Collagen mutation and age contribute to differential craniofacial phenotypes in mouse models of osteogenesis imperfecta.

Craniofacial and dentoalveolar abnormalities are present in all types of osteogenesis imperfecta (OI). Mouse models of the disorder are critical to understand these abnormalities and underlying OI pathogenesis. Previous studies on severely affected OI mice report a broad spectrum of craniofacial phenotypes, exhibiting some similarities to the human disorder. The Brtl/+ and G610c/+ are moderately severe and mild-type IV OI, respectively. Little is known about the aging effects on the craniofacial bones of these models and their homology to human OI. This study aimed to analyze the Brtl/+ and G610c/+ craniofacial morphometries during aging to establish suitability for further OI craniofacial bone intervention studies. We performed morphological measurements on the micro-CT-scanned heads of 3-wk-old, 3-mo-old, and 6-mo-old female Brtl/+ and G610c/+ mice. We observed that Brtl/+ skulls are shorter in length than WT (P < .05), whereas G610c/+ skulls are similar in length to their WT counterparts. The Brtl/+ mice exhibit alveolar bone with a porotic-like appearance that is not observed in G610c/+. As they age, Brtl/+ mice show severe bone resorption in both the maxilla and mandible (P < .05). By contrast, G610c/+ mice experience mandibular resorption consistently across all ages, but maxillary resorption is only evident at 6 mo (P < .05). Western blot shows high osteoclastic activities in the Brtl/+ maxilla. Both models exhibit delayed pre-functional eruptions of the third molars (P < .05), which are similar to those observed in some bisphosphonate-treated OI subjects. Our study shows that the Brtl/+ and G610c/+ mice display clear features found in type IV OI patients; both show age-related changes in the craniofacial growth phenotype. Therefore, understanding the craniofacial features of these models and how they age will allow us to select the most accurate mouse model, mouse age, and bone structure for the specific craniofacial bone treatment of differing OI groups.

Unlocking the link: how hippocampal glutathione-glutamate coupling predicts cognitive impairment in multiple sclerosis patients.

Cognitive impairment is a common symptom of multiple sclerosis and profoundly impacts quality of life. Glutathione (GSH) and glutamate (Glu) are tightly linked in the brain, participating in cognitive function. However, GSH-Glu couplings in cognitive brain regions and their relationship with cognitive impairment in relapsing-remitting multiple sclerosis (RRMS) remains unclear. Forty-one RRMS patients and 43 healthy controls underwent magnetic resonance spectroscopy to measure GSH and Glu levels in the posterior cingulate cortex, medial prefrontal cortex and left hippocampus. Neuropsychological tests were used to evaluate the cognitive function. The Glu/GSH ratio was used to indicate the coupling between GSH and Glu and was tested as a predictor of cognitive performance. The results show that RRMS patients exhibited reduced hippocampal GSH and Glu levels, which were found to be significant predictors of worse verbal and visuospatial memory, respectively. Moreover, GSH levels were dissociated from Glu levels in the left hippocampus of RRMS patients. Hippocampal Glu/GSH ratio is significantly correlated with processing speed and has a greater predictive effect. Here we show the hippocampal Glu/GSH ratio could serve as a new potential marker for characterizing cognitive impairment in RRMS, providing a new direction for clinical detection of cognitive impairment.

Abnormal white and gray matter functional connectivity is associated with cognitive dysfunction in presbycusis.

Presbycusis is characterized by high-frequency hearing loss and is closely associated with cognitive decline. Previous studies have observed functional reorganization of gray matter in presbycusis, but the information transmission between gray matter and white matter remains ill-defined. Using resting-state functional magnetic resonance imaging, we investigated differences in functional connectivity (GM-GM, WM-WM, and GM-WM) between 60 patients with presbycusis and 57 healthy controls. Subsequently, we examined the correlation between these connectivity differences with high-frequency hearing loss as well as cognitive impairment. Our results revealed significant alterations in functional connectivity involving the body of the corpus callosum, posterior limbs of the internal capsule, retrolenticular region of the internal capsule, and the gray matter regions in presbycusis. Notably, disrupted functional connectivity was observed between the body of the corpus callosum and ventral anterior cingulate cortex in presbycusis, which was associated with impaired attention. Additionally, enhanced functional connectivity was found in presbycusis between the internal capsule and the ventral auditory processing stream, which was related to impaired cognition in multiple domains. These two patterns of altered functional connectivity between gray matter and white matter may involve both bottom-up and top-down regulation of cognitive function. These findings provide novel insights into understanding cognitive compensation and resource redistribution mechanisms in presbycusis.

Mutation Rate and Spectrum of the Silkworm in Normal and Temperature Stress Conditions.

Mutation rate is a crucial parameter in evolutionary genetics. However, the mutation rate of most species as well as the extent to which the environment can alter the genome of multicellular organisms remain poorly understood. Here, we used parents-progeny sequencing to investigate the mutation rate and spectrum of the domestic silkworm (Bombyx mori) among normal and two temperature stress conditions (32 °C and 0 °C). The rate of single-nucleotide mutations in the normal temperature rearing condition was 0.41 × 10-8 (95% confidence interval, 0.33 × 10-8-0.49 × 10-8) per site per generation, which was up to 1.5-fold higher than in four previously studied insects. Moreover, the mutation rates of the silkworm under the stresses are significantly higher than in normal conditions. Furthermore, the mutation rate varies less in gene regions under normal and temperature stresses. Together, these findings expand the known diversity of the mutation rate among eukaryotes but also have implications for evolutionary analysis that assumes a constant mutation rate among species and environments.

Neurochemical and functional reorganization of the cognitive-ear link underlies cognitive impairment in presbycusis.

Recent studies suggest that the interaction between presbycusis and cognitive impairment may be partially explained by the cognitive-ear link. However, the underlying neurophysiological mechanisms remain largely unknown. In this study, we combined magnetic resonance spectroscopy (MRS) and resting-state functional magnetic resonance imaging (fMRI) to investigate auditory gamma-aminobutyric acid (GABA) and glutamate (Glu) levels, intra- and inter-network functional connectivity, and their relationships with auditory and cognitive function in 51 presbycusis patients and 51 well-matched healthy controls. Our results confirmed reorganization of the cognitive-ear link in presbycusis, including decreased auditory GABA and Glu levels and aberrant functional connectivity involving auditory networks (AN) and cognitive-related networks, which were associated with reduced speech perception or cognitive impairment. Moreover, mediation analyses revealed that decreased auditory GABA levels and dysconnectivity between the AN and default mode network (DMN) mediated the association between hearing loss and impaired information processing speed in presbycusis. These findings highlight the importance of AN-DMN dysconnectivity in cognitive-ear link reorganization leading to cognitive impairment, and hearing loss may drive reorganization via decreased auditory GABA levels. Modulation of GABA neurotransmission may lead to new treatment strategies for cognitive impairment in presbycusis patients.

Classification of Alzheimer's Disease Based on Deep Learning of Brain Structural and Metabolic Data.

To improve the diagnosis and classification of Alzheimer's disease (AD), a modeling method is proposed based on the combining magnetic resonance images (MRI) brain structural data with metabolite levels of the frontal and parietal regions. First, multi-atlas brain segmentation technology based on T1-weighted images and edited magnetic resonance spectroscopy (MRS) were used to extract data of 279 brain regions and levels of 12 metabolites from regions of interest (ROIs) in the frontal and parietal regions. The t-test combined with false discovery rate (FDR) correction was used to reduce the dimensionality in the data, and MRI structural data of 54 brain regions and levels of 4 metabolites that obviously correlated with AD were screened out. Lastly, the stacked auto-encoder neural network (SAE) was used to classify AD and healthy controls (HCs), which judged the effect of classification method by fivefold cross validation. The results indicated that the mean accuracy of the five experimental model increased from 96 to 100%, the AUC value increased from 0.97 to 1, specificity increased from 90 to 100%, and F1 value increased from 0.97 to 1. Comparing the effect of each metabolite on model performance revealed that the gamma-aminobutyric acid (GABA) + levels in the parietal region resulted in the most significant improvement in model performance, with the accuracy rate increasing from 96 to 98%, the AUC value increased from 0.97 to 0.99 and the specificity increasing from 90 to 95%. Moreover, the GABA + levels in the parietal region was significantly correlated with Mini Mental State Examination (MMSE) scores of patients with AD (r = 0.627), and the F statistics were largest (F = 25.538), which supports the hypothesis that dysfunctional GABAergic system play an important role in the pathogenesis of AD. Overall, our findings support that a comprehensive method that combines MRI structural and metabolic data of brain regions can improve model classification efficiency of AD.

The Landscapes of Full-Length Transcripts and Splice Isoforms as Well as Transposons Exonization in the Lepidopteran Model System, Bombyx mori.

The domesticated silkworm, Bombyx mori, is an important model system for the order Lepidoptera. Currently, based on third-generation sequencing, the chromosome-level genome of Bombyx mori has been released. However, its transcripts were mainly assembled by using short reads of second-generation sequencing and expressed sequence tags which cannot explain the transcript profile accurately. Here, we used PacBio Iso-Seq technology to investigate the transcripts from 45 developmental stages of Bombyx mori. We obtained 25,970 non-redundant high-quality consensus isoforms capturing ∼60% of previous reported RNAs, 15,431 (∼47%) novel transcripts, and identified 7,253 long non-coding RNA (lncRNA) with a large proportion of novel lncRNA (∼56%). In addition, we found that transposable elements (TEs) exonization account for 11,671 (∼45%) transcripts including 5,980 protein-coding transcripts (∼32%) and 5,691 lncRNAs (∼79%). Overall, our results expand the silkworm transcripts and have general implications to understand the interaction between TEs and their host genes. These transcripts resource will promote functional studies of genes and lncRNAs as well as TEs in the silkworm.