Synthesis of 3-heterocyclic phenyl N-alkyl carbamates and their activity as FAAH inhibitors

Fatty acid amide hydrolase (FAAH) is an intracellular serine hydrolase that catalyzes the hydrolysis of the endocannabinoid N-arachidonoylethanolamide (AEA) to arachidonic acid and ethanolamine. FAAH also hydrolyze another important endocannabinoid, 2-arachidonoylglycerol (2-AG), although the main enzyme responsible for hydrolysis of 2-AG is MGL. Inhibition of FAAH or MGL enzymatic activity potentially leads to beneficial effects in many physiological disorders such as pain, inflammation and anxiety, due to increased endocannabinoid induced activation of cannabinoid receptors CB1 and CB2. In the present study a total of 101 compounds were designed, synthesized, characterized and tested against FAAH and MGL enzyme activity. Altogether 47 compounds were found to inhibit FAAH with half-maximal inhibition concentrations (IC50) between 0.74 and 100 nM. All potent compounds belong to the structural family of carbamates. Other carbonyl-containing compounds were prepared for comparison and they were found not to inhibit either FAAH or MGL. The synthesized carbamate derivatives were found to be selective for FAAH as the inhibition of MGL enzyme by these compounds was negligible. From the library of phenyl N-alkyl carbamates the most potent FAAH inhibitors were meta-substituted N-cyclohexylcarbamates. 4,5-Dihydrooxazol-2-yl (221), oxazol-2-yl (242), 2-methyltetrazol-5-yl (273a), imidazol-4-yl (252) and 1,2,3-thiadiazol-4-yl (314) were found to be the best heterocycle substituents of phenolic N-alkyl carbamate. Methyl ester (276) was the best acyclic substituent. These compounds inhibited FAAH with IC50 values between 0.74-3.9 nM. Various synthesis methods were used to achieve the desired compounds. Microwave assisted novel or little known reactions applied in synthesis including condensation of acids and 2-aminophenol/2-amino-3-hydroxypyridine to prepare corresponding fused 2-oxazoles, oxazole formation via condensation of bromoketones and amides, and cleavage of benzyl and methyl ethers using ionic liquids. In conclusion, the results of this work provide useful structure-activity relationship (SAR) information of carbamate compounds as FAAH inhibitors which can be utilized in further developments in this area

Synthesis of 3-heterocycle phenyl N-alkyl carbamates and their activity as FAAH inhibitors

Fatty acid amide hydrolase (FAAH) is an intracellular serine hydrolase that catalyzes the hydrolysis of the endocannabinoid N-arachidonoylethanolamide (AEA) to arachidonic acid and ethanolamine. FAAH also hydrolyze another important endocannabinoid, 2-arachidonoylglycerol (2-AG), although the main enzyme responsible for hydrolysis of 2-AG is MGL. Inhibition of FAAH or MGL enzymatic activity potentially leads to beneficial effects in many physiological disorders such as pain, inflammation and anxiety, due to increased endocannabinoid induced activation of cannabinoid receptors CB1 and CB2. In the present study a total of 101 compounds were designed, synthesized, characterized and tested against FAAH and MGL enzyme activity. Altogether 47 compounds were found to inhibit FAAH with half-maximal inhibition concentrations (IC50) between 0.74 and 100 nM. All potent compounds belong to the structural family of carbamates. Other carbonyl-containing compounds were prepared for comparison and they were found not to inhibit either FAAH or MGL. The synthesized carbamate derivatives were found to be selective for FAAH as the inhibition of MGL enzyme by these compounds was negligible. From the library of phenyl N-alkyl carbamates the most potent FAAH inhibitors were meta-substituted N-cyclohexylcarbamates. 4,5-Dihydrooxazol-2-yl (221), oxazol-2-yl (242), 2-methyltetrazol-5-yl (273a), imidazol-4-yl (252) and 1,2,3-thiadiazol-4-yl (314) were found to be the best heterocycle substituents of phenolic N-alkyl carbamate. Methyl ester (276) was the best acyclic substituent. These compounds inhibited FAAH with IC50 values between 0.74-3.9 nM. Various synthesis methods were used to achieve the desired compounds. Microwave assisted novel or little known reactions applied in synthesis including condensation of acids and 2-aminophenol/2-amino-3-hydroxypyridine to prepare corresponding fused 2-oxazoles, oxazole formation via condensation of bromoketones and amides, and cleavage of benzyl and methyl ethers using ionic liquids. In conclusion, the results of this work provide useful structure-activity relationship (SAR) information of carbamate compounds as FAAH inhibitors which can be utilized in further developments in this area

Factors affecting passener rail demand

Tutkimuksen tavoitteena oli kartoittaa Suomen rautateiden henkilöliikenteen nykytilaa ja arvioida rautateiden henkilöliikenteen kysyntään vaikuttavia tekijöitä. Lisäksi tutkimuksessa selvitetään eri kotimaisten toimijoiden mahdollisuuksia vaikuttaa rautateiden henkilöliikenteen kysyntään. Tutkimuksessa on myös ulkomaisia esimerkkejä ja kokemuksia rautatieliikenteen kilpailukyvystä. Kaukoliikenne on tällä hetkellä muuttuvassa tilassa ja rautateiden henkilöliikenteen kilpailukyvyn tarkastelu on erittäin ajankohtaista. Rautatieliikenne on perinteinen ja yhteiskunnalle tärkeä liikkumismuoto. Suurimmat kehitykset kaukoliikenteessä ovat olleet rataverkon kehittäminen ja sähköistykset sekä junakaluston ja tarjonnan parantuminen. Näillä kaikilla toimenpiteillä on ollut kysyntää lisäävä vaikutus. Lähiliikenteessä on rakennettu kaupunkiratoja, uusittu junakalustoa ja tehty selkeitä lähijunaliikennettä edistäviä liikennepoliittisia toimia, joiden ansiosta matkustajamäärät ovat nousseet. Lisäksi pääkaupunkiseudun asukasmäärän kasvu on lisännyt lähijunaliikenteen kysyntää. Eri toimijoiden yhteistyöllä voidaan vaikuttaa rautateiden henkilöliikenteen kysyntään. Euroopan unionin linjaus, jossa maanteiltä ohjataan matkustajia raiteille, vaikuttaa myös Suomen liikennepolitiikkaan. Suomen liikennepoliittista työtä ja ohjausta tekee Liikenne- ja viestintäministeriö, joka on myös ostokaukoliikenteen ja vyöhykelähiliikenteen tilaaja. Liikennevirasto vaikuttaa kysyntään radan haltijana, kunnossapitäjänä sekä kehittäjänä. Maakuntaliitot ohjaavat maankäyttöä keskittäen ja tiivistäen, jonka kaupungit ja kunnat toteuttavat. Kaupungeille kuuluvat myös asemille johtavat kadut, jotka vaikuttavat liityntään. Helsingin seudun liikenne pääkaupunkiseudun tilaaja/tuottajana on strategiassaan määritellyt lähijunaliikenteensä joukkoliikenteen runkoverkoksi. VR Suomen tämän hetkisenä ainoana liikennöitsijänä operoi junaliikennettä, tekee aikatauluja, vastaa omista hinnoistaan ja kehittää junaliikennettä monin eri tavoin. Suomen kattavan rataverkon hyödyntäminen vaatii eri toimijoiden yhteistyötä, jotta rautateiden henkilöliikenteestä saadaan kilpailukykyinen ja houkutteleva liikkumismuoto

Somatic compensation of inherited bone marrow failure

Inherited bone marrow failure syndromes (IBMFS) are a heterogeneous group of genetic disorders characterized by insufficient blood cell production and increased risk of transformation to myeloid malignancies. While genetically diverse, IBMFS are collectively defined by a cell-intrinsic hematopoietic stem cell (HSC) fitness defect that impairs HSC self-renewal and hematopoietic differentiation. In IBMFS, HSCs frequently acquire mutations that improve cell fitness, a phenomenon known as somatic compensation. Somatic compensation can occur via distinct genetic processes such as loss of the germline mutation or somatic alterations in pathways affected by the disease-causing gene. While the clinical implications of somatic compensation in IBMFS remain to be fully discovered, understanding these mutational processes can help understand disease pathophysiology and may inform future diagnostic and therapeutic approaches. In this review, we highlight current understanding about somatic compensation in IBMFS. (c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )Peer reviewe

Point process models for sweat gland activation observed with noise

The aim of the paper is to construct spatial models for the activation of sweat glands for healthy subjects and subjects suffering from peripheral neuropathy by using videos of sweating recorded from the subjects. The sweat patterns are regarded as realizations of spatial point processes and two point process models for the sweat gland activation and two methods for inference are proposed. Several image analysis steps are needed to extract the point patterns from the videos and some incorrectly identified sweat gland locations may be present in the data. To take into account the errors we either include an error term in the point process model or use an estimation procedure that is robust with respect to the errors.Comment: 27 pages, 12 figure

Global quantile regression

Quantile regression is used to study effects of covariates on a particular quantile of the data distribution. Here we are interested in the question whether a covariate has any effect on the entire data distribution, i.e., on any of the quantiles. To this end, we treat all the quantiles simultaneously and consider global tests for the existence of the covariate effect in the presence of nuisance covariates. This global quantile regression can be used as the extension of linear regression or as the extension of distribution comparison in the sense of Kolmogorov-Smirnov test. The proposed method is based on pointwise coefficients, permutations and global envelope tests. The global envelope test serves as the multiple test adjustment procedure under the control of the family-wise error rate and provides the graphical interpretation which automatically shows the quantiles or the levels of categorical covariate responsible for the rejection. The Freedman-Lane permutation strategy showed liberality of the test for extreme quantiles, therefore we propose four alternatives that work well even for extreme quantiles and are suitable in different conditions. We present a simulation study to inspect the performance of these strategies, and we apply the chosen strategies to two data examples.Comment: 44 pages, 12 figure

Mutaatiot hematopoieettisissa kantasoluissa - merkki ikääntymisestä vai pahanlaatuisen veritaudin esiaste?

Vertaisarvioitu.Ikääntymisen myötä verta muodostaviin hematopoieettisiin kantasoluihin ilmaantuu hankinnaisia mutaatioita. Mutaatiot ovat usein samoja, joita todetaan pahanlaatuisten veritautien yhteydessä. Mutaatiot saattavat antaa kantasolulle kasvuedun, jolloin kantasolu sekä sen jälkeläiset lisääntyvät luuytimessä ja muodostavat kloonin. Klooneja löydetään myös terveiltä ihmisiltä. Ilmiötä kutsutaan klonaaliseksi hematopoieesiksi. Vaikka klonaalinen hematopoieesi ei aiheuta valtaosalle kantajistaan terveyshaittoja, se liittyy lyhyempään elinikään sekä suurentuneeseen veri- sekä sydän- ja verisuonitautien riskiin. Pahanlaatuisten veritautien geenien sekvensointi on nykyisin osa hematologisia tutkimuksia, ja mutaatioita löydetään myös henkilöiltä, joille pahanlaatuisen veritaudin diagnoosia ei voida asettaa. Tällaisissa tapauksissa klonaalisen hematopoieesin aiheuttajamutaation löytyminen auttaa arvioimaan pahanlaatuisten veritautien riskiä ja seurannan tarvetta. Tulevaisuuden lääketutkimuksissa selvitetään, voidaanko kloonin hävittämisellä vähentää terveysriskejä.Peer reviewe

AS-ASL: Algorithm Selection with Auto-sklearn

Peer reviewe

Empirical Hardness of Finding Optimal Bayesian Network Structures: Algorithm Selection and Runtime Prediction

Various algorithms have been proposed for finding a Bayesian network structure that is guaranteed to maximize a given scoring function. Implementations of state-of-the-art algorithms, solvers, for this Bayesian network structure learning problem rely on adaptive search strategies, such as branch-and-bound and integer linear programming techniques. Thus, the time requirements of the solvers are not well characterized by simple functions of the instance size. Furthermore, no single solver dominates the others in speed. Given a problem instance, it is thus a priori unclear which solver will perform best and how fast it will solve the instance. We show that for a given solver the hardness of a problem instance can be efficiently predicted based on a collection of non-trivial features which go beyond the basic parameters of instance size. Specifically, we train and test statistical models on empirical data, based on the largest evaluation of state-of-the-art exact solvers to date. We demonstrate that we can predict the runtimes to a reasonable degree of accuracy. These predictions enable effective selection of solvers that perform well in terms of runtimes on a particular instance. Thus, this work contributes a highly efficient portfolio solver that makes use of several individual solvers.Peer reviewe