Plasma and fecal progestins during placentation in the mare

Aims of this research were to find the time period and specific progestins reflective of the transition from ovarian source to placental source during early gestation in mares. An attempt was made to describe an accurate profile of total and individual progestins in plasma and feces from 64 to 150 days of gestation. There was also an attempt to determine if plasma and fecal progestins increased around 90 days of gestation as previously reported in this laboratory for urinary hormones, estrone sulfate (E1S) and pregnanediol glucuronide (PdG). Blood and fecal samples were collected and ovaries were examined via ultrasound every other day from days 64 to 150 of gestation. Plasma and fecal samples were analyzed using gas chromatography/mass spectrometry (GC/MS) with steroid derivatization. Eight progestins in plasma and ten progestins in feces were identified and quantified. In plasma, 20α-hydroxy-5α-pregnan-3-one (20α-5α) was found in highest concentration, while 5α-pregnane-3β,20β-diol (ββ-diol) was highest in feces. Progestins averaged approximately 100 times higher in feces than in plasma, while ββ-diol was about 800 times higher. There was a linear, parallel increase over time (P<0.05, ANOVA) for total progestins. There was a high, positive correlation between plasma and feces for most progestins, the exception being progesterone (P4), which was negatively correlated because over time, concentrations in plasma decreased while increasing in feces. Log ratios of feces to plasma indicated some progestins increased faster in plasma than feces, and vice-versa, while some remained constant. Spline regression (Gauss-Newton, SAS) analysis of the four main progestins, 3β-hydroxy-5apregnan- 3-one (3β-5α), 20α-5α, 5α-pregnane-3β,20α-diol (βα-diol), and ββ-diol, indicated a difference in the rate of increase over time, occurring at about 112.7 days of gestation in plasma and 109 days of pregnancy in feces, which was nearly 20 days later than that reported for urine. Although the time of change in the rate of increase was highly variable among mares and specific progestins, for most, a clear change was evident by 115 days of gestation. This likely represents a functional feto-placental unit, fully capable of pregnancy maintenance

FMRI connectivity analysis of acupuncture effects on an amygdala-associated brain network

<p>Abstract</p> <p>Background</p> <p>Recently, increasing evidence has indicated that the primary acupuncture effects are mediated by the central nervous system. However, specific brain networks underpinning these effects remain unclear.</p> <p>Results</p> <p>In the present study using fMRI, we employed a within-condition interregional covariance analysis method to investigate functional connectivity of brain networks involved in acupuncture. The fMRI experiment was performed before, during and after acupuncture manipulations on healthy volunteers at an acupuncture point, which was previously implicated in a neural pathway for pain modulation. We first identified significant fMRI signal changes during acupuncture stimulation in the left amygdala, which was subsequently selected as a functional reference for connectivity analyses. Our results have demonstrated that there is a brain network associated with the amygdala during a resting condition. This network encompasses the brain structures that are implicated in both pain sensation and pain modulation. We also found that such a pain-related network could be modulated by both verum acupuncture and sham acupuncture. Furthermore, compared with a sham acupuncture, the verum acupuncture induced a higher level of correlations among the amygdala-associated network.</p> <p>Conclusion</p> <p>Our findings indicate that acupuncture may change this amygdala-specific brain network into a functional state that underlies pain perception and pain modulation.</p

Wandering Pattern Sensing at S-Band

Increasing prevalence of dementia has posed several challenges for care-givers. Patients suffering from dementia often display wandering behavior due to boredom or memory loss. It is considered to be one of the challenging conditions to manage and understand. Traits of dementia patients can compromise their safety causing serious injuries. This paper presents investigation into the design and evaluation of wandering scenarios with patients suffering from dementia using an S-band sensing technique. This frequency band is the wireless channel commonly used to monitor and characterize different scenarios including random, lapping, and pacing movements in an indoor environment. Wandering patterns are characterized depending on the received amplitude and phase information of that measures the disturbance caused in the ideal radio signal. A secondary analysis using support vector machine is used to classify the three patterns. The results show that the proposed technique carries high classification accuracy up to 90% and has good potential for healthcare application

Detection of Essential Tremor at the S -Band

Essential tremor (ET) is a neurological disorder characterized by rhythmic, involuntary shaking of a part or parts of the body. The most common tremor is seen in the hands/arms and fingers. This paper presents an evaluation of ETs monitoring based on finger-to-nose test measurement as captured by small wireless devices working in shortwave or S-band frequency range. The acquired signals in terms of amplitude and phase information are used to detect a tremor in the hands. Linearly transforming raw phase data acquired in the S-band were carried out for calibrating the phase information and to improve accuracy. The data samples are used for classification using support vector machine algorithm. This model is used to differentiate the tremor and nontremor data efficiently based on secondary features that characterize ET. The accuracy of our measurements maintains linearity, and more than 90% accuracy rate is achieved between the feature set and data samples

Impact of Brain-Derived Neurotrophic Factor Val66Met Polymorphism on Cortical Thickness and Voxel-Based Morphometry in Healthy Chinese Young Adults

BACKGROUND: Following voxel-based morphometry (VBM), brain-derived neurotrophic factor (BDNF) Val66Met polymorphism (rs6265) has been shown to affect human brain morphology in Caucasians. However, little is known about the specific role of the Met/Met genotype on brain structure. Moreover, the relationship between BDNF Val66Met polymorphism and Chinese brain morphology has not been studied. METHODOLOGY/PRINCIPAL FINDINGS: The present study investigated brain structural differences among three genotypes of BDNF (rs6265) for the first time in healthy young Chinese adults via cortical thickness analysis and VBM. Brain differences in Met carriers using another grouping method (combining Val/Met and Met/Met genotypes into a group of Met carriers as in most previous studies) were also investigated using VBM. Dual-approach analysis revealed less gray matter (GM) in the frontal, temporal, cingulate and insular cortices in the Met/Met group compared with the Val/Val group (corrected, P<0.05). Areas with less GM in the Val/Met group were included in the Met/Met group. VBM differences in Met carriers were only found in the middle cingulate cortex. CONCLUSIONS/SIGNIFICANCE: The current results indicated a unique pattern of brain morphologic differences caused by BDNF (rs6265) in young Chinese adults, in which the Met/Met genotype markedly affected the frontal, temporal, cingulate, and insular regions. The grouping method with Met carriers was not suitable to detect the genetic effect of BDNF Val66Met polymorphism on brain morphology, at least in the Chinese population, because it may hide some specific roles of Met/Met and Val/Met genotypes on brain structure

Interaction between Dysfunctional Connectivity at Rest and Heroin Cues-Induced Brain Responses in Male Abstinent Heroin-Dependent Individuals

BACKGROUND: The majority of previous heroin cue-reactivity functional magnetic resonance imaging (fMRI) studies focused on local function impairments, such as inhibitory control, decision-making and stress regulation. Our previous studies have demonstrated that these brain circuits also presented dysfunctional connectivity during the resting state. Yet few studies considered the relevance of resting state dysfunctional connectivity to task-related neural activity in the same chronic heroin user (CHU). METHODOLOGY/PRINCIPAL FINDINGS: We employed the method of graph theory analysis, which detected the abnormality of brain regions and dysregulation of brain connections at rest between 16 male abstinent chronic heroin users (CHUs) and 16 non-drug users (NDUs). Using a cue-reactivity task, we assessed the relationship between drug-related cue-induced craving activity and the abnormal topological properties of the CHUs' resting networks. Comparing NDUs' brain activity to that of CHUs, the intensity of functional connectivity of the medial frontal gyrus (meFG) in patients' resting state networks was prominently greater and positively correlated with the same region's neural activity in the heroin-related task; decreased functional connectivity intensity of the anterior cingulate cortex (ACC) in CHUs at rest was associated with more drug-related cue-induced craving activities. CONCLUSIONS: These results may indicate that there exist two brain systems interacting simultaneously in the heroin-addicted brain with regards to a cue-reactivity task. The current study may shed further light on the neural architecture that supports craving responses in heroin dependence

Microstructure Abnormalities in Adolescents with Internet Addiction Disorder

BACKGROUND: Recent studies suggest that internet addiction disorder (IAD) is associated with structural abnormalities in brain gray matter. However, few studies have investigated the effects of internet addiction on the microstructural integrity of major neuronal fiber pathways, and almost no studies have assessed the microstructural changes with the duration of internet addiction. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the morphology of the brain in adolescents with IAD (N = 18) using an optimized voxel-based morphometry (VBM) technique, and studied the white matter fractional anisotropy (FA) changes using the diffusion tensor imaging (DTI) method, linking these brain structural measures to the duration of IAD. We provided evidences demonstrating the multiple structural changes of the brain in IAD subjects. VBM results indicated the decreased gray matter volume in the bilateral dorsolateral prefrontal cortex (DLPFC), the supplementary motor area (SMA), the orbitofrontal cortex (OFC), the cerebellum and the left rostral ACC (rACC). DTI analysis revealed the enhanced FA value of the left posterior limb of the internal capsule (PLIC) and reduced FA value in the white matter within the right parahippocampal gyrus (PHG). Gray matter volumes of the DLPFC, rACC, SMA, and white matter FA changes of the PLIC were significantly correlated with the duration of internet addiction in the adolescents with IAD. CONCLUSIONS: Our results suggested that long-term internet addiction would result in brain structural alterations, which probably contributed to chronic dysfunction in subjects with IAD. The current study may shed further light on the potential brain effects of IAD

Gender-Related Differences in the Dysfunctional Resting Networks of Migraine Suffers

BACKGROUND: Migraine shows gender-specific incidence and has a higher prevalence in females. However, little is known about gender-related differences in dysfunctional brain organization, which may account for gender-specific vulnerability and characteristics of migraine. In this study, we considered gender-related differences in the topological property of resting functional networks. METHODOLOGY/PRINCIPAL FINDINGS: Data was obtained from 38 migraine patients (18 males and 20 females) and 38 healthy subjects (18 males and 20 females). We used the graph theory analysis, which becomes a powerful tool in investigating complex brain networks on a whole brain scale and could describe functional interactions between brain regions. Using this approach, we compared the brain functional networks between these two groups, and several network properties were investigated, such as small-worldness, network resilience, nodal centrality, and interregional connections. In our findings, these network characters were all disrupted in patients suffering from chronic migraine. More importantly, these functional damages in the migraine-affected brain had a skewed balance between males and females. In female patients, brain functional networks showed worse resilience, more regions exhibited decreased nodal centrality, and more functional connections revealed abnormalities than in male patients. CONCLUSIONS: These results indicated that migraine may have an additional influence on females and lead to more dysfunctional organization in their resting functional networks

Neuroimaging perspective in targeted treatment for type 2 diabetes melitus and sleep disorders

Type 2 diabetes mellitus (T2DM) and sleep disorders (SD) have become important and costly health issues worldwide, particularly in China. Both are common diseases related to brain functional and structural abnormalities involving the hypothalamic-pituitary-adrenal (HPA) axis. The brains of individuals who suffer from both diseases simultaneously might be different compared to healthy individuals. This review assessed current neuroimaging findings to develop alternative targeted treatments for T2DM and SD. Relevant articles published between January 2002 and September 2021 were searched in PubMed and Web of Science databases. Generalized treatment methods for T2DM include dietary/weight-loss management, metformin or a combination of two non-insulin drugs, and melatonin for SD, though alternative therapies including electroacupuncture (EA) have been utilized in treating both of these diseases separately because they are convenient, affordable, and safe. Standard and alternative treatments for T2DM were somehow effective in treating SD. Neuroimaging studies of these disorders can achieve higher treatment efficacy by targeting brain areas, such as the hypothalamus (HYP), as visualized via diffusion tensor imaging (DTI), and functional magnetic resonance imaging (fMRI). DTI and fMRI can map the human brain and are utilized in many experiments. Thus, we propose that neuroimaging studies could be used in treatment of SD in T2DM