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Abstract Background The cranial-caudal-medial approach (CCMA) has been proposed for laparoscopic right hemicolectomy nowadays. This study aimed to investigate the safety and oncological efficacy of CCMA in the treatment of right-sided colon cancer compared to the medial–lateral approach (MLA). Methods Patients diagnosed with right-sided colon cancer were included from February 2015 to June 2018, retrospectively, dividing into the CCMA group and the MLA group. We compared the basic characteristics and the short-term and long-term outcomes in two groups. Results Two hundred and ninety-six patients were included in this study. The baseline characteristics were similar in two groups. Compared with MLA group, CCMA group exhibited shorter operation time (136.3 ± 25.3 min vs. 151.6 ± 21.5 min, P

Abstract Background Diabetic neuropathy (DN), a frequent complication in individuals with diabetes mellitus (DM), is hypothesized to have a correlation with systemic iron status, though the nature of this relationship remains unclear. This study employs two-sample Mendelian randomization (MR) analysis to explore this potential genetic association. Methods We used genetic instruments significant associated with iron status including serum iron, ferritin, transferrin, and transferrin saturation, derived from an extensive Genome-Wide Association Study (GWAS) undertaken by the Genetics of Iron Status Consortium, involving a cohort of 48,972 European ancestry individuals. Summary statistics for DN were collected from a public GWAS, including 1,415 patients and 162,201 controls of European descent. Our MR analysis used the inverse-variance-weighted (IVW) method, supplemented by MR-Egger, weighted-median (WM) methods, Cochran’s Q test, MR-Egger intercept analysis, MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) method, and leave-one-out analysis to ensure robustness and consistency of the findings. Results No genetic causal relationship was found between iron status markers and DN (all IVW p value > 0.05). Interestingly, a causative effect of DN on ferritin (IVW: OR = 0.943, 95% CI = 0.892–0.996, p = 0.035) and transferrin saturation (IVW: OR = 0.941, 95% CI = 0.888–0.998, p = 0.044) emerged. Sensitivity analyses confirmed the absence of significant heterogeneity and horizontal pleiotropy. Conclusion While systemic iron status was not found to be causally related to DN, our findings suggest that DN may increase the risk of iron deficiency. These results provide further evidence supporting iron supplementation in patients with DN.

Abstract Background The experiences and challenges associated with breastfeeding multiple births can be considerably more complex than those of singletons. Multiple births refer to the delivery of more than one offspring in a single birth event. Emphasizing the needs and experiences of mothers with multiple births during breastfeeding can enable healthcare providers to design targeted interventions that enhance breastfeeding rates. However, existing breastfeeding and health education resources and practices do not fully meet the needs of women who breastfeed multiples. This review aimed to review and synthesize qualitative studies on the breastfeeding experiences of women with multiple births. Methods A systematic search was conducted in 10 electronic databases for papers published from the inception of the database to March 2024. The Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research was utilized to evaluate the methodological quality of the studies included. The thematic synthesis method of Thomas and Harden was employed to integrate and analyze the included literature to derive new categories and conclusions. Findings Eight studies met the inclusion criteria and quality assessment criteria for this study. Through the integration of their results, four themes were identified: the choice and willingness to breastfeed multiple births; the challenges of breastfeeding multiple births; stage management and individualised adaptation of breastfeeding; and the experience of support. Conclusion Throughout the feeding process from pregnancy to the postpartum period, mothers with multiple births often have predominantly negative experiences with breastfeeding. Consequently, hospitals should create a multidisciplinary follow-up team comprising obstetrics, neonatology, psychology, and community services to offer specialized and personalized support to these women at various stages. Systematic review registration [ https://www.crd.york.ac.uk/PROSPERO/ ], identifier [PROSPERO 2024 CRD42024520348].

Abstract Background Results regarding whether it is essential to incorporate genetic variants into risk prediction models for esophageal cancer (EC) are inconsistent due to the different genetic backgrounds of the populations studied. We aimed to identify single-nucleotide polymorphisms (SNPs) associated with EC among the Chinese population and to evaluate the performance of genetic and non-genetic factors in a risk model for developing EC. Methods A meta-analysis was performed to systematically identify potential SNPs, which were further verified by a case-control study. Three risk models were developed: a genetic model with weighted genetic risk score (wGRS) based on promising SNPs, a non-genetic model with environmental risk factors, and a combined model including both genetic and non-genetic factors. The discrimination ability of the models was compared using the area under the receiver operating characteristic curve (AUC) and the net reclassification index (NRI). The Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to assess the goodness-of-fit of the models. Results Five promising SNPs were ultimately utilized to calculate the wGRS. Individuals in the highest quartile of the wGRS had a 4.93-fold (95% confidence interval [CI]: 2.59 to 9.38) increased risk of EC compared with those in the lowest quartile. The genetic or non-genetic model identified EC patients with AUCs ranging from 0.618 to 0.650. The combined model had an AUC of 0.707 (95% CI: 0.669 to 0.743) and was the best-fitting model (AIC = 750.55, BIC = 759.34). The NRI improved when the wGRS was added to the risk model with non-genetic factors only (NRI = 0.082, P = 0.037). Conclusions Among the three risk models for EC, the combined model showed optimal predictive performance and can help to identify individuals at risk of EC for tailored preventive measures.

Abstract Background Macrophages are key inflammatory immune cells that orchestrate the initiation and progression of autoimmune diseases. The characters of macrophage in diseases are determined by its phenotype in response to the local microenvironment. Ficolins have been confirmed as crucial contributors to autoimmune diseases, with Ficolin-2 being particularly elevated in patients with autoimmune diseases. However, whether Ficolin-A stimulates macrophage polarization is still poorly understood. Methods We investigated the transcriptomic expression profile of murine bone marrow-derived macrophages (BMDMs) stimulated with Ficolin-A using RNA-sequencing. To further confirm a distinct phenotype activated by Ficolin-A, quantitative RT-PCR and Luminex assay were performed in this study. Additionally, we assessed the activation of underlying cell signaling pathways triggered by Ficolin-A. Finally, the impact of Ficolin-A on macrophages were investigated in vivo through building Collagen-induced arthritis (CIA) and Dextran Sulfate Sodium Salt (DSS)-induced colitis mouse models with Fcna-/- mice. Results Ficolin-A activated macrophages into a pro-inflammatory phenotype distinct to LPS-, IFN-γ- and IFN-γ + LPS-induced phenotypes. The transcriptomic profile induced by Ficolin-A was primarily characterized by upregulation of interleukins, chemokines, iNOS, and Arginase 1, along with downregulation of CD86 and CD206, setting it apart from the M1 and M2 phenotypes. The activation effect of Ficolin-A on macrophages deteriorated the symptoms of CIA and DSS mouse models, and the deletion of Fcna significantly alleviated the severity of diseases in mice. Conclusion Our work used transcriptomic analysis by RNA-Seq to investigate the impact of Ficolin-A on macrophage polarization. Our findings demonstrate that Ficolin-A induces a novel pro-inflammatory phenotype distinct to the phenotypes activated by LPS, IFN-γ and IFN-γ + LPS on macrophages.

Abstract The purpose of this study was to identify novel autoantibodies against tumor-associated antigens (TAAs) and explore a diagnostic panel for Ovarian cancer (OC). Enzyme-linked immunosorbent assay was used to detect the expression of five anti-TAA autoantibodies in the discovery (70 OC and 70 normal controls) and validation cohorts (128 OC and 128 normal controls). Machine learning methods were used to construct a diagnostic panel. Serum samples from 81 patients with benign ovarian disease were used to identify the specificity of anti-TAA autoantibodies for OC. In both the discovery and validation cohorts, the expression of anti-CFL1, anti-EZR, anti-CYPA, and anti-PFN1 was higher in patients with OC than that in normal controls. The area under the receiver operating characteristic curve, sensitivity, and specificity of the panel containing anti-CFL1, anti-EZR, and anti-CYPA were 0.762, 55.56%, and 81.31%. The panel identified 53.06%, 53.33%, and 51.11% of CA125 negative, HE4 negative and the Risk of Ovarian Malignancy Algorithm negative OC patients, respectively. The combination of the three anti-TAA autoantibodies can serve as a favorable diagnostic tool for OC and has the potential to be a complementary biomarker for CA125 and HE4 in the diagnosis of ovarian cancer.

Abstract Background Combining conventional radiomics models with deep learning features can result in superior performance in predicting the prognosis of patients with tumors; however, this approach has never been evaluated for the prediction of metachronous distant metastasis (MDM) among patients with retroperitoneal leiomyosarcoma (RLS). Thus, the purpose of this study was to develop and validate a preoperative contrast-enhanced computed tomography (CECT)-based deep learning radiomics model for predicting the occurrence of MDM in patients with RLS undergoing complete surgical resection. Methods A total of 179 patients who had undergone surgery for the treatment of histologically confirmed RLS were retrospectively recruited from two tertiary sarcoma centers. Semantic segmentation features derived from a convolutional neural network deep learning model as well as conventional hand-crafted radiomics features were extracted from preoperative three-phase CECT images to quantify the sarcoma phenotypes. A conventional radiomics signature (RS) and a deep learning radiomics signature (DLRS) that incorporated hand-crafted radiomics and deep learning features were developed to predict the risk of MDM. Additionally, a deep learning radiomics nomogram (DLRN) was established to evaluate the incremental prognostic significance of the DLRS in combination with clinico-radiological predictors. Results The comparison of the area under the curve (AUC) values in the external validation set, as determined by the DeLong test, demonstrated that the integrated DLRN, DLRS, and RS models all exhibited superior predictive performance compared with that of the clinical model (AUC 0.786 [95% confidence interval 0.649–0.923] vs. 0.822 [0.692–0.952] vs. 0.733 [0.573–0.892] vs. 0.511 [0.359–0.662]; both P

Abstract Single-particle cryo-EM is widely used to determine enzyme-nucleosome complex structures. However, cryo-EM sample preparation remains challenging and inconsistent due to complex denaturation at the air-water interface (AWI). Here, to address this issue, we develop graphene-oxide-coated EM grids functionalized with either single-stranded DNA (ssDNA) or thiol-poly(acrylic acid-co-styrene) (TAASTY) co-polymer. These grids protect complexes between the chromatin remodeler SNF2h and nucleosomes from the AWI and facilitate collection of high-quality micrographs of intact SNF2h-nucleosome complexes in the absence of crosslinking. The data yields maps ranging from 2.3 to 3 Å in resolution. 3D variability analysis reveals nucleotide-state linked conformational changes in SNF2h bound to a nucleosome. In addition, the analysis provides structural evidence for asymmetric coordination between two SNF2h protomers acting on the same nucleosome. We envision these grids will enable similar detailed structural analyses for other enzyme-nucleosome complexes and possibly other protein-nucleic acid complexes in general.

Abstract Owing to the advancement of interdisciplinary concepts, for example, wearable electronics, bioelectronics, and intelligent sensing, during the microelectronics industrial revolution, nowadays, extensively mature wearable sensing devices have become new favorites in the noninvasive human healthcare industry. The combination of wearable sensing devices with bionics is driving frontier developments in various fields, such as personalized medical monitoring and flexible electronics, due to the superior biocompatibilities and diverse sensing mechanisms. It is noticed that the integration of desired functions into wearable device materials can be realized by grafting biomimetic intelligence. Therefore, herein, the mechanism by which biomimetic materials satisfy and further enhance system functionality is reviewed. Next, wearable artificial sensory systems that integrate biomimetic sensing into portable sensing devices are introduced, which have received significant attention from the industry owing to their novel sensing approaches and portabilities. To address the limitations encountered by important signal and data units in biomimetic wearable sensing systems, two paths forward are identified and current challenges and opportunities are presented in this field. In summary, this review provides a further comprehensive understanding of the development of biomimetic wearable sensing devices from both breadth and depth perspectives, offering valuable guidance for future research and application expansion of these devices.

Abstract This study investigates the antimicrobial effectiveness of 405 nm light emitting diodes (LEDs) against pathogenic Escherichia coli O157:H7, Listeria monocytogenes, Pseudomonas aeruginosa, Salmonella Typhimurium, and Staphylococcus aureus, in thin liquid films (TLF) and on solid surfaces. Stainless steel (SS), high density polyethylene (HDPE), low density polyethylene (LDPE), and borosilicate glass were used as materials typically encountered in food processing, food service, and clinical environments. Anodic aluminum oxide (AAO) coupons with nanoscale topography were used, to evaluate the effect of topography on inactivation. The impact of surface roughness, hydrophobicity, and reflectivity on inactivation was assessed. A 48 h exposure to 405 nm led to reductions ranging from 1.3 (E. coli) to 5.7 (S. aureus) log CFU in TLF and 3.1 to 6.3 log CFU on different solid contact surfaces and packaging materials. All inactivation curves were nonlinear and followed Weibull kinetics, with better inactivation predictions on surfaces (0.89 ≤ R 2 ≤ 1.0) compared to TLF (0.76 ≤ R 2 ≤ 0.99). The fastest inactivation rate was observed on small nanopore AAO coupons inoculated with L. monocytogenes and S. aureus, indicating inactivation enhancing potential of these surfaces. These results demonstrate significant promise of 405 nm LEDs for antimicrobial applications in food processing and handling and the healthcare industry.

Abstract The dual functions of TMEM16F as Ca2+-activated ion channel and lipid scramblase raise intriguing questions regarding their molecular basis. Intrigued by the ability of the FDA-approved drug niclosamide to inhibit TMEM16F-dependent syncytia formation induced by SARS-CoV-2, we examined cryo-EM structures of TMEM16F with or without bound niclosamide or 1PBC, a known blocker of TMEM16A Ca2+-activated Cl- channel. Here, we report evidence for a lipid scrambling pathway along a groove harboring a lipid trail outside the ion permeation pore. This groove contains the binding pocket for niclosamide and 1PBC. Mutations of two residues in this groove specifically affect lipid scrambling. Whereas mutations of some residues in the binding pocket of niclosamide and 1PBC reduce their inhibition of TMEM16F-mediated Ca2+ influx and PS exposure, other mutations preferentially affect the ability of niclosamide and/or 1PBC to inhibit TMEM16F-mediated PS exposure, providing further support for separate pathways for ion permeation and lipid scrambling.

Background: Due to its non-invasive and widely applicable features, photodynamic therapy (PDT) has been a prominent treatment approach against cancer in recent years. However, its widespread application in clinical practice is limited by the dark toxicity of photosensitizers and insufficient penetration of light sources. This study assessed the anticancer effects of a novel photosensitizer 5-(4-amino-phenyl)-10,15,20-triphenylporphyrin with diethylene-triaminopentaacetic acid (ATPP-DTPA)-mediated PDT (hereinafter referred to as ATPP-PDT) under the irradiation of a 450-nm blue laser on colorectal cancer (CRC) in vivo and in vitro. Methods: After 450-nm blue laser-mediated ATPP-PDT and the traditional photosensitizer 5-aminolevulinic acid (5-ALA)-PDT treatment, cell viability was detected through Cell Counting Kit-8 (CCK-8) and 5-ethynyl-2′-deoxyuridine (EdU) assays. Reactive oxygen species (ROS) generation was quantified by flow cytometry and fluorescence microscopy. Western blotting and transcriptome RNA sequencing and functional experiments were used to evaluate cell apoptosis and its potential mechanism. Anti-tumor experiment in vivo was performed in nude mice with subcutaneous tumors. Results: ATPP-DTPA had a marvelous absorption in the blue spectrum. Compared with 5-ALA, ATPP-DTPA could achieve significant killing effects at a lower dose. Owing to generating an excessive amount of ROS, 450-nm blue laser-mediated PDT based on ATPP-DTPA resulted in evident growth inhibition and apoptosis in CRC cells in vitro. After transcriptome RNA sequencing and functional experiments, p38 MAPK signaling pathway was confirmed to be involved in the regulation of apoptosis induced by 450-nm blue laser-mediated ATPP-PDT. Additionally, animal studies using xenograft model confirmed that ATPP-PDT had excellent anti-tumor effect and reasonable biosafety in vivo. Conclusions: PDT mediated by 450-nm blue laser combined with ATPP-DTPA may be a novel and effective method for the treatment of CRC.

Microbial communities are not only an important indicator of soil status but also a determinant of plant nutrition and health levels. Loss of microbial community ecosystem control can directly lead to microbial disease occurrence. During the process of Yuanyang Nanqi wild imitation planting, root rot diseases frequently occur, seriously affecting their yield and quality. Via amplicon sequencing, this study mainly compared the microbial community composition between the rhizosphere soil and roots of healthy and diseased Yuanyang Nanqi with root rot. The α-diversity showed that the microbial community diversity and abundance in the roots of diseased Yuanyang Nanqi were much lower than those of those in healthy specimens, while no significant difference was found in the rhizosphere soil. The β-diversity showed that the bacterial community in the Gejiu region and the fungal community in the Honghe region were significantly different from those in other regions. The species relative abundance map showed that there was no obvious difference in microbial community composition between the rhizosphere soil and roots of healthy and diseased Nanqi, but in diseased specimens with root rot, the proportions of Pseudomonas and Fusarium increased. Based on a functional prediction analysis of FUNGuild, the results showed that the Nanqi roots were mainly pathological saprophytic type and that their rhizosphere soil was mainly saprophytic type. The microorganisms in the roots of Yuanyang Nanqi tubers with root rot were also isolated and identified through the use of the culture method. The possible pathogenic strains were tested via anti-inoculation, and Fusarium oxysporum was identified as one of the main pathogenic fungi of Nanqi root rot, which was consistent with the amplicon sequencing results. These results will help us understand the change trend of microbial communities in healthy and diseased plants and analyze the pathogens involved, the pathogenesis, and the beneficial microorganisms, which would provide a theoretical basis for effective biological control.

This research examines the behavior of electrochemical passivation and the chemistry of surface films on 654SMO super austenitic stainless steel and C276 nickel-based alloy in simulated condensates from flue gas desulfurization in power plant chimneys. The findings indicate that the resistance to polarization of the protective film on both materials initially rises and then falls with either time spent in the solution or the potential of anodic polarization. Comparatively, 654SMO exhibits greater polarization resistance than C276, indicating its potential suitability as a chimney lining material. Mott–Schottky analysis demonstrates that the density of donors in the passive film formed on 654SMO exceeds that on C276, potentially due to the abundance of Fe oxide in the passive film, which exhibits the characteristics of an n-type semiconductor. The primary components of the passive films on both materials are Fe oxides and Cr oxides. The formation of a thin passive film on C276 in the simulated condensates is a result of the low Gibbs free energy of nickel oxide and low Cr content. The slower diffusion coefficient of point defects leads to the development of a thicker and more compact passive film on the surface of 654SMO.

Abstract Purpose This study aims to evaluate the pain relief function of chemical sphincterotomy in patients undergoing haemorrhoid surgery and compare, through a meta-analysis, the different drugs used to treat this condition. Methods We conducted a search in databases including PubMed, EMBASE and Web of Science. The methodological quality was evaluated using the Revised Cochrane risk-of-bias tool for randomized trials (ROB2). The pain score was assessed using a visual analogue scale (VAS) on day 1, day 2, and day 7, and a meta-analysis was conducted based on the use of random effects models. In addition, the subgroup analysis was evaluated based on the kind of experimental drugs. Heterogeneity and publication bias were assessed. Results Fourteen studies with a total of 681 patients were included in this meta-analysis, and all studies were randomized controlled trials RCTs. Chemical sphincterotomy showed better pain relief function than placebo on day 1 (SMD: 1.16, 95% CI 0.52 to 1.80), day 2 (SMD: 2.12, 95% CI 1.37 to 2.87) and day 7 (SMD: 1.97, 95% CI 1.17 to 2.77) after surgery. In the subgroup meta-analysis, we found that different drugs for chemical sphincterotomy provided different pain relief. Conclusion Chemical sphincterotomy effectively relieves pain after haemorrhoidectomy, and calcium channel blockers have the best effect.

Summary: This study investigates stress’s impact on Alzheimer’s disease (AD) using male APP/PS1 transgenic mice. Negative stressors (chronic social defeat, restraint) and positive hedonia (environmental enrichment, EE) were applied. Stress worsens AD pathology, while EE slows progression. Brain RNA sequencing reveals interleukin-6 (IL-6) and IL-10 as key stress-related AD regulators. Flow cytometry shows that the CD8+/CD4+ T cell ratio shifts in response to stress exposure and EE. Stress exposure increases CD8+/CD4+ ratio, opposite to EE. Depletion and enrichment of CD8+ T cells both accelerate AD, indicating immune intervention’s negative impact. Stress management and balanced immunity may aid AD therapy, highlighting novel potential treatment.

Abstract Background We evaluated the value of electrophysiological indicators by external anal sphincter electromyography (EAS-EMG), sympathetic skin response (SSR), R-R interval variation (RRIV), and Bulbocavernosus Reflex (BCR) in differential diagnosis of multiple system atrophy (MSA) and Parkinson’s disease (PD). Methods A total of 41 patients with MSA and 32 patients with PD were enrolled. The electrophysiological changes of autonomic dysfunction were assessed with BCR, EAS-EMG, SSR, and RRIV, and the abnormal rate of each indicator was calculated. The diagnostic value of each indicator was analyzed with ROC curve. Results The incidence rate of autonomic dysfunction in MSA group was significantly higher than that in PD group (p 0.05). The sensitivity of BCR combined with EAS-EMG indicators in differential diagnosis of MSA and PD were 92.3% in males and 86.7% in females, respectively, and the specificity was 72.7% in males and 90% in females, respectively. Conclusions Combined analysis of BCR and EAS-EMG has high sensitivity and specificity for differential diagnosis of MSA and PD.

To protect from host attack, numerous jumbo bacteriophages establish a micron-scale, protein-based structure to enclose their replicating DNA. Using cryoEM, the authors show that the 2D crystal enclosing this so-called phage nucleus is an assembly of tetramers linked by flexible loops and tails.

This paper deals with a new Bayesian approach to the one-sample test for proportion. More specifically, let x=(x1,…,xn) be an independent random sample of size n from a Bernoulli distribution with an unknown parameter θ. For a fixed value θ0, the goal is to test the null hypothesis H0:θ=θ0 against all possible alternatives. The proposed approach is based on using the well-known formula of the Kullback–Leibler divergence between two binomial distributions chosen in a certain way. Then, the difference of the distance from a priori to a posteriori is compared through the relative belief ratio (a measure of evidence). Some theoretical properties of the method are developed. Examples and simulation results are included.

Current mesenchymal stem cell (MSC) transplantation practices are limited by the loss or reduced performance of MSCs. Here the authors develop a bead-jet printer for intraoperative formulation and printing of MSCs-laden Matrigel beads to improve skeletal muscle and hair follicle regeneration.

Here, Zhang et al. explore fusion protein strategies to facilitate cryo-EM structural studies of GPCRs alone- without signal transducers- in ligand bound or unliganded form.

Accurate recognition of the canopy is a prerequisite for precision orchard yield estimation. This paper proposed an enhanced LA-dpv3+ approach for the recognition of cherry canopies based on UAV image data, with a focus on enhancing feature representation through the implementation of an attention mechanism. The attention mechanism module was introduced to the encoder stage of the DeepLabV3+ architecture, which improved the network’s detection accuracy and robustness. Specifically, we developed a diagonal discrete cosine transform feature strategy within the attention convolution module to extract finer details of canopy information from multiple frequency components. The proposed model was constructed based on a lightweight DeepLabv3+ network architecture that incorporates a MobileNetv2 backbone, effectively reducing computational costs. The results demonstrate that our proposed method achieved a balance between computational cost and the quality of results when compared to competing approaches. Our model’s accuracy exceeded 89% while maintaining a modest model size of only 46.8 MB. The overall performance indicated that with the help of a neural network, segmentation failures were notably reduced, particularly in high-density weed conditions, resulting in significant increases in accuracy (ACC), F1-score, and intersection over union (IOU), which were increased by 5.44, 3.39, and 8.62%, respectively. The method proposed in this paper may be applied to future image-based applications and contribute to automated orchard management.

Abstract In the last few decades, YAP has been shown to be critical in regulating tumor progression. YAP activity can be regulated by many kinase cascade pathways and proteins through phosphorylation and promotion of cytoplasmic localization. Other factors can also affect YAP activity by modulating its binding to different transcription factors (TFs). Programmed cell death (PCD) is a genetically controlled suicide process present with the scope of eliminating cells unnecessary or detrimental for the proper development of the organism. In some specific states, PCD is activated and facilitates the selective elimination of certain types of tumor cells. As a candidate oncogene correlates with many regulatory factors, YAP can inhibit or induce different forms of PCD, including apoptosis, autophagy, ferroptosis and pyroptosis. Furthermore, YAP may act as a bridge between different forms of PCD, eventually leading to different outcomes regarding tumor development. Researches on YAP and PCD may benefit the future development of novel treatment strategies for some diseases. Therefore, in this review, we provide a general overview of the cellular functions of YAP and the relationship between YAP and PCD.

Untethered synthetic microrobots have significant potential to revolutionize biomedical interventions therapy in the future. However, the relatively slow speed of microrobots and viscosity biofluid environments are some of barriers standing in the way of microrobots’ biomedical applications. Herein, inspired by high‐speed biological escape propulsion, NIR‐driven microrobots with a high‐speed, unidirectional propulsion in the high‐viscosity liquid are proposed. The bubble's growth and ejection cause the proposed 3D‐printed microrobot to propel forward. The 3D‐printed claw‐like microrobot achieves motion average speed of 1.4 mm s−1 (three‐body length (bl) s−1) when driven by NIR light in a pure glycerol viscous (945 mPa s, 25 °C) environment, which has a viscosity that is more than 200 times the viscosity of blood and of 54 mm s−1 (120 bl s−1) when driven by NIR light in deionized (DI) water. This work provides more ideas for the design and propulsion of light‐driven microrobots in a high‐viscosity vivo environment, which may broaden the applications of microrobots in the biomedical field, such as propulsion and navigation in confined and hard‐to‐reach body location areas.

The tea yield estimation provides information support for the harvest time and amount and serves as a decision-making basis for farmer management and picking. However, the manual counting of tea buds is troublesome and inefficient. To improve the efficiency of tea yield estimation, this study presents a deep-learning-based approach for efficiently estimating tea yield by counting tea buds in the field using an enhanced YOLOv5 model with the Squeeze and Excitation Network. This method combines the Hungarian matching and Kalman filtering algorithms to achieve accurate and reliable tea bud counting. The effectiveness of the proposed model was demonstrated by its mean average precision of 91.88% on the test dataset, indicating that it is highly accurate at detecting tea buds. The model application to the tea bud counting trials reveals that the counting results from test videos are highly correlated with the manual counting results (R2 = 0.98), indicating that the counting method has high accuracy and effectiveness. In conclusion, the proposed method can realize tea bud detection and counting in natural light and provides data and technical support for rapid tea bud acquisition.

PurposeTo study the status quo of the cognitive function of the breast cancer patients with (who went through) the endocrine therapy by the epidemiological investigation, analyze the key factor of the cognition impairment and explore the impact of the endocrine therapy time on the cognition decline after using Propensity Score Matching to balance the covariates.MethodsIn this study, the epidemiological questionnaire information was collected from 226 female breast cancer endocrine treatment patients who visited the Breast Clinic of Longhua Hospital Affiliated to Shanghai University of Chinese Medicine from November 2020 to February 2022, and the results of the overall cognitive function, the function test of each cognitive domain, the patient’s self-cognition, quality of life, and emotional status evaluation of the patients. In this study, according to the principle of random matching, the nearest matching method with a matching tolerance of 0.2 and a matching ratio of 1:2 was used for orientation score matching. After the covariant such as age, BMI, and duration of education were balanced, the effects of the duration of endocrine therapy on the overall cognitive function and the functions of each cognitive domain were analyzed.ResultsIn 226 cases of female breast cancer patients (who went through) the endocrine therapy, the propensity score matching was performed, ultimately, 99 were ruled out, successful matched ones were 49 of the cognition-decline group and 78 of the standard group. With age, education time, BMI and other covariates balanced, the endocrine therapy duration was the risk factor of the cognition impairment (P < 0.05, OR = 1.296, 95% CI = 1.008−1.665), with the extension of endocrine treatment time, there was a rising risk of the cognition impairment (LLA statistic = 5.872, P < 0.05). The cognitive domain scores in the cognition-decline group were lower than the standard group (P < 0.05), but there was a difference in self-report cognition.ConclusionThe endocrine therapy duration was the risk factor for the cognition impairment of the breast cancer patients, and with prolonged endocrine treatment, there was a rising (an increasing) risk for the cognition impairment.

Abstract The role of PLAC8 in tumorigenesis has been gradually elucidated with the development of research. Although there are common molecular mechanisms that enforce cell growth, the impact of PLAC8 is varied and can, in some instances, have opposite effects on tumorigenesis. To systematically understand the role of PLAC8 in tumors, the molecular functions of PLAC8 in cancer will be discussed by focusing on how PLAC8 impacts tumorigenesis when it arises within tumor cells and how these roles can change in different stages of cancer progression with the ultimate goal of suppressing PLAC8-relevant cancer behavior and related pathologies. In addition, we highlight the diversity of PLAC8 in different tumors and its functional output beyond cancer cell growth. The comprehension of PLAC8’s molecular function might provide new target and lead to the development of novel anticancer therapies.

Background Triple-negative breast cancer is characterized by a poor prognosis and lack of targeted treatments, and thus, new targeting markers and therapeutic strategies are urgently needed. We previously indicated that PLAC8 promotes tumorigenesis and exerts multidrug resistance in breast cancer. Therefore, we aimed to characterize the PLAC8-regulated network in triple-negative breast cancer.Methods We measured the levels of PLAC8 in breast cancer cell lines and found that PLAC8 is post-translationally modified by ubiquitin-fold modifier 1 (UFM1). Then, we revealed a new regulatory system of PD-L1 by PLAC8 in triple-negative breast cancer. We also tested the molecular functions of PLAC8 in triple-negative breast cancer cell lines and measured the expression of PLAC8 and PD-L1 in breast cancer tissues.Results PLAC8 was generally highly expressed in triple-negative breast cancer and could be modified by UFM1, which maintains PLAC8 protein stability. Moreover, PLAC8 could promote cancer cell proliferation and affect the immune response by regulating the level of PD-L1 ubiquitination. Additionally, among patients with breast cancer, the expression of PLAC8 was higher in triple-negative breast cancer than in non-triple-negative breast cancer and positively correlated with the level of PD-L1.Conclusions Our current study discoveries a new PLAC8-regulated network in triple-negative breast cancer and provides corresponding guidance for the clinical diagnosis and immunotherapy of triple-negative breast cancer.

BackgroundNumerous observational studies have revealed that circulating adiponectin (ADPN) is associated with Alzheimer's disease (AD) risk. However, the causality remains unknown. We aimed to assess the causality of circulating ADPN on AD risk using Mendelian randomization (MR).MethodsFourteen single nucleotide polymorphisms (SNPs) significantly associated with ADPN were selected from publicly available genetic abstract data. We applied these SNPs to two recent large-scale genome-wide association studies (GWAS) of AD, one from the FinnGen consortium and the other from a large meta-analysis. The inverse variance weighted method, MR–Egger method, the weighted median method, the Cochran Q statistic, the MR-Pleiotropy Residual Sum and Outlier methods, and the leave-one-out analysis were applied for MR analyses.ResultsIn MR analysis, no significant genetic association was found between plasma ADPN levels and AD risk by analyzing the FinnGen consortium GWAS database in the inverse variance weighted method [odds ratio (OR): 0.874, 95% confidence interval (CI): 0.701–1.089, p = 0.230], MR–Egger (OR: 0.944, 95% CI: 0.692–1.288, p = 0.721), and weighted median method (OR: 0.900, 95% CI: 0.678–1.194, p = 0.449). Additionally, the same analysis was conducted for the meta-analysis database, and we found no significant association (OR: 1.000, 95% CI: 0.999–1.001, p = 0.683).ConclusionOur findings reveal no significant causal association between circulating ADPN and AD risk.

Summary: Capturing conformational snapshots by single-particle cryo-EM facilitates the analysis of ligand binding and activation mechanisms for ion channels and other receptor complexes. Here, we present a protocol to capture intermediate states of nanodisc-reconstituted TRPV1. This protocol covers sample preparation, data acquisition, and image processing with focuses on the symmetry expansion and focused 3D classification. This protocol can be adapted to different proteins and samples.For complete details on the use and execution of this protocol, please refer to Zhang et al. (2021). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Fusarium head blight (FHB) is a global wheat grain disease caused by Fusarium graminearum. Biological control of FHB is considered to be an alternative disease management strategy that is environmentally benign, durable, and compatible with other control measures. In this study, to screen antagonistic bacteria with the potential to against FHB, 45 strains were isolated from different tissues of wheat. Among them, seven strains appeared to effectively inhibit F. graminearum growth, the antagonistic bacterium named XY-1 showed a highly antagonistic effect against FHB using dual culture assays. The strain XY-1 was identified as Bacillus amyloliquefaciens by 16S rDNA sequence. Antibiotic tolerance of antagonistic bacteria showed that XY-1 had antagonistic activity against Colletotrichum gloeosporioides, Rhizoctonia solani, Sclerotium rolfsii, and Alternaria alternata. Nutrition tests showed that the most suitable carbon and nitrogen sources were glucose and beef extract, respectively. The optimum growth temperature and pH value were 28 ℃ and 7.4. Antibiotics tolerance cultivation showed that XY-1 had strong resistance to Chloramphenicol and Ampicillin. Wheat spikes inoculation antagonism tests showed that strain XY-1 displayed strong antifungal activity against F. graminearum. Our study laid a theoretical foundation for the application of strain XY-1 as a biological agent in the field to control FHB.

BackgroundIn this study, we investigated the epidemiological characteristics and predictors of diabetic peripheral neuropathy (DPN) in adult patients with type 2 diabetes mellitus (DM).MethodsThe study was designed as a retrospective cohort trial at the First Affiliated Hospital of Wenzhou Medical University. From January 2017 to December 2020, a total of 1,262 patients with DM were enrolled to assess the risk factors for DPN. The patients were divided into two groups (DPN group and non-DPN group). The Mann–Whitney U test or t-test, receiver operating characteristic (ROC) analyses, univariate chi-square analyses, and multiple logistic regression analyses were used to analyze the adjusted predictors of DPN.ResultsThe overall prevalence of DPN in DM patients was 72.7% (n = 793/1,091). Multivariate analysis revealed that age > 66 years (odds ratio [OR], 2.647; 95% confidence interval [CI] 1.469–4.770; p = 0.002), history of hypertension (OR, 1.829; 95% CI 1.146–2.920; p = 0.011), neutrophil (NE) levels exceeding 4.0 × 109/L (OR 0.256; 95% CI 0.162–0.405; p = 0.001), lymphocyte (LY) levels over 3.0 × 109/L (OR 7.173; 95% CI 4.258–12.086; p = 0.000), HbA1c > 7.7% (OR 3.151; 95% CI 1.959–5.068; p = 0.000), and FT3 > 4.4 pmol/L (OR 0.417; 95% CI 0.263–0.662; p = 0.000) were six significant predictive factors for the prevalence of DPN.ConclusionsHigh levels of LY, HbA1c, history of hypertension, and > 66 years of age increase the risk of DPN in adult patients with DM, while high levels of NE and FT3 were protective factors of DPN. Thus, the prediction of DPN can significantly be improved by identifying older patients over the age of 66 and history of hypertension, as well as establishing the biochemical cutoff values of NE, LY, HbA1c, and FT3.

Objectives: In this study, we propose a deep learning-based approach to predict Intensity-modulated radiation therapy (IMRT) quality assurance (QA) gamma passing rates using delivery fluence informed by log files. Methods: A total of 112 IMRT plans for chest cancers were planned and measured by portal dosimetry equipped on TrueBeam linac. The convolutional neural network (CNN) based learning model was trained using delivery fluence as inputs and gamma passing rates (GPRs) of 4 different criteria (3%/3 mm, 2%/3 mm, 3%/2 mm, and 2%/2 mm) as outputs. Model performance for both validation and test sets was assessed using mean absolute error (MAE), mean squared error (MSE), root MSE (RMSE), Spearman rank correlation coefficients (Sr), and Determination coefficient ( R 2 ) between the measured and predicted GPR values. Results: In the test set, the MAE of the prediction model were 0.402, 0.511, 1.724, and 2.530, the MSE were 0.640, 0.986, 6.654, and 9.508, the RMSE were 0.800, 0.993, 2.580, and 3.083, the Sr were 0.643, 0.684, 0.821, and 0.824 ( P

Arctic hydrology is experiencing rapid changes including earlier snow melt, permafrost degradation, increasing active layer depth, and reduced river ice, all of which are expected to lead to changes in stream flow regimes. Recently, long-term (>60 years) climate reanalysis and river discharge observation data have become available. We utilized these data to assess long-term changes in discharge and their hydroclimatic drivers. River discharge during the cold season (October–April) increased by 10% per decade. The most widespread discharge increase occurred in April (15% per decade), the month of ice break-up for the majority of basins. In October, when river ice formation generally begins, average monthly discharge increased by 7% per decade. Long-term air temperature increases in October and April increased the number of days above freezing (+1.1 d per decade) resulting in increased snow ablation (20% per decade) and decreased snow water equivalent (−12% per decade). Compared to the historical period (1960–1989), mean April and October air temperature in the recent period (1990–2019) have greater correlation with monthly discharge from 0.33 to 0.68 and 0.0–0.48, respectively. This indicates that the recent increases in air temperature are directly related to these discharge changes. Ubiquitous increases in cold and shoulder-season discharge demonstrate the scale at which hydrologic and biogeochemical fluxes are being altered in the Arctic.

In cryogenic electron microscopy (cryo-EM) of radiation-sensitive biological samples, both the signal-to-noise ratio (SNR) and the contrast of images are critically important in the image-processing pipeline. Classic methods improve low-frequency image contrast experimentally, by imaging with high defocus, or computationally, by applying various types of low-pass filter. These contrast improvements typically come at the expense of the high-frequency SNR, which is suppressed by high-defocus imaging and removed by low-pass filtration. Recently, convolutional neural networks (CNNs) trained to denoise cryo-EM images have produced impressive gains in image contrast, but it is not clear how these algorithms affect the information content of the image. Here, a denoising CNN for cryo-EM images was implemented and a quantitative evaluation of SNR enhancement, induced bias and the effects of denoising on image processing and three-dimensional reconstructions was performed. The study suggests that besides improving the visual contrast of cryo-EM images, the enhanced SNR of denoised images may be used in other parts of the image-processing pipeline, such as classification and 3D alignment. These results lay the groundwork for the use of denoising CNNs in the cryo-EM image-processing pipeline beyond particle picking.

Antibody-dependent enhancement (ADE) exists in several kinds of virus. It has a negative influence on antibody therapy for viral infection. This effect was first identified in dengue virus and has since also been described for coronavirus. To date, the rapid spread of the newly emerged coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing coronavirus disease 2019 (COVID-19), has affected over 3.8 million people across the globe. The novel coronavirus poses a great challenge and has caused a wave of panic. In this review, antibody-dependent enhancements in dengue virus and two kinds of coronavirus are summarized. Possible solutions for the effects are reported. We also speculate that ADE may exist in SARS-CoV-2.

AreTomo, an abbreviation for Alignment and Reconstruction for Electron Tomography, is a GPU accelerated software package that fully automates motion-corrected marker-free tomographic alignment and reconstruction in a single package. By correcting in-plane rotation, translation, and importantly, the local motion resulting from beam-induced motion from tilt to tilt, AreTomo can produce tomograms with sufficient accuracy to be directly used for subtomogram averaging. Another major application is the on-the-fly reconstruction of tomograms in parallel with tilt series collection to provide users with real-time feedback of sample quality allowing users to make any necessary adjustments of collection parameters. Here, the multiple alignment algorithms implemented in AreTomo are described and the local motions measured on a typical tilt series are analyzed. The residual local motion after correction for global motion was found in the range of ± 80 Å, indicating that the accurate correction of local motion is critical for high-resolution cryo-electron tomography (cryoET).

The 26S proteasome is a protein degradation machine composed of a 20S core particle (CP) flanked at one or both ends by a 19S ATPase regulatory particle (RP). Here the authors reconstitute asymmetric archaeal proteasomes and reveal allosteric coupling between the conformations of gates in the α-rings positioned at opposite ends of the CP, which modulates RP assembly and substrate entry.

The coronavirus disease 2019 (COVID-19) is a new type of pneumonia caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. COVID-19 is affecting millions of patients, and the infected number keeps increasing. SARS-CoV-2 is highly infectious, has a long incubation period, and causes a relatively high death rate, resulting in severe health problems all over the world. Currently there is no effective proven drug for the treatment of COVID-19; therefore, development of effective therapeutic drugs to suppress SARS-CoV-2 infection is urgently needed. In this review, we first summarize the structure and genome features of SARS-CoV-2 and introduce its infection and replication process. Then, we review the clinical symptoms, diagnosis, and treatment options of COVID-19 patients. We further discuss the potential molecular targets and drug development strategies for treatment of the emerging COVID-19. Finally, we summarize clinical trials of some potential therapeutic drugs and the results of vaccine development. This review provides some insights for the treatment of COVID-19.

Prior to anaphase, securin binds separase and thereby prevents cohesin cleavage. Here, the authors develop a method to produce active securin-free separase, identify a docking motif in cohesin that promotes cleavage, and show that securin interferes with this interaction.

This article presents an indoor infant monitoring system based on Android system which employs a low-cost Bluetooth Low Energy (BLE) pseudolite to accurately locate the infants in the activity indoors and timely remind the parents. It can achieve a positioning accuracy better than 2 m and effectively reduce the risk of injury to infants and young children. The performance of the proposed system, using false negative rate, false alarm rate, and alarm response time as indicators, is compared with that of the system using Quuppa as a positioning source. The experiment results show that both BLE pseudolite and Quuppa as a positioning source can basically meet the positioning accuracy for the infant monitoring system, but the BLE-pseudolite-based system provides a more cost-efficient solution.

Allostery—regulation at distant sites is a key concept in biology. The proteasome exhibits multiple forms of allosteric regulation. This regulatory communication can span a distance exceeding 100 Ångstroms and can modulate interactions between the two major proteasome modules: its core particle and regulatory complexes. Allostery can further influence the assembly of the core particle with regulatory particles. In this focused review, known and postulated interactions between these proteasome modules are described. Allostery may explain how cells build and maintain diverse populations of proteasome assemblies and can provide opportunities for therapeutic interventions.

Viral infection and pathogenesis is mediated by host protein-viral protein complexes that are important targets for therapeutic intervention as they are potentially less prone to development of drug resistance. We have identified human, recombinant antibodies (Fabs) from a phage display library that bind to three HIV-host complexes. We used these Fabs to 1) stabilize the complexes for structural studies; and 2) facilitate characterization of the function of these complexes. Specifically, we generated recombinant Fabs to Vif-CBF-β-ELOB-ELOC (VCBC); ESCRT-I complex and AP2-complex. For each complex we measured binding affinities with KD values of Fabs ranging from 12-419 nM and performed negative stain electron microscopy (nsEM) to obtain low-resolution structures of the HIV-Fab complexes. Select Fabs were converted to scFvs to allow them to fold intracellularly and perturb HIV-host protein complex assembly without affecting other pathways. To identify these recombinant Fabs, we developed a rapid screening pipeline that uses quantitative ELISAs and nsEM to establish whether the Fabs have overlapping or independent epitopes. This pipeline approach is generally applicable to other particularly challenging antigens that are refractory to immunization strategies for antibody generation including multi-protein complexes providing specific, reproducible, and renewable antibody reagents for research and clinical applications. The curated antibodies described here are available to the scientific community for further structural and functional studies on these critical HIV host-factor proteins.

Limbal stem cells are essential for continuous corneal regeneration and injury repair. METTL3-catalyzed N6-methyladenosine (m6A) mRNA modifications are involved in many biological processes and play a specific role in stem cell regeneration, while the role of m6A modifications in corneal injury repair remains unknown. In this study, we generated a limbal stem cell-specific METTL3 knockout mouse model and studied the role of m6A in repairing corneal injury caused by alkali burn. The results showed that METTL3 knockout in the limbal stem cells promotes the in vivo cell proliferation and migration, leading to the fast repair of corneal injury. In addition, m6A modification profiling identified stem cell regulatory factors AHNAK and DDIT4 as m6A targets. Our study reveals the essential functions of m6A RNA modification in regulating injury repair and provides novel insights for clinical therapy of corneal diseases.

Background: The COVID-19 pandemic is a major public health issue and challenge to health professionals. In similar epidemics, nurses experienced more distress than other providers.Methods: We surveyed both on-duty nurses caring for infected patients and second-line nurses caring for uninfected patients from Hubei and other provinces throughout China.Results: We received completed surveys from 1,364 nurses from 22 provinces: 658 front-line and 706 second-line nurses. The median (IQR) GHQ-28 score of all nurses was 17 (IQR 11–24). The overall incidence of mild-to-moderate distress (GHQ score > 5) was 28%; that for severe distress (GHQ score > 11) was 6%. The incidence of mild-to-moderate distress in the second-line nurses was higher than that in the front-line nurses (31 vs. 25%; OR, 0.74; 95 CI, 0.58–0.94). Living alone (OR, 0.62; 95% CI, 0.44–0.86) and feeling supported (OR, 0.82, 95% CI, 0.74–0.90) independently predicted lower anxiety.Conclusions: During the COVID-19 pandemic, the psychological problems of all nurses were generally serious. The interviewed second-line nurses face more serious issues than the front-line nurses.

The size, distribution, and orientation of fractures are generally multiscale and multi-dimensional in nature, leading to complex anisotropic characteristics. Theoretical or semi-analytical methods to determine the effective elastic properties depend on several assumptions, including the absence of the stress interaction and idealized fractures. On the basis of finite-element models, we conduct numerical oscillatory relaxation tests for determining the effective elastic properties of fractured rocks. The numerical approach for calculating equivalent stiffness tensors in two-dimensions is compared to the theoretical models for different fracture densities. Due to fracture interactions at high fracture densities, the suggested model makes a physical prediction. The effective elastic properties obtained from the application to a real fractured model, established from an outcrop, obviously disperse at different frequencies, which can be used to investigate fracture interactions and dynamic stress disturbances. The algorithm is extended to three-dimensional cases and also validated by using conventional effective medium theories. It is found that the fracture density obviously impacts the effective anisotropy properties, and the proposed method gives a reasonable prediction for high-fracture density. This work is significant because it enables the calculation of effective elastic properties of multi-dimensional fractured models and the fracture interaction mechanism.

The Coronavirus Disease 2019 (COVID-19) has swept the whole world with high mortality. Since droplet transmission is the main route of transmission, wearing a mask serves as a crucial preventive measure. However, the virus has spread quite quickly, causing severe mask shortage. Finding alternative materials for homemade masks while ensuring the significant performance indicators will help alleviate the shortage of masks. Referring to the national standard for the "Surgical Mask" of China, 17 materials to be selected for homemade masks were tested in four key indicators: pressure difference, particle filtration efficiency, bacterial filtration efficiency and resistance to surface wetting. Eleven single-layer materials met the standard of pressure difference (≤49 Pa), of which 3 met the standard of resistance to surface wetting (≥3), 1 met the standard of particle filtration efficiency (≥30%), but none met the standard of bacterial filtration efficiency (≥95%). Based on the testing results of single-layer materials, fifteen combinations of paired materials were tested. The results showed that three double-layer materials including double-layer medical non-woven fabric, medical non-woven fabric plus non-woven shopping bag, and medical non-woven fabric plus granular tea towel could meet all the standards of pressure difference, particle filtration efficiency, and resistance to surface wetting, and were close to the standard of the bacterial filtration efficiency. In conclusion, if resources are severely lacking and medical masks cannot be obtained, homemade masks using available materials, based on the results of this study, can minimize the chance of infection to the maximum extent.

Highly effective pesticide applications require a continual adjustment of the pesticide spray flow rate that attends to different canopy characterizations. Real-time image processing with rapid target detection and data-processing technologies is vital for precision pesticide application. However, the extant studies do not provide an efficient and reliable method of extracting individual trees with irregular tree-crown shapes and complicated backgrounds. This paper on our study proposes a Mahalanobis distance and conditional random field (CRF)-based segmentation model to extract cherry trees accurately in a natural orchard environment. This study computed Mahalanobis distance from the image’s color, brightness and location features to acquire an initial classification of the canopy and background. A CRF was then created by using the Mahalanobis distance calculations as unary potential energy and the Gaussian kernel function based on the image color and pixels distance as binary potential energy. Finally, the study completed image segmentation using mean-field approximation. The results show that the proposed method displays a higher accuracy rate than the traditional algorithms K-means and GrabCut algorithms and lower labeling and training costs than the deep learning algorithm DeepLabv3+, with 92.1%, 94.5% and 93.3% of the average P, R and F1-score, respectively. Moreover, experiments on datasets with different overlap conditions and image acquisition times, as well as in different years and seasons, show that this method performs well under complex background conditions, with an average F1-score higher than 87.7%.