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Abstract Background Positive solitude, taken as a meaningful activity, contributes to the improvement of health, well-being, and quality of life of older adults. The purpose of this study was to examine the reliability and validity of the Positive Solitude Scale (PS) among Chinese older to provide a reference for related research. Methods A convenience sample of 608 older people from 10 provinces in China was used to conduct the survey. Results The Chinese version of the PS consisted of 9 items with a unidimensional structure, which could explain 60.91% of the variance. The factor loadings of each item ranged from 0.67 to 0.82, and the communality ranged from 0.44 to 0.68. The confirmatory factor analysis showed good model fit (χ2/df = 2.771, RMSEA = 0.076, CFI = 0.972, IFI = 0.972, TLI = 0.959, PNFI = 0.665, PCFI = 0.675). It was found from the criterion-related validity test that PS scores were significantly and positively correlated with Satisfaction With Life Scale (SWLS), Autonomy, Competence, and Relatedness scores (r = 0.45 to 0.44); PS scores were significantly and negatively correlated with Short-Form UCLA Loneliness Scale (ULS-6), Kessler Psychological Distress Scale (K10), Ego Depletion Scale (EDS), and Acceptance and Action Questionnaire-2nd Edition (AAQ-II) (r = -0.27 to -0.36). The Cronbach’s α coefficient value for the scale was 0.917; the split-half reliability coefficient value was 0.928. In addition, the PS showed cross-gender consistency. Conclusions The PS presented favorable psychometric characteristics in older people, which can be used as a valid tool for assessing older people’s positive solitude.

Abstract Metastasis remains a pivotal characteristic of cancer and is the primary contributor to cancer-associated mortality. Despite its significance, the mechanisms governing metastasis are not fully elucidated. Contemporary findings in the domain of cancer biology have shed light on the molecular aspects of this intricate process. Tumor cells undergoing invasion engage with other cellular entities and proteins en route to their destination. Insights into these engagements have enhanced our comprehension of the principles directing the movement and adaptability of metastatic cells. The tumor microenvironment plays a pivotal role in facilitating the invasion and proliferation of cancer cells by enabling tumor cells to navigate through stromal barriers. Such attributes are influenced by genetic and epigenetic changes occurring in the tumor cells and their surrounding milieu. A profound understanding of the metastatic process’s biological mechanisms is indispensable for devising efficacious therapeutic strategies. This review delves into recent developments concerning metastasis-associated genes, important signaling pathways, tumor microenvironment, metabolic processes, peripheral immunity, and mechanical forces and cancer metastasis. In addition, we combine recent advances with a particular emphasis on the prospect of developing effective interventions including the most popular cancer immunotherapies and nanotechnology to combat metastasis. We have also identified the limitations of current research on tumor metastasis, encompassing drug resistance, restricted animal models, inadequate biomarkers and early detection methods, as well as heterogeneity among others. It is anticipated that this comprehensive review will significantly contribute to the advancement of cancer metastasis research.

Abstract The Huang-Huai-Hai region accounts for 80% of China’s wheat production, leading to severe groundwater depletion and substantial environmental impacts. Here we present an optimization framework for wheat redistribution to reduce both water requirements and environmental impacts without compromising production. Our results show that environmental footprints can be reduced—blue water by 16%, grey water by 21%, and greenhouse gas emissions by 18%—while enhancing resource use efficiency, with irrigation water productivity improving by 21% and nitrogen use efficiency by 11%. Maintaining current production levels is achievable with these adjustments. Furthermore, allowing a 17–18% decrease in wheat production could result in a groundwater depth increase of 9.03–9.38 m by 2030, ensuring sustainable groundwater use. In regions experiencing groundwater depletion, blue water, grey water and greenhouse gas emissions could decrease by over one third. Our findings offer an alternative strategy for promoting sustainable agriculture in regions facing groundwater depletion worldwide.

Abstract Liver sinusoidal endothelial cells (LSECs) are highly specialized endothelial cells that represent the interface between blood cells on one side and hepatocytes on the other side. LSECs not only form a barrier within the hepatic sinus, but also play important physiological functions such as regulating hepatic vascular pressure, anti-inflammatory and anti-fibrotic. Pathologically, pathogenic factors can induce LSECs capillarization, that is, loss of fenestra and dysfunction, which are conducive to early steatosis, lay the foundation for the progression of metabolic dysfunction-associated fatty liver disease (MAFLD), and accelerate metabolic dysfunction-associated steatohepatitis (MASH) and liver fibrosis. The unique localization, phenotype, and function of LSECs make them potential candidates for reducing liver injury, inflammation, and preventing or reversing fibrosis in the future.

Abstract Background Tour guides’ identification and internalization of occupational stigma may exacerbate their career development, perceived professional reputation and status, and mental health. The current study aimed to develop and verify the Tour guides Internalized Occupational Stigma Scale (TIOSS) to provide an effective tool for relevant quantitative research. Methods The study developed an initial questionnaire through literature analysis, expert review, and semi-structured surveys. We conducted item analyses and exploratory factor analyses among 326 tour guides, and confirmatory factor analysis and reliability and validity tests among 315 tour guides. Results The TIOSS consists of 21 items and is formed in three dimensions referring to Stigma Perception (SP), Status Loss (SL), and Career Denial (CD). The correlation coefficient values of the TIOSS total scale and dimension scores with the criterion instruments ranged from 0.17 to 0.68. In addition, the Cronbach’s α coefficients for the TIOSS and its dimensions ranged from 0.837 to 0.928, and the split-half reliability coefficients ranged from 0.843 to 0.916. The study also revealed that the TIOSS was consistent across genders. Conclusion The TIOSS performed favorable reliability and validity to be a valid instrument to assess tour guides' internalized occupational stigma.

Introduction Lung-protective ventilation strategies (LPVS) for one-lung ventilation (OLV) in paediatric patients pose greater challenges than in adults. Optimising LPVS for paediatric OLV to mitigate postoperative pulmonary complications (PPCs) has emerged as a current research focal point. However, there remains a divergence of opinions concerning the individualised setting and application of positive end-expiratory pressure (PEEP). Lung dynamic compliance (Cdyn) can serve as a reflection of the lung’s physiological state in children during OLV and is a readily obtainable parameter. This study protocol is formulated to assess the effectiveness of Cdyn-guided PEEP titration on PPCs during paediatric OLV.Methods and analysis This study constitutes a single-centre, prospective, double-blind, randomised controlled trial. The trial aims to recruit 60 paediatric patients scheduled for video-assisted thoracoscopic surgery. These eligible patients will be randomly assigned to either the Cdyn-guided PEEP group or the conventional PEEP group during general anaesthesia for OLV. The primary outcome will involve assessing the incidence of PPCs at 7 days after surgery. Secondary outcomes will encompass the evaluation of the modified lung ultrasound score following surgery, as well as monitoring the oxygenation index, driving pressure and Cdyn during mechanical ventilation. Data collection will be performed by investigators who are kept blinded to the interventions.Ethics and dissemination The Clinical Trial Ethics Committee at Shenzhen Children’s Hospital has conferred ethical approvals for this trial (approval number: 2022076). Results from this trial will be disseminated in peer-reviewed journals and presented at professional symposiums.Trail registration number NCT05386901.

Abstract Background The present study aimed to examine the relationship between regulatory focus and loneliness stigma, as well as the intergenerational transmission of the two. Specifically, the study analyzed the effects of fathers’ and mothers’ regulatory focus on their own and their spouses’ stigma of loneliness. In addition, a mediation model was constructed to explore how parents’ regulatory focus influences their children’s stigma of loneliness and the potential mediating mechanisms involved. Methods Questionnaires were distributed to 470 college students and their parents, employing the Regulatory Focus Questionnaire (RFQ) and the Stigma of Loneliness Scale (SLS) to collect data. Results The analysis of intergenerational transmission effects revealed that parents’ regulatory focus and loneliness stigma significantly and positively predicted children’s regulatory focus and loneliness stigma, respectively. The Actor-Partner Interdependence Model (APIM) elucidated that both fathers’ and mothers’ promotion focus exerted significant influence on both actor and partner’s loneliness stigma. Furthermore, the mediation model analysis indicated that parents’ loneliness stigma, along with children’s regulatory focus operate as mediators in the influence of parental regulatory focus on loneliness stigma of their college-aged offspring. Conclusions From a familial context, this study, investigated the association between regulatory focus and loneliness stigma, along with the mediating roles within parent-child groups and couples. The findings enhanced our comprehension of the interrelation between regulatory focus and loneliness stigma, underpinned by empirical evidence.

Abstract Background The stigma of loneliness exacerbates the negative effect of loneliness, reduces the willingness to seek help, damages interpersonal relationships, and threatens health status. However, there is currently no valid scale for measuring the stigma of loneliness in China. The study aims to translate the Stigma of Loneliness Scale (SLS) and evaluate the reliability and validity of the Chinese version. Methods The investigation was conducted in two phases. In the first phase, the SLS was used to conduct a questionnaire survey on 657 college students aged 17 to 24; in the second phase, the SLS, the UCLA Loneliness Scale (ULS-8), the Distress Disclosure Index (DDI), the Revised Cheek and Buss Shyness Scale (RCBS), the Self-Concealment Scale (SCS), the Social Interaction Anxiety Scale (SIAS), the Social Phobia Scale (SPS), the Kessler Psychological Distress Scale (K10), and the Rosenberg Self-Esteem Scale (RSES) were used to conduct the questionnaire survey on 801 college and graduates students aged 18 to 39. Results Two dimensions of Self-stigma of Loneliness and Public Stigma of Loneliness were extracted with a cumulative factor interpretation rate of 74.60% when conducting exploratory factor analysis on the first-stage data. The factor loading of each item ranged from 0.585 to 0.890, and the commonality ranged from 0.609 to 0.735. The confirmatory factor analysis and reliability and validity test were carried out on the data gathered in the second phase, indicating that the two-factor model fits well. In addition, the scores of SLS and all dimensions were significantly positively correlated with the total scores of ULS-8, RCBS, SCS, SIAS, SPS, and K10, and negatively correlated with those of DDI and RSES. The Cronbach’s alpha coefficients for SLS and SSL and PSL dimensions were 0.957, 0.941, and 0.955. The cross-group invariance test found that the SLS was equivalent for males and females. Meanwhile, males scored significantly higher than females on both the total scores of SLS score and each dimension. Conclusions The Chinese version of SLS displayed satisfactory psychometric properties and can be a valid tool to assess the stigma of loneliness among Chinese young people.

ABSTRACT: This study was conducted to determine the influence of dietary glucosamine sulfate sodium (GSS) on laying performance, blood profiles, eggshell and inner quality of eggs and relative expression of the genes related to eggshell in laying hens at early stage. A total of 640 twenty-weeks-old Lohmann laying hens were randomly allotted to 4 treatments with 10 replicates of 16 hens each. The experiment lasted for 8 wk, and dietary treatments were: 1) CON, basal diet; 2) G1, CON + 0.2% GSS; 3) G2, CON + 0.4% GSS; 4) G3, CON + 0.6% GSS. The inclusion of GSS increased average daily feed intake, laying rate, and egg mass (P < 0.05) linearly during wk 21 to 25, 25 to 29, and 21 to 29, egg weight during wk 21 to 25 and 25 to 29, and improved (P < 0.05) feed conversion ratio linearly during wk 21 to 25. The supplementation of GSS increased (P < 0.05) albumen height quadratically, Haugh unit, calcium content, calcium mass, phosphorus content and phosphorus mass linearly at the end of 25th and 29th wk. At the end of 29th wk, the eggshell strength, eggshell weight, eggshell ratio, and eggshell thickness were increased (P < 0.05) linearly in GSS treatments compared with CON. The addition of GSS increased (P < 0.05) serum calcium, estrogen 2, and calcitonin, while decreased (P < 0.05) serum tartrate resistant acid phosphatase (TRAP), parathormone, IL-6 and prostaglandin E2 (PGE2) at the end of 29th wk. The inclusion of GSS increased (P < 0.05) the relative expression of ovocalyxin-32 and ovocalyxin-36 linearly at the end of 29th wk, and ovalbumin, osteopontin, calbindin 1, and ovocleidin-116 linearly at the end of 25th and 29th wk. Quadratic effects were observed (P < 0.05) in the laying rate during wk 21 to 25, serum TRAP and PGE2, the relative expression of ovocleidin-116 at the end of 29th wk. In summary, the inclusion of GSS up-regulated relative expression of osteopontin, ovocleidin-116, ovocalyxin-32 and ovocalyxin-36 in uterus, promoted the serum PGE2 and calcitonin, thus increased the calcium content of eggshell and finally enhanced eggshell quality.

Lipid accumulation in ovaries is essential for reproductive success in decapods. Understanding of the mechanism of ovarian lipid accumulation is still in its infancy. In this study, we investigated lipid compositions of ovaries and hepatopancreas throughout vitellogenesis and hemolymph in the late-vitellogenic stage in the mud crab Scylla paramamosain. Total lipid content in ovaries consecutively increased from the early to late stage, and the main accumulated lipids were phosphatidylcholine (PC), alkenylglycerophosphoethanolamine (alkenyl-PE), triacylglycerol (TG), cholesteryl ester, and cholesterol. The lipid composition of hemolymph indicated that PC, alkenyl-PE, diacylglycerol (DG), ether DG, monoacylglycerol, and cholesterol were the main lipids transferred to ovaries from hepatopancreas. In hepatopancreas, the total lipid content appeared to increase during vitellogenesis and the late stage was significantly different from early and mid-stages. TG was the predominant lipid class that slightly decreased from the early to mid-stage, but dramatically increased in the late stage. In contrast, PC and alkenyl-PE significantly increased from the early to mid-stage and remained constantly in relatively low proportion until the late stage. These findings suggested PC and alkenyl-PE in the hepatopancreas likely play critical roles in regulating lipid transfer. Esterified fatty acids in ovaries and hepatopancreas were mainly C16:0, C18:0, 16:1, C18:1, C18:2, C20:4, C20:5, and C22:6, of which highly unsaturated fatty acids (HUFA) primarily occurred in alkenyl-PE and phosphatidylserine (PS) but not PC. In hemolymph, PC was abundant in HUFA besides of saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA), while PS was predominantly composed of SFA and MUFA, implying a transformation of HUFA between phospholipids prior to transfer. These findings highlight the importance of phospholipid metabolism in the hepatopancreas to ovarian lipid accumulation. Our study provides novel insights into the mechanism of ovarian lipid accumulation in decapods.

Thousand-kernel weight (TKW) is a measure of grain weight, a target of wheat breeding. The object of this study was to fine-map a stable quantitative trait loci (QTL) for TKW and identify its candidate gene in a recombinant inbred line (RIL) population derived from the cross of Kenong 9204 (KN9204) and Jing 411 (J411). On a high-density genetic linkage map, 24, 26 and 25 QTL were associated with TKW, kernel length (KL), and kernel width (KW), respectively. A major and stable QTL, QTkw-2D, was mapped to an 8.3 cM interval on chromosome arm 2DL. By saturation of polymorphic markers in its target region, QTkw-2D was confined to a 9.13 Mb physical interval using a secondary mapping population derived from a residually heterozygous line (F6:7). This interval was further narrowed to 2.52 Mb using QTkw-2D near-isogenic lines (NILs). NILsKN9204 had higher fresh and dry weights than NILsJ411 at various grain-filling stages. The TKW and KW of NILsKN9204 were much higher than those of NILsJ411 in field trials. By comparison of both DNA sequence and expression between KN9204 and J411, TraesCS2D02G460300.1 (TraesKN2D01HG49350) was assigned as a candidate gene for QTkw-2D. This was confirmed by RNA sequencing (RNA-seq) of QTkw-2D NILs. These results provide the basis of map-based cloning of QTkw-2D, and DNA markers linked to the candidate gene may be used in marker-assisted selection.

BackgroundImmune checkpoint inhibitor-induced isolated adrenocorticotropic hormone deficiency (IAD) is a rare but potentially fatal disease.MethodsWe comprehensively searched the PubMed database and made a systematic review of immune checkpoint inhibitor-induced isolated adrenocorticotropic hormone deficiency. If the status of other anterior pituitary hormones was not mentioned, the case was excluded.ResultsWe identified 123 cases diagnosed as immune checkpoint inhibitor-induced IAD, consisting of 44 female and 79 male patients. The average age of these patients was 64.3 ± 12.6 years old, and 67.5% were 60 years old or above. The majority (78.9%) of these patients received anti-programmed cell death protein-1 (anti-PD-1) antibodies or anti-programmed cell death ligand 1 (anti-PD-L1) antibodies or both, and 19.5% received combined therapy, sequential therapy, or both. A total of 26 patients received anti-cytotoxic T lymphocyte antigen 4 antibodies (anti-CTLA-4). The median ICI treatment cycle before the diagnosis of adrenal insufficiency was 8 (6, 12), and the median ICI treatment duration before the diagnosis of adrenal insufficiency was 6 (4, 8) months. Eleven cases developed IAD 1 to 11 months after discontinuation of ICIs. Fatigue and appetite loss were the most common symptoms, and surprisingly, there were two asymptomatic cases of IAD. Most patients (88 cases) had normal pituitary magnetic resonance imaging, only 14 cases reported mild atrophy or swelling pituitary gland, and 21 cases reported no imaging results. Most diagnoses were made by basal hormone levels, and pituitary stimulation tests were performed in only a part of the cases. No cases had been reported of discontinuation of ICI use due to IAD nor had there been any deaths due to IAD.ConclusionIAD was predominant in elderly male patients mainly receiving anti-PD-1 or anti-PD-L1 antibodies. It was sometimes difficult to recognize IAD at first glance since non-specific symptoms were common and asymptomatic cases of IAD were also reported. Although IAD can be deadly, it usually does not affect the continued use of ICIs.

Abstract Existing salient object detection networks are large, have many parameters, are bulky and take up a lot of computational resources. Seriously hinder its application and promotion in boning robot. To solve this problem, this paper proposes a lightweight saliency detection algorithm for real-time localization of livestock meat bones. First, a lightweight feature extraction network based on multi-scale attention is constructed in the encoding stage. To ensure that more adequate salient object features are extracted with fewer parameters. Second, the fusion of jump connections is introduced in the decoding phase. Used to capture fine-grained semantics and coarse-grained semantics at full scale. Finally, we added a residual refinement module at the end of the backbone network. For optimizing salient target regions and boundaries. Experimental results on both publicly available datasets and self-made Pig leg X-ray (PLX) datasets show that. The proposed method is capable of ensuring first-class detection accuracy with 40 times less parameters than the conventional model. In the most challenging SOD dataset. The proposed algorithm in this paper achieves a value of Fωβ of 0.699. And the segmentation of livestock bones can be effectively performed on the homemade PLX dataset. Our model has a detection speed of 5fps on industrial control equipment.

Crop pest insects seriously affect yield and quality of crops, and pesticide control methods cause severe environmental pollution, which has inextricably influenced people’s daily lives. Crop pest identification in the field is crucial components of pest control. It is much more complex than generic object recognition due to the apparent differences in the same pest species in the field with various shapes, colours, sizes and complex background. A crop pest recognition method is proposed based on a modified capsule network (MCapsNet). In MCapsNet, a capsule network is used to improve the traditional convolutional neural network (CNN), and an attention module is introduced to capture the most important classification features and speed up the network training. The experimental results on a pest image dataset validate that the proposed method is effective and feasible in classifying various types of insects in field crops and can be implemented in the agriculture sector for crop protection.

IntroductionColorectal adenoma can develop into colorectal cancer. Determining the risk of tumorigenesis in colorectal adenoma would be critical for avoiding the development of colorectal cancer; however, genomic features that could help predict the risk of tumorigenesis remain uncertain.MethodsIn this work, DNA and RNA parallel capture sequencing data covering 519 genes from colorectal adenoma and colorectal cancer samples were collected. The somatic mutation profiles were obtained from DNA sequencing data, and the expression profiles were obtained from RNA sequencing data.ResultsDespite some similarities between the adenoma samples and the cancer samples, different mutation frequencies, co-occurrences, and mutually exclusive patterns were detected in the mutation profiles of patients with colorectal adenoma and colorectal cancer. Differentially expressed genes were also detected between the two patient groups using RNA sequencing. Finally, two random forest classification models were built, one based on mutation profiles and one based on expression profiles. The models distinguished adenoma and cancer samples with accuracy levels of 81.48% and 100.00%, respectively, showing the potential of the 519-gene panel for monitoring adenoma patients in clinical practice.ConclusionThis study revealed molecular characteristics and correlations between colorectal adenoma and colorectal cancer, and it demonstrated that the 519-gene panel may be used for early monitoring of the progression of colorectal adenoma to cancer.

Abstract Background Circular RNA (circRNA), a new class of non-coding RNA, has obvious correlations with the occurrence and development of many diseases, including tumors. This study aimed to investigate the potential roles of circPAK1 in hepatocellular carcinoma (HCC). Methods High-throughput sequencing was performed on 3 pairs of HCC and matched normal tissues to determine the upregulated circRNAs. The expression level of circPAK1 was detected by qRT-PCR in HCC and paired with normal liver tissue samples. The effects of circPAK1 on proliferation, invasion, metastasis and apoptosis of HCC cells were evaluated by in vitro and in vivo experiments. We also constructed Chitosan/si-circPAK1 (CS/si-circPAK1) nanocomplexes using Chitosan material to evaluate its in vivo therapeutic effect on HCC. High-throughput sequencing, RNA-sequencing, RNA probe pull-down, RNA immunoprecipitation and Co-Immunoprecipitation assays were performed to explore the relationship between circPAK1, 14–3-3ζ, p-LATS1 and YAP. Exosomes isolated from lenvatinib-resistant HCC cell lines were used to evaluate the relationship between exosomal circPAK1 and lenvatinib resistance. Results CircPAK1, a novel circRNA, is highly expressed in HCC tumor tissues and cell lines as well as correlated with poor outcomes in HCC patients. Functionally, circPAK1 knockdown inhibited HCC cell proliferation, migration, invasion and angiogenesis while circPAK1 overexpression promoted HCC progression. The tumor-promoting phenotypes of circPAK1 on HCC were also confirmed by animal experiments. Importantly, the application of CS/si-circPAK1 nanocomplexes showed a better therapeutic effect on tumor growth and metastasis. Mechanistically, circPAK1 enhanced HCC progression by inactivating the Hippo signaling pathway, and this kind of inactivation is based on its competitively binding of 14–3-3 ζ with YAP, which weakens the recruitment and cytoplasmic fixation of 14–3-3 ζ to YAP, thus promoting YAP nucleus localization. Additionally, circPAK1 could be transported by exosomes from lenvatinib-resistant cells to sensitive cells and induce lenvatinib resistance of receipt cells. Conclusion CircPAK1 exerts its oncogenic function by competitively binding 14–3-3 ζ with YAP, thus promoting YAP nucleus localization, leading to the inactivation of a Hippo signaling pathway. Exosomal circPAK1 may drive resistance to lenvatinib, providing a potential therapeutic target for HCC patients.

To develop the polysaccharides from Spirulina platensis-chitosan composite film (PSP/CH-film) with good performance, nano-SiO2 modified SiO2/polysaccharides from Spirulina platensis-chitosan composite film (SiO2/PSP/CH-film) was developed. The effect of different mass concentrations and different particle diameters of nano-SiO2 on the structure, physical properties, mechanical properties, bacteriologists and biodegradability of SiO2/PSP/CH-film were explored. The results showed that：Nano-SiO2 had good compatibility with chitosan and polysaccharides from Spirulina platensis, and the surface of SiO2/PSP/CH-film was smooth and flat. The addition of nano-SiO2 with a mass concentration of 0.05%~0.15% and the particle size of 30 nm improved the tensile strength and antibacterial properties of SiO2/PSP/CH-film, increased the thickness, swelling degree and opacity, but it delayed the biodegradability and decreased the elongation at break. When the mass concentration of nano-SiO2 was 0.1% and the particle size was 30 nm, the SiO2/PSP/CH-film exhibited excellent antibacterial properties and tensile strength, which was beneficial to prolong the shelf life of food and improving the actual durability of the film. When the mass concentration of nano-SiO2 was constant and nano-SiO2 with a particle size of 500 nm was added, only the elongation at break increased with the increase of the particle size. Therefore, nano-SiO2, as a good modified material, could be well dispersed in the blending system of PSP/CH-film, improved network structure and comprehensive performance of the composite film.

Abstract Water storage capacity in the layers of canopy, litter, and soil of forest ecosystems has not yet been thoroughly investigated on a global scale. We estimated the global pattern of water storage capacity of forest ecosystems related to water regulation services (WSCFE) in the above three layers based on 1,288 observations and analyzed their 22 controlling environmental factors. The results show that the global mean WSCFE per unit area is 456.7 mm, and the total volume of WSCFE is 22,662.5 km3. Climatic variables are the leading factors contributing to the variations of WSCFE, followed by forest attributes, terrain factors, soil properties, and litter characteristics. This study advances the understanding of the large‐scale variation mechanisms of WSCFE in different forest types and climate zones and provides scientific evidence for ecological protection according to local conditions.

Abstract Background N-myc downstream regulated gene 1 (NDRG1) plays a role in a variety of biological processes including differentiation of osteoclasts. However, it is not known if and how NDRG1 regulates osteogenic differentiation of marrow stromal progenitor cells. Methods Gene expression profiling analysis was performed to study the expression level of Ndrg1 during osteogenic and adipogenic differentiation. Gain-of-function and/or loss-of function experiments were carried out to study the role of NDRG1 in the proliferation and differentiation of marrow stromal progenitor cells and the mechanism underlying the function was investigated. Finally, in vivo transfection of Ndrg1 siRNA was done and its effect on osteogenic and adipogenic differentiation in mice was explored. Results Gene expression profiling analysis revealed that NDRG1 level was regulated during osteogenic and adipogenic differentiation of progenitor cells. The functional experiments demonstrated that NDRG1 negatively regulated the cell growth, and reciprocally modulated the osteogenic and adipogenic commitment of marrow stromal progenitor cells, driving the cells to differentiate toward adipocytes at the expense of osteoblast differentiation. Moreover, NDRG1 interacted with low-density lipoprotein receptor-related protein 6 (LRP6) in the stromal progenitor cells and inactivated the canonical Wnt/β-catenin signaling cascade. Furthermore, the impaired differentiation of progenitor cells induced by Ndrg1 siRNA could be attenuated when β-catenin was simultaneously silenced. Finally, in vivo transfection of Ndrg1 siRNA to the marrow of mice prevented the inactivation of canonical Wnt signaling in the BMSCs of ovariectomized mice, and ameliorated the reduction of osteoblasts on the trabeculae and increase of fat accumulation in the marrow observed in the ovariectomized mice. Conclusion This study has provided evidences that NDRG1 plays a role in reciprocally modulating osteogenic and adipogenic commitment of marrow stromal progenitor cells through inactivating canonical Wnt signaling.

N6-methyladenosine (m6A) is capable of mediating circRNA generation in carcinoma biology. Nevertheless, the posttranscriptional systems of m6A and circRNA in hepatocellular carcinoma (HCC) development are still unclear. The present study identified a circRNA with m6A modification, circHPS5, which was increased in neoplasm HCC tissues and indicated poor patient survival. Silencing of circHPS5 inhibited epithelial-mesenchymal transition (EMT) and cancer stem-like cell (CSC) phenotypes. Notably, METTL3 could direct the formation of circHPS5, and specific m6A controlled the accumulation of circHPS5. YTHDC1 facilitated the cytoplasmic output of circHPS5 under m6A modification. In addition, we demonstrated that circHPS5 can act as a miR-370 sponge to regulate the expression of HMGA2 and further accelerate HCC cell tumorigenesis. Accordingly, the m6A modification of circHPS5 was found to modulate cytoplasmic output and increase HMGA2 expression to facilitate HCC development. The new regulatory model of “circHPS5-HMGA2” provides a new perspective for circHPS5 as an important prognostic marker and therapeutic target in HCC and provides mechanistic insight for exploring the carcinogenic mechanism of circHPS5 in HCC.

The study of microplastics and their impact on aquatic ecosystems has received increasing attention in recent years. Drawing from an analysis of 814 papers related to microplastics published between 2013 and 2022 in the Web of Science Core Repository, this paper explores trends, focal points, and national collaborations in freshwater microplastics research, providing valuable insights for future studies. The findings reveal three distinct stages of microplastics: nascent development (2013–2015), slow rise (2016–2018), and rapid development (2019–2022). Over time, the focus of research has shifted from “surface”, “effect”, “microplastic pollution”, and “tributary” to “toxicity”, “species”, “organism”, “threat”, “risk”, and “ingestion”. While international cooperation has become more prevalent, the extent of collaboration remains limited, mostly concentrated among English-speaking countries or English and Spanish/Portuguese-speaking countries. Future research directions should encompass the bi-directional relationship between microplastics and watershed ecosystems, incorporating chemical and toxicological approaches. Long-term monitoring efforts are crucial to assessing the sustained impacts of microplastics.

Colon cancer and colorectal cancer are two common cancer-related deaths worldwide. Identification of potential biomarkers for the two cancers can help us to evaluate their initiation, progression and therapeutic response. In this study, we propose a new microRNA-disease association identification method, BNNRMDA, to discover potential microRNA biomarkers for the two cancers. BNNRMDA better combines disease semantic similarity and Gaussian Association Profile Kernel (GAPK) similarity, microRNA function similarity and GAPK similarity, and the bound nuclear norm regularization model. Compared to other five classical microRNA-disease association identification methods (MIDPE, MIDP, RLSMDA, GRNMF, AND LPLNS), BNNRMDA obtains the highest AUC of 0.9071, demonstrating its strong microRNA-disease association identification performance. BNNRMDA is applied to discover possible microRNA biomarkers for colon cancer and colorectal cancer. The results show that all 73 known microRNAs associated with colon cancer in the HMDD database have the highest association scores with colon cancer and are ranked as top 73. Among 137 known microRNAs associated with colorectal cancer in the HMDD database, 129 microRNAs have the highest association scores with colorectal cancer and are ranked as top 129. In addition, we predict that hsa-miR-103a could be a potential biomarker of colon cancer and hsa-mir-193b and hsa-mir-7days could be potential biomarkers of colorectal cancer.

Abstract The extent of intra‐annual turnover in phytoplankton communities is directly associated with the overall diversity. However, our understanding of the underlying causes and effects of intra‐annual turnover remains limited. In this study, we performed a two‐season investigation of the phytoplankton composition in the lakes of the Yangtze River catchment in China in spring and summer 2012, which covered a regional spatial scale. We analyzed the Sørensen pairwise dissimilarity (βsor) between the two seasons, their driving factors, and effects on resource use efficiency in phytoplankton. The results showed that the changes in phytoplankton composition from spring to summer were not synchronous among these lakes. The spatial environmental characteristics, temporal changes in environmental variables and the initial phytoplankton composition together explained the variation in βsor for phytoplankton, and their explanatory powers and primary driving variables depended on the phytoplankton taxonomic groups. Among the driving variables, increased nitrogen level and seasonal temperature difference will promote spring–summer community turnover and then improve the phosphorus use efficiency of phytoplankton community. The species diversity of the initial community might increase its stability and slow the spring–summer shift in phytoplankton, especially in cyanobacteria and Chlorophyta. Our study highlights the understanding of the patterns and underlying causes of temporal beta diversity in freshwater phytoplankton communities.

ObjectivesEndometrial carcinoma (EC) is one of the three major gynecological malignancies, in which 15% - 20% patients will have recurrence and metastasis. Though there are many studies on the prognosis on this cancer, the performances of existing models evaluating the risk of its recurrence and metastasis are yet to be improved. In addition, a comprehensive multi-omics analyses on the prognostic signatures of EC are on demand. In this study, we aimed to construct a relatively stable and reliable model for predicting recurrence and metastasis of EC. This will help determine the risk level of patients and choose appropriate adjuvant therapy, thereby avoiding improper treatment, and improving the prognosis of patients.MethodsThe mRNA, microRNA (miRNA), long non-coding RNA (lncRNA), copy number variation (CNV) data and clinical information of patients with EC were downloaded from The Cancer Genome Atlas (TCGA). Differential expression analyses were performed between the recurrence or metastasis group and the non-recurrence/metastasis group. Then, we screened potential prognostic markers from the four kinds of omics data respectively and established prediction models using three classifiers.ResultsWe achieved differential expressed mRNAs, lncRNAs, miRNAs and CNVs between the two groups. According to feature selection scores by the random forest algorithm, 275 CNV features, 50 lncRNA features, 150 miRNA features and 150 mRNA features were selected, respectively. And the prediction model constructed by the features of lncRNA data using random forest method showed the best performance, with an area under the curve of 0.763, and an accuracy of 0.819 under 10-fold cross-validation.ConclusionWe developed a computational model using omics information, which is able to predicting recurrence and metastasis risk of EC accurately.

Cancer of unknown primary (CUP) refers to cancer with primary lesion unidentifiable by regular pathological and clinical diagnostic methods. This kind of cancer is extremely difficult to treat, and patients with CUP usually have a very short survival time. Recent studies have suggested that cancer treatment targeting primary lesion will significantly improve the survival of CUP patients. Thus, it is critical to develop accurate yet fast methods to infer the tissue-of-origin (TOO) of CUP. In the past years, there are a few computational methods to infer TOO based on single omics data like gene expression, methylation, somatic mutation, and so on. However, the metastasis of tumor involves the interaction of multiple levels of biological molecules. In this study, we developed a novel computational method to predict TOO of CUP patients by explicitly integrating expression quantitative trait loci (eQTL) into an XGBoost classification model. We trained our model with The Cancer Genome Atlas (TCGA) data involving over 7,000 samples across 20 types of solid tumors. In the 10-fold cross-validation, the prediction accuracy of the model with eQTL was over 0.96, better than that without eQTL. In addition, we also tested our model in an independent data downloaded from Gene Expression Omnibus (GEO) consisting of 87 samples across 4 cancer types. The model also achieved an f1-score of 0.7–1 depending on different cancer types. In summary, eQTL was an important information in inferring cancer TOO and the model might be applied in clinical routine test for CUP patients in the future.

Lysoforte (LFT) plays a vital role in maintaining broilers' health and intestinal morphology. However, the mechanism behind the effects of LFT improving intestinal morphology and health is still unclear. Therefore, this study was implemented to explore the central genes linked to the regulatory effect of LFT. Seventy-five newly hatched Cobb 500 male broilers were randomly divided into three groups: control, LFT500, and LFT1000 groups, with 25 chicks per group. The control chicks were provided with the basal diet, and the birds in LFT500 and LFT1000 groups were offered the same basal diet with 500 g/ton and 1,000 g/ton LFT, respectively. GSE94622 dataset consisted of the control and two LFT-treated groups (LFT500 and LFT1000). Jejuna samples were obtained from Gene Expression Omnibus (GEO). Totally 106–344 DEGs were obtained by comparing LFT500 and LFT1000 vs. control and LFT1000 vs. LFT500. Gene ontology (GO) enrichment suggested that the DEGs are mainly related to the phosphatidylethanolamine biosynthetic process and neuron projection extension. KEGG analysis suggested the DEGs were enriched in AGE-RAGE, fatty acid elongation, ECM-receptor interaction (ECMRI), glycerophospholipid metabolism, focal adhesion, unsaturated fatty acids biosynthesis, and ABC transporters. Moreover, 29 genes, such as REG4, GJB1, KAT2A, APOA5, SERPINE2, ELOVL1, ABCC2, ANKRD9, CYP4V2, and PISD, might be closely related to promoting jejuna morphology in broilers. Taken together, our observation enhances the understanding of LFT in maintaining intestinal architecture and the general health of broiler chickens.

A thyroid nodule, which is defined as abnormal growth of thyroid cells, indicates excessive iodine intake, thyroid degeneration, inflammation, and other diseases. Although thyroid nodules are always non-malignant, the malignancy likelihood of a thyroid nodule grows steadily every year. In order to reduce the burden on doctors and avoid unnecessary fine needle aspiration (FNA) and surgical resection, various studies have been done to diagnose thyroid nodules through deep-learning-based image recognition analysis. In this study, to predict the benign and malignant thyroid nodules accurately, a novel deep learning framework is proposed. Five hundred eight ultrasound images were collected from the Third Hospital of Hebei Medical University in China for model training and validation. First, a ResNet18 model, pretrained on ImageNet, was trained by an ultrasound image dataset, and a random sampling of training dataset was applied 10 times to avoid accidental errors. The results show that our model has a good performance, the average area under curve (AUC) of 10 times is 0.997, the average accuracy is 0.984, the average recall is 0.978, the average precision is 0.939, and the average F1 score is 0.957. Second, Gradient-weighted Class Activation Mapping (Grad-CAM) was proposed to highlight sensitive regions in an ultrasound image during the learning process. Grad-CAM is able to extract the sensitive regions and analyze their shape features. Based on the results, there are obvious differences between benign and malignant thyroid nodules; therefore, shape features of the sensitive regions are helpful in diagnosis to a great extent. Overall, the proposed model demonstrated the feasibility of employing deep learning and ultrasound images to estimate benign and malignant thyroid nodules.

Tumor mutation burden (TMB) is an important biomarker for tumor immunotherapy. It plays an important role in the clinical treatment process, but the gold standard measurement of TMB is based on whole exome sequencing (WES). WES cannot be done in most hospitals due to its high cost, long turnaround times and operational complexity. To seek out a better method to evaluate TMB, we divided the patients with lung adenocarcinoma (LUAD) in TCGA into two groups according to the TMB value, then analyzed the differences of clinical characteristics and gene expression between the two groups. We further explored the possibility of using histopathological images to predict TMB status, and developed a deep learning model to predict TMB based on histopathological images of LUAD. In the 5-fold cross-validation, the area under the receiver operating characteristic (ROC) curve (AUC) of the model was 0.64. This study showed that it is possible to use deep learning to predict genomic features from histopathological images, though the prediction accuracy was relatively low. The study opens up a new way to explore the relationship between genes and phenotypes.

ABSTRACT As the key contributor to plankton biomass and nutrient cycling in aquatic ecosystems, photosynthetic picoeukaryotes (PPEs) have been recently investigated in freshwater ecosystems. However, the limited access to remote areas creates challenges for PPE sample preservation before sorting and counting by flow cytometry (FCM) in the laboratory. Here, we explored the effects of different preservation methods on the PPE community by combining FCM sorting and high-throughput sequencing. Our results showed that dimethyl sulfoxide (DMSO) cryoprotection could destroy the fluorescence and cell structure of the PPEs, making the subsequent FCM analysis and sorting difficult. Aldehyde fixation maintained the PPE fluorescence, and the fixed samples were of sufficient quality for abundance analysis and sorting by FCM. However, the sequencing results showed that, after preservation by aldehydes, the proportion of PPEs dramatically decreased to approximately 10%, in comparison to 90% in the fresh samples, and the sequences of Ascomycota significantly increased. In contrast, preservation with Pluronic F68 (F68) not only could maintain the PPE abundance close to the initial value but also could keep the PPE community similar to that in the fresh samples over a storage time of 6 months. Thus, F68 cryopreservation is a suitable preservation method for PPE communities from freshwater lakes. IMPORTANCE PPEs contribute significantly to primary productivity in freshwater ecosystems. The combination of FCM sorting and high-throughput sequencing has been shown to be a powerful approach and can largely improve our view of the PPE diversity. However, the water samples could not be counted and sorted immediately after sampling from many lakes due to the inaccessibility of FCM in the field. Thus, the comparison of different preservation methods that allow subsequent analysis of the community structure by high-throughput sequencing is an urgent need. Our results indicated that F68 cryopreservation could maintain the PPE abundance close to the initial value and keep the community similar to that in the fresh samples over a storage time of 6 months.

γ-D-glutamyl-meso-diaminopimelic acid (iE-DAP), a bacterial cell wall component, can trigger an inflammatory response. A mammary inflammatory response causes tight junction (TJ) dysfunction. This study aimed to explore the effects and involved mechanisms of iE-DAP-induced inflammatory response on the TJ integrity in bovine mammary epithelial cells (BMECs). The results showed that iE-DAP-induced inflammatory response and TJ disruption was associated with increased expression levels of inflammatory cytokines and decreased gene expression of ZO-1 and Occludin, as well as a reduction in transepithelial electrical resistance and elevation in paracellular dextran passage. While MLCK inhibitor ML-7 reversed the TJ disruption induced by iE-DAP. NF-κB inhibitor BAY 11-7085 hindered the activation of NF-κB and MLCK signaling pathways, the inflammatory response and TJ disruption induced by iE-DAP. NOD1-specific shRNA also inhibited the activation of the NOD1/NF-κB signaling pathway and reversed the inflammatory response and TJ injury in iE-DAP-treated BMECs. Above results suggest that iE-DAP activated the NF-κB and MLCK signaling pathway in NOD1-dependent manner, which promoted the transcription of inflammatory cytokines and altered the expression and distribution of tight junction proteins, finally caused inflammatory response and TJ disruption. This study might provide theoretical basis and scientific support for the prevention and treatment of mastitis.

Systematic evaluation of nitrogen (N) application in multi-crop production and its environmental impacts are of great significance for sustainable development of agriculture. Previous studies have focused on the evaluation of grain crops at the national and provincial levels, but ignored the county scale. Here, we evaluated the N rate, N use efficiency (NUE), N surplus, and greenhouse gas (GHG) emissions from the production of multiple crops including rice, wheat, maize, soybeans, tea, fruits, and vegetables at the county level of Fujian Province, China. The results showed that the N rates, N surpluses, and GHG emissions were generally higher, and NUEs were generally lower in the southern and southeastern coastal counties of Fujian Province, while the counties in the north and west had the opposite distribution trends. The N input and its negative environmental impacts for grain crops were generally lower than those for cash crops. The average NUE of all crops in Fujian Province in 2014 was 52.31%. The N input and N surplus for fruits accounted for 43.95% and 46.69% of those in the whole province, respectively. The evaluated framework we proposed in this study can be widely applied in the systematic evaluation of N input and its environmental footprints at the county scale for regions with multi-crop production.

Detection of in vivo biodegradation is critical for development of next-generation medical devices such as bioresorbable stents or scaffolds (BRSs). In particular, it is urgent to establish a nondestructive approach to examine in vivo degradation of a new-generation coronary stent for interventional treatment based on mammal experiments; otherwise it is not available to semi-quantitatively monitor biodegradation in any clinical trial. Herein, we put forward a semi-quantitative approach to measure degradation of a sirolimus-eluting iron bioresorbable scaffold (IBS) based on optical coherence tomography (OCT) images; this approach was confirmed to be consistent with the present weight-loss measurements, which is, however, a destructive approach. The IBS was fabricated by a metal-polymer composite technique with a polylactide coating on an iron stent. The efficacy as a coronary stent of this new bioresorbable scaffold was compared with that of a permanent metal stent with the name of trade mark Xience, which has been widely used in clinic. The endothelial coverage on IBS was found to be greater than on Xience after implantation in a rabbit model; and our well-designed ultrathin stent exhibited less individual variation. We further examined degradation of the IBSs in both minipig coronary artery and rabbit abdominal aorta models. The present result indicated much faster iron degradation of IBS in the rabbit model than in the porcine model. The semi-quantitative approach to detect biodegradation of IBS and the finding of the species difference might be stimulating for fundamental investigation of biodegradable implants and clinical translation of the next-generation coronary stents.

BackgroundCholangiocarcinoma (CCA) remains one of the most lethal malignancies with an increasing incidence globally. Through whole-exome sequencing of 67 CCA tissues, we identified new mutated genes in CCA, including MACF1, METTL14, ROBO1, and so on. The study was designed to explore the effects and mechanism of ROBO1 wild type (ROBO1WT) and ROBO1E280* mutation on the progression of CCA.MethodsWhole-exome sequencing was performed to identify novel mutations in CCAs. In vitro and in vivo experiments were used to examine the function and mechanism of ROBO1WT and ROBO1E280* in cholangiocarcinoma. A tissue microarray including 190 CCA patients and subsequent analyses were performed to indicate the clinical significance of ROBO1.ResultsThrough whole-exome sequencing, we identified a novel CCA-related mutation, ROBO1E280*. ROBO1 was downregulated in CCA tissues, and the downregulation of ROBO1 was significantly correlated with poor prognosis. ROBO1WT suppressed the proliferation and angiogenesis of CCA in vitro and in vivo, while ROBO1E280* lost the inhibitory effects. Mechanically, ROBO1E280* translocated from the cytomembrane to the cytoplasm and interrupted the interaction between SLIT2 and ROBO1. We identified OLFML3 as a potential target of ROBO1 by conducting RNA-Seq assays. OLFML3 expression was downregulated by ROBO1WT and recovered by ROBO1E280*. Functionally, the silence of OLFML3 inhibited CCA proliferation and angiogenesis and was sufficient to repress the loss-of-function role of ROBO1E280*.ConclusionsThese results suggest that ROBO1 may act as a tumor suppressor and potential prognostic marker for CCA. ROBO1E280* mutation is a loss-of-function mutation, and it might serve as a candidate therapeutic target for CCA patients.

Accurate and rapid identification of apple diseases is the basis for preventing and treating the apple diseases, and is very significant for assessing disease disaster. Apple disease recognition from its diseased leaf images is one of the interesting research areas in computer and agriculture field. An apple disease recognition method is proposed based on modified convolutional neural networks (MCNN). In MCNN, Inception is introduced into MCNN, global average pooling (GAP) operator is employed instead of several fully connected layers to speedup training model, and modified Softmax classifier is used in the output layer to improve the recognition performance. The modified Softmax classifier uses the modified linear element as the activation function in the hidden layer and adds the local response normalization in MCNN to avoid the gradient disappearance problem effectively. A series of experiments are conducted on two kinds of apple disease image datasets. The results show the feasibility of the algorithm.

BackgroundHepatocellular carcinoma (HCC) is a highly heterogeneous tumor with several rare pathological subtypes and which is still poorly understood. This study aimed to describe the epidemiological and clinical spectrum of five rare HCC subtypes and develop a competing risk nomogram for cancer-specific survival prediction.MethodsThe study cohort was recruited from the Surveillance, Epidemiology, and End Results database. The clinicopathological data of 50,218 patients histologically diagnosed with classic HCC and five rare subtypes (ICD-O-3 Histology Code = 8170/3-8175/3) between 2004 and 2018 were reviewed. The annual percent change (APC) was calculated utilizing Joinpoint regression. The nomogram was developed based on multivariable competing risk survival analyses. Akaike information criterion, Bayesian information criterion, C-index, calibration curve, and area under the receiver operating characteristic curve were obtained to evaluate the prognostic performance. A decision curve analysis was introduced to examine the clinical value of the models.ResultsDespite scirrhous carcinoma, which showed a decreasing trend (APC = -6.8%, P = 0.025), the morbidity of other rare subtypes remained stable from 2004 to 2018. The incidence-based mortality was plateau in all subtypes during the period. Clear cell carcinoma is the most common subtype (n = 551, 1.1%), followed by subtypes of fibrolamellar (n = 241, 0.5%), scirrhous (n = 82, 0.2%), spindle cell (n = 61, 0.1%), and pleomorphic (n = 17, ~0%). The patients with fibrolamellar carcinoma were younger and more likely to have a non-cirrhotic liver and better prognoses. Scirrhous carcinoma shared almost the same macro-clinical characteristics and outcomes as the classic HCC. Clear cell carcinoma tended to occur in the Asia-Pacific elderly male population, and more than half of them were large HCC (Size>5cm). Sarcomatoid (including spindle cell and pleomorphic) carcinoma was associated with a larger tumor size, poorer differentiation, and more dismal prognoses. The pathological subtype, T stage, M stage, surgery, alpha-fetoprotein, and cancer history were confirmed as the independent predictors in patients with rare subtypes. The nomogram showed good calibration, discrimination, and net benefits in clinical practice.ConclusionThe rare subtypes had unique clinicopathological features and biological behaviors compared with the classic HCC. Our findings could provide a valuable reference for clinicians. The constructed nomogram could predict the prognoses with good performance, which is meaningful to individualized management.

BackgroundThe evaluation of the nodal status of hepatocellular carcinoma (HCC) is a classic but controversial topic. This study aimed to investigate the incidence of lymph node metastasis (LNM), explore the role of lymph node dissection (LND), and develop and validate a novel model to predict LNM in patients with HCC, not other specified (NOS).MethodsThe study cohort was taken from the Surveillance, Epidemiology, and End Results database. The annual percent change (APC) was calculated using the Joinpoint regression. Survival analyses adopted the competing risk model. The nomogram was constructed based on the least absolute shrinkage and selection operator (LASSO) logistic regression algorithm and validated by calibration curves. The area under the receiver operating characteristic curve (AUROC) was obtained to compare prognostic performance. Decision curve and clinical impact curve analyses were introduced to examine the clinical value of the models.ResultsA total of 8,829 patients were finally enrolled in this study, and 1,346 (15.2%) patients received LND. The LND rate showed no noticeable fluctuation in the last decade, with an APC of 0.5% (P=0.593). LNM was identified in 56 (4.2%) patients and confirmed an independent prognostic factor of HCC patients (P=0.005). There were 2,497 lymph nodes retrieved, and 93 (3.7%) of them were positive. After propensity score matching, LND indicated no direct oncologic benefit and did not worsen competing risks. Moreover, an increased number of lymph nodes retrieved could not improve prognoses. 1,346 patients with LND were further randomly divided into the training and validation sets with the ratio of 1:1. Race, tumor size, clinical T stage, extrahepatic bile duct invasion, and tumor grade were independent risk factors for LNM. The constructed model was well calibrated and showed good discrimination power and net benefits in clinical practice.ConclusionLNM is an independent prognostic factor in HCC, but routine LND seems to be unnecessary in HCC patients. The constructed model could predict the presence of LNM in HCC patients with good performance, which is meaningful to patient stratification and individual treatment strategies optimization.

In highway management, the prediction of the routine maintenance cost of tunnels is an important issue in saving tunnel maintenance costs due to its uncertainty, and the influencing factors should be carefully selected because too many variables could not be involved in the model. The complicated relationship between variables may lead to the inconsistency of model coefficients with the actual situation even though the goodness of fit of the model constructed with more variables is higher. This paper presents an approach in which quantitative analysis is combined with qualitative analysis to quickly select the independent variables of the tunnel routine maintenance cost (TMC) model. Based on the routine maintenance data collection of nine highway tunnels in Shaanxi province from 2007 to 2016, the independent variables of the models are determined with one-way ANOVA, Pearson correlation, partial correlation, and hierarchical regression. Afterwards, a fixed-effect regression model which can reflect the overall regional features is developed. Results show that tunnel age (Age) and tunnel length proportion (PET) have less effect on TMC among the main influencing factors such as district, Age, annual average daily traffic volume (AADT), truck traffic volume proportion (PTT), PET, and number of ventilation facilities (NVF), while the NVF makes a positive contribution to the TMC. Compared with grouped regression models, the fixed-effect regression model has higher fitting accuracy and a better regression coefficient significance. The quick independent variable selection method can shorten the time of establishing the model and determine the influencing factors of the research object effectively. The established model is suitable for forecasting the TMC and budget arrangement. In addition, the elastic analysis results of regression coefficients are helpful to the decision of maintenance strategy and the allocation of maintenance funds.

Awns play an important role in seed dispersal and photosynthesis of spikes. Three major awn inhibitors (Hd, B1, and B2) are reported in wheat. However, the molecular mechanism underlying awnlessness remained unknown until recently. In this study, we identified two F8 recombinant inbred lines (RILs) that were segregating for awn length. In order to identify the causal gene for awn length in the heterozygous inbred families (HIFs), SNPs were called from RNA sequencing (RNA-Seq) data for HIF-derived progenies with long and short awns. SNPs between long and short awn plants were evenly distributed on chromosomes (chr) other than chromosome 5A. SNPs on chr 5A were clustered in a region distal 688 Mb on the long arm, where inhibitor B1 was located. This suggested that B1 was the causal segregating locus. We precisely mapped B1 to ~1 Mb region using two HIF-derived families. Considering that the lines segregated for long, intermediate and short awn phenotypes we speculated that B1 should have a dosage effect on awn length. Two differentially expressed genes (DEGs) located in the candidate region were regarded as candidate genes for B1, because the molecular expression pattern was consistent with the phenotype. HIFs with long and short awns showed no difference on grain yield and other agronomic traits.

Abstract Background Picophytoplankton are abundant and can contribute greatly to primary production in eutrophic lakes. Mychonastes species are among the common eukaryotic picophytoplankton in eutrophic lakes. We used third-generation sequencing technology to sequence the whole genome of Mychonastes homosphaera isolated from Lake Chaohu, a eutrophic freshwater lake in China. Result The 24.23 Mbp nuclear genome of M.homosphaera, harboring 6649 protein-coding genes, is more compact than the genomes of the closely related Sphaeropleales species. This genome streamlining may be caused by a reduction in gene family number, intergenic size and introns. The genome sequence of M.homosphaera reveals the strategies adopted by this organism for environmental adaptation in the eutrophic lake. Analysis of cultures and the protein complement highlight the metabolic flexibility of M.homosphaera, the genome of which encodes genes involved in light harvesting, carbohydrate metabolism, and nitrogen and microelement metabolism, many of which form functional gene clusters. Reconstruction of the bioenergetic metabolic pathways of M.homosphaera, such as the lipid, starch and isoprenoid pathways, reveals characteristics that make this species suitable for biofuel production. Conclusion The analysis of the whole genome of M. homosphaera provides insights into the genome streamlining, the high lipid yield, the environmental adaptation and phytoplankton evolution.

Fully bioresorbable scaffolds have been designed to overcome the limitations of traditional drug-eluting stents (DESs), which permanently cage the native vessel wall and pose possible complications. The ultrathin-strut designed sirolimus-eluting iron bioresorbable coronary scaffold system (IBS) shows comparable mechanical properties to traditional DESs and exhibits an adaptive degradation profile during target vessel healing, which makes it a promising candidate in all-comers patient population. For implanted medical devices, magnetic resonance (MR) imaging properties, including MR safety and compatibility, should be evaluated before its clinical use, especially for devices with intrinsic ferromagnetism. In this study, MR safety and compatibility of the IBS scaffold were evaluated based on a series of well-designed in-vitro, ex-vivo and in-vivo experiments, considering possible risks, including scaffold movement, over-heating, image artifact, and possible vessel injury, under typical MR condition. Traditional ASTM standards for MR safety and compatibility evaluation of intravascular devices were referred, but not only limited to that. The unique time-relevant MR properties of bioresorbable scaffolds were also discussed. Possible forces imposed on the scaffold during MR scanning and MR image artifacts gradually decreased along with scaffold degradation/absorption. Rigorous experiments designed based on a scientifically based rationale revealed that the IBS scaffold is MR conditional, though not MR compatible before complete absorption. The methodology used in the present study can give insight into the MR evaluation of magnetic scaffolds (bioresorbable) or stents (permanent).

Abstract Background The triglyceride and glucose index (TyG) has been proposed as a marker of insulin resistance. This study aims to evaluate the association of the TyG index with the severity and mortality of coronavirus disease 2019 (COVID-19). Methods The study included a cohort of 151 patients with COVID-19 admitted in a tertiary teaching hospital in Wuhan. Regression models were used to investigate the association between TyG with severity and mortality of COVID-19. Results In this cohort, 39 (25.8%) patients had diabetes, 62 (41.1%) patients were severe cases, while 33 (22.0%) patients died in hospital. The TyG index levels were significantly higher in the severe cases and death group (mild vs. severe 8.7 ± 0.6 vs. 9.2 ± 0.6, P

Many diseases are accompanied by changes in certain biochemical indicators called biomarkers in cells or tissues. A variety of biomarkers, including proteins, nucleic acids, antibodies, and peptides, have been identified. Tumor biomarkers have been widely used in cancer risk assessment, early screening, diagnosis, prognosis, treatment, and progression monitoring. For example, the number of circulating tumor cell (CTC) is a prognostic indicator of breast cancer overall survival, and tumor mutation burden (TMB) can be used to predict the efficacy of immune checkpoint inhibitors. Currently, clinical methods such as polymerase chain reaction (PCR) and next generation sequencing (NGS) are mainly adopted to evaluate these biomarkers, which are time-consuming and expansive. Pathological image analysis is an essential tool in medical research, disease diagnosis and treatment, functioning by extracting important physiological and pathological information or knowledge from medical images. Recently, deep learning-based analysis on pathological images and morphology to predict tumor biomarkers has attracted great attention from both medical image and machine learning communities, as this combination not only reduces the burden on pathologists but also saves high costs and time. Therefore, it is necessary to summarize the current process of processing pathological images and key steps and methods used in each process, including: (1) pre-processing of pathological images, (2) image segmentation, (3) feature extraction, and (4) feature model construction. This will help people choose better and more appropriate medical image processing methods when predicting tumor biomarkers.

Over 50% of diffuse large B-cell lymphoma (DLBCL) patients are diagnosed at an advanced stage. Although there are a few therapeutic strategies for DLBCL, most of them are more effective in limited-stage cancer patients. The prognosis of patients with advanced-stage DLBCL is usually poor with frequent recurrence and metastasis. In this study, we aimed to identify gene expression and network differences between limited- and advanced-stage DLBCL patients, with the goal of identifying potential agents that could be used to relieve the severity of DLBCL. Specifically, RNA sequencing data of DLBCL patients at different clinical stages were collected from the cancer genome atlas (TCGA). Differentially expressed genes were identified using DESeq2, and then, weighted gene correlation network analysis (WGCNA) and differential module analysis were performed to find variations between different stages. In addition, important genes were extracted by key driver analysis, and potential agents for DLBCL were identified according to gene-expression perturbations and the Crowd Extracted Expression of Differential Signatures (CREEDS) drug signature database. As a result, 20 up-regulated and 73 down-regulated genes were identified and 79 gene co-expression modules were found using WGCNA, among which, the thistle1 module was highly related to the clinical stage of DLBCL. KEGG pathway and GO enrichment analyses of genes in the thistle1 module indicated that DLBCL progression was mainly related to the NOD-like receptor signaling pathway, neutrophil activation, secretory granule membrane, and carboxylic acid binding. A total of 47 key drivers were identified through key driver analysis with 11 up-regulated key driver genes and 36 down-regulated key diver genes in advanced-stage DLBCL patients. Five genes (MMP1, RAB6C, ACCSL, RGS21 and MOCOS) appeared as hub genes, being closely related to the occurrence and development of DLBCL. Finally, both differentially expressed genes and key driver genes were subjected to CREEDS analysis, and 10 potential agents were predicted to have the potential for application in advanced-stage DLBCL patients. In conclusion, we propose a novel pipeline to utilize perturbed gene-expression signatures during DLBCL progression for identifying agents, and we successfully utilized this approach to generate a list of promising compounds.

Illumina is the leading sequencing platform in the next-generation sequencing (NGS) market globally. In recent years, MGI Tech has presented a series of new sequencers, including DNBSEQ-T7, MGISEQ-2000 and MGISEQ-200. As a complex application of NGS, cancer-detecting panels pose increasing demands for the high accuracy and sensitivity of sequencing and data analysis. In this study, we used the same capture DNA libraries constructed based on the Illumina protocol to evaluate the performance of the Illumina Nextseq500 and MGISEQ-2000 sequencing platforms. We found that the two platforms had high consistency in the results of hotspot mutation analysis; more importantly, we found that there was a significant loss of fragments in the 101–133 bp size range on the MGISEQ-2000 sequencing platform for Illumina libraries, but not for the capture DNA libraries prepared based on the MGISEQ protocol. This phenomenon may indicate fragment selection or low fragment ligation efficiency during the DNA circularization step, which is a unique step of the MGISEQ-2000 sequence platform. In conclusion, these different sequencing libraries and corresponding sequencing platforms are compatible with each other, but protocol and platform selection need to be carefully evaluated in combination with research purpose.

BackgroundPrevious studies showed altered angiopoietin-like protein-8 (ANGPTL-8) and resistin circulating levels in type 2 diabetes mellitus (T2DM). Whether or not the alteration in ANGPTL-8 and resistin level can be a predictive maker for increased diabetic nephropathy risk remains unclear.AimTo Investigate the possible association of ANGPTL-8 and resistin with DN, and whether this association is affected by NAFLD status.MethodsA total of 278 T2DM patients were enrolled. Serum levels of ANGPTL8, resistin, BMI, blood pressure, duration of diabetes, glycosylated hemoglobin (HbA1c), fasting blood glucose (FPG), hypersensitive C-reactive protein (hs-CRP), lipid profile, liver, and kidney function tests were assessed. The relationship between DN with ANGPTL8 and resistin was analyzed in the unadjusted and multiple-adjusted regression models.ResultsSerum levels of ANGPTL8 and resistin were significantly higher in DN compared with T2DM subjects without DN (respectively; P 0.05). Analysis showed ANGPTL8 levels were positively associated with resistin but only in T2DM patients with DN(r=0.1867; P

Objectives: COVID-19 is highly infectious and has been widely spread worldwide, with more than 159 million confirmed cases and more than 3 million deaths as of May 11, 2021. It has become a serious public health event threatening people’s lives and safety. Due to the rapid transmission and long incubation period, shortage of medical resources would easily occur in the short term of discovering disease cases. Therefore, we aimed to construct an artificial intelligent framework to rapidly distinguish patients with COVID-19 from common pneumonia and non-pneumonia populations based on computed tomography (CT) images. Furthermore, we explored artificial intelligence (AI) algorithms to integrate CT features and laboratory findings on admission to predict the clinical classification of COVID-19. This will ease the burden of doctors in this emergency period and aid them to perform timely and appropriate treatment on patients.Methods: We collected all CT images and clinical data of novel coronavirus pneumonia cases in Inner Mongolia, including domestic cases and those imported from abroad; then, three models based on transfer learning to distinguish COVID-19 from other pneumonia and non-pneumonia population were developed. In addition, CT features and laboratory findings on admission were combined to predict clinical types of COVID-19 using AI algorithms. Lastly, Spearman’s correlation test was applied to study correlations of CT characteristics and laboratory findings.Results: Among three models to distinguish COVID-19 based on CT, vgg19 showed excellent diagnostic performance, with area under the curve (AUC) of the receiver operating characteristic (ROC) curve at 95%. Together with laboratory findings, we were able to predict clinical types of COVID-19 with AUC of the ROC curve at 90%. Furthermore, biochemical markers, such as C-reactive protein (CRP), LYM, and lactic dehydrogenase (LDH) were identified and correlated with CT features.Conclusion: We developed an AI model to identify patients who were positive for COVID-19 according to the results of the first CT examination after admission and predict the progression combined with laboratory findings. In addition, we obtained important clinical characteristics that correlated with the CT image features. Together, our AI system could rapidly diagnose COVID-19 and predict clinical types to assist clinicians perform appropriate clinical management.

The North China Plain (NCP) has the largest groundwater depletion in the world, and it is also the major production area of winter wheat in China. For sustainable food production and sustainable use of irrigated groundwater, it is necessary to optimize the irrigation amount for winter wheat in the NCP. Previous studies on the optimal irrigation amount have less consideration of the groundwater constraint, which may result in the theoretical amount of optimal-irrigation exceeding the amount of regional irrigation availability. Based on the meteorological data, soil data, crop variety data, and field management data from field experimental stations of Tangshan, Huanghua, Luancheng, Huimin, Nangong, Ganyu, Shangqiu, Zhumadian and Shouxian, we simulated the variation of yield and water use efficiency (WUE) under different irrigation levels by using the CERES-Wheat model, and investigated the optimal irrigation amount for high yield (OIy), water saving (OIWUE), and the trade-off between high yield and water saving (OIt) of winter wheat in the NCP. Based on the water balance theory, we then calculated the irrigation availability, which was taken as the constraint to explore the optimal irrigation amount for winter wheat in the NCP. The results indicated that the OIy ranged from 80 mm to 240 mm, and the OIWUE was 17% to 67% less than OIy, ranging from 0 mm to 200 mm. The OIt was between 80 mm and 240 mm, realizing the co-benefits of high yield and water saving. Finally, we determined the optimal irrigation amount (62–240 mm) by the constraint of irrigation availability. Our results can provide a realistic and scientific reference for the security of both grain production and groundwater use in the NCP.

Idiopathic pulmonary fibrosis is a fatal interstitial disease characterized by fibroblast proliferation and differentiation and abnormal accumulation of extracellular matrix, with high mortality and an increasing annual incidence. Since few drugs are available for the treatment of pulmonary fibrosis, there is an urgent need for high-efficiency therapeutic drugs and treatment methods to reduce the mortality associated with pulmonary fibrosis. The interstitium, a highly efficient transportation system that pervades the body, plays an important role in the occurrence and development of disease, and can be used as a new route for disease diagnosis and treatment. In this study, we evaluated the administration of hydroxysafflor yellow A phytosomes via intervaginal space injection (ISI) as an anti-pulmonary fibrosis treatment. Our results show that this therapeutic strategy blocked the activation of p38 protein in the MAPK-p38 signaling pathway and inhibited the expression of Smad3 protein in the TGF-β/Smad signaling pathway, thereby reducing secretion of related inflammatory factors, deposition of collagen in the lungs of mice, and destruction of the alveolar structure. Use of ISI in the treatment of pulmonary fibrosis provides a potential novel therapeutic modality for the disease.

Grain yield (GY) and grain protein content (GPC) are important traits for wheat breeding and production; however, they are usually negatively correlated. The Q gene is the most important domestication gene in cultivated wheat because it influences many traits, including GY and GPC. Allelic variations in the Q gene may positively affect both GY and GPC. Accordingly, we characterized two new Q alleles (Qs1 and Qc1-N8) obtained through ethyl methanesulfonate-induced mutagenesis. Compared with the wild-type Q allele, Qs1 contains a missense mutation in the sequence encoding the first AP2 domain, whereas Qc1-N8 has two missense mutations: one in the sequence encoding the second AP2 domain and the other in the microRNA172-binding site. The Qs1 allele did not significantly affect GPC or other processing quality parameters, but it adversely affected GY by decreasing the thousand kernel weight and grain number per spike. In contrast, Qc1-N8 positively affected GPC and GY by increasing the thousand kernel weight and grain number per spike. Thus, we generated novel germplasm relevant for wheat breeding. A specific molecular marker was developed to facilitate the use of the Qc1-N8 allele in breeding. Furthermore, our findings provide useful new information for enhancing cereal crops via non-transgenic approaches.

Talent is an important strategic resource for regional economic development. Based on the background of “the talent war” that has broken out between various cities in recent years, this study empirically verified the influence of the talent policy on urban innovation in 277 prefecture-level cities in China from 2010 to 2019 using the multi-period difference-in-differences model. The results indicated that “the talent war” caused by the talent policy has positively influenced urban innovation, causing, for instance, a dramatic increase in the number of patents for inventions. Among the subsidy methods of “the talent war” policy, the employment and entrepreneurship subsidy had the greatest incentive effect on urban innovation, followed by the talent housing subsidy. Moreover, the “the talent war” policy exerted a positive impact on urban innovation by improving the innovation willingness of cities and the level of talent gathering. At present, “the talent war” cities have, to a certain extent, restrained the improvement of urban innovation in neighboring cities because of the siphon effect, resulting in the division of the regional labor market. A heterogeneity analysis showed that “the talent war” has significantly promoted substantive innovation and the development of coastal cities with a better business environment and a higher degree of intellectual property protection.