Machine learning-based phenotypic imaging to characterise the targetable biology of Plasmodium falciparum male gametocytes for the development of transmission-blocking antimalarials.

Preventing parasite transmission from humans to mosquitoes is recognised to be critical for achieving elimination and eradication of malaria. Consequently developing new antimalarial drugs with transmission-blocking properties is a priority. Large screening campaigns have identified many new transmission-blocking molecules, however little is known about how they target the mosquito-transmissible Plasmodium falciparum stage V gametocytes, or how they affect their underlying cell biology. To respond to this knowledge gap, we have developed a machine learning image analysis pipeline to characterise and compare the cellular phenotypes generated by transmission-blocking molecules during male gametogenesis. Using this approach, we studied 40 molecules, categorising their activity based upon timing of action and visual effects on the organisation of tubulin and DNA within the cell. Our data both proposes new modes of action and corroborates existing modes of action of identified transmission-blocking molecules. Furthermore, the characterised molecules provide a new armoury of tool compounds to probe gametocyte cell biology and the generated imaging dataset provides a new reference for researchers to correlate molecular target or gene deletion to specific cellular phenotype. Our analysis pipeline is not optimised for a specific organism and could be applied to any fluorescence microscopy dataset containing cells delineated by bounding boxes, and so is potentially extendible to any disease model.

Duodenum-preserving pancreatic head resection or pancreatoduodenectomy for the surgical treatment of paraduodenal pancreatitis: a retrospective cohort study.

PURPOSE: Paraduodenal pancreatitis (PDP) is an uncommon yet well-described type of focal chronic pancreatitis. The aim of our study was to compare the outcomes of surgical treatment of patients with PDP using pancreatoduodenectomy and duodenum-preserving pancreatic head resection (DPPHR). METHODS: A retrospective analysis of 153 consecutive patients with PDP was performed. Patients who were treated with either DPPHR or PD were enrolled. The primary endpoint of the study was pain control achieved at the time of follow-up. The secondary endpoints of the study were complication rate (Clavien-Dindo > 2), hospital length of stay, and 90-day mortality. All patients were followed up after discharge for the assessment of pain cessation for a minimal period of 10 months. RESULTS: The final study population consisted of 71 patients. A total of 14 patients (19.7%) underwent pancreatoduodenectomy, and 57 (80.3%) were managed with DPPHR. Complication rate was significantly lower in DPPHR group at χ2 = 4.2677, p < 0.05. Mean hospital length of stay was 9.3 days (range 3-29) in DPPHR group and 13.9 days (range 7-35) in PD group (p < 0.05). No postoperative mortality was recorded. The mean follow-up period of the patients after surgery was 41.8 ± 20.6 months (range 10-88). Pain scores at the time of operation were calculated as 50.9 ± 12.1 in DPPHR group and 56.1 ± 11.4 in PD group. At the time of follow-up, pain scores improved significantly in both groups and were 10.3 ± 8.8 and 10.9 ± 8.6, respectively. CONCLUSION: DPPHR achieves similar results in pain control as PD with a lower complication rate and shorter hospital LOS.

Recent Discoveries of Diagnostic, Prognostic and Predictive Biomarkers for Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive disease with a dismal prognosis that is frequently diagnosed at an advanced stage. Although less common than other malignant diseases, it currently ranks as the fourth most common cause of cancer-related death in the European Union with a five-year survival rate of below 9%. Surgical resection, followed by adjuvant chemotherapy, remains the only potentially curative treatment but only a minority of patients is diagnosed with locally resectable, non-metastatic disease. Patients with advanced disease are treated with chemotherapy but high rates of treatment resistance and unfavorable side-effect profiles of some of the used regimens remain major challenges. Biomarkers reflect pathophysiological or physiological processes linked to a disease and can be used as diagnostic, prognostic and predictive tools. Thus, accurate biomarkers can allow for better patient stratification and guide therapy choices. Currently, the only broadly used biomarker for PDAC, CA 19-9, has multiple limitations and the need for novel biomarkers is urgent. In this review, we highlight the current situation, recent discoveries and developments in the field of biomarkers of PDAC and their potential clinical applications.