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Currently, global biodiversity loss is a growing problem, and more species are endangered and at risk of extinction [...].Currently, global biodiversity loss is a growing problem, and more species are endangered and at risk of extinction [...].

Although the population of Przewalski’s gazelle (Procapra przewalskii) has increased, this species is still threatened by a variety of risk factors, such as habitat loss and fragmentation, grassland fencing, grazing conflict, the segmentation of different populations, and declines in population genetic diversity. In order to determine the potential suitable habitat of Przewalski’s gazelle and find a new suitable location for its conservation translocation, we used the MaxEnt model to predict the suitable habitats in Qinghai Province, Gansu Province, and the Ordos Plateau in Inner Mongolia and other regions with historical distribution records. On the basis of the MaxEnt model’s prediction of the potential suitable habitat of Przewalski’s gazelle, we used GAP analysis to determine the existing protection gaps and provide a new reference for the future protection of Przewalski’s gazelle. We found that altitude, temperature, vegetation type, and distance from roads were the main environmental factors affecting the geographical distribution of Przewalski’s gazelle. Most of the suitable habitat of Przewalski’s gazelle is confined around Qinghai Lake. GAP analysis revealed that most of the suitable habitats of Przewalski’s gazelle are not included in the established reserves, and Qinghai Lake National Nature Reserve only covers a small area around Qinghai Lake. The whole reserve only accounts for 7.11% of the area of the suitable habitat for Przewalski’s gazelle and 15.79% of the area of the highly suitable habitat for Przewalski’s gazelle. We suggest that conservation translocation for Przewalski’s gazelle should be put on the agenda. It is necessary to consider reintroducing these gazelles into their potential suitable habitats as a feasible way of establishing new populations and saving this species.

The Amur tiger ( ) is a flagship and umbrella species of forest ecosystems in northeastern Asia. Climate change is profoundly and irreversibly affecting wildlife habitat suitability, especially for large mammals. To effectively protect the Amur tiger, it is necessary to understand the impact of climate change on the quality and the connectivity of its habitat. We used the species distribution models combined with the latest Shared Socioeconomic Pathway (SSP) climate scenarios to predict current and future changes in habitats and corridors. We found the following: (1) The total area of the Amur tiger's suitable habitat currently amounts to approximately 4941.94 km , accounting for 27.64% of the study area represented by two adjacent national parks. Among these habitats, the highly suitable areas are mainly located on the both sides of the Sino-Russian border. The landscape connectivity remains relatively stable, and the degree of fragmentation in highly suitable habitats is low. (2) Although the suitable habitat of the Amur tiger shows an expansion trend under most climate scenarios (excluding SSP3-7.0), the area of suitable habitat within the entire study region does not increase significantly. Therefore, we should implement conservation measures to facilitate the continued expansion of suitable habitat for the Amur tiger. The quantity and length of landscape connectivity corridors are expected to vary in response to changes in core habitat patches, while the centroid of highly suitable habitats is also expected to shift to different extents. In such circumstances, new ecological corridors need to be constructed, while existing natural ecological corridors should be preserved.

Glioblastoma (GBM) is the most common primary malignancy of the central nervous system in adults. The prognosis for late-stage glioblastoma (World Health Organization grade IV astrocytic glioma) is very poor. Novel treatment options are sought after and evaluated by clinicians and researchers, and remarkable advances have been made in surgical techniques, radiotherapy, and chemotherapy. However, the treatment of glioblastoma remains extremely difficult and it can extend the lives of patients by only a few months. There has been notable progress in the field of immunotherapy, particularly with the use of tumor vaccines, for treating glioblastoma; especially peptide vaccines and cell-based vaccines such as dendritic cell vaccines and tumor cell vaccines. However, the results of the current clinical trials for vaccination are not satisfactory. This article reviews the progress in the development of vaccines for glioblastoma.

Medical image segmentation represents a pivotal and intricate procedure in the domain of medical image processing and analysis. With the progression of artificial intelligence in recent years, the utilization of deep learning techniques for medical image segmentation has witnessed escalating popularity. Nevertheless, the intricate nature of medical image poses challenges on the segmentation of diminutive targets is still in its early stages. Current networks encounter difficulties in addressing the segmentation of exceedingly small targets, especially when the number of training samples is limited. To overcome this constraint, we have implemented a proficient strategy to enhance lesion images containing small targets and constrained samples. We introduce a segmentation framework termed STS-Net, specifically designed for small target segmentation. This framework leverages the established capacity of convolutional neural networks to acquire effective image representations. The proposed STS-Net network adopts a ResNeXt50-32x4d architecture as the encoder, integrating attention mechanisms during the encoding phase to amplify the feature representation capabilities of the network. We evaluated the proposed network on four publicly available datasets. Experimental results underscore the superiority of our approach in the domain of medical image segmentation, particularly for small target segmentation. The codes are available at https://github.com/zlxokok/STSNet .

Severe Acute Respiratory Infection (SARI) represents a critical global public health challenge, accounting for substantial severe morbidity and hospitalization burdens with distinct geographical patterns in etiological profiles. This study systematically characterizes the epidemiological and clinical phenotypes of SARI patients in Shouguang county, Shandong Province, China. A prospective observational study was conducted at Shouguang People's Hospital between August 28, 2023 and April 30, 2024, enrolling 1,730 hospitalized patients with SARI from the Departments of Infectious Diseases and Respiratory and Critical Care Medicine. Standardized electronic case report forms were used to systematically collect the demographic characteristics, clinical manifestations and laboratory testing results. Oropharyngeal swab specimens were collected within 24 hours of admission for each patient and stored at -80°C. Multiplex real-time quantitative PCR (RT-qPCR) was performed using the ABI 7500 system to detect 11 respiratory viruses infection, including influenza A virus (IFA), influenza B virus (IFB), respiratory syncytial virus (RSV), parainfluenza virus (HPIV), human coronaviruses (HCoV), human metapneumovirus (HMPV), rhinovirus (HRV), enterovirus (EV), human bocavirus (HBoV), human adenovirus (HAdV), and SARS-CoV-2 (COVID-19). 501 samples (28.96%) were tested positive for at least one virus. The most frequently detected viruses and their infection rates were as follows: IFA (11.33%), COVID-19 (6.53%), HPIV (2.31%), HCoV (2.20%), RSV (1.79%), IFB (1.68%), HMPV (1.56%), EV (0.64%), HADV (0.52%), and HBoV (0.06%). Among patients aged 0-14 years, IFA and EV had the highest infection rates, both at 9.46% (7/74). In the 15-24 age group, IFA exhibited the highest infection rate at 19.70% (26/132). In patients aged ≥70 years, COVID-19 was the most frequently detected virus, with a infection rate of 10.69% (65/608). The overall virus infection rate peaked at 60.00% (30/50) in epidemiological week 48 of 2023. During weeks 46-50 of 2023, the overall infection rate remained consistently high (range: 28.42-60.00%). Significant differences in infection rates were observed across hospital departments (χ² = 5.52, P < 0.05), The Department of Infectious Diseases demonstrated a higher infection rate of 34.91% (162/464) compared to 29.07% (368/1266) in the Department of Respiratory Medicine. Viral etiological analysis of SARI patients in Eastern China identified IFA, COVID-19, and HPIV as the three predominant virus, with influenza virus exhibiting the highest frequency of co-infection with other respiratory viruses. Our study further revealed significant heterogeneity in virus distribution across different hospital departments, age groups, and admission periods. The most common clinical manifestations were cough and fever, with distinct symptomatic profiles observed among infections caused by different viruss. These findings provide scientific evidence to inform government strategies for optimizing the prevention and management of respiratory infectious diseases.

Background Sporobolomyces pararoseus is a well-studied oleaginous red yeast that can synthesize a variety of high value-added bioactive compounds. Biofilm is one of the important biological barriers for microbial cells to resist environmental stresses and maintain stable fermentation process. Here, the effect of acidic conditions on the biosynthesis of biofilms in S. pararoseus NGR was investigated through the combination of morphology, biochemistry, and multi-omics approaches. Results The results showed that the acidic environment was the key factor to trigger the biofilm formation of S. pararoseus NGR. When S. pararoseus NGR was cultured under pH 4.7, the colony morphology was wrinkled, the cells were wrapped by a large amount of extracellular matrix, and the hydrophobicity and anti-oxidative stress ability were significantly improved, and the yield of intracellular carotenoids was significantly increased. Transcriptome and metabolome profiling indicated that carbohydrate metabolism, amino acid metabolism, lipid metabolism, and nucleic acid metabolism in S. pararoseus NGR cells were significantly enriched in biofilm cells under pH 4.7 culture conditions, including 56 differentially expressed genes and 341 differential metabolites. Conclusions These differential genes and metabolites may play an important role in the formation of biofilms by S. pararoseus NGR in response to acidic stress. The results will provide strategies for the development and utilization of beneficial microbial biofilms, and provide theoretical support for the industrial fermentation production of microorganisms to improve their resistance and maintain stable growth.

Studies of schizophrenia (SCZ) have associated auditory verbal hallucinations (AVH) with structural and functional abnormalities in frontal cortex, especially medial prefrontal cortex (mPFC). Although abnormal prefrontal network connectivity associated with language production has been studied extensively, the relationship between mPFC dysfunction (highly relevant to the pathophysiology of SCZ) and AVH has been rarely investigated. In this study, proton magnetic resonance spectroscopy was used to measure metabolite levels in the mPFC in 61 SCZ patients with persistent AVH (pAVH), 53 SCZ patients without AVH (non-AVH), and 59 healthy controls (HC). The pAVH group showed significantly lower levels of N -acetyl-aspartate +  N -acetyl-aspartyl-glutamate (tNAA) and glutamate + glutamine (Glx), compared with the non-AVH (tNAA: p  = 0.022, Glx: p  = 0.012) and HC (tNAA: p  = 0.001, Glx: p  = 0.001) groups. No difference was found in the levels of tNAA and Glx between non-AVH and HC. The levels of tNAA and Glx in the mPFC was negatively correlated with the severity of pAVH (tNAA: r  = −0.24, p  = 0.014; Glx: r  = −0.30, p  = 0.002). In conclusion, pAVH in SCZ patients might be related to decreased levels of tNAA and Glx in the mPFC, indicating that tNAA or Glx might play a key role in the pathogenesis of pAVH.

Familial cerebral cavernous malformation (FCCM), especially severe cases, impose a heavy physical and psychological burden on patients and their families. To explore the differences in plasma biomarker levels between patients with FCCM and their healthy first-degree relatives (FDRs) and between FCCM patients with and without severe chronic disease aggressiveness (CDA). In a cross - sectional study, magnetic resonance imaging (MRI) scanning and genetic testing were performed in patients with multiple CCMs and their FDRs. Subsequently, sixty-seven plasma biomarkers were tested using a customised multiplex bead immunoassay kit. Univariate and multivariate unconditional logistic regression analyses were conducted to determine the associations between plasma factors and the risk of developing FCCM and severe CDA. Receiver operating characteristic (ROC) curves were generated for each independent risk factor. As a result, plasma factors of 37 patients with FCCM and 37 FDRs were examined. Low CD31 ( P  < 0.001) and BDNF levels ( P  = 0.013) were independent risk factors for FCCM. The best model was achieved by combining the results of CD31 and BDNF (AUC = 0.845, sensitivity 0.838, specificity 0.784, cutoff score − 4.295) to distinguish patients with FCCM from healthy FDRs. Low Serpin E1/PAI-1 ( P  = 0.011) and high ROBO4 levels ( P  = 0.013) were independent risk factors for severe CDA in patients with FCCM. The best model was achieved by combining the results of Serpin E1/PAI-1 and ROBO4 levels (AUC = 0.913, sensitivity 1.000, specificity 0.760, cutoff score − 0.525) to identify patients with FCCM and severe CDA. In summary, the plasma concentrations of CD31 and BDNF seem to be lower in patients with FCCM than in their healthy FDRs. Low Serpin E1/PAI-1 and high ROBO4 concentrations may be correlated with high lesion burden and risk of recurrent bleeding. Trial registration: ClinicalTrials.gov Identifier: NCT03467295.

A wide array of wildlife species, including many animals, are used in traditional medicines across many medicinal systems, including in Traditional Chinese Medicine (TCM). Due to over-exploitation and habitat loss, the populations of many animals commonly used in TCM have declined and are unable to meet market demand. A number of measures have been taken to try to reduce the impact that this large and growing market for TCM may have on wild animal species. Consumer preferences and behavior are known to play an important role in the consumption and protection of wild animals used in traditional medicine, and thus are likely to be an important factor in the success of many of these mechanisms--particularly given the significant percentage of TCMs that are over-the-counter products (access to which is not mediated by practitioners). In this study we conducted questionnaires and designed stated preference experiments embodying different simulation scenarios using a random sample of the population in Beijing to elicit individuals' knowledge, perceptions and preferences toward wild or farmed animal materials and their substitutes used in traditional Chinese medicine. We found that respondents had a stated preference for wild materials over farm-raised and other alternatives because they believe that the effectiveness of wild-sourced materials is more credible than that of other sources. However, we also found that, although respondents used TCM products, they had a poor understanding of the function or composition of either traditional Chinese medicines or proprietary Chinese medicines (PCM), and paid little attention to the composition of products when making purchasing decisions. Furthermore, awareness of the need for species protection, or \"conservation consciousness\" was found to play an important role in willingness to accept substitutions for wild animal materials, while traditional animal medicinal materials (TAMs) derived from well-known endangered species, such as bear bile and tiger bone, show relatively higher substitutability. These results suggest that there is still hope for conservation measures which seek to promote a transition to farmed animal, plant and synthetic ingredients and provide clear directions for future social marketing, education and engagement efforts.