Effect of chloroprocaine combined with morphine on analgesia, adverse reactions and dynamic changes in inflammation in patients receiving TURP

Purpose: To investigate the influence of chloroprocaine combined with morphine on the analgesic effects, adverse reactions and inflammation factors in patients receiving transurethral resection of the prostate (TURP).Methods: A total of 80 patients with benign prostatic hyperplasia (BPH) in the Fourth Medical Center of Chinese PLA General Hospital, Beijing 100048, China, were divided into morphine group and combination-therapy group (morphine combined with chloroprocaine). Pain index, changes in inflammatory factors and incidence of adverse reactions in the two groups of patients were assessed.Results: The morphine group and combination-therapy group showed basic profile prior to the treatments. Visual Analogue Scale (VAS) scores before operation and 6 h after operation in the morphine group were similar to those in the combination-therapy group, but the scores at 12, 24 and 48 h after operation in the combination-therapy group were significantly lower than those in the morphine group. Similarly, the combination-therapy group showed lower levels of substance P (SP) and bradykinin (BK) at 12, 24 and 48 h after operation than the morphine group (p < 0.05). Both groups exhibited similar levels of serum inflammatory factors before the operation, but the levels decreased in the combination-therapy group when compared with those in the morphine group after operation (p < 0.05). The combination-therapy group also showed a lower incidence of adverse reactions than the morphine group.Conclusion: Chloroprocaine combined with morphine effectively ameliorates postoperative pain, lowers secretion of tumor necrosis factor-alpha (TNF-α) and interleukin-10 (IL-10), and decreases the incidence of postoperative adverse reactions, thus affording a high level of safety after operation

Bradykinin improves postischaemic recovery in the rat heart: role of high energy phosphates, nitric oxide, and prostacyclin

Objective: The aim was to define: (1) whether bradykinin administration during reperfusion improves postischaemic myocardial recovery; (2) whether high energy phosphate compounds are involved in the protective effects of bradykinin; and (3) whether bradykinin-induced release of prostacyclin and nitric oxide mediate the protective effects of bradykinin. Methods: In the Langendorff rat heart preparation, coronary flow, left ventricular developed pressure, and, using 31P magnetic resonance spectroscopy, the high energy phosphate compounds phosphocreatine and β-ATP were assessed during 15 min of global ischaemia and 30 min of reperfusion. Administration of 10−7 M bradykinin was started before ischaemia and maintained throughout the experiment (BK-pre). This was compared to 10−7 M bradykinin given exclusively with reperfusion (BK-post). Then 10−7 M bradykinin was given simultaneously with 10−4 M Nω-nitro-L-arginine-methyl ester (BK-LNAME) or 10−5 M indomethacin (BK-indo). Results: In comparison to control hearts, BK-pre exerted a significant protective effect on the postischaemic recovery of coronary flow [71(5)% v 43(4)%, P < 0.05], left ventricular pressure [81(8)% v 42(5)%, P < 0.05], phosphocreatine [105(4)% v 67(8)%, P < 0.05], and β-ATP [78(9)% v 48(7)%, P < 0.05]. With BK-post, recovery of coronary flow [71(4)% v 43(4)%, P < 0.05] and left ventricular pressure [78(4)% v 42(5)%, P < 0.05] significantly improved; however the recovery of phosphocreatine [70(4)% v 67(8)%, NS] and β-ATP [58(2)% v 48(7)%, NS] was not different from control. When bradykinin and L-NAME or indomethacin was given the beneficial effects of bradykinin on ischaemic hearts were abolished. Conclusions: (1) Bradykinin improved postischaemic myocardial recovery when given before ischaemia or starting exclusively with reperfusion; (2) this was only partially related to a protective action on the high energy phosphate compounds during ischaemia; (3) the beneficial effects of bradykinin on ischaemic hearts are dependent from an unrestrained action of prostacyclin and nitric oxid

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures

Inferring Group-Wise Consistent Multimodal Brain Networks via Multi-View Spectral Clustering

Quantitative modeling and analysis of structural and functional brain networks based on diffusion tensor imaging (DTI) and functional MRI (fMRI) data have received extensive interest recently. However, the regularity of these structural and functional brain networks across multiple neuroimaging modalities and also across different individuals is largely unknown. This paper presents a novel approach to inferring group-wise consistent brain sub-networks from multimodal DTI/resting-state fMRI datasets via multi-view spectral clustering of cortical networks, which were constructed upon our recently developed and validated large-scale cortical landmarks - DICCCOL (Dense Individualized and Common Connectivity-based Cortical Landmarks). We applied the algorithms on DTI data of 100 healthy young females and 50 healthy young males, obtained consistent multimodal brain networks within and across multiple groups, and further examined the functional roles of these networks. Our experimental results demonstrated that the derived brain networks have substantially improved inter-modality and inter-subject consistency

DICCCOL: Dense Individualized and Common Connectivity-Based Cortical Landmarks

Is there a common structural and functional cortical architecture that can be quantitatively encoded and precisely reproduced across individuals and populations? This question is still largely unanswered due to the vast complexity, variability, and nonlinearity of the cerebral cortex. Here, we hypothesize that the common cortical architecture can be effectively represented by group-wise consistent structural fiber connections and take a novel data-driven approach to explore the cortical architecture. We report a dense and consistent map of 358 cortical landmarks, named Dense Individualized and Common Connectivity–based Cortical Landmarks (DICCCOLs). Each DICCCOL is defined by group-wise consistent white-matter fiber connection patterns derived from diffusion tensor imaging (DTI) data. Our results have shown that these 358 landmarks are remarkably reproducible over more than one hundred human brains and possess accurate intrinsically established structural and functional cross-subject correspondences validated by large-scale functional magnetic resonance imaging data. In particular, these 358 cortical landmarks can be accurately and efficiently predicted in a new single brain with DTI data. Thus, this set of 358 DICCCOL landmarks comprehensively encodes the common structural and functional cortical architectures, providing opportunities for many applications in brain science including mapping human brain connectomes, as demonstrated in this work

Using Soil Survey Database to Assess Soil Quality in the Heterogeneous Taihang Mountains, North China

Soil quality evaluation is an effective pathway to understanding the status of soil function and ecosystem productivity. Numerous studies have been made in managed ecosystems and land cover to quantify its effects on soil quality. However, little is coincident regarding soil quality assessment methods and its compatibility in highly heterogeneous soil. This paper used the soil survey database of Taihang Mountains as a case study to: (i) Examine the feasibility of soil quality evaluation with two different indicator methods: Total data set (TDS) and minimum data set (MDS); and (ii) analyze the controlling factors of regional soil quality. Principal component analysis (PCA) and the entropy method were used to calculate soil quality index (SQI). SQI values assessed from the TDS and MDS methods were both significantly correlated with normalized difference vegetation index (p &lt; 0.001), suggesting that both indices were effective to describe soil quality and reflect vegetation growth status. However, the TDS method represented a slightly more accurate assessment than MDS in terms of variance explanation. Boosted regression trees (BRT) models and path analysis showed that soil type and land cover were the most important controlling factors of soil quality, within which soil type had the greatest direct effect and land cover had the most indirect effect. Compared to MDS, TDS is a more sensitive method for assessing regional soil quality, especially in heterogeneous mountains. Soil type is the fundamental factor to determining soil quality. Vegetation and land cover indirectly modulate soil properties and soil quality