Predicting lncRNA-disease associations based on combining selective similarity matrix fusion and bidirectional linear neighborhood label propagation.

Recent studies have revealed that long noncoding RNAs (lncRNAs) are closely linked to several human diseases, providing new opportunities for their use in detection and therapy. Many graph propagation and similarity fusion approaches can be used for predicting potential lncRNA-disease associations. However, existing similarity fusion approaches suffer from noise and self-similarity loss in the fusion process. To address these problems, a new prediction approach, termed SSMF-BLNP, based on organically combining selective similarity matrix fusion (SSMF) and bidirectional linear neighborhood label propagation (BLNP), is proposed in this paper to predict lncRNA-disease associations. In SSMF, self-similarity networks of lncRNAs and diseases are obtained by selective preprocessing and nonlinear iterative fusion. The fusion process assigns weights to each initial similarity network and introduces a unit matrix that can reduce noise and compensate for the loss of self-similarity. In BLNP, the initial lncRNA-disease associations are employed in both lncRNA and disease directions as label information for linear neighborhood label propagation. The propagation was then performed on the self-similarity network obtained from SSMF to derive the scoring matrix for predicting the relationships between lncRNAs and diseases. Experimental results showed that SSMF-BLNP performed better than seven other state of-the-art approaches. Furthermore, a case study demonstrated up to 100% and 80% accuracy in 10 lncRNAs associated with hepatocellular carcinoma and 10 lncRNAs associated with renal cell carcinoma, respectively. The source code and datasets used in this paper are available at: https://github.com/RuiBingo/SSMF-BLNP.

Achievements, challenges, and perspectives in the design of polymer binders for advanced lithium-ion batteries.

Energy storage devices with high power and energy density are in demand owing to the rapidly growing population, and lithium-ion batteries (LIBs) are promising rechargeable energy storage devices. However, there are many issues associated with the development of electrode materials with a high theoretical capacity, which need to be addressed before their commercialization. Extensive research has focused on the modification and structural design of electrode materials, which are usually expensive and sophisticated. Besides, polymer binders are pivotal components for maintaining the structural integrity and stability of electrodes in LIBs. Polyvinylidene difluoride (PVDF) is a commercial binder with superior electrochemical stability, but its poor adhesion, insufficient mechanical properties, and low electronic and ionic conductivity hinder its wide application as a high-capacity electrode material. In this review, we highlight the recent progress in developing different polymeric materials (based on natural polymers and synthetic non-conductive and electronically conductive polymers) as binders for the anodes and cathodes in LIBs. The influence of the mechanical, adhesion, and self-healing properties as well as electronic and ionic conductivity of polymers on the capacity, capacity retention, rate performance and cycling life of batteries is discussed. Firstly, we analyze the failure mechanisms of binders based on the operation principle of lithium-ion batteries, introducing two models of "interface failure" and "degradation failure". More importantly, we propose several binder parameters applicable to most lithium-ion batteries and systematically consider and summarize the relationships between the chemical structure and properties of the binder at the molecular level. Subsequently, we select silicon and sulfur active electrode materials as examples to discuss the design principles of the binder from a molecular structure point of view. Finally, we present our perspectives on the development directions of binders for next-generation high-energy-density lithium-ion batteries. We hope that this review will guide researchers in the further design of novel efficient binders for lithium-ion batteries at the molecular level, especially for high energy density electrode materials.

Hypothalamic Corticotropin-Releasing Hormone Contributes to Hypertension in Spontaneously Hypertensive Rats.

Corticotropin-releasing hormone (CRH) is a neuropeptide regulating neuroendocrine and autonomic function. CRH mRNA and protein levels in the hypothalamic paraventricular nucleus (PVN) are increased in primary hypertension. However, the role of CRH in elevated sympathetic outflow in primary hypertension remains unclear. CRHR1 proteins were distributed in retrogradely labeled PVN presympathetic neurons with an increased level in the PVN tissue in adult spontaneously hypertensive rats (SHRs) compared with age-matched male Wistar-Kyoto (WKY) rats. CRH induced a more significant increase in the firing rate of PVN-rostral ventrolateral medulla (RVLM) neurons and sympathoexcitatory response in SHRs than in WKY rats, an effect that was blocked by preapplication of NMDA receptors (NMDARs) antagonist AP5 and PSD-95 inhibitor, Tat-N-dimer. Blocking CRHRs with astressin or CRHR1 with NBI35965 significantly decreased the firing rate of PVN-RVLM output neurons and reduced arterial blood pressure (ABP) and renal sympathetic nerve activity (RSNA) in SHRs but not in WKY, whereas blocking CRHR2 with antisauvagine-30 did not. Furthermore, Immunocytochemistry staining revealed that CRHR1 colocalized with NMDARs in PVN presympathetic neurons. Blocking CRHRs significantly decreased the NMDA currents in labeled PVN neurons. PSD-95-bound CRHR1 and PSD-95-bound GluN2A in the PVN were increased in SHRs. These data suggested that the upregulation of CRHR1 in the PVN is critically involved in the hyperactivity of PVN presympathetic neurons and elevated sympathetic outflow in primary hypertension.SIGNIFICANCE STATEMENT Our study found that corticotropin-releasing hormone receptor (CRHR)1 protein levels were increased in the paraventricular nucleus (PVN), and CRHR1 interacts with NMDA receptors (NMDARs) through postsynaptic density protein (PSD)-95 in the PVN neurons in primary hypertension. The increased CRHR1 and CRHR1-NMDAR-PSD-95 complex in the PVN contribute to the hyperactivity of the PVN presympathetic neurons and elevated sympathetic vasomotor tone in hypertension in SHRs. Thus, the antagonism of CRHR1 decreases sympathetic outflow and blood pressure in hypertension. These findings determine a novel role of CRHR1 in elevated sympathetic vasomotor tone in hypertension, which is useful for developing novel therapeutics targeting CRHR1 to treat elevated sympathetic outflow in primary hypertension. The CRHR1 receptor antagonists, which are used to treat health consequences resulting from chronic stress, are candidates to treat primary hypertension.

Astrocyte-TREM2 alleviates brain injury by regulating reactive astrocyte states following ischemic stroke.

Triggering receptor expressed on myeloid cells 2 (TREM2) has been shown to confer strong neuroprotective effects in acute ischemic stroke (AIS). However, as the vast majority of research findings to date are based on its functions in microglia, the precise role of TREM2 in astrocytes after AIS is unknown. Here, both loss- and gain-of-function experiments were employed to investigate how astrocytic TREM2 influences the pathogenesis of AIS in vivo and in vitro. Our results demonstrated that cerebral ischemia triggered induction of TREM2 expression on reactive astrocytes following AIS. In addition, astrocyte-specific TREM2 knockout mice exhibited much greater brain injury than TREM2 flox/flox controls following AIS, as evidenced by increased cerebral infarct volume, neuronal apoptosis and neurological deficit, which was associated with an increased expression of pro-inflammatory molecule complement component 3 (C3) on reactive astrocytes and activation of microglia/macrophages but decreased expression of S100 calcium binding protein A10 (S100A10) and arginase1 (Arg1) on reactive astrocytes. Mechanistic analyses revealed that astrocytic TREM2 alleviated brain injury by inhibiting detrimental actions of reactive astrocytes but promoting their neuro- and glioprotective actions via the kruppel-like transcription factor-4-nuclear factor-κB axis. Together, this study provides novel evidence for a critical protective role of astrocyte-derived TREM2 in AIS and highlights a potential therapeutic target for the treatment of AIS.

Queen bee gut microbiota extends honeybee lifespan by inhibiting insulin signaling.

Queen and worker bees are natural models for aging research, as their lifespans vary considerably independent of genetic variation. Investigating the reasons why queens live longer than workers is of great significance for research on the universal processes of aging in animals. The gut microbiome has received attention as a vital regulator of host health, while its precise role in honeybee aging needs further investigation. The effects and mechanisms behind the relationship between gut microbiota and worker lifespan were measured by transplanting queen bee gut bacteria (QG) and worker bee gut bacteria (WG) into microbiota-free (MF) workers. The transplantation of QG to MF bees significantly extended the workers' lifespans compared with MF and WG bees. Untargeted metabolomics identified 49 lifespan-related differential metabolites, and Kyoto Encyclopedia of Genes and Genomes analysis of these revealed three lifespan-related metabolic pathways: insulin/insulin-like growth factor signaling, immune, and ketone body metabolism pathways. Further verification showed that QG inhibited the expression of insulin-like peptides (ILPs), and the expression of ILPs was lower in natural queens than in natural workers. QG transplantation also stimulated the expression of antioxidant genes and lowered oxidative damage products in natural queen bees. However, gut microbiota transplantation failed to mimic the immune properties and ketone body metabolism profiles of natural queens and workers. Concisely, QG could increase the antioxidant capacity to extend lifespan by inhibiting insulin signaling. These findings may help determine the mechanisms behind queen longevity and provide further insights into the role of gut symbionts. IMPORTANCE: Queen and worker bees share the same genetic background but have vastly different lifespans. The gut microbiome regulates host health, suggesting that differences in lifespan between queen and worker bees could be related to gut bacteria. Herein, we used an innovative method to transplant gut microbiota from adult queen or worker bees to microbiota-free bees. The transplantation of queen gut microbiota to microbiota-free bees extended their lifespan. Insulin/insulin-like growth factor signaling, a highly conserved metabolic pathway related to lifespan, displayed identical expression profiles in natural queen bees and microbiota-free bees transplanted with queen microbiota. This finding significantly expands our understanding of the relationships between intestinal bacteria, host health, and the biology of aging.

4 mC site recognition algorithm based on pruned pre-trained DNABert-Pruning model and fused artificial feature encoding.

DNA 4 mC plays a crucial role in the genetic expression process of organisms. However, existing deep learning algorithms have shortcomings in the ability to represent DNA sequence features. In this paper, we propose a 4 mC site identification algorithm, DNABert-4mC, based on a fusion of the pruned pre-training DNABert-Pruning model and artificial feature encoding to identify 4 mC sites. The algorithm prunes and compresses the DNABert model, resulting in the pruned pre-training model DNABert-Pruning. This model reduces the number of parameters and removes redundancy from output features, yielding more precise feature representations while upholding accuracy.Simultaneously, the algorithm constructs an artificial feature encoding module to assist the DNABert-Pruning model in feature representation, effectively supplementing the information that is missing from the pre-trained features. The algorithm also introduces the AFF-4mC fusion strategy, which combines artificial feature encoding with the DNABert-Pruning model, to improve the feature representation capability of DNA sequences in multi-semantic spaces and better extract 4 mC sites and the distribution of nucleotide importance within the sequence. In experiments on six independent test sets, the DNABert-4mC algorithm achieved an average AUC value of 93.81%, outperforming seven other advanced algorithms with improvements of 2.05%, 5.02%, 11.32%, 5.90%, 12.02%, 2.42% and 2.34%, respectively.

Repair of Limb Ischemia Is Dependent on Hematopoietic Stem Cell Specific-SHP-1 Regulation of TGF-ß1.

BACKGROUND: Hematopoietic stem cell (HSC) therapy has shown promise for tissue regeneration after ischemia. Therefore, there is a need to understand mechanisms underlying endogenous HSCs activation in response to ischemic stress and coordination of angiogenesis and repair. SHP-1 plays important roles in HSC quiescence and differentiation by regulation of TGF-ß1 signaling. TGF-ß1 promotes angiogenesis by stimulating stem cells to secrete growth factors to initiate the formation of blood vessels and later aid in their maturation. We propose that SHP-1 responds to ischemia stress in HSC and progenitor cells (HSPC) via regulation of TGF-ß1. METHODS: A mouse hind limb ischemia model was used. Local blood perfusion in the limbs was determined using laser doppler perfusion imaging. The number of positive blood vessels per square millimeter, as well as blood vessel diameter (µm) and area (µm2), were calculated. Hematopoietic cells were analyzed using flow cytometry. The bone marrow transplantation assay was performed to measure HSC reconstitution. RESULTS: After femoral artery ligation, TGF-ß1 was initially decreased in the bone marrow by day 3 of ischemia, followed by an increase on day 7. This pattern was opposite to that in the peripheral blood, which is concordant with the response of HSC to ischemic stress. In contrast, SHP-1 deficiency in HSC is associated with irreversible activation of HSPCs in the bone marrow and increased circulating HSPCs in peripheral blood following limb ischemia. In addition, there was augmented auto-induction of TGF-ß1 and sustained inactivation of SHP-1-Smad2 signaling, which impacted TGF-ß1 expression in HSPCs in circulation. Importantly, restoration of normal T GF-ß1 oscillations helped in the recovery of limb repair and function. CONCLUSIONS: HSPC-SHP-1-mediated regulation of TGF-ß1 in both bone marrow and peripheral blood is required for a normal response to ischemic stress.

HPTRMF: Collaborative Matrix Factorization-Based Prediction Method for LncRNA-Disease Associations Using High-Order Perturbation and Flexible Trifactor Regularization.

Existing matrix factorization methods face challenges, including the cold start problem and global nonlinear data loss during similarity learning, particularly in predicting associations between long noncoding RNAs (LncRNAs) and diseases. To overcome these issues, we introduce HPTRMF, a matrix factorization approach incorporating high-order perturbation and flexible trifactor regularization. HPTRMF constructs a high-order correlation matrix utilizing the known association matrix, leveraging high-order perturbation to effectively address the cold start problem caused by data sparsity. Additionally, HPTRMF incorporates a flexible trifactor regularization term to capture similarity information on LncRNAs and diseases, enabling the effective handling of global nonlinear data loss by capturing such data in the similarity matrix. Experimental results demonstrate the superiority of HPTRMF over nine state-of-the-art algorithms in Leave-One-Out Cross-Validation (LOOCV) and Five-Fold Cross-Validation (5-Fold CV) on three data sets.HPTRMF and data sets are available in https://github.com/Llvvvv/HPTRMF.

Association of dietary selenium intake and all-cause mortality of Parkinson's disease and its interaction with blood cadmium level: a retrospective cohort study.

BACKGROUND: Parkinson's disease (PD) is a slowly progressive neurodegenerating disease that may eventually lead to disabling condition and pose a threat to the health of aging populations. This study aimed to explore the association of two potential risk factors, selenium and cadmium, with the prognosis of Parkinson's disease as well as their interaction effect. METHODS: Data were obtained from the National Health and Nutrition Examination Survey (NHANES) 2005-2006 to 2015-2016 and National Death Index (NDI). Participants were classified as Parkinson's patients by self-reported anti-Parkinson medications usage. Cox regression models and restricted cubic spline models were applied to evaluate the association between PD mortality and selenium intake level as well as blood cadmium level. Subgroup analysis was also conducted to explore the interaction between them. RESULTS: A total of 184 individuals were included. In full adjusted cox regression model (adjusted for age, gender, race, hypertension, pesticide exposure, smoking status and caffeine intake), compared with participants with low selenium intake, those with normal selenium intake level were significantly associated with less risk of death (95%CI: 0.18-0.76, P = 0.005) while no significant association was found between low selenium intake group and high selenium group (95%CI: 0.16-1.20, P = 0.112). Restricted cubic spline model indicated a nonlinear relationship between selenium intake and PD mortality (P for nonlinearity = 0.050). The association between PD mortality and blood cadmium level was not significant (95%CI: 0.19-5.57, P = 0.112). However, the interaction term of selenium intake and blood cadmium showed significance in the cox model (P for interaction = 0.048). Subgroup analysis showed that the significant protective effect of selenium intake existed in populations with high blood cadmium but not in populations with low blood cadmium. CONCLUSION: Moderate increase of selenium intake had a protective effect on PD mortality especially in high blood cadmium populations.

The gene AccCyclin H mitigates oxidative stress by influencing trehalose metabolism in Apis cerana cerana.

BACKGROUND: Environmental stress can induce oxidative stress in Apis cerana cerana, leading to cellular oxidative damage, reduced vitality, and even death. Currently, owing to an incomplete understanding of the molecular mechanisms by which A. cerana cerana resists oxidative damage, there is no available method to mitigate the risk of this type of damage. Cyclin plays an important role in cell stress resistance. The aim of this study was to explore the in vivo protection of cyclin H against oxidative damage induced by abiotic stress in A. cerana cerana and clarify the mechanism of action. We isolated and identified the AccCyclin H gene in A. cerana cerana and analysed its responses to different exogenous stresses. RESULTS: The results showed that different oxidative stressors can induce or inhibit the expression of AccCyclin H. After RNA-interference-mediated AccCyclin H silencing, the activity of antioxidant-related genes and related enzymes was inhibited, and trehalose metabolism was reduced. AccCyclin H gene silencing reduced A. cerana cerana high-temperature tolerance. Exogenous trehalose supplementation enhanced the total antioxidant capacity of A. cerana cerana, reduced the accumulation of oxidants, and improved the viability of A. cerana cerana under high-temperature stress. CONCLUSION: Our findings suggest that trehalose can alleviate adverse stress and that AccCyclin H may participate in oxidative stress reactions by regulating trehalose metabolism. © 2023 Society of Chemical Industry.

CT Radiomics to Predict Macrotrabecular-Massive Subtype and Immune Status in Hepatocellular Carcinoma.

Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is an aggressive variant associated with angiogenesis and immunosuppressive tumor microenvironment, which is expected to be noninvasively identified using radiomics approaches. Purpose To construct a CT radiomics model to predict the MTM subtype and to investigate the underlying immune infiltration patterns. Materials and Methods This study included five retrospective data sets and one prospective data set from three academic medical centers between January 2015 and December 2021. The preoperative liver contrast-enhanced CT studies of 365 adult patients with resected HCC were evaluated. The Third Xiangya Hospital of Central South University provided the training set and internal test set, while Yueyang Central Hospital and Hunan Cancer Hospital provided the external test sets. Radiomic features were extracted and used to develop a radiomics model with machine learning in the training set, and the performance was verified in the two test sets. The outcomes cohort, including 58 adult patients with advanced HCC undergoing transarterial chemoembolization and antiangiogenic therapy, was used to evaluate the predictive value of the radiomics model for progression-free survival (PFS). Bulk RNA sequencing of tumors from 41 patients in The Cancer Genome Atlas (TCGA) and single-cell RNA sequencing from seven prospectively enrolled participants were used to investigate the radiomics-related immune infiltration patterns. Area under the receiver operating characteristics curve of the radiomics model was calculated, and Cox proportional regression was performed to identify predictors of PFS. Results Among 365 patients (mean age, 55 years ± 10 [SD]; 319 men) used for radiomics modeling, 122 (33%) were confirmed to have the MTM subtype. The radiomics model included 11 radiomic features and showed good performance for predicting the MTM subtype, with AUCs of 0.84, 0.80, and 0.74 in the training set, internal test set, and external test set, respectively. A low radiomics model score relative to the median value in the outcomes cohort was independently associated with PFS (hazard ratio, 0.4; 95% CI: 0.2, 0.8; P = .01). The radiomics model was associated with dysregulated humoral immunity involving B-cell infiltration and immunoglobulin synthesis. Conclusion Accurate prediction of the macrotrabecular-massive subtype in patients with hepatocellular carcinoma was achieved using a CT radiomics model, which was also associated with defective humoral immunity. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Yoon and Kim in this issue.

Ame-miR-980-3p participates in autophagy-mediated midgut remodelling in Apis mellifera via targeting Atg2B.

Autophagy is a process that serves to degrade damaged proteins and organelles, thereby promoting cell homeostasis, differentiation, development and survival. Many miRNAs have been found to have regulatory roles in autophagy. In insects, it has been shown that autophagy is involved in hormone-regulated programmed cell death during metamorphic midgut remodelling. However, whether this is also true during the remodelling of the honey bee midgut is unclear. In the present study, we explored the relationship between autophagy and midgut remodelling and sought to identify miRNAs involved in this physiological process. We found that autophagy occurred during midgut remodelling and that the inhibition of autophagy resulted in midgut dysplasia in prepupae. Differentially expressed miRNAs enriched in the autophagy signalling pathway during midgut remodelling were identified by small RNA-seq. Ame-miR-980-3p, which targets the autophagy-related gene Atg2B, was screened out. Furthermore, abnormal expression of ame-miR-980-3p in the pupal stage led to the thinning of the midgut wall of newly emerged bees (NE). When ame-miR-980-3p expression was inhibited, the intestinal villi of NE bees became significantly shorter and sparse, and the lipid signal in the peritrophic matrix of Pb almost disappeared, indicating that the adult midgut was underdeveloped and the lipid absorption ability was weakened. Taken together, ame-miR-980-3p targeted Atg2B to participate in the regulation of midgut autophagy in the pupae, and the abnormal expression of ame-miR-980-3p would interfere with cell proliferation and death in the process of midgut remodelling, hinder the formation of adult midgut and eventually lead to adult midgut dysplasia and affect the lipid absorption function of the midgut in Apis mellifera.

Causal associations between chronic hepatitis B and COVID-19 in East Asian populations.

BACKGROUND: The relationship between chronic hepatitis B (CHB) and Coronavirus disease 2019 (COVID-19) has been inconsistent in traditional observational studies. METHODS: We explored the total causal and direct causal associations between CHB and the three COVID-19 outcomes using univariate and multivariate Mendelian randomization (MR) analyses, respectively. Genome-wide association study datasets for CHB and COVID-19 were obtained from the Japan Biobank and the COVID-19 Host Genetics Initiative, respectively. RESULTS: Univariate MR analysis showed that CHB increased the risk of SARS-CoV-2 infection (OR = 1.04, 95% CI 1.01-1.07, P = 3.39E-03), hospitalized COVID-19 (OR = 1.10, 95% CI 1.06-1.13, P = 7.31E-08), and severe COVID-19 (OR = 1.16, 95%CI 1.08-1.26, P = 1.43E-04). A series of subsequent sensitivity analyses ensured the stability and reliability of these results. In multivariable MR analyses adjusting for type 2 diabetes, body mass index, basophil count, and smoking, genetically related CHB is still positively associated with increased risk of SARS-CoV-2 infection (OR = 1.06, 95% CI 1.02-1.11, P = 1.44E-03) and hospitalized COVID-19 (OR = 1.12, 95% CI 1.07-1.16, P = 5.13E-07). However, the causal link between CHB and severe COVID-19 was attenuated after adjustment for the above variables. In addition, the MR analysis did not support the causal effect of COVID-19 on CHB. CONCLUSIONS: This study provides evidence that CHB increases COVID-19 susceptibility and severity among individuals of East Asian ancestry.

Characterization of photochemical losses of volatile organic compounds and their implications for ozone formation potential and source apportionment during summer in suburban Jinan, China.

Volatile organic compounds (VOCs) undergo substantial photochemical losses during their transport from emission sources to receptor sites, resulting in serious implications for their source apportionment and ozone (O3) formation. Based on the continuous measurements of VOCs in suburban Jinan in August 2022, the effects of photochemical losses on VOC source contributions and O3 formation were evaluated in this study. The observed and initial concentrations of total VOCs (TVOC) were 12.0 ± 5.1 and 16.0 ± 7.4 ppbv, respectively. Throughout the observation period, alkenes had the most prominent photochemical losses (58.2%), followed by aromatic hydrocarbons (23.1%), accounting for 80.6% and 6.9% of the total losses, respectively. During high O3 episodes, the photochemical loss of VOCs was 6.9 times higher than that during the cleaning period. Alkene losses (exceeding 67.3%), specifically losses of isoprene, propylene, ethylene, and n-butene, dominated the total losses of VOCs during the O3 increase period. Eight sources of VOCs were identified by positive matrix factorization (PMF) based on the observed and initial concentration data (OC-PMF and IC-PMF, respectively). Concentrations of all emission sources in the OC-PMF were underestimated by 2.4%-57.1%. Moreover, the contribution of each emission source was over- or underestimated compared with that in case of the IC-PMF. The contributions of biogenic and motor vehicle exhaust emissions were underestimated by 5.3 and 2.8 percentage points, respectively, which was associated with substantial oxidation of the emitted high-reactive species. The contributions of coal/biomass burning and natural gas were overestimated by 2.4 and 3.9 percentage points, respectively, which were related to the emission of low-reactive species (acetylene, ethane, and propane). Based on our results, the photochemical losses of VOCs grossly affect their source apportionment and O3 formation. Thus, photochemical losses of VOCs must be thoroughly accounted to establish a precise scientific foundation for air-pollution control strategies.

Honey bee larval culture in vitro: gut emptying determines the transition from larva to prepupa and recombinant AccApidaecin improves antibacterial activity.

In vitro rearing of honey bee larvae is ideal for bioassay studies; no honey bee stable cell lines are available. Inconsistency of internal development staging of reared larvae and a susceptibility to contamination are common problems encountered. Standardized protocols on rearing larvae in vitro to make the larvae growth and development more similar to that of natural colonies are necessary to ensure the accuracy of experimental results and promote honey bee research as a model organism. Here, we concluded that when larval fasting weight was >160 mg, the time point of gut emptying can be defined as the critical point separating the larval and prepupal stages. In this way, we can conduct precise studies on the prepupal stage, such as organ remodeling during metamorphosis. Simultaneously, we further verified that recombinant AccApidaecin in genetic engineered bacteria added to the larval diet upregulated antibacterial peptide gene expression, and did not stimulate the stress response in larvae, nor did it affect the pupation rate or eclosion rate. This demonstrated that feeding recombinant AccApidaecin can enhance the individual antibacterial ability at the molecular level.

Role of the tyrosine aminotransferase AccTATN gene in the response to pesticide and heavy metal stress in Apis cerana cerana.

Tyrosine aminotransferase (TATN) is the first enzyme involved in the metabolic degradation of tyrosine, and it plays an important role in tyrosine detoxification and helps the body resist oxidative damage. However, the function of TATN in Apis cerana cerana (A. c. cerana) remains unclear. To explore the role of TATN in the response to pesticide and heavy metal stress in A. c. cerana, AccTATN was isolated and identified. AccTATN was highly expressed in the integument and the adult stage. Exposure to multiple pesticides and heavy metal stress upregulated AccTATN expression. RNA interference experiments showed that silencing AccTATN reduced the resistance of A. c. cerana to glyphosate and avermectins stress. The expression of antioxidant-related genes and the activity of antioxidant enzymes were reduced after AccTATN was silenced, leading to the accumulation of oxidative damage. Overexpression of the recombinant AccTATN protein in a prokaryotic system also confirmed its role in heavy metal stress and improved antioxidant capacity. Our study showed that AccTATN may promote resistance to pesticide and heavy metal stress by regulating the antioxidant capacity of A. c. cerana. This study provides a valuable theoretical basis for A. c. cerana conservation.

The role of AccCDK20 and AccCDKN1 from Apis cerana cerana in development and response to pesticide and heavy metal toxicity.

Apis cerana cerana is a native bee species in China and plays a key role in agricultural production and ecological balance. However, the growth and development of Apis cerana cerana has not been smooth, and pesticide and heavy metal stress are key factors that have forced a dramatic decline in population size. This study was performed with the objective of investigating the role of AccCDK20 and AccCDKN1 in honey bee resistance to pesticide and heavy metal stress. RT-qPCR analysis revealed that AccCDK20 transcript levels were highest in brown-eyed pupae and AccCDKN1 transcript levels were highest in 1-day-old worker bees. In different tissues and body parts of adult bees, AccCDK20 transcript levels were highest in the head, and AccCDKN1 transcript levels were highest in the thorax. It was further observed that environmental stress can affect the transcript levels of the AccCDK20 and AccCDKN1 genes. Silencing of the AccCDK20 and AccCDKN1 genes resulted in altered activities of antioxidant-related genes and antioxidant-related enzymes. AccCDK20 and AccCDKN1 transcript levels were upregulated under glyphosate stress, and silencing of the genes resulted in reduced resistance to glyphosate and greatly increased mortality in Apis cerana cerana. In addition, gene function was verified by in vitro repression assays. Overexpression of the AccCDK20 and AccCDKN1 proteins in E. coli cells increased the resistance to ROS damage induced by CHP. In conclusion, AccCDK20 and AccCDKN1 play an indispensable role in honey bee resistance to pesticide and heavy metal stress.

RNAi-mediated silencing of AccCYP6k1 revealed its role in the metabolic detoxification of Apis cerana cerana.

Insect cytochrome P450 monooxygenases (P450s or CYPs) perform important functions in the metabolic detoxification of both endogenous and exogenous substrates. However, the mechanism of action of the P450 genes in bees is unclear. In this study, we investigated the effects of AccCYP6k1 on the metabolism and detoxification of Apis cerana cerana. Spatiotemporal expression profiling revealed that the expression of AccCYP6k1 was the highest in foragers (A15) and was mainly expressed in the leg, midgut and head. RT-qPCR results showed that AccCYP6k1 exhibited different expression patterns following exposure to xenobiotics. In addition, silencing AccCYP6k1 increased the pesticides sensitivity and affected the detoxification system and antioxidant process of A. cerana cerana. In brief, the induced expression of AccCYP6k1 is related to the resistance of A. cerana cerana, while knockdown AccCYP6k1 affect the pesticides resistance and metabolic detoxification system of A. cerana cerana. These findings not only support the theoretical basis of metabolic detoxification in bees but also provide a better understanding of P450-mediated resistance to pesticides in insects.

The latest research progress on minimally invasive treatments for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer-related death worldwide. Due to the high prevalence of hepatitis B virus (HBV) infection in China, the incidence of HCC in China is high, and liver cirrhosis caused by chronic hepatitis also brings great challenges to treatment. This paper reviewed the latest research progress on minimally invasive treatments for HCC, including percutaneous thermal ablation and new nonthermal ablation techniques, and introduced the principles, advantages, and clinical applications of various therapeutic methods in detail. DATA SOURCES: The data of treatments for HCC were systematically collected from the PubMed, ScienceDirect, American Chemical Society and Web of Science databases published in English, using "minimally invasive" and "hepatocellular carcinoma" or "liver cancer" as the keywords. RESULTS: Percutaneous thermal ablation is still a first-line strategy for the minimally invasive treatment of HCC. The effect of microwave ablation (MWA) on downgrading treatment before liver transplantation is better than that of radiofrequency ablation (RFA), while RFA is more widely used in the clinical practice. High-intensity focused ultrasound (HIFU) is mainly used for the palliative treatment of advanced liver cancer. Electrochemotherapy (ECT) delivers chemotherapeutic drugs to the target cells while reducing the blood supply around HCC. Irreversible electroporation (IRE) uses a microsecond-pulsed electric field that induces apoptosis and necrosis and triggers a systemic immune response. The nanosecond pulsed electric field (nsPEF) has achieved a good response in the ablation of mice with HCC, but it has not been reported in China for the treatment of human HCC. CONCLUSIONS: A variety of minimally invasive treatments provide a sufficient survival advantage for HCC patients. Nonthermal ablation will lead to a new wave with its unique advantage of antitumor recurrence and metastasis.

Grad-MobileNet: A Gradient-Based Unsupervised Learning Method for Laser Welding Surface Defect Classification.

Deep learning technology has advanced rapidly and has started to be applied for the detection of welding defects. In the manufacturing process of power batteries for new energy vehicles, welding defects may occur due to the high directivity, convergence, and penetration of the laser beam. The accuracy of deep learning prediction relies heavily on big data, but balanced big data of welding defects is hard to acquire at the battery production site. In this paper, the authors construct a dataset named RIAM, which consists of images captured from an industrial environment for laser welding of power battery modules. RIAM contains four types of images: Normality, Lack of fusion, Surface porosity, and Scaled surface. The characteristics of RIAM are carefully considered in the application scenarios. Moreover, this paper proposes a gradient-based unsupervised model named Grad-MobileNet, which can be trained with only a few normal images and can extract the feature gradients of the input images. Welding defects can then be classified by the gradient distribution. This model is based on MobileNetV3, which is a lightweight convolutional neural network (CNN), and achieves 99% accuracy, which is higher than the accuracy expected from supervised learning.