Effects of Helicobacter pylori and Moluodan on the Wnt/ß-catenin signaling pathway in mice with precancerous gastric cancer lesions.

BACKGROUND: Helicobacter pylori (H. pylori) is the primary risk factor for gastric cancer (GC), the Wnt/ß-Catenin signaling pathway is closely linked to tumourigenesis. GC has a high mortality rate and treatment cost, and there are no drugs to prevent the progression of gastric precancerous lesions to GC. Therefore, it is necessary to find a novel drug that is inexpensive and preventive to against GC. AIM: To explore the effects of H. pylori and Moluodan on the Wnt/ß-Catenin signaling pathway and precancerous lesions of GC (PLGC). METHODS: Mice were divided into the control, N-methyl-N-nitrosourea (MNU), H. pylori + MNU, and Moluodan groups. We first created an H. pylori infection model in the H. pylori + MNU and Moluodan groups. A PLGC model was created in the remaining three groups except for the control group. Moluodan was fed to mice in the Moloudan group ad libitum. The general condition of mice were observed during the whole experiment period. Gastric tissues of mice were grossly and microscopically examined. Through quantitative real-time PCR (qRT-PCR) and Western blotting analysis, the expression of relevant genes were detected. RESULTS: Mice in the H. pylori + MNU group showed the worst performance in general condition, gastric tissue visual and microscopic observation, followed by the MNU group, Moluodan group and the control group. QRT-PCR and Western blotting analysis were used to detect the expression of relevant genes, the results showed that the H. pylori + MNU group had the highest expression, followed by the MNU group, Moluodan group and the control group. CONCLUSION: H. pylori can activate the Wnt/ß-catenin signaling pathway, thereby facilitating the development and progression of PLGC. Moluodan suppressed the activation of the Wnt/ß-catenin signaling pathway, thereby decreasing the progression of PLGC.

Neuronal population activity in the olivocerebellum encodes the frequency of essential tremor in mice and patients.

Essential tremor (ET) is the most prevalent movement disorder, characterized primarily by action tremor, an involuntary rhythmic movement with a specific frequency. However, the neuronal mechanism underlying the coding of tremor frequency remains unexplored. Here, we used in vivo electrophysiology, optogenetics, and simultaneous motion tracking in the Grid2dupE3 mouse model to investigate whether and how neuronal activity in the olivocerebellum determines the frequency of essential tremor. We report that tremor frequency was encoded by the temporal coherence of population neuronal firing within the olivocerebellums of these mice, leading to frequency-dependent cerebellar oscillations and tremors. This mechanism was precise and generalizable, enabling us to use optogenetic stimulation of the deep cerebellar nuclei to induce frequency-specific tremors in wild-type mice or alter tremor frequencies in tremor mice. In patients with ET, we showed that deep brain stimulation of the thalamus suppressed tremor symptoms but did not eliminate cerebellar oscillations measured by electroencephalgraphy, indicating that tremor-related oscillations in the cerebellum do not require the reciprocal interactions with the thalamus. Frequency-disrupting transcranial alternating current stimulation of the cerebellum could suppress tremor amplitudes, confirming the frequency modulatory role of the cerebellum in patients with ET. These findings offer a neurodynamic basis for the frequency-dependent stimulation of the cerebellum to treat essential tremor.

The cerebellum computes frequency dynamics for motions with numerical precision and cross-individual uniformity.

Cross-individual variability is considered the essence of biology, preventing precise mathematical descriptions of biological motion like the physics law of motion. Here we report that the cerebellum shapes motor kinematics by encoding dynamic motor frequencies with remarkable numerical precision and cross-individual uniformity. Using in-vivo electrophysiology and optogenetics in mice, we confirmed that deep cerebellar neurons encoded frequencies via populational tuning of neuronal firing probabilities, creating cerebellar oscillations and motions with matched frequencies. The mechanism was consistently presented in self-generated rhythmic and non-rhythmic motions triggered by a vibrational platform, or skilled tongue movements of licking in all tested mice with cross-individual uniformity. The precision and uniformity allowed us to engineer complex motor kinematics with designed frequencies. We further validated the frequency-coding function of the human cerebellum using cerebellar electroencephalography recordings and alternating-current stimulation during voluntary tapping tasks. Our findings reveal a cerebellar algorithm for motor kinematics with precision and uniformity, the mathematical foundation for brain-computer interface for motor control.