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Abstract Ovarian cancer (OC) is a highly fatal gynecological malignancy worldwide, and cisplatin (CDDP) is commonly used as an initial chemotherapy treatment for OC. Nonetheless, most patients ultimately face recurrence because of resistance to cisplatin. Therefore, it is imperative to investigate the underlying mechanisms of drug resistance in OC. By analyzing differential gene expression using TCGA, GDSC, and GEO public databases, we discovered that increased KLF4 expression is strongly linked to chemotherapy resistance and unfavorable outcomes in OC. Subsequent validation through immunohistochemistry and western blotting confirmed the upregulated KLF4 expression in cisplatin-resistance OC cells lines and tissues. To investigate the function of KLF4, functional experiments were performed both in vitro and in vivo. We observed that knocking down KLF4 impaired cisplatin-resistance of OC. Further mechanism research based on RNA-seq and gene enrichment analysis revealed that interfering KLF4 suppressed the activation of mTORC1 pathway. Finally, rescue experiment demonstrated that using mTORC1 pathway inhibitor could attenuate the cisplatin resistance induced by the overexpression of KLF4. In conclusion, our research indicates that KLF4 promotes cisplatin resistance through the activation of mTORC1 signaling, and proposes that inhibiting KLF4 might serve as a viable therapeutic approach to overcoming drug resistance in ovarian cancer.

Abstract This research endeavors to investigate the functions of N6-methyladenosine (m6A) regulatory genes and key genes linked to m6A modifications within the context of breast cancer (BC). The objective is to identify a promising predictive biomarker related to m6A modifications and validate its significance in BC through experimental methodologies. Utilizing data from The Cancer Genome Atlas (TCGA) database, a model for predicting prognosis was developed. Key genes connected to m6A modifications were discerned using weighted gene co-expression network analysis (WGCNA) coupled with LASSO and Cox regression analyses, which were then utilized to construct a predictive model. The influence of ZNF260 within BC was probed experimentally. The predictive model formulated using m6A regulatory genes and key m6A-associated genes demonstrated the capability to categorize BC patients into distinct risk groups effectively (all P

Abstract Ovarian cancer (OV) is a highly fatal malignant disease that commonly manifests at an advanced stage. Drug resistance, particularly platinum resistance, is a leading cause of treatment failure because first-line systemic chemotherapy primarily relies on platinum-based regimens. By analyzing the gene expression levels in the Cancer Genome Atlas database, Genotype-Tissue Expression database, and Gene Expression Omnibus datasets, we discerned that HOXB2 was highly expressed in OV and was associated with poor prognosis and cisplatin resistance. Immunohistochemistry and loss-of-function experiments on HOXB2 were conducted to explore its role in OV. We observed that suppressing HOXB2 could impair the growth and cisplatin resistance of OV in vivo and in vitro. Mechanical investigation and experimental validation based on RNA-Seq revealed that HOXB2 regulated ATP-binding cassette transporter members and the ERK signaling pathway. We further demonstrated that HOXB2 modulated the expression of long non-coding RNA DANCR, a differentiation antagonizing non-protein coding RNA, and thus influenced its downstream effectors ABCA1, ABCG1, and ERK signaling to boost drug resistance and cancer proliferation. These results verified that high expression of HOXB2 correlated with platinum resistance and poor prognosis of OV. Therefore, targeting HOXB2 may be a promising strategy for OV therapy.

Previous research has commonly assumed that tunnel fire blockage occurs at the central longitudinal axis of tunnels. However, fires may arise at different points within tunnels, each with various distances from the tunnel sidewall. The study aimed to investigate the distribution of ceiling temperature fields across various scenarios of blockage and transverse fire source locations by conducting a sequence of fire experiments within a reduced-scale 1:10 horseshoe-shaped tunnel model. The findings indicate that at sufficiently low ventilation velocities (v’≤0.19), the maximum ceiling temperature rise in the tunnel remains virtually unchanged regardless of the locations of blockage and transverse fire source. For higher ventilation velocities (v’>0.19), the maximum ceiling temperature rise diminishes with greater blockage-fire source distance. Additionally, the maximum ceiling temperature rise increases as the distance between the sidewall and the fire source diminishes. Furthermore, a new model has been formulated to forecast the dimensionless maximum ceiling temperature rise, incorporating both blockage and transverse fire locations.

Compared to single-source fires in tunnels, double-source fires may exhibit more intricate flame merging behavior and higher flame burning rates due to their interaction, thereby escalating the risk of fire propagation within the tunnel. In this investigation, a 1:10 scale model of a horseshoe-shaped tunnel test site was deployed to conduct experiments on lateral double-source fires, scrutinizing flame merging behavior, probability prediction models, and temperature characteristics of tunnel ceiling smoke gas by varying the oil pool size and double-source spacing. Findings from the study suggest that flame merging behavior within the tunnel is contingent upon double-source spacing and heat release rate (HRR), manifesting in three distinct forms: complete merging, intermittent merging, and complete separation. Through the introduction of non-dimensional heat release rate and non-dimensional fire source spacing, a piecewise function has been devised to forecast the probability of flame merging for both fire types. Furthermore, a predictive model for the maximum temperature rise along the longitudinal centerline of a horseshoe tunnel was formulated, drawing from established theoretical frameworks.

BackgroundSpinal muscular atrophy (SMA) is a genetic progressive neuromuscular disease. Nusinersen is the first disease modifying drug approved to treat patients with SMA. Our study aimed to evaluate the efficacy of nusinersen treatment on motor function in children with SMA.MethodsA retrospective analysis was conducted on the data of 52 genetically confirmed SMA patients from November 2020 to September 2023. Motor function was assessed based on standardized scales from baseline to 14 months of follow-up.ResultsOf patients in this study, the majority had SMA type 2 (40/52, 76.9%), 5 (9.6%) and 7 (13.5%) patients had SMA types 1 and 3, respectively. The median disease duration was 11 months (range 0–52), and the median age at initiation of treatment was 44.5 months (range 5–192). Motor function of all the patients with SMA improved from baseline to 14 months of follow-up. Mean increases of 4.6-point (p = 0.173), 4.7-point (p = 0.021) and 2.7-point (p = 0.013) were observed from baseline to 14 months of follow-up for the Children’s Hospital of Philadelphia Infant Test of Neuromuscular Disorders scores, the Hammersmith Functional Motor Scale Expanded (HFMSE) and the Revised Upper Limb Module (RULM), respectively. Increased disease duration and age of treatment initiation were negatively correlated with the changes in HFMSE scores (r = −0.567, p = 0.043; r = −0.771 and p = 0.002, respectively). Similar results were observed for the RULM scores (r = −0.714, p = 0.014; r = −0.638 and p = 0.035, respectively).ConclusionOur study suggested that 14 months of treatment with nusinersen was effective and improved the motor function of children with SMA types 1, 2, or 3. In addition, disease duration and age at treatment initiation were negatively correlated with treatment outcome in the patients.

[INLINE:1] Tibetan singing bowls emit low-frequency sounds and produce perceptible harmonic tones and vibrations through manual tapping. The sounds the singing bowls produce have been shown to enhance relaxation and reduce anxiety. However, the underlying mechanism remains unclear. In this study, we used chronic restraint stress or sleep deprivation to establish mouse models of anxiety that exhibit anxiety-like behaviors. We then supplied treatment with singing bowls in a bottomless cage placed on the top of a cushion. We found that unlike in humans, the combination of harmonic tones and vibrations did not improve anxiety-like behaviors in mice, while individual vibration components did. Additionally, the vibration of singing bowls increased the level of N-methyl-D-aspartate receptor 1 in the somatosensory cortex and prefrontal cortex of the mice, decreased the level of γ-aminobutyric acid A (GABA) receptor α 1 subtype, reduced the level of CaMKII in the prefrontal cortex, and increased the number of GABAergic interneurons. At the same time, electrophysiological tests showed that the vibration of singing bowls significantly reduced the abnormal low-frequency gamma oscillation peak frequency in the medial prefrontal cortex caused by stress restraint pressure and sleep deprivation. Results from this study indicate that the vibration of singing bowls can alleviate anxiety-like behaviors by reducing abnormal molecular and electrophysiological events in somatosensory and medial prefrontal cortex.

In this study, a 1/10 reduced-scale model tunnel with one end closed was constructed to investigate maximum temperature profiles beneath the tunnel ceiling during fire events. By varying the heat release rates (HRRs) and tunnel slopes (0%, 2%, 5%, and 6%) and measuring horizontal temperatures longitudinally along the tunnel ceiling, the effects of these parameters were systematically examined. The findings reveal that the distribution of maximum temperatures within a one-end-closed tunnel can be categorized into three distinct regions: far-field, transition, and near-field regions. Notably, milder tunnel slopes correspond to an elevated maximum temperature beneath the ceiling. By employing dimensional analysis, two prediction models were formulated to forecast maximum temperatures beneath the ceiling for fire sources located in the far-field and near-field regions, respectively. These predictive models were validated against experimental data, demonstrating favorable agreement. This study enhances our understanding of the impact of tunnel slope on temperature distribution during fire events in one-end-closed tunnels. Furthermore, the prediction models developed offer practical tools for assessing and mitigating fire risks in such tunnel configurations.

The effect of a high-fat diet (HFD) on mood is a widely debated topic, with the underlying mechanisms being poorly understood. This study explores the anxiolytic effects of a four-week HFD in C57BL/6 mice. Five-week-old mice were exposed to either an HFD (60% calories from fat) or standard chow diet (CD) for four weeks, followed by cannula implantation, virus infusion, behavioral tests, and biochemical assays. Results revealed that four weeks of an HFD induced anxiolytic-like behaviors and increased the protein levels of mature brain-derived neurotrophic factor (mBDNF) and phosphorylated tyrosine kinase receptor B (p-TrkB) in the medial prefrontal cortex (mPFC). Administration of a BDNF-neutralizing antibody to the mPFC reversed HFD-induced anxiolytic-like behaviors. Elevated BDNF levels were observed in both neurons and astrocytes in the mPFC of HFD mice. Additionally, these mice exhibited a higher number of dendritic spines in the mPFC, as well as upregulation of postsynaptic density protein 95 (PSD95). Furthermore, mRNA levels of the N6-methyladenosine (m6A) demethylase, fat mass and obesity-associated protein (FTO), and the hydrolase matrix metalloproteinase-9 (MMP9), also increased in the mPFC. These findings suggest that an HFD may induce FTO and MMP9, which could potentially regulate BDNF processing, contributing to anxiolytic-like behaviors. This study proposes potential molecular mechanisms that may underlie HFD-induced anxiolytic behaviors.

Most aspect-level sentiment classification networks include the long short-term memory (LSTM) network, coupled with attention mechanism and memory module, is becoming widely applied in aspect-level sentiment classification. Although it has achieved good results, it cannot extract the global and local information of the context at the same time, and it is only based on the semantic relatedness between an aspect and its corresponding context words to model, while neglecting their syntactic dependencies. This paper proposes the aspect-level sentiment classification by combining convolutional neural network (CNN) and proximity-weighted convolution network (PWCN), as well as a new method to calculate the proximity weight. To obtain contextualized word vectors, corpora has been trained by the model of bidirectional encoder representations from transformers (BERT), which can be taken as text features. The CNN is able to extract sequence features from the text and to take the sequence information from the text into account. In addition, the PWCN can consider the syntactic dependencies inside the sentences. The BERT model also has the ability to model complex features of words, such as their syntactic and semantic changes in a linguistic context. Experiments conducted on the SemEval 2014 benchmark demonstrate compared to the well-established ones, the proposed approach had bigger effectiveness.

Background To investigate the differences between physicians in target delineation in intensity-modulated radiation therapy for nasopharyngeal carcinoma as well as their impact on target dose coverage. Methods Ninety-nine in-hospital patients were randomly selected for retrospective analysis, and the target volumes were delineated by 2 physicians. The target volumes were integrated with the original plans, and the differential parameters, including the Dice similarity coefficient (DSC), Hausdorff distance (HD), and Jaccard similarity coefficient (JSC) were recorded. The dose–volume parameters to evaluate target dose coverage were analyzed by superimposing the same original plan to the 2 sets of images on which the target volumes were contoured by the 2 physicians. The significance of differences in target volumes and dose coverage were evaluated using statistical analysis. Results The target dose coverage for different sets of target volumes showed statistically significant differences, while the similarity metrics to evaluate geometric target volume differences did not. More specifically, for PGTVnx, the median DSC, JSC, and HD were 0.85, 0.74, and 11.73, respectively; for PCTV1, the median values were 0.87, 0.77, and 11.78, respectively; for PCTV2, the median values were 0.90, 0.82, and 16.12, respectively. For patients in stages T3-4, DSC, and JSC were reduced but HD was increased compared to those in stages T1-2. Dosimetric analysis indicated that, for the target volumes, significant differences between the 2 physicians were found in D95, D99, and V100 for all the target volumes (ie, PGTVnx, PCTV1, and PCTV2) across the whole group of patients, as well as in patients with disease stages T3-4 and T1-2. Conclusions The target volumes delineated by the 2 physicians had a high similarity, but the maximal distances between the outer contours of the 2 sets were significantly different. In patients with advanced T stages, significant differences in dose distributions were found, stemming from the deviations of target delineation.

This study addressed the issue of the real-time monitoring and control of the transporter in a mountain orchard terrain characterized by varying topography, closed canopy, shade, and other environmental factors. This study involved independent research and the development of a series of electric monorail transporters. First, the application requirements of “Where is the monorail transporter?” were examined, and an accurate location-aware method based on high-frequency radio frequency identification (RFID) technology was proposed. In addition, a location-aware hardware system based on STM32 + RFID + LoRa was designed to determine the position of the monorail transporter on a rail. Second, regarding the application requirements of “Where is the monorail transporter going?”, a multimode control gateway system based on Raspberry Pi + LoRa + 5G was designed. An Android mobile terminal can obtain operational information about the transport plane in real time through the gateway system and remotely control its operation. The track-changing branch structure enables multimachine autonomous intelligent avoidance. Based on the experimental results of monorail transporter positioning in mountain orchards under various typical terrains, such as flat surfaces, turning paths, and uphill/downhill slopes, the road section average relative error of the 7ZDGS–250-type monorail transporter was 1.27% when the distance between benchmark positioning tags was set at 10 m on both flat and turning roads, and that of the 7ZDGS–300-type monorail transporter was 1.35% when the distance between benchmark positioning tags was set at 6 m uphill/downhill. The road section relative error of the 7ZDGS–250-type monorail transporter was 21.18%, and that of the 7ZDGS–300-type monorail transporter was 9.96%. In addition, the experimental results of monorail transporter communication control showed that the combination of the multimode control gateway control system and track-changing branch structure can achieve multimachine cooperation and autonomous avoidance function, ensuring that multiple monorail transporters can operate simultaneously without collision. The findings of this study establish the communication link of “monorail transporter-gateway system-control terminal” and form a precise positioning and real-time control scheme applicable to the operating environment of monorail transporters, thereby improving the intelligence and safety of mountain orchard monorail transporters.

Food safety has emerged as a significant concern for global public health and sustainable development. The development of analytical tools capable of rapidly, conveniently, and sensitively detecting food safety hazards is imperative. Over the past few decades, personal glucose meters (PGMs), characterized by their rapid response, low cost, and high degree of commercialization, have served as portable signal output devices extensively utilized in the construction of biosensors. This paper provides a comprehensive overview of the mechanism underlying the construction of PGM-based biosensors, which consists of three fundamental components: recognition, signal transduction, and signal output. It also detailedly enumerates available recognition and signal transduction elements, and their modes of integration. Then, a multitude of instances is examined to present the latest advancements in the application of PGMs in food safety detection, including targets such as pathogenic bacteria, mycotoxins, agricultural and veterinary drug residues, heavy metal ions, and illegal additives. Finally, the challenges and prospects of PGM-based biosensors are highlighted, aiming to offer valuable references for the iterative refinement of detection techniques and provide a comprehensive framework and inspiration for further investigations.

Head and neck squamous cell carcinoma (HNSCC) usually has a poor prognosis and is associated with a high mortality rate. Its etiology is mainly the result from long-term exposure to either alcohol, tobacco or human papillomavirus (HPV) infection or a combination of these insults. However, HNSCC patients with HPV have been found to show a survival advantage over those without the virus, but the mechanism that confers this advantage is unclear. Due to the large number of HPV-independent HNSCC cases, there is a possibility that the difference in prognosis between HPV-positive (HPV+) and negative (HPV-) patients is due to different carcinogens. To clarify this, we used scRNA data and viral tracking methods in order to identify HPV+ and HPV- cells in the tumour tissues of patients infected with HPV. By comparing HPV+ and HPV- malignant cells, we found a higher level of tumour stemness in HPV- tumour cells. Using tumour stemness-related genes, we established a six-gene prognostic signature that was used to divide the patients into low- and high-risk groups. It was found that HPV patients who were at low-risk of contracting HNSCC had a higher number of CD8+ T-cells as well as a higher expression of immune checkpoint molecules. Correspondingly, we found that HPV+ tumour cells expressed higher levels of CCL4, and these were highly correlated with CD8+ T cells infiltration and immune checkpoint molecules. These data suggest that the stemness features of tumour cells are not only associated with the prognostic risk, but that it could also affect the immune cell interactions and associated signalling pathways.

Grey wolf optimizer (GWO) is a new meta-heuristic swarm intelligence algorithm, which has shown promising performance in solving optimization problems. In order to improve the convergence speed of GWO, an alpha-guided GWO (AgGWO), in which the evolving process of the population is guided by the update direction of alpha (best solution), is proposed. However, in the AgGWO, its evolutionary guidance mechanism makes the algorithm more likely to fall into the local optimal solution and the fixed value of theta may not be suitable for all problems optimization. To overcome these shortcomings and simplify its structure, an improved AgGWO (IAgGWO) is proposed in this paper. In the IAgGWO, the update direction of alpha is used to guide the evolving process of alpha, beta (second best solution), and delta (third best solution), and A and C are the coefficient scalars instead of coefficient vectors in the original algorithm. Therefore, a mutation operator is introduced to further enhance the exploration. The advantageous performance of the IAgGWO is validated by comparisons with other four algorithms on 35 benchmark functions and the engineering problem of two-stage operational amplifier design.

To shorten the response time of permanent magnet synchronous motor (PMSM) control system, improve the robustness of the system, and avoid the influence of system structure and parameters on the control effect, an adaptive non-singular fast terminal sliding mode control scheme based on disturbance observer (DOBANFTSMC) is proposed. Firstly, a nonsingular fast terminal sliding mode surface is used to design the sliding mode controller. Secondly, the disturbance observer is used to compensating for the unknown model of the system, so that the controller design does not need to know the structure and parameters of the system. At the same time, considering the unknown estimation error bounds of the observer, an adaptive law is designed in the controller to adjust the unknown estimation. The stability of the system is proved by the Lyapunov principle. Finally, the simulation and experimental results show that this method can track the load torque quickly, and the system has the advantages of small overshoot, small static error, fast speed, and high robustness.

Pasteurella multocida (Pm) infection causes severe respiratory disease in goats. We investigated the effects of the Pm infection intratracheally on the histopathology, miRNA and mRNA expression dynamics in the lung of goats infected for 1, 2, 5 and 7 days. Pm infection caused fever, which significantly (p < 0.05) increased the body temperature of the goats from day 1 to 5. Haemotoxylin–eosin staining of the infected lung tissue showed characteristics of suppurative pneumonia with inflammatory cells infiltration and the lung structure destruction. During the Pm infection of the goats, compared with the control group, there were 3080, 3508, 2716 and 2675 differentially expressed genes and 42, 69, 91 and 108 significantly expressed miRNAs (|log2Fold Change| > 1, p < 0.05) in the Pm_d1, Pm_d2, Pm_d5 and Pm_d7 groups, respectively. Five miRNAs and nine immune-related genes were selected for confirmation by reverse transcription–polymerase chain reaction. The results indicated that the expression patterns of the miRNAs and genes were consistent with those determined by next-generation sequencing. The differentially expressed genes were enriched in cytokine–cytokine receptor interaction, cell adhesion molecules, complement and coagulation cascades, tight junction and phagosome Kyoto Encyclopedia of Genes and Genomes pathways and cytokine production, leukocyte migration, myeloid leukocyte migration, cell periphery, plasma membrane, extracellular region part, extracellular region and other Gene Ontology terms. The differentially expressed genes were mapped to marker genes in human and mouse lung cells. The results showed the presence of some marker genes of the immune cells. Compared with the CK group, five miRNAs and 892 common genes were differentially expressed in the Pm_d1, Pm_d2, Pm_d5 and Pm_d7 groups. The target relationships between the common 5 miRNAs and 892 differentially expressed genes were explored and the miRNAs involved in the host immune reaction may act through the target genes. Our study characterized goats’ reaction in the lung from histopathological and molecular changes upon Pm infection, which will provide valuable information for understanding the responses in goats during Pm infection.

Purpose: We aimed to establish a nomogram model based on computed tomography (CT) imaging radiomic signature and clinical factors to predict the risk of local recurrence in nasopharyngeal carcinoma (NPC) after intensity-modulated radiotherapy (IMRT).Methods: This was a retrospective study consisting of 156 NPC patients treated with IMRT. Radiomics features were extracted from the gross tumor volume for nasopharynx (GTVnx) in pretreatment CT images for patients with or without local recurrence. Discriminative radiomics features were selected after t-test and the least absolute shrinkage and selection operator (LASSO) analysis. The most stable model was obtained to generate radiomics signature (Rad_Score) by using machine learning models including Logistic Regression, K-Nearest neighbor, Naive Bayes, Decision Tree, Stochastic Gradient Descent, Gradient Booting Tree and Linear Support Vector Classification. A nomogram for local recurrence was established based on Rad_Score and clinical factors. The predictive performance of nomogram was evaluated by discrimination ability and calibration ability. Decision Curve Analysis (DCA) was used to evaluate the clinical benefits of the multi-factor nomogram in predicting local recurrence after IMRT.Results: Local recurrence occurred in 42 patients. A total of 1,452 radiomics features were initially extracted and seven stable features finally selected after LASSO analysis were used for machine learning algorithm modeling to generate Rad_Score. The nomogram showed that the greater Rad_Score was associated with the higher risk of local recurrence. The concordance index, specificity and sensitivity in the training cohort were 0.931 (95%CI:0.8765–0.9856), 91.2 and 82.8%, respectively; whereas, in the validation cohort, they were 0.799 (95%CI: 0.6458–0.9515), 79.4, and 69.2%, respectively.Conclusion: The nomogram based on radiomics signature and clinical factors can predict the risk of local recurrence after IMRT in patients with NPC and provide evidence for early clinical intervention.

In this paper, a tuning procedure of the parameters of fractional order proportional integral controller is presented for time delay system with arbitrary order. On the basis of obtaining stable solution space by utilizing some stability-domain boundaries which include real-root boundary and σ -stability boundary, the optimal solution can be achieved by applying specific frequency-domain specifications which include gain crossing frequency, phase margin, and robustness constraint. Using the same synthesis by traversing phase angle and phase margin in a given interval, the complete solution space of gain crossing frequency can be obtained and visualized, which is equivalent to demonstrate the complete solution space of optimal parameters of fractional order proportional integral controllers. As a comparison, the tuning procedure of the parameters of integral order proportional integral derivative controller is also discussed. At last, the proposed algorithm is validated by numerical simulation and experimental illustrations. The results show the robustness and advantage of the proposed fractional order proportional integral controller over other controllers.

Aiming at the tracking control problem of a class of uncertain nonlinear systems, a nonsingular fast terminal sliding mode control scheme combining RBF network and disturbance observer is proposed. The sliding mode controller is designed by using nonsingular fast terminal sliding mode and second power reaching law to solve the problem of singularity and slow convergence in traditional terminal sliding mode control. By using the universal approximation of RBF network, the unknown nonlinear function of the system is approximated, and the disturbance observer is designed by using the hyperbolic tangent nonlinear tracking differentiator (TANH-NTD) to estimate the interference of the system and enhance the robustness of the system. The stability of the system is proved by the Lyapunov principle. The numerical simulation results show that the method can shorten the system arrival time, improve the tracking accuracy, and suppress the chattering phenomenon.