Staging classification of omicron variant SARS-CoV-2 infection based on dual-spectrometer LIBS (DS-LIBS) combined with machine learning.

Effective differentiation of the infection stages of omicron can provide significant assistance in transmission control and treatment strategies. The combination of LIBS serum detection and machine learning methods, as a novel disease auxiliary diagnostic approach, has a high potential for rapid and accurate staging classification of Omicron infection. However, conventional single-spectrometer LIBS serum detection methods focus on detecting the spectra of major elements, while trace elements are more closely related to the progression of COVID-19. Here, we proposed a rapid analytical method with dual-spectrometer LIBS (DS-LIBS) assisted with machine learning to classify different infection stages of omicron. The DS-LIBS, including a broadband spectrometer and a narrowband spectrometer, enables synchronous collection of major and trace elemental spectra in serum, respectively. By employing the RF machine learning models, the classification accuracy using the spectra data collected from DS-LIBS can reach 0.92, compared to 0.84 and 0.73 when using spectra data collected from single-spectrometer LIBS. This significant improvement in classification accuracy highlights the efficacy of the DS-LIBS approach. Then, the performance of four different models, SVM, RF, IGBT, and ETree, is compared. ETree demonstrates the best, with cross-validation and test set accuracies of 0.94 and 0.93, respectively. Additionally, it achieves classification accuracies of 1.00, 0.92, 0.92, and 0.89 for the four stages B1-acute, B1-post, B2, and B3. Overall, the results demonstrate that DS-LIBS combined with the ETree machine learning model enables effective staging classification of omicron infection.

RASSF1A promotes radiosensitivity in nasopharyngeal carcinoma by promoting FoxO3a and inhibiting the Nrf2/TXNRD1 signaling pathway.

Radiotherapy is widely used as the first-line treatment for nasopharyngeal carcinoma (NPC). However, the resistance of some patients to treatment lowers its clinical effectiveness. Compared to typical epithelial cells, NPC markedly lowers the Ras-association domain family 1A (RASSF1A) protein expression. RASSF1A overexpression sensitizes NPC cells to radiotherapy. Mechanistically, RASSF1A promotes the expression of Forkhead box O3a (FoxO3a) in the nucleus and inhibits the Nuclear factor E2-related factor 2 (Nrf2) signaling pathway via binding to the Kelch-like ECH-associated protein 1 (Keap1) promoter. Through elevating intracellular ROS levels, RASSF1A overexpression inhibits the expression of thioredoxin reductase 1 (TXNRD1), a crucial Nrf2 target gene, and increases NPC sensitivity to radiation. Immunohistochemical staining of NPC tissue sections revealed that the expression of RASSF1A is negatively correlated with that of TXNRD1. The traditional Chinese medicine component andrographolide (AGP), which induces RASSF1A expression, increased the sensitivity of NPC cells to radiotherapy in vitro and in vivo. Our findings implied that RASSF1A increases the sensitivity of NPC to radiation by increasing FoxO3a expression in the nucleus, inhibiting the Nrf2/TXNRD1 signaling pathway, and elevating intracellular ROS levels. AGP targets RASSF1A and may be a promising adjuvant sensitizer for enhancing radiosensitivity in NPC.

Molecular Mechanism of Response and Adaptation of Antioxidant Enzyme System to Salt Stress in Leaves of Gymnocarpos przewalskii.

The antioxidant enzyme system is the main defense system responsible for maintaining cellular reactive oxygen species (ROS) homeostasis and normal plant growth and development after saline stress. In this study, we identified and characterized the members of the SOD, APX and CAT gene families of the antioxidant enzyme system in Gymnocarpos przewalskii, using plant physiology and molecular biology methods, and analyzed the pattern of enzyme activity in response to NaCl stress. It was found that seven, six and two genes of SOD, APX and CAT gene families, respectively, were expressed in the leaf tissue of G. przewalskii, in which most of the genes were significantly upregulated under NaCl stress, and the enzymatic activities were in accordance with the gene expression. Three positive selection sites in the GpCAT1 gene can increase the hydrophilicity of the GpCAT1 protein, increase the volume of the active site and increase the affinity for H2O2, thus improving the catalytic efficiency of GpCAT1. The results of the present study provide new insights for further investigations of the evolution and function of the SOD, APX and CAT gene families in G. przewalskii and their essential roles under salt stress, and the findings will be useful for revealing the molecular mechanism of salt tolerance and breeding of salt-tolerant plants.

Discovery and characterization of potent pan-variant SARS-CoV-2 neutralizing antibodies from individuals with Omicron breakthrough infection.

The SARS-CoV-2 Omicron variant evades most currently approved neutralizing antibodies (nAbs) and caused drastic decrease of plasma neutralizing activity elicited by vaccination or prior infection, urging the need for the development of pan-variant antivirals. Breakthrough infection induces a hybrid immunological response with potentially broad, potent and durable protection against variants, therefore, convalescent plasma from breakthrough infection may provide a broadened repertoire for identifying elite nAbs. We performed single-cell RNA sequencing (scRNA-seq) and BCR sequencing (scBCR-seq) of B cells from BA.1 breakthrough-infected patients who received 2 or 3 previous doses of inactivated vaccine. Elite nAbs, mainly derived from the IGHV2-5 and IGHV3-66/53 germlines, showed potent neutralizing activity across Wuhan-Hu-1, Delta, Omicron sublineages BA.1 and BA.2 at picomolar NT50 values. Cryo-EM analysis revealed diverse modes of spike recognition and guides the design of cocktail therapy. A single injection of paired antibodies cocktail provided potent protection in the K18-hACE2 transgenic female mouse model of SARS-CoV-2 infection.

Bioinformatics and Raman spectroscopy-based identification of key pathways and genes enabling differentiation between acute myeloid leukemia and T cell acute lymphoblastic leukemia.

Acute myeloid leukemia (AML) and T cell acute lymphoblastic leukemia (T-ALL) are two of the most prevalent hematological malignancies diagnosed among adult leukemia patients, with both being difficult to treat and associated with high rates of recurrence and mortality. In the present study, bioinformatics approaches were used to analyze both of these types of leukemia in an effort to identify characteristic gene expression patterns that were subsequently validated via Raman spectroscopy. For these analyses, four Gene Expression Omnibus datasets (GSE13204, GSE51082, GSE89565, and GSE131184) pertaining to acute leukemia were downloaded, and differentially expressed genes (DEGs) were then identified through comparisons of AML and T-ALL patient samples using the R Bioconductor package. Shared DEGs were then subjected to Gene Ontology (GO) enrichment analyses and were used to establish a protein-protein interaction (PPI) network analysis. In total, 43 and 129 upregulated and downregulated DEGs were respectively identified. Enrichment analyses indicated that these DEGs were closely tied to immune function, collagen synthesis and decomposition, inflammation, the synthesis and decomposition of lipopolysaccharide, and antigen presentation. PPI network module clustering analyses further led to the identification of the top 10 significantly upregulated and downregulated genes associated with disease incidence. These key genes were then validated in patient samples via Raman spectroscopy, ultimately confirming the value of these genes as tools that may aid the differential diagnosis and treatment of AML and T-ALL. Overall, these results thus highlight a range of novel pathways and genes that are linked to the incidence and progression of AML and T-ALL, providing a list of important diagnostic and prognostic molecular markers that have the potential to aid in the clinical diagnosis and treatment of these devastating malignancies.

Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection.

Although host responses to the ancestral SARS-CoV-2 strain are well described, those to the new Omicron variants are less resolved. We profiled the clinical phenomes, transcriptomes, proteomes, metabolomes, and immune repertoires of >1,000 blood cell or plasma specimens from SARS-CoV-2 Omicron patients. Using in-depth integrated multi-omics, we dissected the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes in the blood. Specifically, we detected enhanced interferon-mediated antiviral signatures of platelets in Omicron-infected patients, and platelets preferentially formed widespread aggregates with leukocytes to modulate immune cell functions. In addition, patients who were re-tested positive for viral RNA showed marked reductions in B cell receptor clones, antibody generation, and neutralizing capacity against Omicron. Finally, we developed a machine learning model that accurately predicted the probability of re-positivity in Omicron patients. Our study may inspire a paradigm shift in studying systemic diseases and emerging public health concerns.

Elucidating the Heterogeneity of Serum Metabolism in Patients with Myelodysplastic Syndrome and Acute Myeloid Leukemia by Raman Spectroscopy.

Myelodysplastic syndrome (MDS) is difficult to diagnose and classify because it has the potential to evolve into acute myeloid leukemia (AML). Raman spectroscopy and orthogonal partial least squares discrimination analysis (OPLS-DA) are used to systematically analyze peripheral blood serum samples from 33 patients with MDS, 25 patients with AML, and 29 control volunteers to gain insight into the heterogeneity of serum metabolism in patients with MDS and AML. AML patients show unique serum spectral data compared to MDS patients with considerably greater peak intensities of collagen (859 and 1345 cm-1) and carbohydrate (920 and 1123 cm-1) compared to MDS patients. Screening and bioinformatics analysis of MDS- and AML-related genes based on the Gene Expression Omnibus (GEO) database shows that 1459 genes are differentially expressed, and the main signaling pathways are related to Th17 cell differentiation, pertussis, and cytokine receptor interaction. Statistical analysis of serological indexes related to glucose and lipid metabolism shows that patients with AML have increased serum triglyceride (TG) levels and decreased total protein levels. This study provides a spectral basis for the relationship between the massive serological data of patients and the typing of MDS and AML and provides important information for the rapid and early identification of MDS and AML.

Bilayer Hydrogels with Low Friction and High Load-Bearing Capacity by Mimicking the Oriented Hierarchical Structure of Cartilage.

Natural articular cartilages exhibit extraordinary lubricating properties and excellent load-bearing capacity based on their penetrated surface lubricated biomacromolecules and gradient-oriented hierarchical structure. Hydrogels are considered as the most promising cartilage replacement materials due to their excellent flexibility, good biocompatibility, and low friction coefficient. However, the construction of high-strength, low-friction hydrogels to mimic cartilage is still a great challenge. Here, inspired by the structure and functions of natural articular cartilage, anisotropic hydrogels with horizontal and vertical orientation structure were constructed layer by layer and bonded with each other, successfully developing a bilayer oriented heterogeneous hydrogel with a high load-bearing capacity, low friction, and excellent fatigue resistance. The bilayer hydrogel exhibited a high compressive strength of 5.21 ± 0.45 MPa and a compressive modulus of 4.06 ± 0.31 MPa due to the enhancement mechanism of the anisotropic structure within the bottom anisotropic hydrogel. Moreover, based on the synergistic effect of the high load-bearing capacity of the bottom layer and the lubrication of the surface layer, the bilayer hydrogel possesses excellent biotribological properties in hard/soft (0.032) and soft/soft (0.028) contact, which is close to that of natural cartilage. It is worth noting that the bilayer oriented heterogeneous hydrogel is able to withstand repeated loading without fatigue crack. Therefore, this work could open up a new avenue for constructing cartilage-like materials with both high strength and low friction.

Role of STAT3 in the pathogenesis of nasopharyngeal carcinoma and its significance in anticancer therapy.

Nasopharyngeal carcinoma (NPC) is a type of head and neck tumor with noticeable regional and ethnic differences. It is associated with Epstein-Barr virus infection and has a tendency for local and distant metastasis. NPC is also highly sensitive to radiotherapy and chemotherapy. Over 70% of patients present with locoregionally advanced disease, and distant metastasis is the primary reason for treatment failure. A signal transducer and activator of transcription 3 (STAT3) promotes NPC oncogenesis through mechanisms within cancerous cells and their interactions with the tumor microenvironment, which is critical in the initiation, progression, and metastasis of NPC. Further, p-STAT3 is strongly associated with advanced NPC. Recent research on STAT3 has focused on its expression at the center of various oncogenic pathways. Here, we discuss the role of STAT3 in NPC and its potential therapeutic inhibitors and analogs for the treatment and control of NPC.

Curcumin activates Nrf2/HO-1 signaling to relieve diabetic cardiomyopathy injury by reducing ROS in vitro and in vivo.

The hallmark feature of Diabetes mellitus (DM) is hyperglycemia which can lead to excess production of reactive oxygen species (ROS) in the myocardium, contributing to diabetic cardiomyopathy (DCM). Nuclear factor erythroid2-related factor2 (Nrf2), a transcriptional activator, enhances its ability to resist oxidative stress by activating multiple downstream anti-oxidants, anti-inflammatory proteins, and detoxifying enzymes. However, the mechanism of Nrf2 signaling in HG-induced DCM is unclear. In this study, we used HG pretreated H9c2 cells as the experimental basis in vitro, and established a high fat-diet, streptozotocin (STZ) induced Type 2 diabetic rat model in vivo. Meanwhile, we used shRNA-Nrf2 and curcumin (CUR) (as an activator) to affect H9c2 cells, to verify the role of the Nrf2 signaling pathway in DCM. The results showed that the excessive production of ROS caused by HG, which could inhibit the activation of Nrf2-related signaling, resulting in a decrease in cell energy metabolism and an increase in cell apoptosis. Surprisingly, we found that the activation of the Nrf2 signaling pathway significantly increased cardiomyocyte viability, reduced ROS formation, increased antioxidant enzyme activity, and inhibited cardiomyocyte apoptosis. In conclusion, these findings conclusively infer that CUR activation of the Nrf2/HO-1 signaling pathway exerts myocardial protection by reducing ROS formation.

Spatial Distribution Characteristics of the Rural Tourism Villages in the Qinghai-Tibetan Plateau and Its Influencing Factors.

The development of rural tourism (RT) has great significance in reducing poverty and achieving rural vitalization. Qinghai-Tibetan Plateau (QTP) is a depressed area with rich RT resources due to its unspoiled nature and diverse culture. For future sustainable development of RT in QTP, this paper analyzes the spatial distribution characteristics and its influencing factors of RT villages using various spatial analysis methods, such as nearest neighbor index, kernel density estimation, vector buffer analysis, and geographic detectors. The results show the following. First, the RT villages present an agglomeration distribution tendency dense in the southeast and spare in the northwest. The inter-county imbalance distribution feature is obvious and four relatively high-density zones have been formed. Second, the RT villages have significant positive spatial autocorrelation, and the area of cold spots is larger and of hot spots is smaller. Third, the RT villages are mainly distributed with favorable topographic and climate conditions, near the road and water, around the city, and close to tourism resources. Fourth, the spatial distribution is the result of multifactor interactions. Socio-economic and tourism resource are the dominant factor in the mechanism network. Fifth, based on the above conclusions this study provides scientific suggestions for the sustainable development of the RT industry.

The antibacterial and wear-resistant nano-ZnO/PEEK composites were constructed by a simple two-step method.

Although the polyether ether ketone (PEEK) has excellent comprehensive properties, its non-antibacterial and low wear-resistant limit the wide application in the field of artificial joint materials. In this paper, Nano-ZnO was generated in situ on the surface of PEEK powder by one-step hydrothermal method, which improved the binding force of Nano-ZnO and PEEK matrix. Then the PEEK-based nanocomposites were prepared by melt blending with the synthesized Nano-ZnO-PEEK powders and PEEK powders. The microstructure, mechanical, biological and tribological properties of PEEK-based nanocomposites were studied. The results showed that the compressive strength of PEEK-based nanocomposites can reach up to 319.2 ± 2.4 MPa. Both PEEK and PEEK-based nanocomposites were non-toxic to cells. Meanwhile, PEEK-based nanocomposites showed good antibacterial activity against E.coli and Staphylococcus aureus, and the antibacterial activity was better with the increase of Nano-ZnO content. In addition, when the Nano-ZnO content was 5%, the wear rate of PEEK-based nanocomposites was about 68% lower than that of pure PEEK materials. Thus, PEEK-based nanocomposites has a dual function of good antibacterial property and excellent wear resistance.

Stable sensing platform for diagnosing electrolyte disturbance using laser-induced breakdown spectroscopy.

Electrolyte disturbance is very common and harmful, increasing the mortality of critical patients. Hence, rapid and accurate detection of electrolyte levels is vital in clinical practice. Laser-induced breakdown spectroscopy (LIBS) has the advantage of rapid and simultaneous detection of multiple elements, which meets the needs of clinical electrolyte detection. However, the cracking caused by serum drying and the effect of the coffee-ring led to the unstable spectral signal of LIBS and inaccurate detection results. Herein, we propose the ordered microarray silicon substrates (OMSS) obtained by laser microprocessing, to solve the disturbance caused by cracking and the coffee-ring effect in LIBS detection. Moreover, the area of OMSS is optimized to obtain the optimal LIBS detection effect; only a 10 uL serum sample is required. Compared with the silicon wafer substrates, the relative standard deviation (RSD) of the serum LIBS spectral reduces from above 80.00% to below 15.00% by the optimized OMSS, improving the spectral stability. Furthermore, the OMSS is combined with LIBS to form a sensing platform for electrolyte disturbance detection. A set of electrolyte disturbance simulation samples (80% of the ingredients are human serum) was prepared for this platform evaluation. Finally, the platform can achieve an accurate quantitative detection of Na and K elements (Na: RSD < 6.00%, R2 = 0.991; K: RSD < 4.00%, R2 = 0.981), and the detection time is within 5 min. The LIBS sensing platform has a good prospect in clinical electrolyte detection and other blood-related clinical diagnoses.

Cerebral Blood Flow Difference Between Acute and Chronic Tinnitus Perception: A Perfusion Functional Magnetic Resonance Imaging Study.

Purpose: The central nervous mechanism of acute tinnitus is different from that of chronic tinnitus, which may be related to the difference of cerebral blood flow (CBF) perfusion in certain regions. To verify this conjecture, we used arterial spin labeling (ASL) perfusion magnetic resonance imaging (MRI) in this study to compare the CBF alterations of patients with acute and chronic tinnitus. Methods: The current study included patients with chronic tinnitus (n = 35), acute tinnitus (n = 30), and healthy controls (n = 40) who were age-, sex-, and education-matched. All participants underwent MRI scanning and then ASL images were obtained to measure CBF of the entire brain and analyze the differences between groups as well as the correlations with tinnitus characteristics. Results: The chronic tinnitus group showed increased z-CBF in the right superior temporal gyrus (STG) and superior frontal gyrus (SFG) when compared with the acute tinnitus patients. Further connectivity analysis found enhanced CBF connectivity between the right STG and fusiform gyrus (FG), the right SFG and left middle occipital gyrus (MOG), as well as the right parahippocampal gyrus (PHG). Moreover, in the chronic tinnitus group, the tinnitus handicap questionnaire (THQ) score was positively correlated with the normalized z-CBF of right STG (r = 0.440, p = 0.013). Conclusion: Our results confirmed that the CBF changes in some brain regions were different between acute and chronic tinnitus patients, which was correlated with certain tinnitus characteristics. This is of great value to further research on chronicity of tinnitus, and ASL has a promising application in the measurement of CBF.

Insights into Superlow Friction and Instability of Hydrogenated Amorphous Carbon/Fluid Nanocomposite Interface.

Hydrogenated amorphous carbon (a-C:H) film exhibits the superlubricity phenomena as rubbed against dry sliding contacts. However, its antifriction stability strongly depends on the working environment. By composting with the fluid lubricant, the friction response and fundamental mechanisms governing the low-friction performance and instability of a-C:H remain unclear, while they are not accessible by experiment due to the complicated interfacial structure and the lack of advanced characterization technique in situ. Here, we addressed this puzzle with respect to the physicochemical interactions of a-C:H/oil/graphene nanocomposite interface at atomic scale. Results reveal that although the friction capacity and stability of system are highly sensitive to the hydrogenated degrees of mated a-C:H surfaces, the optimized H contents of mated a-C:H surfaces are suggested in order to reach the superlow friction or even superlubricity. Interfacial structure analysis indicates that the fundamental friction mechanism attributes to the hydrogenation-induced passivation of friction interface and squeezing effect to fluid lubricant. Most importantly, the opposite diffusion of fluid oil molecules to the sliding direction is observed, resulting in the transformation of the real friction interface from a-C:H/oil interface to oil/oil interface. These outcomes enable an effective manipulation of the superlow friction of carbon-based films and the development of customized solid-fluid lubrication systems for applications.

The Neural Mechanisms of Tinnitus: A Perspective From Functional Magnetic Resonance Imaging.

Tinnitus refers to sound perception in the absence of external sound stimulus. It has become a worldwide problem affecting all age groups especially the elderly. Tinnitus often accompanies hearing loss and some mood disorders like depression and anxiety. The comprehensive adverse effects of tinnitus on people determine the severity of tinnitus. Understanding the mechanisms of tinnitus and related discomfort may be beneficial to the prevention and treatment, and then getting patients out of tinnitus distress. Functional magnetic resonance imaging (fMRI) is a powerful technique for characterizing the intrinsic brain activity and making us better understand the tinnitus neural mechanism. In this article, we review fMRI studies published in recent years on the neuroimaging mechanisms of tinnitus. The results have revealed various neural network alterations in tinnitus patients, including the auditory system, limbic system, default mode network, attention system, and some other areas involved in memory, emotion, attention, and control. Moreover, changes in functional connectivity and neural activity in these networks are related to the perception, persistence, and severity of tinnitus. In summary, the neural mechanism of tinnitus is a complex regulatory mechanism involving multiple networks. Future research is needed to study these neural networks more accurately to refine the tinnitus models.

Blood cancer diagnosis using ensemble learning based on a random subspace method in laser-induced breakdown spectroscopy.

There are two main challenges in the diagnosis of blood cancer. The first is to diagnose cancer from healthy control, and the second is to identify the types of blood cancer. The chemometrics method combined with laser-induced breakdown spectroscopy (LIBS) can be used for cancer detection. However, chemometrics methods were easily influenced by the spectral feature redundancy and noise, resulting in low accuracy rate because of their simple structure. We proposed an approach using LIBS combined with the ensemble learning based on the random subspace method (RSM). The serum samples were dripped onto a boric acid substrate for LIBS spectrum collection. The complete blood cancer sample set include leukemia [acute myeloid leukemia (AML) and chronic myelogenous leukemia (CML)], multiple myeloma (MM), and lymphoma. The results showed that the accuracy rates using k nearest neighbors (kNN) and linear discriminant analysis (LDA) only were 88.14% and 94.45%, respectively, while using RSM with LDA (RSM-LDA), the average accuracy rate was improved from 94.45% to 98.34%. Furthermore, the variable importance of spectral lines (Na, K, Mg, Ca, H, O, N, C-N) were evaluated by the RSM-LDA model, which can improve the recognition ability of blood cancer types. Comparing the RSM-LDA model and only with LDA, the results showed that the average accuracy rate for cancer type identification was improved from 80.4% to 91.0%. These results demonstrate that LIBS combined with the RSM-LDA model can discriminate the blood cancer from the health control, as well as the recognition the types for blood cancers.