Andrzej Jarynowski

Dr. Andrzej Jarynowski

Freie Universität Berlin, Berlin, Germany
orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 March 2019
Verified
Book Chapter
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SVSalvatore Vitabile
Salvatore Vitabile
MMMichal Marks
Michal Marks
DSDragan Stojanović
Dragan Stojanović
SPSabri Pllana
Sabri Pllana
Jose M. MolinaJose M. Molina
Jose M. Molina
Ioan SalomieIoan Salomie
Ioan Salomie
Recent developments in sensor technology, wearable computing, Internet of Things (IoT), and wireless communication have given rise to research in ubiquitous healthcare and remote monitoring of human’s health and activities. Health monitoring systems involve processing and analysis of data retrieved from smartphones, smart watches, smart bracelets, as well as various sensors and wearable devices. Such systems enable continuous monitoring of patients psychological and health conditions by sensing and transmitting measurements such as heart rate, electrocardiogram, body temperature, respiratory rate, chest sounds, or blood pressure. Pervasive healthcare, as a relevant application domain in this context, aims at revolutionizing the delivery of medical services through a medical assistive environment and facilitates the independent living of patients. In this chapter, we discuss (1) data collection, fusion, ownership and privacy issues; (2) models, technologies and solutions for medical data processing and analysis; (3) big medical data analytics for remote health monitoring; (4) research challenges and opportunities in medical data analytics; (5) examples of case studies and practical solutions.

10 September 2013 in New Phytologist
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Journal Article
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GMGiulia Morieri
Giulia Morieri
EMEduardo A. Martinez
Eduardo A. Martinez
AJAndrzej Jarynowski
Andrzej Jarynowski
HDHugues Driguez
Hugues Driguez
RMRichard Morris
Richard Morris
JDJ. Allan Downie
J. Allan Downie
Summary: Rhizobial nodulation (Nod) factors activate both nodule morphogenesis and infection thread development during legume nodulation. Nod factors induce two different calcium responses: intra‐nuclear calcium oscillations and a calcium influx at the root hair tip. Calcium oscillations activate nodule development; we wanted to test if the calcium influx is associated with infection. Sinorhizobium meliloti nodL and nodF mutations additively reduce infection of Medicago truncatula. Nod‐factors made by the nodL mutant lack an acetyl group; mutation of nodF causes the nitrogen (N)‐linked C16:2 acyl chain to be replaced by C18:1. We tested whether these Nod‐factors differentially induced calcium influx and calcium spiking. The absence of the NodL‐determined acetyl group greatly reduced the induction of calcium influx without affecting calcium spiking. The calcium influx was even further reduced if the N‐linked C16:2 acyl group was replaced by C18:1. These additive effects on calcium influx correlate with the additive effects of mutations in nodF and nodL on legume infection. Infection thread development is inhibited by ethylene, which also inhibited Nod‐factor‐induced calcium influx. We conclude that Nod‐factor perception differentially activates the two developmental pathways required for nodulation and that activation of the pathway involving the calcium influx is important for efficient infection.

13 April 2020 in Society Register
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Journal Article
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AJAndrzej Jarynowski
Andrzej Jarynowski
MWMonika Wójta-Kempa
Monika Wójta-Kempa
DPDaniel Płatek
Daniel Płatek
KCKarolina Czopek
Karolina Czopek
Recently, the whole of Europe, including Poland, have been significantly affected by COVID-19 and its social and economic consequences which are already causing dozens of billions of euros monthly losses in Poland alone. Social behaviour has a fundamental impact on the dynamics of the spread of infectious diseases such as SARS-CoV-2, challenging the existing health infrastructure and social organization. Modelling and understanding mechanisms of social behaviour (e.g. panic and social distancing) and its contextualization with regard to Poland can contribute to better response to the outbreak on a national and local level. In the presented study we aim to investigate the impact of the COVID-19 on society by: (i) measuring the relevant activity in internet news and social media; (ii) analysing attitudes and demographic patterns in Poland. In the end, we are going to implement computational social science and digital epidemiology research approach to provide urgently needed information on social dynamics during the outbreak. This study is an ad hoc reaction only, and our goal is to signal the main areas of possible research to be done in the future and cover issues with direct or indirect relation to public health.

29 November 2021 in Journal of Medical Internet Research
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Journal Article
Open access
AJAndrzej Jarynowski
Andrzej Jarynowski
SASe­me­nov Alexan­der
Se­me­nov Alexan­der
MKMikołaj Kamiński
Mikołaj Kamiński
VBVitaly Belik
Vitaly Belik
Background: There is a limited amount of data on the safety profile of the COVID-19 vector vaccine Gam-COVID-Vac (Sputnik V). Previous infodemiology studies showed that social media discourse could be analyzed to assess the most concerning adverse events (AE) caused by drugs. Objective: We aimed to investigate mild AEs of Sputnik V based on a participatory trial conducted on Telegram in the Russian language. We compared AEs extracted from Telegram with other limited databases on Sputnik V and other COVID-19 vaccines. We explored symptom co-occurrence patterns and determined how counts of administered doses, age, gender, and sequence of shots could confound the reporting of AEs. Methods: We collected a unique dataset consisting of 11,515 self-reported Sputnik V vaccine AEs posted on the Telegram group, and we utilized natural language processing methods to extract AEs. Specifically, we performed multilabel classifications using the deep neural language model Bidirectional Encoder Representations from Transformers (BERT) “DeepPavlov,” which was pretrained on a Russian language corpus and applied to the Telegram messages. The resulting area under the curve score was 0.991. We chose symptom classes that represented the following AEs: fever, pain, chills, fatigue, nausea/vomiting, headache, insomnia, lymph node enlargement, erythema, pruritus, swelling, and diarrhea. Results: Telegram users complained mostly about pain (5461/11,515, 47.43%), fever (5363/11,515, 46.57%), fatigue (3862/11,515, 33.54%), and headache (2855/11,515, 24.79%). Women reported more AEs than men (1.2-fold, P<.001). In addition, there were more AEs from the first dose than from the second dose (1.1-fold, P<.001), and the number of AEs decreased with age (β=.05 per year, P<.001). The results also showed that Sputnik V AEs were more similar to other vector vaccines (132 units) than with messenger RNA vaccines (241 units) according to the average Euclidean distance between the vectors of AE frequencies. Elderly Telegram users reported significantly more (5.6-fold on average) systemic AEs than their peers, according to the results of the phase 3 clinical trials published in The Lancet. However, the AEs reported in Telegram posts were consistent (Pearson correlation r=0.94, P=.02) with those reported in the Argentinian postmarketing AE registry. Conclusions: After the Sputnik V vaccination, Russian Telegram users reported mostly pain, fever, and fatigue. The Sputnik V AE profile was comparable with other vector COVID-19 vaccines. Discussion on social media could provide meaningful information about the AE profile of novel vaccines.

ARAnna Romaszko-Wojtowicz
Anna Romaszko-Wojtowicz
SMStanisław Maksymowicz
Stanisław Maksymowicz
AJAndrzej Jarynowski
Andrzej Jarynowski
ŁJŁukasz Jaśkiewicz
Łukasz Jaśkiewicz
ŁCŁukasz Czekaj
Łukasz Czekaj
ADAnna Doboszyńska
Anna Doboszyńska
The COVID-19 pandemic has revealed the high usefulness of telemedicine. To date, no uniform recommendations or diagnostic protocols for long-COVID patients have been developed. This article presents the preliminary results of the examination of patients after SARS-CoV-2 infection who were provided with medical telemonitoring devices in order to oversee their pulmonological and cardiological health. Three cases have been analyzed. Each patient underwent a 10-day registration of basic vital signs, in three 15-min sessions daily: RR (respiratory rate), ECG (electrocardiogram), HR (pulse), SPO2 (saturation), body temperature and cough. Rule methods and machine learning were employed to automatically detect events. As a result, serious disorders of all the three patients were detected: cardiological and respiratory disorders that required extended diagnostics. Furthermore, average values of the selected parameters (RR, HR, SPO2) were calculated for every patient, including an indication of how often they exceeded the alarm thresholds. In conclusion, monitoring parameters in patients using telemedicine, especially in a time of limited access to the healthcare system, is a valuable clinical instrument. It enables medical professionals to recognize conditions which may endanger a patient’s health or life. Telemedicine provides a reliable assessment of a patient’s health status made over a distance, which can alleviate a patient’s stress caused by long-COVID syndrome. Telemedicine allows identification of disorders and performing further diagnosis, which is possible owing to the implementation of advanced analysis. Telemedicine, however, requires flexibility and the engagement of a multidisciplinary team, who will respond to patients’ problems on an ongoing basis.

10 November 2020 in Language Teaching
Verified
Journal Article
Open access
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MPMichał B. Paradowski
Michał B. Paradowski
AJAndrzej Jarynowski
Andrzej Jarynowski
MJMagdalena Jelińska
Magdalena Jelińska
KCKarolina Czopek
Karolina Czopek