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Major water conservancy projects face the risk of damage from conflict, and the potential consequences of dam failure can lead to widespread public outrage, posing a threat to social stability. This study analyzed the formation model of network public opinion risk, using the Kakhovka Hydropower station damaged during conflict as a case study. Based on data analysis of netizen’ comments on Twitter and Weibo (a Chinese social media platform similar to Twitter), we used data mining algorithm to identify the primary topics of interest and examine the evolution of public opinion. The findings indicate that attention to incident resulting in war damage has a negative impact on social stability through a feedback loop. Netizen on Twitter and Weibo were primarily focused on “Flood” “Crisis” “Charge” and “Help” topics. Among them, Twitter was more popular in terms of public opinion and had faster dissemination speed. “Crisis” and “Charge” were more likely to generate public opinion risks. The potential impact of war damage on social stability is noteworthy, and social stability is largely dependent on the attention level of netizen.

Abstract The kinetical behavior and mechanism of micro-galvanic corrosion of Q690 bainitic weathering steel welded joint in marine atmosphere were investigated. The results showed that a micro-galvanic corrosion cell formed among different regions of the Q690 welded joint. The kinetical behavior of micro-galvanic corrosion could be divided into four stages: the initiation and development of micro-galvanic corrosion, the decreasing of galvanic corrosion rate, the polarity reversal of galvanic couple, and the disappearance of galvanic effect. The difference of corrosion rate between Q690 steel and its welded joint is closely related to the micro-galvanic corrosion kinetic behavior.

Radar is a valuable tool for noncontact vital-sign detection. Interference from respiratory harmonics presents a major challenge in radar cardiogram (RCG) extraction—mainly when the frequency of respiratory harmonics is close to or equal to that of the cardiac sub-signals. To address this problem, a respiratory harmonic suppression method employing correlation analysis and an optimized feedback notch filter is proposed, which is based on 7.29 GHz center-frequency impulse-radio ultra-wideband radar. A genetic optimization algorithm is employed to optimize the parameters of the notch filter. Performance comparison analysis is conducted on the conventional notch filter and the feedback notch filter. Contact (ECG) and non-contact (RCG) data from 10 subjects were analyzed. The results verified that the performance of the optimized feedback notch filter is much better than that of the conventional notch filter in overshoot, bandwidth, and notch depth, and the proposed method can effectively locate, identify, and suppress respiratory harmonics from the RCG band while preserving heartbeat components. Consequently, this approach markedly enhances the precision of RCG extraction. The technique shows considerable promise for deployment in diverse practical settings, including non-contact auxiliary monitoring systems in both intelligent medical environments and home healthcare.

Background: Pulmonary artery stenosis endangers people's health. Quantitative pulmonary pressure ratio (QPPR) is very important for clinicians to quickly diagnose diseases and develop treatment plans. Objective: Our purpose of this paper is to investigate the effects of different degrees (50% and 80%) of pulmonary artery stenosis on QPPR. Methods: An idealized model is established based on the normal size of human pulmonary artery. The hemodynamic governing equations are solved using fluid-structure interaction. Results: The results show that the QPPR decreases with the increase of stenosis degree, and it is closely related to the pressure drop at both ends of stenosis. Blood flow velocity and wall shear stress are sensitive to the stenosis degree. When the degree of stenosis is 80%, the amplitude of changes of blood flow velocity and wall shear stress at both ends of stenosis is lower. Conclusions: The results suggest that the degree of pulmonary artery stenosis has a significant impact on QPPR and hemodynamic changes. This study lays a theoretical foundation for further study of QPPR.

In this study, two new species, Rhizoplaca adpressa Y. Y. Zhang & Li S. Wang and R. auriculata Y. Y. Zhang, Li S. Wang & Printzen, are described from Southwest China, based on their morphology, phylogeny and chemistry. In phylogeny, the two new species are monophyletic, and sister to each other within Rhizoplaca chrysoleuca-complex. Rhizoplaca adpressa is characterized by its placodioid and closely adnate thallus, pale green and heavily pruinose upper surface, narrow (ca. 1 mm) and white free margin on the lower surface of marginal squamules, the absence of a lower cortex, and its basally non-constricted apothecia with orange discs that turn reddish-brown at maturity. Rhizoplaca auriculata is characterized by its squamulose to placodioid thallus, yellowish green and marginally pruinose squamules, wide (1−3 mm) and bluish-black free margin on the lower surface of marginal squamules, the absence of a lower cortex, and its basally constricted apothecia with persistently orange discs. Rhizoplaca adpressa and R. auriculata share the same secondary metabolites of usnic and placodiolic acids.

Isocorydine (ICD) exhibits strong antitumor effects on numerous human cell lines. However, the anticancer activity of ICD against oral squamous cell carcinoma (OSCC) has not been reported. The anticancer activity, migration and invasion ability, and changes in the cytoskeleton morphology and mechanical properties of ICD in OSCC were determined. Changes in the contents of reactive oxygen species (ROS), the mitochondrial membrane potential (MMP), ATP, and mitochondrial respiratory chain complex enzymes Ⅰ–Ⅳ in cancer cells were studied. ICD significantly inhibited the proliferation of oral tongue squamous cells (Cal-27), with an IC50 of 0.61 mM after 24 h of treatment. The invasion, migration, and adhesion of cancer cells were decreased, and cytoskeletal actin was deformed and depolymerized. In comparison to an untreated group, the activities of mitochondrial respiratory chain complex enzymes I-IV were significantly decreased by 50.72%, 27.39%, 77.27%, and 73.89%, respectively. The ROS production increased, the MMP decreased by 43.65%, and the ATP content decreased to 17.1 ± 0.001 (mmol/mL); ultimately, the apoptosis rate of cancer cells increased up to 10.57% after 24 h of action. These findings suggest that ICD exerted an obvious anticancer activity against OSCC and may inhibit Cal-27 proliferation and growth by causing mitochondrial dysfunction and interrupting cellular energy.

Homomorphic encryption (HE) enables third-party servers to perform computations on encrypted user data while preserving privacy. Although conceptually attractive, the speed of software implementations of HE is almost impractical. To address this challenge, various domain-specific architectures have been proposed to accelerate homomorphic evaluation, but efficiency remains a bottleneck. In this paper, we propose a homomorphic evaluation accelerator with heterogeneous reconfigurable modular computing units (RCUs) for the Brakerski/Fan-Vercauteren (BFV) scheme. RCUs leverage operator abstraction to efficiently perform basic sub-operations of homomorphic evaluation such as residue number system (RNS) conversion, number theoretic transform (NTT), and other modular computations. By combining these sub-operations, complex homomorphic evaluation operations like multiplication, rotation, and addition are efficiently executed. To address the high demand for data access and improve memory efficiency, we design a coordinate-based address encoding strategy that enables in-place and conflict-free data access. Furthermore, specific optimizations are performed on the core sub-operations such as NTT and automorphism. The proposed architecture is implemented on Xilinx Virtex-7 and UltraScale+ FPGA platforms and evaluated for polynomials of length 4096. Compared to state-of-the-art accelerators with the same parameter set, our accelerator achieves the following advantages: $1)\,\,2.04\times $ to $3.33\times $ reduction in the area-time product (ATP) for the key sub-operation NTT, $2)\,\,1.08\times $ to $7.42\times $ reduction in latency for homomorphic multiplication with higher area efficiency, and 3) support for a wider range of homomorphic evaluation operations, including rotation, compared to other BFV-based accelerators.

Abstract Background Severe community-acquired pneumonia is one of the most lethal forms of CAP with high mortality. For rapid and accurate decisions, we developed a mortality prediction model specifically tailored for elderly SCAP patients. Methods The retrospective study included 2365 elderly patients. To construct and validate the nomogram, we randomly divided the patients into training and testing cohorts in a 70% versus 30% ratio. The primary outcome was in-hospital mortality. Univariate and multivariate logistic regression analyses were used in the training cohort to identify independent risk factors. The robustness of this model was assessed using the C index, ROC and AUC. DCA was employed to evaluate the predictive accuracy of the model. Results Six factors were used as independent risk factors for in-hospital mortality to construct the prediction model, including age, the use of vasopressor, chronic renal disease, neutrophil, platelet, and BUN. The C index was 0.743 (95% CI 0.719–0.768) in the training cohort and 0.731 (95% CI 0.694–0.768) in the testing cohort. The ROC curves and AUC for the training cohort and testing cohort (AUC = 0.742 vs. 0.728) indicated a robust discrimination. And the calibration plots showed a consistency between the prediction model probabilities and observed probabilities. Then, the DCA demonstrated great clinical practicality. Conclusions The nomogram incorporated six risk factors, including age, the use of vasopressor, chronic renal disease, neutrophil, platelet and BUN, which had great predictive accuracy and robustness, while also demonstrating clinical practicality at ICU admission.

Thermoelectrics has played a fascinating role in the developments of direct energy conversion technologies. Over the past decade, sulfur-based thermoelectric materials have been significantly advanced in optimizing electrical and thermal transport due to their similarities in chemical and structural properties with tellurides and selenides. This review provides research progress on metal sulfides, particularly focuses on materials exhibiting high thermoelectric figure of merit (ZT > 1.0). It highlights the potential compounds, e.g. CuS, SnS, PbS based, and polysulfides. Great strategies of superionic conducting, band configuration tuning, high-entropy alloying, and anomalous harmonic scattering are try to demonstrate the performance-improved mechanisms for thermoelectric sulfides. In addition, some common synthesis recipes are briefly introduced, and thereby making potential candidates as excellent alternatives for producing thermoelectric power generators in the mid temperature. Key outcomes along with how to further improve the thermoelectric performance and promote its scale-up applications are also outlined at the end.

ABSTRACT Importance Adenovirus encephalitis is a significant infectious disease of the central nervous system that commonly affects children under the age of 5 and has a profound impact on the health of infants and young children throughout China. National multicenter epidemiological studies have significant public health implications. Objective This study aims to report the epidemiology of adenovirus encephalitis in hospitalized children in China, providing valuable guidance for clinicians. Methods The data utilized in this study were extracted from the comprehensive Futang Update Medical Records database, which comprises discharge medical records collected by 27 tertiary children's hospitals between January 2016 and December 2018 in China. Specifically, the face sheet of discharge medical records encompassed critical sociodemographic variables and basic medical care details. Results In this database, a total of 544 children were hospitalized due to adenoviral encephalitis. The male‐to‐female ratio was 1.62:1, with more boys being affected across different age groups and places of residence. Of the children hospitalized, the highest number of hospitalizations occurred in the 1–3‐year age group and the number of hospitalizations decreased each year from 2016 to 2018. The disease exhibits seasonal characteristics with a pronounced peak in the summer months of June and July. While most children (58%) did not have any significant complications, one‐third of them developed respiratory complications, including pneumonia and acute bronchitis. The median length of stay for adenoviral encephalitis was 7 days, and the median cost of hospitalization was 2145.56 US dollars. Interpretation This study highlights the prevalence of adenovirus encephalitis in hospitalized children in China. Children aged 1–3 years were found to be the main demographic hospitalized due to this condition, with boys being significantly more affected than girls. The seasonal variations of adenovirus encephalitis were also found to be significant. Fortunately, the fatality rate associated with this condition was low, and the prognosis was generally favorable.

ABSTRACT Severe sepsis causes organ dysfunction and continues to be the leading reason for pediatric death worldwide. Early recognition of sepsis could substantially promote precision treatment and reduce the risk of pediatric death. The host cellular response to infection during sepsis between adults and pediatrics could be significantly different. A growing body of studies focused on finding markers in pediatric sepsis in recent years using multi‐omics approaches. This narrative review summarized the progress in studying pediatric sepsis biomarkers from genome, transcript, protein, and metabolite levels according to the omics technique that has been applied for biomarker screening. It is most likely not a single biomarker could work for precision diagnosis of sepsis, but a panel of markers and probably a combination of markers detected at multi‐levels. Importantly, we emphasize the importance of group distinction of infectious agents in sepsis patients for biomarker identification, because the host response to infection of bacteria, virus, or fungus could be substantially different and thus the results of biomarker screening. Further studies on the investigation of sepsis biomarkers that were caused by a specific group of infectious agents should be encouraged in the future, which will better improve the clinical execution of personalized medicine for pediatric sepsis.

Abstract Upgrading ethanol to long-chain alcohols (LAS, C6+OH) offers an attractive and sustainable approach to carbon neutrality. Yet it remains a grand challenge to achieve efficient carbon chain propagation, particularly with noble metal-free catalysts in aqueous phase, toward LAS production. Here we report an unconventional but effective strategy for designing highly efficient catalysts for ethanol upgrading to LAS, in which Ni catalytic sites are controllably exposed on surface through sulfur modification. The optimal catalyst exhibits the performance well exceeding previous reports, achieving ultrahigh LAS selectivity (15.2% C6OH and 59.0% C8+OH) at nearly complete ethanol conversion (99.1%). Our in situ characterizations, together with theoretical simulation, reveal that the selectively exposed Ni sites which offer strong adsorption for aldehydes but are inert for side reactions can effectively stabilize and enrich aldehyde intermediates, dramatically improving direct-growth probability toward LAS production. This work opens a new paradigm for designing high-performance non-noble metal catalysts for upgrading aqueous EtOH to LAS.

Highlights An air-breathing chemical self-charge concept of oxygen-enriched carbon cathode. The oxygen-enriched carbon material with abundant catechol groups. Rapid air-oxidation chemical self-charge of catechol groups. Abstract The self-charging concept has drawn considerable attention due to its excellent ability to achieve environmental energy harvesting, conversion and storage without an external power supply. However, most self-charging designs assembled by multiple energy harvesting, conversion and storage materials increase the energy transfer loss; the environmental energy supply is generally limited by climate and meteorological conditions, hindering the potential application of these self-powered devices to be available at all times. Based on aerobic autoxidation of catechol, which is similar to the electrochemical oxidation of the catechol groups on the carbon materials under an electrical charge, we proposed an air-breathing chemical self-charge concept based on the aerobic autoxidation of catechol groups on oxygen-enriched carbon materials to ortho-quinone groups. Energy harvesting, conversion and storage functions could be integrated on a single carbon material to avoid the energy transfer loss among the different materials. Moreover, the assembled Cu/oxygen-enriched carbon battery confirmed the feasibility of the air-oxidation self-charging/electrical discharging mechanism for potential applications. This air-breathing chemical self-charge concept could facilitate the exploration of high-efficiency sustainable air self-charging devices.

Mode-locked microcombs with flat spectral profiles provide the high signal-to-noise ratio and are in high demand for wavelength division multiplexing (WDM)-based applications, particularly in future high-capacity communication and parallel optical computing. Here, we present two solutions to generate local relatively flat spectral profiles. One microcavity with ultra-flat integrated dispersion is pumped to generate one relatively flat single soliton source spanning over 150 nm. Besides, one extraordinary soliton crystal with single vacancy demonstrates the local relatively flat microcomb lines when the inner soliton spacings are slightly irregular. Our work paves a new way for soliton-based applications owing to the relatively flat spectral characteristics.

Objective Syringomyelia is a common central nervous system disease characterized by the dilation of the central canal (CC). Regarding the pathogenesis of syringomyelia, cerebrospinal fluid (CSF) circulation obstruction in the subarachnoid space (SAS) of the spinal cord has been widely accepted. However, clinical and animal studies on obstructing the CSF in SAS failed to form syringomyelia, challenging the theory of SAS obstruction. The precise pathogenesis remains unknown. Methods We utilized an extradural compression rat model to investigate the pathogenesis underlying syringomyelia. Magnetic resonance imaging enabled detection of syringomyelia formation. To assess CSF flow within the SAS, Evans blue was infused into the cisterna magna. Histological analysis allowed morphological examination of the CC. Furthermore, CSF flow through the CC was traced using Ovalbumin Alexa-Flour 647 conjugate (OAF-647). Scanning electron microscopy (SEM) enabled visualization of ependymal cilia. Results The findings showed that the dura mater below the compression segment exhibited lighter coloration relative to the region above the compression, indicative of partial obstruction within the SAS. However, the degree of SAS occlusion did not significantly differ between syringomyelia (SM-Y group) and those without (SM-N group). Intriguingly, hematoxylin and eosin staining and CSF tracing revealed occlusion of the CC accompanied by reduced CSF flow in the SM-Y group compared to SM-N and control groups. SEM images uncovered impairment of ependymal cilia inside the syringomyelia. Conclusion CC occlusion may represent a physiological prerequisite for syringomyelia formation, while SAS obstruction serves to initiate disease onset. The impairment of ependymal cilia appears to facilitate progression of syringomyelia.

Abstract Background Exercise mimetics is a proposed class of therapeutics that specifically mimics or enhances the therapeutic effects of exercise. Muscle glycogen and lactate extrusion are critical for physical performance. The mechanism by which glycogen and lactate metabolism are manipulated during exercise remains unclear. This study aimed to assess the effect of miR‐92b on the upregulation of exercise training‐induced physical performance. Methods Adeno‐associated virus (AAV)‐mediated skeletal muscle miR‐92b overexpression in C57BLKS/J mice, and global knockout of miR‐92b mice were used to explore the function of miR‐92b in glycogen and lactate metabolism in skeletal muscle. AAV‐mediated UGP2 or MCT4 knockdown in WT or miR‐92 knockout mice was used to confirm whether miR‐92b regulates glycogen and lactate metabolism in skeletal muscle through UGP2 and MCT4. Body weight, muscle weight, grip strength, running time and distance to exhaustion, and muscle histology were assessed. The expression levels of muscle mass‐related and function‐related proteins were analysed by immunoblotting or immunostaining. Results Global knockout of miR‐92b resulted in normal body weight and insulin sensitivity, but higher glycogen content before exercise exhaustion (0.8538 ± 0.0417 vs. 1.043 ± 0.040, **P = 0.0087), lower lactate levels after exercise exhaustion (4.133 ± 0.2589 vs. 3.207 ± 0.2511, *P = 0.0279), and better exercise capacity (running distance to exhaustion, 3616 ± 86.71 vs. 4231 ± 90.29, ***P = 0.0006; running time to exhaustion, 186.8 ± 8.027 vs. 220.8 ± 3.156, **P = 0.0028), as compared with those observed in the control mice. Mice skeletal muscle overexpressing miR‐92b (both miR‐92b‐3p and miR‐92b‐5p) displayed lower glycogen content before exercise exhaustion (0.6318 ± 0.0231 vs. 0.535 ± 0.0194, **P = 0.0094), and higher lactate accumulation after exercise exhaustion (4.5 ± 0.2394 vs. 5.467 ± 0.1892, *P = 0.01), and poorer exercise capacity (running distance to exhaustion, 4005 ± 81.65 vs. 3228 ± 149.8, ***P

This is an essay in the field of mining engineering. The main minerals of Heishan iron mine are vanadium titanomagnetite and titanomagnetite. Due to the influence of ore properties, the grade of iron concentrate in this type of deposit is generally low and rich in titanium, silicon, magnesium and other elements, which limits the development benefits of this kind of deposit resources. If the grade of iron concentrate can be further improved in the beneficiation process, it will help to improve the mine benefits and reduce the smelting cost of iron concentrate. This paper systematically studies this type of iron ore by means of optical microscope, mineral dissociation analyzer (MLA) and chemical analysis. This type of iron ore was systematically studied by means of optical microscope, mineral dissociation analyzer (MLA) and chemical analysis.

Abstract Biofilms are complex multicellular communities formed by bacteria, and their extracellular polymeric substances are observed as surface-attached or non-surface-attached aggregates. Many types of bacterial species found in living hosts or environments can form biofilms. These include pathogenic bacteria such as Pseudomonas, which can act as persistent infectious hosts and are responsible for a wide range of chronic diseases as well as the emergence of antibiotic resistance, thereby making them difficult to eliminate. Pseudomonas aeruginosa has emerged as a model organism for studying biofilm formation. In addition, other Pseudomonas utilize biofilm formation in plant colonization and environmental persistence. Biofilms are effective in aiding bacterial colonization, enhancing bacterial resistance to antimicrobial substances and host immune responses, and facilitating cell‒cell signalling exchanges between community bacteria. The lack of antibiotics targeting biofilms in the drug discovery process indicates the need to design new biofilm inhibitors as antimicrobial drugs using various strategies and targeting different stages of biofilm formation. Growing strategies that have been developed to combat biofilm formation include targeting bacterial enzymes, as well as those involved in the quorum sensing and adhesion pathways. In this review, with Pseudomonas as the primary subject of study, we review and discuss the mechanisms of bacterial biofilm formation and current therapeutic approaches, emphasizing the clinical issues associated with biofilm infections and focusing on current and emerging antibiotic biofilm strategies.

Highlights The working principle of the asymmetric electrolyte and the long-term-seated contradictory issues were analyzed. The characterization methods for the interfaces of anolyte/catholyte and electrolyte/electrode were summarized for revealing the fundamental mechanism of asymmetric electrolytes. The future research directions for asymmetric electrolyte systems were proposed.

Abstract Background Embryo aneuploidy is a main of principal reason of pregnancy loss, in vitro fertilization (IVF) failure and birth defects in offspring. Previous researchs have demonstrated that Y chromosome AZFc microdeletion was associated with reproduction outcomes, however, the relationship between Y chromosome AZFc microdeletion and embryo aneuploidy remains unexplored. Methods This retrospective cohort study enrolled 513 patients with 603 cycles in the reproductive center of Nanjing Maternity and Child Health Care Hospital from January 1, 2016 to June 30, 2022. The study cohort was divided into two groups: the AZFc microdeletion group, comprising 53 patients and 58 cycles, and the control group, comprising 460 patients and 545 cycles. Statistical methods including restricted cubic spline and generalized estimating equation (GEE) were employed to evaluate the relationship between Y chromosome AZFc microdeletion and embryo euploidy. Results 294 and 2833 blastocysts were selected as AZFc microdeletion group and control group, respectively. Patients with Y chromosome AZFc microdeletion had significantly higher embryo aneuploid rate (33.0% vs. 27.3%, P

Several specimens of Upretia from Southwest China are morphologically and phylogenetically distinct from currently recognized species in the genus. These specimens are here accommodated within a new species, Upretia zeorina Li J. Li & Printzen. It is characterized by an areolate to squamulose thallus with brown to blackish brown upper surface, pruinose, zeorine type apothecia, black discs, narrowly bacilliform conidia, and the production of gyrophoric acid. Two other specimens of Upretia from China are distinct from currently accepted species and tentatively referred to as Upretia sp. 1 and Upretia sp. 2. A key to all known species of Upretia is also provided.

Abstract In this study, uniaxial compression tests and simultaneous acoustic emission (AE) monitoring were carried out on four rocks (yellow sandstone, white sandstone, marble and limestone). The mechanical properties and AE energy evolution characteristics of different rocks were analysed. With the help of critical slowing down (CSD) theory, the AE precursor characteristics of their failure were investigated. It is pointed out that the AE during rock loading has a CSD phenomenon. A sudden change in the variance of one of the CSD indicators can be regarded as a precursor to failure, and it has the advantage of being more accurate and sensitive to failure than the autocorrelation coefficient. The stress level of a rock's failure precursor is closely related to its brittleness characteristics. The higher the brittleness of the rock, the more backward the failure precursor is, and the more difficult the early warning is. The study aims to provide new indicators and references for the monitoring and early warning of rockbursts and other disasters induced by rock fracture in deep underground engineering.

The Russia–Ukraine conflict (RUC) has triggered a serious natural gas (hereafter referred to as gas) and oil supply crisis in Europe. We propose a quantile regression neural network model to capture the non-linear evolution of systemic risk in the European gas and oil markets. We find that the RUC significantly increased systemic risk in both the European gas and the oil markets. The systemic risk is higher, and rises much more quickly and falls much more slowly in the gas market than in the oil market. The dynamics of systemic risk are closely linked to major events during the RUC. The US-dollar-to-ruble exchange rate contributes most to this systemic risk, followed by Europe’s gas stocks and gas imports from Russia. In terms of risk exposure, the gas market is more vulnerable than the oil market. We propose an elasticity coefficient of systemic risk to evaluate its sensitivity to stress scenarios. Our study provides important insights into managing the systemic risk in European gas and oil markets after the RUC.

Heritable endosymbiont Wolbachia is prevalent among arthropods, serving multiple functions for their hosts. However, the role of Wolbachia in mediating thermal preference selection remains largely unexplored. In this study, we utilized a custom-built thermal gradient to evaluate the thermal preference (Tp) of 1367 individuals of the invasive leaf-miner Liriomyza huidobrensis with or without Wolbachia wLhui from Yunnan and Xinjiang populations. Under meticulously controlled conditions and with a vast sample size, we found no significant difference in the mean Tp between wLhui-infected and uninfected leaf miners from either population when host age and sex were not considered. Furthermore, generalized linear model (GLM) analysis revealed no significant correlation between average Tp and age, sex, or Wolbachia infection, nor interactions among these factors, except in the Xinjiang population, where Tp was strongly associated with host age. Finally, we discuss the ecological implications of these findings and propose future research directions on Wolbachia-mediated host Tp in the leaf miner. Overall, our findings do not provide evidence that Wolbachia significantly affects the thermal preference of L. huidobrensis. Further studies across different systems are needed to investigate the complex interactions between Wolbachia and insect thermal behavior.

Building envelopes and indoor environments exhibit thermal inertia, forming a virtual energy storage system in conjunction with the building air conditioner (AC) system. This system represents a current demand response resource for building electricity use. Thus, this study centers on the CatBoost algorithm within machine learning (ML) technology, utilizing the LASSO regression model for feature selection and applying the Optuna framework for hyperparameter optimization (HPO) to develop a cost-optimal control method for minimizing building AC loads. This method addresses the challenges associated with traditional load forecasting and control methods, which are often impacted by environmental temperature, building parameters, and user behavior uncertainties. These methods struggle to accurately capture the complex dynamics and nonlinear relationships of AC operations, making it difficult to devise AC operation and virtual energy storage scheduling strategies effectively. The proposed method was applied and validated using a case study of an office building in Nanjing, China. The prediction results showed coefficient of variation in root mean square error (CV-RMSE) values of 6.4% and 2.2%. Compared with the original operating conditions, the indoor temperature remained within a comfortable range, the AC load was reduced by 5.25%, and the operating energy costs were reduced by 24.94%. These results demonstrate that the proposed method offers improved computational efficiency, enhanced model performance, and economic benefits.

In this study, vinyltriethoxysilane (TEVS) was introduced onto the surface of carbon fiber using liquid-phase oxidation and impregnation methods to incorporate vinyl groups onto the carbon fiber, thereby enhancing the chemical bonding between the carbon fiber and norbornene–polyimide (PI-NA). Through a systematic study of the hydrolysis conditions and concentration of the TEVS solution, the optimal modification conditions were determined. These conditions were used to graft TEVS onto the surface of oxidized carbon fiber to prepare carbon-fiber-reinforced PI-NA composites (CF/PI-NA). The results show that when carbon fiber was treated with a 0.4 wt% TEVS solution, the interlaminar shear strength (ILSS) of the composites reached 65.12 MPa, and the interfacial shear strength (IFSS) reached 88.58 MPa, representing increases of 27.58% and 35.62%, respectively, compared to the CF/PI-NA composite materials prepared from untreated carbon fiber. It is worth noting that the modification method described in the study is simple and easy to implement, and it has the potential for large-scale continuous production applications.

The issues of the same material with different spectra and the same spectra for different materials pose challenges in hyperspectral rock classification. This paper proposes a multidimensional feature network based on 2-D convolutional neural networks (2-D CNNs) and recurrent neural networks (RNNs) for achieving deep combined extraction and fusion of spatial information, such as the rock shape and texture, with spectral information. Experiments are conducted on a hyperspectral rock image dataset obtained by scanning 81 common igneous and metamorphic rock samples using the HySpex hyperspectral sensor imaging system to validate the effectiveness of the proposed network model. The results show that the model achieved an overall classification accuracy of 97.925% and an average classification accuracy of 97.956% on this dataset, surpassing the performances of existing models in the field of rock classification.

Basic leucine zipper (bZIP) transcription factors (TFs) play a crucial role in anthocyanin accumulation in plants. In addition to bZIP TFs, abscisic acid (ABA) increases anthocyanin biosynthesis. Therefore, this study aimed to investigate whether bZIP TFs are involved in ABA-induced anthocyanin accumulation in sweet cherry and elucidate the underlying molecular mechanisms. Specifically, the BLAST method was used to identify bZIP genes in sweet cherry. Additionally, we examined the expression of ABA- and anthocyanin-related genes in sweet cherry following the overexpression or knockdown of a bZIP candidate gene. In total, we identified 54 bZIP-encoding genes in the sweet cherry genome. Basic leucine zipper 6 (bZIP6) showed significantly increased expression, along with increased anthocyanin accumulation in sweet cherry. Additionally, yeast one-hybrid and dual-luciferase assays indicated that PavbZIP6 enhanced the expression of anthocyanin biosynthetic genes (PavDFR, PavANS, and PavUFGT), thereby increasing anthocyanin accumulation. Moreover, PavbZIP6 interacted directly with the PavBBX6 promoter, thereby regulating PavNCED1 to promote abscisic acid (ABA) synthesis and enhance anthocyanin accumulation in sweet cherry fruit. Conclusively, this study reveals a novel mechanism by which PavbZIP6 mediates anthocyanin biosynthesis in response to ABA and contributes to our understanding of the mechanism of bZIP genes in the regulation of anthocyanin biosynthesis in sweet cherry.

A binocular stereo vision measurement system is widely used in fields such as industrial inspection and marine engineering due to its high accuracy, low cost, and ease of deployment. An unreasonable structural design can lead to difficulties in image matching and inaccuracies in depth computation during subsequent processing, thereby limiting the system’s performance and applicability. This paper establishes a systemic error analysis model to enable the validation of changes in structural parameters on the performance of the binocular vision measurement. Specifically, the impact of structural parameters such as baseline distance and object distance on measurement error is analyzed. Extensive experiments reveal that when the ratio of baseline length to object distance is between 1 and 1.5, and the angle between the baseline and the optical axis is between 30 and 40 degrees, the system measurement error is minimized. The experimental conclusions provide guidance for subsequent measurement system research and parameter design.

Laser dazzling on complementary metal oxide semiconductor (CMOS) image sensors is an effective method in optoelectronic countermeasures. However, previous research mainly focused on the laser dazzling under far fields, with limited studies on situations that the far-field conditions were not satisfied. In this paper, we established a Fresnel diffraction model of laser dazzling on a CMOS by combining experiments and simulations. We calculated that the laser power density and the area of saturated pixels on the detector exhibit a linear relationship with a slope of 0.64 in a log-log plot. In the experiment, we found that the back side illumination (BSI-CMOS) matched the simulations, with an error margin of 3%, while the front side illumination (FSI-CMOS) slightly mismatched the simulations, with an error margin of 14%. We also found that the full-screen saturation threshold for the BSI-CMOS was 25% higher than the FSI-CMOS. Our work demonstrates the applicability of the Fresnel diffraction model for BSI-CMOS, which provides a valuable reference for studying laser dazzling.

IntroductionThe prognosis for glioma is generally poor, and the 5-year survival rate for patients with this disease has not shown significant improvement over the past few decades. Parkinson’s disease (PD) is a prevalent movement disorder, ranking as the second most common neurodegenerative disease after Alzheimer’s disease. Although Parkinson’s disease and glioma are distinct diseases, they may share certain underlying biological pathways that contribute to their development.ObjectiveThis study aims to investigate the involvement of genes associated with Parkinson’s disease in the development and prognosis of glioma.MethodsWe obtained datasets from the TCGA, CGGA, and GEO databases, which included RNA sequencing data and clinical information of glioma and Parkinson’s patients. Eight machine learning algorithms were used to identify Parkinson-Glioma feature genes (PGFGs). PGFGs associated with glioma prognosis were identified through univariate Cox analysis. A risk signature was constructed based on PGFGs using Cox regression analysis and the Least Absolute Shrinkage and Selection Operator (LASSO) method. We subsequently validated its predictive ability using various methods, including ROC curves, calibration curves, KM survival analysis, C-index, DCA, independent prognostic analysis, and stratified analysis. To validate the reproducibility of the results, similar work was performed on three external test datasets. Additionally, a meta-analysis was employed to observe the heterogeneity and consistency of the signature across different datasets. We also compared the differences in genomic variations, functional enrichment, immune infiltration, and drug sensitivity analysis based on risk scores. This exploration aimed to uncover potential mechanisms of glioma occurrence and prognosis.ResultsWe identified 30 PGFGs, of which 25 were found to be significantly associated with glioma survival. The prognostic signature, consisting of 19 genes, demonstrated excellent predictive performance for 1-, 2-, and 3-year overall survival (OS) of glioma. The signature emerged as an independent prognostic factor for glioma overall survival (OS), surpassing the predictive performance of traditional clinical variables. Notably, we observed differences in the tumor microenvironment (TME), levels of immune cell infiltration, immune gene expression, and drug resistance analysis among distinct risk groups. These findings may have significant implications for the clinical treatment of glioma patients.ConclusionThe expression of genes related to Parkinson’s disease is closely associated with the immune status and prognosis of glioma patients, potentially regulating glioma pathogenesis through multiple mechanisms. The interaction between genes associated with Parkinson’s disease and the immune system during glioma development provides novel insights into the molecular mechanisms and targeted therapies for glioma.

With the gradual improvement of open teacher selection mechanisms, the comparison of traditionally and alternatively certified teachers has become one of the international focuses in teacher research. Current studies have compared teachers of different certification pathways from multidimensional perspectives; however, no study has yet compared the differences in curriculum leadership between the two types of teachers. Teacher curriculum leadership is the ability of teachers to collaborate with stakeholders in the curriculum area to promote curriculum optimization and the development of students and teachers, and it includes three dimensions: teachers’ curriculum leadership views, practices and identity. This study conducted a comparative analysis of the curriculum leadership of traditionally and alternatively certified teachers based on data from 9,068 teachers of 20 provinces in China. Independent samples t -test and multiple linear regression analysis revealed no significant differences between traditionally and alternatively certified teachers on the overall level of curriculum leadership and the three sub-dimensions of curriculum leadership views, practices, and identity. Theoretically, it provides new evidence for the debate about whether there are differences between the two types of teachers by further corroborating the conclusion that there is no significant difference in the educational effectiveness of traditionally and alternatively certified teachers. Practically, it justifies the rationality of an open teacher selection mechanism and points the way to further reforms in university teacher education.

Effectively improving the green innovation efficiency (GIE) in manufacturing is an important way to break through environmental and energy constraints. This study explored multiple mechanisms of carbon trading in GIE using a sample of A-share listed manufacturing enterprises in China from 2015 to 2020. The findings indicated that (1) carbon trading has a significant promoting effect on the GIE of manufacturing enterprises; (2) carbon trading promotes GIE by increasing government subsidies, research and development investment, and financing constraints; and (3) carbon trading has a single threshold effect on promoting GIE. When the carbon trading price (CTP) is at or below the threshold value, a 1% increase in CTP results in a 0.0785% increase in GIE; when the CTP exceeds the threshold value, the promotion effect weakens to 0.0498%. The threshold value varies according to the heterogeneity of property rights and technical intensity. The government should guide CTPs to the optimal range, provide reward-punishment mechanisms, and formulate stringent but distinct green innovation policies according to the specific characteristics of manufacturing enterprises. This study enriches the cutting-edge literature on environmental and energy economics and expands the research boundaries of carbon trading and enterprise GIE, which also helps improve the carbon trading market and provides micro-level theoretical guidance to deepen environmental policy in practice.

BackgroundBreast cancer (BC) represents a significant health challenge in Europe due to its elevated prevalence and heterogeneity. Despite notable progress in diagnostic and treatment methods, the region continues to grapple with rising BC burdens, with comprehensive investigations into this matter notably lacking. This study explores BC burden and potential contributing risk factors in 44 European countries from 1990 to 2019. The aim is to furnish evidence supporting the development of strategies for managing BC effectively.MethodsDisease burden estimates related to breast cancer from the Global Burden of Disease 2019(GBD2019) across Eastern, Central, and Western Europe were examined using Joinpoint regression for trends from 1990 to 2019. Linear regression models examined relationships between BC burden and Socio-demographic Index (SDI), healthcare access and quality (HAQ), and BC prevalence. We utilized disability-adjusted life year(DALY) proportions for each risk factor to depict BC risks.ResultsIn Europe, the BC burden was 463.2 cases per 100,000 people in 2019, 1.7 times the global burden. BC burden in women was significantly higher and increased with age. Age-standardized mortality and DALY rates of BC in Europe in 2019 decreased by 23.1%(average annual percent change: AAPC -0.92) and 25.9%(AAPC -1.02), respectively, compared to 1990, in line with global trends. From 1990 to 2019, age-standardized DALY declined faster in Western Europe (-34.8%, AAPC -1.49) than in Eastern Europe (-9.4%, AAPC -0.25) and Central Europe (-15.0%, AAPC -0.56). Monaco, Serbia, and Montenegro had the highest BC burden in Europe in 2019. BC burden was negatively correlated with HAQ. In addition, Alcohol use and Tobacco were significant risk factors for DALY. High fasting plasma glucose and obesity were also crucial risk factors that cannot be ignored in DALY.ConclusionThe burden of BC in Europe remains a significant health challenge, with regional variations despite an overall downward trend. Addressing the burden of BC in different regions of Europe and the increase of DALY caused by different risk factors, targeted prevention measures should be taken, especially the management of alcohol and tobacco should be strengthened, and screening services for BC should be popularized, and medical resources and technology allocation should be optimized.

Background: There is a lack of comprehensive profile assessment on complete blood count (CBC)-derived systemic-inflammatory indices, and their correlations with clinical outcome in patients with anterior circulation acute ischemic stroke (AIS) who achieved successful recanalization by endovascular thrombectomy (EVT). Methods: Patients with anterior circulation AIS caused by large vessel occlusion (AIS-LVO) were retrospectively screened from December 2018 to December 2022. Systemic-inflammatory indices including ratios of neutrophil-to-lymphocyte (NLR), monocyte-to-lymphocyte (MLR), platelet-to-lymphocyte (PLR), and platelet-to-neutrophil (PNR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate inflammation systemic index (AISI) on admission and the first day post-EVT were calculated. Their correlations with symptomatic intracranial hemorrhage (sICH) and unfavorable 90-day functional outcome (modified Rankin Scale score of 3–6) were analyzed. Results: A total of 482 patients [65 (IQR, 56–72) years; 33 % female] were enrolled, of which 231 (47.9 %) had unfavorable 90-day outcome and 50 (10.4 %) developed sICH. Day 1 neutrophil and monocyte counts, NLR, MLR, PLR, SII, SIRI, and AISI were increased, while lymphocyte and PNR were decreased compared to their admission levels. In multivariate analyses, neutrophil count, NLR, SII, and AISI on day 1 were independently associated with 90-day functional outcome. Moreover, day 1 neutrophil count, NLR, MLR, PLR, PNR, SII, and SIRI were independently linked to the occurrence of sICH. No admission variables were identified as independent risk factors for patient outcomes. Conclusion: CBC-derived systemic-inflammatory indices measured on the first day after successful EVT are predictive of 90-day functional outcome and the sICH occurrence in patients with anterior circulation AIS-LVO.

Summary: Many Gram-negative bacteria use type Ⅲ secretion system (T3SS) to inject effector proteins and subvert host signaling pathways, facilitating the growth, survival, and virulence. Notably, some bacteria harbor multiple distinct T3SSs with different functions. An extraordinary T3SS, the Escherichia coli Type III Secretion System 2 (ETT2), is widespread among Escherichia coli (E. coli) strains. Since many ETT2 carry genetic mutations or deletions, it is thought to be nonfunctional. However, increasing studies highlight ETT2 contributes to E. coli pathogenesis. Here, we present a comprehensive overview of genetic distribution and characterization of ETT2. Subsequently, we outline its functional potential, contending that an intact ETT2 may retain the capacity to translocate effector proteins and manipulate the host’s innate immune response. Given the potential zoonotic implications associated with ETT2-carrying bacteria, further investigations into the structure, function and regulation of ETT2 are imperative for comprehensive understanding of E. coli pathogenicity and the development of effective control strategies.

Groundwater is the main source of water for living and agriculture in an area. To investigate the relationship between water environment and Kaschin-beck disease (KBD), we collected published data on water samples (data from the KBD areas of Aba Prefecture, Qamdo area, the Yellow River Basin region and the non-KBD area of the Yangtze River Basin region) for thermodynamic simulations to further analyze the hydrogeochemical properties. The analysis results show that: (1) The groundwater in Aba Prefecture and Qamdo area is weakly alkaline. (2) The groundwater type in Aba Prefecture and Qamdo area is Ca-HCO3− type. (3) The average concentration of cations Mg2+and Ca2+ can be expressed as Yellow River Basin > Yangtze River Basin > Aba Prefecture > Qamdo area. The average concentration of cation Na+and anion Cl− can be expressed as Yellow River Basin > Qamdo area > Yangtze River Basin>Aba Prefecture. The value of TDS can be expressed as Yellow River Basin > Qamdo area > Yangtze River Basin > Aba Prefecture. This may indicate that there is no direct relationship between KBD and water environment. (4) The dissolution of calcite and dolomite in quartzite controls the change of element content of water. (5) Analysis of the Gibbs distribution shows that most of the elements in the groundwater of the KBD areas (Aba Prefecture, Qamdo area and the Yelllow River Basin region) and non-KBD area (the Yangtze River Basin region) majorly come from rock weathering. (6) The overall quality of groundwater is good, the salinity is low, and it is suitable for agricultural irrigation.

Moringa oleifera leaf peptide, which is a plant-derived bioactive peptide, exhibits several advantages, including safety, high efficiency and nontoxic side effects. The goal of this study was to identify representative antiosteoporotic peptides from Moringa oleifera leaf proteins and determine their regulatory mechanisms using network pharmacology, molecular docking and molecular dynamics. The following core targets of Moringa oleifera leaf antiosteoporotic peptides were screened by network pharmacology: SRC, MAPK1, JUN and STAT3. Through molecular docking, DPYLGK was identified as a representative active peptide from the Moringa oleifera leaf protein, and SRC was determined to be a potential primary target. Molecular dynamics revealed the intermolecular mechanism of DPYLGK and SRC. Cellular assays showed that DPYLGK promotes bone formation and inhibits bone resorption. These findings demonstrated that DPYLGK is an anti-osteoporotic peptide with dual regulatory effects and will aid in the development of functional foods to prevent osteoporosis.

Background: The diagnostic yield of radial endobronchial ultrasound (r-EBUS) for the diagnosis of peripheral pulmonary lesions (PPLs) varies between studies and is affected by multiple factors. We aimed to evaluate the efficacy and safety of r-EBUS, and to explore the factors influencing the diagnostic yield of r-EBUS in patients with PPLs. Methods: The PubMed, Web of Science, and EMBASE databases were searched to identify relevant studies that used r-EBUS for diagnosing PPLs from the date of inception to Dec 2022. Meta-analysis was conducted using Review Manager 5.4 and Stata 15.1. Results: An analysis of 46 studies with a total of 7252 PPLs was performed. The pooled diagnostic yield of r-EBUS was 73.4 % (95 % CI: 69.9%–76.7 %), with significant heterogeneity detected among studies (I2 = 90 %, P 2 cm in size, malignant in type, solid in appearance on computerized tomography (CT), present in bronchus sign, the within probe location, and the addition of rapid on-site evaluation (ROSE) were associated with increased diagnostic yield, whereas use of a guide sheath (GS), bronchoscopy type, and a multimodality approach failed to influence the outcome. The pooled incidence rates of overall complications, pneumothorax and moderate and severe bleeding were 3.1 % (95 % CI: 2.1%–4.3 %), 0.4 % (95 % CI: 0.1%–0.7 %) and 1.1 % (95 % CI: 0.5%–2.0 %), respectively. Conclusions: r-EBUS has an appreciable diagnostic yield and an excellent safety manifestation when used to deal with PPLs.

BackgroundBread wheat is one of the most important food crops associated with ensuring food security and human nutritional health. The starch quality is an important index of high-quality wheat. It is affected by a complex series of factors; among which, suitable sowing time is a key factor.Aim and methodsTo analyze the integrative effects of sowing time on the starch quality of high-quality wheat, in the present study, we selected a high-quality bread wheat cultivar Jinan 17 and investigated the effect of different sowing times on the starch properties and the related genes by analyzing X-ray diffraction patterns, apparent amylose content, thermal properties, pasting properties, in vitro starch digestibility, and qRT-PCR. Meanwhile, we also investigated the agronomic and yield performance that may be associated with the starch properties.ResultsDelayed sowing had little effect on starch crystalline morphology, but there was a tendency to reduce the formation of crystals within wheat starch granules: (1) delayed sowing for 15 days altered the thermal properties of starch, including onset, peak and termination temperatures, and enthalpy changes; (2) delayed sowing for 30 days changed the thermal characteristics of starch relatively insignificant; (3) significant differences in pasting characteristics occurred: peak viscosity and hold-through viscosity increased, while final viscosity, breakdown viscosity, and setback viscosity tended to increase and then decrease, suggesting that delayed sowing caused changes in the surface of the starch granules resulting in a decrease in digestibility. Analysis of related genes showed that several key enzymes in starch biosynthesis were significantly affected by delayed sowing, leading to a reduction in apparent straight-chain starch content. In addition to starch properties, thousand-kernel weight also increased under delayed sowing conditions compared with normal sowing.ConclusionThe impact of delayed sowing on starch quality is multifaceted and complex, from the fine structure, and functional properties of the starch to the regulation of key gene expression. Our study holds significant practical value for optimizing wheat planting management and maximizing the potential in both quality and yield.

The borehole-ground transient electromagnetic method enhances the detection range and resolution by placing the transmitter electrode within the borehole, allowing for close-proximity excitation of subsurface targets and compensating for the shortcomings of traditional ground-based methods. Utilizing an unstructured vector finite element method combined with a second-order backward Euler variable time-stepping difference scheme and the MUMPS solver, we have achieved three-dimensional forward modeling simulation of the transient electromagnetic field for a borehole-ground electric source. Based on the validation of its accuracy, we analyzed the effectiveness of this method for dynamic monitoring of shale gas reservoir fracturing. Through forward modeling, we examined the characteristics of the radial electric field response during shale gas reservoir fracturing monitoring and evaluated the effectiveness of the borehole-ground TEM method in dynamic monitoring of shale gas reservoirs. The research results indicate that this method can meet the requirements for reservoir fracturing dynamic monitoring and has a promising application prospect.

Study region: The Qinghai Lake basin on the Qinghai-Tibetan Plateau. Study focus: The abrupt rise of the water level of the Qinghai Lake after 2004 has garnered significant attention. Combining remote sensing and observed data, this study estimated the long-term variations in the water area and volume of the lake. In order to explore the factors contributing to the fluctuation in water level, the study developed annual and inter-annual water budgets for two time intervals: 1960 to 2004 and 2004 to 2020. Additionally, a hydrological model was implemented in the Buha River Basin, to gain further insight into the increased runoff and the impact of frozen soil. New hydrological insights for the region: The study found that the rise in lake level since 2004 was primarily driven by increased runoff, followed by increased precipitation, and decreased evaporation. Furthermore, water budgets were established for the freezing period (November to March of the next year) and the thawing period (April to October), respectively. The results revealed that the contribution of surface runoff during the thawing period was significantly larger at 68.20 % compared to 15.64 % during the freezing period, which is consistent to the conclusions of model simulation suggested. These findings suggest that the degradation of frozen soil in the Qinghai Lake Basin was a significant factor positively influencing surface runoff, with its impact intensifying after 2004.

Background: Forest fire is a very common natural or human-made disaster, which not only burns precious forest resources, but also further alters the forest ecosystem structure and functions as well as global climate. Accordingly, effective information extraction, data management, and modeling of historical fire events are imperative for forecasting and mitigating the onset and progression of forest fires. Traditional remote sensing-based forest fire detection and risk prediction operate at the pixel scale, overlooking the integrity of fire behaviour. Moreover, fire cause records typically stem from ground reports, not fully leveraging the advantages of high temporal resolution thermal infrared remote sensing products. Methods: We proposed a framework to identify the causes of forest fire events, experimenting with fire incidents from 2001 to 2020 in the Daxing'anling region of Northeast China. Initially, the Jenk-DBSCAN model was employed to acquire fire footprints representative of forest fire events from MODIS MCD64A1 product, and footprint-based fire event attribute information such as ignition locations and timings. Fire footprints matching ground surveys were subsequently filtered, and corresponding environmental variable datasets (including meteorological, topographical, fuel, and human activity factors) were derived in consideration of the spatio-temporal differences of footprint origin and center points. Finally, the optimal variable combinations of the two datasets were fed to three binary classification models including Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM) respectively to identify natural fires or human-induced fires, followed by assessing the accuracy of the fire cause identification models. Results: Results revealed that there was a high spatio-temporal consistency of those matched fire footprints between the model-extracted and the ground-recorded fire events, evidenced by an overall R2 of 0.87 derived from their area validation. The ignition dates extracted from fire footprints often preceded those reported by local agencies. Among all the selected variable combinations for fire cause identification, the meteorological variables dominated, with daily mean dew point (DEWP) and daily mean visibility (VISIB) being preferentially selected by most models. Across the six models, the model training AUC values were almost greater than 0.8, with the LR model demonstrating superior validation accuracy over RF and SVM. Notably, the accuracy of the LR model using the origin point based dataset surpassed that of the center point-based dataset. The best model achieved an overall accuracy of 90.48%, with the user’s accuracies for human-made fire and natural fire being at 92.86% and 85.71%, respectively. Conclusions: The proposed framework offers a reliable method for enriching attribute information in forest fire management databases. The resulting fire footprints and origin points can assist in better characterizing the progression of forest fire events. Such endeavours help devise targeted forest fire prevention regulations, fostering sustainable forest management.

Diabetes mellitus, a prevalent global health challenge, significantly impacts societal and economic well-being. Islet transplantation is increasingly recognized as a viable treatment for type 1 diabetes that aims to restore endogenous insulin production and mitigate complications associated with exogenous insulin dependence. We review the role of mesenchymal stem cells (MSCs) in enhancing the efficacy of islet transplantation. MSCs, characterized by their immunomodulatory properties and differentiation potential, are increasingly seen as valuable in enhancing islet graft survival, reducing immune-mediated rejection, and supporting angiogenesis and tissue repair. The utilization of MSC-derived extracellular vesicles further exemplifies innovative approaches to improve transplantation outcomes. However, challenges such as MSC heterogeneity and the optimization of therapeutic applications persist. Advanced methodologies, including artificial intelligence (AI) and single-cell RNA sequencing (scRNA-seq), are highlighted as potential technologies for addressing these challenges, potentially steering MSC therapy toward more effective, personalized treatment modalities for diabetes. This review revealed that MSCs are important for advancing diabetes treatment strategies, particularly through islet transplantation. This highlights the importance of MSCs in the field of regenerative medicine, acknowledging both their potential and the challenges that must be navigated to fully realize their therapeutic promise.

IntroductionCluster of differentiation (CD) 44 is a non-kinase cell surface transmembrane glycoprotein critical for tumor maintenance and progression.MethodsWe conducted a systematic analysis of the expression profile and genomic alteration profile of CD44 in 33 types of cancer. The immune characteristics of CD44 were comprehensively explored by TIMER2.0 and CIBERSORT. In addition, the CD44 transcriptional landscape was examined at the single-cell level. Then, Pseudotime trajectory analysis of CD44 gene expression was performed using Monocle 2, and CellChat was utilized to compare the crosstalk differences between CD44+monocytes and CD44- monocytes. Tumor immune dysfunction and exclusion (TIDE) was used to evaluate the predictive ability of CD44 for immune checkpoint blockade (ICB) responses. The effects of CD44 on colorectal cancer (CRC) and macrophage polarization were investigated by knocking down the expression of CD44 in HCT-116 cell and macrophages in vitro.ResultsThe expression of CD44 elevated in most cancers, predicting unfavorable prognosis. In addditon, CD44 was correlation with immune cell infiltration and key immune regulators. CD44+ monocytes had a higher information flow intensity than CD44- monocytes. CD44 had good predictive ability for immune checkpoint blockade responses. Knockdown of CD44 inhibited the proliferation, migration, and invasion of HCT-116 cell in vitro. Knockdown of CD44 inhibited M2 macrophage polarization.DiscussionThese findings suggest that CD44 is involved in regulating tumor development, macrophage polarization, and has certain predictive value for patient clinical prognosis and response to immunotherapy.

Abstract Detecting pancreatic duct adenocarcinoma (PDAC) in its early stages and predicting late‐stage patient prognosis undergoing chemotherapy is challenging. This work shows that the activation of specific oncogenes leads to elevated expression of mRNAs and their corresponding proteins in extracellular vesicles (EVs) circulating in blood. Utilizing an immune lipoplex nanoparticle (ILN) biochip assay, these findings demonstrate that glypican 1 (GPC1) mRNA expression in the exosomes‐rich (Exo) EV subpopulation and GPC1 membrane protein (mProtein) expression in the microvesicles‐rich (MV) EV subpopulation, particularly the tumor associated microvesicles (tMV), served as a viable biomarker for PDAC. A combined analysis effectively discriminated early‐stage PDAC patients from benign pancreatic diseases and healthy donors in sizable clinical from multiple hospitals. Furthermore, among late‐stage PDAC patients undergoing chemotherapy, lower GPC1 tMV‐mProtein and Exo‐mRNA expression before treatment correlated significantly with prolonged overall survival. These findings underscore the potential of vesicular GPC1 expression for early PDAC screenings and chemotherapy prognosis.

Hepatic ischemia/reperfusion injury (HIRI) is a common and inevitable factor leading to poor prognosis in various liver diseases, making the outcomes of current treatments in clinic unsatisfactory. Metformin has been demonstrated to be beneficial to alleviate HIRI in recent studies, however, the underpinning mechanism remains unclear. In this study, we found metformin mitigates HIRI-induced ferroptosis through reshaped gut microbiota in mice, which was confirmed by the results of fecal microbiota transplantation treatment but showed the elimination of the beneficial effects when gut bacteria were depleted using antibiotics. Detailedly, through 16S rRNA and metagenomic sequencing, we identified that the metformin-reshaped microbiota was characterized by the increase of gamma-aminobutyric acid (GABA) producing bacteria. This increase was further confirmed by the elevation of GABA synthesis key enzymes, glutamic acid decarboxylase and putrescine aminotransferase, in gut microbes of metformin-treated mice and healthy volunteers. Furthermore, the benefit of GABA against HIRI-induced ferroptosis was demonstrated in GABA-treated mice. Collectively, our data indicate that metformin can mitigate HIRI-induced ferroptosis by reshaped gut microbiota, with GABA identified as a key metabolite.

Summary: Iron overload is closely associated with metabolic dysfunction. However, the role of iron in the hypothalamus remains unclear. Here, we find that hypothalamic iron levels are increased, particularly in agouti-related peptide (AgRP)-expressing neurons in high-fat-diet-fed mice. Using pharmacological or genetic approaches, we reduce iron overload in AgRP neurons by central deferoxamine administration or transferrin receptor 1 (Tfrc) deletion, ameliorating diet-induced obesity and related metabolic dysfunction. Conversely, Tfrc-mediated iron overload in AgRP neurons leads to overeating and adiposity. Mechanistically, the reduction of iron overload in AgRP neurons inhibits AgRP neuron activity; improves insulin and leptin sensitivity; and inhibits iron-induced oxidative stress, endoplasmic reticulum stress, nuclear factor κB signaling, and suppression of cytokine signaling 3 expression. These results highlight the critical role of hypothalamic iron in obesity development and suggest targets for treating obesity and related metabolic disorders.