Uncalcified Synovial Chondromatosis in the Pisotriquetral Joint

Synovial chondromatosis is a rare lesion in the wrist, but some cases in the distal radioulnar joint have been reported and previous case reports emphasize joint calcifications, shown on preoperative plain radiographs. We report an extremely uncommon case of synovial chondromatosis in the pisotriquetral joint, in which radiographs and magnetic resonance imaging did not demonstrate apparent calcified bodies. In our case, for the accurate diagnosis and treatment, surgical exploration of the joint and synovectomy with removal of loose bodies was performed.     

A Phase I Trial of Trametinib in Combination with Sorafenib in Patients with Advanced Hepatocellular Cancer

Lessons Learned

• The combination of trametinib and sorafenib has an acceptable safety profile, albeit at doses lower than approved for monotherapy.
• Maximum tolerated dose is trametinib 1.5 mg daily and sorafenib 200 mg twice daily.
• The limited anticancer activity observed in this unselected patient population does not support further exploration of trametinib plus sorafenib in patients with hepatocellular carcinoma.

BackgroundThe RAS/RAF/MEK/ERK signaling pathway is associated with proliferation and progression of hepatocellular carcinoma (HCC). Preclinical data suggest that paradoxical activation of the MAPK pathway may be one of the resistance mechanisms of sorafenib; therefore, we evaluated trametinib plus sorafenib in HCC.MethodsThis was a phase I study with a 3+3 design in patients with treatment‐naïve advanced HCC. The primary objective was safety and tolerability. The secondary objective was clinical efficacy.ResultsA total of 17 patients were treated with three different doses of trametinib and sorafenib. Two patients experienced dose‐limiting toxicity, including grade 4 hypertension and grade 3 elevation of aspartate aminotransferase (AST)/alanine aminotransferase (ALT)/bilirubin over 7 days. Maximum tolerated dose was trametinib 1.5 mg daily and sorafenib 200 mg twice a day. The most common grade 3/4 treatment‐related adverse events were elevated AST (37%) and hypertension (24%). Among 11 evaluable patients, 7 (63.6%) had stable disease with no objective response. The median progression‐free survival (PFS) and overall survival (OS) were 3.7 and 7.8 months, respectively. Phosphorylated‐ERK was evaluated as a pharmacodynamic marker, and sorafenib plus trametinib inhibited phosphorylated‐ERK up to 98.1% (median: 81.2%) in peripheral blood mononuclear cells.ConclusionTrametinib and sorafenib can be safely administered up to trametinib 1.5 mg daily and sorafenib 200 mg twice a day with limited anticancer activity in advanced HCC.     

Binding mode of conformations and structure-based pharmacophore development for farnesyltransferase inhibitors

Farnesyltransferase (FTase) is one of the prenyltransferase family enzymes that catalyse the transfer of 15-membered isoprenoid (farnesyl) moiety to the cysteine of CAAX motif-containing proteins including Rho and Ras family of G proteins. Inhibitors of FTase act as drugs for cancer, malaria, progeria and other diseases. In the present investigation, we have developed two structure-based pharmacophore models from protein–ligand complex (3E33 and 3E37) obtained from the protein data bank. Molecular dynamics (MD) simulations were performed on the complexes, and different conformers of the same complex were generated. These conformers were undergone protein–ligand interaction fingerprint (PLIF) analysis, and the fingerprint bits have been used for structure-based pharmacophore model development. The PLIF results showed that Lys164, Tyr166, TrpB106 and TyrB361 are the major interacting residues in both the complexes. The RMSD and RMSF analyses on the MD-simulated systems showed that the absence of FPP in the complex 3E37 has significant effect in the conformational changes of the ligands. During this conformational change, some interactions between the protein and the ligands are lost, but regained after some simulations (after 2 ns). The structure-based pharmacophore models showed that the hydrophobic and acceptor contours are predominantly present in the models. The pharmacophore models were validated using reference compounds, which significantly identified as HITs with smaller RMSD values. The developed structure-based pharmacophore models are significant, and the methodology used in this study is novel from the existing methods (the original X-ray crystallographic coordination of the ligands is used for the model building). In our study, along with the original coordination of the ligand, different conformers of the same complex (protein–ligand) are used. It concluded that the developed methodology is significant for the virtual screening of novel molecules on different targets.     

Dying is the Most Grown-Up Thing We Ever Do: But Do Health Care Professionals Prevent Us from Taking It Seriously?

This paper takes a somewhat slant perspective on flourishing and care in the context of suffering, death and dying, arguing that care in this context consists principally of ‘acts of work and courage that enable flourishing’. Starting with the perception that individuals, society and health care professionals have become dulled to death and the process of dying in Western advanced health systems, it suggests that for flourishing to occur, both of these aspects of life need to be faced more directly. The last days of life need to be ‘undulled’. Reflections upon the experiences of the author as carer and daughter in the face of her mother’s experience of death are used as basis for making suggestions about how care systems and professionals might better assist people in dealing with ‘the most grown up thing’ humans ever do, which is to die.     

基于剂量组学预测肺癌患者放射性肺炎发生的研究

目的 探讨剂量组学在预测肺癌根治性放疗患者放射性肺炎发生中的应用潜能。方法 回顾性收集行根治性放疗的314例肺癌患者的临床资料、放疗剂量文件、定位及随访CT图像,根据临床资料及影像学随访资料对放射性肺炎进行分级,提取全肺的剂量组学特征,构建机器学习模型。应用1000次自助抽样法（bootstrap）的最小绝对值收敛和选择算子嵌套逻辑回归（LASSO‐LR）及1000次bootstrap的赤池信息量准则（AIC）向后法筛选与放射性肺炎相关的剂量组学特征,随机按照7∶3划分为训练集及验证集,应用逻辑回归建立预测模型,并应用ROC曲线及校正曲线评价模型的性能。结果 共提取120个剂量组学特征,经LASSO‐LR降维筛选得到12个特征进入“特征池”,再经过AIC向后法筛选,最终筛选出6个剂量组学特征进行模型构建,训练集AUC为0.77（95%CI为0.65~0.87）,独立验证集AUC为0.72（95%CI为0.64~0.81）。结论 利用剂量组学建立的预测模型具有预测放射性肺炎发生的潜力,但仍需继续纳入多中心数据及前瞻性数据进一步挖掘剂量组学的应用潜能。     

Nanomedicines: From Bench to Bedside and Beyond

Advancing nanomedicines from concept to clinic requires integration of new science with traditional pharmaceutical development. The medical and commercial success of nanomedicines is greatly facilitated when those charged with developing nanomedicines are cognizant of the unique opportunities and technical challenges that these products present. These individuals must also be knowledgeable about the processes of clinical and product development, including regulatory considerations, to maximize the odds for successful product registration. This article outlines these topics with a goal to accelerate the combination of academic innovation with collaborative industrial scientists who understand pharmaceutical development and regulatory approval requirements—only together can they realize the full potential of nanomedicines for patients.