Major depressive disorder (MDD) is a chronic, generally episodic and debilitating disease that affects an estimated 300 million people worldwide, but its pathogenesis is poorly understood. The heritability estimate of MDD is 30–40%, suggesting that genetics alone do not account for most of the risk of major depression. Another factor known to associate with MDD involves environmental stressors such as childhood adversity and recent life stress. Recent studies have emerged to show that the biological impact of environmental factors in MDD and other stress-related disorders is mediated by a variety of epigenetic modifications. These epigenetic modification alterations contribute to abnormal neuroendocrine responses, neuroplasticity impairment, neurotransmission and neuroglia dysfunction, which are involved in the pathophysiology of MDD. Furthermore, epigenetic marks have been associated with the diagnosis and treatment of MDD. The evaluation of epigenetic modifications holds promise for further understanding of the heterogeneous etiology and complex phenotypes of MDD, and may identify new therapeutic targets. Here, we review preclinical and clinical epigenetic findings, including DNA methylation, histone modification, noncoding RNA, RNA modification, and chromatin remodeling factor in MDD. In addition, we elaborate on the contribution of these epigenetic mechanisms to the pathological trait variability in depression and discuss how such mechanisms can be exploited for therapeutic purposes.

Increasing evidence suggests that Parkinson’s disease (PD) exhibits disparate spatial and temporal patterns of progression. Here we used a machine-learning technique—Subtype and Stage Inference (SuStaIn) — to uncover PD subtypes with distinct trajectories of clinical and neurodegeneration events. We enrolled 228 PD patients and 119 healthy controls with comprehensive assessments of olfactory, autonomic, cognitive, sleep, and emotional function. The integrity of substantia nigra (SN), locus coeruleus (LC), amygdala, hippocampus, entorhinal cortex, and basal forebrain were assessed using diffusion and neuromelanin-sensitive MRI. SuStaIn model with above clinical and neuroimaging variables as input was conducted to identify PD subtypes. An independent dataset consisting of 153 PD patients and 67 healthy controls was utilized to validate our findings. We identified two distinct PD subtypes: subtype 1 with rapid eye movement sleep behavior disorder (RBD), autonomic dysfunction, and degeneration of the SN and LC as early manifestations, and cognitive impairment and limbic degeneration as advanced manifestations, while subtype 2 with hyposmia, cognitive impairment, and limbic degeneration as early manifestations, followed later by RBD and degeneration of the LC in advanced disease. Similar subtypes were shown in the validation dataset. Moreover, we found that subtype 1 had weaker levodopa response, more GBA mutations, and poorer prognosis than subtype 2. These findings provide new insights into the underlying disease biology and might be useful for personalized treatment for patients based on their subtype.

The Lifshitz–Kosevich (LK) theory is the pillar of magnetic quantum oscillations, which have been extensively applied to characterise a wide range of metallic states. In this study, we focus on the Shubnikov–de Haas (SdH) effect observed in SmSb, a rare-earth monopnictide. We observed a significant departure from the expected LK theory near TN = 2.4 K: both a peak-like anomaly and an enhancement in the temperature dependence of quantum oscillation amplitude are seen in SmSb. Moreover, we discovered a remarkable sensitivity of the SdH amplitudes to sample purity. By adjusting the sample purity, we were able to tune the temperature dependence of the α band’s SdH amplitudes from a peak-like anomalous behaviour to an enhancement. Therefore, SdH oscillations from the α band connect the two well-known non-LK behaviours, controllable through varying the sample purity, paving the way for developing further understanding of the mechanism leading to the anomalous quantum oscillations.

The commercial space industry seems to draw worldwide attention in the recent two decades to respond to the increasingly broad market demand. Compared with Western countries, the development of China’s commercial space industry is still in its infancy and faces many daunting challenges. Few studies have considered the dual perspective of government and market of commercial space industry in China. Aiming at exploring the influencing factors and future directions of the development of China’s commercial space industry, this paper proposed the theoretical analysis framework consisting of Policy, Innovation and Economics, and conducted a synergistic analysis of government and market in China’s commercial space industry. Specifically, based on the interview data, assisted by a machine learning approach, we have conducted an industry analysis of the influencing factors of commercial space in China. The results show that China’s commercial space industry is rapidly developing with many characteristics. Specifically, at present, there is a lack of specific and operational policies at the implementation level. Despite limited disruptive innovation, commercial space companies have achieved breakthroughs in many key areas. The overall industry is exploring more stable and sustainable profit models. The findings of this study contribute to the topic of industry development in business management literature by underpinning the policy discussion, technological analysis and direction for the future development of China’s commercial space industry. The industry practitioners may also benefit from the practices that were discussed in this research.

BackgroundColorectal cancer (CRC) is the second most deadly cancer worldwide, with chemo-resistance remaining a major obstacle in CRC treatment. Notably, the imbalance of redox homeostasis-mediated ferroptosis and the modulation of hypoxic tumor microenvironment are regarded as new entry points for overcoming the chemo-resistance of CRC.MethodsInspired by this, we rationally designed a light-activatable oxygen self-supplying chemo-photothermal nanoplatform by co-assembling cisplatin (CDDP) and linoleic acid (LA)-tailored IR820 via enhanced ferroptosis against colorectal cancer chemo-resistance. In this nanoplatform, CDDP can produce hydrogen peroxide in CRC cells through a series of enzymatic reactions and subsequently release oxygen under laser-triggered photothermal to alleviate hypoxia. Additionally, the introduced LA can add exogenous unsaturated fatty acids into CRC cells, triggering ferroptosis via oxidative stress-related peroxidized lipid accumulation. Meanwhile, photothermal can efficiently boost the rate of enzymatic response and local blood flow, hence increasing the oxygen supply and oxidizing LA for enhanced ferroptosis.ResultsThis nanoplatform exhibited excellent anti-tumor efficacy in chemo-resistant cell lines and showed potent inhibitory capability in nude mice xenograft models.ConclusionsTaken together, this nanoplatform provides a promising paradigm via enhanced ferroptosis and alleviated hypoxia tumor microenvironment against CRC chemo-resistance.Graphical Abstract