Cordyceps militaris (CM) and its active ingredient cordycepin have been reported to inhibit tumor growth, but the mechanisms are not fully understood. This study used a mouse model for oral cancer and a cell line, 4NAOC-1 derived from the model to study the mechanisms. Our results show that a CM preparation (CMP) can significantly inhibit tumor development and malignant transformation in the model. In vitro data indicate that CMP and cordycepin can inhibit 4NAOC-1 cell proliferation, either anchorage-dependent or -independent. Cordycepin can also increase cell apoptosis, and decrease cell mitosis and EGFR signaling. In accordance, CMP treatment can significantly decrease the levels of ki-67 and EGFR signaling molecules in cancer tissues. We also found that the levels of IL-17A in cancer tissues of control mice were significantly increased, and CMP inhibited these levels. IL-17A can stimulate cancer cell proliferation, which can be suppressed by cordycepin. Furthermore, cordycepin can reduce the expression of IL-17RA and its downstream signaling molecules. Moreover, CMP and cordycepin can significantly decrease IL-17A production in vitro and in vivo. Finally, CMP and its ingredients can enhance tumoricidal activities with increase in IFN-γ and TNFα, and decrease PD-L1 expression. In conclusion, CMP and its ingredient cordycepin can inhibit tumor growth and malignant transformation in a mouse model for oral cancer via inhibition of EGFR- and IL-17RA-signaling and enhancement of anti-tumor immunity.
Introduction
The semantic network is an important mediator of language, enabling both speech production and the comprehension of multimodal stimuli. A major challenge in the field of neurosurgery is preventing semantic deficits. Multiple cortical areas have been linked to semantic processing, though knowledge of network connectivity has lacked anatomic specificity. Using attentional task‐based fMRI studies, we built a neuroanatomical model of this network.
Methods
One hundred and fifty‐five task‐based fMRI studies related to categorization of visual words and objects, and auditory words and stories were used to generate an activation likelihood estimation (ALE). Cortical parcellations overlapping the ALE were used to construct a preliminary model of the semantic network based on the cortical parcellation scheme previously published under the Human Connectome Project. Deterministic fiber tractography was performed on 25 randomly chosen subjects from the Human Connectome Project, to determine the connectivity of the cortical parcellations comprising the network.
Results
The ALE analysis demonstrated fourteen left hemisphere cortical regions to be a part of the semantic network: 44, 45, 55b, IFJa, 8C, p32pr, SFL, SCEF, 8BM, STSdp, STSvp, TE1p, PHT, and PBelt. These regions showed consistent interconnections between parcellations. Notably, the anterior temporal pole, a region often implicated in semantic function, was absent from our model.
Conclusions
We describe a preliminary cortical model for the underlying structural connectivity of the semantic network. Future studies will further characterize the neurotractographic details of the semantic network in the context of medical application.
Background
The default mode network (DMN) is an important mediator of passive states of mind. Multiple cortical areas, such as the anterior cingulate cortex, posterior cingulate cortex, and lateral parietal lobe, have been linked in this processing, though knowledge of network connectivity had limited tractographic specificity.
Methods
Using resting‐state fMRI studies related to the DMN, we generated an activation likelihood estimation (ALE). We built a tractographical model of this network based on the cortical parcellation scheme previously published under the Human Connectome Project. DSI‐based fiber tractography was performed to determine the structural connections between cortical parcellations comprising the network.
Results
Seventeen cortical regions were found to be part of the DMN: 10r, 31a, 31pd, 31pv, a24, d23ab, IP1, p32, POS1, POS2, RSC, PFm, PGi, PGs, s32, TPOJ3, and v23ab. These regions showed consistent interconnections between adjacent parcellations, and the cingulum was found to connect the anterior and posterior cingulate clusters within the network.
Conclusions
We present a preliminary anatomic model of the default mode network. Further studies may refine this model with the ultimate goal of clinical application.
BACKGROUND
The superior parietal lobule (SPL) is involved in somatosensory and visuospatial integration with additional roles in attention, written language, and working memory. A detailed understanding of the exact location and nature of associated white matter tracts could improve surgical decisions and subsequent postoperative morbidity related to surgery in and around this gyrus.
OBJECTIVE
To characterize the fiber tracts of the SPL based on relationships to other well-known neuroanatomic structures through diffusion spectrum imaging (DSI)-based fiber tracking validated by gross anatomical dissection as ground truth.
METHODS
Neuroimaging data of 10 healthy, adult control subjects was obtained from a publicly accessible database published in Human Connectome Project for subsequent tractographic analyses. White matter tracts were mapped between both cerebral hemispheres, and a lateralization index was calculated based on resultant tract volumes. Post-mortem dissections of 10 cadavers identified the location of major tracts and validated our tractography results based on qualitative visual agreement.
RESULTS
We identified 9 major connections of the SPL: U-fiber, superior longitudinal fasciculus, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, middle longitudinal fasciculus, extreme capsule, vertical occipital fasciculus, cingulum, and corpus callosum. There was no significant fiber lateralization detected.
CONCLUSION
The SPL is an important region implicated in a variety of tasks involving visuomotor and visuospatial integration. Improved understanding of the fiber bundle anatomy elucidated in this study can provide invaluable information for surgical treatment decisions related to this region.
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