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Objectives: The objective of this study was to investigate the resistance mechanisms of a multidrug-resistant Salmonella Kentucky ST198 FJ-2064 isolated from a patient in China. Methods: The antimicrobial susceptibility of FJ-2064 was determined by the standard disc dilution and broth microdilution methods. The complete genome of FJ-2064 was sequenced using PacBio and Illumina MiSeq platforms. Polymerase chain reaction (PCR) and S1-PFGE were utilized to confirm the mutation sites and the genomic plasmids, respectively. Results: Isolate FJ-2064 belongs to sequence type ST198 and harboured no visible large plasmids, but was concurrent resistant to 22 detected antimicrobial agents including cefotaxime, ciprofloxacin, and azithromycin. The complete genome sequence identified 20 acquired antibiotic resistance genes (ARGs) and five chromosomal mutations in the gyrA and parC genes of the quinolone resistance determining regions (QRDRs) in FJ-2064. In addition, PCR sequencing confirmed that most of the ARGs were clustered on one multidrug-resistant region and a variant of SGI1-K. In particular, the bla-TEM-1 and bla-CTX−M-55, qnrS1, mph(A) genes, which confer resistance to cephalosporins, quinolones, and macrolides respectively, were all located on the multidrug-resistant region. Conclusions: We have demonstrated one multidrug-resistant region and a variant of SGI1-K in a Salmonella Kentucky ST198 that is co-resistant to cefotaxime, ciprofloxacin, and azithromycin.

Abstract Background The role of tumor-draining lymph nodes in the progression of malignant tumors, including stage III colorectal cancer (CRC), is critical. However, the prognostic and predictive value of the number of examined lymph nodes (ELNs) are not fully understood. Methods This population-based study retrospectively analyzed data from 106,843 patients with stage III CRC who underwent surgical treatment and registered in three databases from 2004 to 2021. The Surveillance, Epidemiology, and End Results (SEER) cohort was divided using into training and test cohorts at a ratio of 3:2. We employed restricted cubic spline (RCS) curves to explore nonlinear relationships between overall survival (OS) and ELNs counts and performed Cox regression to evaluate hazard ratios across different ELNs count subtypes. Additional validation cohorts were utilized from the First Affiliated Hospital, Sun Yat-sen University and The Cancer Genome Atlas (TCGA) under the same criteria. Outcomes measured included OS, cancer-specific survival (CSS), and progression-free survival (PFS). Molecular analyses involved differential gene expression using the “limma” package and immune profiling through CIBERSORT. Tissue microarray slides and multiplex immunofluorescence (MIF) were used to assess protein expression and immune cell infiltration. Results Patients with higher ELNs counts (≥ 17) demonstrated significantly better long-term survival outcomes across all cohorts. Enhanced OS, CSS, and PFS were notably evident in the LN-ELN group compared to those with fewer ELNs. Cox regression models underscored the prognostic value of higher ELNs counts across different patient subgroups by age, sex, tumor differentiation, and TNM stages. Subtype analysis based on ELNs count revealed a marked survival benefit in patients treated with adjuvant chemotherapy in the medium and large ELNs counts (≥ 12), whereas those with fewer ELNs showed negligible benefits. RNA sequencing and MIF indicated elevated immune activation in the LN-ELN group, characterized by increased CD3+, CD4+, and CD8 + T cells within the tumor microenvironment. Conclusions The number of ELNs independently predicts survival and the immunological landscape at the tumor site in stage III CRC, underscoring its dual prognostic and predictive value.

Abstract Perovskite oxides and organic–inorganic halide perovskite materials, with numerous fascinating features, have been subjected to extensive studies. Most of the properties of perovskite materials are dependence on their ferroelectricity that denoted by remanent polarization (Pr). Thus, the increase of Pr in perovskite films is mainly an effort in material physics. At present, commonplace improvement schemes, i.e., controlling material crystallinity, and post‐annealing by using a high‐temperature process, are normally used. However, a simpler and temporal strategy for Pr improvement is always unavailable to perovskite material researchers. In this study, an organic coating layer, low‐temperature, and vacuum‐free strategy is proposed to improve the Pr, directly increasing the Pr from 36 to 56 µC cm−2. Further study finds that the increased Pr originates from the suppression of the oxygen defects and Ti defects. This organic coating layer strategy for passivating the defects may open a new way for the preparation of higher‐performance and cost‐effective perovskite products, further improving its prospective for application in the electron devices field.

Abstract To validate the feasibility of a fiber-optic pressure sensor-based pressure measurement device for monitoring intrarenal pressure and to analyze the effects of ureteral acess sheath (UAS) type, surgical location, perfusion flow rate, and measurement location on intrarenal pressure (IRP). The measurement deviations and response times to transient pressure changes were compared between a fiber-optic pressure sensing device and a urodynamic device IRP in an in vitro porcine kidney and in a water tank. Finally, pressure measurements were performed in anesthetized female pigs using fiber-optic pressure sensing device with different UAS, different perfusion flow rates, and different surgical positions at different renal calyces and ureteropelvic junctions (UPJ). According to our operation, the result is fiber optic pressure sensing devices are highly accurate and sensitive. Under the same conditions, IRP varied among different renal calyces and UPJ (P

Abstract The brief history of monitoring nutrient levels in Chinese lake waters limits our understanding of the causes and the long-term trends of their eutrophication and constrains effective lake management. We therefore synthesize nutrient data from lakes in China to reveal the historical changes and project their future trends to 2100 using models. Here we show that the average concentrations of nitrogen and phosphorus in lake sediments have increased by 267% and 202%, respectively since 1850. In the model projections, 2030–2100, the nitrogen concentrations in the studied lakes in China may decrease, for example, by 87% in the southern districts and by 19% in the northern districts. However, the phosphorus concentrations will continue to increase by an average of 25% in the Eastern Plain, Yunnan–Guizhou Plateau, and Xinjiang. Based on this differentiation, we suggest that nitrogen and phosphorus management in Chinese lakes should be carried out at the district level to help develop rational and sustainable environmental management strategies.

The pancreas exerts endocrine and exocrine functions in energy balance. The neural innervation and immune milieu are both crucial in supporting pancreatic homeostasis. The neuronal network connects the pancreas with the central nervous system (CNS) and the enteric nervous system (ENS) and sustains metabolic activities. The nerves in the pancreas are categorized as spinal sensory afferent fibers, vagal sensory afferent nerves, autonomic fibers of both sympathetic and parasympathetic divisions, and fibers from the ENS and intrapancreatic ganglia. They innervate different regions and various cell types, which collectively determine physiological functions. Studies have established that the diverse pathological conditions, including pancreatitis, diabetes, and pancreatic tumor, are attributed to aberrant immune reactions; however, it is largely not clear how the neuronal network may influence the disease conditions. Enlightened by the recent advances illuminating the organ-wide neuronal architecture and the dysfunctions in pancreatic disorders, this review will highlight emerging opportunities to explore the cellular interrelationship, particularly the neuroimmune components in pancreatic health and diseases.

Abstract The extensive application of nuclear technology has increased the potential of uncontrolled radiation exposure to the public. Since skin is the largest organ, radiation‐induced skin injury remains a serious medical concern. Organisms evolutionally develop distinct strategies to protect against environment insults and the related research may bring novel insights into therapeutics development. Here, 26 increased peptides are identified in skin tissues of frogs (Pelophylax nigromaculatus) exposed to electron beams, among which four promoted the wound healing of irradiated skin in rats. Specifically, radiation‐induced frog skin peptide‐2 (RIFSP‐2), from histone proteolysis exerted membrane permeability property, maintained cellular homeostasis, and reduced pyroptosis of irradiated cells with decreased TBK1 phosphorylation. Subsequently, stearyl‐CoA desaturase 1 (SCD1) is identified, a critical enzyme in biogenesis of monounsaturated fatty acids (MUFAs) as a direct target of RIFSP‐2 based on streptavidin‐biotin system. The lipidomic analysis further assured the restrain of MUFAs biogenesis by RIFSP‐2 following radiation. Moreover, the decreased MUFA limited radiation‐induced and STING‐mediated inflammation response. In addition, genetic depletion or pharmacological inhibition of STING counteracted the decreased pyroptosis by RIFSP‐2 and retarded tissue repair process. Altogether, RIFSP‐2 restrains radiation‐induced activation of SCD1‐MUFA‐STING axis. Thus, the stress‐induced amphibian peptides can be a bountiful source of novel radiation mitigators.

Abstract Exploring the nature of human intelligence and behavior is a longstanding pursuit in cognitive neuroscience, driven by the accumulation of knowledge, information, and data across various studies. However, achieving a unified and transparent interpretation of findings presents formidable challenges. In response, an explainable brain computing framework is proposed that employs the never‐ending learning paradigm, integrating evidence combination and fusion computing within a Knowledge‐Information‐Data (KID) architecture. The framework supports continuous brain cognition investigation, utilizing joint knowledge‐driven forward inference and data‐driven reverse inference, bolstered by the pre‐trained language modeling techniques and the human‐in‐the‐loop mechanisms. In particular, it incorporates internal evidence learning through multi‐task functional neuroimaging analyses and external evidence learning via topic modeling of published neuroimaging studies, all of which involve human interactions at different stages. Based on two case studies, the intricate uncertainty surrounding brain localization in human reasoning is revealed. The present study also highlights the potential of systematization to advance explainable brain computing, offering a finer‐grained understanding of brain activity patterns related to human intelligence.

Abstract Background Gastric cancer (GC) is a common malignancy with its morbidity increasing worldwide. Hence, it is imperative to develop effective treatments. Studies have shown that metformin has potential antitumor effects. The objective of this study was to probe the antitumor mechanism of metformin in GC. Methods The expression of ADAMTS12 in GC tissues and its enrichment pathways were analyzed by bioinformatics methods. ADAMTS12 expression in GC cells was assessed by qRT-PCR. Cell viability and proliferation were analyzed by CCK-8 and colony formation assays, respectively. Extracellular acidification rate (ECAR) and oxygen consumption rate (OCR) of GC cells in different treatment groups were analyzed by Seahorse XP 96, and glycolysis metabolites were detected by corresponding kits. Western blot was employed to analyze the level of glycolysis pathway related protein HK-2, and cell functional assays were conducted to verify the functions of metformin on GC cells. A xenograft model was constructed to validate the inhibitory role of metformin in GC. Results ADAMTS12 expression was elevated in GC tissues/cells and concentrated in glycolysis pathway. Cell functional assays found that ADAMTS12 promoted the proliferation and glycolysis of GC cells. Rescue experiments showed that metformin could reduce the promoting effect of ADAMTS12 overexpression on the proliferation and glycolysis of GC cells. In vivo studies confirmed that metformin suppressed the proliferation and glycolysis process via ADAMTS12 in GC cells. Conclusion Metformin can repress the proliferation and glycolysis of GC cells via ADAMTS12. The results suggest the potential of ADAMTS12 being a target for the metformin therapy of GC.

Abstract Lateral interaction in the biological brain is a key mechanism that underlies higher cognitive functions. Linear self‐organising map (SOM) introduces lateral interaction in a general form in which signals of any modality can be used. Some approaches directly incorporate SOM learning rules into neural networks, but incur complex operations and poor extendibility. The efficient way to implement lateral interaction in deep neural networks is not well established. The use of Laplacian Matrix‐based Smoothing (LS) regularisation is proposed for implementing lateral interaction in a concise form. The authors’ derivation and experiments show that lateral interaction implemented by SOM model is a special case of LS‐regulated k‐means, and they both show the topology‐preserving capability. The authors also verify that LS‐regularisation can be used in conjunction with the end‐to‐end training paradigm in deep auto‐encoders. Additionally, the benefits of LS‐regularisation in relaxing the requirement of parameter initialisation in various models and improving the classification performance of prototype classifiers are evaluated. Furthermore, the topologically ordered structure introduced by LS‐regularisation in feature extractor can improve the generalisation performance on classification tasks. Overall, LS‐regularisation is an effective and efficient way to implement lateral interaction and can be easily extended to different models.

Abstract The m6a demethyltransferase ALKBH5 dynamically modulates gene expression and intracellular metabolic molecules by modifying RNA m6a in cancer cells. However, ALKBH5’s function in gastric cancer (GC) has remained controversial. This study demonstrates that ALKBH5 is highly expressed in GC. Silencing ALKBH5 hampers proliferation, and metastatic potential, and induces cell death in GC cells. Through a comprehensive analysis of the transcriptome and m6A sequencing, alterations in certain ALKBH5 target genes, including CHAC1, were identified. ALKBH5’s demethylation effect regulates CHAC1 RNA stability, leading to reduced CHAC1 expression. Moreover, CHAC1 modulates intracellular ROS levels, influencing the chemotherapy sensitivity of gastric cancer. In summary, our study unveils the pivotal role of the ALKBH5-CHAC1-ROS axis and highlights the significance of m6A methylation in gastric cancer.

Ionic polymer metal composite (IPMC) is regarded as the mainstream application material for achieving flexible driving technology in various engineering fields. In this article, aiming at the non-independence of the current IPMC electric driving method, an IPMC optical-controlled flexible driving method based on the photoinduced effects of lanthanum-modified lead zirconate titanate (PLZT) ceramic is proposed. To this end, a mathematical model for IPMC optical controlled flexible driving is built on the basis of the photovoltaic characteristic of PLZT ceramic, and the driving performance is experimentally analyzed through different lengths of IPMC under the excitation of different direct currents and light intensities. From the analysis and experimental results, when PLZT ceramic is irradiated by different light intensities, the output deformation of IPMC increases with increases in light intensity, and finally reaches a stable state. Moreover, the actuation curves obtained by light excitation and direct current excitation are consistent, and the motion coefficient reflects the driving performance more accurately. In addition, using light energy as an excitation source to drive IPMC not only provides new ideas for its development in the flexible driving field, but also provides a theoretical basis for its practical application.

Hypertension is a major risk factor for many serious diseases. With the aging population and lifestyle changes, the incidence of hypertension continues to rise, imposing a significant medical cost burden on patients and severely affecting their quality of life. Early intervention can greatly reduce the prevalence of hypertension. Research on hypertension early warning models based on electronic health records (EHRs) is an important and effective method for achieving early hypertension warning. However, limited by the scarcity and imbalance of multivisit records, and the nonstationary characteristics of hypertension features, it is difficult to predict the probability of hypertension prevalence in a patient effectively. Therefore, this study proposes an online hypertension monitoring model (HRP-OG) based on reinforcement learning and generative feature replay. It transforms the hypertension prediction problem into a sequential decision problem, achieving risk prediction of hypertension for patients using multivisit records. Sensors embedded in medical devices and wearables continuously capture real-time physiological data such as blood pressure, heart rate, and activity levels, which are integrated into the EHR. The fit between the samples generated by the generator and the real visit data is evaluated using maximum likelihood estimation, which can reduce the adversarial discrepancy between the feature space of hypertension and incoming incremental data, and the model is updated online based on real-time data using generative feature replay. The incorporation of sensor data ensures that the model adapts dynamically to changes in the condition of patients, facilitating timely interventions. In this study, the publicly available MIMIC-III data are used for validation, and the experimental results demonstrate that compared to existing advanced methods, HRP-OG can effectively improve the accuracy of hypertension risk prediction for few-shot multivisit record in nonstationary environments.

Abstract Passivating contactsin heterojunction (HJ) solar cells have shown great potential in reducing recombination losses, and thereby achieving high power conversion efficiencies in photovoltaic devices. In this direction, carbon nanomaterials have emerged as a promising option for carbon/silicon (C/Si) HJsolar cells due to their tunable band structure, wide spectral absorption, high carrier mobility, and properties such as multiple exciton generation. However, the current limitations in efficiency and active area have hindered the industrialization of these devices. In this review, they examine the progress made in overcoming these constraints and discuss the prospect of achieving high power conversion efficiency (PCE) C/Si HJ devices. A C/Si HJ solar cell is also designed by introducing an innovative interface passivation strategy to further boost the PCE and accelerate the large area preparationof C/Si devices. The physical principle, device design scheme, and performanceoptimization approaches of this passivated C/Si HJ cells are discussed. Additionally, they outline potential future pathways and directions for C/Si HJ devices, including a reduction in their cost to manufacture and their incorporation intotandem solar cells. As such, this review aims to facilitate a deeperunderstanding of C/Si HJ solar cells and provide guidance for their further development.

Currently, lithium-ion batteries have an increasingly urgent need for high-performance electrolytes, and additives are highly valued for their convenience and cost-effectiveness features. In this work, the feasibilities of fullerenes and fluorinated fullerenes as typical bis(fluorosulfonyl)imide/1,2-dimethoxymethane (LiFSI/DME) electrolyte additives are rationally evaluated based on density functional theory calculations and molecular dynamic simulations. Interestingly, electronic structures of C60, C60F2, C60F4, C60F6, 1-C60F8, and 2-C60F8 are found to be compatible with the properties required as additives. It is noted that that different numbers and positions of F atoms lead to changes in the deformation and electronic properties of fullerenes. The F atoms not only show strong covalent interactions with C cages, but also affect the C-C covalent interaction in C cages. In addition, molecular dynamic simulations unravel that the addition of trace amounts of C60F4, C60F6, and 2-C60F8 can effectively enhance the Li+ mobility in LiFSI/DME electrolytes. The results expand the range of applications for fullerenes and their derivatives and shed light on the research into novel additives for high-performance electrolytes.

Oppositional defiant symptoms are some of the most common developmental symptoms in children and adolescents with and without oppositional defiant disorder. Research has addressed the close association of the parent–child relationship (PCR) with oppositional defiant symptoms. However, it is necessary to further investigate the underlying mechanism for forming targeted intervention strategies. By using a machine learning-based causal forest (CF) model, we investigated the heterogeneous causal effects of the PCR on oppositional defiant symptoms in children in Chinese elementary schools. Based on the PCR improvement in two consecutive years, 423 children were divided into improved and control groups. The assessment of oppositional defiant symptoms (AODS) in the second year was set as the dependent variable. Additionally, several factors based on the multilevel family model and the baseline AODS in the first year were included as covariates. Consistent with expectations, the CF model showed a significant causal effect between the PCR and oppositional defiant symptoms in the samples. Moreover, the causality exhibited heterogeneity. The causal effect was greater in those children with higher baseline AODS, a worse family atmosphere, and lower emotion regulation abilities in themselves or their parents. Conversely, the parenting style played a positive role in causality. These findings enhance our understanding of how the PCR contributes to the development of oppositional defiant symptoms conditioned by factors from a multilevel family system. The heterogeneous causality in the observation data, established using the machine learning approach, could be helpful in forming personalized family-oriented intervention strategies for children with oppositional defiant symptoms.

Liquid fermentation is an efficient culture for obtaining polysaccharides from edible mushrooms. In this study, the polysaccharide content and biomass were examined by introducing microorganisms into the Wolfiporia cocos fermentation system. Three edible mushroom co-fermentation systems were established, among which the Wolfiporia cocos-Ganoderma lucidum co-fermentation system significantly increased the mycelial biomass of the system by 57.71% compared to Wolfiporia cocos alone and 91.22% compared to Ganoderma lucidum alone, and the intracellular polysaccharide content was significantly increased. Physiological activities of polysaccharides showed that mycelial polysaccharides in the Wolfiporia cocos-Ganoderma lucidum system had stronger anti-tumor cell value-adding and anti-tumor cell migration activities compared with Wolfiporia cocos and Ganoderma lucidum fermentation alone. The transcriptomic study of Wolfiporia cocos mycelium induced by exogenous substances suggested that the exogenous substances could enhance the intracellular polysaccharide content of Wolfiporia cocos through the upregulation of the expression of α-glycosyltransferase encoded by ALG10 and the downregulation of α-glycosidases encoded by MAN1B in the glycolytic metabolism of Wolfiporia cocos. This study provides a new direction for the transformation of polysaccharides from Wolfiporia cocos and Ganoderma lucidum into functional foods and new product development, and provides an experimental basis.

The number of failures serves as a critical indicator that dynamically impacts the reliability of self-announcing failure products, making it highly practical to incorporate the failure count into reliability management throughout the entire product life cycle. This paper investigates comprehensive methodologies for effectively managing the reliability of self-announcing failure products throughout both the warranty and post-warranty stages, taking into account factors such as the failure count, mission cycles, and limited time duration. Three renewable warranty strategies are introduced alongside proposed models for post-warranty replacements. By analyzing variables like the failure number, mission cycles, and time constraints, these proposed warranties provide practical frameworks for efficient reliability management during the warranty stage. Additionally, the introduced warranties utilize cost and time metrics to extract valuable insights that inform decision making and enable effective reliability management during the warranty stage. Moreover, this study establishes cost and time metrics for key post-warranty replacements, facilitating the development of individual cost rates and model applications in other post-warranty scenarios. Analyses of the renewable free-repair–replacement warranties demonstrate that establishing an appropriate number of failures as the replacement threshold can effectively reduce warranty-servicing costs and extend the coverage duration.

Abstract Background Fumarate hydratase–deficient renal cell carcinoma (FH-RCC) is a rare highly aggressive subtype of kidney cancer for which the distinct genomic, transcriptomic, and evolutionary relationships between metastatic and primary lesions are still unclear. Methods In this study, whole-exome, RNA-seq, and DNA methylation sequencing were performed on primary-metastatic paired specimens from 19 FH-RCC cases, including 23 primary and 35 matched metastatic lesions. Phylogenetic and clonal evolutionary analyses were used to investigate the evolutionary characteristics of FH-RCC. Transcriptomic analyses, immunohistochemistry, and multiple immunofluorescence experiments were performed to identify the tumor microenvironmental features of metastatic lesions. Results Paired primary and metastatic lesions generally showed similar characteristics of tumor mutation burden, tumor neoantigen burden, microsatellite instability score, CNV burden, and genome instability index. Notably, we identified an FH-mutated founding MRCA (the most recent common ancestor) clone that dominated the early evolutionary trajectories in FH-RCC. Although both primary and metastatic lesions manifested high immunogenicity, metastatic lesions exhibited higher enrichment of T effector cells and immune-related chemokines, together with upregulation of PD-L1, TIGIT, and BTLA. In addition, we found that concurrent NF2 mutation may be associated with bone metastasis and upregulation of cell cycle signature in metastatic lesions. Furthermore, although in FH-RCC metastatic lesions in general shared similar CpG island methylator phenotype with primary lesions, we found metastatic lesions displaying hypomethylated chemokine and immune checkpoints related genomic loci. Conclusions Overall, our study demonstrated the genomic, epigenomic, and transcriptomic features of metastatic lesions in FH-RCC and revealed their early evolutionary trajectory. These results provided multi-omics evidence portraying the progression of FH-RCC.

Purpose. To investigate the long-term changes in visual quality and pupil size after small incision lenticule extraction (SMILE) for eyes without preoperative cylinder refraction. Methods. Thirty-three myopic eyes (33 patients) without preoperative cylinder refraction were corrected using SMILE. Refractive outcomes, corneal curvature, aberrations, contrast sensitivity (CS), and pupil diameter were evaluated preoperatively, and 30 months postoperatively. Results. The 30-month postoperative uncorrected and corrected distance visual acuity (UDVA and CDVA, LogMAR) were −0.10 ± 0.09 and −0.14 ± 0.06, respectively, whereas the preoperative CDVA (LogMAR) was −0.07 ± 0.05. Cylinder refraction of −0.11 ± 0.21 D (ranging from −0.50 to 0.00) was observed at 30 months postoperatively, increasing from the preoperative cylinder refraction of 0.00 ± 0.00 D (P=0.004). Moreover, the centroid coordinates x, y of corneal anterior astigmatic vectors were −0.19 ± 0.22, 0.81 ± 0.33 at 30 months postoperatively, and 0.02 ± 0.28, 0.76 ± 0.51 preoperatively (Px

Reynoutria japonica Houtt. is an important medical plant with a long history of thousands of years in China, however, its mitochondrial genome (mitogenome) has not been reported yet. In this work, we reported and analyzed the R. japonica mitogenome. The main results include: The R. japonica mitogenome was 302,229 bp in length and encoded 48 genes, including 27 protein-coding genes (PCGs), 3 rRNA genes, and 18 tRNA genes. Repeat sequence analysis revealed that there were 54 repeat sequences ranging from 193 bp to 1,983 bp in the R. japonica mitogenome. Relative synonymous codon usage (RSCU) analysis showed that leucine (900, 11.01%) and serine (732, 8.96%) were the two most abundant amino acids, and the codons with RSCU values showed the preference of A or T ending when greater than 1. The RNA editing sites of PCGs in the R. japonica mitogenome were characterized, and 299 RNA editing sites were found. Extensive sequences transfer between mitochondrion and chloroplast were found in R. japonica, where 11 complete plastid-derived tRNA genes stayed intact in the R. japonica mitogenome. Three genes (ccmFC, cox1, and nad1) were seen to play essential roles in the evolution through selection pressure analysis. The phylogenetic analysis showed that Fallopia multiflora was the closest species with R. japonica, in consistency with the results of chloroplast genome. Overall, the current work presents the first mitogenome of R. japonica and could contribute to the phylogenetic analysis of the family Polygonaceae.

Abstract PBX1 is a transcription factor that regulates a variety of genes, involved in intracellular lipid metabolism, cell proliferation, and other pathways. The promoting and inhibiting function of PBX1 in various cancer types was extensively discussed, however, there have been no studies on PBX1 proteins in colorectal cancer (CRC). This study aimed to reveal the anti-tumor function of PBX1 in CRC and the underlying molecular mechanism. Bioinformatics analysis revealed that PBX1 is downregulated in CRC, indicating that is a potential antioncogene in CRC. Overexpression of PBX1 suppresses tumor growth and metastasis in vitro and in vivo. Mechanistically, we found that PBX1 acted as a transcription factor that suppressed DCDC2 expression and inhibited spindle function. Moreover, the PBX1-DCDC2 axis controlled the Wnt pathway in CRC cells. Overexpression of DCDC2 restored CRC proliferation, metastasis abilities and Wnt pathway. In conclusion, this study suggests that PBX1 acts as a transcription factor to suppress DCDC2 expression and inhibit cell proliferation and metastasis by disrupting spindle function and the Wnt pathway in CRC.

Organic solar cells (OSCs) have attracted attention due to their lightweight nature, flexibility, and facile preparation using solution-based methods. Their efficiency has been further elevated by the rapid advancement of nonfullerene materials, achieving individual cell efficiencies that surpass 19%. Hence, the stability of nonfullerene solar cell production must be scrutinized. The stability of the cathode interface layer significantly impacts the overall stability of OSC devices. PFN-Br, a commonly employed cathode interface material, is susceptible to degradation due to its sensitivity to environmental humidity, consequently compromising the device stability. In this study, we introduce fluorescent dye molecules, rhodamine 101, as cathode interface layers in OSCs to establish device stability and assess their universality. A comparative investigation of rhodamine 101 and PFN-Br devices demonstrates the former’s distinct advantages in terms of thermal stability, photostability, and storage stability even without encapsulation, particularly in an inert environment. By employing the Kelvin probe, we compare the work function of different cathode interface films and reveal that the work function of the rhodamine 101 interface material remains relatively unaffected by environmental factors. As a consequence, the device performance stability is significantly enhanced. The application of such fluorescent dye molecules extends the scope of cathode interface layers, amplifies device stability, and propels industrialization.

Arid central Asia (ACA) is dominated by mid-latitude westerlies and characterized by a climate optimum (a relatively humid climate that has supported the development of human culture) in clear contrast with the climate of monsoonal Asia during the Holocene. Significantly, whether the onset of the Holocene Climate Optimum (HCO) had an impact on cultural exchanges along the ancient Silk Road remains unknown. In this study, we compared the onset of the HCO in different parts of the vast ACA region by referring to a variety of previously established paleo-moisture/precipitation records. Intriguingly, we found significant differences in the onset of the HCO between the western and eastern parts of ACA. The onset of the HCO in the western part of ACA (i.e., to the west of the Tianshan Mountains) mainly occurred at ~8 ka BP (1 ka = 1000 cal yr BP). In contrast, the onset of the HCO occurred at ~6 ka in northern Xinjiang and even as late as ~5 ka in southern Xinjiang; this is a delay of 2–3 thousand years compared with the western part of ACA. These results likely indicate that the onset of the HCO occurred in a time-transgressive manner in ACA, namely, ‘early in the west but late in the east’. On the other hand, we found that the onset of the HCO in the western part of ACA may have resulted in the inception of wheat planting and the development of agricultural civilization and that the onset of the HCO in northern Xinjiang may have prompted the southward migration of Afanasievo culture after ~5 ka. Additionally, the initiation of the HCO in southern Xinjiang could provide an environmental basis for the spread and planting of wheat and millet in this area after ~4.5 ka. We speculate that the spatial differences in the onset of the HCO in ACA are mainly related to temporal changes in the intensity and position of the mid-latitude westerly jet. Although the increase in insolation and reduction in the global ice volume would have led to an increase in the water vapor feeding the western part of ACA around 8 ka, the climate in the eastern part of ACA (namely, the Xinjiang region) could have only become humid after 6 ka when the westerlies were intensified and became positioned in the south. Moreover, the delayed HCO in southern Xinjiang probably benefited from the stronger westerly winds that appeared around 5 ka, which could have overcome the influence of the tall topography of the Tianshan Mountains. Therefore, in addition to external forcing (i.e., insolation), the ocean–atmospheric teleconnection, the regional topography, and their connection to the climate system are important in determining the spatial differences in the time-transgressive onset of the HCO in ACA. Our findings contribute to understanding the spatio-temporal characteristics of the hydroclimate in regions with complex eco-environmental systems and a diverse history of human activity.

Objective: Our study aims to assess the effectiveness and safety profile of Disitamab Vedotin (DV, RC48-ADC), an innovative humanized anti-HER2 antibody conjugated with tubulin-disrupting antimitotic drug monomethyl auristatin E (MMAE) via a cleavable peptide linker. This treatment combined immune checkpoint inhibitors as part of the bladder sparing approach for selected patients suffering from locally and locally advanced bladder urothelial carcinoma.Patients and methods: We conducted a two-center, real-world study involving locally advanced urothelial carcinoma (UC) patients. Patients were classified based on HER2 expression (IHC 3+/2+/1+) or lack of HER2 expression (IHC 0). The primary endpoint was the objective response rate (ORR), assessed by the investigator following the criteria of RECIST V1.1. Secondary endpoints encompassed the pathological complete response rate (pCR), pathological partial response rate (pPR), and pathological stable disease (pSD), along with recurrence-free survival (RFS), the pathological downstaging rate, and the safety profile of the treatment.Results: In this study, nine patients were enrolled, with a median follow-up duration of 12.0 months. The overall confirmed ORR was 88.9%, Five patients achieved a complete response (CR), and three patients achieved a partial response (PR). The radiological complete response (rCR) aligned perfectly with pCR. The median radiological progression-free survival (rPFS) spanned 12.0 months (range from 8.0 to 17.0 months). One patient diagnosed with disease progression (PD) underwent a radical cystectomy. The pathological stage evolved from T2N0M0 to T3aN2M0, followed by adjuvant chemotherapy with a gemcitabine-cisplatin (GC) combination radiotherapy. At the 9-month follow-up, neither recurrence nor metastasis was observed. The rate and intensity of complications were manageable among these patients, with no evidence of grade 4 and 5 adverse events.Conclusion: The combination of DV and PD-1 demonstrated considerable activity in the objective response rate (ORR) in patients with HER2 IHC 0/1+/2+/3+ muscle-invasive bladder cancer (MIBC), along with the longest reported median radiological progression-free survival (rPFS) to date. With an extended duration of treatment, the safety profile of DV plus PD-1 was also confirmed to be manageable.

Carbon/silicon heterojunctions provide a new perspective for silicon solar cells and in particular those made from carbon nanotubes (CNTs) have already achieved industrial‐level power conversion efficiency and device size when using organic passivation and a back‐junction design. However, the current state of the art device geometry for silicon photovoltaics is the interdigitated back contact (IBC) cell and this has yet to be demonstrated for CNT/Si solar cells due to the complexity of fabricating the required patterns. Herein, IBC‐CNT solar cells are demonstrated via the simple spin coating of a conductive hole‐selective passivating film and the evaporation of buried silicon oxide/magnesium electron‐selective contacts for both polarities. The CNT coverage area fraction (fCNT) and the gap between the two polarities are optimized to minimize electrical shading loss and ensure high photocarrier collection. Large‐area (4.76 cm2) highly efficient (17.53%) IBC‐CNT solar cells with a Voc of 651 mV and Jsc of 40.56 mA cm−2 are demonstrated and are prepared with one alignment step for the CNT/Si contact, and photolithographic‐free and room‐temperature processes. These performance parameters are among the best for solution‐processed dopant‐free IBC schemes and indicate the feasibility of using low‐dimensional carbon materials in IBC solar cells.

In the process of rock excavation, cyclic loading may occur before or after the peak value. In order to obtain the fracture damage evolution characteristics of rock under the pre-peak and the post-peak cyclic loading condition, the fracture tests of three-point bending granite beams were conducted by using the digital image correlation method and the acoustic emission technology. Based on the secant modulus, the acoustic emission energy and effective crack length, the rock fracture damage indexes DE, DAE, and DL were constructed respectively, and the rock fracture damage process was quantitatively analyzed. The results show that the damage index of the rock sample has an obvious rate effect. At the same number of cycles, as the loading rate increases, the damage index decreases. For the pre-peak cyclic loading condition, the fracture process of rock from elastic stage to elastic-plastic stage can be well reflected by DE. Under the condition of post-peak cyclic loading, DL can better represent the fracture damage process of rock from step up to continuous failure.

Abstract Background Medication recommendation based on electronic medical record (EMR) is a research hot spot in smart healthcare. For developing computational medication recommendation methods based on EMR, an important challenge is the lack of a large number of longitudinal EMR data with time correlation. Faced with this challenge, this paper proposes a new EMR-based medication recommendation model called MR-KPA, which combines knowledge-enhanced pre-training with the deep adversarial network to improve medication recommendation from both feature representation and the fine-tuning process. Firstly, a knowledge-enhanced pre-training visit model is proposed to realize domain knowledge-based external feature fusion and pre-training-based internal feature mining for improving the feature representation. Secondly, a medication recommendation model based on the deep adversarial network is developed to optimize the fine-tuning process of pre-training visit model and alleviate over-fitting of model caused by the task gap between pre-training and recommendation. Result The experimental results on EMRs from medical and health institutions in Hainan Province, China show that the proposed MR-KPA model can effectively improve the accuracy of medication recommendation on small-scale longitudinal EMR data compared with existing representative methods. Conclusion The advantages of the proposed MR-KPA are mainly attributed to knowledge enhancement based on ontology embedding, the pre-training visit model and adversarial training. Each of these three optimizations is very effective for improving the capability of medication recommendation on small-scale longitudinal EMR data, and the pre-training visit model has the most significant improvement effect. These three optimizations are also complementary, and their integration makes the proposed MR-KPA model achieve the best recommendation effect.

Abstract Background Accurately predicting drug-target binding affinity (DTA) in silico plays an important role in drug discovery. Most of the computational methods developed for predicting DTA use machine learning models, especially deep neural networks, and depend on large-scale labelled data. However, it is difficult to learn enough feature representation from tens of millions of compounds and hundreds of thousands of proteins only based on relatively limited labelled drug-target data. There are a large number of unknown drugs, which never appear in the labelled drug-target data. This is a kind of out-of-distribution problems in bio-medicine. Some recent studies adopted self-supervised pre-training tasks to learn structural information of amino acid sequences for enhancing the feature representation of proteins. However, the task gap between pre-training and DTA prediction brings the catastrophic forgetting problem, which hinders the full application of feature representation in DTA prediction and seriously affects the generalization capability of models for unknown drug discovery. Results To address these problems, we propose the GeneralizedDTA, which is a new DTA prediction model oriented to unknown drug discovery, by combining pre-training and multi-task learning. We introduce self-supervised protein and drug pre-training tasks to learn richer structural information from amino acid sequences of proteins and molecular graphs of drug compounds, in order to alleviate the problem of high variance caused by encoding based on deep neural networks and accelerate the convergence of prediction model on small-scale labelled data. We also develop a multi-task learning framework with a dual adaptation mechanism to narrow the task gap between pre-training and prediction for preventing overfitting and improving the generalization capability of DTA prediction model on unknown drug discovery. To validate the effectiveness of our model, we construct an unknown drug data set to simulate the scenario of unknown drug discovery. Compared with existing DTA prediction models, the experimental results show that our model has the higher generalization capability in the DTA prediction of unknown drugs. Conclusions The advantages of our model are mainly attributed to two kinds of pre-training tasks and the multi-task learning framework, which can learn richer structural information of proteins and drugs from large-scale unlabeled data, and then effectively integrate it into the downstream prediction task for obtaining a high-quality DTA prediction in unknown drug discovery.

Abstract Background In non-small-cell lung cancer (NSCLC), there are many factors that affect prognosis, and the lymph node ratio (LNR) may play a significant role. Our study aimed to confirm the value of the LNR in the prognosis of patients with stage II NSCLC. Methods Patient data were obtained from the Surveillance, Epidemiology and End Results (SEER) database. The classification for the LNR was best determined using the X-tile method. The correlation between the LNR and overall survival (OS) was validated after the Kaplan–Meier analysis was performed. To determine the correlation between the LNR and survival, stratification and the Cox regression analysis were used. Results In our study, 14,183 stage II NSCLC patients were included. Among them, 8303 patients had N1 disease. According to the X-tile analysis, the optimal critical points for the LNR in N1 patients with NSCLC was 0.21 and 0.38. We categorized the cohorts as low (LNR-L ≤ 0.21; n = 5158, 62.1%), medium (0.21 0.38; n = 1409, 17.0%). According to the Kaplan–Meier analysis, the patients with a high LNR were considerably worse than those with a medium or low LNR (P

Objective: To identify circadian clock (CC)-related key genes with clinical significance, providing potential biomarkers and novel insights into the CC of ovarian cancer (OC).Methods: Based on the RNA-seq profiles of OC patients in The Cancer Genome Atlas (TCGA), we explored the dysregulation and prognostic power of 12 reported CC-related genes (CCGs), which were used to generate a circadian clock index (CCI). Weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were used to identify potential hub genes. Downstream analyses including differential and survival validations were comprehensively investigated.Results: Most CCGs are abnormally expressed and significantly associated with the overall survival (OS) of OC. OC patients with a high CCI had lower OS rates. While CCI was positively related to core CCGs such as ARNTL, it also showed significant associations with immune biomarkers including CD8+ T cell infiltration, the expression of PDL1 and CTLA4, and the expression of interleukins (IL-16, NLRP3, IL-1β, and IL-33) and steroid hormones-related genes. WGCNA screened the green gene module to be mostly correlated with CCI and CCI group, which was utilized to construct a PPI network to pick out 15 hub genes (RNF169, EDC4, CHCHD1, MRPL51, UQCC2, USP34, POM121, RPL37, SNRPC, LAMTOR5, MRPL52, LAMTOR4, NDUFB1, NDUFC1, POLR3K) related to CC. Most of them can exert prognostic values for OS of OC, and all of them were significantly associated with immune cell infiltration. Additionally, upstream regulators including transcription factors and miRNAs of key genes were predicted.Conclusion: Collectively, 15 crucial CC genes showing indicative values for prognosis and immune microenvironment of OC were comprehensively identified. These findings provided insight into the further exploration of the molecular mechanisms of OC.

Coexisting multi-pollutants like sulfonamides (SAs) and chlorophenols (CPs) in the ecological environment pose a potential risk to living organisms. The development of a strategy for the effective removal of multiple pollutants has become an urgent need. Herein, we systematically investigated the potential of immobilized bacterial laccase to remove chlorophenols (CPs), sulfonamides (SAs), and their mixtures. Laccase from Bacillus pumilus ZB1 was efficiently immobilized on chitin and its thermal stability, pH stability, and affinity to substrates were improved. Reusability assessment showed the immobilized laccase retained 75.5% of its initial activity after five cycles. The removal efficiency of CPs and SAs by immobilized laccase was significantly improved compared with that of free laccase. In particular, the removal of 2,4-dichlorophenol and 2,4,6-trichlorophenol reached 96.9% and 89.3% respectively within 8 h. The immobilized laccase could remove 63.70% of 2,4-dichlorophenol after four cycles. The degradation pathways of 2,4-dichlorophenol and sulfamethazine were proposed via LC/MS analysis. When the co-pollutants containing 2,4,6-trichlorophenol and sulfamethoxazole, immobilized laccase showed 100% removal of 2,4,6-trichlorophenol and 38.71% removal of sulfamethoxazole simultaneously. Cytotoxicity and phytotoxicity tests indicated that immobilized laccase can alleviate the toxicity of co-pollutants. The results demonstrate that chitin-based laccase immobilization can be an effective strategy for the removal of SAs, CPs, and their co-pollutants.