immunosorbent assay (ELISA) assays. In in vitro experiments, primary chondrocytes were divided into Control, Model, MT, negative control, and inhibitor groups. Western blotting (WB) and Quantitative RT-PCR (q-PCR) were used to detect Silent information regulator transcript-1 (SIRT1)/Nuclear factor kappa-B (NF-κB)/Nuclear factor erythroid-2-related factor 2 (Nrf2)/Transforming growth factor-beta (TGF-β)/Bone morphogenetic proteins (BMPs)-related indicators. Immunofluorescence (IF) analysis was employed to examine the status of type II collagen (COL2A1), SIRT1, phosphorylated NF-κB p65 (p-p65), and phosphorylated mothers against decapentaplegic homolog 2 (p-Smad2). In vivo results revealed that the MT group exhibited a relatively smooth cartilage surface, modest chondrocyte loss, mild synovial hyperplasia, and increased subchondral bone thickness. ICH results showed that MT downregulated the expression of components related to matrix degradation. ELISA results showed that MT reduced serum inflammatory cytokine levels. In vitro experiments confirmed that MT upregulated the expression of SIRT1/Nrf2/TGF-β/BMPs while inhibiting the NF-κB pathway and matrix degradation-related components. The introduction of the SIRT1 inhibitor Selisistat (EX527) reversed the effects of MT. Together, these findings suggest that MT has the potential to ameliorate inflammation, inhibit the release of matrix-degrading enzymes, and improve the cartilage condition. This study provides a new theoretical basis for understanding the role of MT in decelerating cartilage degradation and promoting chondrocyte repair in in vivo and in vitro cultured chondrocytes.

In this paper, we investigate some systems of the Fermat type differential-difference equations with polynomial coefficients and obtain the condition for the existence of finite order transcendental entire solutions and the expression for the entire solutions. We also give some corresponding examples.

The high prevalence of prediabetes and diabetes globally has led to the widespread occurrence of severe complications, such as diabetic neuropathy, which is a result of chronic hyperglycemia. Studies have demonstrated that maternal diabetes can lead to neural tube defects by suppressing neurogenesis during neuroepithelium development. While aberrant autophagy has been associated with abnormal neuronal differentiation, the mechanism by which high glucose suppresses neural differentiation in stem cells remains unclear. Therefore, we developed a neuronal cell differentiation model of retinoic acid induced P19 cells to investigate the impact of high glucose on neuronal differentiation in vitro. Our findings indicate that high glucose (HG) hinders neuronal differentiation and triggers excessive. Furthermore, HG treatment significantly reduces the expression of markers for neurons (Tuj1) and glia (GFAP), while enhancing autophagic activity mediated by peroxisome proliferator-activated receptor gamma (PPARγ). By manipulating PPARγ activity through pharmacological approaches and genetically knocking it down using shRNA, we discovered that altering PPARγ activity affects the differentiation of neural stem cells exposed to HG. Our study reveals that PPARγ acts as a downstream mediator in high glucose-suppressed neural stem cell differentiation and that refining autophagic activity via PPARγ at an appropriate level could improve neuronal differentiation efficiency. Our data provide novel insights and potential therapeutic targets for the clinical management of gestational diabetes mellitus.

Abstract Background Multiple studies have revealed that repeated or long-term exposure to ketamine causes neurodegeneration and cognitive dysfunction. Pyroptosis is an inflammatory form of programmed cell death that has been linked to various neurological diseases. However, the role of NLRP3/caspase-1 axis-related pyroptosis in ketamine-induced neurotoxicity and cognitive dysfunction remains uncertain. Methods To evaluate whether ketamine caused NLRP3/caspase1-dependent pyroptosis, flow cytometry analysis, western blotting, ELISA test, histopathological analysis, Morris water maze (MWM) test, cell viability assay, and lactate dehydrogenase release (LDH) assay were carried out on PC12 cells, HAPI cells, and 7-day-old rats. In addition, the NLRP3 inhibitor MCC950 or the caspase-1 inhibitor VX-765 was used to investigate the role of the NLRP3/caspase-1 axis in ketamine-induced neurotoxicity and cognitive dysfunction. Results Our findings demonstrated that ketamine exposure caused cell damage and increased the levels of pyroptosis in PC12 cells, HAPI cells, and the hippocampus of neonatal rats. After continuous exposure to ketamine, targeting NLRP3 and caspase-1 with MCC950 or VX765 improved pyroptosis, reduced neuropathological damages, and alleviated cognitive dysfunction. Conclusion NLRP3/Caspase-1 axis-dependent pyroptosis is involved in ketamine-induced neuroinflammation and cognitive dysfunction, and it provides a promising strategy to treat ketamine-related neurotoxicity.

The aim of this work is the preliminary clinical validation and accuracy evaluation of our automatic algorithms in assessing progression fetal femur length (FL) in ultrasound images. To compare the random forest regression model with the SegNet model from the two aspects of accuracy and robustness. In this study, we proposed a traditional machine learning method to detect the endpoints of FL based on a random forest regression model. Deep learning methods based on SegNet were proposed for the automatic measurement method of FL, which utilized skeletonization processing and improvement of the full convolution network. Then the automatic measurement results of the two methods were evaluated quantitatively and qualitatively with the results marked by doctors. 436 ultrasonic fetal femur images were evaluated by the two methods above. Compared the results of the above three methods with doctor's manual annotations, the automatic measurement method of femur length based on the random forest regression model was 1.23 ± 4.66 mm and the method based on SegNet was 0.46 ± 2.82 mm. The indicator for evaluating distance was significantly lower than the previous literature. Measurement method based SegNet performed better in the case of femoral end adhesion, low contrast, and noise interference similar to the shape of the femur. The segNet-based method achieves promising performance compared with the random forest regression model, which can improve the examination accuracy and robustness of the measurement of fetal femur length in ultrasound images.

Ketamine is a widely-used anesthetic in the field of pediatrics and obstetrics. Multiple studies have revealed that ketamine causes neurotoxicity in developing animals. However, further studies are needed to determine whether clinical doses of ketamine (20 mg/kg) are able to cause kidney damage in developing animals. Herein, we investigated the effects of continuous ketamine exposure on kidney injury and pyroptosis in seven-day-old rats. Serum renal function indicators, renal histopathological analysis, pyroptosis, as well as oxidative stress indicators, were tested. Additionally, the NLRP3 inhibitor MCC950 and the Caspase-1 inhibitor VX765 were used to evaluate the role of the NLRP3/Caspase-1 axis in ketamine-induced kidney injury among developing rats. Our findings indicate that ketamine exposure causes renal histopathological injury, increased the levels of blood urea nitrogen (BUN) and creatinine (Cre), and led to upregulation in the levels of pyroptosis. Furthermore, we found that ketamine induced an increase in levels of reactive oxygen species (ROS) and malonaldehyde (MDA), as well as a decrease in the content of glutathione (GSH) and catalase (CAT) in the kidneys of neonatal rats. Moreover, targeting NLRP3 and caspase-1 with MCC950 or VX765 improved pyroptosis and reduced renal damage after continuous ketamine exposure. In conclusion, this study suggested that continued exposure to ketamine caused kidney damage among neonatal rats and that the NLRP3/Caspase-1 axis-related pyroptosis may be involved in this process.

Background:The association between triceps skinfold (TSF) thickness and mortality in previous studies was controversial. This study aimed to explore how TSF thickness affects all-cause, cardiovascular, and cerebrovascular mortality among the United States (U.S.) general population.MethodsOur research included 25,954 adults in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2010. Participants were categorized by the baseline TSF quartiles [quartile 1 (Q1): < 11.8, (Q2): 11.8–17.4, (Q3): 17.4–25, and (Q4): ≥25; unit: millimeter (mm)]. Cox regression models were used to assess the association of TSF with all-cause, cardiovascular, and cerebrovascular mortality. The association between mid-arm muscle circumference (MAMC) and mortality was also explored. Subgroup analyses were conducted to assess heterogeneity in different subgroups.ResultsThe highest TSF group (Q4) had the lowest risk to experience all-cause (HR, 0.46; 95% CI, 0.38–0.59; P < 0.001) and cardiovascular mortality (HR, 0.35; 95% CI, 0.23–0.54; P < 0.001) than the lowest TSF group (Q1) after multivariate adjustment. However, there was no relationship between TSF quartiles and cerebrovascular mortality (HR, 0.98; 95%CI, 0.42–2.30; P = 0.97). The protective effects of TSF thickness on mortality still existed after adjusting for BMI and MAMC. For every 1 mm increase in TSF thickness, the risk of all-cause and cardiovascular death decreased by 4% (HR, 0.96; 95% CI, 0.95–0.97; P < 0.001) and 6% (HR, 0.94; 95% CI, 0.93–0.96; P < 0.001), respectively. In the stratified analysis, the relationships between TSF and mortality risk were generally similar across all subgroups.ConclusionsHigher TSF thickness was associated with lower all-cause and cardiovascular mortality, independent of BMI and MAMC. Our study revealed that the TSF thickness may be a convenient and credible indicator to predict mortality, especially in those with severe cardiovascular diseases.

The stress-dependent core structures of dislocations for basal slip in magnesium are calculated using ab initio generalized stacking fault energy surface and microscopic phase-field method. The dissociation of dislocation cores exhibits the dependence on the non-shear component in the stress tensor; the Peierls stress is found to either become virtually zero or increase by an order of magnitude, depending on the applied shear stress magnitude and direction. The results, in contrast to the classical Schmid's law for crystal plasticity, are explained using the Escaig stress concept and the resulting implication on plastic deformation is discussed.

The use of transperineal ultrasound techniques for the assessment of fetal head descent and progression is an adjunct to clinical examination. Automatic identification of parameters based on ultrasound images will greatly reduce the subjectivity and non-repeatability of the clinician's judgment. However, the lack of a pubic symphysis-fetal head dataset hinders the development of algorithms. Here, we present an intrapartum transperineal ultrasound dataset of the Intelligent Fetal Monitoring Lab of Jinan University (named the JNU-IFM dataset), in which intrapartum transperineal ultrasound videos of 78 were recorded from 51 patients. These data were obtained with the Youkey D8 wireless 2D ultrasound probe with its corresponding supporting software by Wuhan Youkey Bio-Medical Electronics Co., Ltd., Wuhan, China. In these videos, 6224 high-quality images with four categories were selected to form the JNU- IFM dataset. These images were labelled using the Pair software and then validated by two experienced radiologists. We hope that this data set can be used in the segmentation of the pubic symphysis-fetal head.

This work provides a phase-field simulation framework that bridges the structure of defects (e.g., dislocations and grain boundaries (GBs)) to their characteristic properties, such as stresses and energies. The validity of the current methodology is examined first by predicting the stress field of a single infinitely long screw dislocation using both the analytical solutions based on anisotropic elasticity and the current phase-field framework. The well-known stress singularity associated with the dislocation core in the former method has been effectively avoided in the latter. The framework is then applied to predicting the dislocation network of {0 0 0 1} twisted GB in Mg, which is found to consist of triangular-shaped regions of stacking faults and perfect crystals separated by partial dislocations. This prediction is consistent with some existing atomistic simulations and the underlying formation mechanism is analyzed rigorously using the displacement field predicted by our model, revealing the energy minimization process via the dissociation of a 〈112¯0〉/3 screw dislocation into a pair of 〈1100〉/3 screw dislocations. Based on the structure prediction, the associated stress field is further simulated, which provides critical information in evaluating the interaction of GBs and other crystalline defects such as impurities and dislocations.

Ketamine is an anesthetic drug that is widely used in human and veterinary medicine. In the developmental stage, long-term exposure to ketamine may cause serious side effects. MCC950 and VX765 play protective roles in many disease models by regulating the NLRP3/Caspase-1 pathway. This study aims to explore the potential protective effect of MCC950 and VX765 on ketamine-induced liver injury in neonatal rats and clarify its underlying mechanism. After administration of MCC950 and VX765 in a ketamine-induced liver injury rat model, liver function and inflammatory factors were determined, and immunohistochemistry and western blotting were performed. We found that ketamine caused liver injury in 7-day-old SD rats, decreased liver function indexes, and increased inflammation. MCC950 and VX765 effectively alleviated liver damage and inflammation, and downregulated the expression of proteins such as NLRP3, Caspase-1, and GSDMD-N. In summary, these results indicated that MCC950 and VX765 could have potential protective effects on ketamine-induced liver injury through inhibiting the NLRP3/Caspase-1 pathway.

Morusin, a prenylated flavone isolated from Morus species, was treated as a potential anti-tumor drug since it inhibited effects on numerous types of human cancer cells. In some sense, drugs-related metabolites always contribute to pharmacological changes, inducing therapy improvement, reduced efficacy, or side-effects. Thus, the characterization of metabolites and the potential functions exerted great importance in clinical applications. Till now, the metabolism feature of morusin was still unclear, and its pharmacological changes were still unconducted, too. In this work, an integrated strategy based on metabolites profiling and network pharmacological was applied to characterize the metabolism feature and reveal pharmacological changes of morusin in vivo. As a result, a total of 31 metabolites (19 in plasma, 8 in urine, 30 in feces, 6 in heart, 17 in liver, 4 in spleen, 6 in lung, 6 in kidney, and 3 in brain) were screened out in rats, and 11 of them were characterized for the first time. Among them, metabolites M6, M18, M19, M20, and M28, were the main metabolites. Phase I metabolic reactions of hydroxylation, dehydrogenation (cyclization), isomerization and phase II reactions of glucuronidation occurred, and glucuronidation and hydroxylation were the two main metabolic reactions. Moreover, the pharmacological difference between morusin and five main metabolites was predicted by an network pharmacological method, and these 6 candidates targeted 177 targets. Meanwhile, in addition to common pathways (PI3K-Akt signaling pathway, proteoglycans in cancer, hepatitis B, cAMP signaling pathway, and viral carcinogenesis) of morusin in cancer, six metabolites’ targets were involved in prostate cancer, chemokine signaling pathway, ras signaling pathway and neuroactive ligand-receptor interaction, indicating that these functional changes might result in novel pharmacological mechanism and new indications. Our work provided the metabolism feature and functional modifications of morusin in vivo for the first time, and meaningful information for further pharmacological validations or potential indications in clinic were supplied.

The recent development of intermolecular C–H insertion in the application of C(sp3)–H bond functionalizations, especially for light alkanes, is reviewed. The challenging problem of regioselectivity in C–H bond insertions has been tackled by the use of sterically bulky metal catalysts, such as metal porphyrins and silver(I) complexes. In some cases, high regioselectivity and enantioselectivity have been achieved in the C–H bond insertion of small alkanes. This review highlights the most recent accomplishments in this field.

Loran is a radio-based navigation system originally designed for naval applications. We show that Loran-C’s high-power and high repeatable accuracy are fantastic for security applications. First, we show how to derive a precise location tag—with a sensitivity of about 20 meters—that is difficult to project to an exact location. A device can use our location tag to block or allow certain actions, without knowing its precise location. To ensure that our tag is reproducible we make use of fuzzy extractors, a mechanism originally designed for biometric authentication. We build a fuzzy extractor specifically designed for radio-type errors and give experimental evidence to show its effectiveness. Second, we show that our location tag is difficult to predict from a distance. For example, an observer cannot predict the location tag inside a guarded data center from a few hundreds of meters away. As an application, consider a location-aware disk drive that will only work inside the data center. An attacker who steals the device and is capable of spoofing Loran-C signals, still cannot make the device work since he does not know what location tag to spoof. We provide experimental data supporting our unpredictability claim.

Several green procedures have been developed for synthesizing functionalized aromatics: i) AuCl3-catalyzed halogenation of aromatic compounds, including aryl boronates; ii) Fe2O3-catalyzed direct aromatic C–H bond borylation; iii) Pd-catalyzed direct cyanation of indoles; iv) direct conversion of arylamines to pinacol boronates.

For media with inclusions (e.g., precipitates, voids, reinforcements, and others), the difference in lattice parameter and the elastic modulus between the matrix and inclusions cause stress concentration at the interfaces. These stress fields depend on the inclusions' size, shape, and distribution and will respond instantly to the evolving microstructure. This study develops a phase-field model concerningmodulus heterogeneity. The effect of modulus heterogeneity on the growth process and equilibrium state of the α plate in Ti-6Al-4V during precipitation is evaluated. The α precipitate exhibits strong anisotropy in shape upon cooling due to the interplay of the elastic strain and interfacial energy. The calculated orientation of the habit plane using the homogeneous modulus of α phase shows the smallest deviation fromthat of the habit plane observed in the experiment, compared to the case where the homogeneous modulus of β phase is adopted. In addition, the equilibrium volume of α phase within the systemusing homogeneous β modulus exhibits the largest dependency on the applied stresses. The stress fields across the α/β interface are further calculated under the assumption of modulus heterogeneity and compared to those using homogeneous modulus of either α or β phase. This study provides an essential theoretical basis for developing mechanics models concerning systems with heterogeneous structures. [ABSTRACT FROM AUTHOR]