1. A method of predicting a treatment outcome in a patient with Major Depressive Disorder (MDD) comprising the steps of:
a) assessing a cognitive andor a genomic parameter in said patient thereby obtaining an assessment score for said parameter; and
b) comparing said assessment score of step a) with a reference set of assessment scores for said parameter to establish a correlation between said assessment score with a corresponding assessment score of the reference set, wherein said corresponding assessment score is linked to a treatment outcome in MDD patients having been treated with a selected antidepressant medication (ADM),
wherein said correlation of step b) is used to predict a treatment outcome for said patient with MDD when treated with the selected ADM.
2. The method according to claim 1, wherein the reference set of assessment scores comprises assessment scores for cognitive andor genomic parameters identified as statistically significant predictors of treatment outcome in MDD patients having been divided into at least two patient sub-groups based on a comparison of:
assessment scores obtained by said patients for at least one parameter before treatment with a selected ADM; and
assessment scores obtained for said same parameter in a group of subjects without MDD.
3. The method according to claim 2, wherein:
a first cognitive parameter is a predictor of treatment outcome for MDD patients in one of the patient sub-groups when the division into said sub-groups is based on the comparison of at least a second cognitive parameter, or
a genomic parameter is a predictor of treatment outcome for MDD patients in one of the patient sub-groups when the division into said sub-groups is based on the comparison of at least one cognitive parameter.
4. The method according to claim 2, wherein the comparison is based on least two cognitive assessment scores and wherein the patients are divided into sub-groups of \u201caverage cognitive performance\u201d and \u201cbelow average cognitive performance\u201d.
5. The method according to claim 1, wherein treatment outcome is determined by a symptom score according to the clinician-rated 17-item Hamilton Rating Scale for Depression (HRSD17) or according to the self-rated the 16-item Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR16), wherein a \u226750% decrease of a symptom score determined before treatment with a selected ADM after 8 weeks of treatment with said selected ADM indicate a treatment response and wherein symptom scores of \u22667 on the HRSD17 or of \u22665 on the QIDS-SR16 after 8 weeks of treatment with said selected ADM indicate remission.
6. The method according to claim 1, wherein:
the cognitive parameter is selected from the group consisting of motor coordination assessed by motor tapping test, decision speed assessed by choice reaction time test, verbal memory assessed by memory recall test, working memory assessed by digit span test, cognitive flexibility assessed by verbal interference test, information processing speed assessed by switching of attention test, response inhibition assessed by gono-go test, attention assessed by continuous performance test, executive function assessed by maze test, emotion identification accuracy and speed assessed by explicit emotion test, and identification and implicit emotion bias assessed by delayed emotion recognition test; or
the genomic parameter is selected from the group single nucleotide polymorphisms (SNPs) shown in FIG. 11.
7. The method according to claim 1, wherein:
the cognitive parameter is selected from the group consisting of motor coordination assessed by motor tapping test, decision speed assessed by choice reaction time test, verbal memory assessed by memory recall test, working memory assessed by digit span test, cognitive flexibility assessed by verbal interference test, information processing speed assessed by switching of attention test, response inhibition assessed by gono-go test, attention assessed by continuous performance test, executive function assessed by maze test, emotion identification accuracy and speed assessed by explicit emotion test, and identification and implicit emotion bias assessed by delayed emotion recognition test, and
the genomic parameter is selected from the group single nucleotide polymorphisms (SNPs) shown in FIG. 11.
8. The method according to claim 1, wherein the ADM is selected from the group consisting of selective serotonin reuptake inhibitors (SSRIs) and serotonin reuptake inhibitors (SNRIs).
9. The method according to claim 8, wherein the ADM is selected from escitalopram, sertraline and venlafaxine-extended release (venlafaxine-XR).
10. The method according to claim 2, wherein:
the cognitive parameter assessed is emotion identification speed and wherein the MDD patients are divided into sub-groups based on to their assessment scores for attention or executive function, wherein either poor attention or poor executive function predicts symptom remission after 8 weeks of treatment with either escitalopram, sertraline or venlafaxine-XR; or
the cognitive parameter assessed is cognitive flexibility and wherein the MDD patients are divided into sub-groups based on to their assessment scores for delayed recognition of emotion speed, wherein delayed emotion identification speed predicts symptom remission after 8 weeks of treatment with either escitalopram, sertraline or venlafaxine-XR.
11. A method of predicting symptom remission or symptom response in a patient with Major Depressive Disorder (MDD) when treated with a selected ADM comprising the steps of:
a) assessing more than one cognitive and genomic parameter in said patient thereby obtaining an assessment score for each of said parameters;
b) comparing said assessment scores of step a) with a reference set of assessment scores for said parameters to establish a correlation between an assessment score for at least one genomic parameter of step a) with a corresponding assessment score of the reference set,
wherein said corresponding assessment score is linked to symptom remission or symptom response in MDD patients having been treated with a selected antidepressant medication (ADM) based on a regression model with cross-validated sensitivity or specificity of greater than 50% where said MDD patients were divided into patient cognitive performance sub-groups based a comparison of:
assessment scores obtained by said patients for at least one cognitive parameter before treatment with a selected ADM; and
assessment scores obtained for said same cognitive parameter in a group of subjects without MDD;
c) determining into which cognitive performance sub-group said patient falls based on said cognitive assessment scores of step a); and
d) correlating said assessment score for said at least one genomic parameter of step a) with a with a corresponding assessment score of the reference set thereby predicting symptom remission or symptom response in said patient when treated with said selected ADM.
12. The method according to claim 11, wherein the cognitive performance sub-groups are \u201caverage cognitive performance\u201d and \u201cbelow average cognitive performance\u201d sub-groups and wherein said ADM is selected from selective serotonin reuptake inhibitors (SSRIs) and serotonin reuptake inhibitors (SNRIs).
13. The method according to claim 11, wherein:
said regression model is a univariate regression model; or
said regression model is a univariate regression model and includes running separate univariate models for each of the genomic parameters, incorporating cross-validation using a k-fold approach.
14. The method according to claim 11, wherein said genomic parameters are single nucleotide polymorphisms (SNPs).
15. The method according to claim 11, wherein said regression model is a multivariate logistic regression model.
16. The method according to claim 11, wherein said regression model provides a statistical significance of p<0.01.
17. The method according to claim 11, wherein:
said patient falls into said \u201cbelow average cognition\u201d sub-group and wherein correlating an assessment score for MAOA rs2235186, MAOA rs979605, HTR3D rs9819507, GRIK1 rs2251036, GIRK2 rs1415485, GIRK4 rs2852217, GRIN1 rs4880213, GRIN2B rs1805490 or DARPP-32 rs907094 with a with a corresponding assessment score of the reference set predicts symptom remission in said patient when treated with escitalopram; or
said patient falls into said \u201caverage cognition\u201d sub-group and wherein correlating an assessment score for HTR2A rs2770296, GRIK2 rs2518227 or FKBP5 rs136078 with a with a corresponding assessment score of the reference set predicts symptom remission in said patient when treated with escitalopram; or
said patient falls into said \u201cbelow average cognition\u201d sub-group and wherein correlating an assessment score for HTR2C rs540285, GRIK1 rs363478, GRIN2A rs1650397, GRIN2A rs6416623, GRIN3A rs2050641, BCL2 rs1944420, BCL2 rs2849380, FKBP5 rs1360780, NR3C2 rs1355613, or NR3C2 rs2070951 with a with a corresponding assessment score of the reference set predicts symptom remission in said patient when treated with sertraline; or
said patient falls into said \u201caverage cognition\u201d sub-group and wherein correlating an assessment score for ABCB1 rs779319 or NR3C2 rs1512343 with a with a corresponding assessment score of the reference set predicts symptom remission in said patient when treated with sertraline.
18. A method of predicting symptom remission or symptom response in a patient with Major Depressive Disorder (MDD) when treated with a selected ADM comprising the steps of:
a) assessing more than one cognitive parameter in said patient thereby obtaining an assessment score for each of said parameters;
b) comparing said assessment scores of step a) with a reference set of assessment scores for said parameters to establish a correlation between an assessment score for at least one cognitive parameter with a corresponding assessment score of the reference set,
wherein said corresponding assessment score is linked to symptom remission or symptom response in MDD patients having been treated with a selected antidepressant medication (ADM) based on a regression model with cross-validated sensitivity or specificity of greater than 50% where said MDD patients were divided into patient cognitive performance sub-groups based a comparison of:
assessment scores obtained by said patients for at least one cognitive parameter before treatment with a selected ADM; and
assessment scores obtained for said same cognitive parameter in a group of subjects without MDD;
c) determining into which cognitive performance sub-group said patient falls based on said cognitive assessment scores of step a); and
d) correlating said assessment score for said at least one cognitive parameter of step a) with a with a corresponding assessment score of the reference set thereby predicting symptom remission or symptom response in said patient when treated with said selected ADM.
19. The method according to claim 18, wherein the cognitive performance sub-groups are \u201caverage cognitive performance\u201d and \u201cbelow average cognitive performance\u201d sub-groups and wherein said ADM is selected from selective serotonin reuptake inhibitors (SSRIs) and serotonin reuptake inhibitors (SNRIs).
20. The method according to claim 18, wherein:
said regression model is a univariate regression model; or
said regression model is a univariate regression model and includes running separate univariate models for each of the cognitive parameters, incorporating cross-validation using a k-fold approach.
21. The method according to claim 18, wherein said regression model is a multivariate logistic regression model.
22. The method according to claim 18, wherein said regression model provides a statistical significance of p<0.01.
23. A method of treating Major Depressive Disorder (MDD) in a patient, wherein said MDD is associated with a cognitive andor a genomic parameter, said method comprising the steps of:
a) assessing said cognitive andor a genomic parameter in said patient thereby obtaining an assessment score for said parameter;
b) comparing said assessment score with a reference set of assessment scores for said parameter to establish a correlation between said assessment score obtained in step a) with a corresponding assessment score of the reference set;
c) selecting an antidepressant medication (ADM) based on said correlation of step b), and wherein said correlation is established for a parameter linked to beneficial treatment outcome in MDD patients having been treated with said ADM; and
d) administering said ADM selected in c) to said patient to treat said MDD.
The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.
1. An oven for use in an aircraft, the oven comprising; a preparation space, an air circulation device that causes circulation of air through the preparation space, and a heating device co-acting with the air circulation device that heats the circulation air, wherein the air circulation device comprises at least one fan and at least one separating wall placed between the fan and the preparation space, wherein the separating wall is a substantially fiat plate having one side facing the preparation space and an opposite side facing away from the preparation space, the separating wall further having an airflow uniformity enhancing device that enhances the uniformity of hot airflow in the preparation space, wherein the airflow uniformity enhancing device includes at least one horizontal flow guide on the side of the fiat plate that faces away from the preparation space, the at least one flow guide extending substantially transversely of the separating wall along an upper edge thereof and directed away from the preparation space, such that heated air can flow round the edge of the separating wall only at determined locations, the at least one horizontal flow guide comprises an undulating contour; the airflow uniformity enhancing device further including at least one vertical guide located on a side of the flat plate and extending in the direction of the at least one flow guide, the vertical flow guide having a middle portion and bent side portions located on opposite sides of the middle portion.
2. The oven as claimed in claim 1, wherein the at least one flow guide is placed substantially at the position of the fan.
3. The oven as claimed in claim 1, wherein the at least one flow guide has a middle part extending substantially transversely of the separating wall and at least one end part which fans out.
4. The oven as claimed in claim 1, wherein the at least one flow guide extends substantially vertically along an edge of the separating wall.
5. The oven as claimed in claim 4, wherein the at lest one flow guide extends over only a part of the height of the separating wall.
6. The oven as claimed in claim 1, wherein the at least one flow guide extends substantially horizontally along an upper edge of the separating wall.
7. The oven as claimed in claim 6, wherein the at least one flow guide extends substantially over the whole width of the separating wall.
8. The oven as claimed in claim 6, wherein the at least one flow guide has a wave-like progression.
9. The oven as claimed in claim 1, wherein the separating wall has at least one opening for drawing air out of the preparation space, and the airflow uniformity enhancing device further includes a throat connected to the at least one opening.
10. The oven as claimed in claim 1, wherein the separating wall extends substantially vertically and the airflow uniformity enhancing device further includes end edges of the separating wall which run close to side walls of the preparation space and which have a form curved or bent toward the preparation space relative to a main place of the separating wall.
11. A separating wall for use in an aircraft oven, the separating wall being between a fan and a preparation space, said separating wall being a substantially fiat plate having one side facing the preparation space and an opposite side facing away from the preparation space, the separation wall further having an airflow uniformity enhancing device that enhances the uniformity of hot airflow in the preparation space, wherein the airflow uniformity enhancing device further includes at least one horizontal flow guide connected to the side of the fiat plate that faces away from the preparation space, the at least one flow guide extending substantially transversely of the separating wall along an upper edge thereof and directed away from the preparation space, such that hot airflow round the edge of the separating wall is only possible at determined locations, the at least one horizontal flow guide comprises an undulating contour; the airflow uniformity enhancing device further including at least one vertical guide located on a side of the flat plate and extending in the direction of the at least one flow guide, the vertical flow guide having a middle portion and bent side portions located on opposite sides of the middle portion.
12. The separating wall as claimed in claim 11, wherein the at least one flow guide is placed substantially at the position of the fan.
13. The separating wall as claimed in claim 11, wherein the at least one flow guide has a middle part extending substantially transversely of the separating wall and at least one end part which fans out.
14. The separating wall as claimed in claim 11, wherein the at least one flow guide extends substantially vertically along an end edge of the separating wall.
15. The separating wall as claimed in claim 14, wherein the at least one flow glow guide extends over only a part of the height of the separating wall.
16. The separating wall as claimed in claim 11, wherein the at least one flow guide extend substantially horizontally along an upper edge of the separating wall.
17. The separating wall as claimed in claim 16, wherein the at least one flow guide extends substantially over the whole width of the separating wall.
18. The separating wall as claimed in claim 16, wherein the at least one flow guide has a wave-like progression.
19. The separating wall as claimed in claim 11, wherein the separating wall has at least one opening for drawing air out of the preparation space, and the airflow uniformity enhancing device further includes a throat connected to the at least one opening.
20. The separating wall as claimed in claim 11, wherein the separating wall extends substantially vertically and the airflow uniformity enhancing device further includes end edges of the separating wall which run close to side walls of the preparation space and which have a form curved or bent toward the preparation space relative to a main plane of the separating wall.