Subjects -> BIOLOGY (Total: 3174 journals)
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BIOLOGY (1491 journals)            First | 1 2 3 4 5 6 7 8 | Last

Showing 401 - 600 of 1720 Journals sorted alphabetically
Cryoletters     Full-text available via subscription   (Followers: 4)
Cuadernos de Neuropsicología     Open Access   (Followers: 1)
Current Applied Science and Technology     Open Access  
Current Bioinformatics     Hybrid Journal   (Followers: 13)
Current Biology     Full-text available via subscription   (Followers: 228)
Current Genomics     Hybrid Journal   (Followers: 8)
Current Landscape Ecology Reports     Hybrid Journal   (Followers: 2)
Current Medical Science     Hybrid Journal   (Followers: 1)
Current Molecular Medicine     Hybrid Journal   (Followers: 3)
Current Opinion in Cell Biology     Hybrid Journal   (Followers: 51)
Current Opinion in Molecular Therapeutics     Full-text available via subscription   (Followers: 8)
Current Opinion in Neurobiology     Hybrid Journal   (Followers: 32)
Current Opinion in Structural Biology     Hybrid Journal   (Followers: 26)
Current Opinion in Systems Biology     Hybrid Journal   (Followers: 2)
Current Pharmacogenomics and Personalized Medicine     Hybrid Journal   (Followers: 3)
Current Protein and Peptide Science     Hybrid Journal   (Followers: 8)
Current Proteomics     Hybrid Journal   (Followers: 4)
Current Protocols in Bioinformatics     Hybrid Journal   (Followers: 1)
Current Protocols in Cell Biology     Hybrid Journal  
Current Protocols in Molecular Biology     Hybrid Journal  
Current Protocols in Mouse Biology     Hybrid Journal  
Current Protocols in Neuroscience     Hybrid Journal  
Current Protocols in Plant Biology     Hybrid Journal   (Followers: 2)
Current Protocols in Protein Science     Hybrid Journal   (Followers: 1)
Current Protocols in Stem Cell Biology     Hybrid Journal  
Current Research in Bacteriology     Open Access   (Followers: 3)
Current Research in Biostatistics     Open Access   (Followers: 8)
Current Research in Chemical Biology     Open Access  
Current Research in Neurobiology     Open Access  
Current Research in Parasitology & Vector-Borne Diseases     Open Access  
Current Research in Structural Biology     Open Access   (Followers: 1)
Current Research in Translational Medicine     Full-text available via subscription   (Followers: 1)
Current Research in Virological Science     Open Access   (Followers: 2)
Current Science     Open Access   (Followers: 116)
Current Stem Cell Reports     Hybrid Journal   (Followers: 4)
Current Stem Cell Research & Therapy     Hybrid Journal   (Followers: 8)
Current Topics in Developmental Biology     Full-text available via subscription   (Followers: 3)
Current Topics in Membranes     Full-text available via subscription   (Followers: 1)
Cytotechnology     Hybrid Journal   (Followers: 11)
Database : The Journal of Biological Databases and Curation     Open Access   (Followers: 10)
Dendrochronologia     Hybrid Journal   (Followers: 1)
Developing World Bioethics     Hybrid Journal   (Followers: 6)
Developmental & Comparative Immunology     Hybrid Journal   (Followers: 5)
Developmental Biology     Hybrid Journal   (Followers: 26)
Developmental Cell     Full-text available via subscription   (Followers: 46)
Developmental Dynamics     Hybrid Journal   (Followers: 4)
Developmental Neurobiology     Hybrid Journal   (Followers: 6)
Dhaka University Journal of Biological Sciences     Open Access  
Diatom Research     Hybrid Journal   (Followers: 3)
Differentiation     Hybrid Journal  
Digital Biomarkers     Open Access   (Followers: 1)
Disease Models and Mechanisms     Open Access   (Followers: 1)
Diseases of Aquatic Organisms     Hybrid Journal  
DNA and Cell Biology     Hybrid Journal   (Followers: 9)
DNA Repair     Hybrid Journal   (Followers: 3)
DNA Research     Open Access   (Followers: 4)
Doklady Physics     Hybrid Journal   (Followers: 1)
Drug Discovery Today: Technologies     Full-text available via subscription   (Followers: 13)
Drug Resistance Updates     Hybrid Journal   (Followers: 3)
e-Jurnal Rekayasa dan Teknologi Budidaya Perairan     Open Access  
Ecocycles     Open Access   (Followers: 4)
Ecohydrology & Hydrobiology     Full-text available via subscription   (Followers: 4)
Ecología en Bolivia     Open Access  
Ecological Engineering     Hybrid Journal   (Followers: 4)
Ecological Questions     Open Access   (Followers: 5)
Ecological Solutions and Evidence     Open Access   (Followers: 2)
Ecology and Society     Open Access   (Followers: 51)
Ecology Letters     Hybrid Journal   (Followers: 246)
Economics & Human Biology     Hybrid Journal   (Followers: 1)
Ecoprint : An International Journal of Ecology     Open Access   (Followers: 4)
Ecoscience     Hybrid Journal   (Followers: 2)
Ecosystem Health and Sustainability     Open Access   (Followers: 1)
Ecosystems and People     Open Access   (Followers: 2)
Educational Technology Research and Development     Partially Free   (Followers: 45)
EDUSAINS     Open Access  
EFB Bioeconomy Journal     Open Access  
Egyptian Journal of Basic and Applied Sciences     Open Access  
Egyptian Journal of Biology     Open Access  
Egyptian Journal of Natural History     Open Access   (Followers: 1)
EJNMMI Research     Open Access  
Ekologia     Open Access  
el-Hayah     Open Access  
Electromagnetic Biology and Medicine     Hybrid Journal  
eLife     Open Access   (Followers: 95)
Embo Molecular Medicine     Open Access   (Followers: 10)
EMBO reports     Full-text available via subscription   (Followers: 23)
Emotion Review     Hybrid Journal   (Followers: 20)
Endangered Species Research     Open Access   (Followers: 6)
Endocrine Connections     Open Access   (Followers: 4)
Endothelium: Journal of Endothelial Cell Research     Full-text available via subscription   (Followers: 3)
Engineering & Technology     Hybrid Journal   (Followers: 22)
Engineering Economist, The     Hybrid Journal   (Followers: 4)
Engineering in Life Sciences     Hybrid Journal   (Followers: 3)
Engineering Optimization     Hybrid Journal   (Followers: 19)
Ensaios e Ciência : Ciências Biológicas, Agrárias e da Saúde     Open Access  
Environmental Biology of Fishes     Hybrid Journal   (Followers: 4)
Environmental DNA     Open Access  
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 21)
Environmental Epigenetics     Open Access   (Followers: 2)
Environmental Microbiology     Hybrid Journal   (Followers: 27)
Environmental Microbiome     Open Access  
Environmental Science & Technology     Hybrid Journal   (Followers: 181)
Enzyme and Microbial Technology     Hybrid Journal   (Followers: 12)
Enzyme Research     Open Access   (Followers: 4)
Epidemiology & Infection     Open Access   (Followers: 23)
Epigenomes     Open Access  
EPMA Journal     Open Access  
Ethiopian Journal of Biological Sciences     Open Access   (Followers: 3)
Ethnobiology and Conservation     Open Access   (Followers: 3)
Ethnobiology Letters     Open Access  
Ethnobotany Research & Applications : a journal of plants, people and applied research     Open Access   (Followers: 2)
Ethnoscientia : Brazilian Journal of Ethnobiology and Ethnoecology     Open Access  
Ethology     Hybrid Journal   (Followers: 11)
Ethology Ecology & Evolution     Hybrid Journal   (Followers: 16)
EuPA Open Proteomics     Open Access   (Followers: 2)
EUREKA : Life Sciences     Open Access  
European Journal of Biological Research     Open Access   (Followers: 1)
European Journal of Biology     Open Access   (Followers: 1)
European Journal of Cell Biology     Hybrid Journal   (Followers: 6)
European Journal of Ecology     Open Access   (Followers: 1)
European Journal of Neuroscience     Hybrid Journal   (Followers: 36)
European Journal of Obstetrics & Gynecology and Reproductive Biology     Hybrid Journal   (Followers: 19)
European Journal of Obstetrics & Gynecology and Reproductive Biology : X     Open Access  
European Journal of Phycology     Hybrid Journal   (Followers: 4)
European Journal of Protistology     Hybrid Journal   (Followers: 5)
European Journal of Soil Biology     Hybrid Journal   (Followers: 3)
European Online Journal of Natural and Social Sciences     Open Access   (Followers: 4)
European Scientific Journal     Open Access   (Followers: 1)
Evidência - Ciência e Biotecnologia - Interdisciplinar     Open Access  
EvoDevo     Open Access   (Followers: 4)
Evolution     Partially Free   (Followers: 129)
Evolution and Human Behavior     Hybrid Journal   (Followers: 22)
Evolution Letters     Open Access   (Followers: 8)
Evolutionary Applications     Open Access   (Followers: 6)
Evolutionary Bioinformatics     Open Access   (Followers: 12)
Evolutionary Biology     Hybrid Journal   (Followers: 25)
Evolutionary Computation     Hybrid Journal   (Followers: 11)
Evolutionary Systematics     Open Access   (Followers: 2)
EXCLI Journal : Experimental and Clinical Sciences     Open Access  
Experimental & Molecular Medicine     Open Access  
Experimental and Applied Acarology     Hybrid Journal   (Followers: 1)
Experimental Parasitology     Hybrid Journal   (Followers: 1)
Expert Opinion on Biological Therapy     Hybrid Journal   (Followers: 4)
Expert Opinion on Environmental Biology     Hybrid Journal  
Expert Review of Proteomics     Hybrid Journal   (Followers: 4)
ExRNA     Open Access  
Extreme Life, Biospeology & Astrobiology - International Journal of the Bioflux Society     Full-text available via subscription   (Followers: 4)
Extremophiles     Hybrid Journal   (Followers: 1)
F&S Science : Official journal of the American Society for Reproductive Medicine     Open Access  
Facta Universitatis, Series : Medicine and Biology     Open Access  
Familial Cancer     Hybrid Journal   (Followers: 2)
FASEB BioAdvances     Open Access  
Fauna Norvegica     Open Access  
Fauna of New Zealand     Open Access  
Febs Journal     Hybrid Journal   (Followers: 29)
Feddes Repertorium     Hybrid Journal  
Fems Yeast Research     Hybrid Journal   (Followers: 11)
FIGEMPA : Investigación y Desarrollo     Open Access   (Followers: 1)
Fire Ecology     Open Access   (Followers: 2)
Fish & Shellfish Immunology     Hybrid Journal   (Followers: 10)
Fish and Shellfish Immunology Reports     Open Access   (Followers: 1)
Fishes     Open Access  
Fitoterapia     Hybrid Journal   (Followers: 4)
Florea : Jurnal Biologi dan Pembelajarannya     Open Access  
Fly     Full-text available via subscription  
Folia Biologica     Free   (Followers: 1)
Folia Histochemica et Cytobiologica     Open Access  
Folia Microbiologica     Hybrid Journal   (Followers: 2)
Folia Primatologica     Full-text available via subscription   (Followers: 4)
Food and Bioproducts Processing     Hybrid Journal   (Followers: 3)
Food and Ecological Systems Modelling Journal     Open Access  
Food and Waterborne Parasitology     Open Access  
Food Webs     Hybrid Journal   (Followers: 1)
Forensic Genomics     Full-text available via subscription   (Followers: 3)
Forest Pathology     Hybrid Journal   (Followers: 1)
Forschung     Hybrid Journal   (Followers: 1)
Foundations of Physics     Hybrid Journal   (Followers: 40)
Free Radical Biology and Medicine     Hybrid Journal   (Followers: 6)
Free Radical Research     Hybrid Journal   (Followers: 2)
Freshwater Science     Full-text available via subscription   (Followers: 14)
Frontiers in Ecology and Evolution     Open Access   (Followers: 45)
Frontiers in Evolutionary Neuroscience     Open Access   (Followers: 7)
Frontiers in Life Science     Hybrid Journal   (Followers: 1)
Frontiers in Marine Science     Open Access   (Followers: 13)
Frontiers in Network Physiology     Open Access   (Followers: 2)
Frontiers in Neurogenesis     Open Access   (Followers: 2)
Frontiers in Neuroprosthetics     Open Access   (Followers: 6)
Frontiers of Biogeography     Open Access   (Followers: 4)
Frontiers of Biology     Hybrid Journal   (Followers: 2)
Frontiers of Environmental Science & Engineering     Hybrid Journal   (Followers: 3)
Frontiers of Medical and Biological Engineering     Hybrid Journal  
Functional & Integrative Genomics     Hybrid Journal   (Followers: 7)
Fundamental and Applied Limnology / Archiv für Hydrobiologie     Full-text available via subscription   (Followers: 3)
Fundamental Research     Open Access  
Fungal Biology     Hybrid Journal   (Followers: 6)
Fungal Biology and Biotechnology     Open Access   (Followers: 2)
Fungal Biology Reviews     Full-text available via subscription   (Followers: 9)
Fungal Diversity     Hybrid Journal   (Followers: 2)
Fungal Ecology     Hybrid Journal   (Followers: 6)
Fungal Genetics Reports     Open Access  

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EPMA Journal
Journal Prestige (SJR): 0.807
Citation Impact (citeScore): 4
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Print) 1878-5077 - ISSN (Online) 1878-5085
Published by Springer-Verlag Homepage  [2469 journals]
  • Mitochondrial health quality control: measurements and interpretation in
           the framework of predictive, preventive, and personalized medicine

    • Abstract: Abstract Mitochondria are the “gatekeeper” in a wide range of cellular functions, signaling events, cell homeostasis, proliferation, and apoptosis. Consequently, mitochondrial injury is linked to systemic effects compromising multi-organ functionality. Although mitochondrial stress is common for many pathomechanisms, individual outcomes differ significantly comprising a spectrum of associated pathologies and their severity grade. Consequently, a highly ambitious task in the paradigm shift from reactive to predictive, preventive, and personalized medicine (PPPM/3PM) is to distinguish between individual disease predisposition and progression under circumstances, resulting in compromised mitochondrial health followed by mitigating measures tailored to the individualized patient profile. For the successful implementation of PPPM concepts, robust parameters are essential to quantify mitochondrial health sustainability. The current article analyses added value of Mitochondrial Health Index (MHI) and Bioenergetic Health Index (BHI) as potential systems to quantify mitochondrial health relevant for the disease development and its severity grade. Based on the pathomechanisms related to the compromised mitochondrial health and in the context of primary, secondary, and tertiary care, a broad spectrum of conditions can significantly benefit from robust quantification systems using MHI/BHI as a prototype to be further improved. Following health conditions can benefit from that: planned pregnancies (improved outcomes for mother and offspring health), suboptimal health conditions with reversible health damage, suboptimal life-style patterns and metabolic syndrome(s) predisposition, multi-factorial stress conditions, genotoxic environment, ischemic stroke of unclear aetiology, phenotypic predisposition to aggressive cancer subtypes, pathologies associated with premature aging and neuro/degeneration, acute infectious diseases such as COVID-19 pandemics, among others.
      PubDate: 2022-05-12
  • Comprehensive analysis of spliceosome genes and their mutants across 27
           cancer types in 9070 patients: clinically relevant outcomes in the context
           of 3P medicine

    • Abstract: Relevance Spliceosome machinery plays important roles in cell biological processes, and its alterations are significantly associated with cancer pathophysiological processes and contribute to the entire healthcare process in the framework of predictive, preventive, and personalized medicine (PPPM/3P medicine). Purpose To understand the expression and mutant status of spliceosome genes (SGs) in common malignant tumors and their relationship with clinical characteristics, a pan-cancer analysis of these SGs was performed across 27 cancer types in 9070 patients to discover biomarkers for cancer early diagnosis and prognostic assessment, effectively stratify patients, and improve the survival and prognosis of patients in 3P medical practice. Methods A total of 150 SGs were collected from the KEGG database. The Python and R language were combined to process the transcriptional data of SGs and clinical data of 27 cancer types in The Cancer Genome Atlas (TCGA) database. Mutations of SGs in 27 cancer types were analyzed to identify the most common mutated SGs, as well as survival-related SGs. Different SGs were screened out, and SGs with survival significance in different types of tumors were found. Furthermore, TCGA and GTEx datasets were used to further confirm the expressions of SGs in different tumors. Western blot assay was performed to verify the expression of SNRPB protein in colon cancer and lung adenocarcinoma. Three SGs were screened out to establish the Bagging model for tumor diagnosis. Results Among 150 SGs, THOC2, PRPF8, SNRNP200, and SF3B1 had the highest mutation rate. The survival time of mutant THOC2 and SF3B1 was better than that of wild type, respectively. The differential expression analysis of 150 SGs between 674 normal tissue samples and 9,163 tumor tissue samples with 27 cancer types of 9070 patients showed that 13 SGs were highly expressed and 1 was low-expressed. For all cancer types, the prognosis (survival time) of the low-expression group of three SGs (SNRPB, LSM7, and HNRNPCL1) was better than the high expression group, respectively (p < 0.05). Cox hazards model showed that male, over 60 years old, clinical stages III–IV, and with highly expressed SNRPB and HNRNPCL1 had a poor prognosis. GEPIA2 website analysis showed that SNRPB and LSM7 were highly expressed in most tumors but not in LAML, showing low expression. Compared with the control group, the expression of SNRPB protein in colon cancer was increased by Western blot (p < 0.05). Enrichment analysis showed that the differential SGs were mainly enriched in RNA splicing and binding. The average error of 10-fold cross-validation of the Bagging model for diagnosed cancer was 0.093, which demonstrates that the Bagging model can effectively diagnose cancer with a small error rate. Conclusions This study provided the first landscape of spliceosome changes across 27 cancer types in 9070 patients and revealed that spliceosome was related to tumor progression. Spliceosome may play important an important role in cancer biological processes. These findings are the important scientific data to demonstrate the common and specific changes of spliceosome genes across 27 cancer types, which is a valuable biomarker resource to under the common or specific molecular mechanisms among different cancer types and establish biomarkers and therapeutic targets for the common or specific management of different types of cancer patients to benefit the research and practice of 3P medicine in cancers.
      PubDate: 2022-05-10
  • Anti-breast cancer effects of phytochemicals: primary, secondary, and
           tertiary care

    • Abstract: Abstract Breast cancer incidence is actually the highest one among all cancers. Overall breast cancer management is associated with challenges considering risk assessment and predictive diagnostics, targeted prevention of metastatic disease, appropriate treatment options, and cost-effectiveness of approaches applied. Accumulated research evidence indicates promising anti-cancer effects of phytochemicals protecting cells against malignant transformation, inhibiting carcinogenesis and metastatic spread, supporting immune system and increasing effectiveness of conventional anti-cancer therapies, among others. Molecular and sub-/cellular mechanisms are highly complex affecting several pathways considered potent targets for advanced diagnostics and cost-effective treatments. Demonstrated anti-cancer affects, therefore, are clinically relevant for improving individual outcomes and might be applicable to the primary (protection against initial cancer development), secondary (protection against potential metastatic disease development), and tertiary (towards cascading complications) care. However, a detailed data analysis is essential to adapt treatment algorithms to individuals’ and patients’ needs. Consequently, advanced concepts of patient stratification, predictive diagnostics, targeted prevention, and treatments tailored to the individualized patient profile are instrumental for the cost-effective application of natural anti-cancer substances to improve overall breast cancer management benefiting affected individuals and the society at large.
      PubDate: 2022-04-14
  • Glycomic biomarkers are instrumental for suboptimal health status
           management in the context of predictive, preventive, and personalized

    • Abstract: Objectives Suboptimal health status (SHS), a reversible borderline condition between optimal health status and disease, has been recognized as a main risk factor for non-communicable diseases (NCDs). From the standpoint of predictive, preventive, and personalized medicine (PPPM/3PM), the early detection of SHS provides a window of opportunity for targeted prevention and personalized treatment of NCDs. Considering that immunoglobulin G (IgG) N-glycosylation levels are associated with NCDs, it can be speculated that IgG N-glycomic alteration might occur at the SHS stage. Methods A case–control study was performed and it consisted of 124 SHS individuals and 124 age-, gender-, and body mass index–matched healthy controls. The IgG N-glycan profiles of 248 plasma samples were analyzed by ultra-performance liquid chromatography instrument. Results After adjustment for potential confounders (i.e., age, levels of education, physical activity, family income, depression score, fasting plasma glucose, and low-density lipoprotein cholesterol), SHS was significantly associated with 16 IgG N-glycan traits at 5% false discovery rate, reflecting decreased galactosylation and fucosylation with bisecting GlcNAc, as well as increased agalactosylation and fucosylation without bisecting GlcNAc. Canonical correlation analysis showed that glycan peak (GP) 20, GP9, and GP12 tended to be significantly associated with the 5 domains (fatigue, the cardiovascular system, the digestive system, the immune system, and mental status) of SHS. The logistic regression model including IgG N-glycans was of moderate performance in tenfold cross-validation, achieving an average area under the receiver operating characteristic curves of 0.703 (95% confidence interval: 0.637–0.768). Conclusions The present findings indicated that SHS-related alteration of IgG N-glycans could be identified at the early onset of SHS, suggesting that IgG N-glycan profiles might be potential biomarker of SHS. The altered SHS-related IgG N-glycans are instrumental for SHS management, which could provide a window opportunity for PPPM in advanced treatment of NCDs and shed light on future studies investigating the pathogenesis of progression from SHS to NCDs.
      PubDate: 2022-04-11
  • Prostate cancer treatment costs increase more rapidly than for any other
           cancer—how to reverse the trend'

    • Abstract: Abstract According to GLOBOCAN, about 1.41 million new prostate cancer (PCa) cases were registered in the year 2020 globally. The corresponding socio-economic burden is enormous. Anti-cancer mRNA-based therapy is a promising approach, the principle of which is currently applied for anti-COVID-19 vaccination, undergoing a detailed investigation in populations considering its short- and long-term effectiveness and potential side effects. Pragmatically considered, it will take years or even decades to make mRNA therapy working for any type of cancers, and if possible, for individual malignancy sub-types which are many specifically for the PCa. Actually, the costs of treating PCa are increasing more rapidly than those of any other cancer. The trend has to be reversed now, not in a couple of years. In general, two main components are making currently applied reactive (management of clinically manifested disease) PCa treatment particularly expensive. On one hand, it is rapidly increasing incidence of the disease and metastatic PCa as its subtype. To this end, rapidly increasing PCa incidence rates in young and middle-aged male sub-populations should be taken into account as a long-term contributor to the metastatic disease potentially developed later on in life. On the other hand, patient stratification to differentiate between non-metastatic PCa (no need for an extensive and costly treatment) and particularly aggressive cancer subtypes requiring personalised treatment algorithms is challenging. Considering current statistics, it becomes obvious that reactive medicine got at its limit in PCa management. Multi-professional expertise is unavoidable to create and implement anti-PCa programmes in the population. In our strategic paper, we exemplify challenging PCa management by providing detailed expert recommendations for primary (health risk assessment), secondary (prediction and prevention of metastatic disease in PCa) and tertiary (making palliative care to the management of chronic disease) care in the framework of predictive, preventive and personalised medicine.
      PubDate: 2022-03-01
      DOI: 10.1007/s13167-022-00276-3
  • Sleep duration and atrial fibrillation risk in the context of predictive,
           preventive, and personalized medicine: the Suita Study and meta-analysis
           of prospective cohort studies

    • Abstract: Background Short and long sleep durations are common behaviors that could predict several cardiovascular diseases. However, the association between sleep duration and atrial fibrillation (AF) risk is not well-established. AF is preventable, and risk prevention approaches could reduce its occurrence. Investigating whether sleep duration could predict AF incidence for possible preventive interventions and determining the impact of various lifestyle and clinical characteristics on this association to personalize such interventions are essential. Herein, we investigated the association between sleep duration and AF risk using a prospective cohort study and a meta-analysis of epidemiological evidence. Methods Data of 6898 people, aged 30–84 years, from the Suita Study, were analyzed. AF was diagnosed during the follow-up by ECG, medical records, checkups, and death certificates, while a baseline questionnaire was used to assess sleep duration. The Cox regression was used to compute the hazard ratios (HRs) and 95% confidence intervals (CIs) of AF risk for daily sleep ≤ 6 (short sleep), ≥ 8 (long sleep), and irregular sleep, including night-shift work compared with 7 h (moderate sleep). Then, we combined our results with those from other eligible prospective cohort studies in two meta-analyses for the short and long sleep. Results In the Suita Study, within a median follow-up period of 14.5 years, short and irregular sleep, but not long sleep, were associated with the increased risk of AF in the age- and sex-adjusted models: HRs (95% CIs) = 1.36 (1.03, 1.80) and 1.62 (1.16, 2.26) and the multivariable-adjusted models: HRs (95% CIs) = 1.34 (1.01, 1.77) and 1.63 (1.16, 2.30), respectively. The significant associations between short and irregular sleep and AF risk remained consistent across different ages, sex, smoking, and drinking groups. However, they were attenuated among overweight and hypertensive participants. In the meta-analyses, short and long sleep durations were associated with AF risk: pooled HRs (95% CIs) = 1.21 (1.02, 1.42) and 1.18 (1.03, 1.35). No signs of significant heterogeneity across studies or publication bias were detected. Conclusion Short, long, and irregular sleep could be associated with increased AF risk. In the context of predictive, preventive, and personalized medicine, sleep duration should be considered in future AF risk scores to stratify the general population for potential personalized lifestyle modification interventions. Sleep management services should be considered for AF risk prevention, and these services should be individualized according to clinical characteristics and lifestyle factors. Graphical abstract
      PubDate: 2022-02-26
      DOI: 10.1007/s13167-022-00275-4
  • Evaluation of thermal sensitivity is of potential clinical utility for the
           predictive, preventive, and personalized approach advancing metabolic
           syndrome management

    • Abstract: Abstract A possible association between metabolic disorders and ambient temperature has been suggested, and cold exposure as a way of increasing energy expenditure has gained considerable interest for preventative/therapeutic measures toward metabolic disorders. Although thermal sensitivity, which has recently been studied in regard to its utility as a risk assessment/patient stratification for various diseases, might influence physiological responses to ambient temperature on an individual basis, more studies are needed. We aimed to investigate the association between self-identified thermal intolerance/sensation and metabolic syndrome (MetS) to verify the working hypothesis that individuals with altered thermal sensitivity may have a predisposition to MetS. We fitted generalized additive models for thermal intolerance/sensation using body mass index (BMI) and waist–hip ratio in women, and identified those with higher/lower thermal intolerance/sensation than those predicted by the models. Higher heat intolerance, higher heat sensation, and lower cold intolerance were associated with a higher prevalence of MetS. The risk of having MetS was increased in those who had two or three associated conditions compared with those with none of these conditions. In an analysis for MetS components, significant associations of thermal sensitivity were present with high glucose, triglyceride, and blood pressure levels. Overall, higher heat intolerance/sensation and lower cold intolerance were associated with increased prevalence of MetS even at a similar level of obesity. Our study indicates that evaluation of thermal sensitivity may help identify individuals at high risk for MetS, and lead to more advanced patient stratification and personalized treatment strategies for MetS, including cold-induced thermogenesis.
      PubDate: 2022-02-18
      DOI: 10.1007/s13167-022-00273-6
  • Muti-omics integration analysis revealed molecular network alterations in
           human nonfunctional pituitary neuroendocrine tumors in the framework of 3P

    • Abstract: Abstract Nonfuctional pituitary neuroendocrine tumor (NF-PitNET) is highly heterogeneous and generally considered a common intracranial tumor. A series of molecules are involved in NF-PitNET pathogenesis that alter in multiple levels of genome, transcriptome, proteome, and metabolome, and those molecules mutually interact to form dynamically associated molecular-network systems. This article reviewed signaling pathway alterations in NF-PitNET based on the analyses of the genome, transcriptome, proteome, and metabolome, and emphasized signaling pathway network alterations based on the integrative omics, including calcium signaling pathway, cGMP-PKG signaling pathway, mTOR signaling pathway, PI3K/AKT signaling pathway, MAPK (mitogen-activated protein kinase) signaling pathway, oxidative stress response, mitochondrial dysfunction, and cell cycle dysregulation, and those signaling pathway networks are important for NF-PitNET formation and progression. Especially, this review article emphasized the altered signaling pathways and their key molecules related to NF-PitNET invasiveness and aggressiveness that are challenging clinical problems. Furthermore, the currently used medication and potential therapeutic agents that target these important signaling pathway networks are also summarized. These signaling pathway network changes offer important resources for insights into molecular mechanisms, discovery of effective biomarkers, and therapeutic targets for patient stratification, predictive diagnosis, prognostic assessment, and targeted therapy of NF-PitNET.
      PubDate: 2022-02-17
      DOI: 10.1007/s13167-022-00274-5
  • Predicting acupuncture efficacy for functional dyspepsia based on routine
           clinical features: a machine learning study in the framework of
           predictive, preventive, and personalized medicine

    • Abstract: Background Acupuncture is safe and effective for functional dyspepsia (FD), while its efficacy varies among individuals. Predicting the response of different FD patients to acupuncture treatment in advance and therefore administering the tailored treatment to the individual is consistent with the principle of predictive, preventive, and personalized medicine (PPPM/3PM). In the current study, the individual efficacy prediction models were developed based on the support vector machine (SVM) algorithm and routine clinical features, aiming to predict the efficacy of acupuncture in treating FD and identify the FD patients who were appropriate to acupuncture treatment. Methods A total of 745 FD patients were collected from two clinical trials. All the patients received a 4-week acupuncture treatment. Based on the demographic and baseline clinical features of 80% of patients in trial 1, the SVM models were established to predict the acupuncture response and improvements of symptoms and quality of life (QoL) at the end of treatment. Then, the left 20% of patients in trial 1 and 193 patients in trial 2 were respectively applied to evaluate the internal and external generalizations of these models. Results These models could predict the efficacy of acupuncture successfully. In the internal test set, models achieved an accuracy of 0.773 in predicting acupuncture response and an R2 of 0.446 and 0.413 in the prediction of QoL and symptoms improvements, respectively. Additionally, these models had well generalization in the independent validation set and could also predict, to a certain extent, the long-term efficacy of acupuncture at the 12-week follow-up. The gender, subtype of disease, and education level were finally identified as the critical predicting features. Conclusion Based on the SVM algorithm and routine clinical features, this study established the models to predict acupuncture efficacy for FD patients. The prediction models developed accordingly are promising to assist doctors in judging patients’ responses to acupuncture in advance, so that they could tailor and adjust acupuncture treatment plans for different patients in a prospective rather than the reactive manner, which could greatly improve the clinical efficacy of acupuncture treatment for FD and save medical expenditures.
      PubDate: 2022-02-02
      DOI: 10.1007/s13167-022-00271-8
  • Metabolic phenotyping of tear fluid as a prognostic tool for personalised
           medicine exemplified by T2DM patients

    • Abstract: Background/aims Concerning healthcare approaches, a paradigm change from reactive medicine to predictive approaches, targeted prevention, and personalisation of medical services is highly desirable. This raises demand for biomarker signatures that support the prediction and diagnosis of diseases, as well as monitoring strategies regarding therapeutic efficacy and supporting individualised treatments. New methodological developments should preferably rely on non-invasively sampled biofluids like sweat and tears in order to provide optimal compliance, reduce costs, and ensure availability of the biomaterial. Here, we have thus investigated the metabolic composition of human tears in comparison to finger sweat in order to find biofluid-specific marker molecules derived from distinct secretory glands. The comprehensive investigation of numerous biofluids may lead to the identification of novel biomarker signatures. Moreover, tear fluid analysis may not only provide insight into eye pathologies but may also be relevant for the prediction and monitoring of disease progression and/ or treatment of systemic disorders such as type 2 diabetes mellitus. Methods Sweat and tear fluid were sampled from 20 healthy volunteers using filter paper and commercially available Schirmer strips, respectively. Finger sweat analysis has already been successfully established in our laboratory. In this study, we set up and evaluated methods for tear fluid extraction and analysis using high-resolution mass spectrometry hyphenated with liquid chromatography, using optimised gradients each for metabolites and eicosanoids. Sweat and tears were systematically compared using statistical analysis. As second approach, we performed a clinical pilot study with 8 diabetic patients and compared them to 19 healthy subjects. Results Tear fluid was found to be a rich source for metabolic phenotyping. Remarkably, several molecules previously identified by us in sweat were found significantly enriched in tear fluid, including creatine or taurine. Furthermore, other metabolites such as kahweol and various eicosanoids were exclusively detectable in tears, demonstrating the orthogonal power for biofluid analysis in order to gain information on individual health states. The clinical pilot study revealed that many endogenous metabolites that have previously been linked to type 2 diabetes such as carnitine, tyrosine, uric acid, and valine were indeed found significantly up-regulated in tears of diabetic patients. Nicotinic acid and taurine were elevated in the diabetic cohort as well and may represent new biomarkers for diabetes specifically identified in tear fluid. Additionally, systemic medications, like metformin, bisoprolol, and gabapentin, were readily detectable in tears of patients. Conclusions The high number of identified marker molecules found in tear fluid apparently supports disease development prediction, developing preventive approaches as well as tailoring individual patients’ treatments and monitoring treatment efficacy. Tear fluid analysis may also support pharmacokinetic studies and patient compliance control.
      PubDate: 2022-01-29
      DOI: 10.1007/s13167-022-00272-7
  • Functional metabolome profiling may improve individual outcomes in
           colorectal cancer management implementing concepts of predictive,
           preventive, and personalized medical approach

    • Abstract: Objectives Colorectal cancer (CRC) is one of the most common solid tumors worldwide, but its diagnosis and treatment are limited. The objectives of our study were to compare the metabolic differences between CRC patients and healthy controls (HC), and to identify potential biomarkers in the serum that can be used for early diagnosis and as effective therapeutic targets. The aim was to provide a new direction for CRC predictive, preventive, and personalized medicine (PPPM). Methods In this study, CRC patients (n = 30) and HC (n = 30) were recruited. Serum metabolites were assayed using an ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) technology. Subsequently, CRC cell lines (HCT116 and HCT8) were treated with metabolites to verify their function. Key targets were identified by molecular docking, thermal shift assay, and protein overexpression/inhibition experiments. The inhibitory effect of celastrol on tumor growth was also assessed, which included IC50 analysis, nude mice xenografting, molecular docking, protein overexpression/inhibition experiments, and network pharmacology technology. Results In the CRC group, 15 serum metabolites were significantly different in comparison with the HC group. The level of glycodeoxycholic acid (GDCA) was positively correlated with CRC and showed high sensitivity and specificity for the clinical diagnostic reference (AUC = 0.825). In vitro findings showed that GDCA promoted the proliferation and migration of CRC cell lines (HCT116 and HCT8), and Poly(ADP-ribose) polymerase-1 (PARP-1) was identified as one of the key targets of GDCA. The IC50 of celastrol in HCT116 cells was 121.1 nM, and the anticancer effect of celastrol was supported by in vivo experiments. Based on the potential of GDCA in PPPM, PARP-1 was found to be significantly correlated with the anticancer functions of celastrol. Conclusion These findings suggest that GDCA is an abnormally produced metabolite of CRC, which may provide an innovative molecular biomarker for the predictive identification and targeted prevention of CRC. In addition, PARP-1 was found to be an important target of GDCA that promotes CRC; therefore, celastrol may be a potential targeted therapy for CRC via its effects on PARP-1. Taken together, the pathophysiology and progress of tumor molecules mediated by changes in metabolite content provide a new perspective for predictive, preventive, and personalized medical of clinical cancer patients based on the target of metabolites in vivo. Clinical trials registration number: ChiCTR2000039410.
      PubDate: 2022-01-27
      DOI: 10.1007/s13167-021-00269-8
  • Development and validation of a transcriptomic signature-based model as
           the predictive, preventive, and personalized medical strategy for preterm
           birth within 7 days in threatened preterm labor women

    • Abstract: Abstract Preterm birth (PTB) is the leading cause of neonatal death. The essential strategy to prevent PTB is the accurate identification of threatened preterm labor (TPTL) women who will have PTB in a short time (< 7 days). Here, we aim to propose a clinical model to contribute to the effective prediction, precise prevention, and personalized medical treatment for PTB < 7 days in TPTL women through bioinformatics analysis and prospective cohort studies. In this study, the 1090 key genes involved in PTB < 7 days in the peripheral blood of TPTL women were ascertained using WGCNA. Based on this, the biological basis of immune-inflammatory activation (e.g., IFNγ and TNFα signaling) as well as immune cell disorders (e.g., monocytes and Th17 cells) in PTB < 7 days were revealed. Then, four core genes (JOSD1, IDNK, ZMYM3, and IL1B) that best represent their transcriptomic characteristics were screened by SVM and LASSO algorithm. Therefore, a prediction model with an AUC of 0.907 was constructed, which was validated in a larger population (AUC = 0.783). Moreover, the predictive value (AUC = 0.957) and clinical feasibility of this model were verified through the clinical prospective cohort we established. In conclusion, in the context of Predictive, Preventive, and Personalized Medicine (3PM), we have developed and validated a model to predict PTB < 7 days in TPTL women. This is promising to greatly improve the accuracy of clinical prediction, which would facilitate the personalized management of TPTL women to precisely prevent PTB < 7 days and improve maternal–fetal outcomes.
      PubDate: 2022-01-18
      DOI: 10.1007/s13167-021-00268-9
  • Predictive factors, preventive implications, and personalized surgical
           strategies for bone metastasis from lung cancer: population-based approach
           with a comprehensive cancer center-based study

    • Abstract: Background Bone metastasis (BM) and skeletal-related events (SREs) happen to advanced lung cancer (LC) patients without warning. LC-BM patients are often passive to BM diagnosis and surgical treatment. It is necessary to guide the diagnosis and treatment paradigm for LC-BM patients from reactive medicine toward predictive, preventive, and personalized medicine (PPPM) step by step. Methods Two independent study cohorts including LC-BM patients were analyzed, including the Surveillance, Epidemiology, and End Results (SEER) cohort (n = 203942) and the prospective Fudan University Shanghai Cancer Center (FUSCC) cohort (n = 59). The epidemiological trends of BM in LC patients were depicted. Risk factors for BM were identified using a multivariable logistic regression model. An individualized nomogram was developed for BM risk stratification. Personalized surgical strategies and perioperative care were described for FUSCC cohort. Results The BM incidence rate in LC patients grew (from 17.53% in 2010 to 19.05% in 2016). Liver metastasis was a significant risk factor for BM (OR = 4.53, 95% CI = 4.38–4.69) and poor prognosis (HR = 1.29, 95% CI = 1.25–1.32). The individualized nomogram exhibited good predictive performance for BM risk stratification (AUC = 0.784, 95%CI = 0.781–0.786). Younger patients, males, patients with high invasive LC, and patients with other distant site metastases should be prioritized for BM prevention. Spine is the most common site of BM, causing back pain (91.5%), pathological vertebral fracture (27.1%), and difficult walking (25.4%). Spinal surgery with personalized spinal reconstruction significantly relieved pain and improved daily activities. Perioperative inflammation, immune, and nutrition abnormities warrant personalized managements. Radiotherapy needs to be recommended for specific postoperative individuals. Conclusions The presence of liver metastasis is a strong predictor of LC-BM. It is recommended to take proactive measures to prevent BM and its SREs, particularly in young patients, males, high invasive LC, and LC with liver metastasis. BM surgery and perioperative management are personalized and required. In addition, adjuvant radiation following separation surgery must also be included in PPPM-guided management. Graphical abstract
      PubDate: 2022-01-10
      DOI: 10.1007/s13167-022-00270-9
  • Modeling SARS-CoV-2 spike/ACE2 protein–protein interactions for
           predicting the binding affinity of new spike variants for ACE2, and novel
           ACE2 structurally related human protein targets, for COVID-19 handling in
           the 3PM context

    • Abstract: Aims The rapid spread of new SARS-CoV-2 variants has highlighted the crucial role played in the infection by mutations occurring at the SARS-CoV-2 spike receptor binding domain (RBD) in the interactions with the human ACE2 receptor. In this context, it urgently needs to develop new rapid tools for quickly predicting the affinity of ACE2 for the SARS-CoV-2 spike RBD protein variants to be used with the ongoing SARS-CoV-2 genomic sequencing activities in the clinics, aiming to gain clues about the transmissibility and virulence of new variants, to prevent new outbreaks and to quickly estimate the severity of the disease in the context of the 3PM. Methods In our study, we used a computational pipeline for calculating the interaction energies at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface for a selected group of characterized infectious variants of concern/interest (VoC/VoI). By using our pipeline, we built 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for the VoC B.1.1.7-United Kingdom (carrying the mutations of concern/interest N501Y, S494P, E484K at the RBD), P.1-Japan/Brazil (RBD mutations: K417T, E484K, N501Y), B.1.351-South Africa (RBD mutations: K417N, E484K, N501Y), B.1.427/B.1.429-California (RBD mutations: L452R), the B.1.141 (RBD mutations: N439K), and the recent B.1.617.1-India (RBD mutations: L452R; E484Q) and the B.1.620 (RBD mutations: S477N; E484K). Then, we used the obtained 3D comparative models of the SARS-CoV-2 spike RBD/ACE2 protein complexes for predicting the interaction energies at the protein–protein interface. Results Along SARS-CoV-2 mutation database screening and mutation localization analysis, it was ascertained that the most dangerous mutations at VoC/VoI spike proteins are located mainly at three regions of the SARS-CoV-2 spike “boat-shaped” receptor binding motif, on the RBD domain. Notably, the P.1 Japan/Brazil variant present three mutations, K417T, E484K, N501Y, located along the entire receptor binding motif, which apparently determines the highest interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface, among those calculated. Conversely, it was also observed that the replacement of a single acidic/hydrophilic residue with a basic residue (E484K or N439K) at the “stern” or “bow” regions, of the boat-shaped receptor binding motif on the RBD, appears to determine an interaction energy with ACE2 receptor higher than that observed with single mutations occurring at the “hull” region or with other multiple mutants. In addition, our pipeline allowed searching for ACE2 structurally related proteins, i.e., THOP1 and NLN, which deserve to be investigated for their possible involvement in interactions with the SARS-CoV-2 spike protein, in those tissues showing a low expression of ACE2, or as a novel receptor for future spike variants. A freely available web-tool for the in silico calculation of the interaction energy at the SARS-CoV-2 spike RBD/ACE2 protein–protein interface, starting from the sequences of the investigated spike and/or ACE2 variants, was made available for the scientific community at: Conclusion In the context of the PPPM/3PM, the employment of the described pipeline through the provided webservice, together with the ongoing SARS-CoV-2 genomic sequencing, would help to predict the transmissibility of new variants sequenced from future patients, depending on SARS-CoV-2 genomic sequencing activities and on the specific amino acid replacement and/or on its location on the SARS-CoV-2 spike RBD, to put in play all the possible counteractions for preventing the most deleterious scenarios of new outbreaks, taking into consideration that a greater transmissibility has not to be necessarily related to a more severe manifestation of the disease.
      PubDate: 2022-01-06
      DOI: 10.1007/s13167-021-00267-w
  • Early gestational profiling of oxidative stress and angiogenic growth
           mediators as predictive, preventive and personalised (3P) medical approach
           to identify suboptimal health pregnant mothers likely to develop

    • Abstract: Background Pregnant women, particularly in developing countries are facing a huge burden of preeclampsia (PE) leading to high morbidity and mortality rates. This is due to delayed diagnosis and unrecognised early targeted preventive measures. Adapting innovative solutions via shifting from delayed to early diagnosis of PE in the context of predictive diagnosis, targeted prevention and personalisation of medical care (PPPM/3 PM) is essential. The subjective assessment of suboptimal health status (SHS) and objective biomarkers of oxidative stress (OS) and angiogenic growth mediators (AGMs) could be used as new PPPM approach for PE; however, these factors have only been studied in isolation with no data on their combine assessment. This study profiled early gestational biomarkers of OS and AGMs as 3 PM approach to identify SHS pregnant mothers likely to develop PE specifically, early-onset PE (EO-PE) and late-onset PE (LO-PE). Methods A prospective cohort of 593 singleton normotensive pregnant (NTN-P) women were recruited at 10–20th (visit 1) and followed from 21 weeks gestation until the time of PE diagnosis and delivery. At visit 1, SHS was assessed using SHS questionnaire-25 (SHSQ-25) and women were classified as SHS and optimal health status (OHS). Biomarkers of OS (8-hydroxy-2-deoxyguanosine [8-OHdG], 8-epi-prostaglansinF2alpha [8-epi-PGF2α] and total antioxidant capacity [TAC]) and AGMs (vascular endothelial growth factor [VEGF-A], soluble Fms-like tyrosine kinase-1 [sFlt-1], placental growth factor [PlGF] and soluble endoglin [sEng]) were measured at visit 1 and time of PE diagnosis. Results Of the 593 mothers, 498 (248 SHS and 250 OHS) returned for delivery and were included in the final analysis. Fifty-six, 97 and 95 of the 248 SHS mothers developed EO-PE, LO-PE and NTN-P respectively, versus 14 EO-PE, 30 LO-PE and 206 NTN-P among the 250 OHS mothers. At the 10–20th week gestation, unbalanced levels of OS and AGMs were observed among SHS women who developed EO-PE than LO-PE compared to NTN-P women (p < 0.0001). The combined ratios of OS and AGMs, mainly the levels of 8-OHdG/PIGF ratio at 10–20th week gestation yielded the best area under the curve (AUC) and highest relative risk (RR) for predicting SHS-pregnant women who developed EO-PE (AUC = 0.93; RR = 6.5; p < 0.0001) and LO-PE (AUC = 0.88, RR = 4.4; p < 0.0001), as well as for OHS-pregnant women who developed EO-PE (AUC = 0.89, RR = 5.6; p < 0.0001) and LO-PE (AUC = 0.85; RR = 5.1; p < 0.0001). Conclusion Unlike OHS pregnant women, SHS pregnant women have high incidence of PE coupled with unbalanced levels of OS and AGMs at 10–20 weeks gestation. Combining early gestational profiling of OS and AGMs created an avenue for early differentiation of PE subtypes in the context of 3 PM care for mothers at high risk of PE.
      PubDate: 2021-12-01
      DOI: 10.1007/s13167-021-00258-x
  • Association of systemic inflammation indices with visual field loss
           progression in patients with primary angle-closure glaucoma: potential
           biomarkers for 3P medical approaches

    • Abstract: Relevance Accumulating evidence suggests a dysfunction of the para-inflammation in the retinal ganglion cell layer and the optic nerve head in patients with glaucoma. Currently, circulating blood platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR) are regarded as novel indicators of systemic inflammation. Biomarkers allow early identification of patients with visual field (VF) loss progression and timely implementation of replacement therapies. Objective This study aimed to investigate whether higher inflammatory indices (PLR, NLR, and LMR) were associated with VF loss progression in patients with primary angle-closure glaucoma (PACG) for the predictive diagnostics, targeted prevention, and personalization of medical services. Methods This prospective cohort study followed up 277 patients with PACG for at least 24 months, with clinical examination and VF testing every 6 months. Inflammatory cell quantification, including platelets, neutrophils, lymphocytes, and monocytes, was measured using the Sysmex XN-A1 automated inflammatory cells quantification system. Three systemic inflammatory indices, PLR, NLR, and LMR, were determined on the basis of baseline neutrophil, lymphocyte, monocyte, and platelet counts in patients with PACG. The risk factors for PACG were analyzed using logistic regression, Cox proportional hazards regression, and the Kaplan–Meier curve. Results Our results revealed that 111 (40.07%) patients showed VF loss progression. The PLR was significantly higher (P = 0.046) in the progression group than in the non-progression group. A higher PLR (OR 1.05, 95% CI 1.01–1.08, P = 0.004) was a risk factor for PACG progression. In multivariate analyses, PLR independently predicted VF loss progression (HR 1.01, 95% CI 1.00–1.01, P = 0.04). Kaplan–Meier curve analysis showed that higher PLR indicated significantly higher rates of VF loss progression (66.91% vs. 52.90%, P = 0.03). Comparable results were observed in the male and female subgroups. Conclusion Our findings revealed the significant association between a high PLR and a greater risk of VF loss progression in patients with PACG. PLR may be highly recommended as a novel predictive/diagnostic tool for the assessment of VF loss progression from the perspectives of predictive, preventive, and personalized medicine in vulnerable populations and for individual screening.
      PubDate: 2021-12-01
      DOI: 10.1007/s13167-021-00260-3
  • Mass spectrometry analysis of human tear fluid biomarkers specific for
           ocular and systemic diseases in the context of 3P medicine

    • Abstract: Abstract Over the last two decades, a large number of non-communicable/chronic disorders reached an epidemic level on a global scale such as diabetes mellitus type 2, cardio-vascular disease, several types of malignancies, neurological and eye pathologies—all exerted system’s enormous socio-economic burden to primary, secondary, and tertiary healthcare. The paradigm change from reactive to predictive, preventive, and personalized medicine (3PM/PPPM) has been declared as an essential transformation of the overall healthcare approach to benefit the patient and society at large. To this end, specific biomarker panels are instrumental for a cost-effective predictive approach of individualized prevention and treatments tailored to the person. The source of biomarkers is crucial for specificity and reliability of diagnostic tests and treatment targets. Furthermore, any diagnostic approach preferentially should be noninvasive to increase availability of the biomaterial, and to decrease risks of potential complications as well as concomitant costs. These requirements are clearly fulfilled by tear fluid, which represents a precious source of biomarker panels. The well-justified principle of a “sick eye in a sick body” makes comprehensive tear fluid biomarker profiling highly relevant not only for diagnostics of eye pathologies but also for prediction, prognosis, and treatment monitoring of systemic diseases. One prominent example is the Sicca syndrome linked to a cascade of severe complications that include dry eye, neurologic, and oncologic diseases. In this review, protein profiles in tear fluid are highlighted and corresponding biomarkers are exemplified for several relevant pathologies, including dry eye disease, diabetic retinopathy, cancers, and neurological disorders. Corresponding analytical approaches such as sample pre-processing, differential proteomics, electrophoretic techniques, high-performance liquid chromatography (HPLC), enzyme-linked immuno-sorbent assay (ELISA), microarrays, and mass spectrometry (MS) methodology are detailed. Consequently, we proposed the overall strategies based on the tear fluid biomarkers application for 3P medicine practice. In the context of 3P medicine, tear fluid analytical pathways are considered to predict disease development, to target preventive measures, and to create treatment algorithms tailored to individual patient profiles.
      PubDate: 2021-12-01
      DOI: 10.1007/s13167-021-00265-y
  • Homocysteine metabolism as the target for predictive medical approach,
           disease prevention, prognosis, and treatments tailored to the person

    • Abstract: Abstract Homocysteine (Hcy) metabolism is crucial for regulating methionine availability, protein homeostasis, and DNA-methylation presenting, therefore, key pathways in post-genomic and epigenetic regulation mechanisms. Consequently, impaired Hcy metabolism leading to elevated concentrations of Hcy in the blood plasma (hyperhomocysteinemia) is linked to the overproduction of free radicals, induced oxidative stress, mitochondrial impairments, systemic inflammation and increased risks of eye disorders, coronary artery diseases, atherosclerosis, myocardial infarction, ischemic stroke, thrombotic events, cancer development and progression, osteoporosis, neurodegenerative disorders, pregnancy complications, delayed healing processes, and poor COVID-19 outcomes, among others. This review focuses on the homocysteine metabolism impairments relevant for various pathological conditions. Innovative strategies in the framework of 3P medicine consider Hcy metabolic pathways as the specific target for in vitro diagnostics, predictive medical approaches, cost-effective preventive measures, and optimized treatments tailored to the individualized patient profiles in primary, secondary, and tertiary care.
      PubDate: 2021-12-01
      DOI: 10.1007/s13167-021-00263-0
  • Integrated genomic analysis of proteasome alterations across 11,057
           patients with 33 cancer types: clinically relevant outcomes in framework
           of 3P medicine

    • Abstract: Relevance Proteasome, a cylindrical complex containing 19S regulatory particle lid, 19S regulatory particle base, and 20S core particle, acted as a major mechanism to regulate the levels of intracellular proteins and degrade misfolded proteins, which involved in many cellular processes, and played important roles in cancer biological processes. Elucidation of proteasome alterations across multiple cancer types will directly contribute to cancer medical services in the context of predictive, preventive, and personalized medicine (PPPM / 3P medicine). Purpose This study aimed to investigate proteasome gene alterations across 33 cancer types for discovery of effective biomarkers and therapeutic targets in the framework of PPPM practice in cancers. Methods Proteasome gene data, including gene expression RNAseq, somatic mutation, tumor mutation burden (TMB), copy number variant (CNV), microsatellite instability (MSI) score, clinical characteristics, immune phenotype, 22 immune cells, cancer stemness index, drug sensitivity, and related pathways, were systematically analyzed with publically available database and bioinformatics across 11,057 patients with 33 cancer types. Results Differentially expressed proteasome genes were extensively found between tumor and control tissues. PSMB4 occurred the top mutation event among proteasome genes, and those proteasome genes were significantly associated with TMB and MSI score. Most of proteasome genes were positively related to CNV among single deletion, control copy number, and single gain. Kaplan–Meier curves and COX regression survival analysis showed proteasome genes were significantly associated with patient survival rate across 33 cancer types. Furthermore, the expressions of proteasome genes were significantly different among different clinical stages and immune subtypes. The expressions of proteasome genes were correlated with immune-related scores (ImmuneScore, StromalScore, and ESTIMATEScore), 22 immune cells, and cancer stemness. The sensitivities of multiple drugs were closely related to proteasome gene expressions. The identified proteasome and proteasome-interacted proteins were significantly enriched in various cancer-related pathways. Conclusions This study provided the first landscape of proteasome alterations across 11,057 patients with 33 cancer types and revealed that proteasome played a significant and wide functional role in cancer biological processes. These findings are the precious scientific data to reveal the common and specific alterations of proteasome genes among 33 cancer types, which benefits the research and practice of PPPM in cancers.
      PubDate: 2021-09-30
      DOI: 10.1007/s13167-021-00256-z
  • All around suboptimal health — a joint position paper of the Suboptimal
           Health Study Consortium and European Association for Predictive,
           Preventive and Personalised Medicine

    • Abstract: Abstract First two decades of the twenty-first century are characterised by epidemics of non-communicable diseases such as many hundreds of millions of patients diagnosed with cardiovascular diseases and the type 2 diabetes mellitus, breast, lung, liver and prostate malignancies, neurological, sleep, mood and eye disorders, amongst others. Consequent socio-economic burden is tremendous. Unprecedented decrease in age of maladaptive individuals has been reported. The absolute majority of expanding non-communicable disorders carry a chronic character, over a couple of years progressing from reversible suboptimal health conditions to irreversible severe pathologies and cascading collateral complications. The time-frame between onset of SHS and clinical manifestation of associated disorders is the operational area for an application of reliable risk assessment tools and predictive diagnostics followed by the cost-effective targeted prevention and treatments tailored to the person. This article demonstrates advanced strategies in bio/medical sciences and healthcare focused on suboptimal health conditions in the frame-work of Predictive, Preventive and Personalised Medicine (3PM/PPPM). Potential benefits in healthcare systems and for society at large include but are not restricted to an improved life-quality of major populations and socio-economical groups, advanced professionalism of healthcare-givers and sustainable healthcare economy. Amongst others, following medical areas are proposed to strongly benefit from PPPM strategies applied to the identification and treatment of suboptimal health conditions: Stress overload associated pathologies Male and female health Planned pregnancies Periodontal health Eye disorders Inflammatory disorders, wound healing and pain management with associated complications Metabolic disorders and suboptimal body weight Cardiovascular pathologies Cancers Stroke, particularly of unknown aetiology and in young individuals Sleep medicine Sports medicine Improved individual outcomes under pandemic conditions such as COVID-19.
      PubDate: 2021-09-13
      DOI: 10.1007/s13167-021-00253-2
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