Carlsen Conner (magicray65)

BACKGROUND Despite sensitivity to first-line chemotherapy, most small-cell lung cancer (SCLC) patients relapse. In this setting, topotecan demonstrated modest activity with significant toxicity. Paclitaxel was also active. This study was designed to evaluate activity and safety of nab-paclitaxel in relapsed SCLC. METHODS In this multicentre prospective Phase 2 trial, patients with refractory or sensitive SCLC progressed to first-line platinum-based chemotherapy received nab-paclitaxel 100 mg/smq on days 1, 8, 15 every 4 weeks up to six cycles, progressive disease or intolerable toxicity. Primary endpoint was investigator-assessed objective tumour response. Secondary endpoints were toxicity, progression-free survival (PFS) and overall survival (OS). RESULTS Of the 68 patients treated, partial response was 8% in the refractory cohort and 14% in the sensitive cohort. Most common toxicities of any grade were fatigue (54%), anaemia (38%), neutropenia (29%), leukopenia (26%) and diarrhoea (21%). Median PFS was similar in both refractory (1.8 months) and sensitive cohorts (1.9 months), while median OS was longer in sensitive one (6.6 versus 3.6 months). CONCLUSIONS Although nab-paclitaxel has shown some modest anti-tumour activity in relapsed SCLC, associated with a favourable toxicity profile, the primary end-point of the study was not met. CLINICAL TRIAL REGISTRATION Clinical Trial registration number is ClinicalTrials.gov Identifier NCT03219762.Identification of novel photosynthetic proteins is important for understanding and improving photosynthetic efficiency. Synergistically, genome neighborhood can provide additional useful information to identify photosynthetic proteins. We, therefore, expected that applying a computational approach, particularly machine learning (ML) with the genome neighborhood-based feature should facilitate the photosynthetic function assignment. Our results revealed a functional relationship between photosynthetic genes and their conserved neighboring genes observed by 'Phylo score', indicating their functions could be inferred from the genome neighborhood profile. Therefore, we created a new method for extracting patterns based on the genome neighborhood network (GNN) and applied them for the photosynthetic protein classification using ML algorithms. Random forest (RF) classifier using genome neighborhood-based features achieved the highest accuracy up to 87% in the classification of photosynthetic proteins and also showed better performance (Mathew's correlation coefficient = 0.718) than other available tools including the sequence similarity search (0.447) and ML-based method (0.361). Furthermore, we demonstrated the ability of our model to identify novel photosynthetic proteins compared to the other methods. Our classifier is available at http//bicep2.kmutt.ac.th/photomod_standalone, https//bit.ly/2S0I2Ox and DockerHub https//hub.docker.com/r/asangphukieo/photomod.The voltage-gated proton channel Hv1 is widely expressed, among others, in immune and cancer cells, it provides an efficient cytosolic H+extrusion mechanism and regulates vital functions such as oxidative burst, migration and proliferation. Here we demonstrate the presence of human Hv1 (hHv1) in the placenta/chorion-derived mesenchymal stem cells (cMSCs) using RT-PCR. The voltage- and pH-dependent gating of the current is similar to that of hHv1 expressed in cell lines and that the current is blocked by 5-chloro-2-guanidinobenzimidazole (ClGBI) and activated by arachidonic acid (AA). Inhibition of hHv1 by ClGBI significantly decreases mineral matrix production of cMSCs induced by conditions mimicking physiological or pathological (inorganic phosphate, Pi) induction of osteogenesis. Wound healing assay and single cell motility analysis show that ClGBI significantly inhibits the migration of cMSCs. Thus, seminal functions of cMSCs are modulated by hHv1 which makes this channel as an attractive target for controlling advantages/disadvantages