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Purpose Alofanib is a small-molecule allosteric extracellular FGFR2 inhibitor. We report safety and preliminary efficacy from the first-in-human phase 1b study of alofanib in heavily pretreated patients with advanced gastric cancer. Methods The standard dose-escalation design 3 + 3 aimed to establish the maximum tolerated dose (MTD) or recommended phase 2 dose (RP2D). Alofanib was administered daily intravenously 5 days on, 2 days off. There were five dose levels (50–350 mg/m2). All patients received alofanib until disease progression or unacceptable toxicity. Results 21 patients were enrolled. Patients were predominantly male (71%), 67% had 2 and more metastatic sites, including liver metastases (43%), 19% had ECOG PS 2, and were heavily pretreated (86% had previous 2 and more treatment lines). During dose escalation, no dose-limiting toxicities were observed, and MTD was not defined. 15 (71.4%) patients had at least one adverse event associated with the treatment (TRAE). Grade 3 or higher TRAEs were observed in 6 patients (28.6%). The most common TRAEs included reactions immediately after administration, diarrhea, thrombocytopenia, arthralgia, and headache. The median progression-free survival and overall survival was 3.63 (95% CI 1.58–5.68) and 7.0 (95% CI 3.82–10.18) months, respectively. The 6- and 12-month overall survival rates were 57.1% and 33.3%. Disease control rate was 68% with one durable partial response. Conclusions The MTD has not been reached and dose of 350 mg/m2, 5 days on, 2 days off has been declared as RP2D. Alofanib showed acceptable tolerability and preliminary signs of clinical activity in the late-line treatment of metastatic gastric cancer. ClinicalTrials.gov identifier: NCT04071184

Alofanib is a potent, small molecule, allosteric inhibitor that binds to the non-active extracellular site of IIIc and IIIb FGFR2 isoforms. Phase 1b clinical study (RPT835GC1B) met its primary endpoints and recommended phase 2 dose was described early. Here, we present pharmacokinetics (PK) and results of biomarker analysis. Alofanib was administered daily intravenously for 5-days followed by a 2-day interval (rest). There were five dose levels using a 3 + 3 design. 21 patients have been enrolled in the study. Patients were Caucasian (100%), predominantly male (71%), 67% had 2 and more metastatic sites, including liver (43%) and bone (14.3%) metastases, 19% had ECOG PS 2, and were heavily pretreated (86% had previous 3 and more lines of therapy). The PK and biomarker analysis set included 18 patients. FGFR2 amplification was accessed by FISH with ZytoLight SPEC FGFR2/CEN 10 Dual Color Probe and FGFR2 expression was accessed by IHC with antibody 1G3 (Abcam (ab 5820). Table summarizes PK data. The geometric mean values of Cmax, AUC0-t, T1/2, Vd increased and CL, Kel decreased approximately dose-proportionally after single dosing, similar to previous preclinical studies. The decrease in the mean value of the Vd for a dose of 350 mg/m2 may be associated with a significant increase in AUC0-t. No correlations between PK values and objective response rate (n=2; 9.5%), progression-free (median 3.63 months (95% CI, 1.58 - 5.68) and overall (median 7.0 months (3.82 - 10.18) survival as well as in patients with liver metastases were found (all P>0.1). A positive FGFR2 IHC expression was observed in all tumor cells and a weak positive reaction in normal epithelium. FGFR2 amplification was confirmed by FISH in 1 (5.6%) patient.Alofanib PK in a gastric patient population is well characterized, supporting the use of a once-daily 350 mg/m2 dose. In further studies, the evaluation of FGFR2 amplification seems to be important. Cohort 1 Cohort 2 Cohort 3 Cohort 4 Cohort 5 50 mg/m2 100 mg/m2 165 mg/m2 250 mg/m2 350 mg/m2 Cmax, mcg/ml (CV%) 21.4 (32.3) 23.7 (18.4) 44.7 (15.5) 72.8 (64.3) 145.9 (42.7) AUC0-t, mcg*h/ml (CV%) 2.3 (31.9) 6.6 (14.2) 13.3 (49.9) 23.8 (8.7) 74.0 (57.5) Vd, ml/m2 (CV%) 4006.1 (28.3) 4907.5 (14.7) 5676.8 (26.6) 6686.7 (11) 3823.0 (63.8) CL, ml/h/m2 (SD) 19609.5 (7740) 14028.2 (1990) 11910.5 (8740) 10011.0 (827) 4183.0 (2420) Kel, 1/h (CV%) 4.9 (15.3) 2.9 (2.8) 2.1 (41.2) 1.5 (3.8) 1.1 (47.0) T1/2, h (SD) 0.1 (0.024) 0.2 (0.01) 0.3 (0.118) 0.5 (0.0171) 0.6 (0.293) Citation Format: Grigory Raskin, Vasily Kazey, Svetlana Gorbacheva, Aiyyna Nikiforova, Galina Statsenko, Elena Artamonova, Liubov Vladimirova, Natalia Besova, Anastasia Mochalova, Ivan Rykov, Vladimir Moiseyenko, Igor Utyashev, Sergei Iugai, Nadezhda Dragun, Dmitry Reznikov, Evgenia Gavrilova, Sergei Tjulandin, Ilya Tsimafeyeu. Pharmacokinetics of alofanib and biomarker analysis in patients with advanced gastric cancer: A phase 1b study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3481.

e16077 Background: Alofanib (RPT835) is a first-in-class allosteric inhibitor that induces conformational changes in the extracellular domain of FGFR2. Here, we present the final results of the phase Ib clinical study (RPT835GC1B) of alofanib. Methods: Patients with metastatic gastric adenocarcinoma resistant to standard therapy with measurable disease were eligible. The dose finding part used a 3+3 design, starting with a dose level of 50 mg/m2, intravenously, 5 days on, 2 days off. Five dose levels were foreseen. Primary endpoint was maximum tolerated dose (MTD). Secondary endpoints included toxicity, PK, objective response rate (ORR), overall survival (OS), and progression-free survival (PFS). Results: 21 patients were enrolled. 4 (19.1%), 14 (66.7%), 9 (43%), 3 (14.3%), and 12 (57%) patients had ECOG PS 2, ≥2 metastatic sites, liver metastases, bone metastases, and 3-6 lines previous therapy, respectively. The MTD has not been reached and dose of 350 mg/m2 has been declared as recommended phase II dose. With median follow-up of 13.0 months 15 (71.4%) patients had any grade treatment related adverse events (TRAE). Grade 3-4 TRAE occurred in 6 (28.6%) patients. Two (9.5%) patients discontinued treatment due to grade 3 diarrhea and grade 4 reactions immediately after injections. There were no treatment-related deaths in the study. One partial response (5.26%) with a duration of 18.53 months was identified. Disease control rate (DCR) was 68.4% and median duration of stable disease was 4.91 months. Median PFS was 3.63 (95% CI 1.58–5.68) months. Median OS was 7.0 (3.82–10.18) months. 6-month OS rate was 57.1%. OS was almost 2 times better in patients with DCR (median 10.05 vs. 5.9 months) and without bone metastases (8.6 vs. 3.1). Only one patient (4.8%) had FGFR2 amplification (time to death was 7 months). PK parameters linearly changed depending on the dose level, but no correlation with efficacy was found. Table summarizes rate of TRAE and DCR in dose cohorts. Conclusions: Alofanib was feasible and showed early signals of efficacy in heavily-pretreated patients with metastatic gastric cancer. A phase 2 randomized trial is planned. Clinical trial information: NCT04071184. [Table: see text]

In this paper, the previously obtained results on recognition of ionograms using deep learning are expanded to predict the parameters of the ionosphere. After the ionospheric parameters have been identified on the ionogram using deep learning in real time, we can predict the parameters for some time ahead on the basis of the new data obtained Examples of predicting the ionosphere parameters using an artificial recurrent neural network architecture long short-term memory are given. The place of the block for predicting the parameters of the ionosphere in the system for analyzing ionospheric data using deep learning methods is shown.

The problem of accurately calculating the probability of connectivity of graph nodes is not only very important for practical use, but also belongs to the class of NP-hard problems. The paper gives the place of application of expert systems, simulation modeling and other well-known methods in solving the problem of accurately calculating the probability of connectivity of graph nodes. The rule-based expert system Drools was chosen as the basis of our engine. The Monte Carlo method is used as a basis for simulation modeling. The rules of the Drools expert system and examples of the system operation are given.

304 Background: FGFR2 promotes gastric cancer progression, suggesting that inhibition of FGFR2 may be an important therapeutic strategy. Alofanib (RPT835) is a small molecule, allosteric inhibitor that binds to the non-active extracellular site of IIIc and IIIb FGFR2 isoforms with IC50 < 10 nM. Methods: RPT835GC1B is a Phase 1b open-label study evaluating the safety and preliminary efficacy of alofanib in patients with metastatic gastric adenocarcinoma pretreated with ≥ 1 previous lines of therapy. The standard dose-escalation part (design 3+3) aimed to establish the maximum tolerated dose (MTD) or recommended phase 2 dose (RP2D) as a primary endpoint. Secondary endpoints included pharmacokinetic (PK) parameters, rate of adverse events, progression-free survival (PFS), overall survival (OS), and objective response rate (ORR). Alofanib was administered daily intravenously for 5-days followed by a 2-day interval (rest). There were five dose levels: 50, 100, 165, 250, and 350 mg/m2. All patients received alofanib until disease progression or unacceptable toxicity. Results: As of 20 September 2021, 21 patients have been enrolled in the study. Patients were Caucasian (100%), predominantly male (71%), 67% had 2 and more metastatic sites, including liver metastases (43%), 14% had ECOG PS 2, and were heavily pretreated (86% had previous 3 and more lines of therapy). All enrolled patients have been studied for safety and have not experienced any dose-limiting toxicities (DLTs) within the 28-day DLT-assessment window. 17 (81%) patients had at least one treatment-related adverse event (trAE). Grade 3 or higher trAEs (5/23.8%) have included raised ALT/AST at 50 mg/m2, neutropenia at 50 mg/m2, diarrhea at 165 mg/m2, headache at 165 mg/m2, increased serum amylase at 350 mg/m2, and reactions immediately after intravenous injections (facial flushing, dizziness, weakness, sweating, and sinus tachycardia) at 350 mg/m2. Three (14.3%) patients discontinued treatment due to trAEs. Most common Grade 1-2 adverse events included reactions immediately after intravenous injections, diarrhea, thrombocytopenia, arthralgia, and headache. Grade 1 hyperphosphatemia was found in 1 (4.8%) patient. Table summarizes efficacy data. Conclusions: The MTD has not been reached and dose of 350 mg/m2 has been declared as RP2D. Alofanib showed acceptable tolerability and preliminary signs of clinical activity in the late-line treatment of metastatic gastric cancer. Clinical trial information: NCT04071184. [Table: see text]

Fibroblast growth factor receptor 2 (FGFR2) is associated with an unfavorable prognosis in patients with gastric cancer. Acquired mutations in FGFR2 develop resistance to multikinase inhibitors. Besides, resistance to monoclonal antibodies depends on the type of FGFR2 isoforms IIIc or IIIb expressed by cancer cells. Alofanib (RPT835) is a small molecule, allosteric inhibitor that binds to the non-active site of FGFR2 extracellular domain. RPT835GC1B (NCT04071184) is an ongoing Phase 1b open-label study evaluating the safety and preliminary efficacy of alofanib in patients with metastatic gastric adenocarcinoma pretreated with ≥ 1 previous lines of therapy. The standard dose-escalation part (design 3+3) aims to establish the maximum tolerated dose (MTD) or recommended phase 2 dose (R2PD) as a primary endpoint. The first part of the study includes a 28-day period when alofanib is administered daily intravenously for 5-days followed by a 2-day interval (rest). There are five dose levels: 50, 100, 165, 250, and 350 mg/m2. Secondary endpoints include pharmacokinetic (PK) parameters, rate of adverse events, progression-free survival (PFS), overall survival (OS), and objective response rate. All patients received alofanib until disease progression or unacceptable toxicity. As of data cutoff on December 30, 2020, 13 patients have been enrolled in the trial. Patients were predominantly male (85%), 54% had 2 and more metastatic sites, including liver metastases (54%), and were heavily pretreated (60% received previous 3-6 lines of therapy). To date, all enrolled patients have been studied for safety and have not experienced any dose-limiting toxicities (DLTs) within the 28-day DLT-assessment window. Grade 3 or higher drug related adverse events have included raised ALT/AST at 50 mg/m2, diarrhea at 165 mg/m2, and hyponatremia at 350 mg/m2. 93% of patients had any grade adverse events. Most common Grade 1-2 adverse events included fatigue, diarrhea, nausea, anemia, thrombocytopenia, increased alkaline phosphatase, and reactions immediately after intravenous injections (facial flushing, dizziness, weakness, sweating, and sinus tachycardia). Grade 1 hyperphosphatemia was founded in 25% of cases. One patient discontinued treatment due to drug related Grade 3 uncontrolled diarrhea. Alofanib has demonstrated evidence of biologic activity in 12 patients in the first 4 dose levels evaluated to date. Disease control rate was 75% (1 durable partial response (13 months) at 50 mg/m2 and 8 stable diseases at 50-250 mg/m2). After a median follow-up of 4.5 months, the median PFS and OS was not reached. In conclusion, dosing up to 350 mg/m2 of alofanib was well tolerated, DLT and MTD were not reached. The early biologic activity of alofanib in the late-line treatment of metastatic gastric cancer is encouraging. In addition to the above, any updated safety, PK, and efficacy data will be presented at the time of the AACR meeting. Citation Format: Ilya Tsimafeyeu, Galina Statsenko, Anastasia Mochalova, Natalia Trenina, Vyacheslav Kurakin, Natalia Besova, Kristina Novoselova, Natalia Abramova, Ekaterina Obarevich, Alina Kashanova, Margarita Suetina, Vladimir Moiseyenko, Mikhail Byakhov, Elena Artamonova, Liubov Vladimirova, Sergei Tjulandin. Preliminary data on a phase 1b, first-in-human study of the allosteric extracellular FGFR2 inhibitor alofanib in patients with refractory metastatic gastric cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr CT113.

During analyzing of geophysical data, the problem of highlighting a form of geophysical signals often appears. In this work, it is proposed to use deep learning, which is currently one of the top priorities in the field of artificial intelligence and machine learning. The samples of geophysical signals, as well as the generated samples of signals by their mathematical models and typical examples of forms, act as a training dataset for deep neural network. End-to-end demonstration examples of the highlighting of reflection traces from different layers of the ionosphere in the ionograms, as well as the highlighting of whistler forms in the VLF spectrograms are presented.

At present, scientists have developed various programs and algorithms for ionogram recognition. They recognize and detect various parameters of the ionosphere. A distinctive feature of the method proposed in the work is the use of deep learning to recognize reflection traces from different layers of the ionosphere. We train deep neural network on the basis of markup dataset created by operators. Demonstration examples of software-implemented system for ionogram recognition are given.

When we analyze geophysical data, the task of searching for structures by their samples and mathematical models often appears. We propose to use deep neural networks (DNN) to search and detect the forms of geophysical structures. At the same time, both the structure samples themselves and the synthesized structure samples according to their mathematical models act as a training dataset. End-to-end demonstration examples of the highlighting of reflection traces from different layers of the ionosphere in the ionograms, as well as the highlighting of whistler forms in the VLF spectrograms are presented.

e15584 Background: Options of therapy are limited for patients with colorectal cancer who developed disease progression during standard 5-FU-, oxaliplatin-, and irinotecan-contained regimens. There is straight information about synergy of irinotecan (SN-38) and oxaliplatin gained from fundamental and early clinical trials. We aimed to analyze effectiveness and safety of triple drug-combination of 5-FU, oxaliplatin and irinotecan (FOLFOXIRI) in heavily pretreated patients with metastatic colorectal cancer. Methods: Patients with a metastatic colorectal cancer who received more than 2 lines of standard 5-FU-, oxaliplatin- and irinotecan-based doublet regimens with or without targeted therapy were included. Reinduction of chemotherapy in previous lines was allowed. The retrospective analysis of medical histories was done. Eligible patients had to receive number of cycles that were sufficient for response rate estimation. Disease response was evaluated according to RECIST 1.1 criteria. Survival analysis was performed using the Kaplan-Meier method. Tolerability was estimated by CTCAE v. 5.0. Results: Forty-six patients were included in retrospective per protocol analysis. The median follow-up was 19 months. The median number of previous lines of chemotherapy was 2 (2-6). Primary resistance to oxaliplatin- and irinotecan-based chemo during previous lines was noted in 20 patients (43%) and 16 patients (35%), respectively, while seven patients (15%) developed the primary resistance to both agents given in a sequential order. All patients were treated with targeted therapy during previous treatment lines. The median of FOLFOXIRI cycles was 8 (range, 2-19). Two patients (4%) were treated with FOLFOXIRI without any targeted agents. The objective response rate was 33% (n = 15). The disease stabilization was reached in 43% (n = 20). The disease control rate was 76% (n = 35). Eleven patients (24%) had the progression of disease at the first follow-up. The median progression free survival and median overall survival were 6 months and 11 months, respectively. Toxicity was evaluated in 35 patients. The most common severe adverse events (grade 3 and 4) were neutropenia (46%) and fatigue (26%). Treatment was delayed in 20 patients (57%), and 13 patients (37%) required dose reduction. One patient had to discontinue treatment due to unacceptable toxicity. Conclusions: According to our study FOLFOXIRI provides the objective response and increased life expectancy in heavily pretreated patients. The further assessment of FOLFOXIRI regimen for refractory colorectal cancer in the prospective trials is needed.

The lightning localization task is very interested for the meteorologist organizations, airlines, networks operators, military and etc. The electromagnetic properties of lightning can be measured using VLF sensor. The paper deals with some hardware and software of VLF sensors used in IKIR FEB RAS.

The paper suggests an approach to the design of a question-answering system based on the interaction of various agents whose work is aimed at obtaining the answer most relevant to the user’s request. The types of such agents, the principles of their work, their functions, the ways of interaction for obtaining the final answer are described. A distinctive feature of the described approach to the implementation of the multi-agent question-answering system is that among the agents providing the system operation, there are those using the machine data and the logical conclusions, as well as those whose main function is to communicate with people and receive the necessary information from them. Thus, the efficiency of such a system is largely determined by the fact that the system uses the most powerful intellectual resources—humans—along with the machine resources and algorithms. A peculiar feature of the question-answering system described in the paper is that the agents ensuring the system operation interact with each other, as well as with users in natural language.

The paper proposes an algorithm for the operation of the natural language question-answering system based on construction of supposed answers and comparison of the corresponding ontosemantic graphs with the ontosemantic graphs constructed on the interrogative sentence that is submitted to the system input. An algorithm for calculating the similarity coefficient of ontosemantic graphs is proposed. Examples illustrating the operation of the described algorithms are given through the paper.

Optimization problems of construction, development and changing the structure of geospace self-organizing question-answering sensor networks (GSQASN) are considered. The task specifies the coordinates of various network nodes. It is required with the specified functional, structural, cost and spatial constraints to change the structure of the GSQASN by adding new nodes, moving to new positions or removing some existing nodes. After the formation of the GSQASN structure we solve the task of question-answer agents placement into GSQASN structure in order to be able to answer the given types of questions under the established limitations. The functional scheme of a given category nodes placement into GSQASN structure and approximate bio-inspired algorithms for solving the tasks are proposed. The results of the work can be used in the construction of specific GSQASN and in the GSQASN design support systems.

In this work we propose a mathematical model of a Russian-text semantic analyzer based on semantic rules. We provide a working algorithm of the semantic analyzer and demonstrate some examples of its software implementation in Java language. According to the developed algorithm, the text that proceeds to the input of the semantic analyzer is gradually reduced: some syntaxemes from the analyzed text, in accordance with semantic rules, are added to a queue with priority; then on each iteration the syntaxeme corresponding to the highest priority element is removed from the text. When a syntaxeme is removed from the text, the corresponding element is removed from the queue. Priority definition for a queue element bases on the value of the group priority of the semantic dependence which is described by a semantic rule, as well as on the position in the analyzed syntaxeme corresponding to the queue element.

e20567 Background: We aimed to evaluate clinical and quality of life (QoL) outcomes of Nivo as 2+ line treatment in NSCLC pts within expanded access program and real world practice. Methods: Adult pts with advanced refractory NSCLC were enrolled in 11 centers in RF. All the pts received Nivo 3 mg/kg q2w. Tumor response was assessed using RECIST v. 1.1, adverse events (AEs) – NCI CTCAE v3.0. Patients filled out RAND SF-36 and ESAS-R at baseline, 1, 3, 6 and 12 mos after treatment start. Overall survival (OS) and progression-free survival (PFS) curves were evaluated by the Kaplan-Meyer method and compared by the log-rank test. GEE method was used for QoL analysis; χ2 test – for disease control rate (DCR) comparison. Results: The preliminary analysis was performed in the group of 200 pts with median follow-up 7.4 mos (65% – males; median age – 62 y.o.; ECOG 0-1 – 81%; former/current smokers – 70.5%; non squamous NSCLC – 64%; ≥2 lines of previous treatment – 53%, bone mts – 22%). DCR was revealed in 60.3% pts (108/179 pts, median first evaluation – 2.1 mos); 13 pts died before first response evaluation; 8 pts were not evaluated for response at cut-off. DCR was higher in squamous NSCLC (66%, squamous vs 51%, non squamous; χ2 = 4.0, p = .045). Median OS – 11.5 mos (95%CI 8.3–14.7), median PFS – 4.2 mos (95%CI 3.5–4.9). Patients with poor ECOG (ECOG 2-3 vs 0-1: median OS – 5.6 mos vs 12.4 mos, median PFS – 2.7 vs 4.2 mos) and those with bone mts (with mts vs without mts: median OS – 5.0 vs 12.5 mos, median PFS – 2.8 vs 4.1 mos) had worse survival; log-rank p < 0.05. QoL improved during 6 mos of treatment in more than 50% pts; average increase by 60% of mean Integral QoL Index (IQoLI) at different time-points was observed. Upon GEE, IQoLI improvement during 12 mos was revealed (p < .0001). The severity of fatigue and dyspnea, which had the highest burden at base-line, decreased during 6 mos of treatment in more than 50% and 30% pts, consequently. AEs were registered in 32.7% pts (median of Nivo treatment – 2 mos); among them 17 pts had grades 3-4 AEs; 5 pts – SAEs. Conclusions: Preliminary results of this study support the acceptable efficacy and safety of Nivo in NSCLC pts. Nivo treatment leads to meaningful QoL improvement and decrease of symptom burden in this patient population.

Based on a new developed author’s method for recognition traces of reflections from different layers of the ionosphere in ionograms, the ionosphere parameters are extracted. The method is based on the use of deep neural networks (DNN). The rules for extracting the ionosphere parameters in ionograms are given. Based on the results obtained by the authors, an intelligent support system for ionogram analysis is being developed.

Topical problems of monitoring and analysis of lightning activity are considered. The paper also presents monthly distributions of lightning discharges over the globe. The instrumentation applied in VLF signal registration is described. An algorithm of search for possible areas of lightning activity affecting whistler occurrence in a defined region is suggested. The algorithm compares each detected whistler with the data of the World Wide Lightning Location Network. It also may be used to analyze different time intervals of the world lightning activity from the moment of whistler formation.

This paper describes performance of an interpreter uncovering meanings of prepositions in "master" — preposition — "slave" constructions. The basis of the semantic interpreter is a set of "if A, than B" rules, with the left parts containing lexical and semantic markers of the "masters" and the "slaves" and morphological markers of the "slaves" (cases) and the right parts containing the meanings of the prepositions which should be attributed if the conditions of the left parts are fulfilled. It is described how, on the basis of the interpreter, the basic onto-sematic rules can be formalized to be implemented into an onto-sematic analyzer and how performance of the analyzer can be improved with implementation of new rules.

Algorithms for streaming whistler recognition are offered. Different stages of algorithms are considered. The developed algorithms are used on a mini-computer software and hardware complexes for monitoring very low-frequency electromagnetic radiation at the Karymshina station in Kamchatka, on Oybenkel Geophysical Observatory of the Yu.G. Shafer Institute of Cosmophysical Research and Aeronomy (the Sakha Republic (Yakutia)), as well as recognition of whistlers is performed on the basis of open access data of abelian.org VLF station network in Todmorden United Kingdom (53,703N, 2.072W), Bielefeld Germany (52.146N, 8.458E), Cumiana Italy (44.96N, 7.42E), Warsaw Poland (52.16313N, 21.03094E), Australia Heathcote (36.804163S 144.67559E). Our whistler recognition results allowed us to establish on the days of strong whistler activity, there is an average positive correlation between the number of whistlers registered at Karymshino station in minutes of a day and the number of lightning strokes registered by WWLLN global network in minutes of a day in the coordinate rectangle LAT 25S-45S, LON 140E-160E (Australia).

Since from November 2017 to August 2018, synchronous registration of atmospherics and whistlers at the radiophysical station “Oibenkyol”, began in the operational mode within the network SSAN/VLF (“Sensor signal analysis network/Very low frequency”). The classification and the characteristics of the registered whistlers are carried out. The correlation analysis of the number of the whistlers registered by the SSAN/VLF with the number of lightning registered by the WWLLN is used to determine the location of lightning sources of whistlers in the opposite hemisphere in the magnetoconjugate point at South of Australia. Thus, the SSAN/VLF make possible the distance monitoring of the dynamics of the various geophysical processes changes. The large number of registered nose whistlers allow performing the statistical analysis of processes occurring in the magnetosphere’ plasma.

The seed selection (a.k.a. the influence maximization) problem has attracted a lot of attention because it enables the optimization of viral marketing in online social networks. Existing approaches select the seeds in batch during a single stage that precedes the initiation of the viral spread. However, they do not take into account the fact that influential users tend to cluster and, thus, select seeds sub-optimally. In this paper, a multi-stage seed selection approach is proposed, that performs seed selection in several stages. In each stage, seeds are selected among the central nodes that have not yet been activated. Thus, the proposed approach exploits the information that is acquired during the previous stages in order to improve its performance in the forthcoming stages. Experimental results using data from a real-world social network show that the proposed approach brings significant improvement in performance (up to 30% compared to the single-stage approach).

e12012 Background: One of the most serious potential side effects of chemotherapy is neutropenia. Grade 3 and 4 neutropenia is especially problematic because of increased incidence of infections, hospitalization, antibiotic treatment, necessity to reduce therapy intensity. The intensity of adjuvant chemotherapy is the key to successful treatment. Dicarbamin is agent for the prevention of chemotherapy-induced neutropenia. Dicarbamin therapy decreases dystrophic changes in myeloid progenitor cells and decreases the relative number of cells with signs of apoptosis. We conducted an analysis of efficacy of dicarbamin in patients during docetaxel-based chemotherapy. Methods: Between May 2011 and July 2012, 87 patients with early breast cancer were treated with adjuvant DAC regimens (docetaxel 75 mg/m2, doxorubicin 50 mg/m2, cyclophosphamide 500 mg/m2 every 3 weeks). All patients were female. All patients were treated with these regimens without prophylactic growth factor support. 42 patients of control (group A) were not given any prophylaxis of neutropenia. 45 patients (group B) were given dicarbamin 100 mg/day on day 5 before chemotherapy administration. Treatment with dicarbamin continued for all treatment period. Neutropenia was evaluated with Common Toxicity Criteria, Version 3.0. Results: Median age was 47 (29 – 55). Grade 4 neutropenia was reported in 13 (30.9%) patients treated without dicarbamin (A) and in 8 (17.7%) patients treated with dicarbamin (B). Grade 4 neutropenia was observed in 39 cycles in group A and in 22 cycles in group B (p=0.016). The beneficial effect of dicarbamin was also demonstrated by a quick recovery of granulocytes levels than in controls. In 17 (37.7%) patients treated with dicarbamin granulocytes levels were normal all period of chemotherapy. The dose intensity of chemotherapy was more in group with dicarbamin prophilaxis. The toxicity of dicarbamin was not observed. Conclusions: Dicarbamin is an active agent for prophylaxis of neutropenia without specific toxicity. The intensity of the DAC-chemotherapy was more in group with dicarbamin prophilaxis.