Scientific collaboration

The Clinical Research Centre offers academic and industrial partners access to an integrated research platform combining clinical phenotyping, metabolic measurements and molecular analytics. We deliver projects as scientific collaborations – from joint grant applications, through cohort and interventional studies, to providing equipment and analytical expertise as research services.

“Research is to see what everybody has seen and to think what nobody has thought.”

Albert Szent-Györgyi, Nobel laureate in Physiology or Medicine

Research and equipment

Clinical infrastructure

We provide the facilities needed to run studies with patients – from collecting biological material, through supporting study monitoring, to team meetings and training.

Facilities

  • Dedicated blood-collection points

    Collection points for biological material staffed by experienced nurses. Samples are pre-processed on site, shortening the time from collection to analysis or freezing.

  • Clinical research monitors’ office

    Dedicated workstations for sponsors’ and CROs’ clinical research monitors, enabling source-data verification and review of study documentation in line with Good Clinical Practice (GCP).

  • Seminar room

    A space for research-team meetings, study initiation and close-out visits, and staff training.

Fitness and exercise physiology

We assess aerobic and anaerobic capacity, the cardiovascular and respiratory response to exercise and the use of energy substrates during muscle work. The results support research on obesity and diabetes as well as athlete testing.

Equipment

  • Cardiopulmonary exercise testing (CPET) – cycle ergometers and treadmill

    A graded exercise test with breath-by-breath gas-exchange analysis. It determines maximal oxygen uptake (VO₂max), ventilatory thresholds and VO₂ kinetics, and the heart-rate and blood-pressure response to exercise.

  • Wingate test

    A short, maximal cycle-ergometer effort with a load matched to body mass. It measures peak power, mean power and the fatigue index – the key parameters of anaerobic capacity.

  • K5 portable analyser (COSMED)

    A lightweight wearable system measuring gas exchange and energy expenditure outside the laboratory – in the field, during training and everyday activity.

Energy metabolism

We measure how much energy the body uses and which substrates it draws on – at rest, after a meal and over a full day.

Equipment

  • Metabolic chambers – WRIC

    Sealed rooms for whole-room indirect calorimetry. A participant can stay inside for up to 24 hours while the system continuously analyses oxygen consumption and carbon-dioxide production. This yields energy expenditure (EE), the respiratory quotient (RQ) and carbohydrate and fat oxidation under tightly controlled conditions. It is the first research infrastructure of this kind in Poland.

  • Indirect calorimetry – RMR (metabolic cart / canopy)

    Resting metabolic rate measured with a transparent canopy or mask. Gas exchange is used to determine baseline energy requirements and the proportion of substrates being oxidised.

Body composition

We precisely determine the amount and distribution of fat, muscle and bone tissue – key for assessing metabolic risk and treatment effects.

Equipment

  • DXA densitometer

    Dual-energy X-ray absorptiometry – a low-dose measurement of fat mass (FM), lean mass (LM) and bone mineral density (BMD), by body segment, with assessment of visceral fat.

  • InBody body-composition analyser

    Multi-frequency bioimpedance (BIA) – a quick, non-invasive measurement of muscle and fat mass, total body water and segmental balance; well suited to repeated measurements during a study.

Mitochondrial function

We study how efficiently cells produce energy and how this changes with exercise, diet and treatment.

Equipment

  • Oroboros O2k high-resolution respirometer

    An oxygraph measuring oxygen consumption by permeabilised muscle fibres, cells and isolated mitochondria. SUIT protocols allow individual respiratory-chain complexes and oxidative capacity to be assessed.

  • Seahorse XF analyser

    An extracellular flux analyser that simultaneously measures the oxygen consumption rate (OCR) and extracellular acidification (ECAR) of living cells – the profile of mitochondrial respiration and glycolysis.

Biochemical analyses

We determine hormones, proteins and biomarkers in biological material collected from study participants.

Equipment

  • DYNEX ELISA system

    An automated system for immunoenzymatic assays – quantitative determination of hormones, proteins and other biomarkers in many samples at once.

  • Tecan Freedom EVO workstation

    A robotic liquid-handling workstation that automates sample and assay preparation, ensuring reproducibility and high throughput.

Molecular biology and biobanking

We analyse participants’ genetic material and store samples for future analyses.

Equipment

  • Molecular biology – isolation, genotyping, qPCR

    DNA and RNA isolation, genotyping of genetic variants and real-time quantitative PCR (qPCR) – the basis of genomic analyses, gene-expression studies and pharmacogenomics.

  • Biobanking (−80 °C)

    Long-term storage of biological material in −80 °C freezers, together with complete sample metadata, enabling future molecular analyses.

Continuous glucose and physical activity monitoring

We record participants’ glucose, activity, sleep and physiological parameters in everyday life – over many days, outside the laboratory.

Equipment

  • Continuous glucose monitoring (CGM)

    Sensors that measure glucose every few minutes over many days. They provide glucose profiles and variability indices such as time in range (TIR) and MAGE, and show glycaemic responses to meals and exercise.

  • Wearable devices

    Activity bands, smartwatches and rings as well as validated research-grade accelerometers. They record step count, physical activity and sedentary behaviour, heart rate and heart-rate variability (HRV), energy expenditure, and sleep duration, stages and quality.

Our collaborations

Publications

2026

  1. Cellular and Humoral Immune Responses in Anti-N Seropositive and Seronegative Vaccinated Participants: Insights from the Bialystok PLUS Study

    Trojan G, Moniuszko-Malinowska A, Adamczuk J, …, Szczerbiński Ł, …, Kamiński KA (19)

    Vaccines (Basel)2026PubMedDOI

  2. Multi-omic signatures of genetic mechanisms inform on type 2 diabetes biology and patient heterogeneity

    Sevilla-González M, Martínez-Muñoz AM, Hanson PA, …, Szczerbinski L, …, Udler MS (22)

    medRxiv2026PubMedDOI

  3. Enhancing Type 1 Diabetes Polygenic Risk Prediction Through Neural Networks and Entropy-Derived Insights

    Nadal-Martínez A, Pérez-Solero G, Ferreiro López S, …, Szczerbinski L, …, Tenorio-Castano J (14)

    Int J Mol Sci2026PubMedDOI

  4. RAB3GAP2 is a regulator of skeletal muscle endothelial cell proliferation and associated with capillary-to-fiber ratio

    Ström K, Oskolkov N, Karaderi T, …, Szczerbiński Ł, …, Hansson O (55)

    Cell Rep2026PubMedDOI

  5. Novel Phenotypic Clusters of Youth-Onset Type 2 Diabetes Offer No Added Prognostic Value to Simple Clinical Measures

    Kreienkamp RJ, Smith K, Wangden TY, …, Szczerbinski L, …, Srinivasan S (17)

    Diabetes Care2026PubMedDOI

2025

  1. Opportunistic screening of type 2 diabetes with deep metric learning using electronic health records

    Jin Q, Zhang H, Szczerbinski L, …, Ghassemi M (15)

    Sci Rep2025PubMedDOI

  2. Common genetic variants near SLC2A2 and glycemic response to glimepiride in the GRADE comparative effectiveness clinical trial

    Li JH, Szczerbinski L, Tripputi M, …, Florez JC (34)

    medRxiv2025PubMedDOI

  3. The Effect of Habitual Sleep Duration on Weight Loss during a Behavioral Weight Loss Intervention in a Mediterranean Population

    Rodríguez-Martín M, Szczerbinski L, Garaulet M, Dashti HS

    J Nutr2025PubMedDOI

  4. The Silent Weight of Nutrition Data in Glucagon-Like Peptide-1 Receptor Agonists Clinical Trials

    Dashti HS, Szczerbinski L

    Adv Nutr2025PubMedDOI

  5. The impact of exercise on skeletal muscle proteome of prediabetic subjects analyzed with data independent mass spectrometry

    Czajkowska A, Szczerbiński Ł, Czajkowski M, …, Zabielski P (8)

    Sci Rep2025PubMedDOI

  6. Donor-specific response of visceral adipocytes differentiated from human adipose-derived mesenchymal stem cells to branched-chain alpha-keto acid (BCKA) dehydrogenase activation

    Supruniuk E, Mikłosz A, Łukaszuk B, …, Szczerbiński Ł, …, Chabowski A (9)

    Biomed Pharmacother2025PubMedDOI

  7. Assessment of the Abnormalities in Chest Computed Tomography and Pulmonary Function Test in Convalescents Six Months After COVID-19

    Guziejko K, Moniuszko-Malinowska A, Flisiak R, …, Szczerbiński Ł, …, Kamiński KA (14)

    Medicina (Kaunas)2025PubMedDOI

  8. COVID-19 conspiracy beliefs in Poland. Predictors, psychological and social impact and adherence to public health guidelines over one year

    Kiszkiel Ł, Sowa P, Laskowski PP, …, Szczerbiński Ł, …, Kamiński K (14)

    Sci Rep2025PubMedDOI

  9. Association between plausible genetic factors and weight loss from GLP1-RA and bariatric surgery

    German J, Cordioli M, Tozzo V, …, Szczerbinski L, …, Ganna A (32)

    Nat Med2025PubMedDOI

  10. Investigation into biased signaling, glycosylation, and drug vulnerability of acute myeloid leukemia

    Pienkowski T, Golonko A, Bolkun L, …, Szczerbinski L, …, Swislocka R (10)

    Pharmacol Ther2025PubMedDOI

  11. Determinants and dynamics of the seroprevalence of anti-SARS-CoV-2 antibodies in Poland

    Adamczuk J, Kamiński KA, Sołomacha S, …, Szczerbiński Ł, …, Moniuszko-Malinowska A (16)

    Adv Med Sci2025PubMedDOI

  12. Association between plausible genetic factors and weight loss from GLP1-RA and bariatric surgery: a multi-ancestry study in 10 960 individuals from 9 biobanks

    German J, Cordioli M, Tozzo V, …, Szczerbinski L, …, Ganna A (32)

    medRxiv2025PubMedDOI

2024

  1. Algorithms for the identification of prevalent diabetes in the All of Us Research Program validated using polygenic scores

    Szczerbinski L, Mandla R, Schroeder P, …, Manning AK (9)

    Sci Rep2024PubMedDOI

  2. Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes

    Huerta-Chagoya A, Schroeder P, Mandla R, …, Szczerbinski L, …, Mercader JM (26)

    Nat Genet2024PubMedDOI

  3. Exploring protein relative relations in skeletal muscle proteomic analysis for insights into insulin resistance and type 2 diabetes

    Czajkowska A, Czajkowski M, Szczerbinski L, …, Kretowski A (9)

    Sci Rep2024PubMedDOI

  4. Biomaterials in Cancer Therapy: Investigating the Interaction between Kaempferol and Zinc Ions through Computational, Spectroscopic and Biological Analyses

    Golonko A, Olichwier AJ, Paszko A, Świsłocka R, Szczerbiński Ł, Lewandowski W

    Materials (Basel)2024PubMedDOI

  5. Apigenin's Modulation of Doxorubicin Efficacy in Breast Cancer

    Golonko A, Olichwier AJ, Szklaruk A, …, Szczerbiński Ł, …, Lewandowski W (7)

    Molecules2024PubMedDOI

  6. The Influence of Lifestyle on Male Fertility in the Context of Insulin Resistance-Identification of Factors That Influence Semen Quality

    Zańko A, Martynowicz I, Citko A, …, Szczerbiński Ł, …, Milewski R (11)

    J Clin Med2024PubMedDOI

  7. Assessment of smell disturbances 6 months after COVID-19 in Polish population

    Okrzeja J, Sołomacha S, Alimowski M, …, Szczerbiński Ł, …, Moniuszko-Malinowska A (14)

    Sci Rep2024PubMedDOI

  8. Dietary factors and their influence on immunotherapy strategies in oncology: a comprehensive review

    Golonko A, Pienkowski T, Swislocka R, …, Szczerbinski L, …, Lewandowski W (8)

    Cell Death Dis2024PubMedDOI

  9. Multi-ancestry polygenic mechanisms of type 2 diabetes

    Smith K, Deutsch AJ, McGrail C, …, Szczerbinski L, …, Udler MS (20)

    Nat Med2024PubMedDOI

2023

  1. The FCGR2A Is Associated with the Presence of Atherosclerotic Plaques in the Carotid Arteries-A Case-Control Study

    Szpakowicz A, Szum-Jakubowska A, Lisowska A, …, Szczerbiński Ł, …, Kamiński KA (10)

    J Clin Med2023PubMedDOI

  2. Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity

    Smith K, Deutsch AJ, McGrail C, …, Szczerbinski L, …, Udler MS (18)

    Res Sq2023PubMedDOI

  3. Multi-ancestry Polygenic Mechanisms of Type 2 Diabetes Elucidate Disease Processes and Clinical Heterogeneity

    Smith K, Deutsch AJ, McGrail C, …, Szczerbinski L, …, Udler MS (18)

    medRxiv2023PubMedDOI

  4. Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes

    Schroeder P, Mandla R, Huerta-Chagoya A, …, Szczerbinski L, …, Mercader JM (19)

    medRxiv2023PubMedDOI

  5. Precision medicine of obesity as an integral part of type 2 diabetes management - past, present, and future

    Szczerbinski L, Florez JC

    Lancet Diabetes Endocrinol2023PubMedDOI

  6. Long-term effects of COVID-19 on the endocrine system - a pilot case-control study

    Szczerbiński Ł, Okruszko MA, Szabłowski M, …, Kamiński K (10)

    Front Endocrinol (Lausanne)2023PubMedDOI

  7. Algorithms for the identification of prevalent diabetes in the All of Us Research Program validated using polygenic scores - a new resource for diabetes precision medicine

    Szczerbinski L, Mandla R, Schroeder P, …, Udler MS (9)

    medRxiv2023PubMedDOI

  8. Assessment of the Immune Response in Patients with Insulin Resistance, Obesity, and Diabetes to COVID-19 Vaccination

    Warpechowski J, Leszczyńska P, Juchnicka D, Olichwier A, Szczerbiński Ł, Krętowski AJ

    Vaccines (Basel)2023PubMedDOI

  9. The Effect of Laparoscopic Sleeve Gastrectomy on the Course of Non-Alcoholic Fatty Liver Disease in Morbidly Obese Patients during One Year of Follow Up

    Głuszyńska P, Łukaszewicz A, Diemieszczyk I, …, Szczerbiński Ł, …, Razak Hady H (9)

    J Clin Med2023PubMedDOI

  10. The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes

    Huerta-Chagoya A, Schroeder P, Mandla R, …, Szczerbiński L, …, Mercader JM (63)

    Diabetologia2023PubMedDOI

  11. Immune Response to Vaccination against COVID-19 at Different Second-Dose Intervals and Their Associations with Metabolic Parameters

    Szczerbiński Ł, Okruszko MA, Szabłowski M, …, Krętowski AJ (9)

    Vaccines (Basel)2023PubMedDOI

2022

  1. Why Do Dietary Flavonoids Have a Promising Effect as Enhancers of Anthracyclines? Hydroxyl Substituents, Bioavailability and Biological Activity

    Golonko A, Olichwier AJ, Swislocka R, Szczerbinski L, Lewandowski W

    Int J Mol Sci2022PubMedDOI

  2. Patient's Perspective of Telemedicine in Poland-A Two-Year Pandemic Picture

    Sołomacha S, Sowa P, Kiszkiel Ł, …, Szczerbiński Ł, …, Kamiński K (9)

    Int J Environ Res Public Health2022PubMedDOI

  3. Testing the Utility of Polygenic Risk Scores for Type 2 Diabetes and Obesity in Predicting Metabolic Changes in a Prediabetic Population: An Observational Study

    Padilla-Martinez F, Szczerbiński Ł, Citko A, …, Kretowski A (9)

    Int J Mol Sci2022PubMedDOI

  4. COVID-19 pandemic influence on self-reported health status and well-being in a society

    Moniuszko-Malinowska A, Czupryna P, Dubatówka M, …, Szczerbiński Ł, …, Kamiński KA (13)

    Sci Rep2022PubMedDOI

  5. Exploring microRNAs as predictive biomarkers for type 2 diabetes mellitus remission after sleeve gastrectomy: A pilot study

    Wojciechowska G, Szczerbinski L, Kretowski M, Niemira M, Hady HR, Kretowski A

    Obesity (Silver Spring)2022PubMedDOI

  6. Risk Factors for Early and Late Complications after Laparoscopic Sleeve Gastrectomy in One-Year Observation

    Głuszyńska P, Diemieszczyk I, Szczerbiński Ł, Krętowski A, Major P, Razak Hady H

    J Clin Med2022PubMedDOI

  7. Untargeted Metabolomics Analysis of the Serum Metabolic Signature of Childhood Obesity

    Szczerbinski L, Wojciechowska G, Olichwier A, …, Kretowski A (14)

    Nutrients2022PubMedDOI

2021

  1. Circulating Nucleic Acid-Based Biomarkers of Type 2 Diabetes

    Padilla-Martinez F, Wojciechowska G, Szczerbinski L, Kretowski A

    Int J Mol Sci2021PubMedDOI

  2. Metabolomic Profile of Skeletal Muscle and Its Change Under a Mixed-Mode Exercise Intervention in Progressively Dysglycemic Subjects

    Szczerbinski L, Golonko A, Taylor M, …, Kretowski A (13)

    Front Endocrinol (Lausanne)2021PubMedDOI

  3. The Response of Mitochondrial Respiration and Quantity in Skeletal Muscle and Adipose Tissue to Exercise in Humans with Prediabetes

    Szczerbinski L, Taylor MA, Puchta U, …, Kretowski A (11)

    Cells2021PubMedDOI

  4. An Association between Diet and MC4R Genetic Polymorphism, in Relation to Obesity and Metabolic Parameters-A Cross Sectional Population-Based Study

    Adamska-Patruno E, Bauer W, Bielska D, …, Szczerbinski L, …, Kretowski A (14)

    Int J Mol Sci2021PubMedDOI

  5. COVID-19 Vaccine Hesitancy in Poland-Multifactorial Impact Trajectories

    Sowa P, Kiszkiel Ł, Laskowski PP, …, Szczerbiński Ł, …, Kamiński K (8)

    Vaccines (Basel)2021PubMedDOI

  6. Atorvastatin impairs liver mitochondrial function in obese Göttingen Minipigs but heart and skeletal muscle are not affected

    Christiansen LB, Dohlmann TL, Ludvigsen TP, …, Szczerbinski L, …, Larsen S (13)

    Sci Rep2021PubMedDOI

  7. A Polygenic Score for Type 2 Diabetes Risk Is Associated With Both the Acute and Sustained Response to Sulfonylureas

    Li JH, Szczerbinski L, Dawed AY, …, Florez JC (7)

    Diabetes2021PubMedDOI

2020

  1. The influence of patient's age on metabolic and bariatric results of laparoscopic sleeve gastrectomy in 2-year observation

    Woźniewska P, Diemieszczyk I, Groth D, …, Szczerbiński Ł, …, Hady HR (8)

    BMC Surg2020PubMedDOI

  2. Circulating miRNAs as a Predictive Biomarker of the Progression from Prediabetes to Diabetes: Outcomes of a 5-Year Prospective Observational Study

    Sidorkiewicz I, Niemira M, Maliszewska K, …, Szczerbinski L, …, Kretowski A (10)

    J Clin Med2020PubMedDOI

  3. Evaluation of Transcriptomic Regulations behind Metabolic Syndrome in Obese and Lean Subjects

    Paczkowska-Abdulsalam M, Niemira M, Bielska A, …, Szczerbiński Ł, …, Krętowski A (12)

    Int J Mol Sci2020PubMedDOI

2019

  1. Ceramide Content in Liver Increases Along with Insulin Resistance in Obese Patients

    Razak Hady H, Błachnio-Zabielska AU, Szczerbiński Ł, …, Krętowski AJ (7)

    J Clin Med2019PubMedDOI

  2. Sex-Specific Glucose Homeostasis and Anthropometric Responses to Sleeve Gastrectomy in Obese Patients

    Taylor MA, Szczerbinski L, Citko A, …, Kretowski A (7)

    Nutrients2019PubMedDOI

  3. Meta-Analysis of Differential miRNA Expression after Bariatric Surgery

    Langi G, Szczerbinski L, Kretowski A

    J Clin Med2019PubMedDOI

  4. Clusters of Glycemic Response to Oral Glucose Tolerance Tests Explain Multivariate Metabolic and Anthropometric Outcomes of Bariatric Surgery in Obese Patients

    Szczerbinski L, Taylor MA, Citko A, …, Kretowski A (7)

    J Clin Med2019PubMedDOI

  5. Efficacy of family history, genetic risk score, and physical activity in assessing the prevalence of type 2 diabetes

    Szczerbiński Ł, Gościk J, Bauer W, …, Krętowski A (10)

    Pol Arch Intern Med2019PubMedDOI

  6. Flow Mediated Skin Fluorescence technique reveals remarkable effect of age on microcirculation and metabolic regulation in type 1 diabetes

    Katarzynska J, Borkowska A, Czajkowski P, …, Szczerbinski L, …, Gebicki J (10)

    Microvasc Res2019PubMedDOI

2018

  1. Hypoglycemia in sulfonylurea-treated KCNJ11-neonatal diabetes: Mild-moderate symptomatic episodes occur infrequently but none involving unconsciousness or seizures

    Lanning MS, Carmody D, Szczerbiński Ł, Letourneau LR, Naylor RN, Greeley SAW

    Pediatr Diabetes2018PubMedDOI

  2. The type 2 diabetes susceptibility TCF7L2 gene variants affect postprandial glucose and fat utilization in non-diabetic subjects

    Adamska E, Kretowski A, Goscik J, …, Szczerbinski L, …, Gorska M (12)

    Diabetes Metab2018PubMedDOI

2014

  1. Hematological parameters in adolescents with hyperuricemia

    Stelmach MJ, Szczerbinski L, Wasilewska N, Protas P, Wasilewska A

    Indian Pediatr2014PubMedDOI

Source: PubMed, as of 6 October 2026.

Google Scholar profile ↗All results in PubMed ↗

Methods and research areas

Deep metabolic phenotyping, precision medicine and pharmacogenomics, genome-wide association studies (GWAS) and polygenic scores (PRS), metabolomics and multi-omic data integration, machine-learning predictive models, as well as clinical registries and clinical-trial support – from concept, through recruitment and data acquisition, to analysis.

Data resources and biobank

We maintain deeply phenotyped research cohorts and a biobank of biological material. The detailed scope of available data and resources is discussed individually – please contact us regarding collaboration.

For collaboration enquiries, please contact us:

badania.cbk@umb.edu.pl

← Back to the home page