Functional consequences of postnatal interventions in a mouse model of Fragile X syndrome.

BACKGROUND: Fragile X syndrome (FXS) is a leading genetic cause of autism and intellectual disability with cortical hyperexcitability and sensory hypersensitivity attributed to loss and hypofunction of inhibitory parvalbumin-expressing (PV) cells. Our studies provide novel insights into the role of excitatory neurons in abnormal development of PV cells during a postnatal period of inhibitory circuit refinement. METHODS: To achieve Fragile X mental retardation gene (Fmr1) deletion and re-expression in excitatory neurons during the postnatal day (P)14-P21 period, we generated CreCaMKIIa/Fmr1Flox/y (cOFF) and CreCaMKIIa/Fmr1FloxNeo/y (cON) mice, respectively. Cortical phenotypes were evaluated in adult mice using biochemical, cellular, clinically relevant electroencephalogram (EEG) and behavioral tests. RESULTS: We found that similar to global Fmr1 KO mice, the density of PV-expressing cells, their activation, and sound-evoked gamma synchronization were impaired in cOFF mice, but the phenotypes were improved in cON mice. cOFF mice also showed enhanced cortical gelatinase activity and baseline EEG gamma power, which were reduced in cON mice. In addition, TrkB phosphorylation and PV levels were lower in cOFF mice, which also showed increased locomotor activity and anxiety-like behaviors. Remarkably, when FMRP levels were restored in only excitatory neurons during the P14-P21 period, TrkB phosphorylation and mouse behaviors were also improved. CONCLUSIONS: These results indicate that postnatal deletion or re-expression of FMRP in excitatory neurons is sufficient to elicit or ameliorate structural and functional cortical deficits, and abnormal behaviors in mice, informing future studies about appropriate treatment windows and providing fundamental insights into the cellular mechanisms of cortical circuit dysfunction in FXS.

Locus coeruleus volume and cell population changes during Alzheimer's disease progression: A stereological study in human postmortem brains with potential implication for early-stage biomarker discovery.

INTRODUCTION: Alzheimer's disease (AD) progression follows a specific spreading pattern, emphasizing the need to characterize those brain areas that degenerate first. The brainstem's locus coeruleus (LC) is the first area to develop neurofibrillary changes (neurofibrillary tangles [NFTs]). METHODS: The methods include unbiased stereological analyses in human brainstems to estimate LC volume and neuronal population in controls and individuals across all AD stages. RESULTS: As the Braak stage increases by 1 unit, the LC volume decreases by 8.4%. Neuronal loss started only midway through AD progression. Age-related changes spare the LC. DISCUSSION: The long gap between NFT accumulation and neuronal loss suggests that a second trigger may be necessary to induce neuronal death in AD. Imaging studies should determine whether LC volumetry can replicate the stage-wise atrophy observed here and how these changes are specific to AD. LC volumetry may develop into a screening biomarker for selecting high-yield candidates to undergo expensive and less accessible positron emission tomography scans and to monitor AD progression from presymptomatic stages.

Systems-Involved Transgender and Gender-Diverse Youth: Homelessness, Juvenile Legal Systems, and Child Welfare and Foster Care.

Transgender and gender-diverse (TGD) youth are overrepresented in legal and social support systems intended to protect and support youth along their developmental journeys. However, these systems often fall short for TGD youth and further stigmatize an already vulnerable population. This article provides an overview of the experience, care, and treatment of systems-involved TGD youth. Working with systems-involved transgender and gender-diverse youth necessitates a high level of compassion and advocacy in pursuit of more equitable care and access.

Cellular transplantation and platelet-rich plasma injections for discogenic pain: a contemporary review.

Degenerative disc disease (DDD) is the leading cause of chronic back pain. It is a pathologic condition associated with aging and is believed to result from catabolic excess in the intervertebral discs' (IVD) extracellular matrix. Two new treatment options are intradiscal cellular transplantation and growth factor therapy. Recent investigations on the use of these therapies are discussed and compared with emerging evidence supporting novel cellular injections. At present, human and animal studies provide a compelling rationale for the use of cellular injections in the treatment of discogenic pain. Since DDD results from the IVD extracellular matrix's unmitigated catabolism, cellular injections are used to induce regeneration and homeostasis in the IVD. Here, we review intervertebral disc anatomy, DDD pathophysiology and clinical considerations, as well as the current and emerging literature investigating outcomes associated with cellular transplantation and platelet-rich plasma for discogenic pain. Further high-quality trials are certainly warranted.

Probing the correlation of neuronal loss, neurofibrillary tangles, and cell death markers across the Alzheimer's disease Braak stages: a quantitative study in humans.

Clarifying the mechanisms connecting neurofibrillary tangle (NFT) neurotoxicity to neuronal dysfunction in humans is likely to be pivotal for developing effective treatments for Alzheimer's disease (AD). To model the temporal progression of AD in humans, we used a collection of brains with controls and individuals from each Braak stage to quantitatively investigate the correlation between intraneuronal caspase activation or macroautophagy markers, NFT burden, and neuronal loss, in the dorsal raphe nucleus and locus coeruleus, the earliest vulnerable areas to NFT accumulation. We fit linear regressions with each count as outcomes, with Braak score and age as the predictors. In progressive Braak stages, intraneuronal active caspase-6 positivity increases both alone and overlapping with NFTs. Likewise, the proportion of NFT-bearing neurons showing autophagosomes increases. Overall, caspases may be involved in upstream cascades in AD and are associated with higher NFTs. Macroautophagy changes correlate with increasing NFT burden from early AD stages.

Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding.

BACKGROUND: Immunofluorescence (IF) plays a major role in quantifying protein expression in situ and understanding cell function. It is widely applied in assessing disease mechanisms and in drug discovery research. Automation of IF analysis can transform studies using experimental cell models. However, IF analysis of postmortem human tissue relies mostly on manual interaction, often subjected to low-throughput and prone to error, leading to low inter and intra-observer reproducibility. Human postmortem brain samples challenges neuroscientists because of the high level of autofluorescence caused by accumulation of lipofuscin pigment during aging, hindering systematic analyses. We propose a method for automating cell counting and classification in IF microscopy of human postmortem brains. Our algorithm speeds up the quantification task while improving reproducibility. NEW METHOD: Dictionary learning and sparse coding allow for constructing improved cell representations using IF images. These models are input for detection and segmentation methods. Classification occurs by means of color distances between cells and a learned set. RESULTS: Our method successfully detected and classified cells in 49 human brain images. We evaluated our results regarding true positive, false positive, false negative, precision, recall, false positive rate and F1 score metrics. We also measured user-experience and time saved compared to manual countings. COMPARISON WITH EXISTING METHODS: We compared our results to four open-access IF-based cell-counting tools available in the literature. Our method showed improved accuracy for all data samples. CONCLUSION: The proposed method satisfactorily detects and classifies cells from human postmortem brain IF images, with potential to be generalized for applications in other counting tasks.