The Involvement of YNR069C in Protein Synthesis in the Baker's Yeast, Saccharomyces cerevisiae.

Maintaining translation fidelity is a critical step within the process of gene expression. It requires the involvement of numerous regulatory elements to ensure the synthesis of functional proteins. The efficient termination of protein synthesis can play a crucial role in preserving this fidelity. Here, we report on investigating a protein of unknown function, YNR069C (also known as BSC5), for its activity in the process of translation. We observed a significant increase in the bypass of premature stop codons upon the deletion of YNR069C. Interestingly, the genomic arrangement of this ORF suggests a compatible mode of expression reliant on translational readthrough, incorporating the neighboring open reading frame. We also showed that the deletion of YNR069C results in an increase in the rate of translation. Based on our results, we propose that YNR069C may play a role in translation fidelity, impacting the overall quantity and quality of translation. Our genetic interaction analysis supports our hypothesis, associating the role of YNR069C to the regulation of protein synthesis.

CSCA U-Net: A channel and space compound attention CNN for medical image segmentation.

Image segmentation is one of the vital steps in medical image analysis. A large number of methods based on convolutional neural networks have emerged, which can extract abstract features from multiple-modality medical images, learn valuable information that is difficult to recognize by humans, and obtain more reliable results than traditional image segmentation approaches. U-Net, due to its simple structure and excellent performance, is widely used in medical image segmentation. In this paper, to further improve the performance of U-Net, we propose a channel and space compound attention (CSCA) convolutional neural network, CSCA U-Net in abbreviation, which increases the network depth and employs a double squeeze-and-excitation (DSE) block in the bottleneck layer to enhance feature extraction and obtain more high-level semantic features. Moreover, the characteristics of the proposed method are three-fold: (1) channel and space compound attention (CSCA) block, (2) cross-layer feature fusion (CLFF), and (3) deep supervision (DS). Extensive experiments on several available medical image datasets, including Kvasir-SEG, CVC-ClinicDB, CVC-ColonDB, ETIS, CVC-T, 2018 Data Science Bowl (2018 DSB), ISIC 2018, and JSUAH-Cerebellum, show that CSCA U-Net achieves competitive results and significantly improves generalization performance. The codes and trained models are available at https://github.com/xiaolanshu/CSCA-U-Net.

Rapid screening of the novel bioactive peptides with notable α-glucosidase inhibitory activity by UF-LC-MS/MS combined with three-AI-tool from black beans.

This work aimed to propose a rapid method to screen the bioactive peptides with anti-α-glucosidase activity instead of traditional multiple laborious purification and identification procedures. 242 peptides binding to α-glycosidase were quickly screened and identified by bio-affinity ultrafiltration combined with LC-MS/MS from the double enzymatic hydrolysate of black beans. Top three peptides with notable anti-α-glucosidase activity, NNNPFKF, RADLPGVK and FLKEAFGV were further rapidly screened and ranked by the three artificial intelligence tools (three-AI-tool) BIOPEP database, PeptideRanker and molecular docking from the 242 peptides. Their IC50 values were in order as 4.20 ± 0.11 mg/mL, 2.83 ± 0.03 mg/mL, 1.32 ± 0.09 mg/mL, which was opposite to AI ranking, for the hydrophobicity index of the peptides was not included in the screening criteria. According to the kinetics, FT-IR, CD and ITC analyses, the binding of the three peptides to α-glucosidase is a spontaneous and irreversible endothermic reaction that results from hydrogen bonds and hydrophobic interactions, which mainly changes the α-helix structure of α-glucosidase. The peptide-activity can be evaluated vividly by AFM in vitro. In vivo, the screened FLKEAFGV and RADLPGVK can lower blood sugar levels as effectively as acarbose, they are expected to be an alternative to synthetic drugs for the treatment of Type 2 diabetes.

Hydrogen peroxide sensitivity connects the activity of COX5A and NPR3 to the regulation of YAP1 expression.

Reactive oxygen species (ROS) are among the most severe types of cellular stressors with the ability to damage essential cellular biomolecules. Excess levels of ROS are correlated with multiple pathophysiological conditions including neurodegeneration, diabetes, atherosclerosis, and cancer. Failure to regulate the severely imbalanced levels of ROS can ultimately lead to cell death, highlighting the importance of investigating the molecular mechanisms involved in the detoxification procedures that counteract the effects of these compounds in living organisms. One of the most abundant forms of ROS is H2 O2 , mainly produced by the electron transport chain in the mitochondria. Numerous genes have been identified as essential to the process of cellular detoxification. Yeast YAP1, which is homologous to mammalian AP-1 type transcriptional factors, has a key role in oxidative detoxification by upregulating the expression of antioxidant genes in yeast. The current study reveals novel functions for COX5A and NPR3 in H2 O2 -induced stress by demonstrating that their deletions result in a sensitive phenotype. Our follow-up investigations indicate that COX5A and NPR3 regulate the expression of YAP1 through an alternative mode of translation initiation. These novel gene functions expand our understanding of the regulation of gene expression and defense mechanism of yeast against oxidative stress.

Boron nanosheets boosting solar thermal water evaporation.

Hydrogel-based solar vapour generators (SVGs) are promising for wastewater treatment and desalination. The performance of SVG systems is governed by solar thermal conversion and water management. Progress has been made in achieving high energy conversion efficiency, but the water evaporation rates are still unsatisfactory under 1 sun irradiation. This study introduced novel two-dimensional (2D) boron nanosheets as additives into hydrogel-based SVGs. The resulting SVGs exhibit an outstanding evaporation rate of 4.03 kg m-2 h-1 under 1 sun irradiation. This significant improvement is attributed to the 2D boron nanosheets, which leads to the formation of a higher content of intermediate water and reduced water evaporation enthalpy to 845.11 kJ kg-1. The SVGs into which boron nanosheets were incorporated also showed high salt resistance and durability, demonstrating their great potential for desalination applications.

Influence of Metal Identity and Complex Nuclearity in Kumada Cross-Coupling Polymerizations with a Pyridine Diimine-Based Ligand Scaffold.

Cross-coupling polymerizations have fundamentally changed the field of conjugated polymers (CPs) by expanding the scope of accessible materials. Despite the prevalence of cross-coupling in CP synthesis, almost all polymerizations rely on mononuclear Ni or Pd catalysts. Here, we report a systematic exploration of mono- and dinuclear Fe and Ni precatalysts with a pyridine diimine ligand scaffold for Kumada cross-coupling polymerization of a donor thiophene and an acceptor benzotriazole monomers. We observe that variation of the metal identity from Ni to Fe produces contrasting polymerization mechanisms, while complex nuclearity has a minimal impact on reactivity. Specifically, Fe complexes appear to catalyze step-growth Kumada polymerizations and can readily access both Csp2-Csp3 and Csp2-Csp2 cross-couplings, while Ni complexes catalyze chain-growth polymerizations and predominantly Csp2-Csp2 cross-couplings. Thus, our work sheds light on important design parameters for transition metal complexes used in cross-coupling polymerizations, demonstrates the viability of iron catalysis in Kumada polymerization, and opens the door to novel polymer compositions.

Influence of resilience on depression among nurses in clean operating departments: The mediating effect of life satisfaction.

BACKGROUND: A clean operating room is an important part of surgical and critical treatment in hospitals. The workload is substantial, the pace is rapid, and the working environment is intense; therefore, nurses who work in clean operating rooms are constantly challenged, which can lead to anxiety, depression, and other mental health issues. Life satisfaction and resilience are important factors that ensure mental health. Therefore, exploring the mediating role of life satisfaction in the influence of resilience on depression among nurses in clean operating rooms can help improve nursing services and teamwork. AIM: To explore the mediating effect of satisfaction on the influence of resilience on depression among nurses in a clean operating department. METHODS: From April to November 2022, 196 nurses from the Department of Clean Operating at Harbin Medical University Cancer Hospital participated in this study. Participants were selected using convenience sampling. Participants' gender, age, marital status, position, length of service, personal monthly income, daily working hours, employment status, and professional title were collected, and the Connor-Davidson resilience scale, satisfaction with life scale, and self-rating depression scale were used to evaluate resilience, life satisfaction, and depression. The researchers conducted professional training in advance, introduced the research methods to the participants before the investigation, and explained the study's significance and purpose. Surveys were distributed and collected on-site. Each questionnaire took 30 min to complete. RESULTS: The average scores for life satisfaction, resilience, and depression were 3.13 (± 0.28), 4.09 (± 0.78), and 56.21 (± 8.70), respectively. The correlation between resilience and depression was negative (r = -0.829, P < 0.01). Life satisfaction was positively related to resilience (r = 0.855, P < 0.01) and negatively related to depression (r = -0.778, P < 0.01). The relationship between resilience and depression was partially mediated by life satisfaction. The value of the mediating effect was -6.853 (26.68% of the total effect). CONCLUSION: Life satisfaction partially mediates the link between resilience and depression among nurses in clean operating departments.

DBP7 and YRF1-6 Are Involved in Cell Sensitivity to LiCl by Regulating the Translation of PGM2 mRNA.

Lithium chloride (LiCl) has been widely researched and utilized as a therapeutic option for bipolar disorder (BD). Several pathways, including cell signaling and signal transduction pathways in mammalian cells, are shown to be regulated by LiCl. LiCl can negatively control the expression and activity of PGM2, a phosphoglucomutase that influences sugar metabolism in yeast. In the presence of galactose, when yeast cells are challenged by LiCl, the phosphoglucomutase activity of PGM2p is decreased, causing an increase in the concentration of toxic galactose metabolism intermediates that result in cell sensitivity. Here, we report that the null yeast mutant strains DBP7∆ and YRF1-6∆ exhibit increased LiCl sensitivity on galactose-containing media. Additionally, we demonstrate that DBP7 and YRF1-6 modulate the translational level of PGM2 mRNA, and the observed alteration in translation seems to be associated with the 5'-untranslated region (UTR) of PGM2 mRNA. Furthermore, we observe that DBP7 and YRF1-6 influence, to varying degrees, the translation of other mRNAs that carry different 5'-UTR secondary structures.

High-definition transcranial stimulation over the dorsolateral prefrontal cortex alters the sunk cost effect: A mental accounting framework.

The sunk cost effect refers to the fact that human decisions are consistently influenced by previous irrecoverable and irrelevant costs. Recent neuroimaging experiments suggest that the dorsolateral prefrontal cortex (dlPFC) plays a pivotal role in the sunk cost effect yet the causal and neurocomputational role of the dlPFC remains elusive. In this study, two cohorts of healthy human male and female adults were recruited to complete a novel two-step decision-making task during the anodal-sham or cathodal-sham high-definition transcranial direct current stimulation (HD-tDCS) over the dlPFC, respectively. Consistent with previous studies, we showed that the sunk cost deterred participants from making further investment and therefore engendered a de-escalation effect. Such behavior can be captured by a weighted mental accounting model with a recalibrated reference point in which the direction and magnitude of the sunk cost effects hinge on the decision weights apportioned to the option values. Interestingly, transcranial stimulation did not influence participants' initial willingness to incur sunk costs but only altered sunk costs' downstream effects. Specifically, anodal stimulation over the right dlPFC amplified the de-escalation effect of sunk costs whereas cathodal stimulation yielded the opposite result. HD-tDCS also changed the decision weights of the mental accounting model, providing a causal and computational link between prefrontal cortex and sunk cost effects.Significance Statement:Traditional economic theory assumes that decisions only concern the marginal costs and benefits yet human choices are notoriously susceptible to previously-incurred costs (termed the sunk cost effect). In the current study, we showed that direct current stimulation of the right dorsolateral prefrontal cortex altered sunk cost effects in participants' subsequent choices. Such effects can be captured by a mental accounting model where transcranial stimulation modulates the decision weights assigned to different options in the value integration process. These findings help elucidate the computational and causal role of the dlPFC in the context of sunk costs.

Application of Graphic Design with Computer Graphics and Image Processing: Taking Packaging Design of Agricultural Products as an Example.

With development of economy, all industries have undergone earthshaking changes. Various new technologies are starting to be employed in all aspects of life, and graphic design is no exception. The use of computer graphics and image processing technologies in graphic design can substantially improve design efficiency and make graphic design job more convenient to develop. The requirements for the quality of graphic design are higher. Quality inspection has become a necessary step in the production process, in which the detection of graphic design defects is an indispensable and important link. The traditional graphic design defect detection adopts the method of manual visual inspection, which has the disadvantages of poor stability, long consumption time, and high labor cost. As an efficient computer graphics and image processing technology, convolutional neural network has received extensive attention in graphic design defect detection because of its advantages of high speed, efficiency, and high degree of automation. Taking agricultural product packaging as an example, this paper studies application technology for graphic design defect detection with convolutional neural network (CNN). The main contents are as follows: construct the original YOLOv3 network model, input the graphic design images of agricultural product packaging into the network model in batches according to the computing power of the hardware equipment, train the YOLOv3 network, and deeply study and analyze the experimental results. The related improvement techniques are then given, based on the characteristics of agricultural product packaging design faults. The backbone network, multiscale feature map, a priori frame, and activation function of YOLOv3 are improved, and then performance of the improved model is verified by experiments.

Ultra-stretchable, super-hydrophobic and high-conductive composite for wearable strain sensors with high sensitivity.

With continuous development of artificial intelligence technology, strain sensors have attracted widespread attention. In this work, a novel high-performance wearable strain sensor is prepared by using a kind of ultra-stretchable, super-hydrophobic and high-conductive composite. The preparation process is as follows, i.e., using common elastic band (EB) as the polymer matrix, nano carbon black (CB) and carbon nanotubes (CNTs) as mixed conductive filler, and then modified by polydimethylsiloxane (PDMS) to obtain the PDMS/(CB + CNTs)/EB composite for assembling assemble flexible wearable strain sensors. Experimental results reveal the following excellent properties: 1) The composite exhibits excellent mechanical properties and super-hydrophobicity, i.e., the tensile strength is up to 996.5%, and the elastic modulus and tensile strength increase 49.2% and 59.2%, compared with pristine EB; 2) The composite strain sensor exhibits high sensitivity (the gauge factor reaches up to 648.83 under strain range of 979.9-996.5%), and it still shows stable performance after 3000 cycles tests (100% strain); 3) It is a well candidate to be used for monitoring human body motions including large and subtle body movements; 4) The composite sensor also has advantages of easy access of raw materials, simple preparation, easy mass production and relatively low production cost, showing a broad application prospect in wearable electronic products.

Observation of Coexisting Weak Localization and Superconducting Fluctuations in Strained Sn1-xInxTe Thin Films.

Topological superconductors have attracted tremendous excitement as they are predicted to host Majorana zero modes that can be utilized for topological quantum computing. Candidate topological superconductor Sn1-xInxTe thin films (0 < x < 0.3) grown by molecular beam epitaxy and strained in the (111) plane are shown to host quantum interference effects in the conductivity coexisting with superconducting fluctuations above the critical temperature Tc. An analysis of the normal state magnetoresistance reveals these effects. A crossover from weak antilocalization to localization is consistently observed in superconducting samples, indicating that superconductivity originates dominantly from charge carriers occupying trivial states that may be strongly spin-orbit split. A large enhancement of the conductivity is observed above Tc, indicating the presence of superconducting fluctuations. Our results motivate a re-examination of the debated pairing symmetry of this material when subjected to quantum confinement and lattice strain.

iRice-MS: An integrated XGBoost model for detecting multitype post-translational modification sites in rice.

Post-translational modification (PTM) refers to the covalent and enzymatic modification of proteins after protein biosynthesis, which orchestrates a variety of biological processes. Detecting PTM sites in proteome scale is one of the key steps to in-depth understanding their regulation mechanisms. In this study, we presented an integrated method based on eXtreme Gradient Boosting (XGBoost), called iRice-MS, to identify 2-hydroxyisobutyrylation, crotonylation, malonylation, ubiquitination, succinylation and acetylation in rice. For each PTM-specific model, we adopted eight feature encoding schemes, including sequence-based features, physicochemical property-based features and spatial mapping information-based features. The optimal feature set was identified from each encoding, and their respective models were established. Extensive experimental results show that iRice-MS always display excellent performance on 5-fold cross-validation and independent dataset test. In addition, our novel approach provides the superiority to other existing tools in terms of AUC value. Based on the proposed model, a web server named iRice-MS was established and is freely accessible at http://lin-group.cn/server/iRice-MS.

A Survey for Predicting ATP Binding Residues of Proteins Using Machine Learning Methods.

Protein-ligand interactions are necessary for majority protein functions. Adenosine- 5'-triphosphate (ATP) is one such ligand that plays vital role as a coenzyme in providing energy for cellular activities, catalyzing biological reaction and signaling. Knowing ATP binding residues of proteins is helpful for annotation of protein function and drug design. However, due to the huge amounts of protein sequences influx into databases in the post-genome era, experimentally identifying ATP binding residues is costineffective and time-consuming. To address this problem, computational methods have been developed to predict ATP binding residues. In this review, we briefly summarized the application of machine learning methods in detecting ATP binding residues of proteins. We expect this review will be helpful for further research.

Pain Reported by Chinese Children During Cancer Treatment: Prevalence, Intensity, Interference, and Management.

BACKGROUND: Pain is a frequently reported and distressing symptoms during cancer treatment. However, there is limited evidence on pain reported by Chinese children with cancer. OBJECTIVES: This study aimed to investigate the prevalence, intensity, interference, and management of pain reported by Chinese children during cancer treatment and explore the predictors of pain interference. METHODS: We conducted a cross-sectional survey to investigate the pain intensity, pain interference, co-occurring symptoms (anger, anxiety, depression, fatigue), and pain management strategies reported by children 8 years and older undergoing active cancer treatment in 4 Chinese hospitals. RESULTS: Data were analyzed for 187 children. The prevalence of moderate to severe pain (≥4/10) was 38.50%, with an average pain interference score of 52.97 out of 100. Approximately 24% of children were prescribed pain medicine. Pain interference and pain intensity were marginally correlated (r = 0.047, P < .01) and were both positively correlated with pain duration and co-occurring symptoms and negatively correlated with perceived pain alleviation (all P < .01). Multiple regression analyses suggested that severe pain intensity (B = 2.028, P = .003) and fatigue (B = 0.440, P < .001) significantly predicted higher levels of pain interference (R2 = 0.547, F = 23.102, P < .001). CONCLUSION: Chinese children with cancer reported a low pain intensity score but a relatively high level of pain interference. According to the children's reports, pain has not been sufficiently addressed through Chinese pediatric oncology supportive care. IMPLICATIONS FOR PRACTICE: There is an urgent requirement for comprehensive pain assessment and standardized, targeted interventions in Chinese pediatric oncology pain management.

Sunk cost effects hinge on the neural recalibration of reference points in mental accounting.

The context of reinforcement history drastically influences human value-based choices. Mental accounting theory concerns how prior outcomes are perceived, combined and assigned into specific "mental" accounts to influence subsequent decisions but remains agnostic about the underlying computational and neural mechanisms. In a two-stage sequential decision-making task, we found previously incurred costs and bonuses biased subjects' choices in the opposite directions with similar magnitudes. Such effects were consistent with a computational model where the reference point was recalibrated by prior gains and losses encoded in the ventral striatum activities. Moreover, individual's susceptibility to prior outcomes was captured by the response of the dorsolateral prefrontal cortex and its functional connectivity with the medial orbitofrontal cortex, whose activity tracked the value of the chosen option. Our findings provide both behavioral and neural evidence of how sunk costs, benefits, and prospects are integrated within the mental accounting framework to influence choice behavior.

Self-Reported Fatigue in Chinese Children and Adolescents During Cancer Treatment.

Background: Fatigue is a prevalent and distressing symptom in children and adolescents with cancer. Objectives: This study aimed to (1) investigate the current fatigue status reported by Chinese children and adolescents with cancer during active cancer treatment and (2) examine whether sociodemographic information, disease and treatment information, co-occurring symptoms, function and related clinical data are significantly associated with fatigue according to the biopsychosocial model. Methods: Participants were children aged 8-17 years, who had undergone treatment for cancer at four hospitals in China. Children completed the Chinese version of the Pediatric Patient-Reported Outcomes Measurement Information System short forms. Results: In total, 187 children (33.16% female, mean age 10.28 years) participated. The mean T-score for child-reported fatigue was 48.52 (34-72). Multiple linear regression analysis showed that fatigue in pediatric active cancer treatment could be significantly predicted by greater child-reported pain interference (ß = 0.391, p < .001), greater depressive symptoms (ß = 0.443, p < .001), and reduced mobility (ß = -0.226, p = .004) (adjusted R2 = 0.613, F = 16.476, p < .001). Conclusions: Children and adolescents with cancer experience multiple, intersecting troubling symptoms during their treatment. There is a need to attend to the biopsychosocial aspects of care for children and adolescents during active cancer treatment. To reduce pediatric oncology patients' fatigue level, clinicians could develop culturally sensitive interventions to alleviate children's pain interference, treat depressive symptoms, and maximize their physical mobility.

Identification and Characteristics of the Three Subgroups of Pain in Chinese Children and Adolescents with Cancer.

PURPOSE: Pain is a distressing symptom for children and adolescents with cancer and is experienced by individuals differently. This study sought to determine subgroups according to their pain experiences, and how demographic, clinical, and quality of life (QOL)-related characteristics might differ across subgroups. DESIGN AND METHODS: This cross-sectional study recruited 187 pediatric patients with cancer aged 8 to 17 years old and asked them to complete measures of pain intensity, pain duration, pain interference and pain control using the Chinese translation of the validated questionnaire from the Pain Squad app, as well as 7 PROMIS measures assessing QOL-related outcomes. Latent profile analysis (LPA) was used to identify latent subgroups. RESULTS: Three subgroups of children were identified: low-pain/low-duration (69.5%), moderate-pain/high-duration (19.8%), and high-pain/moderate-duration (10.7%). Hospitalized children were more likely to be in the moderate-pain/high-duration subgroup. Children in the high-pain/moderate-duration subgroup were more likely to be cared for by unemployed caregivers. Scores on depressive symptoms (p = 0.002), anger (p < 0.001), anxiety (p = 0.045), fatigue (p = 0.044), and mobility (p = 0.008) questionnaire were significantly worse in the high-pain/moderate-duration subgroup than the other two subgroup. PRACTICE IMPLICATIONS: This study provides a scientific foundation for further studies exploring predictive factors related to pain experiences. More targeted treatment strategies targeting the specific characteristics of each subgroup will help improve patients' QOL and use of medical resources. CONCLUSIONS: The 3 identified pain subgroups demonstrate the heterogeneity in pain experiences among pediatric patients with cancer. Knowledge of these subgroups can assist clinicians in better identifying and targeting pain treatment for children with cancer.

PPD: A Manually Curated Database for Experimentally Verified Prokaryotic Promoters.

As a key region, promoter plays a key role in transcription regulation. A eukaryotic promoter database called EPD has been constructed to store eukaryotic POL II promoters. Although there are some promoter databases for specific prokaryotic species or specific promoter type, such as RegulonDB for Escherichia coli K-12, DBTBS for Bacillus subtilis and Pro54DB for sigma 54 promoter, because of the diversity of prokaryotes and the development of sequencing technology, huge amounts of prokaryotic promoters are scattered in numerous published articles, which is inconvenient for researchers to explore the process of gene regulation in prokaryotes. In this study, we constructed a Prokaryotic Promoter Database (PPD), which records the experimentally validated promoters in prokaryotes, from published articles. Up to now, PPD has stored 129,148 promoters across 63 prokaryotic species manually extracted from published papers. We provided a friendly interface for users to browse, search, blast, visualize, submit and download data. The PPD will provide relatively comprehensive resources of prokaryotic promoter for the study of prokaryotic gene transcription. The PPD is freely available and easy accessed at http://lin-group.cn/database/ppd/.

Predicting Preference of Transcription Factors for Methylated DNA Using Sequence Information.

Transcription factors play key roles in cell-fate decisions by regulating 3D genome conformation and gene expression. The traditional view is that methylation of DNA hinders transcription factors binding to them, but recent research has shown that many transcription factors prefer to bind to methylated DNA. Therefore, identifying such transcription factors and understanding their functions is a stepping-stone for studying methylation-mediated biological processes. In this paper, a two-step discriminated method was proposed to recognize transcription factors and their preference for methylated DNA based only on sequences information. In the first step, the proposed model was used to discriminate transcription factors from non-transcription factors. The areas under the curve (AUCs) are 0.9183 and 0.9116, respectively, for the 5-fold cross-validation test and independent dataset test. Subsequently, for the classification of transcription factors that prefer methylated DNA and transcription factors that prefer non-methylated DNA, our model could produce the AUCs of 0.7744 and 0.7356, respectively, for the 5-fold cross-validation test and independent dataset test. Based on the proposed model, a user-friendly web server called TFPred was built, which can be freely accessed at http://lin-group.cn/server/TFPred/.