Brake Thermal Efficiency dan Exhaust Gas Temperature Mesin Bensin Berbahan Bakar Gasoline-Butanol

The development of butanol as a gasoline additive is encouraged by the government to reduce pollution and the fuel crisis. This is because butanol is a green fuel that is environmentally friendly and can be produced. In addition, the octane number and high oxygen concentration in butanol optimize engine performance and improve exhaust emissions. This research correlates engine power and Brake specific fuel consumption (BSFC) with the BTE of gasoline-butanol-fueled engines and identifies the content of Nox compounds in exhaust gases through engine Exhaust Gas Temperature (EGT). The percentage of butanol in gasoline is 5% -15%. Engine speed from 1000-3000 rpm. Dynotest is used to measure BTE while the thermocouple is used to measure exhaust gas temperature. This research proves that the addition of butanol increases energy absorption which is converted into power with effective fuel consumption which means BTE increases. The highest BTE increase was 21.7% in the B15 blend. EGT decreased by 8.6% in the B16 mixture compared to B0. This identifies that the concentration of Nox in the exhaust gas also decreases

Effect of a Short-Course Treatment with Synbiotics on Plasma p-Cresol Concentration in Kidney Transplant Recipients.

We evaluated whether a short-term course with synbiotics may lower plasma p-Cresol concentrations in kidney transplant patients (KTRs) who accumulate this uremic toxin both because of increased production by their dysbiotic gut microbiome and because of reduced elimination by the transplanted kidneys. METHODS: Thirty-six KTRs (29 males, mean age 49.6 ± 9.1 years) with transplant vintage > 12 months, stable graft function, and no episode of acute rejection or infection in the last 3 months were enrolled in this single-center, parallel-group, double-blinded, randomized (2:1 synbiotic to placebo) study. Synbiotic (Probinul Neutro, CadiGroup, Rome, Italy) or placebo was taken at home for 30 days, as 5 g powder packets dissolved in water three times a day far from meals. The main outcome measure was the decrease in total plasma p-Cresol measured by high-performance liquid chromatography at baseline and after 15 and 30 days of placebo or synbiotic treatment. RESULTS: After 15 and 30 days of treatment, plasma p-Cresol decreased by 40% and 33% from baseline (both p < 0.05), respectively, in the synbiotic group, whereas it remained stable in the placebo group. After 30 days of treatment, no significant change was observed in either group in renal function, glycemia, plasma lipids, or albumin concentration. Treatment was well tolerated and did not induce any change in stool characteristics. CONCLUSION: The results of this pilot study suggest that treatment with synbiotics may be effective to lower plasma p-Cresol concentrations in KTRs. Prospective larger scale, longer term studies are needed to establish whether cardiovascular prognosis could also be improved with this nutritional intervention

Model Checking to Assess T-Helper Cell Plasticity

Computational modeling constitutes a crucial step toward the functional understanding of complex cellular networks. In particular, logical modeling has proven suitable for the dynamical analysis of large signaling and transcriptional regulatory networks. In this context, signaling input components are generally meant to convey external stimuli, or environmental cues. In response to such external signals, cells acquire specific gene expression patterns modeled in terms of attractors (e.g., stable states). The capacity for cells to alter or reprogram their differentiated states upon changes in environmental conditions is referred to as cell plasticity. In this article, we present a multivalued logical framework along with computational methods recently developed to efficiently analyze large models. We mainly focus on a symbolic model checking approach to investigate switches between attractors subsequent to changes of input conditions. As a case study, we consider the cellular network regulating the differentiation of T-helper (Th) cells, which orchestrate many physiological and pathological immune responses. To account for novel cellular subtypes, we present an extended version of a published model of Th cell differentiation. We then use symbolic model checking to analyze reachability properties between Th subtypes upon changes of environmental cues. This allows for the construction of a synthetic view of Th cell plasticity in terms of a graph connecting subtypes with arcs labeled by input conditions. Finally, we explore novel strategies enabling specific Th cell polarizing or reprograming events.LabEx MemoLife, Ecole Normale Supérieure, FCT grants: (PEst-OE/EEI/LA0021/2013, IF/01333/2013), Ph.D.program of the Agence National de Recherche sur Le Sida (ANRS), European Research Council consolidator grant

An overview of existing modeling tools making use of model checking in the analysis of biochemical networks

Model checking is a well-established technique for automaticallyverifying complex systems. Recently, model checkers have appearedin computer tools for the analysis of biochemical (and generegulatory) networks. We survey several such tools to assess thepotential of model checking in computational biology. Next, our overviewfocuses on direct applications of existing model checkers, as well ason algorithms for biochemical network analysis influenced by modelchecking, such as those using binary decision diagrams or Booleansatisfiability solvers. We conclude with advantages and drawbacks ofmodel checking for the analysis of biochemical networks

Logical model specification aided by model- checking techniques: application to the mammalian cell cycle regulation

International audienc

Efficacy of Sym004 in Patients With Metastatic Colorectal Cancer With Acquired Resistance to Anti-EGFR Therapy and Molecularly Selected by Circulating Tumor DNA Analyses: A Phase 2 Randomized Clinical Trial.

IMPORTANCE: Acquired resistance to anti-EGFR therapy (epidermal growth factor receptor) is frequently due to RAS and EGFR extracellular domain (ECD) mutations in metastatic colorectal cancer (mCRC). Some anti-EGFR-refractory patients retain tumor EGFR dependency potentially targetable by agents such as Sym004, which is a mixture of 2 nonoverlapping monoclonal antibodies targeting EGFR. OBJECTIVE: To determine if continuous blockade of EGFR by Sym004 has survival benefit. DESIGN, SETTING, AND PARTICIPANTS: Multicenter, phase 2, randomized, clinical trial comparing 2 regimens of Sym004 with investigator's choice from March 6, 2014, through October 15, 2015. Circulating tumor DNA (ctDNA) was analyzed for biomarker and tracking clonal dynamics during treatment. Participants had wild-type KRAS exon 2 mCRC refractory to standard chemotherapy and acquired resistance to anti-EGFR monoclonal antibodies. INTERVENTIONS: Participants were randomly assigned in a 1:1:1 ratio to Sym004, 12 mg/kg/wk (arm A), Sym004, 9 mg/kg loading dose followed by 6 mg/kg/wk (arm B), or investigator's choice of treatment (arm C). MAIN OUTCOMES AND MEASURES: Overall survival (OS). Secondary end points included preplanned exploratory biomarker analysis in ctDNA. RESULTS: A total of 254 patients were randomized (intent-to-treat [ITT] population) (median age, 63 [range, 34-91] years; 63% male; n\u2009=\u2009160). Median OS in the ITT population was 7.9 months (95% CI, 6.5-9.9 months), 10.3 months (95% CI, 9.0-12.9 months), and 9.6 months (95% CI, 8.3-12.2 months) for arms A, B, and C, respectively (hazard ratio [HR], 1.31; 95% CI, 0.92-1.87 for A vs C; and HR, 0.97; 95% CI, 0.68-1.40 for B vs C). The ctDNA revealed high intrapatient genomic heterogeneity following anti-EGFR therapy. Sym004 effectively targeted EGFR ECD-mutated cancer cells, and a decrease in EGFR ECD ctDNA occurred in Sym004-treated patients. However, this did not translate into clinical benefit in patients with EGFR ECD mutations, likely owing to co-occurring resistance mechanisms. A subgroup of patients was defined by ctDNA (RAS/BRAF/EGFR ECD-mutation negative) associated with improved OS in Sym004-treated patients in arm B compared with arm C (median OS, 12.8 and 7.3 months, respectively). CONCLUSIONS AND RELEVANCE: Sym004 did not improve OS in an unselected population of patients with mCRC and acquired anti-EGFR resistance. A prospective clinical validation of Sym004 efficacy in a ctDNA molecularly defined subgroup of patients with refractory mCRC is warranted. TRIAL REGISTRATION: clinicaltrialsregister.eu Identifier: 2013-003829-29

A phase 1b study of the MET inhibitor capmatinib combined with cetuximab in patients with MET-positive colorectal cancer who had progressed following anti-EGFR monoclonal antibody treatment

Background Overcoming resistance to anti-epidermal growth factor receptor (EGFR) monoclonal antibodies (mAbs) in patients with KRAS wildtype (WT) metastatic colorectal cancer (mCRC) could help meet the needs of patients with limited treatment options. Methods In this phase 1b study, patients with N/KRAS WT, MET-positive mCRC who had progressed following anti-EGFR mAb treatment received escalating oral doses of capmatinib (150, 300, and 400 mg) twice daily plus weekly intravenous cetuximab (at the approved dose). The primary objective was to establish a recommended dose for expansion (RDE) of capmatinib in combination with cetuximab. Safety, preliminary activity, pharmacokinetics, and pharmacodynamics were also explored. Results Thirteen patients were enrolled. No patients experienced a dose-limiting toxicity at investigated doses; the RDE was established as capmatinib 400 mg twice daily plus cetuximab. All patients experienced adverse events (AEs) suspected to be related to the study treatment. Five patients (38.5%) reported study-drug-related AEs of grade 3/4 in severity. No patients achieved a complete or partial response according to RECIST v1.1; however, tumor shrinkage of 29-44% was observed in 4 patients. Conclusions Capmatinib plus cetuximab was well tolerated. Preliminary signs of activity were observed. Further investigation is warranted to obtain efficacy data and refine predictive biomarkers of response. Clinical trial registration NCT02205398