Research on the Application of Molecular Image Processing in Rice Quality Inspection.

Objective: With the improvement of living standards, consumers are paying more and more attention to the quality of rice. Traditional rice quality detection relies on human sensory judgment, which is inaccurate and inefficient. With the continuous development of molecular imaging technology, more and more scholars at home and abroad have begun to pay attention to its application in the nondestructive testing of agricultural products. Molecular imaging technology combines the advantages of spectral technology and image technology, which can achieve rapid, nondestructive and accurate detection of rice quality. In this paper, taking rice as the research object, we carried out nondestructive detection research on rice varieties, moisture and starch content using molecular imaging technology. We proposed a rapid detection method based on molecular imaging technology for rice variety identification, moisture content and starch content. Molecular images of the rice samples from four origins were obtained using a molecular imaging system, the regions of interest of the rice were identified and, spectral data, textural features and morphological features of the rice were extracted. Spectral, textural and morphological features were selected by principal component analysis (PCA), and nine feature wavelengths were obtained and an optimal model was established with an accuracy of 91.67%, which demonstrated the feasibility of molecular imaging. By comparing the models, the BCC-LS-SVR model based on the RB function had the highest accuracy with R2 of 0.989, RMSEP of 0.767%, R2 of 0.985, and RMSEC of 0.591%. Moreover, starchy rice was detected using molecular imaging. The PCA-SVR model based on the RBF kernel function had the highest accuracy with R2 of 0.989, RMSEC of 0.445%, R2 of 0.991, and RMSEP of 0.669%. Our models demonstrated high accuracy in identifying rice varieties, as well as quantifying moisture and starch content, showcasing the feasibility of molecular imaging technology in rice quality assessment. This research offers a rapid, nondestructive, and accurate method for rice quality assessment, promising significant benefits for agricultural producers and consumers.

Design, synthesis, and biological evaluation of novel benzimidazole derivatives as anti-cervical cancer agents through PI3K/Akt/mTOR pathway and tubulin inhibition.

Phosphatidylinositol 3-kinase (PI3K) is one of the most attractive therapeutic targets for cervical cancer treatment. In this study, we designed and synthesized a series of benzimidazole derivatives and evaluated their anti-cervical cancer activity. Compound 4r exhibited strong antiproliferative activity in different cervical cancer cell lines HeLa, SiHa and Ca Ski, and relative lower cytotoxicity to normal hepatic and renal cell lines LO2 and HEK-293t (IC50 values were at 21.08 µM and 23.96 µM respectively). Its IC50 value was at 3.38 µM to the SiHa cells. Further mechanistic studies revealed that 4r induced apoptosis, arrested cell cycle in G2/M phase, suppressed PI3K/Akt/mTOR pathway and inhibit the polymerization of tubulin. Molecular docking study suggested that 4r formed key H-bonds action with PI3Kα (PDB ID:8EXU) and tubulin (PDB ID:1SA0). Zebrafish acute toxicity experiments showed that high concentrations of 4r did not cause death or malformation of zebrafish embryos. All these results demonstrated that 4r would be a promising lead candidate for further development of novel PI3K and tubulin dual inhibitors in cervical cancer treatment.

Corrigendum: Genetic liability for diet-derived circulating antioxidants, oxidative stress, and risk of osteoarthritis: a Mendelian randomization study.

[This corrects the article DOI: 10.3389/fnut.2023.1233086.].

ICGA-GPT: report generation and question answering for indocyanine green angiography images.

BACKGROUND: Indocyanine green angiography (ICGA) is vital for diagnosing chorioretinal diseases, but its interpretation and patient communication require extensive expertise and time-consuming efforts. We aim to develop a bilingual ICGA report generation and question-answering (QA) system. METHODS: Our dataset comprised 213 129 ICGA images from 2919 participants. The system comprised two stages: image-text alignment for report generation by a multimodal transformer architecture, and large language model (LLM)-based QA with ICGA text reports and human-input questions. Performance was assessed using both qualitative metrics (including Bilingual Evaluation Understudy (BLEU), Consensus-based Image Description Evaluation (CIDEr), Recall-Oriented Understudy for Gisting Evaluation-Longest Common Subsequence (ROUGE-L), Semantic Propositional Image Caption Evaluation (SPICE), accuracy, sensitivity, specificity, precision and F1 score) and subjective evaluation by three experienced ophthalmologists using 5-point scales (5 refers to high quality). RESULTS: We produced 8757 ICGA reports covering 39 disease-related conditions after bilingual translation (66.7% English, 33.3% Chinese). The ICGA-GPT model's report generation performance was evaluated with BLEU scores (1-4) of 0.48, 0.44, 0.40 and 0.37; CIDEr of 0.82; ROUGE of 0.41 and SPICE of 0.18. For disease-based metrics, the average specificity, accuracy, precision, sensitivity and F1 score were 0.98, 0.94, 0.70, 0.68 and 0.64, respectively. Assessing the quality of 50 images (100 reports), three ophthalmologists achieved substantial agreement (kappa=0.723 for completeness, kappa=0.738 for accuracy), yielding scores from 3.20 to 3.55. In an interactive QA scenario involving 100 generated answers, the ophthalmologists provided scores of 4.24, 4.22 and 4.10, displaying good consistency (kappa=0.779). CONCLUSION: This pioneering study introduces the ICGA-GPT model for report generation and interactive QA for the first time, underscoring the potential of LLMs in assisting with automated ICGA image interpretation.

Characterization and childhood exposure assessment of toxic heavy metals in household dust under true living conditions from 10 China cities.

Health hazards caused by metal exposure in household dust are concerning environmental health problems. Exposure to toxic metals in household dust imposes unclear but solid health risks, especially for children. In this multicenter cross-sectional study, a total of 250 household dust samples were collected from ten stratified cities in China (Panjin, Shijiazhuang, Qingdao, Lanzhou, Luoyang, Ningbo, Xi'an, Wuxi, Mianyang, Shenzhen) between April 2018 and March 2019. Questionnaire was conducted to gather information on individuals' living environment and health status in real-life situations. Multivariate logistic regression and principal component analysis were conducted to identify risk factors and determine the sources of metals in household dust. The median concentration of five metals in household dust from 10 cities ranged from 0.03 to 73.18 µg/g. Among the five heavy metals, only chromium in household dust of Mianyang was observed significantly both higher in the cold season and from the downwind households. Mercury, cadmium, and chromium were higher in the third-tier cities, with levels of 0.08, 0.30 and 97.28 µg/g, respectively. There were two sources with a contribution rate of 38.3 % and 25.8 %, respectively. Potential risk factors for increased metal concentration include long residence time, close to the motorway, decoration within five years, and purchase of new furniture within one year. Under both moderate and high exposure scenarios, chromium showed the highest level of exposure with 6.77 × 10-4 and 2.28 × 10-3 mg·kg-1·d-1, and arsenic imposed the highest lifetime carcinogenic risk at 1.67 × 10-4 and 3.17 × 10-4, respectively. The finding highlighted the priority to minimize childhood exposure of arsenic from household dust.

Pesticide residue and dietary intake risk of vegetables grown in Shanghai under modern urban agriculture in 2018-2021.

Shanghai as an international metropolis is representative of modern urban agriculture in China, so it is of great significance to analyse the pesticide residue in vegetables grown in Shanghai. This study investigated the residue of 68 commonly used pesticides (divided into insecticides, fungicides, herbicides and plant growth regulators) in 7028 vegetable samples in Shanghai from 2018 to 2021, and estimated the dietary intake risk of these pesticides. These samples were divided into 6 categories. A total of 29.21% of vegetable samples had pesticide residues, and 0.47% of samples exceeded the maximum residue limits (MRLs) set by the national food safety standard of China. Leafy vegetables had the highest detection rate of pesticide residues (32.9%), multiple detection rate (12.2%), pesticide residue concentration (35.7 mg/kg), and the number of samples exceeding the MRL (30). There were 36 out of 68 pesticides detected in vegetables, and the top 3 were dimethomorph, propamocarb and acetamiprid. The target hazard quotient (THQ) and hazard index (HI) of these noticeablepesticides were all less than 1, illustrating that there may be no obvious health hazard for residents exposed to the pesticide levels. This study can promote the green development of the pesticide industry and provide important reference data for the monitoring of pesticide residues and their hazards under modern urban agriculture.

Towards ultra-low-cost smartphone microscopy.

The outbreak of COVID-19 exposed the inadequacy of our technical tools for home health surveillance, and recent studies have shown the potential of smartphones as a universal optical microscopic imaging platform for such applications. However, most of them use laboratory-grade optomechanical components and transmitted illuminations to ensure focus tuning capability and imaging quality, which keeps the cost of the equipment high. Here, we propose an ultra-low-cost solution for smartphone microscopy. To realize focus tunability, we designed a seesaw-like structure capable of converting large displacements on one side into small displacements on the other (reduced to ∼9.1%), which leverages the intrinsic flexibility of 3D printing materials. We achieved a focus-tuning accuracy of ∼5 𝜇m, which is 40 times higher than the machining accuracy of the 3D-printed lens holder itself. For microscopic imaging, we used an off-the-shelf smartphone camera lens as the objective and the built-in flashlight as the illumination. To compensate for the resulting image quality degradation, we developed a learning-based image enhancement method. We used the CycleGAN architecture to establish the mapping from smartphone microscope images to benchtop microscope images without pairing. We verified the imaging performance on different biomedical samples. Except for the smartphone, we kept the full costs of the device under 4 USD. We think these efforts to lower the costs of smartphone microscopes will benefit their applications in various scenarios, such as point-of-care testing, on-site diagnosis, and home health surveillance. RESEARCH HIGHLIGHTS: We propose a solution for ultra-low-cost smartphone microscopy. Utilizing the flexibility of 3D-printed material, we can achieve focusing accuracy of ∼5 𝜇m. Such a low-cost device will benefit point-of-care diagnosis and home health surveillance.

Translating color fundus photography to indocyanine green angiography using deep-learning for age-related macular degeneration screening.

Age-related macular degeneration (AMD) is the leading cause of central vision impairment among the elderly. Effective and accurate AMD screening tools are urgently needed. Indocyanine green angiography (ICGA) is a well-established technique for detecting chorioretinal diseases, but its invasive nature and potential risks impede its routine clinical application. Here, we innovatively developed a deep-learning model capable of generating realistic ICGA images from color fundus photography (CF) using generative adversarial networks (GANs) and evaluated its performance in AMD classification. The model was developed with 99,002 CF-ICGA pairs from a tertiary center. The quality of the generated ICGA images underwent objective evaluation using mean absolute error (MAE), peak signal-to-noise ratio (PSNR), structural similarity measures (SSIM), etc., and subjective evaluation by two experienced ophthalmologists. The model generated realistic early, mid and late-phase ICGA images, with SSIM spanned from 0.57 to 0.65. The subjective quality scores ranged from 1.46 to 2.74 on the five-point scale (1 refers to the real ICGA image quality, Kappa 0.79-0.84). Moreover, we assessed the application of translated ICGA images in AMD screening on an external dataset (n = 13887) by calculating area under the ROC curve (AUC) in classifying AMD. Combining generated ICGA with real CF images improved the accuracy of AMD classification with AUC increased from 0.93 to 0.97 (P < 0.001). These results suggested that CF-to-ICGA translation can serve as a cross-modal data augmentation method to address the data hunger often encountered in deep-learning research, and as a promising add-on for population-based AMD screening. Real-world validation is warranted before clinical usage.

Ultrasound-guided puncture drainage versus surgical incision drainage for deep neck space abscesses: a protocol for a systematic review with meta-analysis and trial sequential analysis.

INTRODUCTION: Deep neck space abscesses (DNAs) are serious surgical emergencies, associated with life-threatening complications. Surgical incision and drainage combined with antibiotics is the main treatment for DNAs, but drawbacks still exist. Ultrasound-guided puncture drainage is an alternative treatment for some DNAs with limited clinical evidence. Hence, the optimal drainage technique for the treatment of DNAs remains unclear. Therefore, we will perform a protocol for a systematic review and meta-analysis to identify the efficacy of ultrasound-guided puncture drainage for DNAs. METHODS AND ANALYSIS: PubMed, Ovid Medline, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure, Wanfang database, VIP database and trial registry databases will be searched from inception to September 2023 to identify randomised controlled trials of patients diagnosed with DNAs accepting ultrasound-guided puncture drainage. The primary outcome will be the length of hospital stay. The secondary outcomes will be the cure rate, incidence of retreatment, complications and overall cost to the healthcare system. Fixed-effects or random-effects model will be used according to the statistical heterogeneity. Mean differences or standardised mean differences with 95% CIs for continuous data and risk ratio (RR) with 95% CIs for dichotomous data. The Cochrane risk-of-bias tool 2, Grading of Recommendations Assessment, Development and Evaluation (GRADE) and trial sequential analysis will be conducted to evaluate the evidence quality and control the random errors. Funnel plots and Egger's regression test will be performed to evaluate publication bias. ETHICS AND DISSEMINATION: Ethical approval was not required for this systematic review protocol. The results will be disseminated through peer-reviewed publications. PROSPERO REGISTRATION NUMBER: CRD42023441031.

Bioinspired Gradient Covalent Organic Framework Membranes for Ultrafast and Asymmetric Solvent Transport.

Gradients play a pivotal role in membrane technologies, e.g., osmotic energy conversion, desalination, biomimetic actuation, selective separation, and more. In these applications, the compositional gradients are of great relevance for successful function implementation, ranging from solvent separation to smart devices; However, the construction of functional gradient in membranes is still challenging both in scale and directions. Inspired by the specific function-related, graded porous structures in glomerular filtration membranes, a general approach for constructing gradient covalent organic framework membranes (GCOMx) applying poly (ionic liquid)s (PILs) as template is reported here. With graded distribution of highly porous covalent organic framework (COF) crystals along the membrane, GCOMx exhibts an unprecedented asymmetric solvent transport when applying different membrane sides as the solvent feed surface during filtration, leading to a much-enhanced flux (10-18 times) of the "large-to-small" pore flow comparing to the reverse direction, verified by hydromechanical theoretical calculations. Upon systematic experiments, GCOMx achieves superior permeance in nonpolar (hexane ≈260.45 LMH bar-1) and polar (methanol ≈175.93 LMH bar-1) solvents, together with narrow molecular weight cut-off (MWCO, 472 g mol-1) and molecular weight retention onset (MWRO, <182 g mol-1). Interestingly, GCOMx shows significant filtration performance in simulated kidney dialysis, revealing great potential of GCOMx in bionic applications.

Superior Laryngeal Nerve Block for Microlaryngoscopic Surgery: A Systematic Review and Meta-Analysis.

OBJECTIVES: To assess the safety and efficacy of superior laryngeal nerve block (SLNB) for microlaryngoscopic surgery (MLS). DATA SOURCES: PubMed, Embase, Web of Science, Ovid Medline, Cochrane Library, CNKI database, VIP database, Wanfang database, and trial registry databases. METHODS: PICOS principles were performed: adults undergoing MLS receiving SLNB compared with no-SLNB in randomized controlled trials were included. Primary outcome included the incidence of severe postoperative sore throat (POST). Secondary outcomes included perioperative mean arterial pressure (MAP) and heart rate (HR), incidence of severe postoperative cough, and anesthesia recovery time. RESULTS: Eleven articles with 728 patients were included. Results indicated that SLNB provides lower incidence of severe POST in post-extubation 30 min (relative ratio [RR] = 0.13; 95% confidence intervals [CIs]: 0.05 ~ 0.34), 2 h (RR = 0.09; 95% CI: 0.02 ~ 0.36), 4-6 h (RR = 0.11; 95% CI: 0.03 ~ 0.41), and 24 h (RR = 0.15; 95% CI: 0.03 ~ 0.83); lower MAP (tracheal intubation: standardized mean difference [SMD] = -1.59; 95% CI: -1.69 to -0.42); suspension laryngoscope insertion: (SMD = -0.98; 95% CI: -1.49 to -0.46); tracheal extubation: (SMD = -0.78; 95% CI:-1.24 to -0.31); post-extubation 5 min: (SMD = -0.95; 95% CI: -1.41 to -0.49); lower HR (tracheal intubation: mean difference [MD] = -9.71; 95% CI: -17.16 to -2.27); suspension laryngoscope insertion: (MD = -8.64; 95% CI: -16.79 to -0.49); tracheal extubation: (MD = -10.13; 95% CI: -17.86 to -2.39); post-extubation 5 min: (MD = -13.44; 95% CI: -22.53 to -4.35); lower incidence of severe postoperative cough in post-extubation 30 min (RR = 0.18; 95% CI: 0.06 ~ 0.57) and 2 h (RR = 0.13; 95% CI: 0.02 ~ 0.69); and shorter anesthesia recovery time (MD = -5.34; 95% CI: -8.81 to -1.86) compared to controls. CONCLUSIONS: SLNB could provide lower incidence of severe POST, more stable perioperative MAP and HR, lower incidence of severe postoperative cough, and shorter anesthesia recovery time for MLS. LEVEL OF EVIDENCE: I Laryngoscope, 2024.

ATG14 targets lipid droplets and acts as an autophagic receptor for syntaxin18-regulated lipid droplet turnover.

Lipid droplets (LDs) are dynamic lipid storage organelles that can be degraded by autophagy machinery to release neutral lipids, a process called lipophagy. However, specific receptors and regulation mechanisms for lipophagy remain largely unknown. Here, we identify that ATG14, the core unit of the PI3KC3-C1 complex, also targets LD and acts as an autophagic receptor that facilitates LD degradation. A negative regulator, Syntaxin18 (STX18) binds ATG14, disrupting the ATG14-ATG8 family members interactions and subverting the PI3KC3-C1 complex formation. Knockdown of STX18 activates lipophagy dependent on ATG14 not only as the core unit of PI3KC3-C1 complex but also as the autophagic receptor, resulting in the degradation of LD-associated anti-viral protein Viperin. Furthermore, coronavirus M protein binds STX18 and subverts the STX18-ATG14 interaction to induce lipophagy and degrade Viperin, facilitating virus production. Altogether, our data provide a previously undescribed mechanism for additional roles of ATG14 in lipid metabolism and virus production.

Effects of Zn and oxytetracycline on mobile genetic elements, antibiotic resistance genes, and microbial community evolution in soil.

Antibiotics and heavy metals added to livestock and poultry feed are excreted in manure, which is added to agricultural soil and causes severe pollution. However, the effects of oxytetracycline (OTC) and zinc (Zn), which are present at relatively high levels in feed additives, on antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), and microbial communities have not been comprehensively studied. This study evaluated the effects of OTC and Zn on environmental factors, microorganisms, MGEs, and ARGs. The expression of MGEs in soil was stimulated by adding Zn at concentrations of 500 and 1000 mg/kg or OTC at concentrations of 30 and 100 mg/kg; however, the addition of their combination hindered the expression of MGEs in soil. The abundance of total MGEs and ARGs tended to decrease with increasing concentrations of Zn and OTC and the number of incubation days. Low and high OTC concentrations strongly inhibited sul and tet resistance genes, respectively. Network analysis showed that changes in the population of Firmicutes and Proteobacteria had the greatest impact on ARG abundance. Redundancy analysis revealed that MGEs, particularly intI2, facilitated the transfer and spread of ARGs and had the greatest impact on changes in ARG abundance. These findings provide reference values for the prevention and resolution of ecological and environmental risks posed by the presence of Zn and OTC in organic manure soil.

Development, validation, and implementation of an ultratrace analysis method for the determination of moenomycin A, in aquatic animal products.

Moenomycin A, an antimicrobial growth promoter widely used as an additive in aquaculture feedstuffs, has been restricted for use in the European Union and China due to its potential risk of promoting resistant strains of pathogenic bacteria and causing residues in aquatic animal products. Although methods for analyzing moenomycin A in feedstuffs have been developed, no established method exists for aquatic matrices. In this study, we present, for the first time, a sensitive and validated high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) method for the determination of moenomycin A in aquatic animal products. Samples were extracted using methanol and purified with the QuEChERS method employing C18 sorbent. The aliquot was dried under a nitrogen stream, reconstituted with methanol-water solvent, and analyzed by HPLC-MS/MS. The developed method exhibited good linearity (r2 > 0.995) over a wide concentration range (1-100 µg/L) and a low limit of detection (1 µg/kg). Average recoveries ranged between 70 and 110% at spiked concentrations of 1, 50, and 100 µg/kg, with associated intra- and inter-day relative standard deviations of 1.25 to 7.32% (n = 6) and 2.91 to 10.08% (n = 3), for different representative aquatic animal production, respectively. To the best of our knowledge, this is the first reported HPLC-MS/MS method for the quantification of moenomycin A in aquatic animal products. The new approach was effectively employed in the analysis of moenomycin A across various aquatic samples.

A deep learning model for generating fundus autofluorescence images from color fundus photography.

Background: Fundus Autofluorescence (FAF) is a valuable imaging technique used to assess metabolic alterations in the retinal pigment epithelium (RPE) associated with various age-related and disease-related changes. The practical uses of FAF are ever-growing. This study aimed to evaluate the effectiveness of a generative deep learning (DL) model in translating color fundus (CF) images into synthetic FAF images and explore its potential for enhancing screening of age-related macular degeneration (AMD). Methods: A generative adversarial network (GAN) model was trained on pairs of CF and FAF images to generate synthetic FAF images. The quality of synthesized FAF images was assessed objectively by common generation metrics. Additionally, the clinical effectiveness of the generated FAF images in AMD classification was evaluated by measuring the area under the curve (AUC), using the LabelMe dataset. Results: A total of 8410 FAF images from 2586 patients were analyzed. The synthesized FAF images exhibited an impressive objectively assessed quality, achieving a multi-scale structural similarity index (MS-SSIM) of 0.67. When evaluated on the LabelMe dataset, the combination of generated FAF images and CF images resulted in a noteworthy improvement in AMD classification accuracy, with the AUC increasing from 0.931 to 0.968. Conclusions: This study presents the first attempt to use a generative deep learning model to create authentic and high-quality FAF images from CF images. The incorporation of the translated FAF images on top of CF images improved the accuracy of AMD classification. Overall, this study presents a promising approach to enhance large-scale AMD screening.

Heavy metal contamination in Shanghai agricultural soil.

As heavy metals in soil could enrich in biomass and pose health risk to human, it is vital to monitor their contaminations to ensure qualified agricultural production. In this study, we collected >4000 soil samples from agricultural fields in Shanghai during 2010∼2020, and unveiled heavy metal contamination status in this metropolitan. We found that although Shanghai has a long industrialization history, the heavy metal levels in agricultural soil are within safe ranges according to national standard. Specifically, the median levels of Cd, Hg, As, Pb, Cr and Cu are 0.11, 0.13, 7.47, 23.80, 41.00 and 28.30 mg/kg, respectively, which are as good as, or even better than national averages. However, there are spatial and temporal heterogeneities for heavy metal contaminations in Shanghai. For example, the levels of Cd, Hg and Cr are relatively higher in some districts with high industry density, which should be further monitored in the future. Moreover, while the levels for Cd, Cr and Pb have decreased, the level for Hg has mildly increased during this period which needs counteractive measures. Correlation analysis of heavy metal levels and soil fertility parameters suggested overuse of fertilizers may be related to heavy metal contamination in some regions. In summary, our study present by far the largest and most comprehensive landscape of heavy metal contamination in Shanghai agricultural soil, which will be useful for future policy-design and land use planning to ensure safe agricultural production.

Evaluating the Anti-Melanoma Effects and Toxicity of Cinnamaldehyde Analogues.

Cinnamaldehyde (CA) showed potent activity against melanoma in our previous study, and the structure of unsaturated aldehydes is envisaged to play a role. Nevertheless, its limited drug availability restricts its clinical application. Therefore, a series of CA analogues were synthesized to evaluate their anti-melanoma activities across various melanoma cell lines. These compounds were also tested for their toxicity against the different normal cell lines. The compound with the most potential, CAD-14, exhibited potent activity against the A375, A875 and SK-MEL-1 cells, with IC50 values of 0.58, 0.65, and 0.82 µM, respectively. A preliminary molecular mechanism study of CAD-14 indicated that it could inhibit the p38 pathway to induce apoptosis, and suppress tumor growth by inhibiting the expression of ENO1. Furthermore, an acute toxicity study depicted that CAD-14 has better safety and tolerability than CA in vivo. These findings indicate that CAD-14 might be a lead compound for exploring effective anti-melanoma drugs.

Big data analysis identified a telomere-related signature predicting the prognosis and drug sensitivity in lung adenocarcinoma.

Telomeres exert a critical role in chromosome stability and aberrant regulation of telomerase may result in telomeres dysfunction and genomic instability, which are involved in the occurrence of cancers. However, limited studies have been performed to fully clarify the immune infiltration and clinical significance of telomeres-related genes (TRGs) in lung adenocarcinoma (LUAD). The number of clusters of LUAD was determined by consensus clustering analysis. The prognostic signature was constructed and verified using TCGA and GSE42127 dataset with Least Absolute Shrinkage and Selection Operator cox regression analysis. The correlation between different clusters and risk-score and drug therapy response was analyzed using TIDE and IMvigor210 dataset. Using several miRNA and lncRNA related databases, we constructed a lncRNA-miRNA-mRNA regulatory axis. We identified 2 telomeres-related clusters in LUAD, which had distinct differences in prognostic stratification, TMB score, TIDE score, immune characteristics and signal pathways and biological effects. A prognostic model was developed based on 21 TRGs, which had a better performance in risk stratification and prognosis prediction compared with other established models. TRGs-based risk score could serve as an independent risk factor for LUAD. Survival prediction nomogram was also developed to promote the clinical use of TRGs risk score. Moreover, LUAD patients with high risk score had a high TMB score, low TIDE score and IC50 value of common drugs, suggesting that high risk score group might benefit from receiving immunotherapy, chemotherapy and target therapy. We also developed a lncRNA KCNQ1QT1/miR-296-5p/PLK1 regulatory axis. Our study identified 2 telomeres-related clusters and a prognostic model in LUAD, which could be helpful for risk stratification, prognosis prediction and treatment approach selection.

Water-Soluble Azobenzene-Based Solar Thermal Fuels with Improved Long-Term Energy Storage and Energy Density.

Azobenzene (azo)-based solar thermal fuels (STFs) have been developed to harvest and store solar energy. However, due to the lipophilicity and low energy density of azo-based STFs, the derived devices demand a large amount of toxic organic solvents for continuous and scalable energy storage. Herein, we report an ionic strategy to prepare water-soluble azo-based STFs (WASTFs) with improved energy storage performance, which can be realized through a facile quaternization reaction using commercial reagents. A family of WASTFs were synthesized, and all of them showed good water solubility, long-term thermal half-life (>30 days), and high energy storage density (a highest energy density of ∼143.6 J g-1 corresponding to an energy storage enthalpy of ∼111.8 kJ mol-1). Compared to the electrically neutral azo-based STFs with similar chemical structures, ΔH and thermal half-life (τ1/2) of the WASTFs are 2.5 times higher and 7.3 times longer, respectively. Cation-π interactions between the quaternized moieties [N+(CHx)4] and benzene moieties of azo were confirmed, which could account for their improvement of the energy storage performance. Macroscale heat release with an average temperature difference of ∼2 °C was achieved for the WASTFs prepared in this work. Generally, a novel family of WASTFs are synthesized and show great applicable prospects in fabricating advanced solar energy storage devices.

Optimal concentration of ropivacaine for brachial plexus blocks in adult patients undergoing upper limb surgeries: a systematic review and meta-analysis.

Aim of the Study: Brachial plexus block (BPB) is widely used for patients undergoing upper limb surgeries. Ropivacaine is the most commonly used local anesthetic for BPB. This study aimed to identify the optimal ropivacaine concentration for BPB in adult patients undergoing upper limb surgeries. Materials and Methods: PubMed, Embase, the Cochrane Library, and Web of Science were searched to identify randomized controlled trials (RCTs) that compared the effects of different concentrations of ropivacaine for BPB in adult patients undergoing upper limb surgeries. The primary outcomes were the onset time of sensory and motor block. RevMan 5.4 software was used for analysis. The GRADE approach was used to assess evidence quality. Results: Nine studies involving 504 patients were included. Compared to 0.5% ropivacaine, 0.75% ropivacaine shortened the onset time of sensory (WMD, -2.54; 95% CI; -4.84 to -0.24; <0.0001, moderate quality of evidence) and motor blockade (WMD, -2.46; 95% CI, -4.26 to -0.66; p = 0.01; moderate quality of evidence). However, 0.5% and 0.75% ropivacaine provided similar duration time of sensory (WMD, -0.07; 95% CI, -0.88 to 0.74; p = 0.81; high quality of evidence) and motor blockade (WMD, -0.24; 95% CI, -1.12 to 0.65; p = 0.55; high quality of evidence), as well as time to first request for oral analgesia (WMD, -1.57; 95% CI, -3.14 to 0.01; p = 0.5; moderate quality of evidence). Conclusion: Moderate-quality evidence suggested that, in terms of the onset time of sensory and motor blockade, 0.75% ropivacaine is a preferred concentration for BPB in upper limb surgeries. Systematic Review Registration: identifier CRD42023392145.