Revisiting the sponge sources, stereostructure, and biological activity of cyclocinamide a

The dramatic biogeographical variations in the secondary metabolites from Psammocinia aff. bulbosa have complicated our efforts to reisolate the two most cytotoxic of its metabolites, (+)-psymberin and (+)-cyclocinamide A. Reported now are the results of a new study that demonstrates our ability to repeatedly isolate these two compounds through targeted collection efforts. Additional study of the new sample of (+)-cyclocinamide A has enabled finalizing its biological activity and absolute stereochemistry as 4S, 7S, 11S, 14S.     

Chondrosarcoma of the uterus: case report and literature review

BACKGROUND: Pure heterologous sarcomas of the uterine corpus are extremely rare, accounting for 4% of all uterine sarcomas. Primary chondrosarcoma, which is characterized by the absence of epithelial or other heterologous mesenchymal elements, is included in this group. To this date, only 17 cases, including the presenting case, have been reported. CASE: A 55-year-old female presenting with post-menopausal bleeding was diagnosed with chondrosarcoma of the uterus, after abdominal hysterectomy and bilateral salpingoophorectomy. After 8 months of surgery, there is no evidence of recurrence after receiving external radiotherapy and brachytherapy. CONCLUSION: Primary chondrosarcoma of the uterus is an extremely rare uterine tumour most frequently diagnosed by the pathologist. They are usually aggressive malignant tumours with an early relapse and metastases.     

An estrogen metabolism-related polymorphism of the 17-alpha HSD gene is associated with perimenopausal body mass index

In a cross-sectional study of 2,802 perimenopausal caucasian women, carriage of at least one mutated allele of the 17-alpha-hydroxysteroid dehydrogenase type 1 (17-alpha HSD) vlV A-->C single nucleotide polymorphism (SNP) was associated with a significantly increased body mass index (mean 24.3 +/- 4.4 kg/m(2) vs. 23.5 +/- 4.2 kg/m(2); P<.001), and obesity was more frequent among mutant allele carriers (P=.06; odds ratio 1.38; 95% confidence interval 0.97-1.95), providing evidence of 17-alpha HSD as a candidate gene of perimenopausal obesity.     

Machine learning approach to identify adverse events in scientific biomedical literature

Monitoring the occurrence of adverse events in the scientific literature is a mandatory process in drug marketing surveillance. This is a very time‐consuming and complex task to fulfill the compliance and, most importantly, to ensure patient safety. Therefore, a machine learning (ML) algorithm has been trained to support this manual intellectual review process, by automatically providing a classification of the literature articles into two types. An algorithm has been designed to automatically classify “relevant articles” which are reporting any kind of drug safety relevant information, and those which are not reporting an adverse drug reaction as “not relevant.” The review process is consisted of many rules and aspects which needed to be taken into consideration. Therefore, for the training of the algorithm, thousands of documents from previous screenings have been used. After several iterations of adjustments and fine tuning, the ML approach is definitively a great achievement in pre‐sorting the articles into “relevant” and “non‐relevant” and supporting the intellectual review process.

Study Highlights

• WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?

Using machine learning (ML) to make decisions based on previous decisions is becoming more prominent in the digital world. However, to implement such a workflow in a very regulated field is a big challenge.

• WHAT QUESTION DID THIS STUDY ADDRESS?

To what extend is it possible to replace human decisions needing intellectual input by ML?

• WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?

It shows that it is to a certain extent possible to detect drug safety‐related information to the drugs in focus in written text. Furthermore, it combines the methodologies to show which technical solutions are best.

• HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE?

Using ML in more and more processes will gain efficiency and will make drug discovery, drug development, and postmarketing surveillance more efficient and, most importantly, it will increase the patients’ safety.     

BOOST: a phase 3 trial of sorafenib vs. best supportive care in first line treatment of hepatocellular carcinoma in patients with deteriorated liver function

Aim: Only patients with good liver function {[Child-Pugh (CP)] A class} were eligible for trials testing sorafenib as first-line treatment of hepatocellular car...     

HOXD8 hypermethylation as a fully sensitive and specific biomarker for biliary tract cancer detectable in tissue and bile samples

Background Biliary tract cancers (BTC) are rare but highly aggressive tumours with poor prognosis, usually detected at advanced stages. Herein, we aimed at identifying BTC-specific DNA methylation alterations.Methods Study design included statistical power and sample size estimation. A genome-wide methylation study of an explorative cohort (50 BTC and ten matched non-tumoral tissue samples) has been performed. BTC-specific altered CpG islands were validated in over 180 samples (174 BTCs and 13 non-tumoral controls). The final biomarkers, selected by a machine-learning approach, were validated in independent tissue (18 BTCs, 14 matched non-tumoral samples) and bile (24 BTCs, five non-tumoral samples) replication series, using droplet digital PCR.Results We identified and successfully validated BTC-specific DNA methylation alterations in over 200 BTC samples. The two-biomarker panel, selected by an in-house algorithm, showed an AUC > 0.97. The best-performing biomarker (chr2:176993479-176995557), associated with HOXD8, a pivotal gene in cancer-related pathways, achieved 100% sensitivity and specificity in a new series of tissue and bile samples.Conclusions We identified a novel fully efficient BTC biomarker, associated with HOXD8 gene, detectable both in tissue and bile by a standardised assay ready-to-use in clinical trials also including samples from non-invasive matrices.Subject terms: Diagnostic markers, Biliary tract cancer