Construction of a necroptosis-related lncRNA signature for predicting prognosis and revealing the immune microenvironment in bladder cancer

BACKGROUND

Bladder cancer (BCa) is a common malignancy in the urinary system. Necroptosis, a recently discovered form of programmed cell death, is closely associated with the development and progression of various types of tumors. Targeting necroptosis through anti-cancer strategies has shown potential as a therapy for cancer. We aimed to develop a necroptosis-related lncRNAs (NRlncRNAs) risk model that can predict the survival and tumor immunity of BCa patients.

METHODS

We analyzed sequencing data obtained from the TCGA database, and applied least absolute shrinkage and selection operator (LASSO) and Cox regression analysis to identify crucial NRlncRNAs for building a risk model. Using the risk score, we categorized patients into high- and low-risk groups, and assessed the accuracy with the area under the receiver operating characteristic (AUROC) and Kaplan-Meier curves. We performed the RT-qPCR to detect the expression differences of the genes based on the risk model.

RESULTS

We identified a total of 296 NRlncRNAs, and 6 of them were included in the prognostic model. The AUC values for 1-, 3-, and 5-year predictions were 0.675, 0.726 and 0.734, respectively. Our risk model demonstrated excellent predictive performance and served as an independent predictor with high predictive power. Additionally, we performed PCA, TMB, GSEA analyses, and evaluated immune cell infiltration, to reveal significant differences between the high- and low-risk groups in functional signaling pathways, immunological status, and mutation profiles. Finally, we assessed the chemotherapeutic response of several drugs. According to the RT-qPCR results, we found that four NRlncRNAs of the risk model were more highly expressed in BCa cell lines than human immortalized uroepithelial cell line and regulated the occurrence and progression of bladder cancer.

CONCLUSION

We constructed a novel NRlncRNAs-associated risk model, which could predict the prognosis and immune response of BCa patients.

The E3 ubiquitin ligase TRIM39 modulates renal fibrosis induced by unilateral ureteral obstruction through regulating proteasomal degradation of PRDX3

Renal fibrosis is considered to be the ultimate pathway for various chronic kidney disease, with a complex etiology and great therapeutic challenges. Tripartite motif-containing (TRIM) family proteins have been shown to be involved in fibrotic diseases, but whether TRIM39 plays a role in renal fibrosis remain unexplored. In this study, we investigated the role of TRIM39 in renal fibrosis and its molecular mechanism. TRIM39 expression was analyzed in patients' specimens, HK-2 cells and unilateral ureteral obstruction (UUO) mice were used for functional and mechanistic studies. We found an upregulated expression of TRIM39 in renal fibrosis human specimens and models. In addition, TRIM39 knockdown was found efficient for alleviating renal fibrosis in both UUO mice and HK-2 cells. Mechanistically, we demonstrated that TRIM39 interacted with PRDX3 directly and induced ubiquitination degradation of PRDX3 at K73 and K149 through the K48 chain, which resulted in ROS accumulation and increased inflammatory cytokine generation, and further aggravated renal fibrosis. It provided an emerging potential target for the therapies of renal fibrosis.

Puerarin alleviated oxidative stress and ferroptosis during renal fibrosis induced by ischemia/reperfusion injury via TLR4/Nox4 pathway in rats

PURPOSE

To investigate the role of puerarin on renal fibrosis and the underlying mechanism in renal ischemia and reperfusion (I/R) model.

METHODS

Rats were intraperitoneally injected with puerarin (50 or 100 mg/kg) per day for one week before renal I/R. The level of renal collagen deposition and interstitial fibrosis were observed by hematoxylin and eosin and Sirius Red staining, and the expression of α-smooth muscle actin (α-SMA) was examined by immunohistochemical staining. The ferroptosis related factors and TLR4/Nox4-pathway-associated proteins were detected by Western blotting.

RESULTS

Puerarin was observed to alleviate renal collagen deposition, interstitial fibrosis and the α-SMA expression induced by I/R. Superoxide dismutase (SOD) activities and glutathione (GSH) level were decreased in I/R and hypoxia/reoxygenation (H/R), whereas malondialdehyde (MDA) and Fe2+ level increased. However, puerarin reversed SOD, MDA, GSH and Fe2+ level changes induced by I/R and H/R. Besides, Western blot indicated that puerarin inhibited the expression of ferroptosis related factors in a dose-dependent manner, which further demonstrated that puerarin had the effect to attenuate ferroptosis. Moreover, the increased expression of TLR/Nox4-pathway-associated proteins were observed in I/R and H/R group, but puerarin alleviated the elevated TLR/Nox4 expression.

CONCLUSIONS

Our results suggested that puerarin inhibited oxidative stress and ferroptosis induced by I/R and, thus, delayed the progression of renal fibrosis, providing a new target for the treatment of renal fibrosis.

Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study

BACKGROUND

Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. We aimed to develop and validate a weakly-supervised deep learning model to predict LNM status from digitized histopathological slides in MIBC.

METHODS

We trained a multiple instance learning model with an attention mechanism (namely SBLNP) from a cohort of 323 patients in the TCGA cohort. In parallel, we collected corresponding clinical information to construct a logistic regression model. Subsequently, the score predicted by the SBLNP was incorporated into the logistic regression model. In total, 417 WSIs from 139 patients in the RHWU cohort and 230 WSIs from 78 patients in the PHHC cohort were used as independent external validation sets.

RESULTS

In the TCGA cohort, the SBLNP achieved an AUROC of 0.811 (95% confidence interval [CI], 0.771-0.855), the clinical classifier achieved an AUROC of 0.697 (95% CI, 0.661-0.728) and the combined classifier yielded an improvement to 0.864 (95% CI, 0.827-0.906). Encouragingly, the SBLNP still maintained high performance in the RHWU cohort and PHHC cohort, with an AUROC of 0.762 (95% CI, 0.725-0.801) and 0.746 (95% CI, 0.687-0.799), respectively. Moreover, the interpretability of SBLNP identified stroma with lymphocytic inflammation as a key feature of predicting LNM presence.

CONCLUSIONS

Our proposed weakly-supervised deep learning model can predict the LNM status of MIBC patients from routine WSIs, demonstrating decent generalization performance and holding promise for clinical implementation.

Construction of cancer- associated fibroblasts related risk signature based on single-cell RNA-seq and bulk RNA-seq data in bladder urothelial carcinoma

Background

The ability of cancer-associated fibroblasts (CAFs) to encourage angiogenesis, tumor cell spread, and increase treatment resistance makes them pro-tumorigenic. We aimed to investigate the CAF signature in Bladder urothelial carcinoma (BLCA) and, for clinical application, to build a CAF-based risk signature to decipher the immune landscape and screen for suitable treatment BLCA samples.

Methods

CAF-related genes were discovered by superimposing CAF marker genes discovered from single-cell RNA-seq (scRNA-seq) data taken from the GEO database with CAF module genes discovered by weighted gene co-expression network analysis (WGCNA) using bulk RNA-seq data from TCGA. After identifying prognostic genes related with CAF using univariate Cox regression, Lasso regression was used to build a risk signature. With microarray data from the GEO database, prognostic characteristics were externally verified. For high and low CAF-risk categories, immune cells and immunotherapy responses were analyzed. Finally, a nomogram model based on the risk signature and prospective chemotherapeutic drugs were examined.

Results

Combining scRNA-seq and bulk-seq data analysis yielded a total of 124 CAF-related genes. LRP1, ANXA5, SERPINE2, ECM1, RBP1, GJA1, and FKBP10 were the seven BLCA prognostic genes that remained after univariate Cox regression and LASSO regression analyses. Then, based on these genes, prognostic characteristics were created and validated to predict survival in BLCA patients. Additionally, risk signature had a strong correlation with known CAF scores, stromal scores, and certain immune cells. The CAF-risk signature was identified as an independent prognostic factor for BLCA using multifactorial analysis, and its usefulness in predicting immunotherapy response was confirmed. Based on risk classification, we projected six highly sensitive anticancer medicines for the high-risk group.

Conclusion

The prognosis of BLCA may be accurately predicted using CAF-based risk signature. With a thorough understanding of the BLCA CAF-signature, it might be able to explain the BLCA patients' response to immunotherapy and identify a potential target for BLCA treatment.

Cyanidin-3-O-glucoside plays a protective role against renal ischemia/ reperfusion injury via the JAK/STAT pathway

PURPOSE

To investigate the role of cyanidin-3-O-glucoside (C3G) in renal ischemia/reperfusion (I/R) injury and the potential mechanisms.

METHODS

Mouse models were established by clamping the left renal vessels, and in vitro cellular models were established by hypoxic reoxygenation.

RESULTS

Renal dysfunction and tissue structural damage were significantly higher in the I/R group. After treatment with different concentrations of C3G, the levels of renal dysfunction and tissue structural damage decreased at different levels. And its protective effect was most pronounced at 200 mg/kg. The use of C3G reduced apoptosis as well as the expression of endoplasmic reticulum stress (ERS)-related proteins. Hypoxia/reoxygenation (H/R)-induced apoptosis and ERS are dependent on oxidative stress in vitro. In addition, both AG490 and C3G inhibited the activation of JAK/STAT pathway and attenuated oxidative stress, ischemia-induced apoptosis and ERS.

CONCLUSIONS

The results demonstrated that C3G blocked renal apoptosis and ERS protein expression by preventing reactive oxygen species (ROS) production after I/R via the JAK/STAT pathway, suggesting that C3G may be a potential therapeutic agent for renal I/R injury.

Quantitative Assessment of Tumor-Infiltrating Lymphocytes Using Machine Learning Predicts Survival in Muscle-Invasive Bladder Cancer

(1) Purpose: Although assessment of tumor-infiltrating lymphocytes (TILs) has been acknowledged to have important predictive prognostic value in muscle-invasive bladder cancer (MIBC), it is limited by inter- and intra-observer variability, hampering widespread clinical application. We aimed to evaluate the prognostic value of quantitative TILs score based on a machine learning (ML) algorithm to identify MIBC patients who might benefit from immunotherapy or the de-escalation of therapy. (2) Methods: We constructed an artificial neural network classifier for tumor cells, lymphocytes, stromal cells, and “ignore” cells from hematoxylin-and-eosin-stained slide images using the QuPath open source software. We defined four unique TILs variables based on ML to analyze TILs measurements. Pathological slide images from 133 MIBC patients were retrospectively collected as the discovery set to determine the optimal association of ML-read TILs variables with patient survival outcomes. For validation, we evaluated an independent external validation set consisting of 247 MIBC patients. (3) Results: We found that all four TILs variables had significant prognostic associations with survival outcomes in MIBC patients (p < 0.001 for all comparisons), with higher TILs score being associated with better prognosis. Univariate and multivariate Cox regression analyses demonstrated that electronic TILs (eTILs) variables were independently associated with overall survival after adjustment for clinicopathological factors including age, sex, and pathological stage (p < 0.001 for all analyses). Results analyzed in different subgroups showed that the eTILs variable was a strong prognostic factor that was not redundant with pre-existing clinicopathological features (p < 0.05 for all analyses). (4) Conclusion: ML-driven cell classifier-defined TILs variables were robust and independent prognostic factors in two independent cohorts of MIBC patients. eTILs have the potential to identify a subset of high-risk stage II or stage III-IV MIBC patients who might benefit from adjuvant immunotherapy.

A method for predicting the molar heat capacities of HBr and HCl gases based on the full set of molecular rovibrational energies

A new method is presented for one to obtain the molar heat capacities of diatomic macroscopic gas with a full set of microscopic molecular rovibrational energies. Based on an accurate experimental vibrational energies subset of a diatomic electronic ground state, the full vibrational energies can be obtained by using the variational algebraic method (VAM), the potential energy curves (PECs) will be constructed by the Rydberg-Klein-Rees (RKR) method, the full set of rovibrational energies will be calculated by the LEVEL program, and then the partition functions and the molar heat capacities of macroscopic gas can be calculated with the help of the quantum statistical ensemble theory. Applying the method to the ground state HBr and HCl gases, it is found that the relative errors of the partition functions calculated in the temperature range of 300 ∼ 6000 K are in excellent agreement with those obtained from TIPS database, and the calculated molar heat capacities are closer to the experimental values than those calculated by other methods without considering the energy levels of highly excited quantum states. The present method provides an effective new way for one to obtain the full set of molecular rovibrational energies and the molar heat capacities of macroscopic gas through the microscopic spectral information of a diatomic system.

Study on potential energy curves and ro-vibrational energies of DT, HT and T2 molecules

Accurately monitoring and effectively controlling the tritium compounds based on their ro-vibrational energy structure are important issues in various nuclear systems. Because of their radioactivity, it is difficult to obtain the corresponding energies directly through experiments. In this paper, the potential energy curves and the corresponding ro-vibrational full spectrum of DT, HT and T₂ systems are derived by ab initio methods. However, it is difficult to verify the reliability of the calculated results due to the lack of direct experimental support. Therefore, a data-driven reliability analysis method is proposed, which can confirm the reliability by extracting information from the relevant calculations and multiple experimental data (the vibrational level, rotational level, and molar heat capacity) of similar systems (HD, H₂, D₂). The results show that: 1) The potential energy curves obtained by the ab initio method can provide the full ro-vibrational energy spectrum with an accuracy of approximately 10 cm^-1; 2) Macroscopic heat capacity information can be used to distinguish and calibrate the overall reliability of microscopic ro-vibrational energies; 3) For the isotopic energy level structure of hydrogen, the influence of isotopes is mainly mass effect.

Mutations in chronic myelomonocytic leukemia and their prognostic relevance

Chronic myelomonocytic leukemia (CMML) is a hematologic malignancy that overlaps with myeloproliferative neoplasms (MPN) and myelodysplastic syndromes (MDS) and tends to transform into acute myeloid leukemia (AML). Among cases of CMML, > 90% have gene mutations, primarily involving TET2 (~ 60%), ASXL1 (~ 40%), SRSF2 (~ 50%), and the RAS pathways (~ 30%). These gene mutations are associated with both the clinical phenotypes and the prognosis of CMML, special CMML variants and pre-phases of CMML. Cytogenetic abnormalities and the size of genome are also associated with prognosis. Meanwhile, cases with ASXL1, DNMT3A, NRAS, SETBP1, CBL and RUNX1 mutations may have inferior prognoses, but only ASXL1 mutations were confirmed to be independent predictors of the patient outcome and were included in three prognostic models. Novel treatment targets related to the various gene mutations are emerging. Therefore, this review provides new insights to explore the correlations among gene mutations, clinical phenotypes, prognosis, and novel drugs in CMML.

Seven centuries of reconstructed Brahmaputra River discharge demonstrate underestimated high discharge and flood hazard frequency

The lower Brahmaputra River in Bangladesh and Northeast India often floods during the monsoon season, with catastrophic consequences for people throughout the region. While most climate models predict an intensified monsoon and increase in flood risk with warming, robust baseline estimates of natural climate variability in the basin are limited by the short observational record. Here we use a new seven-century (1309-2004 C.E) tree-ring reconstruction of monsoon season Brahmaputra discharge to demonstrate that the early instrumental period (1956-1986 C.E.) ranks amongst the driest of the past seven centuries (13th percentile). Further, flood hazard inferred from the recurrence frequency of high discharge years is severely underestimated by 24-38% in the instrumental record compared to previous centuries and climate model projections. A focus on only recent observations will therefore be insufficient to accurately characterise flood hazard risk in the region, both in the context of natural variability and climate change.

A joint data and model driven method for study diatomic vibrational spectra including dissociation behavior

The details of quantum multi-body interactions are so rich and subtle which make it difficult to accurately model for some situations such as the behavior of diatomic long-range vibrations. In recent years, data-driven machine learning has made remarkable achievements in capturing complex relationships that are subtle. Combining the characteristics of these two fields, we propose a joint machine learning method to obtain reliable diatomic vibrational spectra including dissociation energy by using accessible heterogeneous micro/macro information such as low lying vibrational energy levels and heat capacity. Applications of this method to CO and Br₂ in the ground state yield their state of the art of vibrational spectra including dissociation limit. The strategy introduced here is an exploration of combining the model-driven and data-driven method to cover subtle physical details that are difficult to study in a single way.

Influenza a virus and Streptococcus pneumonia coinfection potentially promotes bacterial colonization and enhances B lymphocyte depression and reduction

Influenza has frequently been epidemic in recent years. However, the mechanisms of severe pneumonia with postinfluenza Streptococcus pneumoniae (SP) secondary infection have not been fully understood. In this study, we explored the mechanisms of pneumonia in postinfluenza A virus (IAV) infection via a mouse model. Mice were intranasally inoculated with SP three days after IAV inoculation. We then collected samples at three time points to dynamically observe the pathological progression. In IAV infection alone, lymphocyte infiltration and widened alveolar intervals were observed. In the blood, levels of the CD19+, CD19+CD21+ and CD19+CD79β+B lymphocyte subpopulations were reduced, and IFN-γ and IL-10 were elevated. Slight atrophy was seen in the spleen, which was due to splenic B lymphocyteinitiated apoptosis through the mitochondrial pathway. When SP infection occurred after IAV infection, the pulmonary inflammation was significantly aggravated; a fair number of lymphocytes and neutrophils infiltrated simultaneously with exfoliated bronchial epithelial cells, vascular endothelial cells, widened alveolar septum and hemorrhaging. Increasing edema fluid and bacteria accumulated in the alveolar cavity. Decreased CD19+, CD19+CD21+ and CD19+CD79β+B lymphocyte subpopulations and increased interferon gamma (IFN-γ) or interleukin 10 (IL-10) were more prominent compared to those with viral infection alone. Spleen atrophy resulting from coinfection was more obvious because of massive splenic B lymphocyte apoptosis through the mitochondrial pathway compared to viral infection alone. This study shows that although inflammation caused by SP infection alone was temporary, preceding IAV infection provided favorable conditions for SP colonization and multiplication by destroying lung structure and suppressing humoral immunity. Synergistic IAV-SP coinfection is likely to facilitate more SP colonization and promote B lymphocyte-suppression and reduction. Eventually, the pneumonia worsened.

Structural Brain Network Reorganization in Patients with Neuropsychiatric Systemic Lupus Erythematosus

BACKGROUND AND PURPOSE

Patients with neuropsychiatric systemic lupus erythematosus have worse outcomes compared with those with systemic lupus erythematosus. A better understanding of the mechanisms of neuropsychiatric systemic lupus erythematosus could potentially improve diagnosis and management. The goal of this study was to investigate the differences in the structural brain network of patients with neuropsychiatric systemic lupus erythematosus compared with patients with systemic lupus erythematosus by using brain connectivity analysis.

MATERIALS AND METHODS

We recruited 20 subjects for each patient cohort and age-matched healthy controls. The topology and efficiency of the network and the characteristics of various brain hubs were investigated by using brain connectivity analysis of diffusion MR imaging data.

RESULTS

There were more extensive reorganizations in the structural brain network of patients with neuropsychiatric systemic lupus erythematosus than in patients with systemic lupus erythematosus. For example, the network of the former had significantly decreased clustering coefficient and local efficiency. They also had significantly lower nodal efficiency in the superior temporal gyrus (P = .046) and middle temporal gyrus (P = .041).

CONCLUSIONS

Our results hint at a plausible relationship between the neuropsychiatric symptoms and reorganization of the structural brain network of patients with systemic lupus erythematosus. Brain connectivity analysis may be a potential tool to subtype these patients.

Associations of serotonin receptor gene HTR3A, HTR3B, and HTR3A haplotypes with bipolar disorder in Chinese patients

Single nucleotide polymorphisms (SNPs) in HTR3A and HTR3B have been reported to be associated with bipolar disorder in European and Japanese populations. We explored the roles of 21 tag SNPs in HTR3A and HTR3B in susceptibility to bipolar disorder in a Chinese cohort. Twenty-one Tag SNPs were genotyped in a study consisting of 130 patients with bipolar disorder, who visited Shandong Mental Health Center between June 2013 and May 2014, and 109 healthy individuals as controls. All of the tag SNPs were genotyped using Sequenom MassArray matrix-assisted laser desorption/ionization time of flight spectrometry. Plink 1.07, Haploview 4.2, and SPSS 20.0 were used for the analysis of the genotypes and the associations of the haplotypes with bipolar disorder. Association analyses of tag SNPs detected significant associations with the A allele in HTR3A rs1176719 (P = 0.030) and the C allele in HTR3A rs1176713 (P = 0.048). Haplotype-based association analyses indicated a statistically significant (P = 0.035) five-SNP haplotype (rs1062613:C, rs11604247:C, rs1176722:G, rs2276302:A, rs1176719:G) of linkage disequilibrium in block 3. Analysis of our small Chinese sample revealed a significant association of HTR3A with bipolar disorder, but yielded no evidence of an association between HTR3B and bipolar disorder. Furthermore, evidence for an association was found for a haplotype of HTR3A. Studies with larger Chinese samples are needed to verify our findings.

Using multiple barometers to detect the floor location of smart phones with built-in barometric sensors for indoor positioning

Following the popularity of smart phones and the development of mobile Internet, the demands for accurate indoor positioning have grown rapidly in recent years. Previous indoor positioning methods focused on plane locations on a floor and did not provide accurate floor positioning. In this paper, we propose a method that uses multiple barometers as references for the floor positioning of smart phones with built-in barometric sensors. Some related studies used barometric formula to investigate the altitude of mobile devices and compared the altitude with the height of the floors in a building to obtain the floor number. These studies assume that the accurate height of each floor is known, which is not always the case. They also did not consider the difference in the barometric-pressure pattern at different floors, which may lead to errors in the altitude computation. Our method does not require knowledge of the accurate heights of buildings and stories. It is robust and less sensitive to factors such as temperature and humidity and considers the difference in the barometric-pressure change trends at different floors. We performed a series of experiments to validate the effectiveness of this method. The results are encouraging.

Using smart phone sensors to detect transportation modes

The proliferation of mobile smart devices has led to a rapid increase of location-based services, many of which are amassing large datasets of user trajectory information. Unfortunately, current trajectory information is not yet sufficiently rich to support classification of user transportation modes. In this paper, we propose a method that employs both the Global Positioning System and accelerometer data from smart devices to classify user outdoor transportation modes. The classified modes include walking, bicycling, and motorized transport, in addition to the motionless (stationary) state, for which we provide new depth analysis. In our classification, stationary mode has two sub-modes: stay (remaining in the same place for a prolonged time period; e.g., in a parked vehicle) and wait (remaining at a location for a short period; e.g., waiting at a red traffic light). These two sub-modes present different semantics for data mining applications. We use support vector machines with parameters that are optimized for pattern recognition. In addition, we employ ant colony optimization to reduce the dimension of features and analyze their relative importance. The resulting classification system achieves an accuracy rate of 96.31% when applied to a dataset obtained from 18 mobile users.

Environmental prediction, risk assessment and extreme events: adaptation strategies for the developing world

The uncertainty associated with predicting extreme weather events has serious implications for the developing world, owing to the greater societal vulnerability to such events. Continual exposure to unanticipated extreme events is a contributing factor for the descent into perpetual and structural rural poverty. We provide two examples of how probabilistic environmental prediction of extreme weather events can support dynamic adaptation. In the current climate era, we describe how short-term flood forecasts have been developed and implemented in Bangladesh. Forecasts of impending floods with horizons of 10 days are used to change agricultural practices and planning, store food and household items and evacuate those in peril. For the first time in Bangladesh, floods were anticipated in 2007 and 2008, with broad actions taking place in advance of the floods, grossing agricultural and household savings measured in units of annual income. We argue that probabilistic environmental forecasts disseminated to an informed user community can reduce poverty caused by exposure to unanticipated extreme events. Second, it is also realized that not all decisions in the future can be made at the village level and that grand plans for water resource management require extensive planning and funding. Based on imperfect models and scenarios of economic and population growth, we further suggest that flood frequency and intensity will increase in the Ganges, Brahmaputra and Yangtze catchments as greenhouse-gas concentrations increase. However, irrespective of the climate-change scenario chosen, the availability of fresh water in the latter half of the twenty-first century seems to be dominated by population increases that far outweigh climate-change effects. Paradoxically, fresh water availability may become more critical if there is no climate change.

[Acquisition and analysis of lipophosphonoglycan 1 gene and the noncoding region of Leishmania donovani isolates from hilly foci of China]

A fragment about 2.2 kb located at upstream of lipophosphonoglycan 1 (LPG1) gene of Leishmania donovani isolate from hilly foci of China was obtained by PCR. The nucleotide sequence of the fragment was determined by sequencing. The sequence of the LPG1 gene and its downstream fragment (about 2 kb) was determined by using genome walking method. The above two fragment splicing result showed that the nucleotide sequence of the LPG1 gene with the noncoding region was 4 121 bp (GenBank accession number: HMO27899). The BLAST results showed that the LPG1 gene of L. donovani isolate from hilly foci of China had 72%-78% nucleotide identity compared to that of other Leishmania spp. in GenBank.

[The effects of Xuezhikang on serum lipid profile, thromboxane A2 and prostacyclin in patients with hyperlipidemia]

OBJECTIVE

To study the effects of Xuezhikang on lipid profile, thromboxane (TX) A(2), prostacyclin (PGI(2)) in patients with hyperlipidemia.

METHODS

91 patients with hyperlipidemia were randomly divided into a treatment group (n = 47, Xuezhikang 1.2 g/d Bid, p.o) and control group (n = 44, gemfibrozil 1.2 g/d Bid, p.o). serum lipids, TXB(2) and 6-Keto-PGF(1alpha) were determined before and 8 weeks after the treatment.

RESULTS

(1) After 8 weeks of treatment, the level of serum total cholesterol (TC) and low density lipoprotein cholesterol (LDL-C) decreased by 21.6% (P < 0.01) and 33.3% (P < 0. 01) in the Xuezikang group and by 20.4% (P < 0.01) and 24.8% (P < 0.01) in the gemfibrozil group respectively. Serum high density lipoprotein cholesterol (HDL-C) level elevated by 33.7% in the Xuezhikang group (P < 0.01) and 26.9% in the gemfibrozil group (P < 0.01). The effect of Xuezhikang was the same as gemfibrozil. There was no statistically significant difference between the effects of these two drugs. Triglyceride (TG) level decreased by 23.3% in the Xuezhikang group (P < 0.01) and 40.3% in the gemfibrozil group (P < 0.01). TG lowering effect of gemfibrozil was superior to that of Xuezhikang (P < 0.05). (2) The level of lipoprotein (a) [LP (a)] in the plasma decreased by 28.2% (P < 0.01) in the Xuezhikang group and by 4.9% (P > 0.05) in the gemfibrozil group. LP (a) lowering effect of Xuezhikang was superior to that of gemfibrozil (P < 0.01). (3)The Level of thromboxane (TX) B(2) in the plasma decreased by 34.2% in the Xuezhikang group (P < 0.01) and by 8.4% in the gemfibrozil group (P < 0.01). TXB(2) lowering effect of Xuezhikang was superior to that of gemfibrozil (P < 0.01). The level of 6-KetO-PGF(1alpha) in the plasma elevated by 65.4% in the Xuezhikang group (P < 0.01) and by 11.7% in the gemfibrozil group (P < 0.01); the effect of Xuezhikang was superior to that of gemfibrozil (P < 0.01).

CONCLUSION

Xuezhikang could markedly decrease the level of TC and LDL-C and elevate that of HDL-C in patients with hyperlipidemia and the effects of Xuezhikang were the same as those of gemfibrozil. TG lowering effect of gemfibrozil was superior to that of Xuezhikang, but Xuezhikang could markedly decrease the level of Lp (a) and regluate the balance between TXA(2) and PGI(2), its effect being superior to that of gemfibrozil.

A double-stranded RNA element from a hypovirulent strain of Rhizoctonia solani occurs in DNA form and is genetically related to the pentafunctional AROM protein of the shikimate pathway

M2 is a double-stranded RNA (dsRNA) element occurring in the hypovirulent isolate Rhs 1A1 of the plant pathogenic basidiomycete Rhizoctonia solani. Rhs 1A1 originated as a sector of the virulent field isolate Rhs 1AP, which contains no detectable amount of the M2 dsRNA. The complete sequence (3,570 bp) of the M2 dsRNA has been determined. A 6.9-kbp segment of total DNA from either Rhs 1A1 or Rhs 1AP hybridizes with an M2-specific cDNA probe. The sequences of M2 dsRNA and of PCR products generated from Rhs 1A1 total DNA were found to be identical. Thus this report describes a fungal host containing full-length DNA copies of a dsRNA element. A major portion of the M2 dsRNA is located in the cytoplasm, whereas a smaller amount is found in mitochondria. Based on either the universal or the mitochondrial genetic code of filamentous fungi, one strand of M2 encodes a putative protein of 754 amino acids. The resulting polypeptide has all four motifs of a dsRNA viral RNA-dependent RNA polymerase (RDRP) and is phylogenetically related to the RDRP of a mitochondrial dsRNA associated with hypovirulence in strain NB631 of Cryphonectria parasitica, incitant of chestnut blight. This polypeptide also has significant sequence similarity with two domains of a pentafunctional polypeptide, which catalyzes the five central steps of the shikimate pathway in yeast and filamentous fungi.

State of hepatitis B virus DNA in leucocytes of hepatitis B patients

Hepatitis B virus (HBV) DNA in leucocytes from 50 hepatitis patients with various patterns of HBV serological markers and serum HBV DNA and 13 normal controls were examined by Southern blot hybridization with 32P-labeled 3.2 Kb HBV DNA. A free form of HBV DNA was observed in leucocytes of 8 patients, 7 of whom were positive for serum HBeAg, and in 6 patients an integrated form of HBV DNA was identified. HBV DNA was not identified in leucocytes from 13 normal controls. The free form of HBV DNA in leucocytes existed as a heterogeneous smear from 2.0 to 3.2 Kb, similar to the pattern in liver and hepatocellular carcinoma cells but different from serum HBV DNA in which the 3.2 Kb band was absent. The banding pattern of the integrated form of HBV DNA in leucocytes varied among different patients. During preparation of white blood cells and purification of HBV DNA probes, it was important to remove plasma contamination and traces of pBR322, respectively. The presence of extrachromosomal DNA sequences partially homologous to pBR322 could cause false results. The presence of a free and integrated form of HBV DNA in leucocytes is important for explaining the biology of HBV, the harbouring and replication sites of extrahepatic origin, the mechanism of recurrent infection, and the rationale of the treatment of hepatitis B.