Akt acts as a pivotal regulator in the PI3K/Akt signaling pathway and represents a potential drug target for cancer therapy. To search for new inhibitors of Akt kinase, we performed a structure-based virtual screening using the DOCK 4.0 program and the X-ray crystal structure of human Akt kinase. From the virtual screening, 48 compounds were selected and subjected to the Akt kinase inhibition assay. Twenty-six of the test compounds showed more potent inhibitory effects on Akt kinase than the reference compound, H-89. These 26 compounds were further evaluated for their cytotoxicity against HCT-116 human colon cancer cells and HEK-293 normal human embryonic kidney cells. Twelve compounds were found to display more potent or comparable cytotoxic activity compared to compound H-89 against HCT-116 colon cancer cells. The best results were obtained with Compounds a46 and a48 having IC₅₀ values (for HCT-116) of 11.1 and 9.5 µM, respectively, and selectivity indices (IC₅₀ for HEK-293/IC₅₀ for HCT-116) of 12.5 and 16.1, respectively. Through structure-based virtual screening and biological evaluations, we have successfully identified several new Akt inhibitors that displayed cytotoxic activity against HCT-116 human colon cancer cells. Especially, Compounds a46 and a48 may serve as useful lead compounds for further development of new anticancer agents.

Systemic injection of therapeutic antibodies may cause serious adverse effects due to on-target toxicity to the antigens expressed in normal tissues. To improve the targeting selectivity to the region of disease sites, we developed protease-activated pro-antibodies by masking the binding sites of antibodies with inhibitory domains that can be removed by proteases that are highly expressed at the disease sites. The latency-associated peptide (LAP), C2b or CBa of complement factor 2/B were linked, through a substrate peptide of matrix metalloproteinase-2 (MMP-2), to an anti-epidermal growth factor receptor (EGFR) antibody and an anti-tumor necrosis factor-α (TNF-α) antibody. Results showed that all the inhibitory domains could be removed by MMP-2 to restore the binding activities of the antibodies. LAP substantially reduced (53.8%) the binding activity of the anti-EGFR antibody on EGFR-expressing cells, whereas C2b and CBa were ineffective (21% and 9.3% reduction, respectively). Similarly, LAP also blocked 53.9% of the binding activity of the anti-TNF-α antibody. Finally, molecular dynamic simulation showed that the masking efficiency of LAP, C2b and CBa was 33.7%, 10.3% and −5.4%, respectively, over the binding sites of the antibodies. This strategy may aid in designing new protease-activated pro-antibodies that attain high therapeutic potency yet reduced systemic on-target toxicity.

The blood-brain barrier (BBB) remains a major obstacle for effective delivery of therapeutics to treat central nervous system (CNS) disorders. Although transferrin receptor (TfR)-mediated transcytosis is widely employed for brain drug delivery, the inefficient release of therapeutic payload hinders their efficacy from crossing the BBB. Here, we developed a pH-responsive anti-polyethylene glycol (PEG) × anti-TfR bispecific antibody (pH-PEG engager^TfR) that can complex with PEGylated nanomedicine at physiological pH to trigger TfR-mediated transcytosis in the brain microvascular endothelial cells, while rapidly dissociating from PEGylated nanomedicine at acidic endosomes for efficient release of PEGylated nanomedicine to cross the BBB. The pH-PEG engager^TfR significantly increased the accumulation of PEGylated nanomedicine in the mouse brain compared to wild-type PEG engager^TfR (WT-PEG engager^TfR). pH-PEG engager^TfR-decorated PEGylated liposomal doxorubicin exhibited an enhanced antitumor effect and extended survival in a human glioblastoma (GBM) orthotopic xenograft mice model. Conditional release of PEGylated nanomedicine during BBB-related receptor-mediated transcytosis by pH-PEG engager^TfR is promising for enhanced brain drug delivery to treat CNS disorders.

Autoimmune hypophysitis (AH) is a chronic inflammatory disease characterized by infiltration of T and B lymphocytes in the pituitary gland. The mechanisms through which infiltrating lymphocytes cause disease remain unknown. Using a mouse model of AH we assessed whether T lymphocytes undergo activation in the pituitary gland. Infiltrating T cells co-localized with dendritic cells in the pituitary and produced increased levels of interferon-γ and interleukin-17 upon stimulation in vitro. Assessing proliferation of CD3- and B220-postive lymphocytes by double immunohistochemistry (PCNA-staining) and flow cytometry (BrdU incorporation) revealed that a discrete proportion of infiltrating T cells and B cells underwent proliferation within the pituitary parenchyma. This proliferation persisted into the late disease stage (day 56 post-immunization), indicating the presence of a continuous generation of autoreactive T and B cells within the pituitary gland. T cell proliferation in the pituitary was confirmed in patients affected by autoimmune hypophysitis. In conclusion, we show that pituitary-infiltrating lymphocytes proliferate in situ during AH, providing a previously unknown pathogenic mechanism and new avenues for treatment.

Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution.