In-situ co-immobilization of lipase, lipoxygenase and L-cysteine within a metal-amino acid framework for conversion of soybean oil into higher-value products.

We propose a co-immobilized chemo-enzyme cascade system to mitigate random intermediate diffusion from the mixture of individual immobilized catalysts and achieve a one-pot reaction of multi-enzyme and reductant. Catalyzed by lipase and lipoxygenase, unsaturated lipid hydroperoxides (HPOs) were synthesized. 13(S)-hydroperoxy-9Z, 11E-octadecadienoic acid (13-HPODE), one compound of HPOs, was subsequently reduced to 13(S)-hydroxy-9Z, 11E-octadecadienoic acid (13-HODE) by cysteine. Upon the optimized conditions, 75.28 mg of 13-HPODE and 4.01 mg of 13-HODE were produced from per milliliter of oil. The co-immobilized catalysts exhibited improved yield compared to the mixture of individually immobilized catalysts. Moreover, it demonstrated satisfactory durability and recyclability, maintaining a relative HPOs yield of 78.5% after 5 cycles. This work has achieved the co-immobilization of lipase, lipoxygenase and the reductant cysteine for the first time, successfully applying it to the conversion of soybean oil into 13-HODE. It offers a technological platform for transforming various oils into high-value products.

VASE: A High-Entropy Alloy Short-Range Order Structural Descriptor for Machine Learning.

The short-range order (SRO) structure in high-entropy alloys (HEAs) is closely associated with many properties, which can be studied through density functional theory (DFT) calculations. Atomic-scale modeling and calculations require substantial computational resources, and machine learning can provide rapid estimations of DFT results. To describe SRO information in HEAs, a new descriptor based on Voronoi Analysis and Shannon Entropy (VASE) is proposed. Based on Voronoi analysis, the Shannon entropy is introduced to directly characterize atomic spatial arrangement information except for composition and atomic interactions, which is necessary for describing the disorder atomic occupancy in HEAs. The new descriptor is used for predicting the formation energy of FeCoNiAlTiCu system based on machine learning model, which is more accurate than other descriptors (Coulomb matrices, partial radial distribution functions, and Voronoi analysis). Moreover, the model trained based on VASE descriptors exhibits the best predictive performance for unrelaxed structures (24.06 meV/atom). The introduction of Shannon entropy provides an effective representation of atomic arrangement information in HEAs, which is a powerful tool for investigating the SRO phenomena.

Effect of Pretreatments on the Chemical, Bioactive and Physicochemical Properties of Cinnamomum camphora Seed Kernel Extracts.

Cinnamomum camphora seed kernels (CCSKs) are rich in phytochemicals, especially plant extracts. Phytochemicals play a vital role in therapy due to their strong antioxidant and anti-inflammatory activities. Extracts from CCSK can be obtained through multiple steps, including pretreatment, extraction and purification, and the purpose of pretreatment is to separate the oil from other substances in CCSKs. However, C. camphora seed kernel extracts (CKEs) were usually considered as by-products and discarded, and their potential bioactive values were underestimated. Additionally, little has been known about the effect of pretreatment on CKE. This study aimed to investigate the effects of pretreatment methods (including the solvent extraction method, cold pressing method, aqueous extraction method and sub-critical fluid extraction method) on the extraction yields, phytochemical profiles, volatile compounds and antioxidant capacities of different CKE samples. The results showed that the CKE samples were rich in phenolic compounds (15.28-20.29%) and alkaloids (24.44-27.41%). The extraction yield, bioactive substances content and in vitro antioxidant capacity of CKE pretreated by the sub-critical fluid extraction method (CKE-SCFE) were better than CKEs obtained by other methods. CKE pretreated by the solvent extraction method (CKE-SE) showed the best lipid emulsion protective capacity. Moreover, the volatile substances composition of the CKE samples was greatly influenced by the pretreatment method. The results provided a fundamental basis for evaluating the quality and nutritional value of CKE and increasing the economic value of by-products derived from CCSK.

Efficacy and Safety of Sacubitril/Valsartan in Hemodialysis Patients with Chronic Heart Failure: A Retrospective Study at a Single Center.

BACKGROUND Heart failure and end-stage renal disease often coexist, and management of heart failure can be challenging in patients during hemodialysis. Sacubitril-valsartan (SV) is the first drug to receive regulatory approval for use in patients with chronic heart failure with reduced ejection fraction (HFrEF) and New York Heart Association (NYHA) classification II, III, or IV. This study aimed to evaluate the efficacy and safety of SV for use in chronic heart failure patients on maintenance hemodialysis (MHD). MATERIAL AND METHODS From September 2021 to October 2022, 28 patients on MHD with chronic heart failure at the hemodialysis center of Shaanxi Second Provincial People's Hospital were regularly followed. During the 12-week follow-up period, all patients were administered SV at doses of 100-400 mg per day. Biochemical indicators, echocardiographic parameters, life quality scores, and adverse events were evaluated. RESULTS We enrolled 28 patients. Compared with the baseline levels, NYHA class III in these patients treated with SV was significantly decreased from 60.71% to 32.14% (P<0.05), left ventricular ejection fraction (LVEF) was significantly improved from 44.29±8.92% to 53.32±7.88% (P<0.001), the Physical Component Summary (PCS) score was significantly improved from 40.0±6.41 to 56.20±9.86 (P<0.001), and the Mental Component Summary (MCS) score was significantly improved from 39.99±6.14 to 52.59±11.0 (P<0.001). CONCLUSIONS We demonstrated that SV improved NYHA classification and LVEF values of patients on MHD with chronic heart failure and also improved their quality of life.

Digirseophene A promotes recovery in injured developing cerebellum via AMPK/AKT/GSK3ß pathway-mediated neural stem cell proliferation.

Neural stem cells (NSCs) exhibit a remarkable capacity for self-renewal and have the potential to differentiate into various neural lineage cells, which makes them pivotal in the management of neurological disorders. Harnessing the inherent potential of endogenous NSCs for enhancing nerve repair and regeneration represents an optimal approach to addressing diseases of the nervous system. In this study, we explored the potential of a novel benzophenone derivative named Digirseophene A (DGA), which was isolated from the endophytic fungus Corydalis tomentella. Previous experiments have extensively identified and characterized DGA, revealing its unique properties. Our findings demonstrate the remarkable capability of DGA to stimulate neural stem cell proliferation, both in vitro and in vivo. Furthermore, we established a model of radiation-induced cerebellar injury to assess the effects of DGA on the distribution of different cell subpopulations within the damaged cerebellum, thereby suggesting its beneficial role in cerebellar repair. In addition, our observations on a primary NSCs model revealed that DGA significantly increased cellular oxygen consumption, indicating increased energy and metabolic demands. By utilizing various pathway inhibitors in combination with DGA, we successfully demonstrated its ability to counteract the suppressive impacts of AMPK and GSK3ß inhibitors on NSC proliferation. Collectively, our research results strongly suggest that DGA, as an innovative compound, exerts its role in activating NSCs and promoting injury repair through the regulation of the AMPK/AKT/GSK3ß pathway.

Superionic Conduction in K3SbS4 Enabled by Cl-Modified Anion Lattice.

All-solid-state potassium batteries emerge as promising alternatives to lithium batteries, leveraging their high natural abundance and cost-effectiveness. Developing potassium solid electrolytes (SEs) with high room-temperature ionic conductivity is critical for realizing efficient potassium batteries. In this study, we present the synthesis of K2.98Sb0.91S3.53Cl0.47, showcasing a room-temperature ionic conductivity of 0.32 mS/cm and a low activation energy of 0.26 eV. This represents an increase of over two orders of magnitude compared to the parent compound K3SbS4, marking the highest reported ionic conductivity for non-oxide potassium SEs. Solid-state 39K magic-angle-spinning nuclear magnetic resonance on K2.98Sb0.91S3.53Cl0.47 reveals an increased population of mobile K+ ions with fast dynamics. Ab initio molecular dynamics (AIMD) simulations further confirm a delocalized K+ density and significantly enhanced K+ diffusion. This work demonstrates diversification of the anion sublattice as an effective approach to enhance ion transport and highlights K2.98Sb0.91S3.53Cl0.47 as a promising SE for all-solid-state potassium batteries.

Full-Scale Modeling and FBGs Experimental Measurements for Thermal Analysis of Converter Transformer.

As the imbalance between power demand and load capacity in electrical systems becomes increasingly severe, investigating the temperature variations in transformers under different load stresses is crucial for ensuring their safe operation. The thermal analysis of converter transformers poses challenges due to the complexity of model construction. This paper develops a full-scale model of a converter transformer using a multi-core high-performance computer and explores its thermal state at 80%, 100%, and 120% loading ratios using the COUPLED iteration method. Additionally, to validate the simulation model, 24 FBGs are installed in the experimental transformer to record the temperature data. The results indicate a general upward trend in winding the temperature from bottom to top. However, an internal temperature rise followed by a decrease is observed within certain sections. Moreover, as the loading ratio increases, both the peak temperature and temperature differential of the transformer windings rise, reaching a peak temperature of 107.9 °C at a 120% loading ratio. The maximum discrepancy between the simulation and experimental results does not exceed 3.5%, providing effective guidance for the transformer design and operational maintenance.

Vitamin D regulates microbiome-dependent cancer immunity.

A role for vitamin D in immune modulation and in cancer has been suggested. In this work, we report that mice with increased availability of vitamin D display greater immune-dependent resistance to transplantable cancers and augmented responses to checkpoint blockade immunotherapies. Similarly, in humans, vitamin D-induced genes correlate with improved responses to immune checkpoint inhibitor treatment as well as with immunity to cancer and increased overall survival. In mice, resistance is attributable to the activity of vitamin D on intestinal epithelial cells, which alters microbiome composition in favor of Bacteroides fragilis, which positively regulates cancer immunity. Our findings indicate a previously unappreciated connection between vitamin D, microbial commensal communities, and immune responses to cancer. Collectively, they highlight vitamin D levels as a potential determinant of cancer immunity and immunotherapy success.

Dynamic Profiling and Prediction of Antibody Response to SARS-CoV-2 Booster-Inactivated Vaccines by Microsample-Driven Biosensor and Machine Learning.

Knowledge of the antibody response to the third dose of inactivated SARS-CoV-2 vaccines is crucial because it is the subject of one of the largest global vaccination programs. This study integrated microsampling with optical biosensors to profile neutralizing antibodies (NAbs) in fifteen vaccinated healthy donors, followed by the application of machine learning to predict antibody response at given timepoints. Over a nine-month duration, microsampling and venipuncture were conducted at seven individual timepoints. A refined iteration of a fiber optic biolayer interferometry (FO-BLI) biosensor was designed, enabling rapid multiplexed biosensing of the NAbs of both wild-type and Omicron SARS-CoV-2 variants in minutes. Findings revealed a strong correlation (Pearson r of 0.919, specificity of 100%) between wild-type variant NAb levels in microsamples and sera. Following the third dose, sera NAb levels of the wild-type variant increased 2.9-fold after seven days and 3.3-fold within a month, subsequently waning and becoming undetectable after three months. Considerable but incomplete evasion of the latest Omicron subvariants from booster vaccine-elicited NAbs was confirmed, although a higher number of binding antibodies (BAbs) was identified by another rapid FO-BLI biosensor in minutes. Significantly, FO-BLI highly correlated with a pseudovirus neutralization assay in identifying neutralizing capacities (Pearson r of 0.983). Additionally, machine learning demonstrated exceptional accuracy in predicting antibody levels, with an error level of <5% for both NAbs and BAbs across multiple timepoints. Microsample-driven biosensing enables individuals to access their results within hours of self-collection, while precise models could guide personalized vaccination strategies. The technology's innate adaptability means it has the potential for effective translation in disease prevention and vaccine development.

Integrative analysis of chromatin accessibility and transcriptome landscapes in the induction of peritoneal fibrosis by high glucose.

BACKGROUND: Peritoneal fibrosis is the prevailing complication induced by prolonged exposure to high glucose in patients undergoing peritoneal dialysis. METHODS: To elucidate the molecular mechanisms underlying this process, we conducted an integrated analysis of the transcriptome and chromatin accessibility profiles of human peritoneal mesothelial cells (HMrSV5) during high-glucose treatment. RESULTS: Our study identified 2775 differentially expressed genes (DEGs) related to high glucose-triggered pathological changes, including 1164 upregulated and 1611 downregulated genes. Genome-wide DEGs and network analysis revealed enrichment in the epithelial-mesenchymal transition (EMT), inflammatory response, hypoxia, and TGF-beta pathways. The enriched genes included VEGFA, HIF-1α, TGF-ß1, EGF, TWIST2, and SNAI2. Using ATAC-seq, we identified 942 hyper (higher ATAC-seq signal in high glucose-treated HMrSV5 cells than in control cells) and 714 hypo (lower ATAC-seq signal in high glucose-treated HMrSV5 cells versus control cells) peaks with differential accessibility in high glucose-treated HMrSV5 cells versus controls. These differentially accessible regions were positively correlated (R = 0.934) with the nearest DEGs. These genes were associated with 566 up- and 398 downregulated genes, including SNAI2, TGF-ß1, HIF-1α, FGF2, VEGFA, and VEGFC, which are involved in critical pathways identified by transcriptome analysis. Integrated ATAC-seq and RNA-seq analysis also revealed key transcription factors (TFs), such as HIF-1α, ARNTL, ELF1, SMAD3 and XBP1. Importantly, we demonstrated that HIF-1α is involved in the regulation of several key genes associated with EMT and the TGF-beta pathway. Notably, we predicted and experimentally validated that HIF-1α can exacerbate the expression of TGF-ß1 in a high glucose-dependent manner, revealing a novel role of HIF-1α in high glucose-induced pathological changes in human peritoneal mesothelial cells (HPMCs). CONCLUSIONS: In summary, our study provides a comprehensive view of the role of transcriptome deregulation and chromosome accessibility alterations in high glucose-induced pathological fibrotic changes in HPMCs. This analysis identified hub genes, signaling pathways, and key transcription factors involved in peritoneal fibrosis and highlighted the novel glucose-dependent regulation of TGF-ß1 by HIF-1α. This integrated approach has offered a deeper understanding of the pathogenesis of peritoneal fibrosis and has indicated potential therapeutic targets for intervention.

Synergistic catalysis of TiO2/WO3 photoanode and Sb-SnO2 electrode with highly efficient ClO• generation for urine treatment.

Urine is the major source of nitrogen pollutants in domestic sewage and is a neglected source of H2. Although ClO• is used to overcome the poor selectivity and slow kinetics of urea decomposition, the generation of ClO• suffers from the inefficient formation reaction of HO• and reactive chlorine species (RCS). In this study, a synergistic catalytic method based on TiO2/WO3 photoanode and Sb-SnO2 electrode efficiently producing ClO• is proposed for urine treatment. The critical design is that TiO2/WO3 photoanode and Sb-SnO2 electrode that generate HO• and RCS, respectively, are assembled in a confined space through face-to-face (TiO2/WO3//Sb-SnO2), which effectively strengthens the direct reaction of HO• and RCS. Furthermore, a Si solar panel as rear photovoltaic cell (Si PVC) is placed behind TiO2/WO3//Sb-SnO2 to fully use sunlight and provide the driving force of charge separation. The composite photoanode (TiO2/WO3//Sb-SnO2 @Si PVC) has a ClO• generation rate of 260% compared with the back-to-bake assembly way. In addition, the electrons transfer to the NiFe LDH@Cu NWs/CF cathode for rapid H2 production by the constructed photoelectric catalytic (PEC) cell without applied external biasing potential, in which the H2 production yield reaches 84.55 µmol h-1 with 25% improvement of the urine denitrification rate. The superior performance and long-term stability of PEC cell provide an effective and promising method for denitrification and H2 generation.

[Retracted] Antagonist targeting miR­106b­5p attenuates acute renal injury by regulating renal function, apoptosis and autophagy via the upregulation of TCF4.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that the EdU staining assay data shown in Figs. 4C and 5C and the western blotting data shown in Fig. 4E were strikingly similar to data appearing in different form in other research articles written by different authors at different research institutes that had either already been published, or were submitted for publication at around the same time. Owing to the fact that contentious data in the above article had already been submitted for publication elsewhere prior to its submission to International Journal of Molecular Medicine, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [International Journal of Molecular Medicine 48: 169, 2021; DOI: 10.3892/ijmm.2021.5002].

A Novel Approach to Evaluating Crosstalk for Near-Infrared Spectrometers.

Multi-channel and multi-parameter near-infrared spectroscopy (NIRS) has gradually become a new research direction and hot spot due to its ability to provide real-time, continuous, comprehensive indicators of multiple parameters. However, multi-channel and multi-parameter detection may lead to crosstalk between signals. There is still a lack of benchmarks for the evaluation of the reliability, sensitivity, stability and response consistency of the NIRS instruments. In this study, a set of test methods (a human blood model test, ink drop test, multi-channel crosstalk test and multi-parameter crosstalk test) for analyzing crosstalk and verifying the reliability of NIRS was conducted to test experimental verification on a multi-channel (8-channel), multi-parameter (4-parameter) NIRS instrument independently developed by our team. Results show that these tests can be used to analyze the signal crosstalk and verify the reliability, sensitivity, stability and response consistency of the NIRS instrument. This study contributes to the establishment of benchmarks for the NIRS instrument crosstalk and reliability testing. These novel tests have the potential to become the benchmark for NIRS instrument reliability testing.

Blocking Superantigen-Mediated Diseases: Challenges and Future Trends.

Superantigens are virulence factors secreted by microorganisms that can cause various immune diseases, such as overactivating the immune system, resulting in cytokine storms, rheumatoid arthritis, and multiple sclerosis. Some studies have demonstrated that superantigens do not require intracellular processing and instated bind as intact proteins to the antigen-binding groove of major histocompatibility complex II on antigen-presenting cells, resulting in the activation of T cells with different T-cell receptor Vß and subsequent overstimulation. To combat superantigen-mediated diseases, researchers have employed different approaches, such as antibodies and simulated peptides. However, due to the complex nature of superantigens, these approaches have not been entirely successful in achieving optimal therapeutic outcomes. CD28 interacts with members of the B7 molecule family to activate T cells. Its mimicking peptide has been suggested as a potential candidate to block superantigens, but it can lead to reduced T-cell activity while increasing the host's infection risk. Thus, this review focuses on the use of drug delivery methods to accurately target and block superantigens, while reducing the adverse effects associated with CD28 mimic peptides. We believe that this method has the potential to provide an effective and safe therapeutic strategy for superantigen-mediated diseases.

MRI-Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN-RNN Model.

BACKGROUND: Accurate evaluation of the axillary lymph node (ALN) status is needed for determining the treatment protocol for breast cancer (BC). The value of magnetic resonance imaging (MRI)-based tumor heterogeneity in assessing ALN metastasis in BC is unclear. PURPOSE: To assess the value of deep learning (DL)-derived kinetic heterogeneity parameters based on BC dynamic contrast-enhanced (DCE)-MRI to infer the ALN status. STUDY TYPE: Retrospective. SUBJECTS: 1256/539/153/115 patients in the training cohort, internal validation cohort, and external validation cohorts I and II, respectively. FIELD STRENGTH/SEQUENCE: 1.5 T/3.0 T, non-contrast T1-weighted spin-echo sequence imaging (T1WI), DCE-T1WI, and diffusion-weighted imaging. ASSESSMENT: Clinical pathological and MRI semantic features were obtained by reviewing histopathology and MRI reports. The segmentation of the tumor lesion on the first phase of T1WI DCE-MRI images was applied to other phases after registration. A DL architecture termed convolutional recurrent neural network (ConvRNN) was developed to generate the KHimage (kinetic heterogeneity of DCE-MRI image) score that indicated the ALN status in patients with BC. The model was trained and optimized on training and internal validation cohorts, tested on two external validation cohorts. We compared ConvRNN model with other 10 models and the subgroup analyses of tumor size, magnetic field strength, and molecular subtype were also evaluated. STATISTICAL TESTS: Chi-squared, Fisher's exact, Student's t, Mann-Whitney U tests, and receiver operating characteristics (ROC) analysis were performed. P < 0.05 was considered significant. RESULTS: The ConvRNN model achieved area under the curve (AUC) of 0.802 in the internal validation cohort and 0.785-0.806 in the external validation cohorts. The ConvRNN model could well evaluate the ALN status of the four molecular subtypes (AUC = 0.685-0.868). The patients with larger tumor sizes (>5 cm) were more susceptible to ALN metastasis with KHimage scores of 0.527-0.827. DATA CONCLUSION: A ConvRNN model outperformed traditional models for determining the ALN status in patients with BC. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Microarchitecture Alternations of Osteochondral Junction in Patients with Osteonecrosis of the Femoral Head.

The study was aimed to investigate microarchitecture of osteochondral junction in patients with osteonecrosis of the femoral head (ONFH). We hypothesis that there were microarchitecture alternations in osteochondral junction and regional differences between the necrotic region (NR) and adjacent non-necrotic region(ANR) in patients with ONFH. Femoral heads with ONFH or femoral neck fracture were included in ONFH group (n = 11) and control group (n = 11). Cylindrical specimens were drilled on the NR/ANR of femoral heads in ONFH group and matched positions in control group (CO.NR/ CO.ANR). Histology, micro-CT, and scanning electron microscope were used to investigate microarchitecture of osteochondral junction. Layered analysis of subchondral bone plate was underwent. Mankin scores on NR were higher than that on ANR or CO.NR, respectively (P < 0.001, P < 0.001). Calcified cartilage zone on the NR and ANR was thinner than that on the CO.NR and CO.ANR, respectively (P = 0.002, P = 0.002). Tidemark roughness on the NR was larger than that on the ANR (P = 0.002). Subchondral bone plate of NR and ANR was thicker than that on the CON.NR and CON.ANR, respectively (P = 0.002, P = 0.009). Bone volume fraction of subchondral bone plate on the NR was significantly decreasing compared to ANR and CON.NR, respectively (P = 0.015, P = 0.002). Subchondral bone plate on the NR had larger area percentages and more numbers of micropores than ANR and CON.NR (P = 0.002/0.002, P = 0.002/0.002). Layered analysis showed that bone mass loss and hypomineralization were mainly on the cartilage side of subchondral bone plate in ONFH. There were microarchitecture alternations of osteochondral junction in ONFH, including thinned calcified cartilage zone, thickened subchondral bone plate, decreased bone mass, altered micropores, and hypomineralization of subchondral bone plate. Regional differences in microarchitecture of osteochondral junction were found between necrotic regions and adjacent non-necrotic regions. Subchondral bone plate in ONFH had uneven distribution of bone volume fraction and bone mineral density, which might aggravate cartilage degeneration by affecting the transmission of mechanical stresses.

Boosting the Catalase-Like Activity of SAzymes via Facile Tuning of the Distances between Neighboring Atoms in Single-Iron Sites.

A nanozyme with neighboring single-iron sites (Fe2 -SAzyme) was introduced as a bioinspired catalase mimic, featuring excellent activity under varied conditions, twice as high as that of random Fe1 -SAzyme and ultrahigh H2 O2 affinity as that of bioenzymes. Surprisingly, the interatomic spacing tuning between adjacent iron sites also suppressed the competitive peroxidase pathway, remarkably increasing the catalase/peroxidase selectivity up to ~6 times compared to Fe1 -SAzyme. This dramatically switched the catalytic activity of Fe-SAzymes from generating (i.e. Fe1 -SAzymes, preferably mimicking peroxidase) to scavenging ROS (i.e. Fe2 -SAzymes, dominantly mimicking catalase). Theoretical and experimental investigations suggested that the pairwise single-iron sites may serve as a robust molecular tweezer to efficiently trap and decompose H2 O2 into O2 , via cooperative hydrogen-bonding induced end-bridge adsorption. The versatile mechano-assisted in situ MOF capsulation strategy enabled facile access to neighboring M2 -SAzyme (M=Fe, Ir, Pt), even up to a 1000 grams scale, but with no obvious scale-up effect for both structures and performances.

Single-cell RNA sequencing analysis of lung cells in COVID-19 patients with diabetes, hypertension, and comorbid diabetes-hypertension.

Background: There is growing evidence that the lung is a target organ for injury in diabetes and hypertension. There are no studies on the status of the lungs, especially cellular subpopulations, and related functions in patients with diabetes, hypertension, and hypertension-diabetes after combined SARS-CoV-2 infection. Method: Using single-cell meta-analysis in combination with bulk-RNA analysis, we identified three drug targets and potential receptors for SARS-CoV-2 infection in lung tissues from patients with diabetes, hypertension, and hypertension-diabetes, referred to as "co-morbid" patients. Using single-cell meta-analysis analysis in combination with bulk-RNA, we identified drug targets and potential receptors for SARS-CoV-2 infection in the three co-morbidities. Results: The single-cell meta-analysis of lung samples from SARS-CoV-2-infected individuals with diabetes, hypertension, and hypertension-diabetes comorbidity revealed an upregulation of fibroblast subpopulations in these disease conditions associated with a predictive decrease in lung function. To further investigate the response of fibroblasts to therapeutic targets in hypertension and diabetes, we analyzed 35 upregulated targets in both diabetes and hypertension. Interestingly, among these targets, five specific genes were upregulated in fibroblasts, suggesting their potential association with enhanced activation of endothelial cells. Furthermore, our investigation into the underlying mechanisms driving fibroblast upregulation indicated that KREMEN1, rather than ACE2, could be the receptor responsible for fibroblast activation. This finding adds novel insights into the molecular processes involved in fibroblast modulation in the context of SARS-CoV-2 infection within these comorbid conditions. Lastly, we compared the efficacy of Pirfenidone and Nintedanib as therapeutic interventions targeting fibroblasts prone to pulmonary fibrosis. Our findings suggest that Nintedanib may be a more suitable treatment option for COVID-19 patients with diabetes and hypertension who exhibit fibrotic lung lesions. Conclusion: In the context of SARS-CoV-2 infections, diabetes, hypertension, and their coexistence predominantly lead to myofibroblast proliferation. This phenomenon could be attributed to the upregulation of activated endothelial cells. Moreover, it is noteworthy that therapeutic interventions targeting hypertension-diabetes demonstrate superior efficacy. Regarding treating fibrotic lung conditions, Nintedanib is a more compelling therapeutic option.

Cytokines as drivers: Unraveling the mechanisms of epithelial-mesenchymal transition in COVID-19 lung fibrosis.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), like other viruses, can induce proliferation of myofibroblasts and even lead to fibrosis in the lung. Epithelial-mesenchymal transition (EMT) is thought to play an essential role in the pathogenesis of Coronavirus disease 19 (COVID-19). EMT is originally a critical process that regulates the development of different tissues in the embryo, but in inflammatory situations, EMT tries to be activated again to control inflammation or even heal inflammatory damage. However, in pathological situations, such as chronic viral infections (e.g., COVID-19) or pulmonary fibrosis initiation, this benign healing transforms into sinister nature, pushing the lung into the fibrotic process. Notably, the cytokines released by inflammatory cells and the chronic inflammatory microenvironment shared by fibrotic cells promote each other as critical factors in the induction of pathological EMT. In the induction of SARS-CoV-2 virus, cytokines are an essential mediator of EMT transformation, and a summary of whether COVID-19 patients, during the infection phase, have many persistent inflammatory mediators (cytokines) that are a causative factor of EMT has not yet appeared. The following common signaling drivers, including Transforming growth factor beta (TGF-ß), cytokines, Notch signaling pathway, Wnt and hypoxia signaling pathways, drive the regulation of EMT. In this review, we will focus on 3 key EMT signaling pathways: TGF-ß, Leucine zipper transcription factor like 1 (LZTFL1) and the common interleukin family expressed in the lung. TGF-ß-induced SNAIL and LZTFL1 were identified as regulatory EMT in COVID-19. For cytokines, the interleukin family is a common inducer of EMT and plays an essential role in the formation of the microenvironment of fibrosis. We sought to demonstrate that cytokines act as "communicators" and build the "microenvironment" of fibrosis together with EMT as a "bridge" to induce EMT in fibrosis. The mechanisms utilized by these two pathways could serve as templates for other mesenchymal transformations and provide new potential therapeutic targets.

Mechanical characteristics and energy evolution in a rock mass with a weak structural plane.

The present aims to investigate the mechanical characteristics and energy evolution in rock masses containing weak structural planes under conventional triaxial loading conditions. Using a fluid-solid coupling test system of coal rock, numerous conventional triaxial compression tests were performed on rock masses at various dip angles of the structural plane. The obtained empirical outcomes revealed that the deviatoric stress-strain curve of the weak structural plane rock mass with an inclination angle greater than 20° rises step-by-step. On the macro level, slip-stability occurs on the upper and lower parts of the rock mass on the weak structural plane. Then mechanism of the slip-stability phenomenon is explored by analyzing the stress level in the rock mass with various inclination angles. It is found that the energy evolution during deformation and failure reflects the damaged state of the rock. Accordingly, the concept of 'slip dissipation energy' is proposed, and the values of each energy are calculated. The results have a good correspondence with the deviatoric stress-strain curve. Furthermore, it was found that the energy evolution of rock mass with a weak structural plane can be primarily classified into four stages, including storage of the initial energy, slip dissipation, abrupt increase in the pre-peak dissipation energy, and sudden drop in post-peak energy. Rock masses with various levels of dip angles exhibit similar elastic strain energy and dissipation energy at the peak point, demonstrating that energy evolution is dominated by energy storage and dissipation. At the same time, a negative correlation is observed between the structural plane dip angle and the occurrence of instantaneous impact instability failure in rock masses, indicating that a greater dip angle makes the rock mass less prone to experiencing instantaneous impact instability failure. This article provides a new idea for analyzing the geological disasters caused by external disturbances.