Photodynamic Topical Antimicrobial Therapy for Infected Diabetic Foot Ulcers in Patients With Diabetes: A Case Series.
- 作者列表："Brocco E","Curci V","Da Ros R","Miranda C","Boschetti G","Barone S","Tedeschi A","Salutini E","Anichini R
:Diabetic foot ulcers (DFUs) are common, complex, costly complications, associated with frequent recurrences and increased morbidity and mortality. DFUs can be prevented and their healing can be mostly influenced by appropriately and aggressively managing any infection, but the role of antiseptic therapies in reducing healing time lacks sufficient evidence. Several therapeutic interventions have been developed based on the principles of photomedicine to overcome the issue of poor drug circulation in infected areas, with the aim of killing microbial agents while leaving the surrounding host cells unharmed. Such techniques use absorption of photons by specific chromophores. Among these, RLP068 is a tetracationic Zn(II) phthalocyanine derivative activated by exposure to red light, used as a topical treatment for superficial bacterial and fungal infections. The photoactivation of RLP068 results in the production of singlet oxygen and other reactive oxygen species, able to affect a range of cellular targets, including cell membrane and/or wall, cytoplasm, and cellular components, resulting in a rapid, broad range, bactericidal and fungicidal effect. The phase IIa study showed that photoactivated RPL068 is capable of inducing a dose-dependent reduction in total and pathogen microbial load in infected diabetic foot ulcers. In this article, a case series of 22 DFU treated with photoactivated RLP068 at 5 different centers in Italy is presented. Considering microbial agents reduction, ulcer healing facilitation, healing rate (9 DFUs out of 22), and amputation rate (only 1 case over 22), the decrease in the cost of DFU seems to be a point in favor of RLP068 and its cost-effectiveness.
: 糖尿病足溃疡 (DFUs) 是常见、复杂、昂贵的并发症，与频繁复发和发病率及死亡率增加有关。DFUs 是可以预防的，其愈合主要受适当和积极管理任何感染的影响，但防腐治疗在减少愈合时间方面的作用缺乏足够的证据。基于光医学原理开发了几种治疗干预措施，以克服感染区域药物循环不良的问题，目的是杀死微生物制剂，同时使周围宿主细胞不受伤害。这种技术利用特定发色团对光子的吸收。其中，RLP068 是一种通过暴露于红光激活的四环素 Zn(II) 酞菁衍生物，用作表面细菌和真菌感染的局部治疗。RLP068 的光活化导致单线态氧和其他活性氧的产生，能够影响一系列细胞靶点，包括细胞膜和/或细胞壁、细胞质和细胞成分,产生快速、广泛的杀菌和杀真菌作用。IIa 期研究表明，光活化 RPL068 能够诱导感染糖尿病足溃疡的总和病原体微生物负荷的剂量依赖性降低。本文介绍了意大利 5 个不同中心用光活化 RLP068 治疗 22 DFU 的病例系列。综合考虑微生物制剂减少、溃疡愈合易化、愈合率 (22 例中有 9 例 DFUs) 、截肢率 (仅 1 例超过 22 例),DFU 成本的降低似乎是有利于 RLP068 及其成本效益的一点。
METHODS:Aims We aimed to develop a prediction model based on clinical and biochemical variables for gestational diabetes mellitus (GDM) based on the 2013 World Health Organization (WHO) criteria. Methods A total of 1843 women from a Belgian multi-centric prospective cohort study underwent universal screening for GDM. Using multivariable logistic regression analysis, a model to predict GDM was developed based on variables from early pregnancy. The performance of the model was assessed by receiver-operating characteristic (AUC) analysis. To account for over-optimism, an eightfold cross-validation was performed. The accuracy was compared with two validated models (van Leeuwen and Teede). Results A history with a first degree relative with diabetes, a history of smoking before pregnancy, a history of GDM, Asian origin, age, height and BMI were independent predictors for GDM with an AUC of 0.72 [95% confidence interval (CI) 0.69–0.76)]; after cross-validation, the AUC was 0.68 (95% CI 0.64–0.72). Adding biochemical variables, a history of a first degree relative with diabetes, a history of GDM, non-Caucasian origin, age, height, weight, fasting plasma glucose, triglycerides and HbA_1c were independent predictors for GDM, with an AUC of the model of 0.76 (95% CI 0.72–0.79); after cross-validation, the AUC was 0.72 (95% CI 0.66–0.78), compared to an AUC of 0.67 (95% CI 0.63–0.71) using the van Leeuwen model and an AUC of 0.66 (95% CI 0.62–0.70) using the Teede model. Conclusions A model based on easy to use variables in early pregnancy has a moderate accuracy to predict GDM based on the 2013 WHO criteria.
METHODS:Leveraging the availability of nationwide electronic health records from over 500,000 pregnancies in Israel, a machine-learning approach offers an alternative means of predicting gestational diabetes at high accuracy in the early stages of pregnancy. Gestational diabetes mellitus (GDM) poses increased risk of short- and long-term complications for mother and offspring^ 1 – 4 . GDM is typically diagnosed at 24–28 weeks of gestation, but earlier detection is desirable as this may prevent or considerably reduce the risk of adverse pregnancy outcomes^ 5 , 6 . Here we used a machine-learning approach to predict GDM on retrospective data of 588,622 pregnancies in Israel for which comprehensive electronic health records were available. Our models predict GDM with high accuracy even at pregnancy initiation (area under the receiver operating curve (auROC) = 0.85), substantially outperforming a baseline risk score (auROC = 0.68). We validated our results on both a future validation set and a geographical validation set from the most populated city in Israel, Jerusalem, thereby emulating real-world performance. Interrogating our model, we uncovered previously unreported risk factors, including results of previous pregnancy glucose challenge tests. Finally, we devised a simpler model based on just nine questions that a patient could answer, with only a modest reduction in accuracy (auROC = 0.80). Overall, our models may allow early-stage intervention in high-risk women, as well as a cost-effective screening approach that could avoid the need for glucose tolerance tests by identifying low-risk women. Future prospective studies and studies on additional populations are needed to assess the real-world clinical utility of the model.
METHODS::Repurposing of currently approved medications is an attractive option for the development of novel treatment strategies against physiological and infectious diseases. The antidiabetic sulfonylurea glyburide has demonstrated off-target capacity to inhibit activation of the NLRP3 inflammasome in a variety of disease models, including vaginal candidiasis, caused primarily by the fungal pathogen Candida albicans Therefore, we sought to determine which of the currently approved sulfonylurea drugs prevent the release of interleukin 1β (IL-1β), a major inflammasome effector, during C. albicans challenge of the human macrophage-like THP1 cell line. Findings revealed that the second-generation antidiabetics (glyburide, glisoxepide, gliquidone, and glimepiride), which exhibit greater antidiabetic efficacy than prior iterations, demonstrated anti-inflammatory effects with various degrees of potency as determined by calculation of 50% inhibitory concentrations (IC50s). These same compounds were also effective in reducing IL-1β release during noninfectious inflammasome activation (e.g., induced by lipopolysaccharide [LPS] plus ATP), suggesting that their anti-inflammatory activity is not specific to C. albicans challenge. Moreover, treatment with sulfonylurea drugs did not impact C. albicans growth and filamentation or THP1 viability. Finally, the use of ECE1 and Candidalysin deletion mutants, along with isogenic NLRP3-/- cells, demonstrated that both Candidalysin and NLRP3 are required for IL-1β secretion, further confirming that sulfonylureas suppress inflammasome signaling. Moreover, challenge of THP1 cells with synthetic Candidalysin peptide demonstrated that this toxin is sufficient to activate the inflammasome. Treatment with the experimental inflammasome inhibitor MCC950 led to similar blockade of IL-1β release, suggesting that Candidalysin-mediated inflammasome activation can be inhibited independently of potassium efflux. Together, these results demonstrate that the second-generation antidiabetic sulfonylureas retain anti-inflammatory activity and may be considered for repurposing against immunopathological diseases, including vaginal candidiasis.