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A low-cost, wavelength-tunable single-longitudinal-mode (SLM) thulium–holmium co-doped fiber laser (THDFL) in a 2 μm band with a simple structure is described in the present paper. To obtain a stable SLM and narrow laser linewidth, a five-coupler-based three-ring (FCTR) filter is utilized in the ring cavity of the fiber laser. Tunable SLM wavelength output from THDFLs with kHz linewidths can be achieved by designing the FCTR filter with an effective free-spectral range and a 3 dB bandwidth at the main resonant peak. The measurement results show that the laser is in the SLM lasing state, with a highly stabilized optical spectrum, a linewidth of approximately 9.45 kHz, an optical signal-to-noise ratio as high as 73.6 dB, and a relative intensity noise of less than −142.66 dB/Hz. Furthermore, the wavelength can be tuned in the range of 2.6 nm. The proposed fiber laser has a wide range of applications, including coherence optical communication, optical fiber sensing, and dense wavelength-division-multiplexing.

Despite MCT oil’s potential antimicrobial benefits for gastrointestinal health, its effects on disrupting cariogenic pathogens on oral mucosal surfaces remain underexplored. This study evaluated the impact of MCT oil on the adhesion and invasion of Candida albicans and Streptoccocus mutans using planktonic and mucosal models. First, a planktonic model was used to assess the impact of various concentrations of MCT on the growth of S. mutans and C. albicans. Subsequently, a mucosal model was established by seeding TR-146 human buccal mucosal epithelial cells on a 3 µm porous transwell membrane, forming an epithelial barrier. MCT oil was then applied to the epithelial barriers in different durations (10, 30, and 60 min). Subsequently, C. albicans and S. mutans were introduced in the transwell and their adherence to the epithelial cells and their transmigration through the barriers was assessed using colony-forming unit counts and the barrier integrity was assessed by trans epithelial electrical resistance (TEER). Furthermore, cytotoxicity of MCT oil on mucosal cells was assessed by AlamarBlue assay. We found that higher MCT concentrations (90% and 100%) significantly inhibited C. albicans and S. mutans growth in planktonic conditions. Additionally, MCT oil reduced S. mutans adhesion to epithelial cells, highlighting its potential to interfere with bacterial attachment and colonization to oral mucosa. However, the oil had limited effects on C. albicans adhesion and transmigration. MCT demonstrated no cytotoxic effects on the viability of epithelial cells. The study findings highlight the potential benefits of MCT oil, particularly in oral bacterial inhibition, for oral health applications.

The study aimed to prepare complex gels of sonicated quinoa protein (QP) and polysaccharides, comparing the effects of different protein components and pH on gel properties. FTIR analysis demonstrated that the β-structure in protein at pH 7.0 was enhanced by ultrasonic treatment, which could promote the formation of a gel network. Moreover, XG-AG (gel prepared by xanthan gum and albumin) and XG-GG (gel prepared by xanthan gum and globulin) exhibited higher levels of disulfide bonds and free sulfhydryl groups in the gel, requiring more energy to break the intermolecular sulfide bonds during heating. Under the same heating conditions, the rheological properties and gel strength of XG-UQPG (gel prepared by xanthan gum and ultrasonically treated QP) were superior to those of XG-UGG (gel prepared by xanthan gum and ultrasonically treated globulin) and XG-UAG (gel prepared by xanthan gum and ultrasonically treated albumin). Additionally, XG-UGG (pH 7.0) demonstrated the highest water holding capacity (WHC) and oil holding capacity (OHC). This was attributed to the disulfide bonds created in the proteins by the ultrasound treatment, encouraging them to interact to form more uniform holes in gel that can hold more water/oil molecules. Conversely, at pH 4.5, the WHCs of the gels were reduced due to the presence of rougher protein structures. These findings shed light on the impact of protein composition on gel properties and offer insights into enhancing the quality of quinoa protein gel.

Angelica sinensis is a perennial herbaceous species mainly cultivated in the Gansu, Yunnan, and Qinghai provinces of China, and its dried roots have been widely used for nourishing blood and harmonizing vital energy, largely relying on its bioactive compounds (e.g., alkylphthalides, polysaccharides, and flavonoids). In recent years, viral diseases have been suspected to be present in A. sinensis in field cultivation. In order to reveal the infection status and causes, a survey and the identification of viral diseases and their influence on the yield and quality of A. sinensis were conducted in four different counties of Gansu province. The results showed viral disease rates of ca. 21% to 37% for potato virus Y (PVY) and tomato mosaic virus (ToMV), as well as ca. 2.8- to 8.9-fold decreases in root yield on a unit-area basis; meanwhile, the contents of the main bioactive compounds (i.e., ferulic acid, ligustilide, and polysaccharides) were significantly lower in the virus-infected plants (VIPs) compared with the virus-free plants (VFPs); there were significant positive relationships of the viral disease rate with planting density and expression levels of the PVY-coat protein (CP) and ToMV-CP genes (p < 0.01). The above-mentioned observations indicate that it is necessary and urgent to take measures (e.g., controlling plant density, rational rotation, and using virus-free seedlings) to prevent the spread of plant viruses.

The ‘Cuimi’ kumquat is a unique citrus cultivar known for its thin, crisp pulp and sweet, aromatic flavor. In addition to its use in fresh consumption and processing, this variety exhibits certain medicinal properties. This study aims to investigate the genetic diversity of the Huanglongbing (HLB) bacterium across different tissues of the ‘Cuimi’ kumquat, offering a theoretical basis for understanding the HLB epidemic in Dechang County, Sichuan. The research focuses on the absolute quantification of the HLB bacterium in seven specific tissues of the ‘Cuimi’ kumquat, including new leaves, upper phloem of branches, fruit peduncle, pith, fruit axis, old leaves, and lower phloem of branches. Additionally, the types and contents of prophages were identified in these tissues. In the same diseased branch group, Candidatus Liberibacter asiaticus (CLas) exhibited an uneven distribution, with the highest concentration detected in the pith, significantly surpassing levels found in the stem and leaf tissues (new leaves, upper phloem of branches, old leaves, lower phloem of branches). Infected fruit peduncles and pith slices showed noticeable shrinkage and collapse in the phloem. Prophage analysis indicated that multiple types of prophages could be simultaneously detected within the same infected ‘Cuimi’ kumquat branch. New shoot tissues contained both Type 2 and Type 4 prophages, with a relatively higher abundance of Type 4 and a lower abundance of Type 2. The relative abundance of Type 1 prophage in the fruit tissues was generally higher than in other tissues. CLas primarily accumulates in the fruit tissues of the ‘Cuimi’ kumquat, and the situation in Dechang County suggests that individual trees may be infected with multiple prophage strains simultaneously.

Individual tree structure and wood density are important indicators of forest quality and key parameters for biomass calculation. To explore the extraction accuracy of individual tree structure parameters based on LiDAR technology, as well as the correlation between individual tree structure parameters, resistance value and wood density can be beneficial for providing new ideas for predicting wood density. Taking a 23-year-old Ginkgo plantation as the research object, the tree QSM (Quantitative Structure Model) was constructed based on terrestrial and backpack LiDAR point clouds, and the individual tree structure parameters were extracted. The accuracy of estimating structure parameters based on two types of point clouds was compared. A wood density prediction model was constructed using principal component analysis based on the resistance, diameter, tree height, and crown width. The accuracy verification was carried out and it showed that the estimation accuracies of individual tree structure parameters (DBH, tree height, and crown width) extracted from tree QSM constructed based on TLS and BLS all had R2 > 0.8. The estimation accuracy of DBH based on TLS was slightly higher than that based on BLS, and the estimation accuracy of tree height and crown width based on TLS was slightly lower than that based on BLS. BLS has great potential in accurately obtaining forest structure information, improving forest information collection efficiency, promoting forest resource monitoring, forest carbon sink estimation, and forest ecological research. The feasibility of predicting the wood basic density based on wood resistance (R2 = 0.51) and combined with DBH, tree height, and crown width (R2 = 0.49) was relatively high. Accurate and non-destructive estimation of the wood characteristics of standing timber can guide forest cultivation and management and promote sustainable management and utilization of forests.

The variable coefficient nonlinear Schrödinger equation has a wide range of applications in various research fields. This work focuses on the wave propagation based on the variable coefficient nonlinear Schrödinger equation and the variable coefficient fractional order nonlinear Schrödinger equation. Due to the great challenge of accurately solving such problems, this work considers numerical simulation research on this type of problem. We innovatively consider using a mesoscopic numerical method, the lattice Boltzmann method, to study this type of problem, constructing lattice Boltzmann models for these two types of equations, and conducting numerical simulations of wave propagation. Error analysis was conducted on the model, and the convergence of the model was numerical validated. By comparing it with other classic schemes, the effectiveness of the model has been verified. The results indicate that lattice Boltzmann method has demonstrated advantages in both computational accuracy and time consumption. This study has positive significance for the fields of applied mathematics, nonlinear optics, and computational fluid dynamics.

Due to the frequent occurrence of food safety problems in recent years, healthy diets are gradually receiving worldwide attention. Chemical pigments are used in smart food packaging because of their bright colors and high visibility. However, due to shortcomings such as carcinogenicity, people are gradually looking for natural pigments to be applied in the field of smart food packaging. In traditional smart food packaging, the indicator and the packaging bag substrate have different degrees of toxicity. Smart food packaging that combines natural colorants and cellulose-based hydrogels is becoming more and more popular with consumers for being natural, non-toxic, environmentally friendly, and renewable. This paper reviews the synthesis methods and characteristics of cellulose-based hydrogels, as well as the common types and characteristics of natural pigments, and discusses the application of natural colorants and cellulose-based hydrogels in food packaging, demonstrating their great potential in smart food packaging.

Metallic heterostructural nanocrystals (HNCs) hold immense potential in electrocatalytic carbon dioxide reduction reaction (CO2RR) owing to their abundant active sites and high intrinsic activity. However, a significant challenge still remains in achieving controlled nucleation and growth sites for HNCs on supports and comprehending the influence of the structure–activity relationship on electrocatalytic CO2RR performance. This work presents a photochemical self-assembly technique without the necessity for reducing agents or facet-specific capping agents. By controlling lattice mismatch and manipulating transfer paths of photo-generated carriers, we can precisely direct the growth sites and nucleation of nanocrystals, enabling the self-assembly of supported core–shell and Janus nanostructures. Compared to Pd(T)@Au core–shell HNCs with the same loading, Pd cube–Au Janus HNCs exhibit significantly enhanced selectivity and stability toward carbon monoxide (CO) production in CO2RR at less negative potentials. The Pd cube–Au Janus HNC electrocatalyst achieved a Faradaic efficiency (FE) of 92.6 ± 3.5% for CO electroreduction, accompanied by a current density of 72.3 mA·cm−2 at −0.58 V. This work provides an effective strategy for designing advanced supported tandem electrocatalysts to boost the selectivity and durability test of CO2RR.

Future communication systems must support high-speed mobile scenarios, while the mainstream Orthogonal Frequency Division Multiplexing (OFDM) technology faces severe inter-carrier interference in such environments. Therefore, the adoption of Orthogonal Time–Frequency Space (OTFS) modulation in 6G systems is an effective solution. The widely used single-pilot channel estimation in OTFS systems is susceptible to path loss and inaccurate fading coefficient estimation, leading to reduced estimation accuracy, signal distortion, and degraded overall system communication quality. To address this problem, this paper proposes a Constant-Amplitude Zero-Autocorrelation (CAZAC) sequence-based multi-pilot OTFS channel estimation scheme. The proposed method inserts multiple low-power pilots in the delayed Doppler domain (DD) and employs joint signal processing at the receiver to effectively suppress noise, thereby significantly improving the accuracy and reliability of channel estimation. Additionally, this paper analyzes the impact of CAZAC sequence length on estimation performance and provides reasonable parameter selection recommendations. In summary, this work proposes an innovative solution to the channel estimation challenge in OTFS systems, laying a solid theoretical foundation for the realization of future high-speed mobile communication technologies such as 6G, with important academic value and application prospects.

Background: Mask use is a critical precaution to prevent the transmission of SARS-CoV-2 in a crowded or densely populated indoor environment. There is still a lack of large-sample studies on mask use in children during the COVID-19 pandemic. Methods: A questionnaire was distributed to individuals under 18 years of age from the pediatric outpatient department from November 2021 to May 2022. Participants who were willing to be interviewed and had good communication and judgment skills participated in our study. Results: 5053 (a boy-to-girl ratio of 1.13:1 and a median age of 5 years) from 6200 individuals admitted to the pediatric outpatient department were enrolled in the study. The mask-wearing time increased in parallel with age. Children aged 3–5 years wore masks more correctly (χ2 = 41.591, P < 0.05), complained more about the discomfort (χ2 = 193.871, P < 0.05), and their parents/caregivers were significantly better aware of the preventive effect of masks on respiratory disease (χ2 = 19.501, P < 0.05) than parents/caregivers of other age groups. Masks designed for children were more used by those aged 3–5 years in outdoor settings. The commonest adverse events of mask-wearing were respiratory symptoms (61.2%), followed by dermatological symptoms (28.9%) and psychological symptoms (19.7%). Girls wore masks for a longer time and more correctly (χ2 = 10.598, P < 0.05) than boys. Compared with the pre-COVID-19 pandemic, wearing masks could significantly decrease the median frequency of respiratory infections during the COVID-19 pandemic (2[1–4] vs 3[2–4]; z = −2.692, P < 0.05). Conclusions: Wearing proper and well-fitted masks could significantly protect children from respiratory infections in a crowded or densely populated indoor environment during the COVID-19 pandemic. However, mask-associated adverse events, particularly in psychological symptoms, are needed to draw adequate attention, calling for early identifications and psychological interventions.

In recent decades, remote sensing of vegetative drought and phenology has gained considerable attention from researchers, leading to a significant increase in research activity in this area. While new drought indices are being proposed, there is also growing attention on how variations in phenology affect drought detection. This review begins by exploring the crucial role of satellite optical and thermal remote sensing technologies in monitoring vegetative drought. It presents common methods after revisiting the foundational concepts. Then, the review examines remote sensing of land surface phenology (LSP) due to its strong connection with vegetative drought. Subsequently, we investigate vegetative drought detection techniques that consider phenological variability and recommend approaches to improve the detection of vegetative drought, emphasizing the necessity to incorporate phenological metrics. Finally, we suggest potential future work and directions. Unlike other review papers on remote sensing of vegetative drought, this review uniquely surveys the comprehensive advancements in both detecting vegetative drought and estimating LSP through optical and thermal remote sensing. It also highlights the necessity and potential applications for these practices.

Although linear discriminant analysis (LDA)-based subspace learning has been widely applied to hyperspectral image (HSI) classification, the existing LDA-based subspace learning methods exhibit several limitations: (1) They are often sensitive to noise and demonstrate weak robustness; (2) these methods ignore the local information inherent in data; and (3) the number of extracted features is restricted by the number of classes. To address these drawbacks, this paper proposes a novel joint sparse local linear discriminant analysis (JSLLDA) method by integrating embedding regression and locality-preserving regularization into the LDA model for feature dimensionality reduction of HSIs. In JSLLDA, a row-sparse projection matrix can be learned, to uncover the joint sparse structure information of data by imposing a L2,1-norm constraint. The L2,1-norm is also employed to measure the embedding regression reconstruction error, thereby mitigating the effects of noise and occlusions. A locality preservation term is incorporated to fully leverage the local geometric structural information of the data, enhancing the discriminability of the learned projection. Furthermore, an orthogonal matrix is introduced to alleviate the limitation on the number of acquired features. Finally, extensive experiments conducted on three hyperspectral image (HSI) datasets demonstrated that the performance of JSLLDA surpassed that of some related state-of-the-art dimensionality reduction methods.

Background: The evaluation of HPV vaccine effectiveness is essential for informing public health strategies, yet there remains a gap in understanding humoral immune responses generated by different HPV vaccine formulations in regional populations. This study addresses this gap by evaluating the immunogenicity of the newly developed HPV vaccine Cecolin (Wantai), alongside various imported vaccines, including bivalent, quadrivalent, and nonavalent options available in China. Methods: From March 2023 to June 2024, a total of 352 participants were enrolled, including 87 females aged 9–14 years who received two doses of the bivalent HPV vaccine (Cecolin), 215 females aged 15–45 years who were fully vaccinated with various HPV vaccines, and 50 non-recipients. Follow-up assessments were conducted at six timepoints during the administration of Cecolin. Serum was collected at enrollment and at each follow-up visit for antibody assessments using a pseudovirion-based neutralization assay (PBNA). Findings: The longitudinal follow-up of females aged 9–14 years revealed a 100% conversion rate for neutralizing antibodies against HPV types 16 and 18 after the second dose, compared to 94.3% and 97.1% conversion rates six months after the first dose. Compared to participants who received full doses of quadrivalent and nonavalent vaccines, females who received two or three doses of Cecolin exhibited higher neutralizing antibody geometric mean titers (GMTs) and non-vaccine-type (HPV31 and HPV33) antibody seroconversion rates. Interpretation: The domestically produced HPV vaccine Cecolin in China demonstrates strong immunogenicity and holds promise for the large-scale vaccination of females in developing countries to prevent cervical cancer.

For a large ensemble of complex systems, a Many-System Problem (MSP) studies how heterogeneity constrains and hides structural mechanisms, and how to uncover and reveal hidden major factors from homogeneous parts. All member systems in an MSP share common governing principles of dynamics, but differ in idiosyncratic characteristics. A typical dynamic is found underlying response features with respect to covariate features of quantitative or qualitative data types. Neither all-system-as-one-whole nor individual system-specific functional structures are assumed in such response-vs-covariate (Re-Co) dynamics. We developed a computational protocol for identifying various collections of major factors of various orders underlying Re-Co dynamics. We first demonstrate the immanent effects of heterogeneity among member systems, which constrain compositions of major factors and even hide essential ones. Secondly, we show that fuller collections of major factors are discovered by breaking heterogeneity into many homogeneous parts. This process further realizes Andersons More is Different phenomenon. We employ the categorical nature of all features and develop a Categorical Exploratory Data Analysis (CEDA)-based major factor selection protocol. Information theoretical measurements-conditional mutual information and entropy-are heavily used in two selection criteria: C1-confirmable and C2-irreplaceable. All conditional entropies are evaluated through contingency tables with algorithmically computed reliability against the finite sample phenomenon. We study one artificially designed MSP and then two real collectives of Major League Baseball (MLB) pitching dynamics with 62 slider pitchers and 199 fastball pitchers, respectively. Finally, our MSP data analyzing techniques are applied to resolve a scientific issue related to the Rosenberg Self-Esteem Scale.

With the proposal of China’s “double carbon” goal, the use of new energy power generation will gradually replace fossil energy power generation, which requires energy storage technology to store. The discharging characteristics of the energy storage units have a great impact on the system performance. The discharging characteristics of solid heat storage magnesia bricks were studied through simulation and experiment. The experimental results showed that the discharging completion of 6-channel was 5% higher than that of 2-channel at the end of discharging. The discharging completion of 12 m/s wind velocity was 3% higher than that of 6 m/s. Through simulation, the heat extraction of 6 channels was 15.8% and 3.3% higher than that of 2-channel and 4-channel, and the heat extraction of 9 m/s was 0.2% and 2.9% higher than that of 6 m/s and 12 m/s. The error between simulation and experiment was less than 10%, which verified the accuracy of the model and proved that it can be extended to other working conditions. It is recommended to use 6-channel heat storage bricks and the wind velocity shall not exceed 12 m/s.

Our objective was to construct a polygenic risk score (PRS) and assess its utility and effectiveness in predicting the risk of gestational diabetes mellitus (GDM) in a Chinese population. We performed a case-control study involving 638 patients with GDM and 1,062 healthy controls. Genotyping was conducted utilizing a genome-wide association study (GWAS), and a PRS was constructed. We identified 12 susceptibility loci that exhibited significant associations with the risk of GDM at a p-value threshold of ≤5.0 × 10–8, of which four loci were newly discovered. A higher PRS was associated with an increased risk of GDM (OR: 1.44; 95% CI: 1.03, 2.01 for the highest quartile compared to the lowest quartile). The PRS demonstrated a clear linear relationship with the fasting plasma glucose (FPG), 1-hour postprandial glucose (1hPG), and 2-hour postprandial glucose (2hPG) levels. The maximally adjusted β coefficients and their corresponding 95% CIs were 0.181 (0.041, 0.320) for FPG, 0.225 (0.103, 0.346) for 1hPG, and 0.172 (0.036, 0.307) for 2hPG. Among the genetic variants examined, TCF7L2 rs7903146 displayed the strongest association with GDM risk (logOR = 0.18, p = 2.37 × 10–19), followed by ADAMTSL1 rs10963767 (logOR = 0.14, p = 3.58 × 10–15). The areas under the curve (AUCs) was significantly increased from 0.703 (0.678, 0.728) in the traditional risk factor model to 0.765 (0.741, 0.788) by including PRS. These findings indicate that pregnant women with a higher PRS could potentially derive considerable advantages from the implementation of a feasible PRS-based GDM screening program aimed at delivering precision prevention strategies within Chinese populations.

AIM: To analyze research hotspots and trends of artificial intelligence in diabetic retinopathy(DR)based on bibliometrics and high-impact papers.METHODS: Papers on artificial intelligence in DR research published in the Web of Science Core Collection(WoSCC)from January 1, 2012, to December 31, 2022 were retrieved. The data was analyzed by CiteSpace software to examine annual publication number, countries, institutions, source journal, research categories, keywords, and to perform an in-depth analysis of high-impact papers.RESULTS: A total of 1 009 papers on artificial intelligence in DR from 79 countries were included in the study, with 272 papers published in 2022. Notably, China and India contributed 287 and 234 papers, respectively. The United Kingdom exhibited a centrality score of 0.31, while the United States boasted an impressive H-index of 48. Three prominent institutions in the United Kingdom(University of London, Moorfields Eye Hospital, and University College London)and one institution in Egypt(Egyptian Knowledge Bank)all achieved a notable H-index of 14. The primary academic disciplines associated with this research field encompassed ophthalmology, computer science, and artificial intelligence. Burst keywords in the years 2021～2022 included transfer learning, vessel segmentation, and convolutional neural networks.CONCLUSION: China emerged as the leading contributor in terms of publication number in this field, while the United States stood out as a key player. Notably, Egyptian Knowledge Bank and University of London assumed leading roles among research institutions. Additionally, IEEE Access was identified as the most active journal within this domain. The research focus in the field of artificial intelligence in DR has transitioned from AI applications in disease detection and grading to a more concentrated exploration of AI-assisted diagnostic systems. Transfer learning, vessel segmentation, and convolutional neural networks hold substantial promise for widespread applications in this field.

Introduction: Pulmonary fibrosis is a major cause of the poor prognosis of acute respiratory distress syndrome (ARDS). While mechanical ventilation (MV) is an indispensable life-saving intervention for ARDS, it may cause the remodeling process in lung epithelial cells to become disorganized and exacerbate ARDS-associated pulmonary fibrosis. Piezo1 is a mechanosensitive ion channel that is known to play a role in regulating diverse physiological processes, but whether Piezo1 is necessary for MV-exacerbated ARDS-associated pulmonary fibrosis remains unknown. Objectives: This study aimed to explore the role of Piezo1 in MV-exacerbated ARDS-associated pulmonary fibrosis. Methods: Human lung epithelial cells were stimulated with hydrochloric acid (HCl) followed by mechanical stretch for 48 h. A two-hit model of MV after acid aspiration-induced lung injury in mice was used. Mice were sacrificed after 14 days of MV. Pharmacological inhibition and knockout of Piezo1 were used to delineate the role of Piezo1 in MV-exacerbated ARDS-associated pulmonary fibrosis. In some experiments, ATP or the ATP-hydrolyzing enzyme apyrase was administered. Results: The stimulation of human lung epithelial cells to HCl resulted in phenotypes of epithelial-mesenchymal transition (EMT), which were enhanced by mechanical stretching. MV exacerbated pulmonary fibrosis in mice exposed to HCl. Pharmacological inhibition or knockout of Piezo1 attenuated the MV-exacerbated EMT process and lung fibrosis in vivo and in vitro. Mechanistically, the observed effects were mediated by Piezo1-dependent Ca2+ influx and ATP release in lung epithelial cells. Conclusions: Our findings identify a key role for Piezo1 in MV-exacerbated ARDS-associated pulmonary fibrosis that is mediated by increased ATP release in lung epithelial cells. Inhibiting Piezo1 may constitute a novel strategy for the treatment of MV-exacerbated ARDS-associated pulmonary fibrosis.

Although approximately half of all metastatic colorectal cancers (mCRCs) harbour mutations in KRAS or NRAS, hardly any progress has been made regarding targeted treatment for this group over the last few years. Here, we investigated the efficacy of vertical inhibition of the RAS‐pathway by targeting epidermal growth factor receptor (EGFR) and mitogen‐activated protein kinase kinase (MEK) in patient‐derived xenograft (PDX) tumours with primary KRAS mutation. In total, 19 different PDX models comprising 127 tumours were tested. Responses were evaluated according to baseline tumour volume changes and graded as partial response (PR; ≤ − 30%), stable disease (SD; between −30% and +20%) or progressive disease (PD; ≥ + 20%). Vertical inhibition with trametinib and cetuximab induced SD or PR in 74% of analysed models, compared to 24% by monotherapy with trametinib. In cases of PR by vertical inhibition (47%), responses were lasting (as long as day 137), with a low incidence of secondary resistance (SR). Molecular analyses revealed that primary and SR was driven by transcriptional reprogramming activating the RAS pathway in a substantial fraction of tumours. Together, these preclinical data strongly support the translation of this combination therapy into clinical trials for CRC patients.

Abstract The formal C–C bond insertion into aldehydes is an attractive methodology for the assembly of homologated carbonyl compounds. However, the homologation of aldehydes has been limited to diazo approach and the enantioselective reaction was rarely developed. Herein, we report an asymmetric formal C–C bond insertion into aldehydes through diyne cyclization strategy. In the presence of Cu(I)/SaBOX catalyst, this method leads to the efficient construction of versatile axially chiral naphthylpyrroles in moderate to excellent yields with good to excellent enantioselectivities. This protocol represents a rare example of asymmetric formal C–C bond insertion into aldehydes using non-diazo approach. The combined experimental and computational mechanistic studies reveal the reaction mechanism, origin of regioselectivity and stereoselectivity. Notably, the chiral phosphine ligand derived from synthesized axially chiral skeleton was proven to be applicable to asymmetric catalysis.

Abstract In recent years, ground‐based aerospace tracking, telemetry and control (TT&C) systems have been shifting towards an IP‐based cloud TT&C network architecture to improve signal transmission efficiency and system flexibility. However, this new architecture presents new challenges for the performance of tracking loops in the cloud‐based TT&C receiver. The authors present a predictive compensation tracking loop that addresses the problem of packet loss. The loop utilises radial basis function (RBF) online network identification for robust carrier and code frequency offset tracking. To account for packet loss, the phenomenon is modelled as a Bernoulli random process, and the predictive compensation loop uses the trained RBF network to maintain the system's tracking state. When normal data are received again, the loop can track the received information well and align the frequency offset locking state. The authors compare the performance of the proposed predictive compensation tracking loop with traditional loop tracking performance using data hold strategies under different packet loss rates. The results demonstrate the effectiveness of the proposed approach in maintaining stable tracking and solving in the discontinuous reception of the loop under packet loss environments. The proposed predictive compensation tracking loop offers a practical solution for addressing packet loss, which is a common issue in real‐world applications.

Abstract Anterior cruciate ligament (ACL) injury, a common sports injury, is associated with a high risk of subsequent osteoarthritis (OA), which can cause serious pain and disability. Understanding the detailed mechanism underlying the predisposition of knee with ACL injury to secondary OA at an early stage is key to preventing future degradation and progression to a clinically significant disease. A total of 56 male Sprague Dawley rats (age, 8 weeks; weight, 180–220 g) were randomly divided into three experimental groups: control, ACL transection (ACLT; where surgical procedure was performed with ACLT), and sham (where surgical procedure was performed without ACLT). The ACLT and sham groups were further divided into three subgroups based on when the rats were sacrificed: 4, 8, and 12 weeks after the surgical procedure. The control group and the aforementioned subgroups contained 8 rats each. We used nuclear magnetic resonance (NMR)-based metabolomic analysis to analyze rat serum samples for the metabolic characteristics and the underlying mechanisms. In total, 28 metabolites were identified in the NMR spectra of the rat sera. At 4 and 8 weeks postoperatively, the sham group demonstrated metabolic profiles different from those of the ACLT group. However, this difference was not observed 12 weeks postoperatively. In total, five metabolites (acetate, succinate, sn-glycero-3-phosphocholine, glucose, and phenylalanine) and five metabolic pathways (phenylalanine, tyrosine, and tryptophan biosynthesis; phenylalanine metabolism; pyruvate metabolism; starch and sucrose metabolism; and histidine metabolism) demonstrated significant differences between the ACLT and sham groups. ACL injury was noted to considerably affect biochemical homeostasis and metabolism; however, these metabolic changes persisted briefly. Moreover, glucose was a characteristic metabolite, and several energy-related metabolic pathways were significantly disturbed. Therefore, an ACL injury may lead to considerable impairments in energy metabolism. Abnormal glucose levels facilitate chondrocyte function impairment and thereby lead to OA progression. Furthermore, lactate may aid in identifying metabolic changes specific to knee trauma not related to an ACL injury. Overall, the metabolic changes in rat serum after an ACL injury were closely related to disturbances in energy metabolism and amino acid metabolism. The current results may aid in understanding the pathogenesis of posttraumatic osteoarthritis.

Abstract Non-retroviral endogenous viral elements (nrEVEs) are widely dispersed throughout the genomes of eukaryotes. Although nrEVEs are known to be involved in host antiviral immunity, it remains an open question whether they can be domesticated as functional proteins to serve cellular innovations in arthropods. In this study, we found that endogenous toti-like viral elements (ToEVEs) are ubiquitously integrated into the genomes of three planthopper species, with highly variable distributions and polymorphism levels in planthopper populations. Three ToEVEs display exon‒intron structures and active transcription, suggesting that they might have been domesticated by planthoppers. CRISPR/Cas9 experiments revealed that one ToEVE in Nilaparvata lugens, NlToEVE14, has been co-opted by its host and plays essential roles in planthopper development and fecundity. Large-scale analysis of ToEVEs in arthropod genomes indicated that the number of arthropod nrEVEs is currently underestimated and that they may contribute to the functional diversity of arthropod genes.

Abstract Green technologies, such as solar panels, foster the use of clean energy, yet often involve large-scale investments. Hence, adoption by retail consumers has been a key barrier. Here, we show that message framing can significantly increase customers’ serious commitment to adopting solar panels by providing empirical evidence in the field from a large-scale randomized controlled trial with a nationwide online retailer in the Netherlands (N = 26,873 participants). We design four messages aimed at promoting the purchase behavior of solar panel installations. Our messages present outcomes for oneself or for the environment and highlight cost savings versus earnings (for oneself) or reducing emissions versus generating green electricity (for the environment). Across all messages, we observe a higher rate of customers committing to solar panels compared to the baseline. However, the framing in terms of financial savings for oneself was by far the most effective, resulting in a 40% higher level of commitment than the baseline and 30% higher than the average of the other three messages, which were not significantly different in effect from each other. Our results show that message framing is cost-efficient and scalable among retail consumers to promote large-scale investments in green technologies and thus clean energy.

ABSTRACT: Lacto-N-tetraose (LNT) is one of the most important components of human milk oligosaccharides, which has various beneficial health effects. β-Galactosidase is an important enzyme used in dairy processing. The transglycosylation activity of β-galactosidases offers an attractive approach for LNT synthesis. In this study, we reported for the first time the biochemical characterization of a novel β-galactosidase (LzBgal35A) from Lacticaseibacillus zeae. LzBgal35A belongs to glycoside hydrolases (GH) family 35 and shared the highest identity of 59.9% with other reported GH 35 members. The enzyme was expressed as soluble protein in Escherichia coli. The purified LzBgal35A displayed optimal activity at pH 4.5 and 55°C. It was stable within the pH range of 3.5 to 7.0 and up to 60°C. Moreover, LzBgal35A could catalyze the synthesis of LNT via transferring the galactose residue from o-nitrophenyl-β-galactopyranoside to lacto-N-triose II. Under optimal conditions, the conversion rate of LNT reached 45.4% (6.4 g/L) within 2 h, which was by far the highest yield of LNT synthesized through a β-galactosidase-mediated transglycosylation reaction. This study demonstrated that LzBgal35A has great potential application in LNT synthesis.

Abstract Objectives Pulmonary embolism (PE) is a life‐threatening complication that can occur in patients with lung cancer. In this study, we aimed to identify risk factors and examine the clinical characteristics of advanced lung cancer patients with PE. Methods We conducted a retrospective review of patients admitted to our two hospitals between January 2020 and June 2022. The case group consisted of patients with lung cancer and PE, and a closely matched control group was included to identify risk factors. Statistical analysis was conducted using R language. Results A total of 4957 patients were reviewed, and 162 patients (comprising 54 cases and 108 controls) were included in this study. The prevalence of lung cancer with PE in the study population was 1.08%. The majority of patients were male, and the most common histological subtype was adenocarcinoma (67%), followed by squamous cell carcinoma, small cell carcinoma, and poorly differentiated non‐small cell lung cancer. The majority of patients had a high performance status (PS) score, with 50% experiencing respiratory failure (mainly hypoxia) and 33% with deep vein thrombosis (DVT). Forty‐eight percent of patients were diagnosed with concurrent PE. Further analysis showed that PE was an independent predictor of poor survival, and a PS score of >1 was an independent risk factor for PE in patients with lung cancer. Conclusion Our study provides valuable insights into the epidemiology and prognosis of PE in lung cancer patients and suggests that a poor ECOG PS, which has not been previously reported, is an independent risk factor for PE.

In recent years, contamination of mineral oil hydrocarbons (MOH) in milk powder, especially infant formula, has become a public concern, and related international regulation has gradually escalated. However, there is no standard method for the determination of MOH in milk powder. In this paper, the sample pretreatment method based on the EU limits and analytical requirements were improved and optimized, and the saponification method, hexane extraction, silica gel clean-up, epoxidation reaction method in order were used, and a highly sensitive method for the determination of mineral oils of saturated hydrocarbons (MOSH) and mineral oils of aromatic hydrocarbons (MOAH) in milk powder by on-line high performance liquid chromatography-gas chromatography (HPLC-GC) were established. Results showed that, the method achieved a limit of quantification (LOQ) of 0.5 mg/kg and recoveries of 81.1%~112.0% (RSD=0.3%~3.8%), meeting the method requirements of the European Joint Research Center (JRC). The method was applied to analyze the international proficiency testing samples, and the results showed the detection results of MOSH and MOAH from C16 to C25 and C25 to C35 were close to the true values, and the absolute values of their z'-scores were less than 2. This indicated that the method passed the validation, and the method could be referred to as the standard for the determination of MOSH and MOAH in milk powder.

Abstract Objectives To examine the characteristics of blood lymphocyte subsets in dermatomyositis-interstitial lung disease (DM-ILD) inflicted patients with positive anti-melanoma differentiation-associated gene 5 (anti-MDA5), as well as its prognosis value in this set of patients. Methods Data were retrospectively collected from 253 DM-ILD patients from three hospitals in China between January 2016 to January 2021. Patients were grouped into anti-MDA5 antibody positive group (MDA5+ DM-ILD) and anti-MDA5 antibody negative group (MDA5− DM-ILD) based on myositis-specific autoantibody test results. Demographic characteristics, lymphocyte subsets patterns and other clinical features were compared between the two groups. The association of lymphocyte subsets with 180-day mortality was investigated using survival analysis in MDA5+ DM-ILD. Results Out of 253 eligible patients with DM-ILD, 59 patients were anti-MDA5+ and 194 were anti-MDA5−. Peripheral blood lymphocyte count, CD3+ count, percentage of CD3+, CD3+CD4+ count, and CD3+CD8+ count was lower in MDA5+ DM-ILD than in MDA5− DM-ILD− (all P

Abstract Increasing evidence shows the African lineage Zika virus (ZIKV) displays a more severe neurovirulence compared to the Asian ZIKV. However, viral determinants and the underlying mechanisms of enhanced virulence phenotype remain largely unknown. Herein, we identify a panel of amino acid substitutions that are unique to the African lineage of ZIKVs compared to the Asian lineage by phylogenetic analysis and sequence alignment. We then utilize reverse genetic technology to generate recombinant ZIKVs incorporating these lineage-specific substitutions based on an infectious cDNA clone of Asian ZIKV. Through in vitro characterization, we discover a mutant virus with a lysine to arginine substitution at position 101 of capsid (C) protein (termed K101R) displays a larger plaque phenotype, and replicates more efficiently in various cell lines. Moreover, K101R replicates more efficiently in mouse brains and induces stronger inflammatory responses than the wild type (WT) virus in neonatal mice. Finally, a combined analysis reveals the K101R substitution promotes the production of mature C protein without affecting its binding to viral RNA. Our study identifies the role of K101R substitution in the C protein in contributing to the enhanced virulent phenotype of the African lineage ZIKV, which expands our understanding of the complexity of ZIKV proteins.

Abstract Objective To evaluate the clinical efficacy of photodynamic therapy (PDT) as an adjunct or alternative to traditional antifungal drugs in the treatment of oral candidiasis, and to provide evidence-based medical evidence for its use in the treatment of oral candidiasis. Methods Computer combined with manual retrieval of China Academic Journals Full-text Database (CNKI), China Biomedical Literature Database (CBM), Chinese Science and Technology Journal Database (VIP), Wanfang Database, PubMed, Web of Science, Cochrane Library, Embase, Scopus retrieval for articles published before January 2023, basic information and required data were extracted according to the inclusion and exclusion criteria, and the Revman V5.4 software was used to conduct Meta-analysis of the included literature. Results A total of 11 articles were included, 7 of which used nystatin as an antifungal drug, 2 of which were combined treatment of PDT and nystatin, 2 of the remaining 4 articles were treated with fluconazole, and 2 were treated with miconazole. Meta results showed that PDT was superior to nystatin in reducing the number of oral candida colonies in the palate of patients MD = -0.87, 95%CI = (-1.52,-0.23), P = 0.008, the difference was statistically significant, and the denture site MD = -1.03, 95%CI = (-2.21, -0.15), P = 0.09, the difference was not statistically significant; compared with the efficacy of fluconazole, RR = 1.01, 95%CI = (0.56,1.83), P = 0.96; compared with miconazole RR = 0.55, 95%CI = (0.38, 0.81), P = 0.002; PDT combined with nystatin RR = 1.27, 95%CI = (1.06, 1.52), P = 0.01; recurrence rate RR = 0.28, 95%CI = (0.09, 0.88), P = 0.03. Conclusions PDT was effective in the treatment of oral candidiasis; PDT was more effective than nystatin for the treatment of denture stomatitis in the palate, while there was no significant difference between the two for the denture site; The efficacy of PDT for oral candidiasis was similar to that of fluconazole; PDT was less effective than miconazole for oral candidiasis; Compared with nystatin alone, the combination of PDT and nystatin is more effective in treating oral candidiasis with less risk of recurrence.

Abstract Background To investigate the association between CT signs and clinicopathological features and disease recurrence in patients with hepatoid adenocarcinoma of stomach (HAS). Methods Forty nine HAS patients undergoing radical surgery were retrospectively collected. Association between CT and clinicopathological features and disease recurrence was analyzed. Multivariate logistic model was constructed and evaluated for predicting recurrence by using receiver operating characteristic (ROC) curve. Survival curves between model-defined risk groups was compared using Kaplan–Meier method. Results 24(49.0%) patients developed disease recurrence. Multivariate logistic analysis results showed elevated serum CEA level, peritumoral fatty space invasion and positive pathological vascular tumor thrombus were independent factors for disease recurrence. Odds ratios were 10.87 (95%CI, 1.14–103.66), 6.83 (95%CI, 1.08–43.08) and 42.67 (95%CI, 3.66–496.85), respectively. The constructed model showed an area under ROC of 0.912 (95%CI,0.825–0.999). The model-defined high-risk group showed poorer overall survival and recurrence-free survival than the low-risk group (both P

Abstract Background The high mutation rate throughout the entire melanoma genome presents a major challenge in stratifying true driver events from the background mutations. Numerous recurrent non-coding alterations, such as those in enhancers, can shape tumor evolution, thereby emphasizing the importance in systematically deciphering enhancer disruptions in melanoma. Results Here, we leveraged 297 melanoma whole-genome sequencing samples to prioritize highly recurrent regions. By performing a genome-scale CRISPR interference (CRISPRi) screen on highly recurrent region-associated enhancers in melanoma cells, we identified 66 significant hits which could have tumor-suppressive roles. These functional enhancers show unique mutational patterns independent of classical significantly mutated genes in melanoma. Target gene analysis for the essential enhancers reveal many known and hidden mechanisms underlying melanoma growth. Utilizing extensive functional validation experiments, we demonstrate that a super enhancer element could modulate melanoma cell proliferation by targeting MEF2A, and another distal enhancer is able to sustain PTEN tumor-suppressive potential via long-range interactions. Conclusions Our study establishes a catalogue of crucial enhancers and their target genes in melanoma growth and progression, and illuminates the identification of novel mechanisms of dysregulation for melanoma driver genes and new therapeutic targeting strategies.

Abstract Schistosoma japonicum infection is an important public health problem and the S. japonicum infection is associated with a variety of diseases, including colorectal cancer. We collected the paraffin samples of CRC patients with or without S. japonicum infection according to standard procedures. Data-Independent Acquisition was used to identify differentially expressed proteins (DEPs), protein–protein interaction (PPI) network construction, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis and machine learning algorithms (least absolute shrinkage and selection operator (LASSO) regression) were used to identify candidate genes for diagnosing CRC with S. japonicum infection. To assess the diagnostic value, the nomogram and receiver operating characteristic (ROC) curve were developed. A total of 115 DEPs were screened, the DEPs that were discovered were mostly related with biological process in generation of precursor metabolites and energy,energy derivation by oxidation of organic compounds, carboxylic acid metabolic process, oxoacid metabolic process, cellular respiration aerobic respiration according to the analyses. Enrichment analysis showed that these compounds might regulate oxidoreductase activity, transporter activity, transmembrane transporter activity, ion transmembrane transporter activity and inorganic molecular entity transmembrane transporter activity. Following the development of PPI network and LASSO, 13 genes (hsd17b4, h2ac4, hla-c, pc, epx, rpia, tor1aip1, mindy1, dpysl5, nucks1, cnot2, ndufa13 and dnm3) were filtered, and 3 candidate hub genes were chosen for nomogram building and diagnostic value evaluation after machine learning. The nomogram and all 3 candidate hub genes (hsd17b4, rpia and cnot2) had high diagnostic values (area under the curve is 0.9556). The results of our study indicate that the combination of hsd17b4, rpia, and cnot2 may become a predictive model for the occurrence of CRC in combination with S. japonicum infection. This study also provides new clues for the mechanism research of S. japonicum infection and CRC.

Without assuming any functional or distributional structure, we select collections of major factors embedded within response-versus-covariate (Re-Co) dynamics via selection criteria [C1: confirmable] and [C2: irrepaceable], which are based on information theoretic measurements. The two criteria are constructed based on the computing paradigm called Categorical Exploratory Data Analysis (CEDA) and linked to Wiener-Granger causality. All the information theoretical measurements, including conditional mutual information and entropy, are evaluated through the contingency table platform, which primarily rests on the categorical nature within all involved features of any data types: quantitative or qualitative. Our selection task identifies one chief collection, together with several secondary collections of major factors of various orders underlying the targeted Re-Co dynamics. Each selected collection is checked with algorithmically computed reliability against the finite sample phenomenon, and so is each members major factor individually. The developments of our selection protocol are illustrated in detail through two experimental examples: a simple one and a complex one. We then apply this protocol on two data sets pertaining to two somewhat related but distinct pitching dynamics of two pitch types: slider and fastball. In particular, we refer to a specific Major League Baseball (MLB) pitcher and we consider data of multiple seasons.