Patohistoloogilise diagnostika digitaalsed rakendused ja tulevikusuunad

Haiguse tõttu muutunud koe uuringu käsitluses leiab lisaks traditsioonilistele meetoditele üha enam rakendust digitaalne uurimine. Ligi kakskümmend aastat vanas valdkonnas tõi olulisima arengu kaasa tervikslaidi digiteerimise tehnoloogia, mille tulemusena saadud digitaalsed koelõigud on sobivaks andmestikuks masin- ja süvaõppel põhinevatele arendustele. Teema aktuaalsusele viitab viimastel aastatel hüppeliselt suurenenud virtuaalmikroskoopia ja digianalüüsi (nimetatakse kokku ka digipatoloogiaks) kasutamine diagnostilise meetodina, seda nii infotehnoloogilise arenduse, teaduslike rakenduste kui ka kliinilise kasutamise vallas. Digitaalne patohistoloogiline diagnostika leiab kliinilist rakendust rutiinsete ülesannete automatiseerimisel, näiteks kasvajamarkerite hindamisel. Tulevikuperspektiive nähakse uute prognostiliste markerite leidmises, koe virtuaalses värvimises, morfoloogilise ja molekulaarpatoloogilise info ühendamises ning kolmemõõtmelise kujutise loomises

Üldpädevuste kujundamine ja osaliste agentsus mitteformaalõppes

Artiklis anname ülevaate üldpädevuste käsitlemisest mitteformaalõppes. Eesmärk on välja selgitada, kuidas mitteformaalõppe poliitikadokumentides ja praktikas avaldub üldpädevuste arendamine ja osaliste agentsus. Selleks analüüsime üldpädevuste avaldumist kuue valdkondliku raja 23 poliitikadokumendis ja nende radade praktikute arusaamades. Mitteformaalõppe põhimõtete rakendajatega tehtud 12 fookusgrupiintervjuu  põhjal selgitasime välja, kuidas toetatakse ja arendatakse üldpädevusi ning konstrueeritakse osaliste  agentsust. Kriitilisel diskursuseanalüüsil selgus, et üldpädevusi poliitikadokumentides otseselt ei nimetata, ent sisuliselt need mitteformaalõppele seatud eesmärkides siiski väljenduvad. Ka praktikud kirjeldavad  üldpädevuste arendamist oma igapäevatöös, kuid ei nimeta neid riiklikust õppekavast tuttavate terminitega ega mõtesta üldpädevustena. Praktikute kirjeldustes konstrueeritakse mitteformaalõpet õppija agentsuse toetajana, mis annab õppe eesmärgi seadel ja hindamisel vastutuse õppijale. Praktikute enesekäsitluses on läbi põimunud osaleja, arendaja ja õppimise võimaldaja rollid.  Summar

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

Stroke genetics informs drug discovery and risk prediction across ancestries

: Previous genome-wide association studies (GWASs) of stroke&nbsp;-&nbsp;the second leading cause of death worldwide&nbsp;-&nbsp;were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P &lt; 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries