Comparative analysis of immunological changes following realgar and arsenic trioxide treatments in a murine model of myelodysplastic syndrome.

BACKGROUND: Myelodysplastic syndrome (MDS) is a prevalent hematological neoplastic disorder in clinics and its immunopathogenesis has garnered growing interest. Oral and intravenous arsenic agents have long been used to treat hematological malignancies. The main component of oral arsenic is realgar (arsenic disulfide), while arsenic trioxide is the main component of intravenous arsenic. METHODS: This study aimed to assess the effects of ATO and Realgar on the enhancement of peripheral blood, drug safety, and T cell immune status in the NUP98-HOXD13 (NHD13) mice model of MDS, specifically in the peripheral blood, spleen, and liver. RESULTS: The study findings indicate that realgar and arsenic trioxide (ATO) can improve peripheral hemogram in mice, whereas realgar promotes higher peripheral blood cell production than ATO. Furthermore, the clinical administration method and dose did not cause significant toxicity or side effects and thus can be considered safe. Coexistence and interconversion of hyperimmune function and immunosuppression in mice were also observed in this study. In addition, there were interactions between immune cells in the peripheral blood, spleen, and liver to regulate the immune balance of the body and activate immunity via T-cell activation. CONCLUSION: In summary, oral and intravenous arsenic agents are beneficial in improving peripheral hemogram and immunity in mice.

Abnormal femoral trochlea morphology is a risk factor for secondary injury of anterior cruciate ligament after reconstruction.

Secondary injury of the anterior cruciate ligament (ACL) is a common concern after anterior cruciate ligament (ACL) reconstruction, and identification of morphological risk factors is essential to prevent these injuries. We hypothesized that abnormal femoral trochlea morphology is associated with secondary ACL injuries after reconstruction. This study aimed to investigate the relationship between femoral trochlear morphology and secondary ACL injuries after reconstruction. A retrospective analysis was conducted on 20 patients who experienced secondary ACL injuries after reconstruction in our hospital between 2017 and 2022 (experimental group), and 40 patients were included in the control group. The following femoral trochlear characteristics were compared between the 2 groups: medial condylar height (MCH), trochlear sulcus height (TSH), lateral condylar height (LCH), trochlear sulcus depth (TSD), trochlear sulcus angle (TSA), medial trochlear inclination (MTI), and lateral trochlear inclination (LTI). The study found that patients in the secondary ACL injury after reconstruction group exhibited the following differences when compared to the control group: decreased MCH (56.33 ±â€…3.52 vs 59.93 ±â€…3.24, P value = .015), decreased TSD (4.89 ±â€…1.56 vs 6.98 ±â€…1.23, P value ˂ .001), decreased MTI (12.54 ±â€…6.57 vs 19.45 ±â€…6.35, P value ˂ .001), and increased TSA (145.23 ±â€…9.76 vs 139.25 ±â€…8.42, P value ˂ .001). This study demonstrated a significant correlation between abnormal femoral trochlear morphological characteristics and secondary ACL injuries after reconstruction. Decreased MCH, TSD, and MTI along with increased TSA are associated with a higher risk of secondary ACL injury. These data could thus help identify individuals susceptible to secondary ACL injuries after reconstruction.

Predicting lung adenocarcinoma prognosis, immune escape, and pharmacomic profile from arginine and proline-related genes.

Lung adenocarcinoma (LUAD) is a highly heterogeneous disease that ranks first in morbidity and mortality. Abnormal arginine metabolism is associated with inflammatory lung disease and may influence alterations in the tumor immune microenvironment. However, the potential role of arginine and proline metabolic patterns and immune molecular markers in LUAD is unclear. Gene expression, somatic mutations, and clinicopathological information of LUAD were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression analysis was performed to identify metabolic genes associated with overall survival (OS). Unsupervised clustering divided the sample into two subtypes with different metabolic and immunological profiles. Gene set enrichment analysis (GESA) and gene set variation analysis (GSVA) were used to analyze the underlying biological processes of the two subtypes. Drug sensitivity between subtypes was also predicted; then prognostic features were developed by multivariate Cox regression analysis. In addition, validation was obtained in the GSE68465, and GSE50081 dataset. Then, gene expression, and clinical characterization of hub genes CPS1 and SMS were performed; finally, in vitro validation experiments for knockdown of SMS were performed in LUAD cell lines. In this study, we first identified 12 arginine and proline-related genes (APRGs) significantly associated with OS and characterized the clinicopathological features and tumor microenvironmental landscape of two different subtypes. Then, we established an arginine and proline metabolism-related scoring system and identified two hub genes highly associated with prognosis, namely CPS1, and SMS. In addition, we performed CCK8, transwell, and other functional experiments on SMS to obtain consistent results. Our comprehensive analysis revealed the potential molecular features and clinical applications of APRGs in LUAD. A model based on 2 APRGs can accurately predict survival outcomes in LUAD, improve our understanding of APRGs in LUAD, and pave a new pathway to guide risk stratification and treatment strategy development for LUAD patients.

Regulation of early diagnosis and prognostic markers of lung adenocarcinoma in immunity and hypoxia.

Lung adenocarcinoma is still cancer with the highest mortality. Hypoxia and immunity play an essential role in the occurrence and development of tumors. Therefore, this study is mainly to find new early diagnosis and prognosis markers and explore the relationship among the markers and immunity and hypoxia, to improve the prognosis of patients. Firstly, based on the clinical database in TCGA, we determined the most critical clinicopathological parameters affecting the prognosis of patients through a variety of analysis methods. According to pathological parameters, logistic most minor absolute contraction selection operator (lasso), univariate and multivariate regression analysis, the risk genes related to early prognosis were screened, and the risk model was established. Then, in different risk groups, GSEA and CIBERSORT algorithms were used to analyze the distribution and enrichment of the immune cells and hypoxia, to study the effects of early prognostic indicators on hypoxia and immunity. At the same time, we analyzed the different levels of risk genes in normal cells (BSEA-2B) and tumor cells (H1299, A549, PC9, and H1975). Finally, A549 and PC9 cells were induced by CoCl2 to establish a hypoxic environment, and the correlation between risk genes and HIF1A was analyzed. The risk model based on risk genes (CYP4B1, KRT6A, and FAM83A) was accurate and stable for the prognosis of patients. It is closely related to immunity and hypoxia. In BSEA-2B cells, the mRNA and protein expression of CYP4B1 was higher, while the expression of KRT6A and FAM83A was lower. Finally, we found that FAM83A and HIF1A showed a significant positive correlation when A549 and PC9 cells were exposed to hypoxia. The discovery of early diagnostic markers related to immunity, hypoxia, and prognosis, provides a new idea for early screening and prognostic treatment of lung adenocarcinoma.

B cell-related tertiary lymphoid structure may exert inhibitory effects on lung adenocarcinoma and SARS-COV-2.

Background: The prognosis of lung adenocarcinoma (LUAD) is poor. Infection with coronavirus disease 2019 (COVID-19) may further worsen the outcome of LUAD. This study utilized the immune model and the COVID-19 receptor signal to identify the potential immune structure affecting the prognosis of COVID-19 and LUAD. Methods: A prognostic model was established and verified. The correlation between immune cells and risk score was examined through a variety of immune calculation methods. Gene set variation analysis (GSVA) was used to explore the correlation between the immune signaling pathway, risk model, COVID-19 binding receptor (CO19ORS) signal, and different clinicopathological factors. Results: The analysis showed that the prognosis of patients was better in the low-risk group versus the high-risk group. The tertiary lymphoid structure dominated by T and B cells (TLS1) can improve the prognosis of patients in the low-risk group. Interestingly, the CO19ORS was enriched only in females and aged >65 years. The age group >65 years is closely related to the tertiary lymphatic structure of the newborn (TLS2), while the female sex is closely related to the TLS2 and TLS1 signature. The two groups exhibited a high level of inflammation-related signal distribution. In the near future, I will collect LUAD and COVID-19 related organizations to verify the changes of 8 risk protein. Conclusion: TLS1 structure may improve the prognosis of patients with LUAD and SARS-COV-2 (Severe acute respiratory syndrome coronavirus 2). This unexpected discovery provides new insight into the comprehensive treatment of patients with LUAD and SARS-COV-2.

Biotic Supplements in Patients With Chronic Kidney Disease: Meta-Analysis of Randomized Controlled Trials.

OBJECTIVE: Gut flora imbalance characterizes patients with chronic kidney disease (CKD). Although biotic supplementation has been proposed to lessen inflammation and oxidative stress and, thus, reduce the risk of progressive kidney damage and cardiovascular disease, the effects remain controversial. We conducted a meta-analysis to assess the therapeutic benefits of biotics in CKD. METHODS: PubMed, Embase, and Cochrane databases were systematically searched for randomized controlled trials that evaluated any biotic (prebiotic, probiotic, synbiotics) supplements in patients with CKD (CKD, stage 3-4 to end-stage renal disease). Primary endpoints included changes in renal function, markers of inflammation, and oxidative stress. Secondary endpoints included changes in levels of uremic toxins and variations in lipid metabolism. RESULTS: Twenty-three eligible studies included 842 participants. In a pooled-analysis, biotics did not change estimated glomerular filtration rate (mean difference [MD] = 0.08, P = .92) or serum albumin (MD = -0.01, P = .86), although prebiotics reduced serum creatinine (standardized mean difference [SMD] = -0.23, P = .009) and blood urea nitrogen (MD = -6.05, P < .00001). Biotics improved total antioxidative capacity (SMD = 0.37, P = .007) and malondialdehyde (SMD = -0.96, P = .006) and reduced the inflammatory marker interleukin-6 (SMD = -0.30, P = .01) although not C-reactive protein (SMD = -0.22, P = .20). Biotic intervention reduced some uremic toxins, including p-cresol sulfate (SMD = -2.18, P < .0001) and indoxyl sulfate (MD = -5.14, P = .0009), which decreased in dialysis-dependent patients. Another toxin, indole-3-acetic acid (MD = -0.22, P = .63), did not change. Lipids were unaffected by biotic intervention (total cholesterol: SMD = -0.01, P = .89; high-density lipoprotein: SMD = -0.08, P = .76; low-density lipoprotein: MD = 3.54, P = .28; triglyceride: MD = -2.26, P = .58). CONCLUSION: The results highlight the favorable influence of biotics on circulating markers of creatinine, oxidant stress (malondialdehyde, total antioxidative capacity), inflammation (interleukin-6), and uremic toxins (p-cresol sulfate) in patients with CKD. Biotics did not affect estimated glomerular filtration rate, albumin, indole-3-acetic acid, or lipids in either predialysis or dialysis patients.

CXCL10 and CXCR3 in the Trigeminal Ganglion Contribute to Trigeminal Neuropathic Pain in Mice.

PURPOSE: Trigeminal neuropathic pain is very common clinically, but effective treatments are lacking. Chemokines and their receptors have been implicated in the pathogenesis of chronic pain. This study explored the role of the chemokine CXCL10 and its receptor, CXCR3, in trigeminal neuropathic pain in mice. MATERIALS AND METHODS: Trigeminal neuropathic pain was established by partial infraorbital nerve ligation (pIONL) in wild-type and Cxcr3 -/- mice. Facial mechanical allodynia was evaluated by behavioral testing. A lentivirus containing Cxcr3 shRNA (LV-Cxcr3 shRNA) was microinjected into the trigeminal ganglion (TG) to knock down Cxcr3 expression. Quantitative polymerase chain reaction assays and immunofluorescence staining were used to examine Cxcl10/Cxcr3 mRNA expression and protein distribution. Western blotting was performed to examine activation of extracellular signal-regulated kinase (ERK) and AKT in the TG. Intra-TG injection of an AKT inhibitor was performed to examine the role of AKT in trigeminal neuropathic pain. RESULTS: pIONL induced persistent trigeminal neuropathic pain, which was alleviated in Cxcr3 -/- mice. Intra-TG injection of LV-Cxcr3 shRNA attenuated pIONL-induced mechanical allodynia. Furthermore, pIONL increased the expression of CXCR3 and its major ligand, CXCL10, in TG neurons. Intra-TG injection of CXCL10 induced pain hypersensitivity in wild-type mice but not in Cxcr3 -/- mice. CXCL10 also induced activation of ERK and AKT in the TG of wild-type mice. Finally, pIONL-induced activation of ERK and AKT was reduced in Cxcr3 -/- mice. Intra-TG injection of the AKT inhibitor alleviated pIONL-induced mechanical allodynia in WT mice but not in Cxcr3 -/- mice. CONCLUSION: CXCL10 acts on CXCR3 to induce ERK and AKT activation in TG neurons and contributes to the maintenance of trigeminal neuropathic pain.

Identifying drug-pathway association pairs based on L1L2,1-integrative penalized matrix decomposition.

The traditional methods of drug discovery follow the "one drug-one target" approach, which ignores the cellular and physiological environment of the action mechanism of drugs. However, pathway-based drug discovery methods can overcome this limitation. This kind of method, such as the Integrative Penalized Matrix Decomposition (iPaD) method, identifies the drug-pathway associations by taking the lasso-type penalty on the regularization term. Moreover, instead of imposing the L1-norm regularization, the L2,1-Integrative Penalized Matrix Decomposition (L2,1-iPaD) method imposes the L2,1-norm penalty on the regularization term. In this paper, based on the iPaD and L2,1-iPaD methods, we propose a novel method named L1L2,1-iPaD (L1L2,1-Integrative Penalized Matrix Decomposition), which takes the sum of the L1-norm and L2,1-norm penalties on the regularization term. Besides, we perform permutation test to assess the significance of the identified drug-pathway association pairs and compute the P-values. Compared with the existing methods, our method can identify more drug-pathway association pairs which have been validated in the CancerResource database. In order to identify drug-pathway associations which are not validated in the CancerResource database, we retrieve published papers to prove these associations. The results on two real datasets prove that our method can achieve better enrichment for identified association pairs than the iPaD and L2,1-iPaD methods.

Joint L1/2-Norm Constraint and Graph-Laplacian PCA Method for Feature Extraction.

Principal Component Analysis (PCA) as a tool for dimensionality reduction is widely used in many areas. In the area of bioinformatics, each involved variable corresponds to a specific gene. In order to improve the robustness of PCA-based method, this paper proposes a novel graph-Laplacian PCA algorithm by adopting L1/2 constraint (L1/2 gLPCA) on error function for feature (gene) extraction. The error function based on L1/2-norm helps to reduce the influence of outliers and noise. Augmented Lagrange Multipliers (ALM) method is applied to solve the subproblem. This method gets better results in feature extraction than other state-of-the-art PCA-based methods. Extensive experimental results on simulation data and gene expression data sets demonstrate that our method can get higher identification accuracies than others.

Identifying drug-pathway association pairs based on L2,1-integrative penalized matrix decomposition.

BACKGROUND: Traditional drug identification methods follow the "one drug-one target" thought. But those methods ignore the natural characters of human diseases. To overcome this limitation, many identification methods of drug-pathway association pairs have been developed, such as the integrative penalized matrix decomposition (iPaD) method. The iPaD method imposes the L1-norm penalty on the regularization term. However, lasso-type penalties have an obvious disadvantage, that is, the sparsity produced by them is too dispersive. RESULTS: Therefore, to improve the performance of the iPaD method, we propose a novel method named L2,1-iPaD to identify paired drug-pathway associations. In the L2,1-iPaD model, we use the L2,1-norm penalty to replace the L1-norm penalty since the L2,1-norm penalty can produce row sparsity. CONCLUSIONS: By applying the L2,1-iPaD method to the CCLE and NCI-60 datasets, we demonstrate that the performance of L2,1-iPaD method is superior to existing methods. And the proposed method can achieve better enrichment in terms of discovering validated drug-pathway association pairs than the iPaD method by performing permutation test. The results on the two real datasets prove that our method is effective.

Exogenous brain-derived neurotrophic factor relieves pain symptoms of diabetic rats by reducing excitability of dorsal root ganglion neurons.

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes lacking of effective treatments. Enhanced excitability of dorsal root ganglion (DRG) neuron plays a crucial role in the progression of diabetic neuropathic hyperalgesia. Brain-derived neurotrophic factor (BDNF) is known as a neuromodulator of nociception, but whether and how BDNF modulates the excitability of DRG neurons in the development of DPN remain to be clarified. This study investigated the role of exogenous BDNF and its high-affinity tropomyosin receptor kinase B (TrkB) in rats with streptozotocin-induced diabetic neuropathic pain. The results showed that continued intrathecal administration of BDNF to diabetic rats dramatically alleviated mechanical and thermal hyperalgesia, as well as inhibited hyperexcitability of DRG neurons. These effects were blocked by pretreatment with TrkB Fc (a synthetic fusion protein consisting of the extracellular ligand-binding domain of the TrkB receptor). The expression of BDNF and TrkB was upregulated in the DRG of diabetic rats. Intrathecal administration of BDNF did not affect this upregulation. These data provide novel information that exogenous BDNF relieved pain symptoms of diabetic rats by reducing hyperexcitability of DRG neurons and might be the potential treatment of painful diabetic neuropathy.

Combined enzymatic and mechanical cell disruption and lipid extraction of green alga Neochloris oleoabundans.

Microalgal biodiesel is one of the most promising renewable fuels. The wet technique for lipids extraction has advantages over the dry method, such as energy-saving and shorter procedure. The cell disruption is a key factor in wet oil extraction to facilitate the intracellular oil release. Ultrasonication, high-pressure homogenization, enzymatic hydrolysis and the combination of enzymatic hydrolysis with high-pressure homogenization and ultrasonication were employed in this study to disrupt the cells of the microalga Neochloris oleoabundans. The cell disruption degree was investigated. The cell morphology before and after disruption was assessed with scanning and transmission electron microscopy. The energy requirements and the operation cost for wet cell disruption were also estimated. The highest disruption degree, up to 95.41%, assessed by accounting method was achieved by the combination of enzymatic hydrolysis and high-pressure homogenization. A lipid recovery of 92.6% was also obtained by the combined process. The combined process was found to be more efficient and economical compared with the individual process.

NMR-based metabonomic and quantitative real-time PCR in the profiling of metabolic changes in carbon tetrachloride-induced rat liver injury.

Carbon tetrachloride (CCl4) is commonly used as a model toxicant to induce chronic and acute liver injuries. In this study, metabolite profiling and gene expression analysis of liver tissues were performed by nuclear magnetic resonance and quantitative real-time polymerase chain reaction to understand the responses of acute liver injury system in rats to CCl4. Acute liver injury was successfully induced by CCl4 as revealed by histopathological results and significant increase in alanine aminotransferase and serum aspartate aminotransferase. We found that CCl4 caused a significant increase in lactate, succinate, citrate, dimethylgycine, choline and taurine. CCl4 also caused a decrease in some of the amino acids such as leucine/isoleucine, glutamine/glutathione and betaine. Gene function analysis revealed that 10 relevant enzyme genes exhibited changes in expressions in the acute liver injury model. In conclusion, the metabolic pathways, including tricarboxylic acid cycle, antioxidant defense systems, fatty acid ß-oxidation, glycolysis and choline and mevalonate metabolisms were impaired in CCl4-treated rat livers. These findings provided an overview of the biochemical consequences of CCl4 exposure and comprehensive insights into the metabolic aspects of CCl4-induced hepatotoxicity in rats. These findings may also provide reference of the mechanisms of acute liver injury that could be used to study the changes in functional genes and metabolites.

Metabolomic study of the fever model induced by baker's yeast and the antipyretic effects of aspirin in rats using nuclear magnetic resonance and gas chromatography-mass spectrometry.

A metabolomic investigation of baker's yeast-induced fever in rats was carried out. Plasma derived from Sprague-Dawley rats treated by subcutaneous administration of 20% (w/v) baker's yeast was analyzed using gas chromatography-mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR). Statistical data analysis using t-test and orthogonal partial least-squares discriminant analysis revealed many significant changes in the metabolic data in the plasma of the fever group. Clear separation was achieved between the fever and control groups. Seventeen marked metabolites were found in the fever group. The metabolites, which include amino acids, carbohydrate, organic acids, and fatty acids, mostly contributed to the discrimination of plasma samples from the control and fever groups. These results suggested that fever may involve in the perturbation of amino acid metabolism coupled with energy metabolism, lipid metabolism, and glycometabolism. After determining the antipyretic effects of aspirin on the fever group, four metabolites in the fever rat plasma were found to be signally regulated and recognized as potential biomarkers, including 3-hydroxybutyric acid, gamma-aminobutyric acid, glucose, and linoleic acid. The metabolic relationships that possibly exist between these potential biomarkers were speculated, and the mechanism of baker's yeast-induced fever was illustrated based on the metabolic relationships. This study found that metabolomic approaches such as GC-MS and NMR could be used as potential powerful tools to investigate the biochemical changes and mechanisms in certain pathological states at the metabolism level.