The impact of donor hepatitis B virus infection on transplant outcomes in deceased donor kidney transplantation recipients.

Background: The use of hepatitis B virus (HBV)-positive donor kidneys to expand the donor pool has been implemented, but limited evidence exists regarding their impact on transplant outcomes. This study aimed to investigate the effects of donor HBV infection on transplant outcomes. Methods: Donor and recipient data between 2015 and 2021 were collected. A total of 743 kidney transplant cases were screened, including 94 donor hepatitis B surface antigen (HBsAg)+/recipient HBsAg- (D+R-) and 649 donor HBsAg-/recipient HBsAg- (D-R-) cases. The analysis endpoints included recipient HBV infection, delayed graft function (DGF), peak estimated glomerular filtration rate (eGFR) within 12 months, recipient survival, and death-censored graft survival (DCGS). Results: The D+R- group had a significantly higher risk of HBV infection compared to the D-R- group (6/72 vs. 3/231; relative risk, 6.4; p = 0.007). The risk of HBV transmission decreased significantly with increasing hepatitis B surface antibody (HBsAb) titer (p for trend = 0.003). Furthermore, the D+R- group did not exhibit an increased risk of DGF compared to the D-R- group (odds ratio, 0.70; p = 0.51) in the multivariable mixed model. Both groups had similar peak eGFR within 12 months (ß = 1.01, p = 0.71), and this had no impact on patient survival (hazard ratio [HR], 0.36; p = 0.10) and DCGS (HR, 0.79, p = 0.59) in the shared-frailty Cox model. Conclusion: The use of HBsAg-positive donor kidneys appears relatively safe for HBV-immunized recipients in the short term. D+R- does not negatively affect graft function recovery and provides comparable posttransplant outcomes. Maintaining an HBsAb titer over 100 IU/L before transplantation is critical to reduce the risk of HBV transmission.

Comprehensive biochemical analysis and nutritional evaluation of fatty acid and amino acid profiles in eight seahorse species (Hippocampus spp.).

Seahorses are increasingly recognized for their nutritional potential, which underscores the necessity for comprehensive biochemical analyses. This study aims to investigate the fatty acid and amino acid compositions of eight seahorse species, including both genders of Hippocampus trimaculatus, Hippocampus kelloggi, Hippocampus abdominalis, and Hippocampus erectus, to evaluate their nutritional value. We employed Gas Chromatography-Mass Spectrometry (GC-MS) and High-Performance Liquid Chromatography (HPLC) to analyze the fatty acid and amino acid profiles of the seahorse species. GC-MS was used to detect 34 fatty acid methyl esters, while HPLC provided detailed amino acid profiles. GC-MS analysis demonstrated high precision with relative standard deviations (RSDs) generally below 2.53 %, satisfactory repeatability (RSDs from 6.55 % to 8.73 %), and stability (RSDs below 2.82 %). Recovery rates for major fatty acids ranged from 98.73 % to 109.12 %. HPLC analysis showed strong separation of amino acid profiles with theoretical plate numbers exceeding 5000. Precision tests yielded RSDs below 1.23 %, with reproducibility and stability tests showing RSDs below 2.73 % and 2.86 %, respectively. Amino acid recovery rates ranged from 97.58 % to 104.66 %. Nutritional analysis revealed significant variations in fatty acid content among the species. Female H. erectus showed higher levels of hexadecanoic acid and saturated fatty acids, while male H. abdominalis had lower concentrations of n-3 full cis 4,7,10,13,16,19-docosahexaenoic acid (DHA). Total lipid yields varied from 3.2491 % to 12.3175 %, with major fatty acids constituting 17.9717 %-74.6962 % of total lipids. In conclusion, this study provides essential insights into the fatty acid and amino acid composition of seahorses, supporting their potential as valuable dietary supplements. The differences between genders in specific fatty acids suggest a nuanced nutritional profile that could be exploited for targeted dietary applications. Further research is needed to explore the seasonal and environmental variations affecting seahorse biochemical composition.

Deep learning-enabled classification of kidney allograft rejection on whole slide histopathologic images.

Background: Diagnosis of kidney transplant rejection currently relies on manual histopathological assessment, which is subjective and susceptible to inter-observer variability, leading to limited reproducibility. We aim to develop a deep learning system for automated assessment of whole-slide images (WSIs) from kidney allograft biopsies to enable detection and subtyping of rejection and to predict the prognosis of rejection. Method: We collected H&E-stained WSIs of kidney allograft biopsies at 400x magnification from January 2015 to September 2023 at two hospitals. These biopsy specimens were classified as T cell-mediated rejection, antibody-mediated rejection, and other lesions based on the consensus reached by two experienced transplant pathologists. To achieve feature extraction, feature aggregation, and global classification, we employed multi-instance learning and common convolution neural networks (CNNs). The performance of the developed models was evaluated using various metrics, including confusion matrix, receiver operating characteristic curves, the area under the curve (AUC), classification map, heat map, and pathologist-machine confrontations. Results: In total, 906 WSIs from 302 kidney allograft biopsies were included for analysis. The model based on multi-instance learning enables detection and subtyping of rejection, named renal rejection artificial intelligence model (RRAIM), with the overall 3-category AUC of 0.798 in the independent test set, which is superior to that of three transplant pathologists under nearly routine assessment conditions. Moreover, the prognosis models accurately predicted graft loss within 1 year following rejection and treatment response for rejection, achieving AUC of 0.936 and 0.756, respectively. Conclusion: We first developed deep-learning models utilizing multi-instance learning for the detection and subtyping of rejection and prediction of rejection prognosis in kidney allograft biopsies. These models performed well and may be useful in assisting the pathological diagnosis.

Geometric Understanding of Discriminability and Transferability for Visual Domain Adaptation.

To overcome the restriction of identical distribution assumption, invariant representation learning for unsupervised domain adaptation (UDA) has made significant advances in computer vision and pattern recognition communities. In UDA scenario, the training and test data belong to different domains while the task model is learned to be invariant. Recently, empirical connections between transferability and discriminability have received increasing attention, which is the key to understand the invariant representations. However, theoretical study of these abilities and in-depth analysis of the learned feature structures are unexplored yet. In this work, we systematically analyze the essentials of transferability and discriminability from the geometric perspective. Our theoretical results provide insights into understanding the co-regularization relation and prove the possibility of learning these abilities. From methodology aspect, the abilities are formulated as geometric properties between domain/cluster subspaces (i.e., orthogonality and equivalence) and characterized as the relation between the norms/ranks of multiple matrices. Two optimization-friendly learning principles are derived, which also ensure some intuitive explanations. Moreover, a feasible range for the co-regularization parameters is deduced to balance the learning of geometric structures. Based on the theoretical results, a geometry-oriented model is proposed for enhancing the transferability and discriminability via nuclear norm optimization. Extensive experiment results validate the effectiveness of the proposed model in empirical applications, and verify that the geometric abilities can be sufficiently learned in the derived feasible range.

When Invariant Representation Learning Meets Label Shift: Insufficiency and Theoretical Insights.

As a crucial step toward real-world learning scenarios with changing environments, dataset shift theory and invariant representation learning algorithm have been extensively studied to relax the identical distribution assumption in classical learning setting. Among the different assumptions on the essential of shifting distributions, generalized label shift (GLS) is the latest developed one which shows great potential to deal with the complex factors within the shift. In this paper, we aim to explore the limitations of current dataset shift theory and algorithm, and further provide new insights by presenting a comprehensive understanding of GLS. From theoretical aspect, two informative generalization bounds are derived, and the GLS learner are proved to be sufficiently close to optimal target model from the Bayesian perspective. The main results show the insufficiency of invariant representation learning, and prove the sufficiency and necessity of GLS correction for generalization, which provide theoretical supports and innovations for exploring generalizable model under dataset shift. From methodological aspect, we provide a unified view of existing shift correction frameworks, and propose a kernel embedding-based correction algorithm (KECA) to minimize the generalization error and achieve successful knowledge transfer. Both theoretical results and extensive experiment evaluations demonstrate the sufficiency and necessity of GLS correction for addressing dataset shift and the superiority of proposed algorithm.

Widely targeted metabolomics-based analysis of the impact of L. plantarum and L. paracasei fermentation on rosa roxburghii Tratt juice.

Rosa roxburghii Tratt fruits (RRT) exhibit extremely high nutritional and medicinal properties due to its unique phytochemical composition. Probiotic fermentation is a common method of processing fruits. Variations in the non-volatile metabolites and bioactivities of RRT juice caused by different lactobacilli are not well understood. Therefore, we aimed to profile the non-volatile components and investigate the impact of L. plantarum fermentation (LP) and L. paracasei fermentation (LC) on RRT juice (the control, CG). There were both similarities and differences in the effects of LP and LC on RRT juice. Both of the two strains significantly increased the content of total phenolic, total flavonoid, and some bioactive compounds such as 2-hydroxyisocaproic acid, hydroxytyrosol and indole-3-lactic acid in RRT juice. Interestingly, compared with L. paracasei, L. plantarum showed better ability to increase the content of total phenolic and these valuable compounds, as well as certain bioactivities. The antioxidant capacity and α-glucosidase inhibitory activity of RRT juice were notably enhanced after the fermentations, whereas its cholesterol esterase inhibitory activity was reduced significantly. Moreover, a total of 1466 metabolites were identified in the unfermented and fermented RRT juices. There were 278, 251 and 134 differential metabolites in LP vs CG, LC vs CG, LC vs LP, respectively, most of which were upregulated. The key differential metabolites were classified into amino acids and their derivatives, organic acids, nucleotides and their analogues, phenolic acids and alkaloids, which can serve as potential markers for authentication and discrimination between the unfermented and lactobacilli fermented RRT juice samples. The KEGG enrichment analysis uncovered that metabolic pathways, purine metabolism, nucleotide metabolism and ABC transporters contributed mainly to the formation of unique composition of fermented RRT juice. These results provide good coverage of the metabolome of RRT juice in both unfermented and fermented forms and also provide a reference for future research on the processing of RRT or other fruits.

Characterization and prebiotic potential of polysaccharides from Rosa roxburghii Tratt pomace by ultrasound-assisted extraction.

In this study, polysaccharides (RRTPs) were extracted from Rosa roxburghii Tratt pomace by hot water or ultrasound (US)-assisted extraction. The structural properties and potential prebiotic functions of RRTPs were investigated. Structural characterization was conducted through HPAEC, HPGPC, GC-MS, FT-IR and SEM. Chemical composition analysis revealed that RRTPs extracted by hot water (RRTP-HW) or US with shorter (RRTP-US-S) or longer duration (RRTP-US-L) all consisted of galacturonic acid, galactose, glucose, arabinose, rhamnose and glucuronic acid in various molar ratio. US extraction caused notable reduction in molecular weight of RRTPs but no significant changes in primary structures. Fecal fermentation showed RRTPs could reshape microbial composition toward a healthier balance, leading to a higher production of beneficial metabolites including total short-chain fatty acids, curcumin, noopept, spermidine, 3-feruloylquinic acid and citrulline. More beneficial shifts in bacterial population were observed in RRTP-HW group, while RRTP-US-S had stronger ability to stimulate bacterial short-chain fatty acids production. Additionally, metabolic profiles with the intervention of RRTP-HW, RRTP-US-S or RRTP-US-L were significantly different from each other. The results suggested RRTPs had potential prebiotic effects which could be modified by power US via molecular weight degradation.

Characterization of bacterial diversity and screening of cellulose-degrading bacteria in the gut system of Glenea cantor (Fabricius) larvae.

The intestinal bacteria of longhorn beetles would be ideal targets for pest control and lignocellulosic resources by destroying or exploiting their cellulose-degrading function. This article aims to investigate the diversity and community structure of intestinal bacteria the oligophagous longhorn beetle Glenea cantor. Additionally, it seeks to identify the presence of lignocellulose-degrading bacteria in the gut, and explore their role in consuming host kapok trees Bombax malabaricum. In this study, the bacterial community from G. cantor was examined by Illumina sequencing of 16S ribosomal RNA (rRNA) targeting the V3 and V4 regions. A total of 563,201 valid sequences and 814 OTUs were obtained. The dominant phyla were Proteobacteria, and the dominant genera were Acinetobacter and Lactococcus. The analysis of microbial diversity revealed a high bacterial diversity in the samples, with the gut bacteria playing a crucial role in the physiological activities of the host, particularly, 9 genera of intestinal bacteria with cellulose degradation function were found, highlighting their vital role in cellulose degradation. Five strains of cellulose-degrading bacteria, belonging to the genus Pseudomonas, were obtained from the intestinal tract of G. cantor larvae using traditional isolation and culture techniques as well as 16S rDNA sequencing. Among these strains, A4 exhibited a cellulase activity of 94.42 ± 0.42 U/mL, while A5 displayed the highest filter paper enzyme activity of 127.46 ± 3.54 U/mL. These results offered valuable insights into potential targets for pest control through internal attack digestion and cellulose-degrading bacteria in longhorn beetles.

Physical Stimulation Methods Developed for In Vitro Neuronal Differentiation Studies of PC12 Cells: A Comprehensive Review.

PC12 cells, which are derived from rat adrenal pheochromocytoma cells, are widely used for the study of neuronal differentiation. NGF induces neuronal differentiation in PC12 cells by activating intracellular pathways via the TrkA receptor, which results in elongated neurites and neuron-like characteristics. Moreover, the differentiation requires both the ERK1/2 and p38 MAPK pathways. In addition to NGF, BMPs can also induce neuronal differentiation in PC12 cells. BMPs are part of the TGF-ß cytokine superfamily and activate signaling pathways such as p38 MAPK and Smad. However, the brief lifespan of NGF and BMPs may limit their effectiveness in living organisms. Although PC12 cells are used to study the effects of various physical stimuli on neuronal differentiation, the development of new methods and an understanding of the molecular mechanisms are ongoing. In this comprehensive review, we discuss the induction of neuronal differentiation in PC12 cells without relying on NGF, which is already established for electrical, electromagnetic, and thermal stimulation but poses a challenge for mechanical, ultrasound, and light stimulation. Furthermore, the mechanisms underlying neuronal differentiation induced by physical stimuli remain largely unknown. Elucidating these mechanisms holds promise for developing new methods for neural regeneration and advancing neuroregenerative medical technologies using neural stem cells.

[Clinical characteristics and prognosis of children with perianal fistulizing Crohn's disease]. / å„¿ç«¥è‚›å‘¨ç˜˜ç®¡åž‹å ‹ç½—æ©ç— çš„ä¸´åºŠç‰¹å¾åŠé¢„åŽ.

OBJECTIVES: To investigate the clinical characteristics, treatment, and prognosis of children with perianal fistulizing Crohn's disease (pfCD). METHODS: A retrospective analysis was conducted on the children, aged 6-17 years, who were diagnosed with Crohn's disease (CD) from April 2015 to April 2023. According to the presence or absence of perianal fistulizing lesions, they were divided into two groups: pfCD (n=60) and non-pfCD (n=82). The two groups were compared in terms of clinical characteristics, treatment, and prognosis. RESULTS: The incidence of pfCD was 42.3% (60/142). The proportion of males in the pfCD group was higher than that in the non-pfCD group. Compared with the non-pfCD group, the pfCD group had a significantly higher proportion of children with involvement of the colon and small intestine or those with upper gastrointestinal lesions (P<0.05). Compared with the non-pfCD group, the pfCD group had a significantly higher rate of use of infliximab during both induction and maintenance treatment (P<0.05). In the pfCD group, the children with complex anal fistula accounted for 62% (37/60), among whom the children receiving non-cutting suspended line drainage accounted for 62% (23/37), which was significantly higher than the proportion among the children with simple anal fistula patients (4%, 1/23) (P<0.05). There were no significant differences between the two groups in mucosal healing rate and clinical remission rate at week 54 of treatment (P>0.05). The pfCD group achieved a fistula healing rate of 57% (34/60) at week 54, and the children with simple anal fistula had a significantly higher rate than those with complex anal fistula (P<0.05). CONCLUSIONS: There is a high incidence rate of pfCD in children with CD, and among the children with pfCD, there is a high proportion of children with the use of biological agents. There is a high proportion of children receiving non-cutting suspended line drainage among the children with complex anal fistula. The occurrence of pfCD should be closely monitored during the follow-up in children with CD.

Anti-apoptotic effect of adrenomedullin gene delivery on Leydig cells by suppressing TGF-ß1 via the Hippo signaling pathway.

This study aims to establish whether adrenomedullin (ADM) is capable to restore the steroidogenic functions of Leydig cells by suppressing transforming growth factor-ß1 (TGF-ß1) through Hippo signaling. Primary Leydig cells were treated with lipopolysaccharide (LPS), an adeno-associated virus vector that expressed ADM (Ad-ADM) or sh-RNA of TGF-ß1 (Ad-sh-TGF-ß1). The cell viability and medium concentrations of testosterone were detected. Gene expression and protein levels were determined for steroidogenic enzymes, TGF-ß1, RhoA, YAP, TAZ and TEAD1. The role of Ad-ADM in the regulation of TGF-ß1 promoter was confirmed by ChIP and Co-IP. Similar to Ad-sh-TGF-ß1, Ad-ADM mitigated the decline in the number of Leydig cells and plasma concentrations of testosterone by restoring the gene and protein levels of SF-1, LRH1, NUR77, StAR, P450scc, 3ß-HSD, CYP17 and 17ß-HSD. Similar to Ad-sh-TGF-ß1, Ad-ADM not only inhibited the LPS-induced cytotoxicity and cell apoptosis but also restored the gene and protein levels of SF-1, LRH1, NUR77, StAR, P450scc, 3ß-HSD, CYP17 and 17ß-HSD, along with the medium concentrations of testosterone in LPS-induced Leydig cells. Like Ad-sh-TGF-ß1, Ad-ADM improved LPS-induced TGF-ß1 expression. In addition, Ad-ADM suppressed RhoA activation, enhanced the phosphorylation of YAP and TAZ, reduced the expression of TEAD1 which interacted with HDAC5 and then bound to TGF-ß1 gene promoter in LPS-exposed Leydig cells. It is thus suspected that ADM can exert anti-apoptotic effect to restore the steroidogenic functions of Leydig cells by suppressing TGF-ß1 through Hippo signaling.

Cu-MOFs based photocatalyst triggered antibacterial platform for wound healing: 2D/2D Schottky junction and DFT calculation.

Herein, we developed a multimodal antibacterial nanoplatform via synergism effect including knife-effect, photothermal, photocatalytic induced reactive oxygen species (ROS), and Cu2+ inherent attribute. Typically, 0.8-TC/Cu-NS possesses higher photothermal property with the higher photothermal conversion efficiency of 24% and the moderate temperature up to 97 °C. Meanwhile, 0.8-TC/Cu-NS exhibits the more active ROS, 1O2 and ·O2-. Hence, 0.8-TC/Cu-NS possesses best antibacterial properties against S. aureus and E. coli in vitro with efficiency of 99.94%/99.97% under near-infrared (NIR) light, respectively. In the therapeutic practical use for wound healing of Kunming mice, this system exhibits outstanding curing capacity and good biocompatibility. Based on the electron configuration measurement and density functional theory (DFT) simulation, it is confirmed that the electrons on CB of Cu-TCPP flow fleetingly to MXene trough the interface, with redistribution of charge and band upward bending over Cu-TCPP. As a result, the self-assembled 2D/2D interfacial Schottky junction have made great favor to accelerate photogenerated charges mobility, hamper charge recombination, and increases the photothermal/photocatalytic activity. This work gives us a hint to mostly design the multimodal synergistic nanoplatform under NIR light in biological applications without drug resistance.

Four New Polyhydroxy Cyclohexanes from the Stems of Fissistigma tientangense.

Four undescribed polyhydroxy cyclohexanes, fissoxhydrylenes A-D (1-4), together with two known biogenetically related polyhydroxy cyclohexanes (5 and 6) were isolated from the stems of Fissistigma tientangense Tsiang et P. T. Li. Their structures were elucidated by detailed analysis of NMR, HR-ESI-MS, IR, UV and Optical rotations data. The absolute configuration of 1 was confirmed by X-ray crystallographic. The absolute configurations of 2-4 were confirmed by chemical reaction and optical rotations. Compound 4 represent the first example of a no substituent polyhydroxy cyclohexanes from natural products. All isolated compounds were evaluated for their anti-inflammatory activities against the lipopolysaccharide-induced nitric oxide (NO) production in mouse macrophage RAW 264.7 cells in vitro. Compounds 3 and 4 showed inhibitory activities with the IC50 values of 16.63±0.06 µM and 14.38±0.08 µM, respectively.

Guaiane-Type Sesquiterpenes from the Stems of Fissistigma oldhamii.

Two new guaiane-type sesquiterpenes dysodensiols J and L, one new natural product dysodensiol K together with four known biogenetically related guaiane-type sesquiterpenes were isolated from the stems of Fissistigma oldhamii. Their structures were elucidated by detailed analysis of NMR, HR-ESI-MS, IR and Optical rotations data. Compound 1 contains an uncommon five-membered ether ring. The inhibitory effect of all compounds on the proliferation of primary synovial cells was evaluated. Compound 3 showed inhibitory activity with an IC50 value of 6.8 µM. Compounds 5-7 exhibited moderate inhibitory activity with IC50 values of 23.8, 26.6, and 27.1 µM, respectively.

Consensus for criteria of running a pediatric inflammatory bowel disease center using a modified Delphi approach.

BACKGROUND: Good quality of care for inflammatory bowel disease (IBD) depends on high-standard management and facility in the IBD center. Yet, there are no clear measures or criteria for evaluating pediatric IBD (PIBD) center in China. The aim of this study was to develop a comprehensive set of quality indicators (QIs) for evaluating PIBD center in China. METHODS: A modified Delphi consensus-based approach was used to identify a set of QIs of structure, process, and outcomes for defining the criteria. The process included an exhaustive search using complementary approaches to identify potential QIs, and two web-based voting rounds to select the QIs defining the criteria for PIBD center. RESULTS: A total of 101 QIs (35 structures, 48 processes and 18 outcomes) were included in this consensus. Structure QIs focused on the composition of multidisciplinary team, facilities and services that PIBD center should provide. Process QIs highlight core requirements in diagnosing, evaluating, treating PIBD, and disease follow-up. Outcome QIs mainly included criteria evaluating effectiveness of various interventions in PIBD centers. CONCLUSION: The present Delphi consensus developed a set of main QIs that may be useful for managing a PIBD center. Video Abstract.

Evaluation of heavy metal pollution with uneven spatial sampling distribution based on Voronoi area density.

Ecological risk index and Voronoi diagram have been extensively used as a diagnostic guide for heavy metal pollution to support people in-depth analysis of the possibility of various contamination sources causing damage to social production, life, and the ecological environment. However, under the condition of uneven distribution of detection points, there are often situations where the Voronoi polygon area corresponding to a large degree of pollution is small or the area of the Voronoi polygon is great with a low level of pollution, and using the Voronoi area weighting or the Voronoi area density may ignore heavily polluted local areas. This study proposes the Voronoi density-weighted summation to accurately measure the concentration and diffusion of heavy metal pollution in the target area for the above issues. Then, we propose a contribution value method based on k-means to determine the number of divisions to ensure the prediction accuracy and computational cost at the same time. Moreover, applying local entropy deepens the understanding of local regional and overall system situations. Through four representative regions, the results show that the proposed whole scheme based on Voronoi diagram can effectively predict and evaluate the spatial distribution of heavy metal pollution, which provides a theoretical basis for comprehending and exploring the complex pollution environment.

BuresNet: Conditional Bures Metric for Transferable Representation Learning.

As a fundamental manner for learning and cognition, transfer learning has attracted widespread attention in recent years. Typical transfer learning tasks include unsupervised domain adaptation (UDA) and few-shot learning (FSL), which both attempt to sufficiently transfer discriminative knowledge from the training environment to the test environment to improve the model's generalization performance. Previous transfer learning methods usually ignore the potential conditional distribution shift between environments. This leads to the discriminability degradation in the test environments. Therefore, how to construct a learnable and interpretable metric to measure and then reduce the gap between conditional distributions is very important in the literature. In this article, we design the Conditional Kernel Bures (CKB) metric for characterizing conditional distribution discrepancy, and derive an empirical estimation with convergence guarantee. CKB provides a statistical and interpretable approach, under the optimal transportation framework, to understand the knowledge transfer mechanism. It is essentially an extension of optimal transportation from the marginal distributions to the conditional distributions. CKB can be used as a plug-and-play module and placed onto the loss layer in deep networks, thus, it plays the bottleneck role in representation learning. From this perspective, the new method with network architecture is abbreviated as BuresNet, and it can be used extract conditional invariant features for both UDA and FSL tasks. BuresNet can be trained in an end-to-end manner. Extensive experiment results on several benchmark datasets validate the effectiveness of BuresNet.

Case report: Application of nonsurgical method in saving transplant renal vein thrombosis caused by acute diarrhea.

Transplant renal vein thrombosis is a rare complication after kidney transplantation, which can seriously threaten graft survival. Though the measures like thrombolytic therapy or operative intervention could be taken to deal with this complication, allograft loss is the most common outcome. Thus, early finding as well as decisive intervention is crucial to saving the graft. Here we present a 46-year-old male patient who underwent kidney transplantation from a cadaveric donor who developed a transplant renal venous thrombosis induced by acute diarrhea more than 1 year after renal transplantation with an initial symptom of sudden anuria and pain in the graft area. Subsequently, serum creatinine levels increased to 810.0 µmol/L. Pelvic CT showed increased vascular density of the transplanted kidney, and contrast-enhanced ultrasound confirmed venous thrombosis. The patient was treated with heparin sodium alone and diuresis gradually resumed. After more than 1 year of follow-up, serum creatinine returned to the baseline level prior to thrombosis. Our case indicates that quick ancillary examination and treatment without hesitation would be indispensable in rescuing allografts with renal vein thrombus. Unfractionated heparin can be recommended as an effective treatment for mid-long-term renal transplantation patients with renal vein thrombosis.

SP600125 Enhances Temperature-Controlled Repeated Thermal Stimulation-Induced Neurite Outgrowth in PC12-P1F1 Cells.

This study evaluated the mechanism of temperature-controlled repeated thermal stimulation (TRTS)-mediated neuronal differentiation. We assessed the effect of SP600125, a c-Jun N-terminal kinase (JNK) inhibitor, on neuronal differentiation of rat PC12-P1F1 cells, which can differentiate into neuron-like cells by exposure to TRTS or neurotrophic factors, including bone morphogenetic protein (BMP) 4. We evaluated neuritogenesis by incubating the cells under conditions of TRTS and/or SP600125. Cotreatment with SP600125 significantly enhanced TRTS-mediated neuritogenesis, whereas that with other selective mitogen-activated protein kinase (MAPK) inhibitors did not-e.g., extracellular signal-regulated kinase (ERK)1/2 inhibitor U0126, and p38 MAPK inhibitor SB203580. We tried to clarify the mechanism of SP600125 action by testing the effect of U0126 and the BMP receptor inhibitor LDN193189 on the SP600125-mediated enhancement of intracellular signaling. SP600125-enhanced TRTS-induced neuritogenesis was significantly inhibited by U0126 or LDN193189. Gene expression analysis revealed that TRTS significantly increased ß3-Tubulin, MKK3, and Smad7 gene expressions. Additionally, Smad6 and Smad7 gene expressions were substantially attenuated through SP600125 co-treatment during TRTS. Therefore, SP600125 may partly enhance TRTS-induced neuritogenesis by attenuating the negative feedback loop of BMP signaling. Further investigation of the mechanisms underlying the effect of SP600125 during TRTS-mediated neuritogenesis may contribute to the future development of regenerative neuromedicine.

Local adrenomedullin gene delivery inhibits Leydig cell dysfunction by rescuing steroidogenic enzymes in vivo.

Adrenomedullin (ADM) has beneficial effects on Leydig cells under pathological conditions, including lipopolysaccharide (LPS)-induced orchitis. Our previous studies demonstrated that ADM exerts a restorative effect on steroidogenesis in LPS-treated primary rat Leydig cells by attenuating oxidative stress, inflammation and apoptosis. In this study, we aim to investigate whether ADM inhibits Leydig cell dysfunction by rescuing steroidogenic enzymes in vivo. Rats were administered with LPS and injected with Ad-ADM, an adeno-associated virus vector that expressed ADM. Then, rat testes were collected for 3ß-hydroxysteroid dehydrogenase (3ß-HSD) immunofluorescence staining. Steroidogenic enzymes or steroidogenic regulatory factors or protein, including steroidogenic factor-1 (SF-1), liver receptor homologue-1 (LRH1), Nur77, steroidogenic acute regulatory protein (StAR), cytochrome P450 cholesterol side chain cleavage enzyme (P450scc), 3ß-HSD, cytochrome P450 17α-hydroxylase/17, 20 lyase (CYP17) and 17ß-hydroxysteroid dehydrogenase (17ß-HSD), were detected via gene expression profiling and western blot analysis. Plasma testosterone concentrations were measured. Results showed that ADM may inhibit Leydig cell dysfunction by rescuing steroidogenic enzymes and steroidogenic regulatory factors in vivo. The reduction in the number of Leydig cells after LPS exposure was reversed by ADM. ADM rescued the gene or protein levels of SF-1, LRH1, Nur77, StAR, P450scc, 3ß-HSD, CYP17 and 17ß-HSD and plasma testosterone concentrations. To summarize ADM could rescue some important steroidogenic enzymes, steroidogenic regulatory factors and testosterone production in Leydig cells in vivo.