Peptide modulators targeting protein-protein interactions (PPIs) exhibit greater potential than small-molecule drugs in several important aspects including facile modification and relative large contact surface area. Stabilized peptides constructed by variable chemistry methods exhibit improved peptide stability and cell permeability compared to that of the linears. Herein, we designed a stabilized peptide-based proteolysis-targeting chimera (PROTAC) targeting estrogen receptor α (ERα) by tethering an N-terminal aspartic acid cross-linked stabilized peptide ERα modulator (TD-PERM) with a pentapeptide that binds the Von Hippel-Lindau (VHL) E3 ubiquitin ligase complex. The resulting heterobifunctional peptide (TD-PROTAC) selectively recruits ERα to the VHL E3 ligase complex, leading to the degradation of ERα in a proteasome-dependent manner. Compared with the control peptides, TD-PROTAC shows significantly enhanced activities in reducing the transcription of the ERα-downstream genes and inhibiting the proliferation of ERα-positive breast cancer cells. In addition, in vivo experiments indicate that TD-PROTAC leads to tumor regression in the MCF-7 mouse xenograft model. This work is a successful attempt to construct PROTACs based on cell-permeable stabilized peptides, which significantly broadens the chemical space of PROTACs and stabilized peptides.

Lack of specific and efficient therapy leads to the high mortality rate of acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Losartan is a potent pharmaceutical drug for ALI/ARDS. However, the protective effects and mechanisms of losartan remain incompletely known. This study evaluates the effects of losartan on ALI/ARDS and further investigates the possible mechanisms of these protective effects. Mice received i.p. injections of the AT1 inhibitor losartan (15 mg/kg), or control vehicle, half hour after cecal ligation and puncture (CLP). Plasma TNF-alpha, IL-1beta, and IL-6 cytokines were assayed 6 h after CLP. Blood gas, wet/dry lung weight ratio, lung tissue histology for occurrence of ALI/ARDS, and survival were examined. Lastly, nuclear factor kappaB (NF-kappaB) activations, IkappaB-alpha degradations, phosphorylations of p38 MAPK, extracellular signal-regulated kinase 1/2, and c-Jun N-terminal kinase expressions were evaluated in lung tissue. Losartan treatment significantly attenuated TNF-alpha, IL-6, and IL-1beta 6 h after CLP. Furthermore, losartan prevented blood gas and histopathologic appearance of ALI/ARDS after sepsis and significantly improved survival. Finally, losartan given after sepsis led to inhibition of lung tissue NF-kappaB activation (P < 0.01 vs. CLP group), attenuated degradation of IkappaB-alpha, and inhibited phosphorylation of p38MAPK, extracellular signal-regulated kinase 1/2, and c-Jun N-terminal kinase, pathways critical for cytokine release. These data reveal that losartan exerts a protective effect on ALI/ARDS, and this protective effect may be dependent, at least in part, on NF-kappaB and MAPK mechanisms.

Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms.

Multi-modal pre-training models have been intensively explored to bridge vision and language in recent years. However, most of them explicitly model the cross-modal interaction between image-text pairs, by assuming that there exists strong semantic correlation between the text and image modalities. Since this strong assumption is often invalid in real-world scenarios, we choose to implicitly model the cross-modal correlation for large-scale multi-modal pretraining, which is the focus of the Chinese project 'Wen-Lan' led by our team. Specifically, with the weak correlation assumption over image-text pairs, we propose a twotower pre-training model called BriVL within the crossmodal contrastive learning framework. Unlike OpenAI CLIP that adopts a simple contrastive learning method, we devise a more advanced algorithm by adapting the latest method MoCo into the cross-modal scenario. By building a large queue-based dictionary, our BriVL can incorporate more negative samples in limited GPU resources. We further construct a large Chinese multi-source imagetext dataset called RUC-CAS-WenLan for pre-training our BriVL model. Extensive experiments demonstrate that the pre-trained BriVL model outperforms both UNITER and OpenAI CLIP on various downstream tasks.

Highlights d The crystal structure of Stp1 reveals the binding of an unexpected fourth metal ion d A potent and selective inhibitor ATA blocks the phosphatase activity of Stp1 d ATA represses the transcriptional expression of virulence factors d ATA attenuates the infection burden of S. aureus in the mouse model

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Background Metagenome next-generation sequencing (mNGS) is a valuable diagnostic tool that can be used for the identification of early pathogens of acute respiratory distress syndrome (ARDS) in severe pneumonia. Little is known about the use of this technology in clinical application and the evaluation of the prognostic value of ARDS. Methods We performed a retrospective cohort study of patients with ARDS caused by severe pneumonia. Samples were collected from patients in the intensive care unit (ICU) of Jiangmen Central Hospital from January 2018 to August 2019. The no-next generation sequencing (NGS) group was composed of patients given conventional microbiological tests to examine sputum, blood, or bronchoalveolar lavage fluid. The NGS group was composed of patients tested using mNGS and conventional microbiological tests. We evaluated the etiological diagnostic effect and clinical prognostic value of mNGS in patients with ARDS caused by severe pneumonia. Results The overall positive rate (91.1%) detected by the mNGS method was significantly higher than that of the culture method (62.2%, P = 0.001), and antibody plus polymerase chain reaction (28.9%, P < 0.001). Following adjustment of the treatment plan based on microbial testing results, the Acute Physiology and Chronic Health Evaluation-II (APACHE II) score of the NGS group was lower than that of the no-NGS group 7 days after treatment (P < 0.05). The 28-day mortality rate of the NGS group was significantly lower than that of the no-NGS group (P < 0.05). Longer ICU stay, higher APACHE II score and sequential organ failure assessment score were risk factors for the death of ARDS, and adjusting the medication regimen based on mNGS results was a protective factor. The detection of mNGS can significantly shorten the ICU stay of immunosuppressed patients (P < 0.01), shorten the ventilation time (P < 0.01), and reduce the ICU hospitalization cost (P < 0.05). Conclusions Metagenome next-generation sequencing is a valuable tool to determine the etiological value of ARDS caused by severe pneumonia to improve diagnostic accuracy and prognosis for this disease. For immunosuppressed patients, mNGS technology can be used in the early stage to provide more diagnostic evidence and guide medications.