Lipids of Chlamydomonas reinhardtii. Analysis of Molecular Species and Intracellular Site(s) of Biosynthesis

Membrane lipids of Chlamydomonas reinhardtii were separated into the major components, MGDG, DGDG, SQDG, DGTS, PG, PE, PI, and the molecular species of each lipid were isolated and analyzed. The fatty acid composition was determined for the total lipid, the particular lipid classes and the molecular species. The positional distribution of fatty acids between the C-1 and C-2 position of the glycerol moiety was also determined. MGDG, DGDG, SQDG, PG and probably PI were found to be of plastidic (prokaryotic) origin, while DGTS and PE were found to be of cytoplasmic (eukaryotic) origin. Prokaryotic lipids mainly contained 18:3(9,12,15), 18:2,16:4 and 16:3, while DGTS and PE were rich in 18:3(5,9,12), 18:4(5,9,12,15), 18:2 and 18:1(11) fatty acids. From the fact that each lipid class was characterized by an individual pattern of molecular species, we conclude that during their biosynthesis, all the lipids act individually as substrates for the lipid-linked desaturation of fatty acids. Moreover, our results suggest that in Chlamydomonas, 18:3(5,9,12) and 18:4(5,9,12,15) are formed in the cytoplasm using DGTS and PE as substrate

Fully automatic algorithm for detecting and tracking anatomical shoulder landmarks on fluoroscopy images with artificial intelligence.

OBJECTIVE Patients with rotator cuff tears present often with glenohumeral joint instability. Assessing anatomic angles and shoulder kinematics from fluoroscopy requires labelling of specific landmarks in each image. This study aimed to develop an artificial intelligence model for automatic landmark detection from fluoroscopic images for motion tracking of the scapula and humeral head. MATERIALS AND METHODS Fluoroscopic images were acquired for both shoulders of 25 participants (N = 12 patients with unilateral rotator cuff tear, 6 men, mean (standard deviation) age: 63.7 ± 9.7 years; 13 asymptomatic subjects, 7 men, 58.2 ± 8.9 years) during a 30° arm abduction and adduction movement in the scapular plane with and without handheld weights of 2 and 4 kg. A 3D full-resolution convolutional neural network (nnU-Net) was trained to automatically locate five landmarks (glenohumeral joint centre, humeral shaft, inferior and superior edges of the glenoid and most lateral point of the acromion) and a calibration sphere. RESULTS The nnU-Net was trained with ground-truth data from 6021 fluoroscopic images of 40 shoulders and tested with 1925 fluoroscopic images of 10 shoulders. The automatic landmark detection algorithm achieved an accuracy above inter-rater variability and slightly below intra-rater variability. All landmarks and the calibration sphere were located within 1.5 mm, except the humeral landmark within 9.6 mm, but differences in abduction angles were within 1°. CONCLUSION The proposed algorithm detects the desired landmarks on fluoroscopic images with sufficient accuracy and can therefore be applied to automatically assess shoulder motion, scapular rotation or glenohumeral translation in the scapular plane. CLINICAL RELEVANCE STATEMENT This nnU-net algorithm facilitates efficient and objective identification and tracking of anatomical landmarks on fluoroscopic images necessary for measuring clinically relevant anatomical configuration (e.g. critical shoulder angle) and enables investigation of dynamic glenohumeral joint stability in pathological shoulders. KEY POINTS • Anatomical configuration and glenohumeral joint stability are often a concern after rotator cuff tears. • Artificial intelligence applied to fluoroscopic images helps to identify and track anatomical landmarks during dynamic movements. • The developed automatic landmark detection algorithm optimised the labelling procedures and is suitable for clinical application

Severity of rotator cuff disorders and additional load affect fluoroscopy-based shoulder kinematics during arm abduction.

BACKGROUND Rotator cuff disorders, whether symptomatic or asymptomatic, may result in abnormal shoulder kinematics (scapular rotation and glenohumeral translation). This study aimed to investigate the effect of rotator cuff tears on in vivo shoulder kinematics during a 30° loaded abduction test using single-plane fluoroscopy. MATERIALS AND METHODS In total, 25 younger controls, 25 older controls and 25 patients with unilateral symptomatic rotator cuff tears participated in this study. Both shoulders of each participant were analysed and grouped on the basis of magnetic resonance imaging into healthy, rotator cuff tendinopathy, asymptomatic and symptomatic rotator cuff tears. All participants performed a bilateral 30° arm abduction and adduction movement in the scapular plane with handheld weights (0, 2 and 4 kg) during fluoroscopy acquisition. The range of upward-downward scapular rotation and superior-inferior glenohumeral translation were measured and analysed during abduction and adduction using a linear mixed model (loads, shoulder types) with random effects (shoulder ID). RESULTS Scapular rotation was greater in shoulders with rotator cuff tendinopathy and asymptomatic rotator cuff tears than in healthy shoulders. Additional load increased upward during abduction and downward during adduction scapular rotation (P < 0.001 in all groups but rotator cuff tendinopathy). In healthy shoulders, upward scapular rotation during 30° abduction increased from 2.3° with 0-kg load to 4.1° with 4-kg load and on shoulders with symptomatic rotator cuff tears from 3.6° with 0-kg load to 6.5° with 4-kg load. Glenohumeral translation was influenced by the handheld weights only in shoulders with rotator cuff tendinopathy (P ≤ 0.020). Overall, superior glenohumeral translation during 30° abduction was approximately 1.0 mm with all loads. CONCLUSIONS The results of glenohumeral translation comparable to control but greater scapular rotations during 30° abduction in the scapular plane in rotator cuff tears indicate that the scapula compensates for rotator cuff deficiency by rotating. Further analysis of load-dependent joint stability is needed to better understand glenohumeral and scapula motion. LEVEL OF EVIDENCE Level 2. TRIAL REGISTRATION Ethical approval was obtained from the regional ethics committee (Ethics Committee Northwest Switzerland EKNZ 2021-00182), and the study was registered at clinicaltrials.gov on 29 March 2021 (trial registration number NCT04819724, https://clinicaltrials.gov/ct2/show/NCT04819724 )

Body odors of newborns activate neuronal regions associated with reward in women

abstract in symposium Cerebral Imaging in Taste and OlfactionOlfactory signals are prime mediators of mother-infant bonding in. mammals, and they have been shown to be linked with maternal. attitudes and behavior in our own species as well. Human mothers. are indeed highly attentive to their infants odor cues, but although. we have good understanding of the neuronal network supporting. mother-infant olfactory recognition in various mammals, to date. no such information exists for humans. The present study is a first attempt at delineating the neural. network underlying the processing of infant odor properties by. women. Using functional magnetic resonance imaging (fMRI),. we measured the pattern of cerebral activation of first-time mothers. and nulliparous women while smelling the body odor of unfamiliar. 2 day-old newborn infants. Both groups of participants did. perceive infants body odor as equally pleasant, intense, and familiar. Smelling an infant’s body odor provoked significant activity in. neostriatal areas, the hippocampus, and the insular cortex. The. cerebral activation of mothers and nulliparous women differed,. however, within these areas. Mothers demonstrated higher activity. bilaterally within the caudate nuclei compared to nulliparous. women. This study reveals that body odors from 2 day-old newborns produce. activation in reward-related cerebral areas in women, regardless. of their maternal status. Recent mothers show, however,. stronger infant odor-elicited activation in the caudate nucleus, suggesting. that they may be more sensitive than nulliparous women to. the reinforcing value of their offspring odor qualities. This suggests. that body odors might act as a catalyst for reward learning mechanisms. involved in the development of bonding

Fully automatic algorithm for detecting and tracking anatomical shoulder landmarks on fluoroscopy images with artificial intelligence

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)Objective: Patients with rotator cuff tears present often with glenohumeral joint instability. Assessing anatomic angles and shoulder kinematics from fluoroscopy requires labelling of specific landmarks in each image. This study aimed to develop an artificial intelligence model for automatic landmark detection from fluoroscopic images for motion tracking of the scapula and humeral head. Materials and methods: Fluoroscopic images were acquired for both shoulders of 25 participants (N = 12 patients with unilateral rotator cuff tear, 6 men, mean (standard deviation) age: 63.7 ± 9.7 years; 13 asymptomatic subjects, 7 men, 58.2 ± 8.9 years) during a 30° arm abduction and adduction movement in the scapular plane with and without handheld weights of 2 and 4 kg. A 3D full-resolution convolutional neural network (nnU-Net) was trained to automatically locate five landmarks (glenohumeral joint centre, humeral shaft, inferior and superior edges of the glenoid and most lateral point of the acromion) and a calibration sphere. Results: The nnU-Net was trained with ground-truth data from 6021 fluoroscopic images of 40 shoulders and tested with 1925 fluoroscopic images of 10 shoulders. The automatic landmark detection algorithm achieved an accuracy above inter-rater variability and slightly below intra-rater variability. All landmarks and the calibration sphere were located within 1.5 mm, except the humeral landmark within 9.6 mm, but differences in abduction angles were within 1°. Conclusion: The proposed algorithm detects the desired landmarks on fluoroscopic images with sufficient accuracy and can therefore be applied to automatically assess shoulder motion, scapular rotation or glenohumeral translation in the scapular plane. Clinical relevance statement: This nnU-net algorithm facilitates efficient and objective identification and tracking of anatomical landmarks on fluoroscopic images necessary for measuring clinically relevant anatomical configuration (e.g. critical shoulder angle) and enables investigation of dynamic glenohumeral joint stability in pathological shoulders. Key Points: • Anatomical configuration and glenohumeral joint stability are often a concern after rotator cuff tears. • Artificial intelligence applied to fluoroscopic images helps to identify and track anatomical landmarks during dynamic movements. • The developed automatic landmark detection algorithm optimised the labelling procedures and is suitable for clinical application

TGF-beta1-mediated control of central nervous system inflammation and autoimmunity through the inhibitory receptor CD26.

The T cell marker CD26/dipeptidyl peptidase (DP) IV is associated with an effector phenotype and markedly elevated in the human CNS disorder multiple sclerosis. However, little is known about the in vivo role of CD26/DP IV in health and disease, and the underlying mechanism of its function in CNS inflammation. To directly address the role of CD26/DP IV in vivo, we examined Th1 immune responses and susceptibility to experimental autoimmune encephalomyelitis in CD26(-/-) mice. We show that gene deletion of CD26 in mice leads to deregulation of Th1 immune responses. Although production of IFN-gamma and TNF-alpha by pathogenic T cells in response to myelin Ag was enhanced in CD26(-/-) mice, production of the immunosuppressive cytokine TGF-beta1 was diminished in vivo and in vitro. In contrast to the reduction in TGF-beta1 production, responsiveness to external TGF-beta1 was normal in T cells from CD26(-/-) mice, excluding alterations in TGF-beta1 sensitivity as a mechanism causing the loss of immune regulation. Natural ligands of CD26/DP IV induced TGF-beta1 production in T cells from wild-type mice. However, natural ligands of CD26/DP IV failed to elicit TGF-beta1 production in T cells from CD26(-/-) mice. The striking functional deregulation of Th1 immunity was also seen in vivo. Thus, clinical experimental autoimmune encephalomyelitis scores were significantly increased in CD26(-/-) mice immunized with peptide from myelin oligodendrocyte glycoprotein. These results identify CD26/DP IV as a nonredundant inhibitory receptor controlling T cell activation and Th1-mediated autoimmunity, and may have important therapeutic implications for the treatment of autoimmune CNS disease