肺结节病合并Alternaria alternata所致皮肤链格孢病1例

患者,女,61岁,确诊肺结节病、口服糖皮质激素7月,双手背及腕部红色斑块3个月。组织病理示表皮轻度棘层增厚,真皮浅、中层中性粒细胞、淋巴、组织细胞、浆细胞、多核巨细胞混合性浸润,可见散在双轮廓厚壁酵母样结构。六铵银染色见不规则肿胀菌丝及酵母样厚壁孢子。真菌培养见棕/灰褐色菌落,镜下见棕色分隔孢子。ITS区序列分析鉴定为Alternaria alternate。口服伊曲康唑胶囊200 mg/d,联合外用硝酸舍他康唑乳膏2次/d,连续用药4个月后皮损完全消退,随访半年,未见复发。     

Leptin gene-targeted editing in ob/ob mouse adipose tissue based on the CRISPR/Cas9 system

Gene therapy has become the most effective treatment for monogenic diseases. Congenital LEPTIN deficiency is a rare autosomal recessive monogenic obesity syndrome caused by mutations in the Leptin gene. Ob/ob mouse is a monogenic obesity model, which carries a homozygous point mutation of C to T in Exon 2 of the Leptin gene. Here, we attempted to edit the mutated Leptin gene in ob/ob mice preadipocytes and inguinal adipose tissues using CRISPR/Cas9 to correct the C to T mutation and restore the production of LEPTIN protein by adipocytes. The edited preadipocytes exhibit a correction of 5.5% of Leptin alleles and produce normal LEPTIN protein when differentiated into mature adipocytes. The ob/ob mice display correction of 1.67% of Leptin alleles, which is sufficient to restore the production and physiological functions of LEPTIN protein, such as suppressing appetite and alleviating insulin resistance. Our study suggests CRISPR/Cas9-mediated in situ genome editing as a feasible therapeutic strategy for human monogenic diseases, and paves the way for further research on efficient delivery system in potential future clinical application.     

Experimental warming shifts coupling of carbon and nitrogen cycles in an alpine meadow

增温对高寒草甸生态系统碳氮循环耦合关系的影响 陆地生态系统碳吸收受土壤氮素可用性的调节。然而,全球变化背景下的不同生态系统组分的碳氮比及其所反映的碳氮循环耦合关系尚不十分清楚。本文运用数据同化的方法,将一个高寒草甸增温试验的14组数据同化到草地生态系统模型中,从而评估了增温如何影响陆地生态系统的碳氮循环耦合关系。研究结果表明,增温提高了土壤氮素的有效性,降低了土壤活性碳库的碳氮比,导致植物对土壤氮的吸收增加。但是由于植物叶片吸收的碳比吸收的氮增加更多,使得叶片中碳氮比增加,而根部的碳输入增加则低于氮的增加,导致根部的碳氮比减少。同时,增温降低了凋落物碳氮比,可能是在土壤高氮有效性的条件下,凋落物氮的固定得到增强;而且增温加速了凋落物的分解。同时增温还增加了慢速土壤有机质的碳氮比,使得该土壤碳库的碳固存潜力增大。由于大多数模型在不同的环境中通常使用相对固定的碳氮比,本研究所发现的气候变暖条件下碳氮比的差异变化可为模型参数化提供一个有效的参考,有利于模型对未来气候变化背景下生态系统碳氮耦合关系响应的预测。     

Human bone marrow mesenchymal stem cell-derived extracellular vesicles impede the progression of cervical cancer via the miR-144-3p/CEP55 pathway

Cervical cancer is the most common gynaecological malignancy, with a high incidence rate and mortality rate in middle-aged women. Human bone marrow mesenchymal stem cells (hBMSCs) have been implicated in the initiation and subsequent development of cancer, along with the involvement of extracellular vesicles (EVs) mediating intracellular communication by delivering microRNAs (miRNAs or miRs). This study is aimed at investigating the physiological mechanisms by which EVs-encapsulated miR-144-3p derived from hBMSCs might mediate the progression of cervical cancer. The expression profiles of centrosomal protein, 55 Kd (CEP55) and miR-144-3p in cervical cancer cell lines and tissues, were quantified by RT-qPCR and Western blot analysis. The binding affinity between miR-144-3p and CEP55 was identified using in silico analysis and luciferase activity determination. Cervical cancer cells were co-cultured with EVs derived from hBMSCs that were treated with either miR-144-3p mimic or miR-144-3p inhibitor. Cervical cancer cell proliferation, invasion, migration and apoptosis were detected in vitro. The effects of hBMSCs-miR-144-3p on tumour growth were also investigated in vivo. miR-144-3p was down-regulated, whereas CEP55 was up-regulated in cervical cancer cell lines and tissues. CEP55 was targeted by miR-144-3p, which suppressed cervical cancer cell proliferation, invasion and migration and promoted apoptosis via CEP55. Furthermore, similar results were obtained by hBMSCs-derived EVs carrying miR-144-3p. In vivo assays confirmed the tumour-suppressive effects of miR-144-3p in hBMSCs-derived EVs on cervical cancer. Collectively, hBMSCs-derived EVs-loaded miR-144-3p impedes the development and progression of cervical cancer through target inhibition of CEP55, therefore providing us with a potential therapeutic target for treating cervical cancer.     

Identification of five small heat shock protein genes in Spodoptera frugiperda and expression analysis in response to different environmental stressors

Spodoptera frugiperda (J. E. Smith) is a highly adaptable polyphagous migratory pest in tropical and subtropical regions. Small heat shock proteins (sHsps) are molecular chaperones that play important roles in the adaptation to various environment stressors. The present study aimed to clarify the response mechanisms of S. frugiperda to various environmental stressors. We obtained five S. furcifera sHsp genes (SfsHsp21.3, SfsHsp20, SfsHsp20.1, SfsHsp19.3, and SfsHsp29) via cloning. The putative proteins encoded by these genes contained a typical α-crystallin domain. The expression patterns of these genes during different developmental stages, in various tissues of male and female adults, as well as in response to extreme temperatures and UV-A stress were studied via real-time quantitative polymerase chain reaction. The results showed that the expression levels of all five SfsHsp genes differed among the developmental stages as well as among the different tissues of male and female adults. The expression levels of most SfsHsp genes under extreme temperatures and UV-A-induced stress were significantly upregulated in both male and female adults. In contrast, those of SfsHsp20.1 and SfsHsp19.3 were significantly downregulated under cold stress in male adults. Therefore, the different SfsHsp genes of S. frugiperda play unique regulatory roles during development as well as in response to various environmental stressors.     

Advancement and properties of circular RNAs in prostate cancer: An emerging and compelling frontier for discovering

Prostate cancer (PC) is the most common carcinoma among men worldwide which results in 26% of leading causes of cancer-related death. However, the ideal and effective molecular marker remains elusive. CircRNA, initially observed in plant-infected viruses and Sendai virus in 1979, is generated from pre-mRNA back-splicing and comes in to play by adequate expression. The differential expression in prostate tissues compared with the control reveals the promising capacity in modulating processes including carcinogenesis and metastasis. However, the biological mechanisms of regulatory network in PC needs to systemically concluded. In this review, we enlightened the comprehensive studies on the definite mechanisms of circRNAs affecting tumor progression and metastasis. What''s more, we validated the potential clinical application of circRNAs serving as diagnostic and prognostic biomarker. The discussion and analysis in circRNAs will broaden our knowledge of the pathogenesis of PC and further optimize the current therapies against different condition.     

Novel artificial intelligence machine learning approaches to precisely predict survival and site-specific recurrence in cervical cancer: A multi-institutional study

BackgroundMachine learning (ML) has been gradually integrated into oncologic research but seldom applied to predict cervical cancer (CC), and no model has been reported to predict survival and site-specific recurrence simultaneously. Thus, we aimed to develop ML models to predict survival and site-specific recurrence in CC and to guide individual surveillance.MethodsWe retrospectively collected data on CC patients from 2006 to 2017 in four hospitals. The survival or recurrence predictive value of the variables was analyzed using multivariate Cox, principal component, and K-means clustering analyses. The predictive performances of eight ML models were compared with logistic or Cox models. A novel web-based predictive calculator was developed based on the ML algorithms.ResultsThis study included 5112 women for analysis (268 deaths, 343 recurrences): (1) For site-specific recurrence, larger tumor size was associated with local recurrence, while positive lymph nodes were associated with distant recurrence. (2) The ML models exhibited better prognostic predictive performance than traditional models. (3) The ML models were superior to traditional models when multiple variables were used. (4) A novel predictive web-based calculator was developed and externally validated to predict survival and site-specific recurrence.ConclusionML models might be a better analytic approach in CC prognostic prediction than traditional models as they can predict survival and site-specific recurrence simultaneously, especially when using multiple variables. Moreover, our novel web-based calculator may provide clinicians with useful information and help them make individual postoperative follow-up plans and further treatment strategies.