A behavioral mechanistic investigation of the role of 5-HT\u3csub\u3e1A\u3c/sub\u3e receptors in the mediation of rat maternal behavior

Previous work suggests that 5-HT1A receptors play a special role in rodent maternal aggression, but not in other aspects of maternal care (e.g. pup retrieval and nest building). The present study re-assessed the basic effects of 5-HT1A activation or blockade on various maternal responses in postpartum female rats. We also examined the possible behavioral mechanisms underlying the maternal effects of 5-HT1A. Sprague–Dawley mother rats were injected with a 5-HT1A agonist 8-OH-DPAT (0.1, 0.5 or 1.0 mg/kg, sc), a 5-HT1A antagonist WAY-101405 (0.1, 0.5 or 1.0 mg/kg, sc) or 0.9% saline solution on postpartum days 3, 5, and 7. Maternal behavior was tested 30 min before, 30 min, 120 min, and 240 min after the injection. Acute and repeated 8-OH-DPAT treatment significantly disrupted pup retrieval, pup licking, nursing, and nest building in a dose-dependent fashion, whereas WAY-101405 had no effect at the tested doses. The 5-HT1A receptor specificity of 8-OH-DPAT\u27s action was confirmed as its maternal disruption effect was reversed by pretreatment of WAY-100635 (a highly selective 5-HT1A receptor antagonist). Subsequent pup preference test found that 8-OH-DPAT did not decrease the pup preference over a novel object, thus no inhibition on maternal motivation or maternal affect. The pup separation test and pup retrieval on an elevated plus maze test also failed to find any motivational and motor impairment effect with 8-OH-DPAT. However, 8-OH-DPAT at the maternal disruptive dose did disrupt the prepulse inhibition (a measure of attentional function) of acoustic startle response and enhanced the basal startle response. These findings suggest that stimulation of 5-HT1A receptors by 8-OH-DPAT impairs maternal care by partially interfering with the attentional processing or basal anxiety. More work is needed to further delineate the psychological and neuronal mechanisms underlying the maternal disruptive effect of 5-HT1A receptor activation

Transplantation of Pro-Oligodendroblasts, Preconditioned by LPS-Stimulated Microglia, Promotes Recovery After Acute Contusive Spinal Cord Injury

Spinal cord injury (SCI) is a significant clinical challenge, and to date no effective treatment is available. Oligodendrocyte progenitor cell (OPC) transplantation has been a promising strategy for SCI repair. However, the poor posttransplantation survival and deficiency in differentiation into myelinating oligodendrocytes (OLs) are two major challenges that limit the use of OPCs as donor cells. Here we report the generation of an OL lineage population [i.e., pro-oligodendroblasts (proOLs)] that is relatively more mature than OPCs for transplantation after SCI. We found that proOLs responded to lipopolysaccharide (LPS)-stimulated microglia conditioned medium (L+M) by preserving toll-like receptor 4 (TLR4) expression, improving cell viability, and enhancing the expression of a myelinating OL marker myelin basic protein (MBP), compared to other OL lineage cells exposed to either LPS-stimulated (L+M) or nonstimulated microglia conditioned medium (L−M). When L+M-stimulated proOLs were intrathecally delivered through a lumbar puncture after a T10 thoracic contusive SCI, they promoted behavioral recovery, as assessed by the Basso‐Beattie‐Bresnahan (BBB) locomotor rating scale, stride length, and slips on the grid tests. Histologically, transplantation of L+M proOLs caused a considerable increase in intralesional axon numbers and myelination, and less accumulation of invading macrophages when compared with the vehicle control or OPC transplantation. Thus, transplantation of proOLs, preconditioned by L+M, may offer a better therapeutic potential for SCI than OPCs since the former may have initiated the differentiation process toward OLs prior to transplantation

TfR1 binding with H-ferritin nanocarrier achieves prognostic diagnosis and enhances the therapeutic efficacy in clinical gastric cancer

H-ferritin (HFn) nanocarrier is emerging as a promising theranostic platform for tumor diagnosis and therapy, which can specifically target tumor cells via binding transferrin receptor 1 (TfR1). This led us to investigate the therapeutic function of TfR1 in GC. The clinical significance of TfR1 was assessed in 178 GC tissues by using a magneto-HFn nanoparticle-based immunohistochemistry method. The therapeutic effects of doxorubicin-loaded HFn nanocarriers (HFn-Dox) were evaluated on TfR1-positive GC patient-derived xenograft (GC-PDX) models. The biological function of TfR1 was investigated through in vitro and in vivo assays. TfR1 was upregulated (73.03%) in GC tissues, and reversely correlated with patient outcome. TfR1-negative sorted cells exhibited tumor-initiating features, which enhanced tumor formation and migration/invasion, whereas TfR1-positive sorted cells showed significant proliferation ability. Knockout of TfR1 in GC cells also enhanced cell invasion. TfR1-deficient cells displayed immune escape by upregulating PD-L1, CXCL9, and CXCL10, when disposed with IFN-γ. Western blot results demonstrated that TfR1-knockout GC cells upregulated Akt and STAT3 signaling. Moreover, in TfR1-positive GC-PDX models, the HFn-Dox group significantly inhibited tumor growth, and increased mouse survival, compared with that of free-Dox group. TfR1 could be a potential prognostic and therapeutic biomarker for GC: (i) TfR1 reversely correlated with patient outcome, and its negative cells possessed tumor-aggressive features; (ii) TfR1-positive cells can be killed by HFn drug nanocarrier. Given the heterogeneity of GC, HFn drug nanocarrier combined with other therapies toward TfR1-negative cells (such as small molecules or immunotherapy) will be a new option for GC treatment

Deep Learning of Dark Energy Spectroscopic Instrument Mock Spectra to Find Damped Ly alpha Systems

We have updated and applied a convolutional neural network (CNN) machine-learning model to discover and characterize damped Lyα systems (DLAs) based on Dark Energy Spectroscopic Instrument (DESI) mock spectra. We have optimized the training process and constructed a CNN model that yields a DLA classification accuracy above 99% for spectra that have signal-to-noise ratios (S/N) above 5 per pixel. The classification accuracy is the rate of correct classifications. This accuracy remains above 97% for lower S/N ≈1 spectra. This CNN model provides estimations for redshift and H i column density with standard deviations of 0.002 and 0.17 dex for spectra with S/N above 3 pixel-1. Also, this DLA finder is able to identify overlapping DLAs and sub-DLAs. Further, the impact of different DLA catalogs on the measurement of baryon acoustic oscillations (BAO) is investigated. The cosmological fitting parameter result for BAO has less than 0.61% difference compared to analysis of the mock results with perfect knowledge of DLAs. This difference is lower than the statistical error for the first year estimated from the mock spectra: above 1.7%. We also compared the performances of the CNN and Gaussian Process (GP) models. Our improved CNN model has moderately 14% higher purity and 7% higher completeness than an older version of the GP code, for S/N > 3. Both codes provide good DLA redshift estimates, but the GP produces a better column density estimate by 24% less standard deviation. A credible DLA catalog for the DESI main survey can be provided by combining these two algorithms