Towards Understanding: The Study of Hughes\u27 Poetry as the Epitome of the Expressive, Cultural, and Political Elements of African American Literature

Unfortunately, a disconnection currently exists between the academic world and the sweet, soulful study of African American literature (AA literature). Because there is limited exposure to AA literature in academics, except for specialized courses in which it serves as the intended focus, most people do not know how to approach it as serious academic study because of its stark differences from Western literature. In sum: African American writers often do not utilize Standard English (SE), so their work is misinterpreted as non-academic in comparison to other Western works of prominence; AA literature tells a different cultural story that most of America does not identify; and the literature often serves as a political platform that authors use to inform the public of their plight. More often than not, the expressive, cultural, and political elements of AA literature are not simultaneously considered in critical analysis of the literature, which leads one to misinterpret it. Expressive, cultural, and political elements are clearly present in African American works, and their study is a vital part of understanding AA literature. Take, for instance, Henry Louis Gates, Jr., who advocates using African derived interpretive tools to dissect AA literature and, consequently, shifts the focus to the African American expressive, cultural, and political aspects. And Terry Eagleton, a renowned literary critic, also argues in After Theory that the political nature or cultural elements of a work cannot be separated from it (23). Nor can the language people use be separated form the literature they produce. John and Russell Rickford, authors of Spoken Soul, note that some people wrongly assume that [African American Language (AAL)] has no dictionary, no textbooks, no grammar, no rules. It is rebellious and outside rule-based language (91). Suggestively, then, one not only has to study the African American expression and language to better understand the literature, but he also has to accept the language as valid as well. But because the expressive elements are at variance from mainstream literature, mainstream literary critics have a difficult time considering AA literature candidates for serious linguistic study

Apriori prediction of chemotherapy response in locally advanced breast cancer patients using CT imaging and deep learning: transformer versus transfer learning

ObjectiveNeoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response to NAC for patients with Locally Advanced Breast Cancer (LABC) before treatment initiation could be beneficial to optimize therapy, ensuring the administration of effective treatments. The objective of the work here was to develop a predictive model to predict tumor response to NAC for LABC using deep learning networks and computed tomography (CT).Materials and methodsSeveral deep learning approaches were investigated including ViT transformer and VGG16, VGG19, ResNet-50, Res-Net-101, Res-Net-152, InceptionV3 and Xception transfer learning networks. These deep learning networks were applied on CT images to assess the response to NAC. Performance was evaluated based on balanced_accuracy, accuracy, sensitivity and specificity classification metrics. A ViT transformer was applied to utilize the attention mechanism in order to increase the weight of important part image which leads to better discrimination between classes.ResultsAmongst the 117 LABC patients studied, 82 (70%) had clinical-pathological response and 35 (30%) had no response to NAC. The ViT transformer obtained the best performance range (accuracy = 71 ± 3% to accuracy = 77 ± 4%, specificity = 86 ± 6% to specificity = 76 ± 3%, sensitivity = 56 ± 4% to sensitivity = 52 ± 4%, and balanced_accuracy=69 ± 3% to balanced_accuracy=69 ± 3%) depending on the split ratio of train-data and test-data. Xception network obtained the second best results (accuracy = 72 ± 4% to accuracy = 65 ± 4, specificity = 81 ± 6% to specificity = 73 ± 3%, sensitivity = 55 ± 4% to sensitivity = 52 ± 5%, and balanced_accuracy = 66 ± 5% to balanced_accuracy = 60 ± 4%). The worst results were obtained using VGG-16 transfer learning network.ConclusionDeep learning networks in conjunction with CT imaging are able to predict the tumor response to NAC for patients with LABC prior to start. A ViT transformer could obtain the best performance, which demonstrated the importance of attention mechanism

Activation and desensitization of the olfactory cAMP-gated transduction channel: identification of functional modules

Olfactory receptor neurons respond to odor stimulation with a receptor potential that results from the successive activation of cyclic AMP (cAMP)-gated, Ca2+-permeable channels and Ca2+-activated chloride channels. The cAMP-gated channels open at micromolar concentrations of their ligand and are subject to a Ca2+-dependent feedback inhibition by calmodulin. Attempts to understand the operation of these channels have been hampered by the fact that the channel protein is composed of three different subunits, CNGA2, CNGA4, and CNGB1b. Here, we explore the individual role that each subunit plays in the gating process. Using site-directed mutagenesis and patch clamp analysis, we identify three functional modules that govern channel operation: a module that opens the channel, a module that stabilizes the open state at low cAMP concentrations, and a module that mediates rapid Ca2+-dependent feedback inhibition. Each subunit could be assigned to one of these functions that, together, define the gating logic of the olfactory transduction channel

Vascular and blood-brain barrier-related changes underlie stress responses and resilience in female mice and depression in human tissue

Prevalence, symptoms, and treatment of depression suggest that major depressive disorders (MDD) present sex differences. Social stress-induced neurovascular pathology is associated with depressive symptoms in male mice; however, this association is unclear in females. Here, we report that chronic social and subchronic variable stress promotes blood-brain barrier (BBB) alterations in mood-related brain regions of female mice. Targeted disruption of the BBB in the female prefrontal cortex (PFC) induces anxiety- and depression-like behaviours. By comparing the endothelium cell-specific transcriptomic profiling of the mouse male and female PFC, we identify several pathways and genes involved in maladaptive stress responses and resilience to stress. Furthermore, we confirm that the BBB in the PFC of stressed female mice is leaky. Then, we identify circulating vascular biomarkers of chronic stress, such as soluble E-selectin. Similar changes in circulating soluble E-selectin, BBB gene expression and morphology can be found in blood serum and postmortem brain samples from women diagnosed with MDD. Altogether, we propose that BBB dysfunction plays an important role in modulating stress responses in female mice and possibly MDD

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM