Transcriptome and single-cell analysis reveal disulfidptosis-related modification patterns of tumor microenvironment and prognosis in osteosarcoma.

Osteosarcoma (OS) is the most common malignant bone tumor with high pathological heterogeneity. Our study aimed to investigate disulfidptosis-related modification patterns in OS and their relationship with survival outcomes in patients with OS. We analyzed the single-cell-level expression profiles of disulfidptosis-related genes (DSRGs) in both OS microenvironment and OS subclusters, and HMGB1 was found to be crucial for intercellular regulation of OS disulfidptosis. Next, we explored the molecular clusters of OS based on DSRGs and related immune cell infiltration using transcriptome data. Subsequently, the hub genes of disulfidptosis in OS were screened by applying multiple machine models. In vitro and patient experiments validated our results. Three main disulfidptosis-related molecular clusters were defined in OS, and immune infiltration analysis suggested high immune heterogeneity between distinct clusters. The in vitro experiment confirmed decreased cell viability of OS after ACTB silencing and higher expression of ACTB in patients with lower immune scores. Our study systematically revealed the underlying relationship between disulfidptosis and OS at the single-cell level, identified disulfidptosis-related subtypes, and revealed the potential role of ACTB expression in OS disulfidptosis.

L-cysteine contributes to destructive activities of odontogenic cysts/tumor.

BACKGROUND: Odontogenic cysts/tumor can cause severe bone destruction, which affects maxillofacial function and aesthetics. Meanwhile, metabolic reprogramming is an important hallmark of diseases. Changes in metabolic flow affect all aspects of disease, especially bone-related diseases. At present, the researches on pathogenesis of odontogenic cysts/tumor are mainly focused on the level of gene regulation, but the effects of metabolic alterations on odontogenic cysts/tumor have still underexplored. MATERIALS AND METHODS: Imaging analysis was used to evaluate the lesion size of different odontogenic lesions. Tartrate resistant acid phosphatase (TRAP) and immunohistochemistry (IHC) assays were utilized to detect the differences in bone destruction activity in odontogenic cysts and tumors. Furthermore, metabolomics and weighted gene co-expression network analysis (WGCNA) were conducted for the metabolomic features and key metabolite screening, respectively. The effect of ferroptosis inhibition on bone destruction was confirmed by IHC, immunofluorescence, and malondialdehyde colorimetric assay. RESULTS: The bone destruction activity of ameloblastoma (AM) was the strongest and the weakest in odontogenic cysts (OC). High-throughput targeted metabolomics was used to map the metabolomic profiles of OC, odontogenic keratocyst (OKC) and AM. WGCNA and differential analysis identified L-cysteine in OKC and AM. Cystathionine γ-lyase (CTH) was further screened by Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The functions of L-cysteine were further validated. Finally, we confirmed that CTH affected destructive activities by regulating the sensitivity of epithelial cells to ferroptosis. CONCLUSION: High-throughput targeted metabolomics performed on diseased tissue confirmed the unique alteration of metabolic profiles in OKC and AM. CTH and its metabolite L-cysteine are the key factors regulating destructive activities.

Prognostic value of dynamic changes of pre- and post-operative tumor markers in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) prognosis assessment is vital for personalized treatment plans. This study investigates the prognostic value of dynamic changes of tumor markers CEA, CA19-9, CA125, and AFP before and after surgery and constructs prediction models based on these indicators. METHODS: A retrospective clinical study of 2599 CRC patients who underwent radical surgery was conducted. Patients were randomly divided into training (70%) and validation (30%) datasets. Univariate and multivariate Cox regression analyses identified independent prognostic factors, and nomograms were constructed. RESULTS: A total of 2599 CRC patients were included in the study. Patients were divided into training (70%, n = 1819) and validation (30%, n = 780) sets. Univariate and multivariate Cox regression analyses identified age, total number of resected lymph nodes, T stage, N stage, the preoperative and postoperative changes in the levels of CEA, CA19-9, and CA125 as independent prognostic factors. When their postoperative levels are normal, patients with elevated preoperative levels have significantly worse overall survival. However, when the postoperative levels of CEA/CA19-9/CA125 are elevated, whether their preoperative levels are elevated or not has no significance for prognosis. Two nomogram models were developed, and Model I, which included CEA, CA19-9, and CA125 groups, demonstrated the best performance in both training and validation sets. CONCLUSION: This study highlights the significant predictive value of dynamic changes in tumor markers CEA, CA19-9, and CA125 before and after CRC surgery. Incorporating these markers into a nomogram prediction model improves prognostic accuracy, enabling clinicians to better assess patients' conditions and develop personalized treatment plans.

Osteogenesis or Apoptosis-Twofold Effects of Zn2+ on Bone Marrow Mesenchymal Stem Cells: An In Vitro and In Vivo Study.

Zinc (Zn) is a bioabsorbable metal that shows great potential as an implant material for orthopedic applications. Suitable concentrations of zinc ions promote osteogenesis, while excess zinc ions cause apoptosis. As a result, the conflicting impacts of Zn2+ concentration on osteogenesis could prove to be significant problems for the creation of novel materials. This study thoroughly examined the cell viability, proliferation, and osteogenic differentiation of rat bone marrow mesenchymal stem cells (rBMSCs) cultured in various concentrations of Zn2+ in vitro and validated the osteogenesis effects of zinc implantation in vivo. The effective promotion of cell survival, proliferation, migration, and osteogenic differentiation of bone marrow mesenchymal stem cell (BMSCs) may be achieved at a low concentration of Zn2+ (125 µM). The excessively high concentration of zinc ions (>250 µM) not only reduces BMSCs' viability and proliferation but also causes them to suffer apoptosis due to the disturbed zinc homeostasis and excessive Zn2+. Moreover, transcriptome sequencing was used to examine the underlying mechanisms of zinc-induced osteogenic differentiation with particular attention paid to the PI3K-AKT and TGF-ß pathways. The present investigation elucidated the dual impacts of Zn2+ microenvironments on the osteogenic characteristics of rBMSCs and the associated processes and might offer significant insights for refining the blueprint for zinc-based biomaterials.

Metabolic Landscape of Osteosarcoma: Reprogramming of Lactic Acid Metabolism and Metabolic Communication.

BACKGROUND: Lactic acid, previously regarded only as an endpoint of glycolysis, has emerged as a major regulator of tumor invasion, growth, and the tumor microenvironment. In this study, we aimed to explore the reprogramming of lactic acid metabolism relevant to osteosarcoma (OS) microenvironment by decoding the underlying lactic acid metabolic landscape of OS cells and intercellular signaling alterations. METHODS: The landscape of OS metabolism was evaluated using single-cell gene expression data, lactic acid metabolism clustering, and screening of the hub genes in lactic acid metabolism of OS samples using transcriptome data. The role of the hub gene NADH:Ubiquinone Oxidoreductase Complex Assembly Factor 6 (NDUFAF6) was validated with in vitro studies and patient experiments. RESULTS: Single-cell RNA sequencing data validated a lactic acid metabolismhigh subcluster in OS. Further investigation of intercellular communications revealed a unique metabolic communication pattern between the lactic acid metabolismhigh subcluster and other subclusters. Next, two lactic acid metabolic reprogramming phenotypes were defined, and six lactic acid metabolism-related genes (LRGs), including the biomarker NDUFAF6, were screened in OS. In vitro studies and patient experiments confirmed that NDUFAF6 is a crucial lactic acid metabolism-associated gene in OS. CONCLUSIONS: The patterns of lactic acid metabolism in OS suggested metabolic reprogramming phenotypes relevant to the tumor microenvironment (TME) and identified NDUFAF6 as an LRG prognostic biomarker.

Prognostic value of normal levels of preoperative tumor markers in colorectal cancer.

Carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 125 (CA125), and alpha-fetoprotein (AFP) are widely used tumor markers for colorectal cancer (CRC), but their clinical significance is unknown when the levels of these tumor markers were within the normal range. This retrospective study included 2145 CRC patients. The entire cohort was randomly divided into training and validation datasets. The optimal cut-off values of tumor markers were calculated using X-tile software, and univariate and multivariate analyses were performed to assess its association with overall survival (OS). The nomogram model was constructed and validated. The entire cohort was randomly divided into a training dataset (1502 cases, 70%) and a validation dataset (643 cases,30%). Calculated from the training dataset, the optimal cut-off value was 2.9 ng/mL for CEA, 10.1 ng/mL for CA19-9, 13.4 U/mL for CA125, and 1.8 ng/mL for AFP, respectively. Multivariate analysis revealed that age, tumor location, T stage, N stage, preoperative CA19-9, and CA125 levels were independent prognostic predictors. Even within the normal range, CRC patients with relatively high levels of CA19-9 or CA125 worse OS compared to those with relatively low levels. Then, based on the independent prognostic predictors from multivariate analysis, two models with/without (model I/II) CA19-9 and CA125 were built, model I showed better prediction and reliability than model II. Within the normal range, relatively high levels of preoperative CA19-9 and CA125 were significantly associated with poor OS in CRC patients. The nomogram based on CA19-9 and CA125 levels showed improved predictive accuracy ability for CRC.

Single-cell analysis unveils activation of mast cells in colorectal cancer microenvironment.

The role of mast cells (MCs) in colorectal cancer (CRC) remains unclear, and a comprehensive single-cell study on CRC MCs has not been conducted. This study used a multi-omics approach, integrating single-cell sequencing, spatial transcriptomics, and bulk tissue sequencing data to investigate the heterogeneity and impact of MCs in CRC. Five MC signature genes (TPSAB1, TPSB2, CPA3, HPGDS, and MS4A2) were identified, and their average expression was used as a marker of MCs. The MC density was found to be lower in CRC compared to normal tissue, but MCs in CRC demonstrated distinct activation features. Activated MCs were defined by high expression of receptors and MC mediators, while resting MCs had low expression. Most genes, including the five MC signature genes, were expressed at higher levels in activated MCs. The MC signature was linked to a better prognosis in both CRC and pan-cancer patient cohorts. Elevated KITLG expression was observed in fibroblasts and endothelial cells in CRC samples compared to normal tissue, and co-localization of MCs with these cell types was revealed by spatial transcriptome analysis. In conclusion, this study finds decreased MC density in CRC compared to normal tissue, but highlights a shift in MC phenotype from CMA1high resting cells to activated TPSAB1high, CPA3high, and KIThigh cells. The elevated KITLG expression in the tumor microenvironment's fibroblasts and endothelial cells may activate MCs through the KITLG-KIT axis, potentially suppressing tumor progression.

Deep learning-based identification of spine growth potential on EOS radiographs.

OBJECTIVES: To develop an automatic computer-based method that can help clinicians in assessing spine growth potential based on EOS radiographs. METHODS: We developed a deep learning-based (DL) algorithm that can mimic the human judgment process to automatically determine spine growth potential and the Risser sign based on full-length spine EOS radiographs. A total of 3383 EOS cases were collected and used for the training and test of the algorithm. Subsequently, the completed DL algorithm underwent clinical validation on an additional 440 cases and was compared to the evaluations of four clinicians. RESULTS: Regarding the Risser sign, the weighted kappa value of our DL algorithm was 0.933, while that of the four clinicians ranged from 0.909 to 0.930. In the assessment of spine growth potential, the kappa value of our DL algorithm was 0.944, while the kappa values of the four clinicians were 0.916, 0.934, 0.911, and 0.920, respectively. Furthermore, our DL algorithm obtained a slightly higher accuracy (0.973) and Youden index (0.952) compared to the best values achieved by the four clinicians. In addition, the speed of our DL algorithm was 15.2 ± 0.3 s/40 cases, much faster than the inference speeds of the clinicians, ranging from 177.2 ± 28.0 s/40 cases to 241.2 ± 64.1 s/40 cases. CONCLUSIONS: Our algorithm demonstrated comparable or even better performance compared to clinicians in assessing spine growth potential. This stable, efficient, and convenient algorithm seems to be a promising approach to assist doctors in clinical practice and deserves further study. CLINICAL RELEVANCE STATEMENT: This method has the ability to quickly ascertain the spine growth potential based on EOS radiographs, and it holds promise to provide assistance to busy doctors in certain clinical scenarios. KEY POINTS: • In the clinic, there is no available computer-based method that can automatically assess spine growth potential. • We developed a deep learning-based method that could automatically ascertain spine growth potential. • Compared with the results of the clinicians, our algorithm got comparable results.

A pH-neutral bioactive glass empowered gelatin-chitosan-sodium phytate composite scaffold for skull defect repair.

The ideal skull defect repairing material should have good biocompatibility and mechanical properties, and contribute to osteogenesis. In this study, we designed and fabricated biodegradable, bioactive and mechanically robust porous scaffolds composed completely of biological materials. We used a gelatin-chitosan blend as the matrix, sodium phytate instead of toxic glutaraldehyde for cross-linking, and the pH-neutral bioactive glass (PSC) to improve biological activity and mechanical properties. The chitosan-gelatin-30%PSC/sodium phytate composite scaffold avoided the problems of high toxicity in conventional cross-linking agents with glutaraldehyde, the poor mechanical support of the pure chitosan or gelatin scaffold, and the mismatch of the degradation rate with bone repair, becoming a promising new candidate for skull defect repair.

Development of A Minimum Dataset for the Monitoring of Recombinant Human Growth Hormone (rhGH) Therapy Use in Children with Growth Hormone Deficiency (GHD) - A GloBE-Reg Initiative.

Introduction Although there are some recommendations in the literature on the assessments that should be performed in children on recombinant human growth hormone (rhGH) therapy, the level of consensus on these measurements is not clear. The objective of the current study was to identify the minimum dataset (MDS) that could be measured in a routine clinical setting across the world, aiming to minimise burden on clinicians and improve quality of data collection. Methods This study was undertaken by the GH Scientific Study Group (SSG) in GloBE-Reg, a new project that has developed a common registry platform that can support long-term safety and effectiveness studies of drugs. Twelve clinical experts from 7 international endocrine organisations identified by the GloBE-Reg Steering Committee, 2 patient representatives and representatives from 2 pharmaceutical companies with previous GH registry expertise collaborated to develop this recommendation. A comprehensive list of data fields routinely collected by each of the clinical and industry experts for children with GHD was compiled. Each member was asked to determine the: (1) Importance of the data field and (2) Ease of data collection. Data fields that achieved 70% consensus in terms of importance qualified for the MDS, provided <50% deemed the item difficult to collect. Results A total of 246 items were compiled and 27 removed due to redundancies, with 219 items subjected to the grading system. Of the 219 items, 111 achieved at least 70% consensus as important data to collect when monitoring children with GH deficiency (GHD) on rhGH treatment. Sixty-nine of the 219 items were deemed easy to collect. Combining the criteria of importance and ease of data collection, 63 met the criteria for the MDS. Several anomalies to the MDS rule were identified and highlighted for discussion, including whether the patients were involved in current or previous clinical trials, need for HbA1c monitoring, other past medical history, and adherence, enabling formulation of the final MDS recommendation of 43 items; 20 to be completed once, 14 every 6 months and 9 every 12 months. Conclusion In summary, this exercise performed through the GloBE-Reg initiative provides a recommendation of the minimum dataset requirement, collected through real-world data, for the monitoring of safety and effectiveness of rhGH in children with GHD, both for the current daily preparations and the newer long-acting growth hormone.

Dynamic landscapes and the influence of human activities in the Yellow River Delta wetland region.

The Yellow River Delta (YRD) wetland is one of the largest and youngest wetland ecosystems in the world. It plays an important role in regulating climate and maintaining ecological balance in the region. This study analyzes the spatiotemporal changes in land use, wetland migration, and landscape pattern from 2013 to 2022 using Landsat-8 and Sentinel-1 data in YRD. Then wetland landscape changes and the impact of human activities are determined by analyzing correlation between landscape and socio-economic indicators including nighttime light centroid, total light intensity, cultivated land area and centroid, building area and centroid, economic and population. The results show that the total wetland area increased 1426 km2 during this decade. However, the wetland landscape pattern tended to be fragmented from 2013 to 2022, with wetlands of different types interlacing and connectivity decreasing, and distribution becoming more concentrated. Different types of human activities had influences on different aspects of wetland landscape, with the expansion of cultivated land mainly compressing the core area of wetlands from the edge, the expansion of buildings mainly disrupting wetland connectivity, and socio-economic indicators such as total light intensity and the centroid mainly causing wetland fragmentation. The results show the changes of the YRD wetland and provide an explanation of how human activities effect the change of its landscape, which provides available data to achieve sustainable development goals 6.6 and may give an access to measure the change of wetland using human-activity data, which could help to adject behaviors to protect wetlands.

A nomogram was developed using clinicopathological features to predict postoperative liver metastasis in patients with colorectal cancer.

PURPOSE: The objective of this study is to examine the risk factors that contribute to the development of liver metastasis (LM) in patients who have suffered radical resection for colorectal cancer (CRC), and to establish a nomogram model that can be used to predict the occurrence of the LM. METHODS: The present study enrolled 1377 patients diagnosed with CRC between January 2010 and July 2021. The datasets were allocated to training (n = 965) and validation (n = 412) sets in a randomly stratified manner. The study utilized univariate and multivariate logistic regression analyses to establish a nomogram for predicting LM in patients with CRC. RESULTS: Multivariate analysis revealed that T stage, N stage, number of harvested lymph nodes (LNH), mismatch repair (MMR) status, neutrophil count, monocyte count, postoperative carcinoembryonic antigen (CEA) levels, postoperative cancer antigen 125 (CA125) levels, and postoperative carbohydrate antigen 19-9 (CA19-9) levels were independent predictive factors for LM after radical resection. These factors were then utilized to construct a comprehensive nomogram for predicting LM. The nomogram demonstrated great discrimination, with an area under the curve (AUC) of 0.782 for the training set and 0.768 for the validation set. Additionally, the nomogram exhibited excellent calibration and significant clinical benefit as confirmed by the calibration curves and the decision curve analysis, respectively. CONCLUSION: This nomogram has the potential to support clinicians in identifying high-risk patients who may develop LM post-surgery. Clinicians can devise personalized treatment and follow-up plans, ultimately leading to an improved prognosis for patients.

Carbon Monitor Europe near-real-time daily CO2 emissions for 27 EU countries and the United Kingdom.

With the urgent need to implement the EU countries pledges and to monitor the effectiveness of Green Deal plan, Monitoring Reporting and Verification tools are needed to track how emissions are changing for all the sectors. Current official inventories only provide annual estimates of national CO2 emissions with a lag of 1+ year which do not capture the variations of emissions due to recent shocks including COVID lockdowns and economic rebounds, war in Ukraine. Here we present a near-real-time country-level dataset of daily fossil fuel and cement emissions from January 2019 through December 2021 for 27 EU countries and UK, which called Carbon Monitor Europe. The data are calculated separately for six sectors: power, industry, ground transportation, domestic aviation, international aviation and residential. Daily CO2 emissions are estimated from a large set of activity data compiled from different sources. The goal of this dataset is to improve the timeliness and temporal resolution of emissions for European countries, to inform the public and decision makers about current emissions changes in Europe.

Therapeutic potential of melatonin in the intervertebral disc degeneration through inhibiting the ferroptosis of nucleus pulpous cells.

Ferroptosis, a novel type of cell death mediated by the iron-dependent lipid peroxidation, contributes to the pathogenesis of the intervertebral disc degeneration (IDD). Increasing evidence demonstrated that melatonin (MLT) displayed the therapeutic potential to prevent the development of IDD. Current mechanistic study aims to explore whether the downregulation of ferroptosis contributes to the therapeutic capability of MLT in IDD. Current studies demonstrated that conditioned medium (CM) from the lipopolysaccharide (LPS)-stimulated macrophages caused a series of changes about IDD, including increased intracellular oxidative stress (increased reactive oxygen species and malondialdehyde levels, but decreased glutathione levels), upregulated expression of inflammation-associated factors (IL-1ß, COX-2 and iNOS), increased expression of key matrix catabolic molecules (MMP-13, ADAMTS4 and ADAMTS5), reduced the expression of major matrix anabolic molecules (COL2A1 and ACAN), and increased ferroptosis (downregulated GPX4 and SLC7A11 levels, but upregulated ACSL4 and LPCAT3 levels) in nucleus pulposus (NP) cells. MLT could alleviate CM-induced NP cell injury in a dose-dependent manner. Moreover, the data substantiated that intercellular iron overload was involved in CM-induced ferroptosis in NP cells, and MLT treatment alleviated intercellular iron overload and protected NP cells against ferroptosis, and those protective effects of MLT in NP cells further attenuated with erastin and enhanced with ferrostatin-1(Fer-1). This study demonstrated that CM from the LPS-stimulated RAW264.7 macrophages promoted the NP cell injury. MLT alleviated the CM-induced NP cell injury partly through inhibiting ferroptosis. The findings support the role of ferroptosis in the pathogenesis of IDD, and suggest that MLT may serve as a potential therapeutic approach for clinical treatment of IDD.

Identification of a novel cuproptosis-related gene signature for rheumatoid arthritis-A prospective study.

BACKGROUND: Rheumatoid arthritis (RA) is a multifactorial systemic autoimmune disease characterized by ongoing synovial inflammation, leading to the degradation of cartilage. Cuproptosis, as a newly characterized form of cell death, may influence RA progression by regulating immune cells and chondrocytes. This study sets out to identify the hub cuproptosis-related gene (CRG) associated with the pathogenesis of RA. METHODS: A series of bioinformatic analyses were performed to evaluate the expression score of CRGs and the immune infiltration landscape between RA and normal samples. The hub gene was screened through the correlation analysis of CRGs, and the interaction network between the hub gene and transcription factors (TFs) was constructed. Finally, the hub gene was validated through quantitative real-time polymerase chain reaction (qRT-PCR) of patient samples and cell experiments. RESULTS: Drolipoamide S-acetyltransferase (DLAT) was screened as the hub gene. Correlation analysis between the hub gene and immune microenvironment demonstrated that DLAT had the highest correlation with T follicular helper cells. Eight pairs of DLAT-TF interaction networks were constructed. Single-cell sequencing showed that CRGs were highly expressed in RA chondrocytes, and chondrocytes could be classified into three different subsets. qRT-PCR was used to validate the above results. Dlat knockdown in immortalized human chondrocytes led to significantly improved mitochondrial membrane potentials and reduced levels of intracellular reactive oxygen species (ROS), mitochondrial ROS and apoptosis. CONCLUSIONS: This study rudimentarily demonstrates the correlation between CRGs and immune cell infiltration in RA. The biomarker DLAT may provide comprehensive insights into the pathogenesis and drug targets of RA.

Medical Prospect of Melatonin in the Intervertebral Disc Degeneration through Inhibiting M1-Type Macrophage Polarization via SIRT1/Notch Signaling Pathway.

The study aims to explore the medical prospect of melatonin (MLT) and the underlying therapeutic mechanism of MLT-mediated macrophage (Mφ) polarization on the function of nucleus pulposus (NP) in intervertebral disc degeneration (IDD). RAW 264.7 Mφs were induced by lipopolysaccharide (LPS) to simulate Mφ polarization and the inflammatory reaction of Mφs with or without MLT were detected. Conditioned medium (CM) collected from these activated Mφs with or without MLT treatment were further used to incubate NP cells. The oxidative stress, inflammation and extracellular matrix (ECM) metabolism in NP cells were determined. Then, the changes in SIRT1/Notch signaling were detected. The agonist (SRT1720) and inhibitor (EX527) of SIRT1 were used to further explore the association among MLT. The interaction between SIRT1 and NICD was detected by immunoprecipitation (IP). Finally, puncture-induced rat IDD models were established and IDD degrees were clarified by X-ray, MRI, H&E staining and immunofluorescence (IF). The results of flow cytometry and inflammation detection indicated that LPS could induce M1-type Mφ polarization with pro-inflammatory properties. MLT significantly inhibited the aforementioned process and inhibited M1-type Mφ polarization, accompanied by the alleviation of inflammation. Compared with those without MLT, the levels of oxidative stress, pro-inflammatory cytokines and ECM catabolism in NP cells exposed to CM with MLT were markedly downregulated in a dose-dependent manner. The inhibition of SIRT1 and the enhancement of Notch were observed in activated Mφs and they can be reversed after MLT treatment. This prediction was further confirmed by using the SRT1720 and EX527 to activate or inhibit the signaling. The interaction between SIRT1 and NICD was verified by IP. In vivo study, the results of MRI, Pfirrmann grade scores and H&E staining demonstrated the degree of disc degeneration was significantly lower in the MLT-treated groups when compared with the IDD control group. The IF data showed M1-type Mφ polarization decreased after MLT treatment. MLT could inhibit M1-type Mφ polarization and ameliorate the NP cell injury caused by inflammation in vitro and vivo, which is of great significance for the remission of IDD. The SIRT1/Notch signaling pathway is a promising target for MLT to mediate Mφ polarization.

Near-real-time global gridded daily CO2 emissions 2021.

We present a near-real-time global gridded daily CO2 emissions dataset (GRACED) throughout 2021. GRACED provides gridded CO2 emissions at a 0.1° × 0.1° spatial resolution and 1-day temporal resolution from cement production and fossil fuel combustion over seven sectors, including industry, power, residential consumption, ground transportation, international aviation, domestic aviation, and international shipping. GRACED is prepared from the near-real-time daily national CO2 emissions estimates (Carbon Monitor), multi-source spatial activity data emissions and satellite NO2 data for time variations of those spatial activity data. GRACED provides the most timely overview of emissions distribution changes, which enables more accurate and timely identification of when and where fossil CO2 emissions have rebounded and decreased. Uncertainty analysis of GRACED gives a grid-level two-sigma uncertainty of value of ±19.9% in 2021, indicating the reliability of GRACED was not sacrificed for the sake of higher spatiotemporal resolution that GRACED provides. Continuing to update GRACED in a timely manner could help policymakers monitor energy and climate policies' effectiveness and make adjustments quickly.

Selective photoelectrochemical oxidation of glucose to glucaric acid by single atom Pt decorated defective TiO2.

Photoelectrochemical reaction is emerging as a powerful approach for biomass conversion. However, it has been rarely explored for glucose conversion into value-added chemicals. Here we develop a photoelectrochemical approach for selective oxidation of glucose to high value-added glucaric acid by using single-atom Pt anchored on defective TiO2 nanorod arrays as photoanode. The defective structure induced by the oxygen vacancies can modulate the charge carrier dynamics and band structure, simultaneously. With optimized oxygen vacancies, the defective TiO2 photoanode shows greatly improved charge separation and significantly enhanced selectivity and yield of C6 products. By decorating single-atom Pt on the defective TiO2 photoanode, selective oxidation of glucose to glucaric acid can be achieved. In this work, defective TiO2 with single-atom Pt achieves a photocurrent density of 1.91 mA cm-2 for glucose oxidation at 0.6 V versus reversible hydrogen electrode, leading to an 84.3 % yield of glucaric acid under simulated sunlight irradiation.

Oblique Lateral Endoscopic Decompression and Interbody Fusion for Severe Lumbar Spinal Stenosis: Technical Note and Preliminary Results.

OBJECTIVE: Adequacy of decompression for oblique lateral interbody fusion (OLIF) is a real concern in patients with severe lumbar spinal stenosis (LSS). With this in mind, we combined OLIF with spinal endoscopic technique to achieve a solid fusion and an adequate decompression after one operation. METHODS: This is a technical note. The theoretical basis and operation process of this technique were introduced, and consecutive cases were retrospectively collected. Consecutive patients diagnosed with monosegmental severe LSS (L4/5) and underwent oblique lateral endoscopic decompression and interbody fusion (OLEDIF) from January 2018 to February 2020 were retrospectively collected. Clinical outcomes were assessed by claudication distance, Visual Analog Scale (VAS), and Oswestry Disability Index (ODI) scores. Secondary indicators included operation time, operative blood loss, and postoperative complications. RESULTS: Ten patients were selected for the OLEDIF procedure. They were five women and five men ranging in age from 49 to 75 years (mean age of 63.9 years) and in BMI from 25.4 to 30.2 kg/m2 (mean BMI of 27.5 kg/m2 ). The preoperative claudication distance was 160.00 ± 68.96 m (range 70-250 m), which was significantly extended on the 3-month and 1-year follow-up (1020.00 ± 407.70 m and 1040.00 ± 416.87 m, respectively). The preoperative VAS score of back pain and radiating leg pain was 5.50 ± 0.97 (range 4-7) and 6.40 ± 0.97 (range 5-8). The score on postoperative month 3 was 1.60 ± 0.52 (range 1-2) and 1.20 ± 0.79 (range 0-2), and the 1-year follow-up score was 1.90 ± 0.74 (range 1-3) and 1.60 ± 0.70 (range 1-3), respectively. The preoperative ODI was 72.23 ± 6.30 (range 64.4-82.2), the 3-month follow-up ODI was 31.12 ± 4.20 (range 24.4-35.6), and the 1-year follow-up ODI was 29.33 ± 5.92 (range 20.0-37.8). Compared with the transforaminal lumbar interbody fusion (TLIF) in the literature, the operation time was not prolonged (189.3 ± 32.5 min vs. 214.9 ± 60.0 min) but the amount of blood loss decreased significantly (113.3 ± 26.7 ml vs. 366.8 ± 298.2 ml). No complications were found except one case presented with dysesthesia of the left leg. Imaging results showed good fusion without cage subsidence during 1-year follow-up. CONCLUSION: OLEDIF can achieve complete ventral decompression of the spinal canal and solid fusion of the lumbar spine at one time. It is an effective minimally invasive technique for the treatment of monosegmental severe LSS, which is promising and worthy of further clinical practice.

Carbon Monitor Cities near-real-time daily estimates of CO2 emissions from 1500 cities worldwide.

Building on near-real-time and spatially explicit estimates of daily carbon dioxide (CO2) emissions, here we present and analyze a new city-level dataset of fossil fuel and cement emissions, Carbon Monitor Cities, which provides daily estimates of emissions from January 2019 through December 2021 for 1500 cities in 46 countries, and disaggregates five sectors: power generation, residential (buildings), industry, ground transportation, and aviation. The goal of this dataset is to improve the timeliness and temporal resolution of city-level emission inventories and includes estimates for both functional urban areas and city administrative areas that are consistent with global and regional totals. Comparisons with other datasets (i.e. CEADs, MEIC, Vulcan, and CDP-ICLEI Track) were performed, and we estimate the overall annual uncertainty range to be ±21.7%. Carbon Monitor Cities is a near-real-time, city-level emission dataset that includes cities around the world, including the first estimates for many cities in low-income countries.