A novel prognostic signature based on cancer stemness and metabolism-related genes for cervical squamous cell carcinoma and endocervical adenocarcinoma.

BACKGROUND: CESC is the second most commonly diagnosed gynecological malignancy. Given the pivotal involvement of metabolism-related genes (MRGs) in the etiology of multiple tumors, our investigation aims to devise a prognostic risk signature rooted in cancer stemness and metabolism. METHODS: The stemness index based on mRNA expression (mRNAsi) of samples from the TCGA dataset was computed using the One-class logistic regression (OCLR) algorithm. Furthermore, potential metabolism-related genes related to mRNAsi were identified through weighted gene co-expression network analysis (WGCNA). We construct a stemness-related metabolic gene signature through shrinkage estimation and univariate analysis, thereby calculating the corresponding risk scores. Moreover, we selected corresponding DEGs between groups with high- and low-risk score and conducted routine bioinformatic analyses. Furthermore, we validated the expression of four hub genes at the protein level through immunohistochemistry (IHC) in samples obtained from our patient cohort. RESULTS: According to the findings, it was found that six genes-AKR1B10, GNA15, ALDH1B1, PLOD2, LPCAT1, and GPX8- were differentially expressed in both TCGA-CSEC and GEO datasets among 23 differentially expressed metabolism-related genes (DEMRGs). mRNAsi exhibited a notable association with the extent of key oncogene mutation. The results showed that the AUC values for forecasting survival at 1, 3, and 5 years are 0.715, 0.689, and 0.748, individually. We observed a notable association between the risk score and different immune cell populations, along with enrichment in crucial signaling pathways in CESC. Four genes differentially expressed between different risk score groups were validated by IHC to be highly expressed in the CESC samples at the protein level. CONCLUSION: The current investigation indicated that a 3-gene signature based on stemness-related metabolic and 4 hub genes with differential expression between high and low-risk score subgroups may serve as valuable prognostic markers and potential therapeutic targets in CESC.

DACNN-aided nonlinear equalizer for a probabilistic shaping coherent optical communication system.

The probabilistic shaping (PS) technique is a key technology for fiber optic communication systems to further approach the Shannon limit. To solve the problem that nonlinear equalizers are ineffective for probabilistic shaping optical communication systems with non-uniform distribution, a distribution alignment convolutional neural network (DACNN)-aided nonlinear equalizer is proposed. The approach calibrates the equalizer using the probabilistic shaping prior distribution, which reduces the training complexity and improves the performance of the equalizer simultaneously. Experimental results show nonlinear equalization of 120 Gb/s PS 64QAM signals in a 375 km transmission scenario. The proposed DACNN equalizer improves the receiver sensitivity by 2.6 dB and 1.1 dB over the Volterra equalizer and convolutional neural network (CNN) equalizer, respectively. Meanwhile, DACNN converges with fewer training epochs than CNN, which provides great potential for mitigating the nonlinear distortion of PS signals in fiber optic communication systems.

OAM mode-division multiplexing IM/DD transmission at 4.32†Tbit/s with a low-complexity adaptive-network-based fuzzy inference system nonlinear equalizer.

Stochastic nonlinear impairment is the primary factor that limits the transmission performance of high-speed orbital angular momentum (OAM) mode-division multiplexing (MDM) optical fiber communication systems. This Letter presents a low-complexity adaptive-network-based fuzzy inference system (LANFIS) nonlinear equalizer for OAM-MDM intensity-modulation direct-detection (IM/DD) transmission with three OAM modes and 15 wavelength division multiplex (WDM) channels. The LANFIS equalizer could adjust the probability distribution functions (PDFs) of the distorted pulse amplitude modulation (PAM) symbols to fit the statistical characteristics of the WDM-OAM-MDM transmission channel. Therefore, although the transmission symbols in the WDM-OAM-MDM system are subjected to a stochastic nonlinear impairment, the proposed LANFIS equalizer can effectively compensate the distorted signals. The proposed equalizer outperforms the Volterra equalizer with improvements in receiver sensitivity of 2, 1.5, and 1.3 dB for three OAM modes at a wavelength of 1550.12 nm, respectively. It also outperforms a CNN equalizer, with improvements in receiver sensitivity of 1, 0.5, and 0.3 dB, respectively. Moreover, complexity reductions of 67%, 74%, and 99.9% are achieved for the LANFIS equalizer compared with the Volterra, CNN, and ANFIS equalizers, respectively. The proposed equalizer has high performance and low complexity, making it a promising candidate for a high-speed WDM-OAM-MDM system.

HBP1 promotes chicken preadipocyte proliferation via directly repressing SOCS3 transcription.

Preadipocyte proliferation is an essential process in adipose development. During proliferation of preadipocytes, transcription factors play crucial roles. HMG-box protein 1 (HBP1) is an important transcription factor of cellular proliferation. However, the function and underlying mechanisms of HBP1 in the proliferation of preadipocytes remain unclear. Here, we found that the expression level of HBP1 decreased first and then increased during the proliferation of chicken preadipocytes. Knockout of HBP1 could inhibit the proliferation of preadipocytes, while overexpression of HBP1 could promote the proliferation of preadipocytes. ChIP-seq data showed that HBP1 had the unique DNA binding motif in chicken preadipocytes. By integrating ChIP-Seq and RNA-Seq, we revealed a total of 3 candidate target genes of HBP1. Furthermore, the results of ChIP-qPCR, RT-qPCR, luciferase reporter assay and EMSA showed that HBP1 could inhibit the transcription of suppressor of cytokine signaling 3 (SOCS3) by binding to its promoter. Moreover, we confirmed that SOCS3 can mediate the regulation of HBP1 on the proliferation of preadipocytes through RNAi and rescue experiments. Altogether, these data demonstrated that HBP1 directly targets SOCS3 to regulate chicken preadipocyte proliferation. Our findings expand the transcriptional regulatory network of preadipocyte proliferation, and they will be helpful in formulating a molecular breeding scheme to control excessive abdominal fat deposition and to improve meat quality in chickens.

Comparative analyses of laying performance and follicular development characteristics between fat and lean broiler lines.

The deposition of high levels of fat in broiler breeder hens can have a profound impact on follicular development and laying performance. This study was formulated with the goal of comparing egg production and follicular development characteristics at different laying stages in the Northeast Agricultural University broiler lines divergently selected for abdominal fat content (NEAUHLF). The egg production was analyzed using the birds from the 19th to 24th generations of NEAUHLF; the follicular development characteristics were analyzed by hematoxylin-eosin staining and quantitative real-time polymerase chain reaction using the birds from the 24th generation of NEAUHLF. The results showed that the age at first egg of lean hens was significantly earlier than that of fat hens in this study. While no significant differences in total egg output from the first egg to 50 wk of age were noted when comparing these 2 chicken lines, lean hens laid more eggs from the first egg to 35 wk of age relative to fat hens, whereas fat hens laid more eggs from wk 36 to 42 and 43 to 50 relative to their lean counterparts. No differences in ovarian morphology and small yellow follicle (SYF) histological characteristics were noted when comparing these 2 chicken lines at 27 wk of age. At 35 and 52 wk of age, however, lean hens exhibited significantly lower ovarian weight, ovarian proportion values, numbers of hierarchical follicles, hierarchical follicle weight, and SYF granulosa layer thickness as compared to fat hens, together with a significant increase in the number of prehierarchical follicles relative to those in fat hens. Gene expression analyses suggested that follicle selection was impaired in the fat hens in the early laying stage, whereas both follicle selection and maturation were impaired in the lean hens in the middle and late laying stages. Overall, these data highlight that fat deposition in broiler hens can have a range of effects on follicular development and egg production that are laying stage-dependent.

Aggregation-Induced Emission-Based Macrophage-Like Nanoparticles for Targeted Photothermal Therapy and Virus Transmission Blockage in Monkeypox.

The recent prevalence of monkeypox has led to the declaration of a Public Health Emergency of International Concern. Monkeypox lesions are typically ulcers or pustules (containing high titers of replication-competent virus) in the skin and mucous membranes, which allow monkeypox virus to transmit predominantly through intimate contact. Currently, effective clinical treatments for monkeypox are lacking, and strategies for blocking virus transmission are fraught with drawbacks. Herein, this work constructs a biomimetic nanotemplate (termed TBD@M NPs) with macrophage membranes as the coat and polymeric nanoparticles loading a versatile aggregation-induced emission featured photothermal molecule TPE-BT-DPTQ as the core. In a surrogate mouse model of monkeypox (vaccinia-virus-infected tail scarification model), intravenously injected TBD@M NPs show precise tracking and near-infrared region II fluorescence imaging of the lesions. Upon 808 nm laser irradiation, the virus is eliminated by the photothermal effect and the infected wound heals rapidly. More importantly, the inoculation of treated lesion tissue suspensions does not trigger tail infection or inflammatory activation in healthy mice, indicating successful blockage of virus transmission. This study demonstrates for the first time monkeypox theranostics using nanomedicine, and may bring a new insight into the development of a viable strategy for monkeypox management in clinical trials.

Oxylipin transport by lipoprotein particles and its functional implications for cardiometabolic and neurological disorders.

Lipoprotein metabolism is critical to inflammation. While the periphery and central nervous system (CNS) have separate yet connected lipoprotein systems, impaired lipoprotein metabolism is implicated in both cardiometabolic and neurological disorders. Despite the substantial investigation into the composition, structure and function of lipoproteins, the lipoprotein oxylipin profiles, their influence on lipoprotein functions, and their potential biological implications are unclear. Lipoproteins carry most of the circulating oxylipins. Importantly, lipoprotein-mediated oxylipin transport allows for endocrine signaling by these lipid mediators, long considered to have only autocrine and paracrine functions. Alterations in plasma lipoprotein oxylipin composition can directly impact inflammatory responses of lipoprotein metabolizing cells. Similar investigations of CNS lipoprotein oxylipins are non-existent to date. However, as APOE4 is associated with Alzheimer's disease-related microglia dysfunction and oxylipin dysregulation, ApoE4-dependent lipoprotein oxylipin modulation in neurological pathologies is suggested. Such investigations are crucial to bridge knowledge gaps linking oxylipin- and lipoprotein-related disorders in both periphery and CNS. Here, after providing a summary of existent literatures on lipoprotein oxylipin analysis methods, we emphasize the importance of lipoproteins in oxylipin transport and argue that understanding the compartmentalization and distribution of lipoprotein oxylipins may fundamentally alter our consideration of the roles of lipoprotein in cardiometabolic and neurological disorders.

Hidden conditional random field-based equalizer for the 3D-CAP-64 transmission of OAM mode-division multiplexed ring-core fiber communication.

As a key technique for achieving ultra-high capacity optical fiber communications, orbital angular momentum (OAM) mode-division multiplexing (MDM) is affected by severe nonlinear impairments, including modulation related nonlinearities, square-law nonlinearity and mode-coupling-induced nonlinearity. In this paper, an equalizer based on a hidden conditional random field (HCRF) is proposed for the nonlinear mitigation of OAM-MDM optical fiber communication systems with 20 GBaud three-dimensional carrierless amplitude and phase modulation-64 (3D-CAP-64) signals. The HCRF equalizer extracts the stochastic nonlinear feature of the OAM-MDM 3D-CAP-64 signals by estimating the conditional probabilities of the hidden variables, thereby enabling the signals to be classified into subclasses of constellation points. The nonlinear impairment can then be mitigated based on the statistical probability distribution of the hidden variables of the OAM-MDM transmission channel in the HCRF equalizer. Our experimental results show that compared with a convolutional neural network (CNN)-based equalizer, the proposed HCRF equalizer improves the receiver sensitivity by 2 dB and 1 dB for the two OAM modes used here, with l = + 2 and l = + 3, respectively, at the 7% forward error correction (FEC) threshold. When compared with a Volterra nonlinear equalizer (VNE) and CNN-based equalizer, the computational complexity of the proposed HCRF equalizer was found to be reduced by 30% and 41%, respectively. The bit error ratio (BER) performance and reduction in computational complexity indicate that the proposed HCRF equalizer has great potential to mitigate nonlinear distortions in high-speed OAM-MDM fiber communication systems.

Effects of early maternal separation on the expression levels of hippocampal and prefrontal cortex genes and pathways in lactating piglets.

Introduction: In actual production, due to increased litter size when raising pigs, the management of piglets by split-suckling leads to intermittent neonatal maternal separation (MS). Early lactation is a critical period for the cognitive development of the brain of newborn piglets, and we hypothesized that intermittent MS may affect piglets' neurodevelopment and cognitive ability. Methods: To determine the effects of the MS, we selected hippocampal and prefrontal cortex (PFC) tissues from piglets for the detection of neurodevelopmental or cognitive related indicators, the control group (Con group, n = 6) was established with no MS and an experimental group (MS group, n = 6) was established with MS for 6 h/day. Piglets in the MS group were milk-supplemented during the separation period and all piglets in both treatment groups were weaned at postnatal day (PND) 35. On PND 35, three male piglets from each group were sacrificed for hippocampus and PFC samples used for reference transcriptome sequencing. Following bioinformatics analysis, Gene ontology (GO) enrichment, Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, and candidate gene screening and pathway were performed for differentially expressed genes. Results: The results showed that a total of 1,632 differential genes were identified in the hippocampus of the MS group, including 1,077 up-regulated differential genes, 555 down-regulated differential genes, and 655 significant GO entries. Analysis of the PFC of the MS group revealed 349 up-regulated genes, 151 down-regulated differential genes, and 584 significant GO entries. Genes associated with neurodevelopment were screened for large fold differences in the hippocampus, and genes associated with cognition were screened for large fold differences in the PFC. Quantitative real-time PCR (qRT-PCR) was used to verify the sequencing data. Western blot (WB) experiments revealed that MS inhibited the neurodevelopment-related WNT signaling pathway in the hippocampus and the cognitive-related PI3K-AKT signaling pathway in the PFC. Discussion: Taken together, these findings suggest that intermittent MS may affect some cognitive functions in piglets by damaging hippocampal and PFC genes or pathways.

A pyroptosis-related gene signature that predicts immune infiltration and prognosis in colon cancer.

Background: Colon cancer (CC) is a highly heterogeneous malignancy associated with high morbidity and mortality. Pyroptosis is a type of programmed cell death characterized by an inflammatory response that can affect the tumor immune microenvironment and has potential prognostic and therapeutic value. The aim of this study was to evaluate the association between pyroptosis-related gene (PRG) expression and CC. Methods: Based on the expression profiles of PRGs, we classified CC samples from The Cancer Gene Atlas and Gene Expression Omnibus databases into different clusters by unsupervised clustering analysis. The best prognostic signature was screened and established using least absolute shrinkage and selection operator (LASSO) and multivariate COX regression analyses. Subsequently, a nomogram was established based on multivariate COX regression analysis. Next, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to explore the potential molecular mechanisms between the high- and low-risk groups and to explore the differences in clinicopathological characteristics, gene mutation characteristics, abundance of infiltrating immune cells, and immune microenvironment between the two groups. We also evaluated the association between common immune checkpoints and drug sensitivity using risk scores. The immunohistochemistry staining was utilized to confirm the expression of the selected genes in the prognostic model in CC. Results: The 1163 CC samples were divided into two clusters (clusters A and B) based on the expression profiles of the 33 PRGs. Genes with prognostic value were screened from the DEGs between the two clusters, and an eight PRGs prognostic model was constructed. GSEA and GSVA of the high- and low-risk groups revealed that they were mainly enriched in inflammatory response-related pathways. Compared to those in the low-risk group, patients in the high-risk group had worse overall survival, an immunosuppressive microenvironment, and worse sensitivity to immunotherapy and drug treatment. Conclusion: Our findings provide a foundation for future research targeting pyroptosis and new insights into prognosis and immunotherapy from the perspective of pyroptosis in CC.

400 Gbit/s 4 mode transmission for IM/DD OAM mode division multiplexing optical fiber communication with a few-shot learning-based AffinityNet nonlinear equalizer.

Nonlinear impairment in a high-speed orbital angular momentum (OAM) mode-division multiplexing (MDM) optical fiber communication system presents high complexity and strong stochasticity due to the massive optoelectronic devices. In this paper, we propose an Affinity Network (AffinityNet) nonlinear equalizer for an OAM-MDM intensity-modulation direct-detection (IM/DD) transmission with four OAM modes. The labeled training and testing signals from the OAM-MDM system can be regarded as "small sample" and "large target", respectively. AffinityNet can be used to build an accurate nonlinear model using "small sample" based on few-shot learning and can predict the stochastic characteristic nonlinearity of OAM-MDM with a high level of generalization. As a result, the AffinityNet nonlinear equalizer can effectively compensate the stochastic nonlinearity in the OAM-MDM system, despite the large difference between the training and testing signals due to the stochastic nonlinear impairment. An experiment was conducted on a 400 Gbit/s transmission with four OAM modes using a pulse amplitude modulation-8 (PAM-8) signal over a 2 km ring-core fiber (RCF). Our experimental results show that the proposed nonlinear equalizer outperformed the conventional Volterra equalizer with improvements in receiver sensitivity of 1.7, 1.8, 3, and 3.3 dB for the four OAM modes at the 15% forward error correction (FEC) threshold, respectively. In addition, the proposed equalizer outperformed a convolutional neural network (CNN) equalizer with improvements in receiver sensitivity of 0.8, 0.5, 0.9, and 1.4 dB for the four OAM modes at the 15% FEC threshold. In the experiment, a complexity reduction of 37% and 83% of the AffinityNet equalizer is taken compared to the conventional Volterra equalizer and CNN equalizer, respectively. The proposed equalizer is a promising candidate for a high-speed OAM-MDM optical fiber communication system.

Generalizing through Forgetting - Domain Generalization for Symptom Event Extraction in Clinical Notes.

Symptom information is primarily documented in free-text clinical notes and is not directly accessible for downstream applications. To address this challenge, information extraction approaches that can handle clinical language variation across different institutions and specialties are needed. In this paper, we present domain generalization for symptom extraction using pretraining and fine-tuning data that differs from the target domain in terms of institution and/or specialty and patient population. We extract symptom events using a transformer-based joint entity and relation extraction method. To reduce reliance on domain-specific features, we propose a domain generalization method that dynamically masks frequent symptoms words in the source domain. Additionally, we pretrain the transformer language model (LM) on task-related unlabeled texts for better representation. Our experiments indicate that masking and adaptive pretraining methods can significantly improve performance when the source domain is more distant from the target domain.

Identification and verification of ferroptosis-related genes in diabetic foot using bioinformatics analysis.

Ferroptosis is a novel form of cell death that plays a key role in several diseases, including inflammation and tumours; however, the role of ferroptosis-related genes in diabetic foot remains unclear. Herein, diabetic foot-related genes were downloaded from the Gene Expression Omnibus and the ferroptosis database (FerrDb). The least absolute shrinkage and selection operator regression algorithm was used to construct a related risk model, and differentially expressed genes were analysed through immune infiltration. Finally, we identified relevant core genes through a protein-protein interaction network, subsequently verified using immunohistochemistry. Comprehensive analysis showed 198 genes that were differentially expressed during ferroptosis. Based on functional enrichment analysis, these genes were primarily involved in cell response, chemical stimulation, and autophagy. Using the CIBERSORT algorithm, we calculated the immune infiltration of 22 different types of immune cells in diabetic foot and normal tissues. The protein-protein interaction network identified the hub gene TP53, and according to immunohistochemistry, the expression of TP53 was high in diabetic foot tissues but low in normal tissues. Accordingly, we identified the ferroptosis-related gene TP53 in the diabetic foot, which may play a key role in the pathogenesis of diabetic foot and could be used as a potential biomarker.

Effects of short-distance transportation on physiological indexes, intestinal morphology, microbial community, and the transcriptome of the jejunum in weaned piglets.

Transportation of livestock is unavoidable in animal production. A total of 72 piglets were randomly divided into the CON group and the TSG group, and the piglets in CON group were transported for two hours. The purpose of this study was to determine the effects of short-distance road transportation lasting 2 h on the jejunum of weaned piglets. Our results showed that compared with the control group, there was no impact on the growth performance of piglets in the transport group (P > 0.05). The concentrations of cortisol, heat shock protein (HSP)70, HSP90, C-reactive protein, interleukin (IL)-6, IL-8, IL-12, and interferon-γ and the activity of reactive oxygen species were increased in the jejunum of piglets in the transport group (P < 0.05 compared with the control group). The concentrations of glutathione peroxidase, claudin-1, occludin, and zonula occludens-1 showed no between-group differences (P > 0.05). Regarding intestinal morphology, the transport group showed infiltration of a small amount of lymphocytes into the jejunum mucosa epithelium that was accompanied by edema of the lamina propria, whereas the control group showed no obvious abnormalities. At the genus level, in the transport group, the 16S rRNA sequencing revealed a downward trend in the relative abundance of Lactobacillus and an upward trend in the relative abundance of Muribaculaceae_unclassified. There was also increased mRNA expression of genes associated with inflammation in the transport group, but the genes and pathways related to apoptosis were not activated. In summary, weaned piglets undergoing 2 h of short-distance road transportation showed stress and inflammatory reactions of the jejunum but did not exhibit oxidative damage or activation of the apoptosis pathway of the jejunum. Furthermore, the growth performance of the piglets was not affected by the trip.

Effects of early intermittent maternal separation on behavior, physiological, and growth performance in piglets.

In pig production, the management of piglets by batch lactation due to the increase in litter sizes of sows may result in intermittent early neonatal maternal separation (NMS). We speculated that NMS may affect the piglets cognitive growth performance and health. To determine the extent of the effect, 12 litters of crossbred piglets (Large White × Duroc × Min-pig) were used in this trial. Piglets in the control (Con) group (n = 6) were given a standard feeding method during lactation. Piglets in the experimental group (n = 6) were subjected to the NMS model, in which sows were led out of the enclosure with food every day (8:00-11:00 and 13:00-16:00) starting from postnatal day (PND) 7. During the separation, the piglets were supplemented with milk. All experimental piglets were weaned on PND 35. The piglets were observed for aggression, play, mutual sniffing, and exploratory behavior on PNDs 7, 8, 21, 22, 34, 35, 38, 39, 51, 52, 64, and 65. Physiological indicators, namely serum adrenaline, cortisol, interleukin (IL)-1ß, IL-4, IL-6, and tumor necrosis factor (TNF)-α were measured on PNDs 35, 38, and 65, while piglet growth performance was evaluated during suckling and 1 month after weaning. The results showed that aggressive behavior in the MS group was significantly higher than that in the Con group (P < 0.05). Playful and mutual sniffing behaviors in the MS group were significantly lower than those in the Con group except for PNDs 38 and 39 (P < 0.05). Active exploratory behavior in the MS group was significantly higher than that in the Con group on PNDs 7 and 8, and PNDs 21 and 22 (P < 0.05). The frequency of belly-nosing behavior was significantly higher in the MS group than that in the Con group except for PNDs 64 and 65 (P < 0.05). Compared with the Con group, epinephrine, IL-1ß, IL-6, and TNF-α concentrations on PNDs 35, 38, and 65 were significantly increased in the MS group (P < 0.01), while IL-4 concentration was significantly decreased (PND 35: P < 0.05; PNDs 38 and 65: P < 0.01). Compared with the Con group, the piglet diarrhea rate in the MS group during suckling was significantly increased (P < 0.01), the weaning weight was significantly decreased (P < 0.05), and it had no significant effect on the body weight at the end of the trial (P > 0.05). In conclusion, the early intermittent NMS created stress and affected the growth performance of piglets during suckling. However, the growth rate was improved by compensatory measures during late weaning.

Although management methods, such as split-suckling and foster care, in pig production can improve piglet survival rates, these methods inevitably lead to neonatal maternal separation which is an early stress on the body, and can have serious negative effects on the body. In this experiment, we investigated the effect level of neonatal maternal separation on behavior, physiology, and growth performance of piglets. The study found that early intermittent maternal separation leads to anxiety and behavioral changes in piglets, negatively affecting diarrhea rates and weaning weights in suckling piglets, but the effects on growth performance in lactating piglets can be ameliorated during the nursing period.

Bioinformatics analysis and verification of m6A related genes based on the construction of keloid diagnostic model.

Keloids are formed due to abnormal hyperplasia of the skin connective tissue. We explored the relationship between N6-methyladenosine (m6A)-related genes and keloids. The transcriptomic datasets (GSE44270 and GSE185309) of keloid and normal skin tissues samples were obtained from the Gene Expression Omnibus database. We constructed the m6A landscape and verified the corresponding genes using immunohistochemistry. We extracted hub genes for unsupervised clustering analysis using protein-protein interaction (PPI) network; gene ontology enrichment analysis was performed to determine the biological processes or functions affected by the differentially expressed genes (DEGs). We performed immune infiltration analysis to determine the relationship between keloids and the immune microenvironment using single-sample gene set enrichment analysis and CIBERSORT. Differential expression of several m6A genes was observed between the two groups; insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3) was significantly upregulated in keloid patients. PPI analysis elucidated six genes with significant differences between the two keloid sample groups. Enrichment analysis revealed that the DEGs were mainly enriched in cell division, proliferation, and metabolism. Moreover, significant differences in immunity-related pathways were observed. Therefore, the results of this study will provide a reference for the elucidation of the pathogenesis and therapeutic targets of keloids.

Multifunctional AIE Nanosphere-Based "Nanobomb" for Trimodal Imaging-Guided Photothermal/Photodynamic/Pharmacological Therapy of Drug-Resistant Bacterial Infections.

Injudicious or inappropriate use of antibiotics has led to the prevalence of drug-resistant bacteria, posing a huge menace to global health. Here, a self-assembled aggregation-induced emission (AIE) nanosphere (AIE-PEG1000 NPs) that simultaneously possesses near-infrared region II (NIR-II) fluorescence emissive, photothermal, and photodynamic properties is prepared using a multifunctional AIE luminogen (AIE-4COOH). The AIE-PEG1000 NPs were encapsulated with teicoplanin (Tei) and ammonium bicarbonate (AB) into lipid nanovesicles to form a laser-activated "nanobomb" (AIE-Tei@AB NVs) for the multimodal theranostics of drug-resistant bacterial infections. In vivo experiments validate that the "nanobomb" enables high-performance NIR-II fluorescence, infrared thermal, and ultrasound (AB decomposition during the photothermal process to produce numerous CO2/NH3 bubbles, which is an efficient ultrasound contrast agent) imaging of multidrug-resistant bacteria-infected foci after intravenous administration of AIE-Tei@AB NVs followed by 660 nm laser stimulation. The highly efficient photothermal and photodynamic features of AIE-Tei@AB NVs, combined with the excellent pharmacological property of rapidly released Tei during bubble generation and NV disintegration, collectively promote broad-spectrum eradication of three clinically isolated multidrug-resistant bacteria strains and rapid healing of infected wounds. This multimodal imaging-guided synergistic therapeutic strategy can be extended for the theranostics of superbugs.

Adaptive Bayesian neural networks nonlinear equalizer in a 300-Gbit/s PAM8 transmission for IM/DD OAM mode division multiplexing.

The strong stochastic nonlinear impairment induced by random mode coupling appears to be a long-standing performance-limiting problem in the orbital angular momentum (OAM) mode division multiplexing (MDM) of intensity modulation direct detection (IM/DD) transmission systems. In this Letter, we propose a Bayesian neural network (BNN) nonlinear equalizer for an OAM-MDM IM/DD transmission with three modes. Unlike conventional Volterra and convolutional neural network (CNN) equalizers with fixed weight coefficients, the weights and biases of the BNN nonlinear equalizer are regarded as probability distributions, which can accurately match the stochastic nonlinear model of the OAM-MDM. The BNN nonlinear equalizer is capable of adaptively updating its weights and biases sample-by-sample, according to the probability distribution. An experiment was conducted on a 300-Gbit/s PAM8 signal with three modes over a 2.6-km OAM-MDM RCF transmission. The experimental results demonstrate that the proposed BNN nonlinear equalizer exhibits promising solutions to effectively mitigate nonlinear distortions, which outperforms conventional Volterra and CNN equalizers with receiver sensitivity improvements of 1.0 dBm and 2.5 dBm, respectively, under hard-decision forward error correction (HD-FEC) thresholds. Moreover, compared with the Volterra and CNN equalizers, the complexity of the OAM-MDM is significantly improved through the BNN nonlinear equalizer. The proposed BNN nonlinear equalizer is a promising candidate for the high capacity inter-data center interconnects.

Turnover intention of nurses in public hospitals and its association with quality of working life: a cross-sectional survey in six provinces in China.

Objectives: High turnover intention can exacerbate the workforce shortage of nurses. This study aimed to determine the level of turnover intention of public hospital nurses in China and its associated factors. Methods: A cross-sectional questionnaire survey of 2,863 nurses was conducted in 48 public hospitals across six provinces in mainland China, measuring the sociodemographic (gender, age, marital status, and monthly basic salary) and work characteristics (professional title, workload, night sleep deprivation, and workplace violence) of respondents, their quality of working life (QWL), and turnover intention. Multivariate logistic regression models were established to determine the association between QWL and turnover intention after adjustment for variations of the sociodemographic and work characteristics. Results: Overall, 42.8% of respondents reported turnover intention. Higher QWL scores (AOR = 0.824 for job and career satisfaction, p < 0.001; AOR = 0.894 for professional pride, p < 0.001; AOR = 0.911 for balance between work and family, p < 0.05) were associated with lower turnover intention. Workplace violence was the strongest predictor of higher turnover intention (AOR = 3.003-4.767) amongst the sociodemographic and work characteristics, followed by an age between 30 and 40 years (AOR = 1.457 relative to <30 years), and night sleep deprivation (AOR = 1.391-1.808). Senior professional title had a protective effect (AOR = 0.417 relative to no title) on turnover intention. Conclusion: High levels of turnover intention are evident across China in nurses employed by public hospitals, in particular in those aged between 30 and 40 years. Low QWL and poor work environment are significant predictors of turnover intention.