Z-Spectral MRI Quantifies the Mass and Metabolic Activity of Adipose Tissues With Fat-Water-Fraction and Amide-Proton-Transfer Contrasts.

BACKGROUND: Brown adipose tissue (BAT) is metabolically activatable and plays an important role in obesity and metabolic diseases. With reduced fat-water-fraction (FWF) compared with white adipose tissue (WAT), BAT mass and its functional activation may be quantified with Z-spectra MRI, with built-in FWF and the metabolic amide proton transfer (APT) contrasts. PURPOSE: To investigate if Z-spectral MRI can quantify the mass and metabolic activity of adipose tissues. STUDY TYPE: Prospective. SUBJECTS: Seven groups of 8-week-old male rats, including two groups (n = 7 per group) for in vivo MRI study and five groups (n = 5 per group) for ex vivo validation; 12 young and healthy volunteers with 6 male and 6 female. FIELD STRENGTH/SEQUENCE: The 7 T small animal and 3 T clinical systems, T2-weighted imaging, Rapid Acquisition with Relaxation Enhancement (RARE) readout based chemical exchange saturation transfer (CEST) Z-spectral MRI sequence. ASSESSMENT: Quantified FWF and APT from Z-spectra in rats before and after norepinephrine (NE) stimulation and in healthy human subjects; ex vivo measurements of total proteins in BAT from rats. STATISTICAL TESTS: Two-tailed unpaired Student's t-tests and repeated measures ANOVA. P-value <0.05 was considered significant. RESULTS: Decreased FWF (from 39.6% ± 7.2% before NE injection to 16.4% ± 7.2% 120 minutes after NE injection, P < 0.0001) and elevated APT (from 1.1% ± 0.5% before NE injection to 2.9% ± 0.5% 120 minutes after NE injection, P < 0.0001) signals in BAT were observed with in vivo Z-spectral MRI in rats injected with NE at 7 T MRI. At clinical 3 T, Z-spectral MRI was used to quantify the FWF (58.5% ± 7.2% in BAT and 73.7% ± 6.5% in WAT with P < 0.0001) and APT (2.6% ± 0.8% in BAT and 0.9% ± 0.3% in WAT with P < 0.0001) signals in healthy volunteers. APT signals of BAT were negatively correlated with the BMI in humans (r = 0.71). DATA CONCLUSION: Endogenous Z-spectral MRI was demonstrated to simultaneously quantify BAT mass and function based on its FWF and APT contrasts. TECHNICAL EFFICACY STAGE: 1.

TiCl4precursor affecting the performance of HTM-free carbon-based perovskite solar cell.

The presence of TiO2used as an efficient electron transport layer is crucial to achieving high-performance solar cells, especially for a hole transport material (HTM)-free carbon-based perovskite solar cell (PSC). The hydrolysis of TiCl4is one of the most widely used routes for forming TiO2layer in solar cells, which includes the stock solution preparation from TiCl4initial precursor and the thermal hydrolysis of the stock solution. The second thermal hydrolysis step has been extensively studied, while the initial hydrolysis reaction in the first step is not receiving sufficient attention, especially for its influence on the photovoltaic performance of HTM-free carbon-based devices. In this study, the role of TiCl4stock solution in the growth process of TiO2layer is examined. Based on the analysis of the Ti(IV) intermediate states for different TiCl4concentrations from Raman spectra, 2 M TiCl4precursor exhibits moderate nucleation and growth kinetics without generating too many intermediates which occurs in 3 M TiCl4precursor, yielding ∼300 nm size spherical TiO2agglomerates with a rutile phase. In the aspect of devices, the HTM-free carbon-based PSCs fabricated using 2 M TiCl4precursor deliver a conversion efficiency beyond 17%, which may be attributed to the reduced defect in compact TiO2layer.

Efficacy of mouthwash on reducing salivary SARS-CoV-2 viral load and clinical symptoms: a systematic review and meta-analysis.

BACKGROUND: COVID-19 has been a public health emergency of international concern (PHEIC) for a lengthy period of time. The novel coronavirus is primarily spread via aerosols at a short distance, with infected individuals releasing large amounts of aerosols when speaking and coughing. However, there is an open question regarding whether mouthwash could effectively reduce virus transmission during the COVID-19 pandemic and support the prevention of infection among medical workers. METHODS: Cochrane Library, PubMed, Web of Science, and Embase databases were systematically searched from the inception of each database to January 12, 2023 for currently available randomized clinical trials (RCTs) on the effect of mouthwash on novel coronavirus load in the oral cavity in COVID-19 patients. The treatment group received mouthwash for rinsing the mouth, while the control group received a placebo or distilled water for COVID-19 patients. The primary outcomes were CT value and viral load. Odds ratios (ORs) were estimated using a random-effects model. Subgroup and sensitivity analyses were performed to minimize the bias and the impact of heterogeneity. RESULTS: Thirteen RCTs were included. Seven studies reported the intervention effect of mouthwash on the CT value of novel coronavirus. The analysis results showed that the mouthwash group had a positive impact on the CT value of novel coronavirus [ SMD = 0.35, 95% CI (0.21, 0.50)] compared with the control group. In addition, subgroup analysis showed a significant positive effect of mouthwash on CT values in the treatment group compared with the control group, with chlorhexidine (CHX) [SMD = 0.33, 95% CI (0.10, 0.56)], povidone-iodine (PVP-I) [SMD = 0.61, 95% CI (0.23, 0.99)], or hydrogen peroxide (HP) [SMD = 1.04, 95% CI (0.30, 1.78)] as an ingredient of the mouthwash. Six studies reported the intervention effect of mouthwash on the viral load, 263 cases in the treatment group and 164 cases in the control group. The analysis results showed that there was no statistical difference between the mouthwash group and the control group in the viral load of novel coronavirus [SMD = -0.06, 95% CI (-0.18, 0.05)]. In the subgroup analysis by measurement time, there were statistically significant differences between the mouthwash and control groups for CT values [SMD = 0.52, 95% CI (0.31, 0.72)] and viral load [SMD = - 0.32, 95% CI (- 0.56, - 0.07)] within 30 min of gargling. CONCLUSIONS: In summary, mouthwash has some efficacy in reducing the viral load of novel coronavirus, especially within 30 min after rinsing the mouth. Mouthwash containing CHX, PVP-I and HP all had significant positive effects on CT values, and PVP-I-containing mouthwash may be a promising option to control novel coronavirus infections and relieve virus-related symptoms. However, studies on the dose and frequency of use of mouthwash for infection control are still lacking, which may limit the clinical application of mouthwash. TRIAL REGISTRATION: Protocol registration: The protocol was registered at PROSPERO (CRD42023401961).

Tb3+-based multi-mode optical ratiometric thermometry.

Owing to some special superiority, luminescence ratiometric thermometry, mainly including dual excitations single emission and single excitation dual emissions, has gained popularity over the past few years. However, developing novel ratiometric thermometry that can work in multi-mode is still a challenge. Here we report a temperature measurement method based on the photoinduced luminescence of Tb3+ in the low-cost and easy to prepare calcium tungstate. Both the conventional luminescence intensity ratio (LIR) and recently developed single-band ratiometric (SBR) strategies have been achieved in our materials. On the one hand, upon excitation of the charge transfer state, the emissions from the excited 5D4 and 5D3 states present different responses to temperature. A thermometry depending on the LIR between these two emissions has thus been developed, with adjustable relative sensitivity that is sensitive to the excitation wavelength. On the other hand, both the emissions from the excited 5D4 and 5D3 states respond dissimilarly to the temperature variation. A SBR thermometer has thus been constructed with two excitation modes, reaching the maximum relative sensitivity of 1.83% K-1 at 573 K. The present work is expected to inspire other researchers to exploit more multi-mode optical ratiometric thermometries.

Enhancing Short Track Speed Skating Performance through Improved DDQN Tactical Decision Model.

This paper studies the tactical decision-making model of short track speed skating based on deep reinforcement learning, so as to improve the competitive performance of corresponding short track speed skaters. Short track speed skating, a traditional discipline in the Winter Olympics since its establishment in 1988, has consistently garnered attention. As artificial intelligence continues to advance, the utilization of deep learning methods to enhance athletes' tactical decision-making capabilities has become increasingly prevalent. Traditional tactical decision techniques often rely on the experience and knowledge of coaches and video analysis methods that require a lot of time and effort. Consequently, this study proposes a scientific simulation environment for short track speed skating, that accurately simulates the physical attributes of the venue, the physiological fitness of the athletes, and the rules of the competition. The Double Deep Q-Network (DDQN) model is enhanced and utilized, with improvements to the reward function and the distinct description of four tactics. This enables agents to learn optimal tactical decisions in various competitive states with a simulation environment. Experimental results demonstrate that this approach effectively enhances the competition performance and physiological fitness allocation of short track speed skaters.

A Hardware-Friendly High-Precision CNN Pruning Method and Its FPGA Implementation.

To address the problems of large storage requirements, computational pressure, untimely data supply of off-chip memory, and low computational efficiency during hardware deployment due to the large number of convolutional neural network (CNN) parameters, we developed an innovative hardware-friendly CNN pruning method called KRP, which prunes the convolutional kernel on a row scale. A new retraining method based on LR tracking was used to obtain a CNN model with both a high pruning rate and accuracy. Furthermore, we designed a high-performance convolutional computation module on the FPGA platform to help deploy KRP pruning models. The results of comparative experiments on CNNs such as VGG and ResNet showed that KRP has higher accuracy than most pruning methods. At the same time, the KRP method, together with the GSNQ quantization method developed in our previous study, forms a high-precision hardware-friendly network compression framework that can achieve "lossless" CNN compression with a 27× reduction in network model storage. The results of the comparative experiments on the FPGA showed that the KRP pruning method not only requires much less storage space, but also helps to reduce the on-chip hardware resource consumption by more than half and effectively improves the parallelism of the model in FPGAs with a strong hardware-friendly feature. This study provides more ideas for the application of CNNs in the field of edge computing.

Effects of probiotics on preventing caries in preschool children: a systematic review and meta-analysis.

This paper systematically evaluate the effects of probiotics on preventing caries in preschool children. The present systematic review was conducted following the Transparent Reporting of Systematic Reviews and Meta-Analyses (PRISMA) guidelines and recorded in the International prospective register of systematic reviews (PROSPERO) database (registration no: CRD42022325286). Literature were screened from PubMed, Embase, Web of Sciences, China National Knowledge Infrastructure (CNKI), Wanfang and other databases from inception to April 2022 to identify randomized controlled trials on the clinical efficacies of probiotics in preventing dental caries in preschool children and extract relevant data. The meta-analysis was performed using the RevMan5.4 software and the Stata16. Cochrane handbook was used to assess the risk of bias. The Grading of Recommendations Assessment, Development and Evaluation (GRADEprofiler 3.6) was used to determine the evidence quality. A total of 17 randomized controlled trials were eligible, of which two trials had certain levels of bias and 15 had a low risk of bias. Evidence quality assessment showed that the included trials were of medium quality. The meta-analysis results showed that Lactobacillus rhamnosus was associated with a reduced incidence (p = 0.005) and progression (p < 0.001) of caries in preschool children. Probiotics could reduce the number of high-level Streptococcus mutans in saliva (p < 0.00001) but could not reduce the number of Streptococcus mutans in dental plaque nor the amount of Lactobacillus in the saliva and dental plaque. Current evidence shows that probiotics could prevent caries in preschool children, but Lactobacillus rhamnosus was more effective in preventing caries than others. Although probiotics could reduce high levels of Streptococcus mutans in saliva, they could not reduce the amount of Lactobacillus in saliva and dental plaque.

Eu3+-based dual-excitation single-emission luminescent ratiometric thermometry.

Recently, single-band ratiometric (SBR) thermometry becomes a hot-spot in the research field of optical thermometry. Here we propose a new SBR thermometry by combining the temperature-induced red shift of charge transfer state (CTS) of W-O and Eu-O with the ground state absorption (GSA) and excited state absorption (ESA) of Eu3+. The emitting intensity of the 5D0-7F2 transition of Eu3+ is monitored under CTS, GSA and ESA excitations at different temperatures. It is found that the SBR thermometry, depending on the combination of [GSA + CTS] of Eu3+ doped calcium tungstate, has the highest relative sensitivity of 1.25% K-1 at 573 K, higher than conventional luminescent ratiometric thermometry such as the 2H11/2 and 4S3/2 thermally coupled states of Er3+.

Efficient near-infrared broadband garnet phosphor for pc-LED and its application to vascular visualization and night vision.

Ultra-broadband near-infrared (NIR) spectroscopy has unparalleled application prospects in intelligent detection and phosphor-converted light-emitting diodes (pc-LED), which are most likely to become the next generation of NIR light sources, has become a hot spot for research nowadays. To cope with the demand for more NIR spectroscopy applications, more efficient NIR phosphors need to be developed. Here, by screening the subject with a smaller band gap and by screening the suitable ion electronegativity of the lattice position where the Cr3+ is located, and then through the energy transfer, a series of Gd3Zn2GaGe2O12:xCr3+, yYb3+ (GZGG:Cr3+/Yb3+) NIR broadband garnet phosphors were found for the first time. By controlling the energy transfer process, the internal quantum yield (IQY) (54.9%), external quantum yield (EQY) (24.65%), bandwidth (260 nm), and thermal stability (60% at 150 °C) of NIR emission were substantially improved. The obtained phosphors are packaged with blue light chips into pc-LED, which can be applied in different fields such as vascular visualization and night vision.

Ultra-sensitive luminescence ratiometric thermometry from 2E→4A2 transitions of AlTaO4:Cr3.

In recent years, non-contact ratiometric luminescence thermometry has continued to gain popularity among researchers, owing to its compelling features, such as high accuracy, fast response, and convenience. The development of novel optical thermometry with ultrahigh relative sensitivity (Sr) and temperature resolution has become a frontier topic. In this work, we present a novel, to the best of our knowldege, luminescence intensity ratio (LIR) thermometry method that relies on AlTaO4:Cr3+ materials, based on the fact that they possess both anti-Stokes phonon sideband emission and R-line emission at the 2E→4A2 transitions and have been confirmed to follow the Boltzmann distribution. In the temperature range 40-250 K, the emission band of the anti-Stokes phonon sideband shows an upward trend, while the bands of the R-lines show the opposite downward trend. Relying on this fascinating feature, the newly proposed LIR thermometry achieves a maximum relative sensitivity of 8.45%K-1 and a temperature resolution of 0.038 K. Our work is expected to provide guiding insights for optimizing the sensitivity of Cr3+-based LIR thermometers and provide some novel entry points for designing excellent and reliable optical thermometers.

Near-Infrared Broadband ZnTa2O6:Cr3+ Phosphor for pc-LEDs and Its Application to Nondestructive Testing.

Broadband near-infrared (NIR) phosphors are necessary materials for developing portable NIR light sources. Moreover, exploiting an NIR phosphor with a main peak located beyond a wavelength of 900 nm remains a challenge because this spectral range has great potential in biological nondestructive testing and solution testing. In this study, a range of Cr3+-doped ZnTa2O6 (ZTO) phosphors were completely synthesized by a solid-state method, which show broadband Cr3+ emission centered at 935 nm with a large full width at half maximum (FWHM) of 185 nm due to two distorted octahedral sites. A packaged phosphor-converted light-emitting diode (pc-LED) device is used to penetrate a 5-cm-thick chicken breast and identify diverse solutions based on differences in the measured transmission spectra. The results indicate broad application prospects in the field of biological tissue penetration and solution analysis.

Chromium(III)-Doped Phosphors of High-Efficiency Two-Site Occupation Broadband Infrared Emission for Vessel Visualization Applications.

The exploration of efficient broadband near-infrared (NIR) emitting materials is essential to establishing new NIR applications. In this work, an excellent NIR phosphor Mg7Ga2GeO12:Cr3+, with an emission band of 650-1350 nm and a full width at half maximum of 266 nm, was successfully prepared. When Ga3+ ions were replaced by In3+ ions, its emission intensity increased 4 times, and the internal and external quantum efficiency reached 86 and 37%, respectively. A NIR phosphor-converted light-emitting diode (pc-LED) component was made by combining a synthetic Mg7Ga1.84In0.07GeO12:0.09Cr3+ phosphor with a 450 nm blue luminescent chip. The vascular and skeletal distribution on human fingers and the back of the hand can be seen under the display of a commercial NIR camera, indicating that Mg7Ga1.84In0.07GeO12:0.09Cr3+ phosphors have promising applications in the field of the blood vessel and bone visualization.

Cesium acetate-assisted crystallization for high-performance inverted CsPbI3perovskite solar cells.

Efficient inverted (p-i-n) type CsPbI3perovskite solar cells (PSCs) have revealed promising applications due to their excellent thermal and photostability. Regulating the nucleation and crystallization of perovskite film is an important route to improving the performance of CsPbI3PSCs. Herein, we explored cesium acetate (CsAc) as additive to manipulate the crystallization process of CsPbI3perovskite films. By involving in the intermediate phase DMA1-xCsxPbI3-yAcyof perovskite, the pseudo-halide acetate (Ac-) can retard the ion exchange reaction between DMA+and Cs+, leading to a perovskite with dense morphology, low defect density, and a long carrier lifetime. As a result, the optimal CsPbI3PSCs yielded a high power conversion efficiency of 18.3%. Moreover, the encapsulated devices showed excellent operational stability and the devices retained their initial performance following 500 h of operation at the maximum power point under one-sun illumination in ambient conditions.

A Hardware-Friendly Low-Bit Power-of-Two Quantization Method for CNNs and Its FPGA Implementation.

To address the problems of convolutional neural networks (CNNs) consuming more hardware resources (such as DSPs and RAMs on FPGAs) and their accuracy, efficiency, and resources being difficult to balance, meaning they cannot meet the requirements of industrial applications, we proposed an innovative low-bit power-of-two quantization method: the global sign-based network quantization (GSNQ). This method involves designing different quantization ranges according to the sign of the weights, which can provide a larger quantization-value range. Combined with the fine-grained and multi-scale global retraining method proposed in this paper, the accuracy loss of low-bit quantization can be effectively reduced. We also proposed a novel convolutional algorithm using shift operations to replace multiplication to help to deploy the GSNQ quantized models on FPGAs. Quantization comparison experiments performed on LeNet-5, AlexNet, VGG-Net, ResNet, and GoogLeNet showed that GSNQ has higher accuracy than most existing methods and achieves "lossless" quantization (i.e., the accuracy of the quantized CNN model is higher than the baseline) at low-bit quantization in most cases. FPGA comparison experiments showed that our convolutional algorithm does not occupy on-chip DSPs, and it also has a low comprehensive occupancy in terms of on-chip LUTs and FFs, which can effectively improve the computational parallelism, and this proves that GSNQ has good hardware-adaptation capability. This study provides theoretical and experimental support for the industrial application of CNNs.

Blind Deblurring of Remote-Sensing Single Images Based on Feature Alignment.

Motion blur recovery is a common method in the field of remote sensing image processing that can effectively improve the accuracy of detection and recognition. Among the existing motion blur recovery methods, the algorithms based on deep learning do not rely on a priori knowledge and, thus, have better generalizability. However, the existing deep learning algorithms usually suffer from feature misalignment, resulting in a high probability of missing details or errors in the recovered images. This paper proposes an end-to-end generative adversarial network (SDD-GAN) for single-image motion deblurring to address this problem and to optimize the recovery of blurred remote sensing images. Firstly, this paper applies a feature alignment module (FAFM) in the generator to learn the offset between feature maps to adjust the position of each sample in the convolution kernel and to align the feature maps according to the context; secondly, a feature importance selection module is introduced in the generator to adaptively filter the feature maps in the spatial and channel domains, preserving reliable details in the feature maps and improving the performance of the algorithm. In addition, this paper constructs a self-constructed remote sensing dataset (RSDATA) based on the mechanism of image blurring caused by the high-speed orbital motion of satellites. Comparative experiments are conducted on self-built remote sensing datasets and public datasets as well as on real remote sensing blurred images taken by an in-orbit satellite (CX-6(02)). The results show that the algorithm in this paper outperforms the comparison algorithm in terms of both quantitative evaluation and visual effects.

Protection of Vasoactive Intestinal Peptide on the Blood-Brain Barrier Dysfunction Induced by Focal Cerebral Ischemia in Rats.

OBJECTIVE: To investigate the effects of vasoactive intestinal peptide on the blood brain barrier function after focal cerebral ischemia in rats. MATERIALS AND METHODS: Rats were intracerebroventricular injected with vasoactive intestinal peptide after a two hours middle cerebral artery occlusion. Functional outcome was studied with the neurological severity score. The brain edema and the infarction were evaluated via histology. The blood brain barrier permeability was assessed using Evans Blue dye injection method. We also measure the apoptosis of brain microvascular endothelial cells and brain levels of B-cell leukemia-2 protein by immunohistochemical analysis and western blotting, respectively. RESULTS: In contrast to the cases treated with vehicle at 72 h after middle cerebral artery occlusion, the treatment with vasoactive intestinal peptide significantly (P < 0.05) reduced the neurological severity score, the brain edema and infarct volume. The Evans Blue leakage and brain water content were obviously reduced (P < 0.05) in vasoactive intestinal peptide-treated rats compared with those of control rats at 72 and 96 h after stroke. In addition, vasoactive intestinal peptide decreased the numbers of terminal deoxynucleotidyl transferase-mediated dUTP-nick end labeling positive endothelial cells and increased the protein levels of B-cell leukemia-2 in the ischemic hemisphere at 72 h after ischemia. CONCLUSIONS: Our data suggest that treatment with vasoactive intestinal peptide ameliorates the blood brain barrier function, contributing to reduce in brain damage both morphologically and functionally in the ischemic rat. This amelioration may be associated with attenuation in apoptosis of brain microvascular endothelial cells by increased B-cell leukemia-2 expression.

Two-Terminal Perovskite-Based Tandem Solar Cells for Energy Conversion and Storage.

The organic-inorganic hybrid perovskite solar cells present a rapid improvement on power conversion efficiency from 3.8% to 25.5% in the past decades. Owing to the tuneable bandgaps, low-cost, and ease of fabrication, perovskites become ideal candidate materials for fabricating tandem solar cells, especially for efficient and high-voltage monolithic two-terminal devices. In this review, an overview of recent advances in various monolithic perovskite-based tandem solar cells with a focus on the key challenges is provided. Subsequently, the recombination layer materials, construction of wide-bandgap perovskite layer, stability of narrow-bandgap, and current matching principle in tandems are highlighted in order to optimize the output voltage and conversion efficiency of tandem solar cells. Finally, the recent progress is summarized with a focus on potential applications of tandem solar cells for energy conversion and storage, including hydrogen production by water splitting, CO2 reduction, supercapacitors, and rechargeable batteries, benefiting from the adjustable output voltage of tandem solar cells. It is hoped that this work can offer a feasible strategy to explore more possibilities for fabricating new two-terminal tandem solar cells with high voltage and high conversion efficiency for energy conversion and storage.

HOXB2 and FOXC1 synergistically drive the progression of Wilms tumor.

OBJECTIVE: To uncover the expression patterns of HOXB2 and FOXC1 in Wilms tumor samples, and their synergistical regulations on the development of Wilms tumor. METHODS: Expression levels of HOXB2 and FOXC1 in 58 cases of Wilms tumor tissues and paracancerous ones were detected. The influences of HOXB2 and FOXC1 on prognosis in Wilms tumor patients were analyzed. Their regulatory effects on proliferative and migratory abilities in WT-CLS1 and HFWT cells were examined by cell counting kit-8 (CCK-8) and Transwell assay, respectively. The interaction between HOXB2 and FOXC1, and their synergistical regulation on the development of Wilms tumor were finally explored. RESULTS: HOXB2 and FOXC1 were upregulated in Wilms tumor tissues. Higher levels of HOXB2 and FOXC1 indicated higher risks of advanced stage and lymphatic metastasis, as well as worse prognosis in Wilms tumor patients. Knockdown of HOXB2 or FOXC1 weakened proliferative and migratory abilities in WT-CLS1 and HFWT cells, while the opposite trends were observed in those overexpressing HOXB2 or FOXC1. The positive interaction between HOXB2 and FOXC1 was identified, which synergistically drove the malignant development of Wilms tumor. CONCLUSIONS: HOXB2 and FOXC1 are upregulated in Wilms tumor samples, and they are closely linked to tumor staging and lymphatic metastasis in Wilms tumor patients. HOXB2 and FOXC1 synergistically drive the malignant development of Wilms tumor by stimulating proliferative and migratory potentials.

A low-carbon economic dispatch method for regional integrated energy system based on multi-objective chaotic artificial hummingbird algorithm.

This paper investigates Regional Integrated Energy Systems (RIES), emphasizing the connection of diverse energy supply subsystems to address varied user needs and enhance operational efficiency. A novel low-carbon economic dispatch method, utilizing the multi-objective chaotic artificial hummingbird algorithm, is introduced. The method not only optimizes economic and environmental benefits but also aligns with "carbon peak and carbon neutrality" objectives. The study begins by presenting a comprehensive low-carbon economic dispatch model, followed by the proposal of the multi-objective chaotic artificial hummingbird algorithm, crucial for deriving the Pareto frontier of the low-carbon economic dispatch model. Additionally, we introduce a TOPSIS approach based on combined subjective and objective weights, this approach harnesses the objective data from the Pareto solution set deftly, curbs the subjective biases of dispatchers effectively and facilitates the selection of an optimal system operation plan from the Pareto frontier. Finally, the simulation results highlight the outstanding performance of our method in terms of optimization outcomes, convergence efficiency, and solution diversity. Noteworthy among these results is an 8.8% decrease in system operational economic costs and a 14.2% reduction in carbon emissions.

Identification and validation of genes associated with copper death in oral squamous cell carcinoma based on machine learning and weighted gene co-expression network analysis.

OBJECTIVE: To identify copper-induced death-associated hub genes in oral squamous cell carcinoma (OSCC) and understand their functional and biological significance using machine learning and Weighted Gene Co-expression Network Analysis (WGCNA). METHODS: OSCC transcriptomic data from GEO and TCGA databases were subjected to data integration, batch effect removal, background correction, and quantile normalization to select cuproptosis-associated genes using Spearman's correlation analysis. The 'limma' R package was used to filter differentially expressed genes (DEGs). Core module genes selected using gene co-expression network analysis with R package 'WGCNA' were screened using Support Vector Machine (SVM), LASSO regression, and Random Forest (RF) machine learning algorithms and validated using TCGA database samples. Core gene expression variations between OSCC and adjacent normal tissues were validated using immunohistochemistry. Immune infiltration analysis using package 'CIBERSORT' correlated hub genes with immune cells. RESULTS: From 19 cuproptosis-related genes (identified from literature), 2382 cuproptosis-related mRNA were obtained through Spearman's correlation analysis; 112 DEGs using 'limma' R package and 32 hub genes using WGCNA were obtained. Hub genes TMPRSS11B, SERPINH1, and CDH3 were identified using machine learning algorithms. TCGA validation showed that TMPRSS11B significantly underexpressed (P < 0.001) but SERPINH1 and CDH3 significantly overexpressed (P < 0.001) in tumor samples. The AUC for TMPRSS11B, SERPINH1, and CDH3 in ROC curve analysis were 78.1%, 95.6%, and 87.5%, respectively. CONCLUSION: TMPRSS11B, SERPINH1, and CDH3 may be pivotal for OSCC development and progression and potential targets for new therapeutic and predictive strategies. However, their specific functions and mechanisms underlying OSCC remain to be elucidated.