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Zeli Xun,1,* Pengfei Gao,2,3,* Yanan Du,1 Xue Yan,3 Jingmin Yang,2– 4 Zhihua Wang1 1Department of Endocrinology, Xi’an Children’s Hospital, Shanxi, People’s Republic of China; 2State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, People’s Republic of China; 3Shanghai WeHealth Biomedical Technology Co, Ltd, Shanghai, People’s Republic of China; 4Key Laboratory of Birth Defects and Reproductive Health of National Health and Family Planning Commission (Chongqing Key Laboratory of Birth Defects and Reproductive Health, Chongqing Population and Family Planning, Science and Technology Research Institute), Chongqing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhihua Wang, Xi’an Children’s Hospital, Shanxi, 710002, People’s Republic of China, Email xasetyy@126.comAim: Mutations in the SLC12A3 gene have been reported to cause Gitelman syndrome (GS), characterized by hypokalemic metabolic alkalosis. The aim of this research is to investigate the genetic mutations and clinical features of patients with clinical suspicion of GS.Methods: Six families were enrolled. The symptoms, clinical examination, laboratory results, genotypes, and effect of mutations on mRNA splicing were analyzed. Genomic DNA was screened for gene variations using whole exome sequence and Sanger sequencing. DNA sequences were compared with reference sequences.Results: Genetic analysis revealed nine genetic variants of SLC12A3, including three novel heterozygous mutations (c.1096– 2A>G, c.1862A>G, and c.2747+4del) and six previously characterized mutations (c.965– 1_976delinsACCGAAAATTTT, c.506– 1G>A, c.602– 16G>A, c.533C >T, c.1456 G>A, and c.1108 G>C). Probands presented with the clinical syndrome of hypokalemia, increased plasma renin, hypocalciuria and hypokalemic alkalosis.Conclusion: These clinical manifestations and genotypes were consistent with the diagnostic criteria of GS. The study described the phenotypes and genotypes of six pedigrees involving GS patients, demonstrating the importance of SLC12A3 gene screening for GS. This study expands the mutation spectrum of SLC12A3 gene in GS.Keywords: SLC12A3, Gitelman syndrome, gene mutation, mRNA splicing, clinical characteristics

Abstract Machining quality prediction based on cutting big data is the core focus of current developments in intelligent manufacturing. Presently, predictions of machining quality primarily rely on process and signal analyses. Process-based predictions are generally constrained to the development of rudimentary regression models. Signal-based predictions often require large amounts of data, multiple processing steps (such as noise reduction, principal component analysis, modulation, etc.), and have low prediction efficiency. In addition, the accuracy of the model depends on tedious manual parameter tuning. This paper proposes a convolutional neural network quality intelligent prediction model based on automatic feature extraction and adaptive data fusion (CNN-AFEADF). Firstly, by processing signals from multiple directions, time-frequency domain images with rich features can be obtained, which significantly benefit neural network learning. Secondly, the corresponding images in three directions are fused into one image by setting different fusion weight parameters. The optimal fusion weight parameters and window length are determined by the Particle Swarm Optimization algorithm (PSO). This data fusion method reduces training time by 16.74 times. Finally, the proposed method is verified by various experiments. This method can automatically identify sensitive data features through neural network fitting experiments and optimization, thereby eliminating the need for expert experience in determining the significance of data features. Based on this approach, the model achieves an average relative error of 2.95%, reducing the prediction error compared to traditional models. Furthermore, this method enhances the intelligent machining level.

Abstract Rationale and Objectives The management of complex renal cysts is guided by the Bosniak classification system, which may be inadequate for risk stratification of patients to determine the appropriate intervention. Radiomics models based on CT imaging may provide additional useful information. Materials and Methods A total of 322 patients with Bosniak II-IV cysts were included in the study from January 2010 to December 2019. Contrast-enhanced CT scans were performed on all patients. ITK-snap was used for segmentation, and the PyRadiomics 3.0.1 package was used for feature extraction. The radiomics features were screened via the least absolute shrinkage and selection operator (LASSO) regression method. After feature selection, a logistic regression (LR) model, support vector machine (SVM) model and random forest (RF) model were constructed. Results In the present study, 217 benign renal cysts (67.4%) and 105 cystic renal cell carcinomas (32.6%) were identified. According to the Bosniak classification, the sample included 179 (55.6%) Bosniak II cysts, 38 (11.8%) Bosniak IIF cysts, 44 (13.7%) Bosniak III cysts and 61 (18.9%) Bosniak IV cysts. A total of 1334 radiomics features were extracted from both unenhanced and cortical CT scans. After LASSO regression, all the models (LR, SVM and RF) showed satisfactory discrimination and reliability in both unenhanced and cortical CT scans (AUC > 0.950). In the Bosniak IIF-III subgroup analysis, the diagnostic accuracy of the LR model was very low for both the unenhanced and cortical scans. In contrast, the SVM model and RF model showed excellent and stable performance in classifying Bosniak IIF-III cysts. The AUCs of the models were all > 0.85, with a maximum of 0.941. The sensitivity, specificity, accuracy, and AUC of the RF model were 0.889, 0.913, 0.902, and 0.941, respectively. Conclusion Our data indicate that radiomics models can effectively distinguish between cystic renal cell carcinoma (cRCC) and complex renal cysts (Bosniak II-IV). Radiomics models may still have high diagnostic accuracy even for Bosniak IIF-III cysts that are clinically difficult to distinguish. However, external validation of these findings is still needed.

Abstract Background It is well-established that understanding the mechanism of prostate cancer (PCa)-associated metastasis is paramount for improving its prognosis. Metastasis is known to involve the communication between tumor-associated macrophages (TAMs) and tumor cells. Exosomes are crucial in mediating this intercellular communication within the tumor microenvironment. Nonetheless, the role of exosomal proteins in PCa metastasis is not yet fully understood. Here, we investigated the mechanisms of prostate cancer-derived exosomal PSM-E on regulating macrophage M2 polarization to suppress tumor invasion and metastasis. Methods PSM-E levels in exosomes were detected by transmission electron microscopy and Western blotting analysis. The diagnostic value of urine-derived exosomal PSM-E in PCa were evaluated by LC-MS/MS, correlation analysis, and ROC curves analysis. The mechanisms underlying the inhibitory effect of exosomal PSM-E on the M2 polarization of macrophages was investigated by co-IP, IHC staining, and PCa tumorigenesis model, etc. Results We revealed that exosomal PSM-E is upregulated in exosomes derived from the serum and urine of PCa patients. Clinically, an elevated exosomal PSM-E expression in urine is significantly correlated with an advanced pathological tumor stage and a high Gleason score. Our research also revealed that exosomal PSM-E inhibits prostate cancer cell proliferation, invasion, and metastasis by suppressing macrophage polarization in vitro and in vivo. Furthermore, we provided compelling evidence that exosomal PSM-E inhibits M2 polarization of macrophages by recruiting RACK1 and suppressing the FAK and ERK signaling pathways, consequently suppressing PCa invasion and metastasis. Furthermore, we found that the protease-associated domain of PSM-E and the fourth tryptophan-aspartate repeat of RACK1 are crucial for the interaction between PSM-E and RACK1. Conclusions Notably, exosomes carrying PSM-E from PCa urine could potentially serve as a biomarker for PCa, and targeting exosomal PSM-E may represent a strategy for preventing tumor progression in this patient population.

Abstract Background Lychee seeds were fermented by three kinds of bacteria (Lactobacillus plantarum, Saccharomyces cerevillus and ganoderma lucidum mycelium), and two effective strains were selected by two indexes of activity content and antioxidant, so as to further verify whether lychee seeds have waste multiplication effect and can protect cells damaged by oxidation from anti-inflammatory, anti-aging and safety. Results The contents of polyphenols, flavonoids and proteins in the solution fermented by Ganoderma lucidum mycelium did not increase, thus affecting the antioxidant capacity of the solution was far less than that of the water extract. The active content of the other two fermentation solutions was higher than that of the water extract, and the ability of scavenging free radicals of the two solutions increased with the increase of the volume fraction. At the cellular level, the two fermentation solutions showed repair effects on UVA-induced damaged cells. The contents of type I collagen (COL-1), total antioxidant capacity and ELN were increased, the contents of reactive oxygen species and MDA were decreased, and the expressions of inflammatory factors IL-6, TNF-a, iNOS and COX-2 were decreased in HaCaT cells. From the gene level, the mRNA contents of IL-6, TNF-a, Caspase-3, Caspase-9, Bax and Bcl were significantly decreased. The test of chick embryo chorioallantoic membrane (HTET CAM) showed that there was no bleeding and litchi seed fermentation liquid was not irritating. Conclusions Therefore, two kinds of litchi seed fermentation can be used as natural plant raw materials for cosmetics, and have strong antioxidant, anti-inflammatory and anti-aging functions on skin, and also have good human safety. Graphical Abstract

Abstract Backgroud Intrauterine Adhesions (IUA) is a common gynecological disease which is seriously endangers the reproductive function of women without any ideal treatment. Some researchers found Menstrual Blood-derived Mesenchymal Stem Cells (MenSCs) can repair of damaged endometrium, however, has not been fully clarified. This study aims to evaluate the therapeutic effects of MenSCs in IUA and the repair mechanism in vivo. Methods This study is Laboratory-based study. To evaluate the therapeutic effects of MenSCs in IUA, We cultivated MenSCs, established mouse endometrial injury model, observed the uterine morphology and degree of endometrial fibrosis and compared the expression of CXC chemokine ligand-13 (CXCL13)、CXC chemokine receptor-5 (CXCR5)、Plasmin Activating Inhibitor-1(Pai-1), Transforming Growth Faction-β1(TGF- β1) and Matrix Metalloproteinase-9 (Mmp-9) among each groups. GraphPad Prism 8.0 was used for statistical processing. Data were expressed as mean ± SD. Statistical comparisons among groups were performed with one-way ANOVA. P

Abstract Polyvinyl chloride (PVC) is the world’s third-most widely manufactured thermoplastic, but has the lowest recycling rate. The development of PVC-like plastics that can be depolymerized back to monomer contributes to a circular plastic economy, but has not been accessed. Here, we develop a series of chemically recyclable plastics from the reversible copolymerization of cyclic anhydride with chloral. The copolymerization is highly efficient through the anionic or cationic mechanism under mild conditions, yielding polyesters with tunable structure and properties from multiple commercial monomers. Notably, these polyesters manifest mechanical properties comparable to PVC and polystyrene. Meanwhile, such polyesters are flame-retardant like PVC due to high chloride content. Of significance, these polyesters can be depolymerized back to starting monomers at high temperatures owing to the reversibility of the copolymerization, leading to a circular economy. Overall, the readily available monomers, simple synthesis, advantageous performance, and practical recyclability make the polymers promising for applications.

Abstract The severe mismatch between solid bioelectronics and dynamic biological tissues has posed enduring challenges in the biomonitoring community. Here, we developed a reconfigurable liquid cardiac sensor capable of adapting to dynamic biological tissues, facilitating ambulatory cardiac monitoring unhindered by motion artifacts or interference from other biological activities. We employed an ultrahigh-resolution 3D scanning technique to capture tomographic images of the skin on the wrist. Then, we established a theoretical model to gain a deep understanding of the intricate interaction between our reconfigurable sensor and dynamic biological tissues. To properly elucidate the advantages of this sensor, we conducted cardiac monitoring alongside benchmarks such as the electrocardiogram. The liquid cardiac sensor was demonstrated to produce stable signals of high quality (23.1 dB) in ambulatory settings.

Abstract Background Both interpregnancy intervals (IPI) and environmental factors might contribute to low birth weight (LBW). However, the extent to which air pollution influences the effect of IPIs on LBW remains unclear. We aimed to investigate whether IPI and air pollution jointly affect LBW. Methods A retrospective cohort study was designed in this study. The data of birth records was collected from the Jiangsu Maternal Child Information System, covering January 2020 to June 2021 in Nantong city, China. IPI was defined as the duration between the delivery date for last live birth and date of LMP for the subsequent birth. The maternal exposure to ambient air pollutants during pregnancy—including particulate matter (PM) with an aerodynamic diameter of ≤ 2.5 μm (PM2.5), PM10, ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2) and carbon monoxide (CO)—was estimated using a hybrid kriging-LUR-RF model. A novel air pollution score was proposed, assessing combined exposure to five pollutants (excluding CO) by summing their concentrations, weighted by LBW regression coefficients. Multivariate logistic regression models were used to estimate the effects of IPI, air pollution and their interactions on LBW. Relative excess risk due to interaction (RERI), attributable proportion of interaction (AP) and synergy index (S) were utilized to assess the additive interaction. Results Among 10, 512 singleton live births, the LBW rate was 3.7%. The IPI-LBW risk curve exhibited an L-shaped pattern. The odds ratios (ORs) for LBW for each interquartile range increase in PM2.5, PM10, O3 and the air pollution score were 1.16 (95% CI: 1.01–1.32), 1.30 (1.06–1.59), 1.22 (1.06–1.41), and 1.32 (1.10–1.60) during the entire pregnancy, respectively. An additive interaction between IPI and PM2.5 was noted during the first trimester. Compared to records with normal IPI and low PM2.5 exposure, those with short IPI and high PM2.5 exposure had the highest risk of LBW (relative risk = 3.53, 95% CI: 1.85–6.49, first trimester). Conclusion The study demonstrates a synergistic effect of interpregnancy interval and air pollution on LBW, indicating that rational birth spacing and air pollution control can jointly improve LBW outcomes.

Abstract The COVID-19 pandemic has underscored the critical need for precise diagnostic methods to distinguish between similar respiratory infections, such as COVID-19 and Mycoplasma pneumoniae (MP). Identifying key biomarkers and utilizing machine learning techniques, such as random forest analysis, can significantly improve diagnostic accuracy. We conducted a retrospective analysis of clinical and laboratory data from 214 patients with acute respiratory infections, collected between October 2022 and October 2023 at the Second Hospital of Nanping. The study population was categorized into three groups: COVID-19 positive (n = 52), MP positive (n = 140), and co-infected (n = 22). Key biomarkers, including C-reactive protein (CRP), procalcitonin (PCT), interleukin- 6 (IL-6), and white blood cell (WBC) counts, were evaluated. Correlation analyses were conducted to assess relationships between biomarkers within each group. The random forest analysis was applied to evaluate the discriminative power of these biomarkers. The random forest model demonstrated high classification performance, with area under the ROC curve (AUC) scores of 0.86 (95% CI: 0.70–0.97) for COVID-19, 0.79 (95% CI: 0.64–0.92) for MP, 0.69 (95% CI: 0.50–0.87) for co-infections, and 0.90 (95% CI: 0.83–0.95) for the micro-average ROC. Additionally, the precision-recall curve for the random forest classifier showed a micro-average AUC of 0.80 (95% CI: 0.69–0.91). Confusion matrices highlighted the model’s accuracy (0.77) and biomarker relationships. The SHAP feature importance analysis indicated that age (0.27), CRP (0.25), IL6 (0.14), and PCT (0.14) were the most significant predictors. The integration of computational methods, particularly random forest analysis, in evaluating clinical and biomarker data presents a promising approach for enhancing diagnostic processes for infectious diseases. Our findings support the use of specific biomarkers in differentiating between COVID-19 and MP, potentially leading to more targeted and effective diagnostic strategies. This study underscores the potential of machine learning techniques in improving disease classification in the era of precision medicine.

Abstract Background The region-specific importance of carcinogenic HPV genotypes is required for optimizing HPV-based screening and promoting appropriate multivalent HPV prophylactic vaccines. This information is lacking for Ningbo, one of the first cities of China’s Healthy City Innovation Pilot Program for Cervical Cancer Elimination. Here, we investigated high-risk HPV (HR-HPV) genotype-specific distribution and attribution to biopsy-confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+) before mass vaccination in Ningbo, China. Methods A total of 1393 eligible CIN2+ archived blocks (including 161 CIN2, 1107 CIN3, and 125 invasive cervical cancers [ICC]) were collected from 2017 to 2020 in Ningbo. HR-HPV DNA was genotyped using the SPF10-DEIA-LiPA25 version 1 detection system and the SureX HPV 25X Genotyping Kit. Genotype-specific attribution to CIN2+ was estimated using a fractional contribution approach. Results Ranking by the attributable proportions, HPV16 remained the most important genotype in both cervical precancers and cancers, accounting for 36.8% of CIN2, 53.2% of CIN3, and 73.3% of ICC cases. Among cervical precancers, HPV52 (17.3% in CIN2, 12.7% in CIN3) and HPV58 (13.9%, 14.9%) ranked second and third, while HPV33 (8.3%, 7.9%) and HPV31 (6.5%, 4.1%) ranked fourth and fifth, respectively. However, among ICCs, HPV18 (5.7%) accounted for the second highest proportion, followed by HPV33 (5.4%), HPV58 (4.0%), and HPV45 (3.2%). HPV18/45 together accounted for 46.8% of adenocarcinomas, which was slightly lower than that of HPV16 (47.7%). The remaining HR-HPV genotypes (HPV35/39/51/56/59/66/68) combined accounted for only 6.7% of CIN2, 2.9% of CIN3, and 4.2% of ICC. Conclusions With Ningbo’s strong medical resources, it will be important to continue HPV16/18 control efforts, and could broaden to HPV31/33/45/52/58 for maximum health benefits. However, different strategies should be proposed for other HR-HPV genotypes based on their lower carcinogenic risks.

Abstract. Background:. Evaluating the impact of digestive system diseases is vital for devising effective prevention strategies. However, comprehensive reports on the burden of digestive system diseases in China are lacking. Our study aimed to provide an overview of the burden and trends of digestive system diseases from 1990 to 2019 in China and its provinces. Methods:. This cross-sectional study utilized the Global Disease Burden Study 2019 to estimate the incidence, mortality rate, disability-adjusted life years (DALYs), years of life disability, years of life lost, and changes in the burden of digestive diseases across Chinese provinces from 1990 to 2019. The analysis of disease burden primarily examines the characteristics of sub-disease distribution, time trends, age distribution, and sex distribution. Additionally, we compared provincial age-standardized DALYs for digestive diseases with the expected rates based on the socio-demographic index (SDI). Results:. In 2019, there were 499.2 million cases of digestive system diseases in China, resulting in 1,557,310 deaths. Stomach cancer, colon and rectal cancer, and esophageal cancer are the top three diseases associated with mortality and DALY related to digestive system diseases. Meanwhile, cirrhosis and other chronic liver diseases, gastroesophageal reflux disease, and gallbladder and biliary diseases are the top three kinds of diseases with the highest prevalence among digestive system diseases. The risk of gastric cancer sharply increases among men after the age of 40 years, leading to a significant disparity in burden between men and women. As the SDI increased, the DALYs associated with digestive system diseases in China and its provinces showed a downward trend. Conclusion:. Our study highlights the inverse correlation between DALYs associated with digestive system diseases and the SDI.

Abstract Background Worldwide, ulcerative colitis (UC) is becoming increasingly fast growing. Ginsenoside Rh2 has been reported to alleviate UC. However, the latent biological mechanism of Rh2 in the treatment of UC remains uncertain. In this study, the goal was to determine the therapeutic effect of Rh2 on dextran sulfate sodium (DSS)-induced UC. Methods A DSS-induced UC mouse model was established and divided into 7 groups for Rh2 gavage and/or miR-125a-5p lentivirus injection (n = 10 per group). Colonic specimens were collected for phenotypic and pathological analysis. miR-125a-5p and specific protein 1 (SP1) expression, inflammation-related factors IL-6 and IL-10, and apoptosis were detected in mice. Human normal colon epithelial cell line NCM460 was treated with H2O2 and ferric chloride hexahydrate to construct an in vitro cell model of colitis and induce ferroptosis. Independent sample t-test was used to compare cell proliferation, cell entry, apoptosis, and oxidative stress between the two groups. One way analysis of variance combined with the least significant difference t test was used for comparison between groups. Multiple time points were compared by repeated measurement analysis of variance. Results DSS-induced UC mice had significantly decreased body weight, increased disease activity index, decreased colon length, and decreased miR-125a-5p expression (all P

Abstract The planthopper Nilaparvata muiri is a sister species to N. lugens (Hemiptera: Delphacidae), a notorious insect pest in Asian rice fields. N. muiri and N. lugens have a different host preference despite the similarities in many biological features. To better understand the adaptive evolution of planthoppers, comprehensive genomic information on N. muiri and N. lugens are urgently needed. In this study, we used ultra-low input PacBio HiFi libraries and Hi-C sequencing technologies to assemble a reference genome of a single N. muiri at the chromosomal level. The genome size was determined to be 531.62 Mb with a contig N50 size of 2.47 Mb and scaffold N50 size of 38.37 Mb. Totally, 96.61% assembled sequences were anchored to the 15 pseudo-chromosomes. BUSCO analysis yielded an Insecta completeness score of 98.6%. A total of 22,057 protein-coding genes were annotated, and 168.16 Mb repetitive sequences occupying 31.63% of genome were pinpointed. The assembled genome is valuable for evolutionary and genetic studies of planthoppers, and may provide sights to pest control.

Abstract Given the growing emphasis on energy efficiency, environmental sustainability, and agricultural demand, there’s a pressing need for decentralized and scalable ammonia production. Converting nitrate ions electrochemically, which are commonly found in industrial wastewater and polluted groundwater, into ammonia offers a viable approach for both wastewater treatment and ammonia production yet limited by low producibility and scalability. Here we report a versatile and scalable solution-phase synthesis of high-entropy single-atom nanocages (HESA NCs) in which Fe and other five metals-Co, Cu, Zn, Cd, and In-are isolated via cyano-bridges and coordinated with C and N, respectively. Incorporating and isolating the five metals into the matrix of Fe resulted in Fe-C5 active sites with a minimized symmetry of lattice as well as facilitated water dissociation and thus hydrogenation process. As a result, the Fe-HESA NCs exhibited a high selectivity toward NH3 from the electrocatalytic reduction of nitrate with a Faradaic efficiency of 93.4% while maintaining a high yield rate of 81.4 mg h−1 mg−1.

Abstract This paper presents a novel approach to the phase space reconstruction technique, fractional-order phase space reconstruction (FOSS), which generalizes the traditional integer-order derivative-based method. By leveraging fractional derivatives, FOSS offers a novel perspective for understanding complex time series, revealing unique properties not captured by conventional methods. We further develop the multi-span transition entropy component method (MTECM-FOSS), an advanced complexity measurement technique that builds upon FOSS. MTECM-FOSS decomposes complexity into intra-sample and inter-sample components, providing a more comprehensive understanding of the dynamics in multivariate data. In simulated data, we observe that lower fractional orders can effectively filter out random noise. Time series with diverse long- and short-term memory patterns exhibit distinct extremities at different fractional orders. In practical applications, MTECM-FOSS exhibits competitive or superior classification performance compared to state-of-the-art algorithms when using fewer features, indicating its potential for engineering tasks.

Abstract Despite the well-established significance of transcription factors (TFs) in pathogenesis, their utilization as pharmacological targets has been limited by the inherent challenges in modulating their protein interactions. The lack of defined small-molecule binding pockets and the nuclear localization of TFs do not favor the use of traditional tools. Aptamers possess large molecular weights, expansive blocking surfaces and efficient cellular internalization, making them compelling tools for modulating TF interactions. Here, we report a structure-guided design strategy called Blocker-SELEX to develop inhibitory aptamers (iAptamers) that selectively block TF interactions. Our approach leads to the discovery of iAptamers that cooperatively disrupt SCAF4/SCAF8-RNAP2 interactions, dysregulating RNAP2-dependent gene expression, which impairs cell proliferation. This approach is further applied to develop iAptamers blocking WDR5-MYC interactions. Overall, our study highlights the potential of iAptamers in disrupting pathogenic TF interactions, implicating their potential utility in studying the biological functions of TF interactions and in nucleic acids drug discovery.

Abstract Background Parathyroid carcinoma (PC) is a rare malignancy, often diagnosed incidentally through postoperative pathological examination. The occurrence of nodular goiter, intrathyroidal parathyroid carcinoma, contralateral parathyroid adenoma (PA), and papillary thyroid microcarcinoma (PTMC) is extremely uncommon, which prompted us to report our case experience. Case presentation We describe a 67-year-old male who presented with a cervical mass causing tracheal compression, which prompted him to seek medical advice. Based on preoperative auxiliary examination results from color Doppler ultrasound, SPECT parathyroid imaging, and blood tests, he was initially diagnosed with a suspected parathyroid adenoma and nodular goiter. Excision of the right lobe and isthmus of the thyroid, and left superior parathyroid gland was conducted, which were sent to intraoperative frozen pathological examination. During intraoperative observation, adhesion around the right thyroid lobe was discovered. Consequently, right central area lymph node dissection was performed due to suspicion of an aggressive malignant tumor. Histology and immunohistochemistry analysis revealed incidental intrathyroidal parathyroid carcinoma, contralateral parathyroid adenoma, classical papillary thyroid microcarcinoma, and nodular goiter. Conclusion Parathyroid carcinoma should be highly suspected when extremely high levels of PTH and severe hypercalcemia are present, which cannot be simply explained by a preoperatively localized parathyroid adenoma, especially when suspicious malignant adhesion is found during intraoperative exploration. In cases where multifocal thyroid nodules are associated with increased uptake of 99Tc-sestamibi, the possibility of coexisting carcinomas should be considered, not only for thyroid malignancy but also for the potential presence of intrathyroidal parathyroid carcinoma.

Abstract. Background:. Early detection of esophageal squamous cell carcinoma (ESCC) can considerably improve the prognosis of patients. Aberrant cell-free DNA (cfDNA) methylation signatures are a promising tool for detecting ESCC. However, available markers based on cell-free DNA methylation are still inadequate. This study aimed to identify ESCC-specific cfDNA methylation markers and evaluate the diagnostic performance in the early detection of ESCC. Methods:. We performed whole-genome bisulfite sequencing (WGBS) for 24 ESCC tissues and their normal adjacent tissues. Based on the WGBS data, we identified 21,469,837 eligible CpG sites (CpGs). By integrating several methylation datasets, we identified several promising ESCC-specific cell-free DNA methylation markers. Finally, we developed a dual-marker panel based on methylated KCNA3 and OTOP2, and then, we evaluated its performance in our training and validation cohorts. Results:. The ESCC diagnostic model constructed based on KCNA3 and OTOP2 had an AUC of 0.91 [95% CI: 0.85–0.95], and an optimal sensitivity and specificity of 84.91% and 94.32%, respectively, in the training cohort. In the independent validation cohort, the AUC was 0.88 [95% CI: 0.83–0.92], along with an optimal sensitivity of 81.5% and specificity of 92.9%. The model sensitivity for stage I–II ESCC was 78.4%, which was slightly lower than the sensitivity of the model (85.7%) for stage III–IV ESCC. Conclusion:. The dual-target panel based on cfDNA showed excellent performance for detecting ESCC and might be an alternative strategy for screening ESCC.

Abstract Ethylene regulates plant growth, development, and stress adaptation. However, the early signaling events following ethylene perception, particularly in the regulation of ethylene receptor/CTRs (CONSTITUTIVE TRIPLE RESPONSE) complex, remains less understood. Here, utilizing the rapid phospho-shift of rice OsCTR2 in response to ethylene as a sensitive readout for signal activation, we revealed that MHZ3, previously identified as a stabilizer of ETHYLENE INSENSITIVE 2 (OsEIN2), is crucial for maintaining OsCTR2 phosphorylation. Genetically, both functional MHZ3 and ethylene receptors prove essential for OsCTR2 phosphorylation. MHZ3 physically interacts with both subfamily I and II ethylene receptors, e.g., OsERS2 and OsETR2 respectively, stabilizing their association with OsCTR2 and thereby maintaining OsCTR2 activity. Ethylene treatment disrupts the interactions within the protein complex MHZ3/receptors/OsCTR2, reducing OsCTR2 phosphorylation and initiating downstream signaling. Our study unveils the dual role of MHZ3 in fine-tuning ethylene signaling activation, providing insights into the initial stages of the ethylene signaling cascade.

Abstract Measurement of the cervical range of motion (CROM) is significant for early diagnosis of cervical spondylosis and determination of the severity of the disease. Aiming at the problem of convenient and continuous measurement of CROM and the reduction of the impact of data fluctuations, this paper proposes a low‐cost method for testing and analyzing CROM. This paper analyzes the correspondence between smartphone orientation sensor angle and CROM, obtains smartphone orientation sensing data, and uses the extreme‐point symmetric mode decomposition method by calculating the energy of the difference value to extract the adaptive global mean curve of the CROM data, and calculates the cervical ROM. The statistical analysis of the CROM test results is carried out. Results show that the method proposed can obtain the CROM including flexion and extension, lateral flexion, and rotation in a single measurement, which has the advantages of continuous measurement and low cost.

Leaf chlorophyll content (LCC) retrieval from remote sensing imagery is essential for monitoring vegetation growth and stress in the agroforestry industry. Many remote sensing inversion methods for estimating LCC primarily rely on 1D radiative transfer models (RTMs) that abstract canopies into horizontal layers or simple geometric primitives. Yet, this methodology faces challenges when applied to heterogeneous canopies, particularly in fine-scale mapping where each pixel's reflectance is significantly influenced by its surroundings, e.g. crown shadows. While 3D RTMs hold promise for addressing these challenges by explicitly describing complex canopy structures, their computational demands and the complexity involved in parameterizing detailed 3D structures limit the generation of extensive training datasets, requiring simulations across numerous parameter combinations. In this study, we used a semi-empirically accelerated 3D RTM, termed Semi-LESS, with a 1D residual network to accurately retrieve leaf chlorophyll content (LCC) from UAV images and LiDAR data at a 3-m resolution. We first reconstructed structures of forest plots using UAV LiDAR point cloud, based on which, UAV images with varying leaf and soil optical properties are simulated using the Semi-LESS. Subsequently, a training dataset consisting LCC and its corresponding reflectance was generated from the simulated UAV images by focusing on sunlit pixels. A 1D residual network is trained using the training dataset for LCC estimation. For comparison, we also trained an estimation model using a dataset generated from PROSAIL. The results show that estimation model trained with Semi-LESS surpasses PROSAIL in retrieving LCC from both simulation datasets and field measurements of two forest plots. The RMSE of Semi-LESS was 5.40–6.92 µg/cm2 for simulation datasets and 8.21–9.76 µg/cm2 for field measurements, whereas PROSAIL exhibited lower accuracy with an RMSE of 7.76–9.83 µg/cm2 for simulation datasets and 12.76–13.06 µg/cm2 in field measurements. The results demonstrate that Semi-LESS coupled with deep learning is reliable and has great potential for LCC mapping using UAV images, which is particularly useful for fine-scale applications such as crop and orchard monitoring. This approach also highlights the impact of shadows on LCC retrieval.

In mines with deep levels and those exhibiting anomalous geothermal temperatures, high geothermal environments can affect the erosion process of waterlogged coal by immersion. To study the influence of a high geothermal environment regarding the self-ignition of waterlogged coal, immersion of the coals in aqueous solutions under various temperature conditions (room temperature 20 °C, 40 °C, 60 °C and 80°) for 30 days. Low-temperature nitrogen adsorption, infrared spectroscopy, and simultaneous thermal analysis were utilized to examine the alterations in the micro physicochemical structure and oxidation process of waterlogged coal samples at room temperature and high geothermal temperature. Compared with room temperature conditions, the high geothermal environment increased the number and volume of pores in the waterlogged coal, broke intermolecular hydrogen bonds, and increased the total number of reactive groups. These microstructural changes affected the oxidation process of the waterlogged coal, causing in the oxidation characteristic temperature points on the TG and DSC curves as well as the activation energies E of the second and third stages of TG being significantly lower than those of the waterlogged coal under room temperature conditions. This study suggests that the high geothermal environment enhances the spontaneous combustion tendency of waterlogged coal and accelerates its oxidation process.

Study region: The Nujiang Fault Zone near Baoshan in western Yunnan. Study focus: Major hydrochemical elements and stable isotopes of 15 hot spring water samples are analyzed to reveal hydrogeochemical evolution processes, recharge sources, geothermal conditions, and structural control genesis of the hot springs. New hydrological insight for the region: Baoshan is experiencing a wave of clean energy development, specifically geothermal energy. The Nujiang Fault Zone, which separates the Tengchong Block from the Baoshan Block, constitutes a low- to medium-temperature geothermal system characterized by numerous hot springs. The hot springs under investigation are located near Baoshan along the Nujiang Fault. Four hydrochemical types have been identified, with HCO3-Ca⋅Mg being the predominant type. The primary components of spring waters originate from the weathering or dissolution of carbonate and silicate minerals, as well as the reverse cation exchange. Stable isotopes indicate that these hot springs are predominantly formed by the atmospheric precipitation during the summer monsoon. The recharge areas are located in the mountainous regions around the Nujiang River, at elevations ranging from 1606 to 2504 m and temperatures between 3°C and 8°C. The estimated temperature of the geothermal reservoir ranges from 73°C to 192°C. During the ascent process, the mixing ratio of cold water is between 60 % and 79 %, and the circulation depth ranges from 1928 to 4221 m. The positive correlation between Li and Cl indicates that hot springs originate from the same parent geothermal fluid controlled by the Nujiang Fault or by two secondary faults intersecting at depths. The hot springs with shallower circulation depths are mainly composed of HCO3-Ca⋅Mg type, while the deeper circulating spring waters consist primarily of HCO3-Na type. The height difference between the discharge location of the hot springs and the surface of the Nujiang River correlates positively with the geothermal reservoir temperature. This paper emphasizes the hydrogeochemical characterization of hot springs within regional fault zones, which holds significant implications for the development and exploration of geothermal systems in similar structural control areas.

The quadrivalent human papillomavirus (qHPV) vaccine demonstrated high efficacy against vaccine-type-related precancers in Chinese females through a 6.6-year double-blind, randomized control trial (V501–041, NCT00834106). We present results for its long-term follow-up (LTFU) phase, evaluating vaccine effectiveness and immunogenicity throughout 13 years post Dose 1. Participants receiving qHPV vaccines at ages 20–45 in the V501–041 study constituted the early vaccination group (EVG). Those who received the placebo in V501–041 but were vaccinated during 2018–2020 formed the catch-up vaccination group (CVG), while the control group (CG) comprised those remaining unvaccinated throughout V501–041 and LTFU. The primary endpoint was histopathologically-confirmed cervical intraepithelial neoplasia (CIN) 2+ tested PCR-positive for HPV-16/18. Antibodies against HPV-6, 11, 16, and 18 were assessed using an immunoglobulin G (IgG) Luminex immunoassay at year 13. A total of 1100 participants from V501–041, of whom 978 were followed in LTFU, were included with a median follow-up of 152.2 months. No cases of the primary endpoint were observed in the EVG during 5513.6 person-years of follow-up, while one case was observed in the CG over 2951.4 person-years of follow-up, indicating a 100% risk reduction in the EVG compared to the CG. In the CVG, no cases were detected from vaccination to the latest follow-up (0.0 per 10 000 person-years), contrasting with an incidence of 22.3 per 10 000 person-years prior to vaccination. Seropositivity rates at year 13 remained >92% (for HPV-6/11/16) and 84% (HPV-18). These findings demonstrated continued vaccine protection against cervical precancers and sustained immunogenicity through 13 years post-vaccination.Trial Registration The LTFU study was registered at the Chinese Clinical Trial Registry, ChiCTR2100052313.

The performance degradation is a crucial factor affecting the commercialization of proton exchange membrane electrolyzer. However, it is difficult to establish a mechanism model incorporating all degradation categories due to their different time and spatial scales. In this paper, the data-driven method is employed to predict the electrolyzer voltage variation over time based on a convolutional neural network-long short term memory (CNN-LSTM) model. First, two datasets including constant operation for 1140 h and start-stop load for 660 h are collected from the durability tests. Second, the data-driven models are trained through the experimental data and the model hyper-parameters are optimized. Finally, the electrolyzer degradation in the next few hundred hours is predicted, and the prediction accuracy is compared with other time-series algorithms. The results show that the model can predict the degradation precisely on both datasets, with the R2 higher than 0.98. Compared to conventional models, the algorithm shows better fitting characteristic to the experimental data, especially as the prediction time increases. For constant and start-stop operations, the electrolyzers degradate by 4.5 % and 2.5 % respectively after 1000 h. The proposed method shows great potential for real-time monitoring in the electrolyzer system.

The human gastrointestinal tract, boasting the most diverse microbial community, harbors approximately 100 trillion microorganisms comprising viruses, bacteria, fungi, and archaea. The profound genetic and metabolic capabilities of the gut microbiome underlie its involvement in nearly every facet of human biology, from health maintenance and development to aging and disease. Recent recognition of microbiota – gut – brain axis, referring to the bidirectional communication network between gut microbes and their host, has led to a surge in interdisciplinary research. This review begins with an overview of the current understandings regarding the influence of gut microbes on intestinal and blood-brain barrier integrity. Subsequently, we discuss the mechanisms of the microbiota – gut – brain axis, examining the role of gut microbiota-related neural transmission, metabolites, gut hormones and immunity. We propose the concept of microbiota-mediated multi-barrier modulation in the potential treatment in gastrointestinal and neurological disorders. Furthermore, the role of lymphatic network in the development and maintenance of barrier function is discussed, providing insights into lesser-known conduits of communication between the microbial ecosystem within the gut and the brain. In the final section, we conclude by describing the ongoing frontiers in understanding of the microbiota – gut – brain axis’s impact on human health and disease.

ABSTRACTThe discrepancies in data across different phases and the unexplored optimal spatial resolution present challenges when using multi-temporal canopy height models to accurately discern actual forest growth. In this study, we evaluated the reliability of bi-temporal CHMs to characterize growth changes in a boreal natural forest over a four-year period. A maximum mosaic method was introduced to construct a CHM from various flight strips, aimed at minimizing data alignment errors. Subsequently, the canopy height and height changed derived from six different height percentile metrics and five spatial resolutions were evaluated. The results showed that higher resolution (e.g., < 2 m) and lower height metrics (e.g., 85th height percentile) consistently underestimated. Tree growth correlation with individual segmentation surpassed field-measurements at all resolutions and height metrics. for the optimal resolution and height metrics, the results suggest that using a 95th height percentile the 10 m scale effectively represents both canopy height ([Formula: see text] = 0.95, [Formula: see text] = 0.88 m, [Formula: see text] = 5.83%; [Formula: see text] = 0.96, [Formula: see text] = 1.11 m, [Formula: see text] = 6.91%) and height changes ([Formula: see text] = 0.59, [Formula: see text] = 0.86 m, [Formula: see text] = 18.38%). This study demonstrates the necessity of carefully evaluating data characteristics and resolutions when employing multi-temporal CHM for forest dynamics monitoring.

Abstract Global reanalyzes are widely used for investigations of Antarctic climate variability and change. The European Centre for Medium‐Range Weather Forecasts 5th generation reanalysis (ERA5) is well regarded and spans 1940 to today. We investigate whether ERA5 reliably represents the 2‐m air temperature trends across the 1940–2022 (83 years) period at seasonal and annual time scales. We compare ERA5 temperatures with an observation‐based temperature reconstruction for Antarctica (RECON) that has monthly resolution for 1958–2022, the period of reliable observational availability. Results for individual stations are also examined. ERA5 anomalously warms Antarctica in relation RECON especially for the period prior to 1979 when satellite observations over the Southern Ocean were sparse. Trend hotspots that are shown to be artifacts are found at three locations and are present until today. The results demonstrate that ERA5 temperature trends can be questionable even today, but variability is well captured after 1979.

Biofilm reactors, known for utilizing biofilm formation for cell immobilization, offer enhanced biomass concentration and operational stability over traditional planktonic systems. However, the dense nature of biofilms poses challenges for substrate accessibility to cells and the efficient release of products, making mass transfer efficiency a critical issue in these systems. Recent advancements have unveiled the intricate, heterogeneous architecture of biofilms, contradicting the earlier view of them as uniform, porous structures with consistent mass transfer properties. In this review, we explore six biofilm reactor configurations and their potential combinations, emphasizing how the spatial arrangement of biofilms within reactors influences mass transfer efficiency and overall reactor performance. Furthermore, we discuss how to apply artificial intelligence in processing biofilm measurement data and predicting reactor performance. This review highlights the role of biofilm reactors in environmental and energy sectors, paving the way for future innovations in biofilm-based technologies and their broader applications.

ABSTRACT: Currently, developing nonantibiotic growth promoters is a broad consensus in broiler industry, which is one of the effective ways to reduce drug-resistant strains. Chuanminshen violaceum is a traditional Chinese medicinal herb that is commonly used for its roots, while the stems and leaves are often discarded, resulting in a huge amount of waste. This study optimized the preparation process of water extract of Chuanminshen violaceum stems and leaves (CVSLE) by response surface analysis based on the yields of polysaccharide and protein. The CVSLE and herbal powder (CVSL) were then processed into granules before being used as feed additives. The Macleaya cordata powder was used as positive control. The results showed that the addition of CVSLE (0.5% of the feed) showed the highest growth-promoting activity than other CVSLE groups (0.2% and 1%), 1% CVSL group and positive control (0.05%). CVSLE at the dosage of 0.5% could significantly increase the ADG and reduce the FCR from d 21 to 42, d 0 to 42. The HI antibody titers against Newcastle disease virus and avian influenza virus were significantly enhanced at 21, 28 and 42 d. CVSLE did not affect the slaughtering performances, but could significantly elevate the spleen, thymus and bursa of Fabricius indices and the transcriptional levels of IL-2, IL-4, IL-10 and IFN-γ in spleen. The intestinal barrier function of broilers was significantly enhanced by increased levels of immune barrier (sIgA), physical barrier (ZO-1, OCL and Muc-2) and flora barrier (Lactobacillus and Bifidobacterium). These results suggest that CVSLE was a promising herbal additive candidate for broilers.

ObjectiveThe research focused on a comparative analysis of triage strategies for women with Atypical Squamous Cells of Undetermined Significance (ASC-US) before and after receiving the HPV vaccine, aiming to optimize cervical cancer prevention strategies, especially in resource-limited healthcare settings.Materials and methodsBetween September 2018 and December 2023, 7,511 women aged 21 years or older who underwent liquid-based cytology for cervical cancer screening were recruited. Women diagnosed with ASC-US were included in the study. All participants underwent HPV testing and liquid-based cytology examination, and those with abnormal results were referred for colposcopy. Women with abnormal colposcopy findings underwent further histopathological examination. The gold standard for diagnosis was pathological, with cervical intraepithelial neoplasia grade 2 or higher (CIN2+) on histology as the endpoints. In the final analysis, 933 women with ASC-US were enrolled as the unvaccinated group, with 179 of them testing positive for HPV 16/18. Assuming that all women would receive the bivalent vaccine targeting HPV 16/18 in the post-vaccine era, and given that the vaccine protection rate is 100% against HPV 16/18, then 754 women excluding those of HPV 16/18 positive would comprise the vaccinated group.ResultsIn the unvaccinated group, the overall HPV positivity rate was 59.27% among ASC-US women, with a 100% HPV prevalence rate among those with CIN2+ lesions. The combination genotyping model of HPV16/18 showed the highest specificity (81.77%) and the lowest referral rate (32.37%). In the vaccinated group, the HPV positivity rate was 49.61% among ASC-US women, with a 100% HPV prevalence rate among those with CIN2+ lesions. The specificity of HPV33/58 was the highest (86.99%), and the colposcopy referral rate was lowest (27.54%), with statistical significance. Sensitivity, positive predictive value, and negative predictive value were not statistically significant.ConclusionHPV16/18 demonstrated a more efficacious triaging effect in the unvaccinated group. HPV33/58 will potentially replace HPV16/18 as the priority screening genotyping among vaccinated populations.

Collagen is crucial for tissue structure, functional maintenance, and cellular processes such as proliferation and differentiation. However, the specific changes in collagen expression and its associated genes in the lung tissues of yaks at high altitudes and their relationship with environmental adaptation remain poorly understood. Studying differences in the content of collagen fibers and gene expression between yaks at high (4,500 m) and low (2,600 m) altitudes, as well as between cattle at low altitudes (2,600 m). Using Masson staining, we found that the collagen fiber content in the lung tissues of yaks at low altitude was significantly higher compared to yaks at high altitude and cattle at the same altitude (P < 0.05). It was revealed through transcriptomic analyses that genes differentially expressed between high and low altitude yaks, as well as between low altitude yaks and cattle, were notably enriched in pathways related to cell adhesion, collagen synthesis, focal adhesion, and ECM-receptor interactions. Specifically, genes involved in mesenchymal collagen synthesis (e.g., COL1A1, COL1A2, COL3A1), basement membrane collagen synthesis (e.g., COL4A1, COL4A2, COL4A4, COL4A6), and peripheral collagen synthesis (e.g., COL5A1, COL6A1, COL6A2, COL6A3) were significantly upregulated in the lung tissues of yaks at low altitude compared to their high altitude counterparts and cattle (P < 0.05). In conclusion, yaks at lower altitudes exhibit increased collagen synthesis by upregulating collagen gene expression, which contributes to maintaining alveolar stability and septal flexibility. Conversely, the expression of collagen genes in yak lung tissues was down-regulated with the increase in altitude, and it was speculated that the decrease in collagen may be used to constrain the function of elastic fibers that are more abundant at high altitude, so as to enable them to adapt to the harsh environment with hypoxia and high altitude. This adaptation mechanism highlights the role of collagen in environmental acclimatization and contributes to our understanding of how altitude and species influence collagen-related physiological processes in yaks.

Abstract As an emerging cancer treatment strategy, reactive oxygen species-based tumor catalytic therapies face enormous challenges due to hypoxia and the overexpression of glutathione (GSH) in the tumor microenvironment. Herein, a self-assembled copper-based nanoplatform, TCCHA, was designed for enzyme-like catalysis-enhanced chemodynamic/photodynamic/antiangiogenic tritherapy against hepatocellular carcinoma. TCCHA was fabricated from Cu2+, 3,3′-dithiobis (propionohydrazide), and photosensitizer chlorine e6 via a facile one-pot self-assembly strategy, after which an aldehyde hyaluronic acid was coated, followed by loading of the antivascular drug AL3818. The obtained TCCHA nanoparticles exhibited pH/GSH dual-responsive drug release behaviors and multienzymatic activities, including Fenton, glutathione peroxidase-, and catalase-like activities. TCCHA, a redox homeostasis disruptor, promotes ⋅OH generation and GSH depletion, thus increasing the efficacy of chemodynamic therapy. TCCHA, which has catalase-like activity, can also reinforce the efficacy of photodynamic therapy by amplifying O2 production. In vivo, TCCHA efficiently inhibited tumor angiogenesis and suppressed tumor growth without apparent systemic toxicity. Overall, this study presents a facile strategy for the preparation of multienzyme-like nanoparticles, and TCCHA nanoparticles display great potential for enzyme catalysis-enhanced chemodynamic/photodynamic/antiangiogenic triple therapy against cancer. Graphical Abstract

Abstract Background Liver transplantation (LT) is offered as a cure for Hepatocellular carcinoma (HCC), however 15–20% develop recurrence post-transplant which tends to be aggressive. In this study, we examined the transcriptome profiles of patients with recurrent HCC to identify differentially expressed genes (DEGs), the involved pathways, biological functions, and potential gene signatures of recurrent HCC post-transplant using deep machine learning (ML) methodology. Materials and methods We analyzed the transcriptomic profiles of primary and recurrent tumor samples from 7 pairs of patients who underwent LT. Following differential gene expression analysis, we performed pathway enrichment, gene ontology (GO) analyses and protein-protein interactions (PPIs) with top 10 hub gene networks. We also predicted the landscape of infiltrating immune cells using Cibersortx. We next develop pathway and GO term-based deep learning models leveraging primary tissue gene expression data from The Cancer Genome Atlas (TCGA) to identify gene signatures in recurrent HCC. Results The PI3K/Akt signaling pathway and cytokine-mediated signaling pathway were particularly activated in HCC recurrence. The recurrent tumors exhibited upregulation of an immune-escape related gene, CD274, in the top 10 hub gene analysis. Significantly higher infiltration of monocytes and lower M1 macrophages were found in recurrent HCC tumors. Our deep learning approach identified a 20-gene signature in recurrent HCC. Amongst the 20 genes, through multiple analysis, IL6 was found to be significantly associated with HCC recurrence. Conclusion Our deep learning approach identified PI3K/Akt signaling as potentially regulating cytokine-mediated functions and the expression of immune escape genes, leading to alterations in the pattern of immune cell infiltration. In conclusion, IL6 was identified to play an important role in HCC recurrence.

Abstract Background Pneumoconiosis, a chronic disease stemming from prolonged inhalation of dust particles, stands as a significant global burden of occupational diseases. This study aims to investigate the survival outcomes of pneumoconiosis patients in Huangshi city, China, while also evaluating the disease burden on afflicted patients. Methods Data for this study were sourced from the Huangshi Center for Disease Control and Prevention. Survival analyses of pneumoconiosis patients were conducted employing life tables and the Kaplan-Meier method. The Cox proportional hazards models were deployed to identify factors influencing pneumoconiosis patients’ survival duration. Competing risks models were employed to confirm the validity of the model outcomes. Additionally, in the disease burden assessment, disability-adjusted life years (DALYs) were computed for various demographic groups and time frames. Results A total of 5,641 pneumoconiosis cases, diagnosed in Huangshi City, Hubei Province between 1958 and 2021, were incorporated into the cohort analysis. The probability of mortality and the risk ratio increased with advancing age. Notably, the median survival time of stage III pneumoconiosis patients was significantly shorter compared with those in stages I and II. The Cox proportional hazards model and competing risks analyses underscored several significant factors influencing survival time, including dust exposure duration (HR = 1.197, 95% CI: 1.104–1.298), age at first diagnosis (HR = 3.149, 95% CI: 2.961–3.349), presence of silicosis (HR = 1.378, 95% CI: 1.254–1.515), and stage II-III pneumoconiosis (HR = 1.456, 95% CI: 1.148–1.848). Cumulatively, DALYs amounted to 7,974.35 person-years, with an average of 1.41 person-years. The period between 2000 and 2019 witnessed the highest disease burden. Conclusion Our findings highlight the urgent need for improved prevention, earlier detection, and more effective management strategies for the occupational pneumoconiosis population. This study not only underscores the persistent issue of pneumoconiosis in industrial environments but also serves as a crucial call to action for policymakers and healthcare providers.

Abstract The rapid development of ultrawideband (UWB) communication systems has resulted in increasing performance requirements for the antenna system. In addition to a wide bandwidth, fast propagation rates and compact dimensions, flexibility, wearability or portability are also desirable for UWB antennas, as are excellent notch characteristics. Although progress has been made in the development of flexible/wearable antennas desired notch properties are still rather limited. Moreover, most presently available flexible UWB antennas are fabricated using environmentally not attractive subtractive etching-based processes. The usage of facile additive sustainably inkjet printing processes also utilizing low temperature plasma-activated conductive inks is rarely reported. In addition, the currently used tri-notched flexible UWB antenna designs have a relatively large footprint, which poses difficulties when integrated into miniaturized and compact communication devices. In this work, a silver nano ink is used to fabricate the antenna via inkjet printing and an efficient plasma sintering procedure. For the targeted UWB applications miniaturized tri-notched flexible antenna is realized on a flexible polyethylene terephthalate (PET) substrate with a compact size of 17.6 mm × 16 mm × 0.12 mm. The antenna operates in the UWB frequency band (2.9–10.61 GHz), and can shield interferences from WiMAX (3.3–3.6 GHz), WLAN (5.150–5.825 GHz) and X-uplink (7.9–8.4 GHz) bands, as well as exhibits a certain of bendability. Three nested "C" slots of different sizes were adopted to achieve notch features. The simulation and test results demonstrate that the proposed antenna can generate signal radiation in the desired UWB frequency band while retaining the desired notch properties and having acceptable SAR values on-body, making it a viable candidate for usage in flexible or wearable communication transmission devices. The research provides a facile and highly efficient method for fabricating flexible/wearable UWB antennas, that is, the effective combination of inkjet printing processing, flexible substrates, low temperature-activated conductive ink and antenna structure design.

Abstract Background Previous studies have largely neglected the role of sulfur metabolism in LUAD, and no study has combine iron, copper, and sulfur-metabolism associated genes together to create prognostic signatures. Methods This study encompasses 1564 LUAD patients, 1249 NSCLC patients, and over 10,000 patients with various cancer types from diverse cohorts. We employed the R package ConsensusClusterPlus to separate patients into different ICSM (Iron, Copper, and Sulfur-Metabolism) subtypes. Various machine-learning methods were utilized to develop the ICSMI. Enrichment analyses were conducted using ClusterProfiler and GSVA, while IOBR quantified immune cell infiltration. GISTIC2.0 and maftools were utilized for CNV and SNV data analysis. The Oncopredict package predicted drug information based on GDSC1. TIDE algorithm and cohorts GSE91061 and IMvigor210 evaluated patient response to immunotherapy. Single-cell data was processed using the Seurat package, AUCell package calculated cells geneset activity scores, and the Scissor algorithm identified ICSMI-associated cells. In vitro experiments was conducted to explore the role of ICSMRGs in LUAD. Results Unsupervised clustering identified two distinct ICSM subtypes of LUAD, each with unique clinical characteristics. The ICSMI, comprising 10 genes, was constructed using integrated machine-learning methods. Its prognostic power was validated in 10 independent datasets, revealing that LUAD patients with higher ICSMI levels had poorer prognoses. Furthermore, ICSMI demonstrated superior predictive abilities compared to 102 previously published signatures. A nomogram incorporating ICSMI and clinical features exhibited high predictive performance. ICSMI positively correlated with patients gene mutations, and integrated analysis of bulk and single-cell transcriptome data revealed its association with TME modulators. Cells representing the high-ICSMI phenotype exhibited more malignant features. LUAD patients with high ICSMI levels exhibited sensitivity to chemotherapy and targeted therapy but displayed resistance to immunotherapy. In a comprehensive analysis across various cancers, ICSMI retained significant prognostic value and emerged as a risk factor for the majority of cancer patients. Conclusions ICSMI provides critical prognostic insights for LUAD patients, offering valuable insights into the tumor microenvironment and predicting treatment responsiveness.

Abstract To explore the spontaneous combustion characteristics and hazards of the low-temperature oxidation (LTO) stage in the process of spontaneous combustion of coal and mudstone, the pore structure, spontaneous combustion characteristic parameters, and exothermic characteristics of coal and mudstone were tested and studied, and the oxidation kinetic parameters were calculated. The results show that mudstone has a larger specific surface area and pore volume than coal. From the fractal characteristics, the pore structure of mudstone is more complex than that of coal. According to the comparison of theoretical and actual gas generation and oxygen consumption rate curves, it is found that there is an interaction between coal and mudstone in the LTO process. With the increase of mudstone mass ratio, gas production, and its oxygen consumption rate increase. Among them, CM-4 (Coal:Mudstone = 1:1) has the highest exothermic intensity and the exothermic factor (A) and fire coefficient (K) increase with the increase of mudstone content. The apparent activation energy of the mudstone sample is lower than that of the raw coal, indicating that the sample after adding mudstone is more likely to have spontaneous combustion in the LTO stage.

Abstract We aimed to identify the druggable cell-intrinsic vulnerabilities and target-based drug therapies for PitNETs using the high-throughput drug screening (HTS) and genomic sequencing methods. We examined 9 patient-derived PitNET primary cells in HTS. Based on the screening results, the potential target genes were analyzed with genomic sequencing from a total of 180 PitNETs. We identified and verified one of the most potentially effective drugs, which targeted the Histone deacetylases (HDACs) both in in vitro and in vivo PitNET models. Further RNA sequencing revealed underlying molecular mechanisms following treatment with the representative HDACs inhibitor, Panobinostat. The HTS generated a total of 20,736 single-agent dose responses which were enriched among multiple inhibitors for various oncogenic targets, including HDACs, PI3K, mTOR, and proteasome. Among these drugs, HDAC inhibitors (HDACIs) were, on average, the most potent drug class. Further studies using in vitro, in vivo, and isolated PitNET primary cell models validated HDACIs, especially Panobinostat, as a promising therapeutic agent. Transcriptional surveys revealed substantial alterations to the Nrf2 signaling following Panobinostat treatment. Moreover, Nrf2 is highly expressed in PitNETs. The combination of Panobinostat and Nrf2 inhibitor ML385 had a synergistic effect on PitNET suppression. The current study revealed a class of effective anti-PitNET drugs, HDACIs, based on the HTS and genomic sequencing. One of the representative compounds, Panobinostat, may be a potential drug for PitNET treatment via Nrf2-mediated redox modulation. Combination of Panobinostat and ML385 further enhance the effectiveness for PitNET treatment.

Abstract In order to study the effect of temperature on the structure and mechanical properties of coal with different metamorphic degree. Three coal samples with varying degrees of metamorphism were chosen for analysis. The discrete element software PFC2D is used to simulate the heat treatment and compression of coal. The findings indicate that during the heating process, low-order coal exhibits noticeable thermal cracks at an early stage, while thermal crack development in middle-order coal is concentrated in the later stages. In contrast, high-order coal demonstrates a more stable macroscopic structure. The strength and stiffness of low rank coal show the lowest value and decrease significantly within 135 °C. However, the strength and stiffness of medium rank coal decrease significantly after 135 °C. The changes of mechanical properties and damage modes of coal caused by thermal damage are often ignored, which may lead to the deviation of design and research results from the actual situation. Therefore, this study is of great significance to the prevention and control of coal mine disasters.

In this study, soft gel stripping experiments were conducted under different temperatures and flow velocity conditions by a flow loop. The flow area of pipes increased with an increase in flow velocity. However, partial or complete removal of soft gels occurred when flow velocity increased to a critical point. The hydrodynamic force from oil flow, adhesive contact force and yield stress of soft gels were calculated and compared. The hydrodynamic force increased with an increase in flow velocity. Under the dissolution and shear effect, the flow area showed a step-wise increase when hydrodynamic force did not meet the requirements of adhesion failure and structural failure. The soft gels were stripped completely when the force met the requirements. The lower strength of soft gels resulted in lower requirements of adhesion failure and structural failure. Thus, accumulation problems of soft gels can be solved by changing flow parameters.

Introduction Tuberculosis (TB) is a major global health issue, particularly, in India and South Africa. We aim to evaluate the potential of the new TB vaccine, Vaccae, to enhance TB control by integrating with active case finding (ACF) strategies in these regions.Methods Using age-structured dynamic models, we projected the epidemiological and economic outcomes of combining Vaccae vaccination with ACF over 27 years. In India, four age-targeted strategies were analysed: (1) adolescent (15 years), (2) adolescent and young adult (AYA, 15–34 years), (3) adult (18–55 years) and (4) elderly (60+ years). In South Africa, strategies were based on HIV status: (1) HIV-targeted, (2) non-HIV and (3) general population. The vaccine efficacy of Vaccae was set at 54.7%, priced at US$120 per course. Outcomes measured included reductions in TB incidence and mortality, prioritised based on budget, incremental cost-effectiveness ratios (ICER) and benefit-cost ratios (BCR).Results In India, the adult strategy could prevent 8.70 (95% UI: 6.86–11.13) million TB cases and 0.61 (0.39–0.91) million deaths, reducing incidence and mortality by 20.1% (18.7%–23.5%) and 19.0% (17.5%–22.5%), respectively. In South Africa, the general population strategy could avert 0.67 (0.45–0.99) million TB cases and 0.21 (0.15–0.28) million deaths, reducing incidence by 28.1% (26.1%–30.3%) and mortality by 27.0% (23.5%–30.0%). The vaccination budgets for the AYA strategy in India and the HIV-targeted strategy in South Africa were US$14.0 (10.14–23.29) billion and US$0.09 (0.06–0.15) billion, respectively. The ICERs were US$1082 (927–1426) and US$70 (53–123) per disability-adjusted life year averted, and the BCRs were 2.0 (1.6–2.4) and 176 (83.4–255.3), respectively. Thus, the AYA strategy in India and the HIV-targeted strategy in South Africa were the most favourable.Conclusion Integrating Vaccae vaccination with ACF could significantly enhance TB control in high-burden countries. Policymakers should consider these strategies, with further research needed to confirm the findings.

The combustion characteristics of spark assistant compression ignition mode under different loads and fuels were explored, as well as by constructing artificial neural networks(ANN) model, the prediction ability of different algorithms for engine performance was discussed. Burning methanol and n-butanol can help to improve IMEP and induce earlier spontaneous combustion. The knock intensity(KI) of engine fueled with methanol was highest followed by n-butanol and gasoline, but maximum amplitude of filtered pressure oscillation(MAPO) shows the opposite trend. KI showed great positive liner correlation with ignition timing. Methanol showed the most outstanding tolerance on the compression ignition state. Fueled with methanol can decreased equivalent brake specific fuel consumption(ESFC) up to 52.9 % compared with the initial SI gasoline engine. N-butanol can improve BSNOx, BSTHC and BSCO concurrently, however fueled with methanol will worsen BSNOx. ANN model for engine combustion, economy and emissions performance was built. The prediction accuracy of Bayesian regularization algorithm for engine performance predicting was highest, but it have no advantage in the calculating times when the amount of data was large while the Levenberg-Marquardt algorithm would be the ideal efficient. The mean square error of ESFC and emissions parameters under scaled conjugate gradients algorithm always poorest.

Pain and depression comorbidity (PD) among older adults in China is common and significantly affects their physical and mental health. The psychosocial factors may affect people's feelings, understanding and expression of pain and depression, leading to inaccurate assessment of this condition. Educational attainment is thought to be associated with either pain or depression. However, we do not yet know the relationship between educational attainment and PD. Using data from the 2018 China Health and Retirement Longitudinal Study in 2018, we analyzed various variables in 7742 individuals aged 60 years and older. Our results indicate significant differences between the PD and non-PD populations in terms of social, lifestyle, and behavioral factors. We observed a significant decrease in the incidence of PD among older adults with higher levels of education (p

BackgroundObservational studies have indicated a potential association between autoimmune diseases and the occurrence of Osteoarthritis (OA), with an increased risk of mortality among affected patients. However, whether a causal relationship exists between the two remains unknown.MethodsIn the Mendelian randomization (MR) study, we accessed exposure Genome-wide association study (GWAS) data from both the MRC Integrative Epidemiology Unit (MRC-IEU) and the FinnGen consortium. GWAS data for OA were obtained from MRC-IEU. We employed univariable, multivariable, and reverse MR analyses to explore potential associations between autoimmune disorders and OA. Additionally, a two-step mediation MR analysis was performed to investigate indirect factors possibly influencing the relationship between autoimmune disorders and OA. Afterward, we conducted an observational analysis to further explore the relationship between autoimmune disease and occurrence as well as of OA using a real-world database (the MIMIC-IV database). Based on public gene expression sequencing data, we further explored the potential shared pathogenesis between autoimmune diseases and OA.ResultsIn our univariable MR study, we identified five autoimmune diseases that are associated with OA. These include Celiac disease (OR = 1.061, 95% CI = 1.018–1.105, p = 0.005), Crohn’s disease (OR = 1.235, 95% CI = 1.149–1.327, p = 9.44E-09), Ankylosing spondylitis (OR = 2.63, 95% CI = 1.21–5.717, p = 0.015), RA (OR = 1.082, 95% CI = 1.034–1.133, p = 0.001), and Ulcerative colitis (OR = 1.175, 95% CI = 1.068–1.294, p = 0.001). In the mediation effect analysis, it was found that there is no correlation between cytokines and autoimmune diseases and OA. Based on transcriptome data analysis, it was found that metabolism-related pathways play a key role in the co-morbidity of autoimmune diseases and OA.ConclusionOur findings revealed that genes associated with Celiac disease, Crohn’s disease, Ankylosing spondylitis, RA, and Ulcerative colitis were independently linked to the development of OA. Furthermore, we conducted an analysis of potential pathogenic genes between these diseases and OA, offering a novel approach for the simultaneous treatment of multiple conditions.