Carboxymethyl chitosan and dialdehyde cellulose nanocrystal based injectable self-healing emulsion gel.

The study aims to demonstrate a general method for producing emulsion gels with self-healing properties. Specifically, the self-healing emulsion gels were fabricated by crosslinking carboxymethyl chitosan (CMC) stabilized emulsion with dialdehyde cellulose nanocrystal (DACNC). The reversible imine bonds between primary amino groups from CMC and aldehyde groups from DACNC endow the emulsion gel with self-healing properties. The compressive strength of the emulsion gels was greatly increased from 37.43 kPa 83.7 kPa by encapsulating emulsion droplets (φ = 0 %-40 %.) in the gel matrix. Moreover, the emulsion gels exhibited much better self-healing and injectability ability compared to hydrogel because the emulsion droplets interacted with the 3D gel matrix, which were observed by cryo-SEM and CLSM. The emulsion droplets distributed in the gel matrix improved the mobility and interfacial contact area of CMC and DACNC. Water contact measurement confirmed that the CMC/DACNC self-healing emulsion gels showed a hydrophilic surface. The CMC/DACNC emulsion gels could maintain a good structural stability as the oil loss was <1 % after centrifugation. This research provides a method to keep the structural stability of emulsion gels by inducing self-healing ability and modified cellulose nanocrystals, which could extend the shelf life and application area of emulsion gels.

Sex-Based Differences in Melanoma Survival Improvement from 2004 to 2018.

Background: Melanoma is the deadliest form of skin cancer and its incidence and mortality vary by sex, age, race, and socioeconomic status. Relatively few studies, however, have characterized disparities in survival improvement across these demographic groups in melanoma. METHODS: Survival data from the Surveillance, Epidemiology, and End Results (SEER) database were obtained from 2004 to 2018. The compiled data were analyzed for cancer-specific survival (CSS) to produce multivariable Cox regressions that estimate sex-based survival disparities across patient demographic groups. Additionally, time-to-progression and survival analyses were conducted for a cohort of patients with carcinoma-in situ (CIS) that developed into melanoma. RESULTS: In both female and male patients, melanoma diagnosis in more recent years (2014-2018 versus 2004-2008) was associated with an improved CSS, with females demonstrating an HR of 0.55 (95% CI: 0.49-0.60) and males demonstrating an HR of 0.49 (0.46-0.53). The trend remained consistent upon analyzing the effects of both sex and race on survival improvement for White and Hispanic males and females, but the results were not significant for Black and Asian patients. Joint sex and age analysis demonstrated significant reductions in HR across all age groups for female and male patients with a diagnosis in more recent years. Analysis of lesions progressing from CIS to melanoma (high-risk CIS) demonstrated an increased OR for males over females (OR: 1.70; 95% CI: 1.55-1.85), while survival analysis demonstrated no difference between sexes in the HR. Finally, for male patients, high-risk CIS demonstrated worse CSS compared to female patients with high-risk CIS (OR: 1.43; 95% CI: 1.15-1.79). CONCLUSION: Overall, melanoma survival has improved in recent years, though some patient subgroups have experienced a lower improvement in survival from 2004 to 2018.

Odorant Receptors Expressing and Antennal Lobes Architecture Are Linked to Caste Dimorphism in Asian Honeybee, Apis cerana (Hymenoptera: Apidae).

Insects heavily rely on the olfactory system for food, mating, and predator evasion. However, the caste-related olfactory differences in Apis cerana, a eusocial insect, remain unclear. To explore the peripheral and primary center of the olfactory system link to the caste dimorphism in A. cerana, transcriptome and immunohistochemistry studies on the odorant receptors (ORs) and architecture of antennal lobes (ALs) were performed on different castes. Through transcriptomesis, we found more olfactory receptor genes in queens and workers than in drones, which were further validated by RT-qPCR, indicating caste dimorphism. Meanwhile, ALs structure, including volume, surface area, and the number of glomeruli, demonstrated a close association with caste dimorphism. Particularly, drones had more macroglomeruli possibly for pheromone recognition. Interestingly, we found that the number of ORs and glomeruli ratio was nearly 1:1. Also, the ORs expression distribution pattern was very similar to the distribution of glomeruli volume. Our results suggest the existence of concurrent plasticity in both the peripheral olfactory system and ALs among different castes of A. cerana, highlighting the role of the olfactory system in labor division in insects.

Corrigendum: Sestrin2 protects against hypoxic nerve injury by regulating mitophagy through SESN2/AMPK pathway.

[This corrects the article DOI: 10.3389/fmolb.2023.1266243.].

DeepCG: A cell graph model for predicting prognosis in lung adenocarcinoma.

Lung cancer is the first leading cause of cancer-related death in the United States, with lung adenocarcinoma as the major subtype accounting for 40% of all cases. To improve patient survival, image-based prognostic models were developed due to the ready availability of pathological images at diagnosis. However, the application of these models is hampered by two main challenges: the lack of publicly available image datasets with high-quality survival information and the poor interpretability of conventional convolutional neural network models. Here, we integrated matched transcriptomic and H&E staining data from TCGA (The Cancer Genome Atlas) to develop an image-based prognostic model, termed Deep-learning based Cell Graph (DeepCG) model. Instead of survival data, we used a gene signature to predict patient prognostic risks, which was then used as labels for training DeepCG. Importantly, by employing graph structures to capture cell patterns, DeepCG can provide cell-level interpretation, which was more biologically relevant than previous region-level insights. We validated the prognostic values of DeepCG in independent datasets and demonstrated its ability to identify prognostically informative cells in images.

Effect of telehealth interventions on adherence to endocrine therapy among patients with breast cancer: a systematic review and meta-analysis.

PURPOSE: To evaluate the effect of telehealth interventions on adherence to endocrine therapy among patients with breast cancer. METHODS: A systematic search of five English databases (PubMed, Web of Science, Embase, the American Psychological Association PsycNet, and the Cochrane Library) and four Chinese databases (Chinese National Knowledge Infrastructure, SinoMed, WanFang Data, and WeiPu Data) was performed from inception to March 31, 2023. Two investigators independently screened the available studies for eligibility and extracted relevant data. Quality assessment was conducted using the Cochrane Risk of Bias Tool. The effect size was computed based on the risk ratio for dichotomous data and standardized mean difference for continuous data using Review Manager 5.4. RESULTS: A total of 1,780 participants from eight randomized controlled trials were included. These studies involved treatment with aromatase inhibitors only (n = 3) or aromatase inhibitors plus tamoxifen (n = 5). Telehealth interventions involved web-based interventions, telephone-based interventions, interventions via mobile applications, and interventions based on technology. In three studies, subjective measures were used, while objective measures were utilized in another three. Two studies incorporated a combination of both subjective and objective measures. The duration of the interventions varied among studies, ranging from a week to 36 months. The follow-up duration ranged from 4 weeks to 36 months. The quality of included studies was moderate to high. The meta-analysis of the five studies reporting dichotomous data showed that telehealth interventions had a significant effect on adherence to endocrine therapy (RR = 0.86, 95% CI = 0.76-0.97). Moreover, four studies reported continuous data. The meta-analysis demonstrated that telehealth interventions significantly improved adherence to endocrine therapy at 1 month (SMD = 0.50, 95% CI = 0.10-0.90), 3 months (SMD = 0.58, 95% CI = 0.17-0.99), and 6 months (SMD = 0.27, 95% CI = 0.08-0.47) of follow-up. CONCLUSION: Telehealth interventions may facilitate adherence to endocrine therapy among patients with breast cancer. Further research should adopt a theory-based design and explore the longer-term effects.

The protein phosphatase qGL3/OsPPKL1 self-regulates its degradation to orchestrate brassinosteroid signaling in rice.

Brassinosteroids (BRs) are a class of phytohormones that regulate plant growth and development. In previous studies, we cloned and identified PROTEIN PHOSPHATASE WITH KELCH-LIKE1 (OsPPKL1) as the causal gene for the quantitative trait locus GRAIN LENGTH3 (qGL3) in rice (Oryza sativa). We also showed that qGL3/OsPPKL1 is mainly located in the cytoplasm and nucleus and negatively regulates BR signaling and grain length. Because qGL3 is a negative regulator of BR signaling, its turnover is critical for rapid response to changes in BRs. Here, we demonstrate that qGL3 interacts with the WD40-domain-containing protein WD40-REPEAT PROTEIN48 (OsWDR48), which contains a nuclear export signal (NES). The NES signal is crucial for the cytosolic localization of OsWDR48 and also functions in the self-turnover of qGL3. We show that OsWDR48 physically interacts with and genetically acts through qGL3 to modulate BR signaling. Moreover, qGL3 may indirectly promote the phosphorylation of OsWDR48 at the Ser-379 and Ser-386 sites. Substitutions of both phosphorylation sites in OsWDR48 to non-phosphorylatable alanine enhanced the strength of the OsWDR48-qGL3 interaction. Furthermore, we found that brassinolide can promote the accumulation of non-phosphorylated OsWDR48, leading to strong interaction intensity between qGL3 and OsWDR48. Taken together, our results show that OsWDR48 facilitates qGL3 retention and induces degradation of qGL3 in the cytoplasm. These findings suggest that qGL3 self-modulates its turnover by binding to OsWDR48 to regulate its cytoplasmic localization and stability, leading to efficient orchestration of BR signal transduction in rice.

Uncertainty Evaluation of Soil Heavy Metal(loid) Pollution and Health Risk in Hunan Province: A Geographic Detector with Monte Carlo Simulation.

Research on soil heavy metal(loid) pollution and health risk assessment is extensive, but a notable gap exists in systematically examining uncertainty in this process. We employ the Nemerow index, the health risk assessment model, and the geographic detector model (GDM) to analyze soil heavy metal(loid) pollution, assess health risks, and identify driving factors in Hunan Province, China. Furthermore, the Monte Carlo simulation (MCS) method is utilized to quantitatively evaluate the uncertainties associated with the sampling point positions, model parameters, and classification boundaries of the driving factors in these processes. The experimental findings reveal the following key insights: (1) Regions with high levels of heavy metal(loid) pollution, accompanied by low uncertainty, are identified in Chenzhou and Hengyang Cities in Hunan Province. (2) Arsenic (As) and chromium (Cr) are identified as the primary contributors to health risks. (3) The GDM results highlight strong nonlinear enhanced interactions among lithology and other factors. (4) The input GDM factors, such as temperature, river distance, and gross domestic product (GDP), show high uncertainty on the influencing degree of soil heavy metal(loid) pollution. This study thoroughly assesses high heavy metal(loid) pollution in Hunan Province, China, emphasizing uncertainty and offering a scientific foundation for land management and pollution remediation.

Correction to "Rapamycin Inhibits Osteoclastogenesis and Prevents LPS-Induced Alveolar Bone Loss by Oxidative Stress Suppression".

[This corrects the article DOI: 10.1021/acsomega.3c01289.].

PhasiHunter: a robust phased siRNA regulatory cascade mining tool based on multiple reference sequences.

SUMMARY: In recent years, phased small interfering RNA has been found to play crucial roles in many biological processes in plants. However, efficiently predicting phasiRNA regulatory cascades with computational methods is still challenging. Here, we introduce PhasiHunter, a phasiRNA regulatory network prediction tool that has several distinctive features compared to existing tools: (i) PhasiHunter employs two major phasiRNA prediction algorithms, namely phase score and hypergeometric distribution-based methods, to ensure the integrity and accuracy of prediction; (ii) PhasiHunter can identify phasiRNAs and their regulatory networks based on multiple reference sequences and the predicted results can be automatically integrated; (iii) PhasiHunter can efficiently identify the phasiRNAs generated through alternative splicing events; and (iv) the excellent data structure and parallel computing architecture allow PhasiHunter to predict phasiRNAs and their regulatory pathways with high efficiency. AVAILABILITY AND IMPLEMENTATION: PhasiHunter is an open-source tool that is available at https://github.com/HuangLab-CBI/PhasiHunter.

Sestrin2 protects against hypoxic nerve injury by regulating mitophagy through SESN2/AMPK pathway.

Hypoxia induced by high altitude can lead to severe neurological dysfunction. Mitophagy is known to play a crucial role in hypoxic nerve injury. However, the regulatory mechanism of mitophagy during this injury remains unclear. Recent studies have highlighted the role of Sestrin2 (SESN2), an evolutionarily conserved stress-inducible protein against acute hypoxia. Our study demonstrated that hypoxia treatment increased SESN2 expression and activated mitophagy in PC12 cells. Furthermore, the knock-out of Sesn2 gene led to a significant increase in mitochondrial membrane potential and ATP concentrations, which protected the PC12 cells from hypoxic injury. Although the AMPK/mTOR pathway was significantly altered under hypoxia, it does not seem to participate in mitophagy regulation. Instead, our data suggest that the mitophagy receptor FUNDC1 plays a vital role in hypoxia-induced mitophagy. Moreover, SESN2 may function through synergistic regulation with other pathways, such as SESN2/AMPK, to mediate cellular adaptation to hypoxia, including the regulation of mitophagy in neuron cells. Therefore, SESN2 plays a critical role in regulating neural cell response to hypoxia. These findings offer valuable insights into the underlying molecular mechanisms governing the regulation of mitophagy under hypoxia and further highlight the potential of SESN2 as a promising therapeutic target for hypoxic nerve injury.

Reduced Racial Disparity as a Result of Survival Improvement in Prostate Cancer.

Prostate cancer is a cancer type associated with a high level of racial and socioeconomic disparities as reported by many previous studies. However, the changes in these disparities in the past two decades have not been systematically studied. In this study, we investigated the Surveillance Epidemiology End Results (SEER) data for prostate cancer patients diagnosed during 2004-2018. African Americans and Asians showed significantly better and worse cancer-specific survival (CSS), respectively, compared to non-Hispanic white individuals after adjusting for confounding factors such as age and cancer stage. Importantly, the data indicated that racial disparities fluctuated and reached the highest level during 2009-2013, and thereafter, it showed a substantial improvement. Such a change cannot be explained by the improvement in early diagnosis but is mainly driven by the differential improvement in CSS between races. Compared with Asians and non-Hispanic whites, African American patients achieved a more significant survival improvement during 2014-2018, while no significant improvement was observed for Hispanics. In addition, the SEER data showed that high-income patients had significantly longer CSS than low-income patients. Such a socioeconomic disparity was continuously increasing during 2004-2018, which was caused by the increased survival benefits of the high-income patients with respect to the low-income patients. Our study suggests that more efforts and resources should be allocated to improve the treatment of patients with low socioeconomic status.

TimiGP: Inferring cell-cell interactions and prognostic associations in the tumor immune microenvironment through gene pairs.

Determining the prognostic association of different immune cell types in the tumor microenvironment is critical for understanding cancer biology and developing new therapeutic strategies. However, this is challenging in certain cancer types, where the abundance of different immune subsets is highly correlated. In this study, we develop a computational method named TimiGP to overcome this challenge. Based on bulk gene expression and survival data, TimiGP infers cell-cell interactions that reveal the association between immune cell relative abundance and prognosis. As demonstrated in metastatic melanoma, TimiGP prioritizes immune cells critical in prognosis based on the identified cell-cell interactions. Highly consistent results are obtained by TimiGP when applied to seven independent melanoma datasets and when different cell-type marker sets are used as inputs. Additionally, TimiGP can leverage single-cell RNA sequencing data to delineate the tumor immune microenvironment at high resolutions across a wide range of cancer types.

Promoting active aging through assistive product design innovation: a preference-based integrated design framework.

Background: With the accelerating trend of global aging, over one billion people need to use one or more types of assistive products. However, the high abandonment rate of current assistive products is affecting the quality of life of the older adults, posing challenges to public health. Accurately capturing the preference factors of the older adults in the design process is an important way to improve the acceptance of assistive products. In addition, a systematic approach is needed to translate these preference factors into innovative product solutions. These two issues are less addressed in existing research. Methods: First, the evaluation grid method was used to conduct in-depth interviews with users and extract the structure of preference factors for assistive products. Quantification theory type I was used to calculate the weight of each factor. Secondly, universal design principles, TRIZ theory's contradiction analysis techniques, and invention principles were used to translate the preference factors into design guidelines. Then, finite structure method (FSM), morphological chart, and CAD techniques were used to visualize the design guidelines as alternatives. Finally, Analytic Hierarchy Process (AHP) was used to evaluate and rank the alternatives. Results: A Preference-based Assistive Product Design Model (PAPDM) was proposed. The model includes three stages: definition, ideation, and evaluation. A case study on walking aid demonstrated the execution of PAPDM. The results show that 28 preference factors influence the four psychological needs of the older adults: sense of security, sense of independence, self-esteem, and sense of participation. These psychological needs were reflected in the shape, color, material, universality, user-friendly, reliability, and smart functions of assistive products. The preference factors were transformed into five design guidelines, and three alternatives were generated. Finally, the evaluation concludes that solution C was the optimal solution. Conclusion: The PAPDM framework provides designers with a transparent, progressive approach to designing assistive products that meet unique needs and preferences of older adults. This enhances objectivity and scientific rigor in assistive product development, avoiding blind design and production. By considering the perspective of older adults from the outset, we can avoid high abandonment rates of assistive products and contribute to promoting active aging.

Rapamycin Inhibits Osteoclastogenesis and Prevents LPS-Induced Alveolar Bone Loss by Oxidative Stress Suppression.

Periodontitis is a progressive inflammatory skeletal disease characterized by periodontal tissue destruction, alveolar bone resorption, and tooth loss. Chronic inflammatory response and excessive osteoclastogenesis play essential roles in periodontitis progression. Unfortunately, the pathogenesis that contributes to periodontitis remains unclear. As a specific inhibitor of the mTOR (mammalian/mechanistic target of rapamycin) signaling pathway and the most common autophagy activator, rapamycin plays a vital role in regulating various cellular processes. The present study investigated the effects of rapamycin on osteoclast (OC) formation in vitro and its effects on the rat periodontitis model. The results showed that rapamycin inhibited OC formation in a dose-dependent manner by up-regulating the Nrf2/GCLC signaling pathway, thus suppressing the intracellular redox status, as measured by 2',7'-dichlorofluorescein diacetate and MitoSOX. In addition, rather than simply increasing the autophagosome formation, rapamycin increased the autophagy flux during OC formation. Importantly, the anti-oxidative effect of rapamycin was regulated by an increase in autophagy flux, which could be attenuated by blocking autophagy with bafilomycin A1. In line with the in vitro results, rapamycin treatment attenuated alveolar bone resorption in rats with lipopolysaccharide-induced periodontitis in a dose-dependent manner, as assessed by micro-computed tomography, hematoxylin-eosin staining, and tartrate-resistant acid phosphatase staining. Besides, high-dose rapamycin treatment could reduce the serum levels of proinflammatory factors and oxidative stress in periodontitis rats. In conclusion, this study expanded our understanding of rapamycin's role in OC formation and protection from inflammatory bone diseases.

Factors associated with professional identity among ICU nurses during COVID-19: A cross-sectional study.

AIM: To determine the associated factors of professional identity among intensive care unit (ICU) nurses during the COVID-19 pandemic in China. DESIGN: Multicentre cross-sectional study. METHODS: This study invited 348 ICU nurses in five hospitals in China from May to July 2020. Online self-report questionnaires were adopted to collect their demographic and occupational characteristics, perceived professional benefits and professional identity. Based on univariate and multiple linear regression analysis, a path analysis was performed to determine the associated factors' effects on professional identity. RESULTS: The mean score of professional identity was 102.38 ± 16.46. Perceived professional benefits, doctor recognition level and family support level were associated with ICU nurses' professional identity. The path analysis revealed that perceived professional benefits and doctor recognition level had direct effects on professional identity. In addition, doctor recognition level and family support level had indirect effects on professional identity through the mediation of perceived professional benefits.

Nocardia farcinica Pneumonia with Sepsis and a Bronchial Neoplasm in a Healthy Patient: A Case Report.

There are few reports on sepsis caused by infection with Nocardia in people with normal immune function, and there is no report on bronchial tumor caused by Nocardia. This paper describes a case of Nocardia farcinica pneumonia with sepsis and a bronchial neoplasm in a healthy patient.

Binding peptide generation for MHC Class I proteins with deep reinforcement learning.

MOTIVATION: MHC Class I protein plays an important role in immunotherapy by presenting immunogenic peptides to anti-tumor immune cells. The repertoires of peptides for various MHC Class I proteins are distinct, which can be reflected by their diverse binding motifs. To characterize binding motifs for MHC Class I proteins, in vitro experiments have been conducted to screen peptides with high binding affinities to hundreds of given MHC Class I proteins. However, considering tens of thousands of known MHC Class I proteins, conducting in vitro experiments for extensive MHC proteins is infeasible, and thus a more efficient and scalable way to characterize binding motifs is needed. RESULTS: We presented a de novo generation framework, coined PepPPO, to characterize binding motif for any given MHC Class I proteins via generating repertoires of peptides presented by them. PepPPO leverages a reinforcement learning agent with a mutation policy to mutate random input peptides into positive presented ones. Using PepPPO, we characterized binding motifs for around 10 000 known human MHC Class I proteins with and without experimental data. These computed motifs demonstrated high similarities with those derived from experimental data. In addition, we found that the motifs could be used for the rapid screening of neoantigens at a much lower time cost than previous deep-learning methods. AVAILABILITY AND IMPLEMENTATION: The software can be found in https://github.com/minrq/pMHC. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.