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Background Accurate and robust pathological image analysis for colorectal cancer (CRC) diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients’ treatment. The current heavy workload of pathologists in clinics/hospitals may easily lead to unconscious misdiagnosis of CRC based on daily image analyses. Methods Based on a state-of-the-art transfer-learned deep convolutional neural network in artificial intelligence (AI), we proposed a novel patch aggregation strategy for clinic CRC diagnosis using weakly labeled pathological whole-slide image (WSI) patches. This approach was trained and validated using an unprecedented and enormously large number of 170,099 patches, > 14,680 WSIs, from > 9631 subjects that covered diverse and representative clinical cases from multi-independent-sources across China, the USA, and Germany. Results Our innovative AI tool consistently and nearly perfectly agreed with (average Kappa statistic 0.896) and even often better than most of the experienced expert pathologists when tested in diagnosing CRC WSIs from multicenters. The average area under the receiver operating characteristics curve (AUC) of AI was greater than that of the pathologists (0.988 vs 0.970) and achieved the best performance among the application of other AI methods to CRC diagnosis. Our AI-generated heatmap highlights the image regions of cancer tissue/cells. Conclusions This first-ever generalizable AI system can handle large amounts of WSIs consistently and robustly without potential bias due to fatigue commonly experienced by clinical pathologists. It will drastically alleviate the heavy clinical burden of daily pathology diagnosis and improve the treatment for CRC patients. This tool is generalizable to other cancer diagnosis based on image recognition.

Cleft lip and palate are common birth defects resulting from failure of the facial processes to fuse during development. The mammalian grainyhead-like (Grhl1-3) genes play key roles in a number of tissue fusion processes including neurulation, epidermal wound healing and eyelid fusion. One family member, Grhl2, is expressed in the epithelial lining of the first pharyngeal arch in mice at embryonic day (E)10.5, prompting analysis of the role of this factor in palatogenesis. Grhl2null mice die at E11.5 with neural tube defects and a cleft face phenotype, precluding analysis of palatal fusion at a later stage of development. However, in the first pharyngeal arch of Grhl2-null embryos, dysregulation of transcription factors that drive epithelialmesenchymal transition (EMT) occurs. The aberrant expression of these genes is associated with a shift in RNA-splicing patterns that favours the generation of mesenchymal isoforms of numerous regulators. Driving the EMT perturbation is loss of expression of the EMT-suppressing transcription factors Ovol1 and Ovol2, which are direct GRHL2 targets. The expression of the miR-200 family of microRNAs, also GRHL2 targets, is similarly reduced, resulting in a 56-fold upregulation of Zeb1 expression, a major driver of mesenchymal cellular identity. The critical role of GRHL2 in mediating cleft palate in Zeb1 −/− mice is evident, with rescue of both palatal and facial fusion seen in Grhl2 −/− ;Zeb1 −/− embryos. These findings highlight the delicate balance between GRHL2/ZEB1 and epithelial/mesenchymal cellular identity that is essential for normal closure of the palate and face. Perturbation of this pathway may underlie cleft palate in some patients.

Background The ketogenic diet (KD) has been recognized as a potentially effective therapy to treat neuropsychiatric diseases, including epilepsy. Previous studies have indicated that KD treatment elevates γ-Amino butyric acid (GABA) levels in both human and murine brains, which presumably contributes to the KD’s anti-seizure effects. However, this has not been systematically investigated at the synaptic level, and the underlying molecular mechanisms remain to be elucidated. Methods Kainic acid (KA)-induced acute and chronic seizure models were utilized to examine the effects of KD treatment on seizure threshold and epileptogenesis. Synaptic activities in the hippocampus were recorded with the technique of electrophysiology. The effects of the KD on Neuregulin 1 (Nrg1) expression were assessed via RNA sequencing, real-time PCR and Western blotting. The obligatory role of Nrg1 in KD’s effects on seizures was evaluated through disruption of Nrg1 signaling in mice by genetically deleting its receptor-ErbB4. Results We found that KD treatment suppressed seizures in both acute and chronic seizure models and enhanced presynaptic GABA release probability in the hippocampus. By screening molecular targets linked to GABAergic activity with transcriptome analysis, we identified that KD treatment dramatically increased the Nrg1 gene expression in the hippocampus. Disruption of Nrg1 signaling by genetically deleting its receptor-ErbB4 abolished KD’s effects on GABAergic activity and seizures. Conclusion Our findings suggest a critical role of Nrg1/ErbB4 signaling in mediating KD’s effects on GABAergic activity and seizures, shedding light on developing new therapeutic interventions to seizure control.

In Chinese female diabetic patients, the incidence of cancer increased with serum uric acid levels.