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Abstract Tourism is an emotional sphere, and researchers focus on emotions to optimize tourism experiences. Tourism studies on emotions mostly ignore differences in emotions across demographic tourist groups by gender and age, thus limiting the understanding of emotions to the explicit characteristics of tourists’ emotions. On the basis of geotagged facial expressions on social media platforms, this study aims to visualize the emotions of groups in scenic spots and then reveal the variations between groups’ emotions within theme parks. By employing a facial recognition algorithm, an emotion distribution graph was proposed to represent groups’ emotions in detail. Some analytical methods were combined to characterize of the emotion distribution of each group. Through a comprehensive comparison, the results suggest that there are unique characteristics of emotion distribution for each group and considerable variations between them. This study helps researchers achieve a deeper understanding of tourists’ emotional differences and enhances the theorization of emotions. This research also highlights the advantages and significant practical implications of our method framework.

Cities constitute a critical component of the “dual carbon” strategy, highlighting the importance of examining the carbon emission trends within various city categories to formulate a low-carbon development path. In this paper, 21 cities (prefectures) in Sichuan province were divided into 4 categories (service-based cities, resource-based cities, industry-based cities, and other cities) through K-means clustering, and the differences in driving factors of carbon emissions in different types of cities were explored. At the same time, baseline scenarios, technological innovation scenarios, controlled development scenarios, and mandatory emission reduction scenarios were set up to dynamically simulate the evolution path of urban carbon emissions in the next 30 years from the bottom-up. The results show that: (1) Input scale is the main driving factor for carbon emission growth in Sichuan province, while input carbon intensity is the leading factor for carbon emission reduction. Environmental input and population scale have opposite effects on carbon emission of different urban types. (2) Resource-based cities face challenges in completing the phased goal of “carbon peaking” under both baseline scenarios and controlled development scenarios. These cities have gradually become the predominant city type of emission source in Sichuan province, surpassing service-based cities. (3) Except for the normal scenario, Sichuan province can achieve the target of “carbon peaking” in other scenarios, and is expected to achieve the target of 90 % greenhouse gas reduction by 2050. (4) Among the 81 development paths derived from the urban scenario combinations, the path labeled M−B−C−M exhibits the lowest economic-ecological comprehensive impact coefficient. The bottom-up carbon emission scenario analysis framework established in this paper offers a novel perspective for the study of “carbon peaking” and can provide theoretical support for policymakers in devising regional low-carbon development strategies.

BackgroundRecent findings highlight the significant impact of intestinal fungi on the complex makeup of the gut microbiota and human health, challenging past oversights. However, a lack of thorough systematic and quantitative analyses remains. This study aims to address this gap by thoroughly examining the current research on gut fungi. Through analyzing developments and unique features in this area, our goal is to foster a deeper understanding and identify future research pathways.MethodsWe performed an extensive bibliometric analysis on documents from 2000 to 2023, sourced from the Web of Science Core Collection (WoSCC). Utilizing advanced visualization tools such as VOSviewer, CiteSpace, and Bibliometrix R, we meticulously examined and illustrated the data in scientific landscapes and networks.ResultsA total of 1434 papers were analyzed, revealing a substantial increase in publication volume over the past two decades, particularly in 2020. Contributions came from 67 countries, 2178 institutions, and 8,479 authors. China led in publication output with 468 articles, followed by the University of California with 84 articles, and ZHANG F as the most prolific author with 17 articles. Emerging research areas such as “Fungal-Bacteria Interactions,” “Gut Fungus and Gut-Brain Axis,” and “Gut Fungus and Immunity” are expected to attract growing interest in the future.ConclusionThis extensive bibliometric analysis offers a current overview of scholarly efforts concerning intestinal fungi, highlighting the predominant landscape in this field. These insights can assist scholars in identifying appropriate publication avenues, forming collaborative relationships, and enhancing understanding of key themes and emerging areas, thereby stimulating future research endeavors.

The Tibetan Plateau, known as the "Roof of the World" , is one of the most tectonically complex areas on Earth. Its deep tectonics and dynamical mechanisms have been the focus of intense research in the fields of deep geophysics and continental dynamics. The eastern Tibetan Plateau is characterized by strong topographic fluctuations, frequent seismic activities, and abundant metal deposits, which reveal the extremely complex crust–mantle structure, deep deformation, and intense deep material movement. In recent years, with the rapid development of comprehensive geophysical observation techniques, deep structure imaging methods, and geodynamic simulations, significant progress has been made in deep tectonics, block motions, deep dynamic models, strong seismic activity, deep seismic mechanisms, as well as the deep structure of metal mineralization in the eastern Tibetan Plateau. The Workshop on Tectonics and Geophysics in the east part of Tibetan Plateau (WTGTP) is an annual academic exchange symposium for the eastern part of the Tibetan Plateau. The 9th and 10th conferences were held in Xichang, China, in 2021 and online in 2022, respectively. Based on the reports of these conferences, in combination with the relevant research results in recent years, this paper focuses on the India–Eurasian plate collision, tectonic deformation and dynamic mechanisms, and strong earthquake activity and deep seismic mechanisms in the eastern Tibetan Plateau. The paper describes the research progress pertaining to the tectonic structure, deep structural deformation, and dynamic mechanisms of the eastern Tibetan Plateau. The research prospects of further delineating the deep structure and geophysics of the Tibetan Plateau are preliminarily addressed, with the goal of providing a useful reference for interested researchers. The research in this field has great significance because it enhances our understanding of the deep tectonic processes that shape the Tibetan Plateau. Such knowledge could have implications for predicting and mitigating seismic hazards in the region. Additionally, research into the metallogenic tectonics of the eastern Tibetan Plateau may provide insights into the formation of mineral deposits in other parts of the world. Overall, research into the deep tectonics and dynamical mechanisms of the Tibetan Plateau is a complex and challenging field that requires the use of advanced technology and multidisciplinary approaches. The WTGTP provides a valuable forum for researchers to share their findings and collaborate on solutions to these geologically complex problems.

Accurate forecasts of water demand are a crucial factor in the strategic planning and judicious use of finite water resources within a region, underpinning sustainable socio-economic development. This study aims to compare the applicability of various artificial intelligence models for long-term water demand forecasting across different water use sectors. We utilized the Tuojiang River basin in Sichuan Province as our case study, comparing the performance of five artificial intelligence models: Genetic Algorithm optimized Back Propagation Neural Network (GA-BP), Extreme Learning Machine (ELM), Gaussian Process Regression (GPR), Support Vector Regression (SVR), and Random Forest (RF). These models were employed to predict water demand in the agricultural, industrial, domestic, and ecological sectors using actual water demand data and relevant influential factors from 2005 to 2020. Model performance was evaluated based on the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with the most effective model used for 2025 water demand projections for each sector within the study area. Our findings reveal that the GPR model demonstrated superior results in predicting water demand for the agricultural, domestic, and ecological sectors, attaining R2 values of 0.9811, 0.9338, and 0.9142 for the respective test sets. Also, the GA-BP model performed optimally in predicting industrial water demand, with an R2 of 0.8580. The identified optimal prediction model provides a useful tool for future long-term water demand forecasting, promoting sustainable water resource management.

The NE margin of the Tibetan plateau influenced by multiple blocks, the regional dynamic model and lithospheric deformation characteristics are still controversial. In this study, 15 years data from permanent broadband seismic stations of the seismic network in the study area were adopted for splitting analyses of teleseismic phases XKS (SKS PKS and SKKS, shortly named XKS) using a grid search method, longer observations provided each station with a large number of clear seismic phases. The results show that the fast wave directions of XKS splitting are oriented toward WNW or NW, with reference to the direction of absolute plate motion, the lithospheric deformation is dominantly driven by the asthenosphere, although there are local variations. On both sides of the Haiyuan fault zone, there is a noticeable variation in lithospheric azimuthal anisotropy, further enhances the possibility that it is an extended boundary of the Tibetan plateau. Rheological anisotropic features on the western side of the Ordos block emphasize the obstruction of the rigid Ordos lithosphere. The crust and mantle seem to be coupled below the Qinling orogen, possibly related to the lateral movement of lithospheric material. However, in the Hexi corridor, there may be layered anisotropy within the lithosphere, which is inferred to relate to the subductions of the Alxa block and the Qilian orogen. The thicker lithosphere on the southern margin of the Alxa block may influence the asthenospheric flow. In addition, anisotropy results at the southeastern edge of the Alxa block and the Yinchuan graben reflect the possibility that the lithosphere may be characterized by a combination of horizontal and vertical movements. These results have greatly improved our understanding of the dynamic models and lithospheric deformation characteristics of the northeastern margin of the Tibetan plateau and adjacent areas.

Type 2 diabetes often presents with reproductive disorders, including reduced male and female fertility. Here they show that diabetes disrupts the APLN signaling axis in the testes and that spermatogenesis can be restored through treatment with an APLN antagonist.

Abstract In the context of the COVID-19 pandemic, global vaccine campaigns are a mass vaccination intervention conducted through routine service provision for individuals who have reached a specified age. However, obtaining a high uptake rate to reach herd immunity may be undermined by various social motivations. To scrutinize the practical and dynamic strategies for a successful vaccination campaign, we map out the determinants that exacerbate vaccine hesitancy by leveraging the capacity of rich metadata from Twitter. Here, we uncover the collective propensities underlying dynamic social motivations and the uneven distribution of vaccines across the globe. Our findings suggest that profiling the status quo of public perceptions and engaging in introspection about vaccine-promoting policies in due course are integral components of preparedness against the ongoing pandemic. Simultaneously, we propose several recommendations to remind governments of the importance of building confidence in vaccination in a targeted way, and we assert that national barriers should be abandoned and that international responsibility should be assumed.

The brewing conditions of beverage milk tea determine the taste of milk tea. This study investigated the changes in sensory characteristics and small molecule compounds in milk tea made from large-leaf yellow tea under different brewing conditions by sensory analysis, colorimeter, and LC-MS. The results show that the tea to milk ratio is the most important process affecting the taste, and the color values of b* (+yellow, - blue) can be used to evaluate the taste of milk tea made from large leaf yellow tea. The composition of small molecular compounds is affected by tea to milk ratio, which can change the taste of milk tea. l-cysteine and 8-methylsulfinyloctyl glucosinolate are significantly positively correlated with taste by metabolomics analysis. l-cysteine was used to verify the analysis results by LC-MS. The total acceptance of milk tea is improved by adding l-cysteine at a low level (0.025–0.035 mM).

Cisplatin (Cp), a chemotherapeutic agent, interacts with purines on tumor DNA, causing tumor cell apoptosis. However, cisplatin has the characteristics of non-specific distribution and lack of selectivity, resulting in systemic toxicity. Moreover, it cannot maintain the drug’s high concentration in the tumor-weak acid environment. These flaws of cisplatin restrict its use in clinical applications. Therefore, a pH-responsive carbon nanotube-modified nano-drug delivery system (CNTs/Gel/Cp) was constructed in this study using gelatin (Gel)-modified carbon nanotubes (CNTs/Gel) loaded with cisplatin to release drugs precisely and slowly, preventing premature inactivation and maintaining an effective concentration. When MCp:MCNTs/Gel = 1:1, the drug reaches the highest loading rate and entrapment efficiency. To achieve the sustained-release effect, CNTs/Gel/Cp can release the medicine steadily for a long time in a pH environment of 6.0. Additionally, CNTs/Gel/Cp display antitumor properties comparable to cisplatin in a manner that varies with the dosage administered. These findings indicate that CNTs/Gel/Cp have an effective, sustained release of cisplatin and a good antitumor effect, providing a theoretical and experimental basis for the clinical application of modified carbon nanotubes (CNTs) as a new drug delivery system.

Microbial CH4 kept the early Earth warm under the faint young sun, but clear records are lacking. Here the authors present isotopic evidence that CH4 seepage in the Canadian shield is from hydrogen biodegradation in a Neoarchean ecosystem rather than an abiotic synthesis product.

Abstract The dissemination of one public hot event is usually affected by some related information, and the implication of co-propagation by different information is critical for the integrated analysis. To help in designing effective communication strategies during the whole event, we propose the cross-transmission susceptible-forwarding-immune (CT-SFI) model to describe the dynamics of co-propagation particularly with focus on the cross-transmission effects. This model is based on the forwarding quantity and takes into account the behavior that users may have a strong attraction or continuous attraction within or without an active time after contacting one information. Data fitting using the real data of Chinese Sina-microblog can accurately parameterize the model and parameter sensitivity analysis gives some strategies for co-propagation.

The outbreak of a novel coronavirus (COVID-19) generated an outbreak of public opinions in the Chinese Sina-microblog. To help in designing effective communication strategies during a major public health emergency, we propose a multiple-information susceptible-discussing-immune (M-SDI) model in order to understand the patterns of key information propagation on social networks. We develop the M-SDI model, based on the public discussion quantity and take into account of the behavior that users may re-enter another related topic or Weibo after discussing one. Data fitting using the real data of COVID-19 public opinion obtained from Chinese Sina-microblog can parameterize the model to make accurate prediction of the public opinion trend until the next major news item occurs. The reproduction ratio has fallen from 1.7769 and maintained around 0.97, which reflects the peak of public opinion has passed but it will continue for a period of time.

Abstract Background The aim of this study was to investigate the prevalence and genotypic profiles of Candida albicans in patients with oral lichen planus (OLP). Materials and methods Positive rates and genotypic profiles of Candida albicans strains from OLP patients and healthy controls were analyzed. Random amplified polymorphic DNA and internal transcribed spacer of ribosome DNA polymerase chain reactions were used to sequence the DNA of these strains, and then their genetic similarity was measured using BLAST, UIV Band, and Vector NTI Suite Sequence Analyses Software. Results The prevalence of C. albicans strains detected from erosive-OLP, non-erosive OLP, and normal individuals was 18.87, 18.75, and 7.92%, respectively. Four different genotypes were revealed by the two methods. To be specific, type I was found only in the healthy subjects; type II a and II b were found in non-erosive OLP, and type III was identified in erosive OLP. Intragroup similarity coefficients, i.e. SAB were 100%, and inter-groups similarity coefficients, i.e. SAB were less than 30%. Conclusions The genotypic results of C. albicans in OLP revealed an endogenous rather than exogenous infection of C. albicans. In addition, a possible pathogenic role of C. albicans in OLP, with the etiologic sense contributing to a more proper recognition on the pathogenesis, development, and progression of OLP, as well as some strategies for its diagnosis and treatment were identified.

Thermal batteries are high-temperature lithium metal batteries. The thermal stability and the specific capacity of cathode materials are key factors to its application. In this case, NiO with high decomposition temperature and theoretical capacity was constructed as a thermal battery cathode. At 500℃, the specific capacity of NiO cathode was about 642 mAh g−1 with a large current density of 0.1 A cm−2 and a cut-off voltage of 1.0 V. This capacity reached 89.4% of the theoretical value at those harsh discharge conditions. As the discharge temperature increased to 700℃, an obvious discharge voltage platform of 1.5 V and a specific capacity of 243 mAh g−1 were still observed for NiO cathodes. While thermal batteries using other common cathode materials cannot discharge efficiently at 700 °C. The XRD and TEM indicated that the high-temperature reaction of the NiO cathode was a one-step reaction: NiO + 2Li++2e-→ Ni + Li2O. This ultra-high temperature discharge ability suggests the NiO cathode can be very promising in high-capacity and long-life thermal battery applications.

Heat stroke (HS) models in rats are associated with severe intestinal injury, which is often considered as the key event at the onset of HS. Probiotics can regulate the gut microbiota by inhibiting the colonization of harmful bacteria and promoting the proliferation of beneficial bacteria. Here, we investigated the preventive effects of a probiotic Bacillus licheniformis strain (BL, CMCC 63516) on HS rats as well as its effects on intestinal barrier function and gut microbiota. All rats were randomly divided into four groups: control (Con) + PBS (pre-administration with 1 ml PBS twice a day for 7 days, without HS induction), Con + BL group (pre-administration with 1 ml 1 × 108 CFU/ml BL twice a day for 7 days, without HS induction), HS + PBS (PBS, with HS induction), and HS + BL (BL, with HS induction). Before the study, the BL strain was identified by genomic DNA analysis. Experimental HS was induced by placing rats in a hot and humid chamber for 60 min until meeting the diagnostic criterion of HS onset. Body weight, core body temperature, survival rate, biochemical markers, inflammatory cytokines, and histopathology were investigated to evaluate the preventive effects of BL on HS. D-Lactate, I-FABP, endotoxin, and tight-junction proteins were investigated, and the fluorescein isothiocyanate-dextran (FD-4) test administered, to assess the degree of intestinal injury and integrity. Gut microbiota of rats in each group were analyzed by 16S rRNA sequencing. The results showed that pre-administration with BL significantly attenuated hyperthermia, reduced HS-induced death, alleviated multiple-organ injury, and decreased the levels of serum inflammatory cytokines. Furthermore, BL sustained the intestinal barrier integrity of HS rats by alleviating intestinal injury and improving tight junctions. We also found that BL significantly increased the ratios of two probiotic bacteria, Lactobacillus and Lactococcus. In addition, Romboutsia, a candidate biomarker for HS diagnosis, was unexpectedly detected. In summary, BL pre-administration for 7 days has preventative effects on HS that may be mediated by sustaining intestinal barrier function and modulating gut microbiota.

Vaccine development utilizing various platforms is one of the strategies that has been proposed to address the coronavirus disease 2019 (COVID-19) pandemic. Adjuvants are critical components of both subunit and certain inactivated vaccines because they induce specific immune responses that are more robust and long-lasting. A review of the history of coronavirus vaccine development demonstrates that only a few adjuvants, including aluminum salts, emulsions, and TLR agonists, have been formulated for the severe acute respiratory syndrome-associated coronavirus (SARS-CoV), Middle East respiratory syndrome-related coronavirus (MERS-CoV), and currently the SARS-CoV-2 vaccines in experimental and pre-clinical studies. However, there is still a lack of evidence regarding the effects of the adjuvants tested in coronavirus vaccines. This paper presents an overview of adjuvants that have been formulated in reported coronavirus vaccine studies, which should assist with the design and selection of adjuvants with optimal efficacy and safety profiles for COVID-19 vaccines.

BackgroudEffective communication of accurate information through social media constitutes an important component of public health interventions in modern time, when traditional public health approaches such as contact tracing, quarantine and isolation are among the few options for the containing the disease spread in the population. The success of control of COVID-19 outbreak started from Wuhan, the capital city of Hubei Province of China relies heavily on the resilience of residents to follow public health interventions which induce substantial interruption of social-economic activities, and evidence shows that opinion leaders have been playing significant roles in the propagation of epidemic information and public health policy and implementations.MethodsWe design a mathematical model to quantify the roles of information superspreaders in single specific information which outbreaks rapidly and usually has a short duration period, and to examine the information propagation dynamics in the Chinese Sina-microblog. Our opinion-leader susceptible-forwarding-immune (OL-SFI) model is formulated to track the temporal evolution of forwarding quantities generated by opinion leaders and normal users.ResultsData fitting from the real data of COVID-19 obtained from Chinese Sina-microblog can identify the different contact rates and forwarding probabilities (and hence calculate the basic information forwarding reproduction number of superspreaders), and can be used to evaluate the roles of opinion leaders in different stages of the information propagation and the outbreak unfolding.ConclusionsThe parameterized model can be used to nearcast the information propagation trend, and the model-based sensitivity analysis can help to explore important factors for the roles of opinion leaders.

The uneven distribution, scarcity, and pollution of water resources can significantly hinder socioeconomic development. A conceptual framework of Water Resources Endowment-Efficiency-Pressure-Response-Structure-Cycle (2EPRSC) was proposed, and 16 indicators were selected to establish the evaluation index system. Taking the five economic zones in the Sichuan Province of China as the research area, the genetic algorithm optimized entropy weighting method-cloud model was applied to determine the water security grades. Subsequently, the coupling coordination degree (CCD) model was established based on water security system (WSS)-SES to analyze the CCD. The results showed that (1) temperature and investment were the two indicators with more significant impacts on water security in Sichuan Province. (2) From 2012 to 2022, water security in Sichuan Province as a whole presented a decreasing and then increasing trend. (3) From 2012 to 2022, CCDs of the WSS-SES in Sichuan Province's economic zones were mostly at moderate imbalance, with the Chengdu Plain economic zone showing the highest CCD. Overall, the CCD scores across the economic zones were on an ascending trajectory. The study, grounded in the state of water security and CCD in Sichuan, can forge a scientific foundation for the sustainable development of WSS-SES. [ABSTRACT FROM AUTHOR]

Abstract Background Emphysematous pyelonephritis is a rare and severe urinary tract infection that is potentially life-threatening and easily progresses to septic shock. In this report, we present a unique case of emphysematous pyelonephritis caused by Raoultella ornithinolytica. Case presentation An 86-year-old man presented with severe back pain of 3 days’ duration. He had a history of hypertension and diabetes for more than 20 years, and his infection indicators and serum creatinine were elevated. Abdominal computed tomography revealed an abnormal gas shadow around his right kidney and the anterior edge of his right psoas muscle. Consequently, he was initially diagnosed with emphysematous pyelonephritis. There was no evidence of nephrolithiasis or other anatomical or structural abnormalities that could have precipitated this focal renal infection. Both blood and drainage fluid cultures revealed R. ornithinolytica. After early anti-infection treatment, percutaneous drainage and moderate control of blood glucose, the patient gradually recovered. Conclusions Emphysematous pyelonephritis caused by R. ornithinolytica is rare but has a high drug resistance rate potentially and may cause severe infections. Early diagnosis, prompt use of antibiotics that are sensitive to the organism, and decompression drainage could be the key to treatment.

Highlights The strengthening mechanism of spontaneous orientation polarization of anisotropic equivalent dipoles within high-entropy alloys (HEAs) is proposed for enhancing dielectric attenuation of HEAs. The source of carbon supporter is expanded to the biomass category, which can construct the shell-core heterointerfaces with HEAs by means of a reformative carbothermal shock method. The sample carbonized cellulose paper/HEAs-Mn2.15 achieves efficient electromagnetic wave absorption of -51.35 dB at an ultra-thin thickness of 1.03 mm. This work combines theoretical calculations and electromagnetic simulations to propose feasible strategies for the design and application of electromagnetic functional devices such as ultra-wideband bandpass filter.

Traditional treatments against advanced non-small cell lung cancer (NSCLC) with high morbidity and mortality continue to be dissatisfactory. Given this situation, there is an urgent requirement for alternative modalities that provide lower invasiveness, superior clinical effectiveness, and minimal adverse effects. The combination of photodynamic therapy (PDT) and immunotherapy gradually become a promising approach for high-grade malignant NSCLC. Nevertheless, owing to the absence of precise drug delivery techniques as well as the hypoxic and immunosuppressive characteristics of the tumor microenvironment (TME), the efficacy of this combination therapy approach is less than ideal. In this study, we construct a novel nanoplatform that indocyanine green (ICG), a photosensitizer, loads into hollow manganese dioxide (MnO2) nanospheres (NPs) (ICG@MnO2), and then encapsulated in PD-L1 monoclonal antibodies (anti-PD-L1) reprogrammed exosomes (named ICG@MnO2@Exo-anti-PD-L1), to effectively modulate the TME to oppose NSCLC by the synergy of PDT and immunotherapy modalities. The ICG@MnO2@Exo-anti-PD-L1 NPs are precisely delivered to the tumor sites by targeting specially PD-L1 highly expressed cancer cells to controllably release anti-PD-L1 in the acidic TME, thereby activating T cell response. Subsequently, upon endocytic uptake by cancer cells, MnO2 catalyzes the conversion of H2O2 to O2, thereby alleviating tumor hypoxia. Meanwhile, ICG further utilizes O2 to produce singlet oxygen (1O2) to kill tumor cells under 808 nm near-infrared (NIR) irradiation. Furthermore, a high level of intratumoral H2O2 reduces MnO2 to Mn2+, which remodels the immune microenvironment by polarizing macrophages from M2 to M1, further driving T cells. Taken together, the current study suggests that the ICG@MnO2@Exo-anti-PD-L1 NPs could act as a novel drug delivery platform for achieving multimodal therapy in treating NSCLC.

IntroductionAtopic dermatitis (AD) is a common clinical recurrent atopic disease in dermatology, most seen in children and adolescents. In recent years, AD has been found to be closely associated with microbial communities.MethodsTo explore the synergistic effects between colonizing bacteria from different sites and AD, we comparatively analyzed the skin, oral, and gut microbiota of children with AD (50 individuals) and healthy children (50 individuals) by 16S rRNA gene sequencing. Twenty samples were also randomly selected from both groups for metabolic and macrogenomic sequencing.ResultsThe results of our sequencing study showed reduced microbiota diversity in the oral, skin, and gut of children with AD (P < 0.05). Metabolomics analysis showed that serotonergic synapse, arachidonic acid metabolism, and steroid biosynthesis were downregulated at all three loci in the oral, skin, and gut of children with AD (P < 0.05). Macrogenomic sequencing analysis showed that KEGG functional pathways of the three site flora were involved in oxidative phosphorylation, ubiquitin-mediated proteolysis, mRNA surveillance pathway, ribosome biogenesis in eukaryotes, proteasome, basal transcription factors, peroxisome, MAPK signaling pathway, mitophagy, fatty acid elongation, and so on (P < 0.05).DiscussionThe combined microbial, metabolic, and macrogenetic analyses identified key bacteria, metabolites, and pathogenic pathways that may be associated with AD development. We provides a more comprehensive and in-depth understanding of the role of the microbiota at different sites in AD patients, pointing to new directions for future diagnosis, treatment and prognosis.

ObjectiveIn several randomized controlled trials (RCTs), sacrospinous hysteropexy and other forms of hysteropreservation have been compared. Nevertheless, there is no definitively best treatment. This study summarized RCT evidence for various uterine preservation surgical procedures.MethodsFrom each database inception to August 2023, we searched PubMed, Embase, Cochrane Library, and Web of Science for eligible RCTs. A comparison was made between sacrospinous hysteropexy and other hysteropreservation, including vaginal and abdominal surgery. For categorical and continuous variables, relative risks (RRs) and mean differences (MDs) were calculated using random-effects models.ResultsWe reviewed a total 1,398 studies and ultimately included five RCTs that met all inclusion criteria. These five studies included a total of 1,372 uterine POP cases all of whom received transvaginal surgery and had a follow-up period for assessment of recurrence from 12 months to 5 years. There were no significant differences between sacrospinous hysteropexy and other hysteropreservation for the incidences of recurrence (RR,1.24; 95% CI, 0.58 to 2.63; p = 0.58) or hematoma (RR,0.70; 95% CI, 0.17 to 2.92; p = 0.62). Moreover, neither sacrospinous hysteropexy nor hysteropreservation had any significant effect on the risk of mesh exposure (RR,0.34; 95% CI, 0.03 to 4.31; p = 0.41), dyspareunia (RR,0.45; 95% CI, 0.13 to1.6; p = 0.22), urinary tract infection (RR,0.66; 95% CI, 0.38 to 1.15; p = 0.15), bothersome bulge symptoms (RR,0.03; 95% CI, −0.02 to 0.08; p = 0.24), operative time (MD, −4.53; 95% CI, −12.08 to 3.01; p = 0.24), and blood loss (MD, −25.69; 95% CI, −62.28 to 10.91; p = 0.17). However, sacrospinous hysteropexy was associated with a lower probability of pain (RR,4.8; 95% CI, 0.79 to 29.26; p = 0.09) compared with other hysteropreservation.ConclusionThere was no difference between sacrospinous hysteropexy and hysteropreservation in terms of recurrence, hematoma, mesh exposure, dyspareunia, urinary tract infection, bothersome bulge symptoms, operative time, pain, and blood loss.Systematic Review RegistrationPROSPERO [CRD42023470025].

Precipitation plays a significant role in global water and energy cycles, largely affecting many aspects of human life, such as transportation and agriculture. Recently, meteorologists have tried to predict precipitation with deep learning methods by learning from much historical meteorological data. Under this paradigm, the task of precipitation nowcasting is formulated as a spatiotemporal sequence forecasting problem. However, current studies suffer from two inherent drawbacks of the definition of the problem. First, considering that the weather patterns vary in spatial and temporal dimensions, a spatiotemporally shared kernel is not optimal for capturing features across different regions and seasons. Second, these methods isolate the precipitation from other meteorological elements, such as temperature, humidity, and wind. The disability of cross-model learning prevents the possibility of the promotion of precipitation prediction. Therefore, this article proposes a spatiotemporal inference network (STIN) to produce precipitation prediction from multimodal meteorological data with spatiotemporal specific filters. Specifically, we first design a spatiotemporal-aware convolutional layer (STAConv), in which kernels are generated conditioned on the incoming spatiotemporally features vector. Replacing normal convolution with STAConv enables the extraction of spatiotemporal specific information from the meteorological data. Based on the STAConv, the spatiotemporal-aware convolutional neural network (STACNN) is further proposed, fusing the multimodal information, including temperature, humidity, and wind. Then, an encoder–decoder framework composed of RNN layers is built to extract representative temporal dynamics from multimodal information. To investigate the practicality of the proposed method, we employ STIN to predict the following precipitation intensity. Extensive experiments on three meteorological datasets demonstrate the effectiveness of our model on precipitation nowcasting.

The charging load of electric vehicles (EV) is one of the most rapidly increasing loads in current power distribution systems. It may cause distribution transformer/feeder overload without proper coordination or control, especially in residential area where household load and EV charging load are sharing transformer capacity. Existing smart meter-based orderly charging control (OCC) approaches commonly require costly but unreliable communication schemes to control EV charging behavior. In this work, a smart meter-based distributed controller is designed to establish a meter-to-EV communication interface with low cost and enhanced reliability, based on the state-of-the-art charging standard. An event-driven OCC algorithm is developed, and then, deployed in the data hub (concentrator) of the AMI with an easy-to-implement optimization formulation. The effectiveness of the proposed approach is validated using a numerical case study and a practical field test in Hangzhou, China. Both results indicate promising advantages of the proposed OCC approach in reducing the peak load of emerging EV charging demand by more than 30%.

The adsorption of CO on a ternary Cu catalyst was studied at room temperature in a static Tian-calvet microcalorimeter. For carbon monoxide adsorption on a hydrogen-reduced Cu/ZnO/Al(sub 2)O(sub 3) catalyst, the adsorption rate constant (K(sub a)) is found to be in the range from 10(super -6) to 10(super -4) Pa(super -1) S(super -1), and the desorption rate constant (k(sub d) from 10(super -4) to 10(super -2) S(super -1), both increasing with fractional coverage theta.

With the rapid development of the Internet, the continuous increase of malware and its variants have brought greatly challenges for cyber security. Due to the imbalance of the data distribution, the research on malware detection focuses on the accuracy of the whole data sample, while ignoring the detection rate of the minority categories' malware. In the dataset sample, the normal data samples account for the majority, while the attacks' malware accounts for the minority. However, the minority categories' attacks will bring great losses to countries, enterprises, or individuals. For solving the problem, this study proposed the GNGS algorithm to construct a new balance dataset for the model algorithm to pay more attention to the feature learning of the minority attacks' malware to improve the detection rate of attacks' malware. The traditional malware detection method is highly dependent on professional knowledge and static analysis, so we used the Self-Attention with Gate mechanism (SAG) based on the Transformer to carry out feature extraction between the local and global features and filter irrelevant noise information, then extracted the long-distance dependency temporal sequence features by the BiGRU network, and obtained the classification results through the SoftMax classifier. In the study, we used the Alibaba Cloud dataset for malware multi-classification. Compared the GSB deep learning network model with other current studies, the experimental results showed that the Gaussian noise generation strategy (GNGS) could solve the unbalanced distribution of minority categories' malware and the SAG-BiGRU algorithm obtained the accuracy rate of 88.7% on the eight-classification, which has better performance than other existing algorithms, and the GSB model also has a good effect on the NSL-KDD dataset, which showed the GSB model is effective for other network intrusion detection.

Abstract Both the hippocampus and amygdala are involved in working memory (WM) processing. However, their specific role in WM is still an open question. Here, we simultaneously recorded intracranial EEG from the amygdala and hippocampus of epilepsy patients while performing a WM task, and compared their representation patterns during the encoding and maintenance periods. By combining multivariate representational analysis and connectivity analyses with machine learning methods, our results revealed a functional specialization of the amygdala-hippocampal circuit: The mnemonic representations in the amygdala were highly distinct and decreased from encoding to maintenance. The hippocampal representations, however, were more similar across different items but remained stable in the absence of the stimulus. WM encoding and maintenance were associated with bidirectional information flow between the amygdala and the hippocampus in low-frequency bands (1–40 Hz). Furthermore, the decoding accuracy on WM load was higher by using representational features in the amygdala during encoding and in the hippocampus during maintenance, and by using information flow from the amygdala during encoding and that from the hippocampus during maintenance, respectively. Taken together, our study reveals that WM processing is associated with functional specialization and interaction within the amygdala-hippocampus circuit.