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Abstract Background Depersonalization-Derealization Disorder (DPD), a prevalent psychiatric disorder, fundamentally disrupts self-consciousness and could significantly impact the quality of life of those affected. While existing research has provided foundational insights for this disorder, the limited exploration of brain dynamics in DPD hinders a deeper understanding of its mechanisms. It restricts the advancement of diagnosis and treatment strategies. To address this, our study aimed to explore the brain dynamics of DPD. Methods In our study, we recruited 84 right-handed DPD patients and 67 healthy controls (HCs), assessing them using the Cambridge Depersonalization Scale and a subliminal self-face recognition task. We also conducted a Transcranial Direct Current Stimulation (tDCS) intervention to understand its effect on brain dynamics, evidenced by Functional Magnetic Resonance Imaging (fMRI) scans. Our data preprocessing and analysis employed techniques such as Independent Component Analysis (ICA) and Dynamic Functional Network Connectivity (dFNC) to establish a comprehensive disease atlas for DPD. We compared the brain's dynamic states between DPDs and HCs using ANACOVA tests, assessed correlations with patient experiences and symptomatology through Spearman correlation analysis, and examined the tDCS effect via paired t-tests. Results We identified distinct brain networks corresponding to the Frontoparietal Network (FPN), the Sensorimotor Network (SMN), and the Default Mode Network (DMN) in DPD using group Independent Component Analysis (ICA). Additionally, we discovered four distinct dFNC states, with State-1 displaying significant differences between DPD and HC groups (F = 4.10, P = 0.045). Correlation analysis revealed negative associations between the dwell time of State-2 and various clinical assessment factors. Post-tDCS analysis showed a significant change in the mean dwell time for State-2 in responders (t-statistic = 4.506, P = 0.046), consistent with previous clinical assessments. Conclusions Our study suggests the brain dynamics of DPD could be a potential biomarker for diagnosis and symptom analysis, which potentially leads to more personalized and effective treatment strategies for DPD patients. Trial registrations The trial was registered at the Chinese Clinical Trial Registry on 03/01/2021 (Registration number: ChiCTR2100041741, https://www.chictr.org.cn/showproj.html?proj=66731 ) before the trial.

Abstract Depersonalization/derealization disorder (DPD) is a prevalent yet inadequately understood clinical condition characterized by a recurrent or persistent sense of unreality. This study aims to provide insight into DPD through descriptive and comparative analyses involving a large group of Chinese participants. The socio-demographic details (age, gender proportion, education, occupational status, marital status), depersonalized and dissociative symptom characteristics (symptomatic factors or subscales of the Cambridge Depersonalization Scale and the Dissociative Experiences Scale), development trajectory (age of onset, potential precipitating factors, course characteristics), treatment history (duration of delayed healthcare attendance, duration of delayed diagnosis, previous diagnoses), and adverse childhood experiences of the DPD patients are presented. Comparisons of anxiety and depressive symptoms, alongside psychosocial functioning, between DPD participants and those diagnosed with generalized anxiety disorder, bipolar disorders, and major depressive disorder were conducted. The analysis highlights a higher male preponderance and early onset of DPD, symptomatology marked by derealization, notable impairment in psychosocial functioning, and prolonged periods of delayed healthcare attendance and diagnosis associated with symptom severity. Furthermore, noteworthy relationships between adverse childhood experiences and symptom levels were identified. The findings substantiate the view that DPD is a serious but neglected mental disorder, urging initiatives to improve the current condition of DPD patients.

As the most widely distributed scavenger birds on the Qinghai-Tibetan Plateau, Himalayan vultures (Gyps himalayensis) feed on the carcasses of various wild and domestic animals, facing the dual selection pressure of pathogens and antibiotics and are suitable biological sentinel species for monitoring antibiotic resistance genes (ARGs). This study used metagenomic sequencing to comparatively investigate the ARGs and mobile genetic elements (MGEs) of wild and captive Himalayan vultures. Overall, the resistome of Himalayan vultures contained 414 ARG subtypes resistant to 20 ARG types, with abundances ranging from 0.01 to 1,493.60 ppm. The most abundant resistance type was beta-lactam (175 subtypes), followed by multidrug resistance genes with 68 subtypes. Decreases in the abundance of macrolide-lincosamide-streptogramin (MLS) resistance genes were observed in the wild group compared with the zoo group. A total of 75 genera (five phyla) of bacteria were predicted to be the hosts of ARGs in Himalayan vultures, and the clinical (102 ARGs) and high-risk ARGs (35 Rank I and 56 Rank II ARGs) were also analyzed. Among these ARGs, twenty-two clinical ARGs, nine Rank I ARG subtypes, sixteen Rank II ARG subtypes were found to differ significantly between the two groups. Five types of MGEs (128 subtypes) were found in Himalayan vultures. Plasmids (62 subtypes) and transposases (44 subtypes) were found to be the main MGE types. Efflux pump and antibiotic deactivation were the main resistance mechanisms of ARGs in Himalayan vultures. Decreases in the abundance of cellular protection were identified in wild Himalayan vultures compared with the captive Himalayan vultures. Procrustes analysis and the co-occurrence networks analysis revealed different patterns of correlations among gut microbes, ARGs, and MGEs in wild and captive Himalayan vultures. This study is the first step in describing the characterization of the ARGs in the gut of Himalayan vultures and highlights the need to pay more attention to scavenging birds.

The traveling salesman problem (TSP) is a classic non-deterministic polynomial-hard (NP-hard) problem. Currently, almost all the research works utilizing Transformers to solve TSP problems employ supervised learning. However, it is extremely challenging to obtain accurate solution labels for the model in large-scale instances, resulting in a severe lack of scale generalization capability. Recent research combines knowledge distillation and Transformer to effectively address the distribution generalization issue. Nonetheless, if the framework is directly applied to the problem of scale generalization, the solution is not satisfactory. To address the aforementioned issues, we propose an adaptive soft probability distributed distillation (ASPDD) framework to improve Transformer scale generalization capability. The ASPDD framework uses a soft probability distributed distillation (SPDD) method to improve the knowledge interaction between the student and teacher models. In particular, ASPDD introduces an adaptive selection strategy, so that the student model can find weak points for improvement training in each training. This framework is utilized for training a model for a small-scale instance (TSP20) and deploying it to a large-scale instance. Extensive benchmarking (10000 instances) demonstrates that our ASPDD framework can achieve competitive results as compared to other Transformer baseline models and knowledge distillation frameworks. In addition, the ASPDD framework is applied to eleven publicly accessible benchmark datasets (TSPLIB). On six benchmark datasets, the experimental results demonstrate that our ASPDD framework outperforms previous knowledge distillation models.

Background: Significant progress has been achieved in the management of multiple myeloma (MM) by implementing high-dose therapy and stem cell transplantation. Moreover, the prognosis of patients has been enhanced due to the introduction of novel immunomodulatory drugs and the emergence of new targeted therapies. However, predicting the survival rates of patients with multiple myeloma is still tricky. According to recent researches, platelets have a significant impact in affecting the biological activity of tumors and are essential parts of the tumor microenvironment. Nonetheless, it is still unclear how platelet-related genes (PRGs) connect to the prognosis of multiple myeloma.Methods: We analyzed the expression of platelet-related genes and their prognostic value in multiple myeloma patients in this study. We also created a nomogram combining clinical metrics. Furthermore, we investigated disparities in the biological characteristics, immunological microenvironment, and reaction to immunotherapy, along with analyzing the drug susceptibility within diverse risk groups.Results: By using the platelet-related risk model, we were able to predict patients’ prognosis more accurately. Subjects in the high-risk cohort exhibited inferior survival outcomes, both in the training and validation datasets, as compared to those in the low-risk cohort (p < 0.05). Moreover, there were differences in the immunological microenvironments, biological processes, clinical features, and chemotherapeutic drug sensitivity between the groups at high and low risk. Using multivariable Cox regression analyses, platelet-related risk score was shown to be an independent prognostic influence in MM (p < 0.001, hazard ratio (HR) = 2.001%, 95% confidence interval (CI): 1.467–2.730). Furthermore, the capacity to predict survival was further improved when a combined nomogram was utilized. In training cohort, this outperformed the predictive value of International staging system (ISS) alone from a 5-years area under curve (AUC) = 0.668 (95% CI: 0.611–0.725) to an AUC = 0.721 (95% CI: 0.665–0.778).Conclusion: Our study revealed the potential benefits of PRGs in terms of survival prognosis of MM patients. Furthermore, we verified its potential as a drug target for MM patients. These findings open up novel possibilities for prognostic evaluation and treatment choices for MM.

PurposeTo assess the prognostic significance of β2-microglobulin decline index (β2M DI) in multiple myeloma (MM).Methods150 MM patients diagnosed with MM were enrolled in this study. Cox proportional hazards model was used to analyze the uni- and multivariate prognosis in training cohort (n=105). A new combined prognostic model containing β2M DI was built up based on the data in training cohort. The validation group was used to verify the model.Resultsβ2M DI showed significant correlation with prognosis in both uni- and multivariate analyses and had a good correlation with complete response (CR) rate and deep remission rate. The ROC and calibration curves in validation cohort (n=45) indicated a good predictive performance of the new model. Based on the median risk score of the training group, we classified patients into high- and low- risk groups. In both training and validation groups, patients in the low-risk group had longer overall survival (OS) time than that in the high-risk group (p

Sensing the lowering of endoplasmic reticulum (ER) calcium (Ca2+), STIM1 mediates a ubiquitous Ca2+ influx process called the store-operated Ca2+ entry (SOCE). Dysregulated STIM1 function or abnormal SOCE is strongly associated with autoimmune disorders, atherosclerosis, and various forms of cancers. Therefore, uncovering the molecular intricacies of post-translational modifications, such as oxidation, on STIM1 function is of paramount importance. In a recent proteomic screening, we identified three protein disulfide isomerases (PDIs)—Prolyl 4-hydroxylase subunit beta (P4HB), protein disulfide-isomerase A3 (PDIA3), and thioredoxin domain-containing protein 5 (TXNDC5)—as the ER-luminal interactors of STIM1. Here, we demonstrated that these PDIs dynamically associate with STIM1 and STIM2. The mutation of the two conserved cysteine residues of STIM1 (STIM1-2CA) decreased its Ca2+ affinity both in cellulo and in situ. Knockdown of PDIA3 or P4HB increased the Ca2+ affinity of wild-type STIM1 while showing no impact on the STIM1-2CA mutant, indicating that PDIA3 and P4HB regulate STIM1’s Ca2+ affinity by acting on ER-luminal cysteine residues. This modulation of STIM1’s Ca2+ sensitivity was further confirmed by Ca2+ imaging experiments, which showed that knockdown of these two PDIs does not affect STIM1-mediated SOCE upon full store depletion but leads to enhanced SOCE amplitudes upon partial store depletion. Thus, P4HB and PDIA3 dynamically modulate STIM1 activation by fine-tuning its Ca2+ binding affinity, adjusting the level of activated STIM1 in response to physiological cues. The coordination between STIM1-mediated Ca2+ signaling and redox responses reported herein may have implications for cell physiology and pathology.

The development of education should serve the needs of economic and social development by providing high-quality and appropriate professionals for economic development. Recently, the implementation of Double High Plan has provided many opportunities for the cultivation of high-level professional groups. In the process of professional group construction, the extent of coupling between the level of professional group construction and the level of regional economic clusters is an important evaluation. This work is based on the list of proposed projects for the construction of high-level professional clusters in Guangdong Province between 2019 and 2021. This list is issued by the department of education of Guangdong Province. The quantitative indicators and coupling models are established to estimate the degree of coupling between the construction of professional clusters in 9 prefecture-level cities located in the Pearl River Delta region and the level of regional industrial clusters. The results presented in this work show that the professional cluster construction and industrial construction level of four prefecture-level cities, including Guangzhou, Shenzhen, Foshan, and Dongguan, achieve coordinated development, while the remaining areas are mostly in transformation and integration stages. This is because the development level of industrial clusters has surpassed the construction of professional clusters in universities, resulting in a mismatch between talent cultivation and the requirements of economic development. This mismatch is manifested in three aspects. First, the supply and demand do not align in terms of the scale of professional groups and industrial clusters. Second, insufficient integration of professional clusters and industrial clusters. Finally, this mismatch is evident in imbalanced resource allocation. The fit between the setting of professional clusters and the structure of industrial clusters is not high. Based on the aforementioned analysis, this work presents suggestions for promoting the integration of industry and education and school-enterprise cooperation among universities in the Pearl River Delta region. This will eventually enhance the construction of high-level professional groups in the Pearl River Delta region and result in coordinated economic and social development.

The progress of communication technology and the Internet has made the dual-channel supply chain have great development. Supply chain members have to compete and cooperate with other enterprises on the chain in order to obtain greater self-benefit. In the competitive-cooperative relationship among enterprises, price discrimination and sales effort are common tools of operation, and Nash equilibrium theory is a common strategy in the process of supply chain game. Whether manufacturers can promote retailers to implement sales efforts through price discrimination and ensure that the overall revenue of the supply chain is improved at the Nash equilibrium is great significance to both the supply chain and individual enterprises. This paper constructs a decentralized dual-channel supply chain mathematical model composed of an independent manufacturer, an offline retailer, and an online retailer, taking into account the impact of the offline retailer’s sales efforts on his demand and its positive external for the other channel. The revenue matrix of retailers’ decisions about whether or not to pay their sales efforts is built under the condition that manufacturers charge different wholesale prices to different retailers and solves the condition of every decision combination becoming the Nash equilibrium using the Nash equilibrium game theory. Finally, the optimal pricing strategy of the manufacturers is analysed to get the constraints of this dual-channel supply chain achieving Pareto improvement when manufacturer uses wholesale price discrimination strategy.

In recent years, the swift growth of industrialization and globalization has exacerbated serious problems, such as climate change resulting from carbon emissions. As the largest carbon emitter globally, China is striving to explore a low-carbon economic transition path to alleviate environmental issues and ensure long-term development. The relevance of investing in green projects is highlighted in the UN's Sustainable Development Goals. Exploring the effects of green investments on carbon emissions by Chinese companies and the dynamics between the two is crucial for China’s green transition. This study investigates whether companies can reduce their carbon emissions per unit of activity by investing in green projects. Additionally, it evaluates how management decisions influence the effectiveness of these investments in reducing emissions. The study samples firms from the Stock exchanges in Shanghai and Shenzhen for the period 2010–2020. Data are obtained from the China Stock Market and Accounting Research (CSMAR) and DIB, etc. Findings indicate that firms can reduce their corporate carbon emissions by increasing their green investments. Furthermore, factors like management shareholding, etc help strengthen the link between corporate green investment and carbon intensity. This study not only enhance the theoretical comprehension of the link between green investment and carbon emission reduction but also enriches stakeholder theory. The instrumental role of management in urging firms to decrease their carbon emissions via green investments is evident in practice, offering a roadmap for businesses to prioritize green investment choice and create a pathway to a carbon-neutral economy.

Background: One particular type of cellular death that is known as ferroptosis is caused by the excessive lipid peroxidation. It is a regulated form of cell death that can affect the response of the tumor cells. Currently, it is not known if the presence of this condition can affect the prognosis of patients with multiple myeloma (MM).Methods: In this study, we studied the expression differences and prognostic value of ferroptosis-related genes (FRGs) in MM, and established a ferroptosis risk scoring model. In order to improve the prediction accuracy and clinical applicability, a nomogram was also established. Through gene enrichment analysis, pathways closely related to high-risk groups were identified. We then explored the differences in risk stratification in drug sensitivity and immune patterns, and evaluated their value in prognostic prediction and treatment response. Lastly, we gathered MM cell lines and samples from patients to confirm the expression of marker FRGs using quantitative real-time PCR (qRT-PCR).Results: The ability to predict the survival of MM patients is a challenging issue. Through the use of a risk model derived from ferroptosis, we were able to develop a more accurate prediction of the disease’s prognosis. They were then validated by a statistical analysis, which showed that the model is an independent factor in the prognosis of MM. Patients of high ferroptosis risk scores had a much worse chance of survival than those in the low-risk groups. The calibration and power of the nomogram were also strong. We noted that the link between the ferroptosis risk score and the clinical treatment was suggested by the FRG’s significant correlation with the immune checkpoint genes and the medication sensitivity. We validated the predictive model using qRT-PCR.Conclusion: We demonstrated the association between FRGs and MM, and developed a new risk model for prognosis in MM patients. Our study sheds light on the potential clinical relevance of ferroptosis in MM and highlights its potential as a therapeutic target for patients with this disease.

IntroductionHimalayan vultures (Gyps hinalayensis) are widely distributed on the Qinghai-Tibetan Plateau and play a crucial role in maintaining the ecological balance by feeding on decayed corpses of wild and domestic animals. Large-scale culture and metagenomics studies have broadened our understanding of viral diversity in animals’ gastrointestinal tracts. However, despite the importance of gut viral communities in regulating bacterial diversity and performing symbiotic functions, no gut viral study has been conducted on Himalayan vultures. Furthermore, the impact of captivity on the gut virome of these vultures remains unknown.MethodsIn this study, metagenomic sequencing methods targeting DNA of virus-like particles enriched from feces were used to characterize the gut DNA viromes of wild and captive Himalayan vultures.ResultsIn total, 22,938 unique viral operational taxonomic units (vOTUs) were identified and assigned to 140 viral genera in 41 viral families. These families included viruses associated with bacteria, animals, plants, insects, and archaea. Phage communities, including Siphoviridae, Microviridae, Myoviridae, Inoviridae, and Herelleviridae, dominated the gut virome of Himalayan vultures. Wild vultures exhibited higher viral richness and diversity compared with those in captivity. The functional capacity of the gut virome was characterized by identifying 93 KEGG pathways, which were significantly enriched in metabolism and genetic information processing. Abundant auxiliary metabolic genes, such as carbohydrate-active enzyme, and antibiotic resistance genes, were also found in the vultures’ gut virome.DiscussionOur findings reveal the complex and diverse viral community present in the gut virome of Himalayan vultures, which varies between wild, and captive states. The DNA virome dataset establishes a baseline for the vultures’ gut virome and will serve as a reference for future virus isolation and cultivation. Understanding the impact of captivity on the gut virome contributes to our knowledge of vultures’ response to captivity and aids in optimizing their rehabilitation and implementing protective measures.

IntroductionTo date, there is no conclusive evidence for early interventions on ultra-high risk (UHR) for psychosis. The Chinese herbal medicine is confirmed to be beneficial in improving psychiatric symptoms and cognitive impairments for schizophrenia patients. However, the effect of Chinese herbal medicine on treating UHR patients remains unknown.MethodsEighty UHR patients were recruited from the outpatient department. They were randomly assigned to receive either Shi-Zhen-An-Shen herbal formula granule (SZAS-HFG) combined with aripiprazole placebo or aripiprazole combined with SZAS-HFG placebo for a 12-week treatment. The psychiatric symptoms were assessed using the Structured Interview for Prodromal Syndromes (SIPS). The Trail Making Test part A (TMT-A), Brief Visuospatial Memory Test (BVMT), Hopkins Verbal Learning Test (HVLT), and Continuous Performance Test (CPT) were used to assess cognitive functions. we also employed the Global Assessment of Functioning (GAF) to evaluate social functioning. The linear mixed-effects models were performed to detect the difference in effectiveness between the two groups.ResultsAfter 12-week treatment, both groups showed significant effects of time on SIPS, TMT-A, HVLT, BVMT, and GAF. There was a significant effect of group only on CPT. Moreover, we also found a significant interaction effect on GAF.ConclusionSZAS-HFG can effectively alleviate psychosis symptoms, and improve cognitive impairments and overall functioning as well as aripiprazole.Clinical trial registration: Chinese Clinical Trial Registry, ChiCTR-IOR-17013513.

Background: Metabolic reprogramming is an important hallmark of cancer. Glycolysis provides the conditions on which multiple myeloma (MM) thrives. Due to MM’s great heterogeneity and incurability, risk assessment and treatment choices are still difficult.Method: We constructed a glycolysis-related prognostic model by Least absolute shrinkage and selection operator (LASSO) Cox regression analysis. It was validated in two independent external cohorts, cell lines, and our clinical specimens. The model was also explored for its biological properties, immune microenvironment, and therapeutic response including immunotherapy. Finally, multiple metrics were combined to construct a nomogram to assist in personalized prediction of survival outcomes.Results: A wide range of variants and heterogeneous expression profiles of glycolysis-related genes were observed in MM. The prognostic model behaved well in differentiating between populations with various prognoses and proved to be an independent prognostic factor. This prognostic signature closely coordinated with multiple malignant features such as high-risk clinical features, immune dysfunction, stem cell-like features, cancer-related pathways, which was associated with the survival outcomes of MM. In terms of treatment, the high-risk group showed resistance to conventional drugs such as bortezomib, doxorubicin and immunotherapy. The joint scores generated by the nomogram showed higher clinical benefit than other clinical indicators. The in vitro experiments with cell lines and clinical subjects further provided convincing evidence for our study.Conclusion: We developed and validated the utility of the MM glycolysis-related prognostic model, which provides a new direction for prognosis assessment, treatment options for MM patients.

As a comprehensive secondary prevention program, cardiac rehabilitation (CR) is a beneficial and cost-effective intervention for patients with heart disease, but the participation rate of patients in CR is low globally. In recent years, due to the COVID-19 pandemic and scientific and technological advances, an increasing number of alternative CR modes have been developed, such as remote CR, home-based CR, hybrid CR and virtual CR. These alternative CR modes represent changes and new opportunities for patients with heart disease. In this review, we will discuss in detail the impact of CR on patients with different types of heart disease, review the various alternative CR models, and explore some prospects for the future of CR in the field of heart disease.

Previous studies suggest a close relationship between self-disorders and schizophrenia or unipolar depression. However, few studies have explored the characteristics of self-processing in bipolar disorder (BD) during different clinical states. This study compared the differences in self-face recognition (SFR) among patients with bipolar mania (BPM), bipolar depression (BPD), bipolar remission (RM), and healthy controls (HC). Images of subject's own face, a familiar face, and an unfamiliar face were combined in pairs at a certain proportion to obtain three types of blended images. We then compared the tendency between BD and HC while judging two kinds of blended faces emerging from presentation software. The results showed that the BPM and BPD groups seemed to lack an advantage in self-recognition. Self-processing and familiarity processing were significantly enhanced in BPM patients, while only familiarity processing was enhanced in BPD. The severity of clinical symptoms was not significantly correlated with self-bias or familiarity bias in BD.

Background: Cuproptosis is a newly identified unique copper-triggered modality of mitochondrial cell death, distinct from known death mechanisms such as necroptosis, pyroptosis, and ferroptosis. Multiple myeloma (MM) is a hematologic neoplasm characterized by the malignant proliferation of plasma cells. In the development of MM, almost all patients undergo a relatively benign course from monoclonal gammopathy of undetermined significance (MGUS) to smoldering myeloma (SMM), which further progresses to active myeloma. However, the prognostic value of cuproptosis in MM remains unknown.Method: In this study, we systematically investigated the genetic variants, expression patterns, and prognostic value of cuproptosis-related genes (CRGs) in MM. CRG scores derived from the prognostic model were used to perform the risk stratification of MM patients. We then explored their differences in clinical characteristics and immune patterns and assessed their value in prognosis prediction and treatment response. Nomograms were also developed to improve predictive accuracy and clinical applicability. Finally, we collected MM cell lines and patient samples to validate marker gene expression by quantitative real-time PCR (qRT-PCR).Results: The evolution from MGUS and SMM to MM was also accompanied by differences in the CRG expression profile. Then, a well-performing cuproptosis-related risk model was developed to predict prognosis in MM and was validated in two external cohorts. The high-risk group exhibited higher clinical risk indicators. Cox regression analyses showed that the model was an independent prognostic predictor in MM. Patients in the high-risk group had significantly lower survival rates than those in the low-risk group (p < 0.001). Meanwhile, CRG scores were significantly correlated with immune infiltration, stemness index and immunotherapy sensitivity. We further revealed the close association between CRG scores and mitochondrial metabolism. Subsequently, the prediction nomogram showed good predictive power and calibration. Finally, the prognostic CRGs were further validated by qRT-PCR in vitro.Conclusion: CRGs were closely related to the immune pattern and self-renewal biology of cancer cells in MM. This prognostic model provided a new perspective for the risk stratification and treatment response prediction of MM patients.

Abstract Background Himalayan Griffons (Gyps himalayensis), large scavenging raptors widely distributed in Qinghai-Tibetan Plateau, have evolved a remarkable ability to feed on carcasses without suffering any adverse effects. The gut microbiome plays an important role in animal physiological and pathological processes, and has also been found to play a health protective role in the vulture adaptation to scavenging. However, the microbial taxonomic diversity (including nonculturable and culturable microbes), functions, and metabolites related to Himalayan Griffons have not been fully explored. Methods In the present study, the 28 fecal samples of the Himalayan Griffons and 8 carrion samples were collected and sequenced using high-throughput 16S rRNA gene sequencing methods to analyze the composition and functional structures of the microbiomes. Twelve fecal samples of the Himalayan Griffons were analyzed using untargeted Liquid Chromatography Mass Spectroscopy (LC–MS) to identify metabolites. We used different culture conditions to grow Himalayan Griffons gut microbes. Inhibitory effects of gut beneficial bacteria on 5 common pathogenic bacteria were also tested using the Oxford cup method. Results According to the results of the culture-independent method, a high abundance of four major phyla in Himalayan Griffons were identified, including Fusobacteria, Firmicutes, Bacteroidetes, and Proteobacteria. The most abundant genera were Fusobacterium, followed by Clostridium_sensu_stricto_1, Cetobacterium, Epulopiscium, and Bacteroides. The predicted primary functional categories of the Himalayan Griffons’ gut microbiome were associated with carbohydrate and amino acid metabolism, replication and repair, and membrane transport. LC–MS metabolomic analysis showed a total of 154 metabolites in all the fecal samples. Cultivation yielded 184 bacterial isolates with Escherichia coli, Enterococcus faecium, Enterococcus hirae, and Paeniclostridium sordellii as most common isolates. Moreover, 7 potential beneficial gut bacteria isolated showed certain inhibition to 5 common pathogenic bacteria. Conclusions Our findings broaden and deepen the understanding of Himalayan Griffons’ gut microbiome, and highlighted the importance of gut microbiome-mediated adaptation to scavenging habits. In particular, our results highlighted the protective role of gut beneficial bacteria in the Himalayan Griffons against pathogenic bacteria that appear in rotten food resources.

IntroductionAbnormalities of the cerebellum have been displayed to be a manifestation of schizophrenia (SCH) which is a detrimental psychiatric disorder. It has been recognized that the cerebellum contributes to motor function, sensorimotor function, cognition, and other brain functions in association with cerebral functions. Multiple studies have observed that abnormal alterations in cerebro-cerebellar functional connectivity (FC) were shown in patients with SCH. However, the FC of cerebellar networks in SCH remains unclear.MethodsIn this study, we explored the FC of cerebellar networks of 45 patients with first-episode SCH and 45 healthy control (HC) subjects by using a defined Yeo 17 network parcellation system. Furthermore, we performed a correlation analysis between cerebellar networks’ FC and positive and negative symptoms in patients with first-episode SCH. Finally, we established the classification model to provide relatively suitable features for patients with first-episode SCH concerning the cerebellar networks.ResultsWe found lower between-network FCs between 14 distinct cerebellar network pairs in patients with first-episode SCH, compared to the HCs. Significantly, the between-network FC in N2-N15 was positively associated with positive symptom severity; meanwhile, N4-N15 was negatively associated with negative symptom severity. Besides, our results revealed a satisfactory classification accuracy (79%) of these decreased between-network FCs of cerebellar networks for correctly identifying patients with first-episode SCH.ConclusionConclusively, between-network abnormalities in the cerebellum are closely related to positive and negative symptoms of patients with first-episode SCH. In addition, the classification results suggest that the cerebellar networks can be a potential target for further elucidating the underlying mechanisms in first-episode SCH.

IntroductionAccumulating evidence has shown that acupuncture could significantly improve the sleep quality and cognitive function of individuals suffering from insufficient sleep. Numerous animal studies have confirmed the effects and mechanisms of acupuncture on acute sleep deprivation (SD). However, the role of acupuncture on individuals after acute SD remains unclear.MethodsIn the current study, we recruited 30 healthy subjects with regular sleep. All subjects received resting-state fMRI scans during the rested wakefulness (RW) state and after 24 h of total SD. The scan after 24 h of total SD included two resting-state fMRI sessions before and after needling at Shenmen (HT7). Both edge-based and large-scale network FCs were calculated.ResultsThe edge-based results showed the suprathreshold edges with abnormal between-network FC involving all paired networks except somatosensory motor network (SMN)-SCN between the SD and RW state, while both decreased and increased between-network FC of edges involving all paired networks except frontoparietal network (FPN)-subcortical network (SCN) between before and after acupuncture at HT7. Compared with the RW state, the large-scale brain network results showed decreased between-network FC in SMN-Default Mode Network (DMN), SMN-FPN, and SMN-ventral attention network (VAN), and increased between-network FC in Dorsal Attention Network (DAN)-VAN, DAN-SMN between the RW state and after 24 h of total SD. After acupuncture at HT7, the large-scale brain network results showed decreased between-network FC in DAN-VAN and increased between-network FC in SMN-VAN.ConclusionAcupuncture could widely modulate extensive brain networks and reverse the specific between-network FC. The altered FC after acupuncture at HT7 may provide new evidence to interpret neuroimaging mechanisms of the acupuncture effect on acute SD.

With the rapid development of global industrialization and modernization, carbon emissions have brought about serious climate warming and environmental pollution problems. Chinese enterprises, as the major players in carbon emissions, are important in terms of promoting the green transformation of the economy. It is particularly important to investigate the relationship and mechanism of action between carbon emission reduction and corporate sustainable development in Chinese enterprises. This study aims to determine whether reducing the intensity of carbon emissions can make businesses more sustainable and to analyze the moderating influences of government environmental subsidies, media monitoring, and executives’ green opinions on the link between the two variables. The study sample consists of Shanghai and Shenzhen A-shares data from 2015 to 2020, and a fixed-effects model is employed for analysis. Data were obtained from the China Stock Market & Accounting Research database, the Financial News Database of Listed Companies, and enterprise financial statement notes, etc. Stata17.0 was used to clean and analyze the data. The results indicate that businesses can greatly improve their long-term viability by lowering their carbon emissions. Additionally, government environmental subsidies, media monitoring, and executives’ green perceptions all enhance the correlation between corporate sustainability and reduce carbon emission intensity. This study not only enriches the relationship between environmental governance and sustainable development from a theoretical perspective, but also further expands the stakeholder theory. It also finds the mechanism of the role of the government and media on corporate carbon emissions for sustainable development in practice, which provides effective guidance to accelerate the promotion of carbon emission reduction and, thus, the sustainable development of Chinese enterprises.

Existing optogenetic methods to induce calcium mobilisation lack selectivity and specificity. Here, the authors design and engineer a single-component light-operated calcium channel to provide optical control over calcium signals and calcium-dependent physiological responses: LOCa.

Introduction: Non-invasive brain stimulation (NIBS) techniques have been widely used for the purpose of improving clinical symptoms of schizophrenia. However, the ambiguous stimulation targets may limit the efficacy of NIBS for schizophrenia. Exploring effective stimulation targets may improve the clinical efficacy of NIBS in schizophrenia.Methods: We first conducted a neurosynth-based meta-analysis of 715 functional magnetic resonance imaging studies to identify schizophrenia-related brain regions as regions of interest. Then, we performed the resting-state functional connectivity analysis in 32 patients with first-episode schizophrenia to find brain surface regions correlated with the regions of interest in three pipelines. Finally, the 10–20 system coordinates corresponding to the brain surface regions were considered as potential targets for NIBS.Results: We identified several potential targets of NIBS, including the bilateral dorsal lateral prefrontal cortex, supplementary motor area, bilateral inferior parietal lobule, temporal pole, medial prefrontal cortex, precuneus, superior and middle temporal gyrus, and superior and middle occipital gyrus. Notably, the 10-20 system location of the bilateral dorsal lateral prefrontal cortex was posterior to F3 (F4), not F3 (F4).Conclusion: Conclusively, our findings suggested that the stimulation locations corresponding to these potential targets might help clinicians optimize the application of NIBS therapy in individuals with schizophrenia.

The self-perception or self-experience of patients with depersonalization/derealization disorder (DPD) is altered, leading to a profound disruption in self-awareness. The main aim of the study is to explore the characteristics of subliminal self-face processing in DPD patients. To our knowledge, this is the first experimental study that has measured and evaluated subliminal self-processing in DPD. To better understand this, we examined the ability of patients with DPD and healthy controls (HC) to identify pictures of faces using an experimental paradigm of breaking continuous flash suppression. There were 23 DPD outpatients from Beijing Anding Hospital, Capital Medical University and 23 matched HC who participated in this experiment. The time needed for a face to break into awareness was taken as the measure of participants’ subliminal processing of that face. The results indicated that there were significant differences between the DPD patients and HC in subliminal reaction times to different faces. Under experimental conditions, the average reaction response of self-face recognition in the HC group was significantly faster than for a famous face. However, this difference was not observed in DPD patients, which means that DPD patients did not show the processing advantage of their own faces as did the HC. The results suggest a deficit in subliminal self-face processing in DPD.

Summary: Store-operated calcium release-activated calcium (CRAC) channels mediate a variety of cellular signaling functions. The CRAC channel pore-forming protein, Orai1, is a hexamer arranged with 3-fold symmetry. Despite its importance in moving Ca2+ ions into cells, a detailed mechanistic understanding of Orai1 activation is lacking. Herein, a working model is proposed for the putative open state of Orai from Drosophila melanogaster (dOrai), which involves a “twist-to-open” gating mechanism. The proposed model is supported by energetic, structural, and experimental evidence. Fluorescent imaging demonstrates that each subunit on the intracellular side of the pore is inherently strongly cross-linked, which is important for coupling to STIM1, the pore activator, and graded activation of the Orai1 channel. The proposed model thus paves the way for understanding key aspects of calcium signaling at a molecular level. : Biological Sciences; Molecular Biology; Structural Biology Subject Areas: Biological Sciences, Molecular Biology, Structural Biology

Introduction: Non-invasive brain stimulation seems to be beneficial for DPD patients. However, the sites used in previous studies were empirical. Exploring new stimulation locations via functional magnetic resonance imaging may improve the efficacy. Objectives: The objective was to find potential locations for non-invasive brain stimulation on the depersonalization-derealization disorder. Methods: We explored the potential brain surface regions from three pipelines: pipeline 1: activation likelihood estimation meta-analysis (five studies with 36 foci included); pipeline 2: functional connectivity analysis based on DPD-network (76 subjects included); and pipeline 3: functional connectivity analysis based on DPD regions of interest from the meta-analysis. Potential targets were the 10–20 system coordinates for brain surface regions. Results: We identified several potential brain surface regions, including the bilateral medial prefrontal cortex, dorsal lateral prefrontal cortex, superior parietal gyrus, superior temporal gyrus, and right ventrolateral prefrontal cortex as potential sites. Conclusion: Our findings of the potential stimulation targets might help clinicians optimize the application of non-invasive brain stimulation therapy in individuals with DPD.

The reasonable distribution of revenue determines not only the coordination but also the development of supply chain. A hybrid channel supply chain model composed of manufacturer and traditional and online retailers was identified as the object of study, decision models under different cooperation modes were built, different revenues of supply chain members and overall were analyzed, satisfaction of characteristic function required by the Shapley value was proved, and the Shapley values of revenue distribution were calculated. In view of the shortcoming of the Shapley value method which takes contribution margin as the only consideration and ignores the impact of other factors such as cost on revenue distribution, the cost correction model was built by using production and sales cost to modify the traditional Shapley value; the reasonable distribution of individual benefits under the premise of maximizing the overall revenue of hybrid channel supply chain was realized.

Objective: To evaluate whether radiomic features extracted from intra and peri-nodular lesions can enhance the ability to differentiate between invasive adenocarcinoma (IA), minimally invasive adenocarcinoma (MIA), and adenocarcinoma in situ (AIS) manifesting as ground-glass nodule (GGN).Materials and Methods: This retrospective study enrolled 120 patients with a total of 121 pathologically confirmed lung adenocarcinomas (85 IA and 36 AIS/MIA) from January 2015 to May 2019. The recruited patients were randomly divided into training (84 nodules) and validation sets (37 nodules), with a ratio of 7:3. The minority group in the training set was balanced by the synthetic minority over-sampling (SMOTE) method. The intra-, peri-nodular, and gross region of interests (ROI) were delineated with manual annotation. Image features were quantitatively extracted from each ROI on CT images. The minimum redundancy maximum relevance (mRMR) feature ranking method and the least absolute shrinkage and selection operator (LASSO) classifier were used to eliminate unnecessary features. The intra- and peri-nodular radiomic features were combined to produce the gross radiomic signature. A combined clinical-radiomic model was constructed by multivariable logistic regression analysis. The predicted performances of different models were evaluated using receiver operating curve (ROC) and calibration curve.Results: The gross radiomic signature (AUC: training set = 0.896; validation set = 0.876) showed a good ability to discriminate the invasiveness of adenocarcinoma, comparing to intra-nodular (AUC: training set = 0.862; validation set = 0.852) or peri-nodular radiomic signature (AUC: training set = 0.825; validation set = 0.820). The AUC of the combined clinical-radiomic model was 0.917 for the training and 0.876 for the validation cohort, respectively.Conclusions: The gross radiomic signature of intra- and peri-nodular regions improved the prediction ability and aided predicting the invasiveness of lung adenocarcinoma appearing as GGN.

For a MIMO downlink system with finite-bit feedback,combined with the Golden code and the precoding technology,a new precoding design criterion and its related codeword selection method,transmissionschemes and corresponding low complexity decoding methods were proposed.In fact,based on fully utilizing the characteristics that the Golden code could overcome the channel depth fading,a double precoding matrix was constructed as transmission signals by using the selected precoding codeword,so that the decoding complexity could be reduced to linear.In the meantime,a joint ML and MMSE decoding method was proposed for the traditional transmission scheme,which could dynamically adjust the decoding complexity based on a threshold.The numerical simulation results confirm the superiority of the proposed schemes and methods.

Stromal interaction molecule 1 (STIM1) monitors ER-luminal Ca2 + levels to maintain cellular Ca2 + balance. Here the authors find that the STIM1 luminal domain monomer has multiple Ca2 + - binding sites which set the threshold for physiological activation of STIM1 in cells.

Abstract Background Because phylogenetic inference is an important basis for answering many evolutionary problems, a large number of algorithms have been developed. Some of these algorithms have been improved by integrating gene evolution models with the expectation of accommodating the hierarchy of evolutionary processes. To the best of our knowledge, however, there still is no single unifying model or algorithm that can take all evolutionary processes into account through a stepwise or simultaneous method. Results On the basis of three existing phylogenetic inference algorithms, we built an integrated pipeline for inferring the evolutionary history of a given gene family; this pipeline can model gene sequence evolution, gene duplication-loss, gene transfer and multispecies coalescent processes. As a case study, we applied this pipeline to the STIMATE (TMEM110) gene family, which has recently been reported to play an important role in store-operated Ca2+ entry (SOCE) mediated by ORAI and STIM proteins. We inferred their phylogenetic trees in 69 sequenced chordate genomes. Conclusions By integrating three tree reconstruction algorithms with diverse evolutionary models, a pipeline for inferring the evolutionary history of a gene family was developed, and its application was demonstrated.

Biocompatible and biodegradable poly(lactic-co-glycolic acid) (PLGA) has been approved by the US Food and Drug Administration and has frequently been used to develop potential vaccine delivery systems. The immunoregulation and immunopotentiation of Chinese yam polysaccharide (CYP) have been widely demonstrated. In the current study, cell uptake mechanisms in dendritic cells (DCs) were monitored in vitro using confocal laser scanning microscopy, transmission electron microscopy, and flow cytometry. To study a CYP-PLGA nanoparticle-adjuvanted delivery system, CYP and ovalbumin (OVA) were encapsulated in PLGA nanoparticles (CYPPs) to act as a vaccine, and the formulation was tested in immunized mice. The CYPPs more easily underwent uptake by DCs in vitro, and CYPP/OVA could stimulate more effective antigen-specific immune responses than any of the single-component formulations in vivo. Mice immunized using CYPP/OVA exhibited more secretion of OVA-specific IgG antibodies, better proliferation, and higher cytokine secretion by splenocytes and significant activation of CD3+CD4+ and CD3+CD8+ T cells. Overall, the CYPP/OVA formulation produced a stronger humoral and cellular immune response and a mixed Th1/Th2 immune response with a greater Th1 bias in comparison with the other formulations. In conclusion, the data demonstrate that the CYPP-adjuvanted delivery system has the potential to strengthen immune responses and lay the foundation for novel adjuvant design.

Abstract Gut microbiome contributes to host health by maintaining homeostasis, increasing digestive efficiency, and facilitating the development of immune system. Wild greylag geese (Anser anser) and ruddy shelducks (Tadorna ferruginea), migrating along the central Asian flyway, appear to be one of the most popular species in the rare birds rearing industries of China. However, the structure and function of the gut microbial communities associated with these two bird species remain poorly understood. Here, for the first time, we compared gut metagenomes from greylag geese to ruddy shelducks and investigated the similarities and differences between these two bird species in detail. Taxonomic classifications revealed the top three bacterial phyla, Firmicutes, Proteobacteria, and Fusobacteria, in both greylag geese and ruddy shelducks. Furthermore, between the two species, 12 bacterial genera were found to be more abundant in ruddy shelducks and 41 genera were significantly higher in greylag geese. A total of 613 genera (approximately 70%) were found to be present in both groups. Metabolic categories related to carbohydrate metabolism, metabolism of cofactors and vitamins, lipid metabolism, amino acid metabolism, and glycan biosynthesis and metabolism were significantly more abundant in ruddy shelducks, while greylag geese were enriched in nucleotide metabolism and energy metabolism. The herbivorous greylag geese gut microbiota harbored more carbohydrate‐active enzymes than omnivorous ruddy shelducks. In our study, a range of antibiotic resistance categories were also identified in the gut microbiota of greylag geese and ruddy shelducks. In addition to providing a better understanding of the composition and function of wild birds gut microbiome, this comparative study provides reference values of the artificial domestication of these birds.

The endoplasmic reticulum (ER) Ca2+ sensors stromal interaction molecule 1 (STIM1) and STIM2, which connect ER Ca2+ depletion with extracellular Ca2+ influx, are crucial for the maintenance of Ca2+ homeostasis in mammalian cells. Despite the recent progress in unraveling the role of STIM2 in Ca2+ signaling, the mechanistic underpinnings of its activation remain underexplored. We use an engineering approach to direct ER-resident STIMs to the plasma membrane (PM) while maintaining their correct membrane topology, as well as Förster resonance energy transfer (FRET) sensors that enabled in cellulo real-time monitoring of STIM activities. This allowed us to determine the calcium affinities of STIM1 and STIM2 both in cellulo and in situ, explaining the current discrepancies in the literature. We also identified the key structural determinants, especially the corresponding G residue in STIM1, which define the distinct activation dynamics of STIM2. The chimeric E470G mutation could switch STIM2 from a slow and weak Orai channel activator into a fast and potent one like STIM1 and vice versa. The systemic dissection of STIM2 activation by protein engineering sets the stage for the elucidation of the regulation and function of STIM2-mediated signaling in mammals.