Mieap, a p53-Inducible Protein, Controls Mitochondrial Quality by Repairing or Eliminating Unhealthy Mitochondria

Maintenance of healthy mitochondria prevents aging, cancer, and a variety of degenerative diseases that are due to the result of defective mitochondrial quality control (MQC). Recently, we discovered a novel mechanism for MQC, in which Mieap induces intramitochondrial lysosome-like organella that plays a critical role in the elimination of oxidized mitochondrial proteins (designated MALM for Mieap-induced accumulation of lysosome-like organelles within mitochondria). However, a large part of the mechanisms for MQC remains unknown. Here, we report additional mechanisms for Mieap-regulated MQC. Reactive oxygen species (ROS) scavengers completely inhibited MALM. A mitochondrial outer membrane protein NIX interacted with Mieap in a ROS-dependent manner via the BH3 domain of NIX and the coiled-coil domain of Mieap. Deficiency of NIX also completely impaired MALM. When MALM was inhibited, Mieap induced vacuole-like structures (designated as MIV for Mieap-induced vacuole), which engulfed and degraded the unhealthy mitochondria by accumulating lysosomes. The inactivation of p53 severely impaired both MALM and MIV generation, leading to accumulation of unhealthy mitochondria. These results suggest that (1) mitochondrial ROS and NIX are essential factors for MALM, (2) MIV is a novel mechanism for lysosomal degradation of mitochondria, and (3) the p53-Mieap pathway plays a pivotal role in MQC by repairing or eliminating unhealthy mitochondria via MALM or MIV generation, respectively

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Macroscopic Cluster Organizations Change the Complexity of Neural Activity

In this study, simulations are conducted using a network model to examine how the macroscopic network in the brain is related to the complexity of activity for each region. The network model is composed of multiple neuron groups, each of which consists of spiking neurons with different topological properties of a macroscopic network based on the Watts and Strogatz model. The complexity of spontaneous activity is analyzed using multiscale entropy, and the structural properties of the network are analyzed using complex network theory. Experimental results show that a macroscopic structure with high clustering and high degree centrality increases the firing rates of neurons in a neuron group and enhances intraconnections from the excitatory neurons to inhibitory neurons in a neuron group. As a result, the intensity of the specific frequency components of neural activity increases. This decreases the complexity of neural activity. Finally, we discuss the research relevance of the complexity of the brain activity

Variation in rotavirus vaccine coverage by sub-counties in Kenya

Abstract Rotavirus gastroenteritis is an important cause of childhood morbidity and mortality in Kenya. In July 2014, Kenya introduced the rotavirus vaccine into her national immunization program. Although immunization coverage is crucial in assessing the real-world impact of this vaccine, variability in the vaccine coverage across the country is likely to occur. In view of this, we estimated the extent of coverage for the rotavirus vaccine at two socio-economically different sub-counties using the administrative data. The findings indicate disparities in vaccine coverage and access between the sub-counties and, thus, underscore the need to strengthen immunization systems to facilitate timely, accessible, and equitable vaccine delivery across the country. Both sub-counties recorded high vaccine dropout, suggestive of poor utilization of the vaccine. In this regard, increased social mobilization is needed to encourage vaccine compliance and to enhance tracking of vaccine defaulters. While efforts to improve the accuracy of the administrative coverage estimates are crucial, vaccination coverage surveys will be needed to verify the administrative coverage data and help identify specific factors relating to rotavirus vaccine coverage in the country

Bioinformatics approaches for unveiling virus-host interactions

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus–host interactions through host range prediction and protein–protein interaction prediction. Although many algorithms have been developed to predict virus–host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus–host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus–host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health

Variations in the Expression of Photosynthesis–Related Proteins in Field Chattonella Marina Cells During a Harmful Algal Bloom

Time series variations in protein expression profiles in field Chattonella marina cells were investigated during a HAB occurred in the inner part of Ariake Sea, Japan (5–14 September, 2012). This study aimed to gather information on the molecular mechanisms underlying the physiological responses in field C. marina population during HAB. Proteomic analysis showed that the abundance of ~37% protein spots (40 out of 108 detected from 2–DE gel images) significantly varied with the sampling date. Significant decreases in the abundances of proteins involved in photosystem II (LHCP 4), electron transfer chain (Cyt c553), Calvin cycle (GAPDH), and chloroplast antioxidant system (2–Cys Prx) were observed as the bloom progressed, suggesting the efficiencies of those photosynthetic pathways declined during the bloom. In addition, the abundances of the above proteins showed significant positive correlations with the F_v/F_m ratio and growth rate of C. marina and with DIN concentrations (except LHCP 4). Our findings suggested that declined expressions of those photosynthesis–related proteins presented some molecular foundation of the decreases in F_v/F_m ratio and growth rate of C. marina during the bloom, and also provided insight into mechanistic links between the external/internal factors and physiological responses of C. marina that may ultimately dictate the ecology of the bloom

Analysis of Environmental and Pathogenic Bacteria Attached to Aerosol Particles Size-Separated with a Metal Mesh Device

Metal mesh devices (MMDs) are novel materials that enable the precise separation of particles by size. Structurally, MMDs consist of a periodic arrangement of square apertures of characteristic shapes and sizes on a thin nickel membrane. The present study describes the separation of aerosol particles using palm-top-size collection devices equipped with three types of MMDs differing in pore size. Aerosols were collected at a farm located in the suburbs of Nairobi, Kenya; aerosol particles were isolated, and pathogenic bacteria were identified in this microflora by next-generation sequencing analysis. The composition of the microflora in aerosol particles was found to depend on particle size. Gene fragments were obtained from the collected aerosols by PCR using primers specific for the genus Mycobacterium. This analysis showed that Mycobacterium obuense, a non-tuberculous species of mycobacteria that causes lung diseases, was present in these aerosols. These findings showed that application of this MMD analytical protocol to aerosol particles can facilitate the investigation of airborne pathogenic bacteria