Three novel woody litter inhabiting fungi in Didymosphaeriaceae, Phaeoseptaceae and Synnemasporellaceae from Zhujiangyuan Nature Reserve, Yunnan Province, P.R. China.

Zhujiangyuan Nature Reserve, located in Qujing City, Yunnan Province, China, is reported with high fauna and floral diversity, while the fungal diversity of the region is poorly documented. During the summer season in 2023, decaying wood-inhabiting microfungi were collected from different microhabitats. The novel species were identified based on morphological characteristics and phylogenetic analyses (based on combined datasets of ITS, LSU, SSU, tef1-α, and rpb2 regions). Two species belong to Dothideomycetes (viz., Spegazziniazhujiangyuanensis sp. nov. and Phaeoseptumzhujiangyuanense sp. nov. in Pleosporales) while the other one resides in Sordariomycetes (Synnemasporellafanii sp. nov. in Diaporthales). The results are in conformity with the earlier studies that predicted higher fungal diversity in this region.

Fungi associated with dead branches of Magnolia grandiflora: A case study from Qujing, China.

As a result of an ongoing survey of microfungi associated with garden and ornamental plants in Qijing, Yunnan, China, several saprobic fungal taxa were isolated from Magnolia grandiflora. Both morphological and combined SSU, LSU, ITS, tef1, and rpb2 locus phylogenetic analyses (maximum-likelihood and Bayesian analyses) were carried out to identify the fungal taxa. Three new species are introduced in Pleosporales, viz., Lonicericola qujingensis (Parabambusicolaceae), Phragmocamarosporium magnoliae, and Periacma qujingensis (Lentitheciaceae). Botryosphaeria dothidea, Diplodia mutila, and Diplodia seriata (in Botryosphaeriaceae) are reported from Magnolia grandiflora for the first time in China. Angustimassarina populi (Amorosiaceae) is reported for the first time on M. grandiflora from China, and this is the first report of a member of this genus outside Europe. Shearia formosa is also reported for the first time on M. grandiflora from China.

Taxonomic and Phylogenetic Characterizations Reveal Four New Species, Two New Asexual Morph Reports, and Six New Country Records of Bambusicolous Roussoella from China.

During the ongoing investigation of bambusicolous ascomycetous fungi in Yunnan, China, 24 specimens belonging to the family Roussoellaceae were collected and identified based on morphological features and phylogenetic support. Maximum-likelihood (ML) analyses and Bayesian analyses were generated based on the combined data set of ITS, LSU, tef1, and rpb2 loci. The phylogenetic analyses revealed four novel lineages in Roussoella s. str.; thus, we introduced four new species viz., Roussoella multiloculate sp. nov., R. papillate sp. nov., R. sinensis sp. nov., and R. uniloculata sp. nov. Their morphological characters were compared with the known Roussoella taxa, which lack sequence data in the GenBank. Asexual morphs of R. kunmingensis and R. padinae were recorded from dead bamboo culms in China (from the natural substrates) for the first time. Neoroussoella bambusae, Roussoella japanensis, R. nitidula, R. padinae, R. scabrispora, and R. tuberculate were also reported as the first records from China. All new taxa are described and illustrated in detail. Plates are provided for new reports.

ReaxFF-MPNN machine learning potential: a combination of reactive force field and message passing neural networks.

Reactive force field (ReaxFF) is a powerful computational tool for exploring material properties. In this work, we proposed an enhanced reactive force field model, which uses message passing neural networks (MPNN) to compute the bond order and bond energies. MPNN are a variation of graph neural networks (GNN), which are derived from graph theory. In MPNN or GNN, molecular structures are treated as a graph and atoms and chemical bonds are represented by nodes and edges. The edge states correspond to the bond order in ReaxFF and are updated by message functions according to the message passing algorithms. The results are very encouraging; the investigation of the potential, such as the potential energy surface, reaction energies and equation of state, are greatly improved by this simple improvement. The new potential model, called reactive force field with message passing neural networks (ReaxFF-MPNN), is provided as an interface in an atomic simulation environment (ASE) with which the original ReaxFF and ReaxFF-MPNN potential models can do MD simulations and geometry optimizations within the ASE. Furthermore, machine learning, based on an active learning algorithm and gradient optimizer, is designed to train the model. We found that the active learning machine not only saves the manual work to collect the training data but is also much more effective than the general optimizer.

Altered neurotransmitter levels with post-traumatic stress disorder.

AIM: The aim of this study was to observe the changes in the monoamine neurotransmitter levels of patients with post-traumatic stress disorder (PTSD) and explore whether the neurotransmitter level is correlated with the severity of PTSD. MATERIAL AND METHODS: A total of 15 PTSD patients without any physical injuries were enrolled into the study. Another 15 cases of pre-restoration patients were recruited as controls who experienced traumatic events but did not experience PTSD or had a Posttraumatic stress disorder Check List-Civilian version (PCL-C) score lower than 12 points. The levels of plasma monoamine neurotransmitters, including norepinephrine, 5-hydroxytryptamine, and dopamine, were tested using enzyme-linked immunosorbent assays. RESULTS: No significant differences were found between the monoamine neurotransmitter levels of the PTSD and the control groups (p > 0.05). A correlation study confirmed that the monoamine neurotransmitter levels and the PCL-C scores of the PTSD group were not significantly correlated (p > 0.05). CONCLUSION: No neurotransmitter changes are seen in PTSD caused by simple mental trauma, and the PCL-C scores do not associate with PTSD.

Comprehensive identification of high-frequency and co-occurring Mafa-B, Mafa-DQB1, and Mafa-DRB alleles in cynomolgus macaques of Vietnamese origin.

High-frequency alleles and/or co-occurring human leukocyte antigen (HLA) alleles across loci appear to be more important than individual alleles, because they might be markers of disease risk that have clinical value as biomarkers for targeted screening or the development of new therapies. To better elucidate the major histocompatibility complex background and to facilitate the experimental use of cynomolgus macaques, Mafa-B, Mafa-DQB1, and Mafa-DRB alleles were characterized and their combinations were investigated from 30 macaques of Vietnamese origin by cloning and sequencing. A total of 48 Mafa-B, 22 Mafa-DQB1, and 42 Mafa-DRB alleles, were detected in this study, respectively. In addition, two Mafa-DQB1 and eight Mafa-DRB alleles represented novel sequences that had not been documented in earlier studies. Our results also showed that the macaque from Vietnam might be valuable because >30% of the test animals possessed Mafa-DRB*w304 (30%) and -DQB1*0616 (30%). We report that the combination of major histocompatibility complex (MHC) class I and II alleles, including the combination of DRB3*0403-DRB*w304, DRB1*1013-DRB*w304, and Mafa-B*007:01:01-DRB*w304, which was in 17%, 13%, and 13% of the animals, respectively. Interesting, more than two Mafa-DQB1 alleles detected in one animal in this study suggest that Mafa-DQB1, like Mafa-DRB, might be a duplication in the chromosome, which have ever been documented in cynomolgus monkeys but has not yet been observed in rhesus macaques or other primates. Our results for the high frequency of commonly co-occurring MHC alleles across loci in a cohort of the Vietnamese cynomolgus macaque emphasized the value of this species as a model for biomedical research.