Efficient removal of ammonia-nitrogen in wastewater by zeolite molecular sieves prepared from coal fly ash.

Zeolite molecular sieves are potential adsorbents for wastewater treatment, characterized by high efficiency, simple process, easy regeneration, and low treatment cost. In this study, zeolite A molecular sieves were prepared using coal fly ash (CFA), which is an effective method for the utilization of CFA. The results showed that the CFA-based zeolite molecular sieves synthesized under optimized conditions exhibited excellent adsorption and removal rates (> 40%) for ammonia-nitrogen in wastewater of different concentrations and properties. The analysis of adsorption kinetics revealed that the adsorption process followed pseudo-second-order kinetics model, indicating that the adsorption of ammonia-nitrogen on zeolite is primarily controlled by chemisorption rather than physisorption. The adsorption process can be divided into two stages, with a higher adsorption rate and a smaller diffusion boundary layer thickness in the first stage, and a lower adsorption rate and an increased diffusion boundary layer thickness in the second stage. This indicates that as the adsorption proceeds, the internal diffusion resistance within the particles gradually increases, leading to a decrease in the adsorption rate until reaching equilibrium, where both the diffusion and adsorption become stable. The adsorption isotherms of ammonia-nitrogen on zeolite A conformed to the assumptions of the Langmuir model, suggesting that the adsorption mechanism primarily involves uniform monolayer adsorption on the surface without intermolecular interactions.

NOX1-mediated oxidative stress induces chondrocyte ferroptosis by inhibiting the Nrf2/HO-1 pathway.

Osteoarthritis (OA) is a common joint disease associated with the aging of the population, and it reduces the quality of life of patients. It is characterized by the destruction of articular cartilage and the secretion of inflammatory cytokines. Owing to the unclear pathogenesis of OA, current treatment methods have significant limitations. Oxidative stress has been revealed to play an important role in the development of OA. Our experiments indicated that the levels of GSH decreased and the level of MDA increased in chondrocytes, which induced ferroptosis in chondrocytes in OA. We also revealed that ferroptosis was the main mechanism of cartilage destruction caused by the addition of the ferroptosis activator erastin and the ferroptosis inhibitor ferrostatin-1. NOX1 is the main modulator of oxidative stress by increasing the generation of reactive oxidative species (ROS). We suppressed the expression of NOX1 in chondrocytes through cell transfection. The expression of collagen II and MMP13, and the secretion of IL-1ß and TNF-α were reversed. An increase in the mitochondrial membrane potential and a decrease in the level of intracellular ROS indicate an improvement in oxidative damage. Additionally, we determined the effect of the Nrf2/HO-1 pathway on NOX1-mediated chondrocyte injury. We found that NOX1 inhibited the expression of Nrf2/HO-1, but the activation of Nrf2 improved the oxidative damage to chondrocytes in vivo and vitro. This study revealed that NOX1-mediated oxidative stress induces chondrocyte ferroptosis by inhibiting the Nrf2/HO-1 pathway. Our findings contribute to revealing the pathogenesis of OA, providing targets for drug design and optimizing the clinical treatment of OA.

Research Progress on Detection of Pathogens in Medical Wastewater by Electrochemical Biosensors.

The detection of pathogens in medical wastewater is crucial due to the high content of pathogenic microorganisms that pose significant risks to public health and the environment. Medical wastewater, which includes waste from infectious disease and tuberculosis facilities, as well as comprehensive medical institutions, contains a variety of pathogens such as bacteria, viruses, fungi, and parasites. Traditional detection methods like nucleic acid detection and immunological assays, while effective, are often time-consuming, expensive, and not suitable for rapid detection in underdeveloped areas. Electrochemical biosensors offer a promising alternative with advantages including simplicity, rapid response, portability, and low cost. This paper reviews the sources of pathogens in medical wastewater, highlighting specific bacteria (e.g., E. coli, Salmonella, Staphylococcus aureus), viruses (e.g., enterovirus, respiratory viruses, hepatitis virus), parasites, and fungi. It also discusses various electrochemical biosensing techniques such as voltammetry, conductometry, impedance, photoelectrochemical, and electrochemiluminescent biosensors. These technologies facilitate the rapid, sensitive, and specific detection of pathogens, thereby supporting public health and environmental safety. Future research may should pay more attention on enhancing sensor sensitivity and specificity, developing portable and cost-effective devices, and innovating detection methods for diverse pathogens to improve public health protection and environmental monitoring.

Meta Learning with Attention Based FP-GNNs for Few-Shot Molecular Property Prediction.

Molecular property prediction holds significant importance in drug discovery, enabling the identification of biologically active compounds with favorable drug-like properties. However, the low data problem, arising from the scarcity of labeled data in drug discovery, poses a substantial obstacle for accurate predictions. To address this challenge, we introduce a novel architecture, AttFPGNN-MAML, for few-shot molecular property prediction. The proposed approach incorporates a hybrid feature representation to enrich molecular representations and model intermolecular relationships specific to the task. By leveraging ProtoMAML, a meta-learning strategy, our model is trained and adapted to new tasks. Evaluation on two few-shot data sets, MoleculeNet and FS-Mol, demonstrates our method's superior performance in three out of four tasks and across various support set sizes. These results convincingly validate the effectiveness of our method in the realm of few-shot molecular property prediction. The source code is publicly available at https://github.com/sanomics-lab/AttFPGNN-MAML.

DNA methylation regulator-based molecular subtyping and tumor microenvironment characterization in hepatocellular carcinoma.

Backgroud: Although recent studies have reported the regulation of the immune response in hepatocellular carcinoma (HCC) through DNA methylation, the comprehensive impact methylation modifications on tumor microenvironment characteristics and immunotherapy efficacy has not been fully elucidated. Methods: In this research, we conducted a comprehensive assessment of the patterns of DNA methylation regulators and the profiles of the tumor microenvironment (TME) in HCC, focusing on 21 specific DNA methylation regulators. We subsequently developed a unique scoring system, a DNA methylation score (DMscore), to assess the individual DNA methylation modifications among the three distinct methylation patterns for differentially expressed genes (DEGs). Results: Three distinct methylation modification patterns were identified with distinct TME infiltration characteristics. We demonstrated that the DMscore could predict patient subtype, TME infiltration, and patient prognosis. A low DMscore, characterized by an elevated tumor mutation burden (TMB), hepatitis B virus (HBV)/hepatitis C virus (HCV) infection, and immune activation, indicates an inflamed tumor microenvironment phenotype with a 5-year survival rate of 7.8%. Moreover, a low DMscore appeared to increase the efficacy of immunotherapy in the anti-CTLA-4/PD-1/PD-L1 cohort. Conclusions: In brief, this research has enhanced our understanding of the correlation between modifications in DNA methylation patterns and the profile of the tumor microenvironment in individuals diagnosed with HCC. The DMscore may serve as an alternative biomarker for survival and efficacy of immunotherapy in patients with HCC.

Obesity and lipid metabolism in the development of osteoporosis (Review).

Osteoporosis is a common bone metabolic disease that causes a heavy social burden and seriously threatens life. Improving osteogenic capacity is necessary to correct bone mass loss in the treatment of osteoporosis. Osteoblasts are derived from the differentiation of bone marrow mesenchymal stem cells, a process that opposes adipogenic differentiation. The peroxisome proliferator­activated receptor γ and Wnt/ß­catenin signaling pathways mediate the mutual regulation of osteogenesis and adipogenesis. Lipid substances play an important role in the occurrence and development of osteoporosis. The content and proportion of lipids modulate the activity of immunocytes, mainly macrophages, and the secretion of inflammatory factors, such as IL­1, IL­6 and TNF­α. These inflammatory effectors increase the activity and promote the differentiation of osteoclasts, which leads to bone imbalance and stronger bone resorption. Obesity also decreases the activity of antioxidases and leads to oxidative stress, thereby inhibiting osteogenesis. The present review starts by examining the bidirectional differentiation of BM­MSCs, describes in detail the mechanism by which lipids affect bone metabolism, and discusses the regulatory role of inflammation and oxidative stress in this process. The review concludes that a reasonable adjustment of the content and proportion of lipids, and the alleviation of inflammatory storms and oxidative damage induced by lipid imbalances, will improve bone mass and treat osteoporosis.

MolProphet: A One-Stop, General Purpose, and AI-Based Platform for the Early Stages of Drug Discovery.

Artificial intelligence (AI) is an effective tool to accelerate drug discovery and cut costs in discovery processes. Many successful AI applications are reported in the early stages of small molecule drug discovery. However, most of those applications require a deep understanding of software and hardware, and focus on a single field that implies data normalization and transfer between those applications is still a challenge for normal users. It usually limits the application of AI in drug discovery. Here, based on a series of robust models, we formed a one-stop, general purpose, and AI-based drug discovery platform, MolProphet, to provide complete functionalities in the early stages of small molecule drug discovery, including AI-based target pocket prediction, hit discovery and lead optimization, and compound targeting, as well as abundant analyzing tools to check the results. MolProphet is an accessible and user-friendly web-based platform that is fully designed according to the practices in the drug discovery industry. The molecule screened, generated, or optimized by the MolProphet is purchasable and synthesizable at low cost but with good drug-likeness. More than 400 users from industry and academia have used MolProphet in their work. We hope this platform can provide a powerful solution to assist each normal researcher in drug design and related research areas. It is available for everyone at https://www.molprophet.com/.

Single-cell RNA sequencing reveals that an imbalance in monocyte subsets rather than changes in gene expression patterns is a feature of postmenopausal osteoporosis.

The role of monocytes in postmenopausal osteoporosis is widely recognized; however, the mechanisms underlying monocyte reprogramming remain unknown. In this study, single-cell RNA sequencing (scRNA-seq) was conducted on CD14+ bone marrow monocytes obtained from 3 postmenopausal women with normal BMD and 3 women with postmenopausal osteoporosis (PMOP). Monocle2 was used to classify the monocytes into 7 distinct clusters. The proportion of cluster 1 significantly decreased in PMOP patients, while the proportion of cluster 7 increased. Further analysis via GSEA, transcription factor activity analysis, and sc-metabolic analysis revealed significant differences between clusters 1 and 7. Cluster 7 exhibited upregulated pathways associated with inflammation, immunity, and osteoclast differentiation, whereas cluster 1 demonstrated the opposite results. Monocle2, TSCAN, VECTOR, and scVelo data indicated that cluster 1 represented the initial subset and that cluster 7 represents one of the terminal subsets. BayesPrism and ssGSEA were employed to analyze the bulk transcriptome data obtained from the GEO database. The observed alterations in the proportions of 1 and 7 were validated and found to have diagnostic significance. CD16 serves as the marker gene for cluster 7, thus leading to an increased proportion of CD16+ monocytes in women with PMOP. Flow cytometry was used to assess the consistency of outcomes with those of the bioinformatic analysis. Subsequently, an additional scRNA-seq analysis was conducted on bone marrow mononuclear cells obtained from 3 patients with PMOP and 3 postmenopausal women with normal BMD. The differential proportions of cluster 1 and cluster 7 were once again confirmed, with the pathological effect of cluster 7 may attribute to cell-cell communication. The scRNA-seq findings suggest that an imbalance in monocyte subsets is a characteristic feature of PMOP. These findings elucidate the limitations of utilizing bulk transcriptome data for detecting alterations in monocytes, which may influence novel research inquiries.

Monocytes are a type of white blood cell that plays a role in postmenopausal osteoporosis (PMOP), a condition where bones become weak and brittle after menopause. However, how monocytes change in this condition is not fully understood. In this study, single-cell RNA sequencing was used to analyze bone marrow monocytes from postmenopausal women with normal bone density and those with osteoporosis. Two distinct types of monocytes were identified, which were called clusters 1 and 7. In women with PMOP, there was a decrease in cluster 1 monocytes and an increase in cluster 7 monocytes. This change was validated in external datasets and in peripheral blood. Further analysis showed that cluster 7 monocytes positively correlated with inflammation, immunity, and osteoclast differentiation (a process that leads to bone resorption). Cluster 1 monocytes were found to be the initial subset, while cluster 7 monocytes were one of the terminal subsets. Overall, this study suggests that an imbalance in monocyte subsets is a characteristic feature of postmenopausal osteoporosis. These findings have important implications for understanding the role of monocytes in bone health.

Boosted Electrocatalytic Degradation of Levofloxacin by Chloride Ions: Performances Evaluation and Mechanism Insight with Different Anodes.

As chloride (Cl-) is a commonly found anion in natural water, it has a significant impact on electrocatalytic oxidation processes; yet, the mechanism of radical transformation on different types of anodes remains unexplored. Therefore, this study aims to investigate the influence of chlorine-containing environments on the electrocatalytic degradation performance of levofloxacin using BDD, Ti4O7, and Ru-Ti electrodes. The comparative analysis of the electrode performance demonstrated that the presence of Cl- improved the removal and mineralization efficiency of levofloxacin on all the electrodes. The enhancement was the most pronounced on the Ti4O7 electrode and the least significant on the Ru-Ti electrode. The evaluation experiments and EPR characterization revealed that the increased generation of hydroxyl radicals and active chlorine played a major role in the degradation process, particularly on the Ti4O7 anode. The electrochemical performance tests indicated that the concentration of Cl- affected the oxygen evolution potentials of the electrode and consequently influenced the formation of hydroxyl radicals. This study elucidates the mechanism of Cl- participation in the electrocatalytic degradation of chlorine-containing organic wastewater. Therefore, the highly chlorine-resistant electrocatalytic anode materials hold great potential for the promotion of the practical application of the electrocatalytic treatment of antibiotic wastewater.

The subacute toxicity and underlying mechanisms of biomimetic mesoporous polydopamine nanoparticles.

Recently, mesoporous nanomaterials with widespread applications have attracted great interest in the field of drug delivery due to their unique structure and good physiochemical properties. As a biomimetic nanomaterial, mesoporous polydopamine (MPDA) possesses both a superior nature and good compatibility, endowing it with good clinical transformation prospects compared with other inorganic mesoporous nanocarriers. However, the subacute toxicity and underlying mechanisms of biomimetic mesoporous polydopamine nanoparticles remain uncertain. Herein, we prepared MPDAs by a soft template method and evaluated their primary physiochemical properties and metabolite toxicity, as well as potential mechanisms. The results demonstrated that MPDA injection at low (3.61 mg/kg) and medium doses (10.87 mg/kg) did not significantly change the body weight, organ index or routine blood parameters. In contrast, high-dose MPDA injection (78.57 mg/kg) is associated with disturbances in the gut microbiota, activation of inflammatory pathways through the abnormal metabolism of bile acids and unsaturated fatty acids, and potential oxidative stress injury. In sum, the MPDA dose applied should be controlled during the treatment. This study first provides a systematic evaluation of metabolite toxicity and related mechanisms for MPDA-based nanoparticles, filling the gap between their research and clinical transformation as a drug delivery nanoplatform.

Exploring ß-glucan as a micro-nano system for oral delivery targeted the colon.

The critical role of oral colon-specific delivery systems (OCDDS) is important for delivering active agents to the colon and rectum specifically via the oral route. The use of micro/nanostructured OCDDS further improves drug stability, bioavailability, and retention time, leading to enhanced therapeutic effects. However, designing micro/nanoscale OCDDSs is challenging due to pH changes, enzymatic degradation, and systemic absorption and metabolism. Biodegradable natural polysaccharides are a promising solution to these problems, and ß-glucan is one of the most promising natural polysaccharides due to its unique structural features, conformational flexibility, and specific processing properties. This review covers the diverse chemical structures of ß-glucan, its benefits (biocompatibility, easy modification, and colon-specific degradation), and various ß-glucan-based micro/nanosized OCDDSs, as well as their drawbacks. The potential of ß-glucan offers exciting new opportunities for colon-specific drug delivery.

Effect of terahertz electromagnetic field on single-file water transport through a carbon nanotube.

With the advancement in terahertz technology, the terahertz electromagnetic field has been proven to be an effective strategy to tune the nanofluidic transport. In this study, we utilize molecular dynamics simulations to systematically analyze the transport of single-file water through a carbon nanotube (CNT) under terahertz electromagnetic fields, focusing on the CNT length, field strength, polarization direction and frequency. Strikingly, with the increase in field strength, the water flow exhibits a transition from normal to super permeation states because of the resonance effect, and the threshold field shifts to low values for long CNTs. The field component parallel to the CNT axis contributes to the resonance effect and increasing water flow, but the vertical component maintains the structure of the single-file water chain and even impedes the water flow. As a result, for a continuous change of field direction, the water flow changes from super permeation to normal states. With the increase in field frequency, the water flow also changes from super permeation to normal or even frozen states, where a higher frequency is required to trigger the super permeation states for lower field strength. Our results provide a comprehensive insight into the effect of terahertz electromagnetic field on the transport of single-file water chains and should have great implications for designing novel nanofluidic devices.

The biological significance of cuproptosis-key gene MTF1 in pan-cancer and its inhibitory effects on ROS-mediated cell death of liver hepatocellular carcinoma.

Metal regulatory transcription factor 1 (MTF1) has been reported to be correlated with several human diseases, especially like cancers. Exploring the underlying mechanisms and biological functions of MTF1 could provide novel strategies for clinical diagnosis and therapy of cancers. In this study, we conducted the comprehensive analysis to evaluate the profiles of MTF1 in pan-cancer. For example, TIMER2.0, TNMplot and GEPIA2.0 were employed to analyze the expression values of MTF1 in pan-cancer. The methylation levels of MTF1 were evaluated via UALCAN and DiseaseMeth version 2.0 databases. The mutation profiles of MTF1 in pan-cancers were analyzed using cBioPortal. GEPIA2.0, Kaplan-Meier plotter and cBioPortal were also used to explore the roles of MTF1 in cancer prognosis. We found that high MTF1 expression was related to poor prognosis of liver hepatocellular carcinoma (LIHC) and brain lower grade glioma (LGG). Also, high expression level of MTF1 was associated with good prognosis of kidney renal clear cell carcinoma (KIRC), lung cancer, ovarian cancer and breast cancer. We investigated the genetic alteration and methylation levels of MTF1 between the primary tumor and normal tissues. The relationship between MTF1 expression and several immune cells was analyzed, including T cell CD8 + and dendritic cells (DC). Mechanically, MTF1-interacted molecules might participate in the regulation of metabolism-related pathways, such as peptidyl-serine phosphorylation, negative regulation of cellular amide metabolic process and peptidyl-threonine phosphorylation. Single cell sequencing indicated that MTF1 was associated with angiogenesis, DNA repair and cell invasion. In addition, in vitro experiment indicated knockdown of MTF1 resulted in the suppressed cell proliferation, increased reactive oxygen species (ROS) and promoted cell death in LIHC cells HepG2 and Huh7. Taken together, this pan-cancer analysis of MTF1 has implicated that MTF1 could play an essential role in the progression of various human cancers.

Contribution of whole slide imaging-based deep learning in the assessment of intraoperative and postoperative sections in neuropathology.

The pathological diagnosis of intracranial germinoma (IG), oligodendroglioma, and low-grade astrocytoma on intraoperative frozen section (IFS) and hematoxylin-eosin (HE)-staining section directly determines patients' treatment options, but it is a difficult task for pathologists. We aimed to investigate whether whole-slide imaging (WSI)-based deep learning can contribute new precision to the diagnosis of IG, oligodendroglioma, and low-grade astrocytoma. Two types of WSIs (500 IFSs and 832 HE-staining sections) were collected from 379 patients at multiple medical centers. Patients at Center 1 were split into the training, testing, and internal validation sets (3:1:1), while the other centers were the external validation sets. First, we subdivided WSIs into small tiles and selected tissue tiles using a tissue tile selection model. Then a tile-level classification model was established, and the majority voting method was used to determine the final diagnoses. Color jitter was applied to the tiles so that the deep learning (DL) models could adapt to the variations in the staining. Last, we investigated the effectiveness of model assistance. The internal validation accuracies of the IFS and HE models were 93.9% and 95.3%, respectively. The external validation accuracies of the IFS and HE models were 82.0% and 76.9%, respectively. Furthermore, the IFS and HE models can predict Ki-67 positive cell areas with R2 of 0.81 and 0.86, respectively. With model assistance, the IFS and HE diagnosis accuracy of pathologists improved from 54.6%-69.7% and 53.5%-83.7% to 87.9%-93.9% and 86.0%-90.7%, respectively. Both the IFS model and the HE model can differentiate the three tumors, predict the expression of Ki-67, and improve the diagnostic accuracy of pathologists. The use of our model can assist clinicians in providing patients with optimal and timely treatment options.

Oxidative stress: A common pathological state in a high-risk population for osteoporosis.

Osteoporosis is becoming a major concern in the field of public health. The process of bone loss is insidious and does not directly induce obvious symptoms. Complications indicate an irreversible decrease in bone mass. The high-risk populations of osteoporosis, including postmenopausal women, elderly men, diabetic patients and obese individuals need regular bone mineral density testing and appropriate preventive treatment. However, the primary changes in these populations are different, increasing the difficulty of effective treatment of osteoporosis. Determining the core pathogenesis of osteoporosis helps improve the efficiency and efficacy of treatment among these populations. Oxidative stress is a common pathological state secondary to estrogen deficiency, aging, hyperglycemia and hyperlipemia. In this review, we divided oxidative stress into the direct effect of reactive oxygen species (ROS) and the reduction of antioxidant enzyme activity to discuss their roles in the development of osteoporosis. ROS initiated mitochondrial apoptotic signaling and suppressed osteogenic marker expression to weaken osteogenesis. MAPK and NF-κB signaling pathways mediated the positive effect of ROS on osteoclast differentiation. Antioxidant enzymes not only eliminate the negative effects of ROS, but also directly participate in the regulation of bone metabolism. Additionally, we also described the roles of proinflammatory factors and HIF-1α under the pathophysiological changes of inflammation and hypoxia, which provided a supplement of oxidative stress-induced osteoporosis. In conclusion, our review showed that oxidative stress was a common pathological state in a high-risk population for osteoporosis. Targeted oxidative stress treatment would greatly optimize the therapeutic schedule of various osteoporosis treatments.

Metformin reverses oxidative stress­induced mitochondrial dysfunction in pre­osteoblasts via the EGFR/GSK­3ß/calcium pathway.

Oxidative stress is one of the main causes of osteoblast apoptosis induced by post­menopausal osteoporosis. The authors previously found that metformin can reverse the loss of bone mass in post­menopausal osteoporosis. The present study aimed to further clarify the effects and mechanisms of action of metformin in post­menopausal osteoporosis under conditions of oxidative stress. Combined with an in­depth investigation using the transcriptome database, the association between oxidative stress and mitochondrial dysfunction in post­menopausal osteoporosis was confirmed. A pre­osteoblast model of oxidative stress was constructed, and the apoptotic rate following the addition of hydrogen peroxide and metformin was detected using CCK­8 assay and Annexin V­FITC/PI staining. Mitochondrial membrane potential was detected using the JC­1 dye, the intracellular calcium concentration was detected using Fluo­4 AM, the intracellular reactive oxygen species (ROS) level was observed using DCFH­DA, and the mitochondrial superoxide level was observed using MitoSOX Red. Bay K8644 was used to increase the level of intracellular calcium. siRNA was used to interfere with the expression of glycogen synthase kinase (GSK)­3ß. Western blot analysis was used to detect the expression of mitochondrial dysfunction­related proteins. The results revealed that oxidative stress decreased mitochondrial membrane potential and increased intracellular ROS, mitochondrial superoxide and cytoplasmic calcium levels in pre­osteoblasts; however, metformin improved mitochondrial dysfunction and reversed oxidative stress­induced injury. Metformin inhibited mitochondrial permeability transition pore opening, suppressed the cytoplasmic calcium influx and reversed pre­osteoblast apoptosis by promoting GSK­3ß phosphorylation. Moreover, it was found that EGFR was the cell membrane receptor of metformin in pre­osteoblasts, and the EGFR/GSK­3ß/calcium axis played a key role in metformin reversing the oxidative stress response of pre­osteoblasts in post­menopausal osteoporosis. On the whole, these findings provide a pharmacological basis for the use of metformin for the treatment of post­menopausal osteoporosis.

A combined analysis of bulk and single-cell sequencing data reveals metabolic enzyme, pyruvate dehydrogenase E1 subunit beta (PDHB), as a prediction biomarker for the tumor immune response and immunotherapy.

Pyruvate dehydrogenase E1 subunit beta (PDHB) is located in mitochondria and catalyzes the conversion of glucose-derived acetyl-CoA. The detailed roles of PDHB in human cancers is unclear. Here, through comprehensive bioinformatics analysis, we found that PDHB was aberrantly expressed in multiple human cancers and is associated with patients' clinical stage. The abnormal expression of PDHB was related to the prognostic values of cancers, such as kidney renal clear cell carcinoma (KIRC) and kidney renal papillary cell carcinoma (KIRP). The Wanderer database with clinical data from Cancer Genome Atlas (TCGA) showed a significant correlation between PDHB expression and the pathologic stage of KIRP patients. We also evaluated the mutation profiles of PDHB in pan-cancer, and showed its roles on the patients' prognosis. At last, from several immunity algorithms, we demonstrated that the expression of PDHB was correlated with the infiltration of various immune cells in pan-cancer. Moreover, the aberrant PDHB had effects on the response to immune checkpoint inhibitors in cancer patients, such as anti-PD-1. Taken together, our study demonstrated the prognostic values of PDHB in pan-cancers. PDHB may be a potential molecular marker to predicting the immune response in cancer patients.

Comprehensive analysis regarding the prognostic significance of downregulated ferroptosis-related gene AKR1C2 in gastric cancer and its underlying roles in immune response.

Ferroptosis is a cell death form that has been reported to be involved in the progression of gastric cancer (GC). However, the underlying mechanism of ferroptosis in GC still needs to be further explored. This study conducted a survey regarding the biological functions of ferroptosis-related gene AKR1C2 in GC. Multiple bioinformatic platforms were applied to indicate that the expression level of AKR1C2 was downregulated in GC tissues, which displayed good prognostic value. Clinical statistics proved that AKR1C2 expression was correlated with several tumor characteristics of GC patients, such as characteristics of N-stage tumor or residual tumor. Additionally, LinkedOmics was employed to explore the co-expression network and molecular pathways of AKR1C2 in GC. Eventually, AKR1C2 was found to be involved in several immune-related signatures, such as immunostimulators, immunoinhibitors, chemokines and chemokine receptors. To sum up, these results may provide a novel insight into the significance and biological functions of ferroptosis-related gene AKR1C2 in GC tumorigenesis.

The role of melatonin in the development of postmenopausal osteoporosis.

Melatonin is an important endogenous hormone that modulates homeostasis in the microenvironment. Recent studies have indicated that serum melatonin levels are closely associated with the occurrence and development of osteoporosis in postmenopausal women. Exogenous melatonin could also improve bone mass and increase skeletal strength. To determine the underlying mechanisms of melatonin in the prevention and treatment of postmenopausal osteoporosis, we performed this review to analyze the role of melatonin in bone metabolism according to its physiological functions. Serum melatonin is related to bone mass, the measurement of which is a potential method for the diagnosis of osteoporosis. Melatonin has a direct effect on bone remodeling by promoting osteogenesis and suppressing osteoclastogenesis. Melatonin also regulates the biological rhythm of bone tissue, which benefits its osteogenic effect. Additionally, melatonin participates in the modulation of the bone microenvironment. Melatonin attenuates the damage induced by oxidative stress and inflammation on osteoblasts and prevents osteolysis from reactive oxygen species and inflammatory factors. As an alternative drug for osteoporosis, melatonin can improve the gut ecology, remodel microbiota composition, regulate substance absorption and maintain metabolic balance, all of which are beneficial to the health of bone structure. In conclusion, our review systematically demonstrates the effects of melatonin on bone metabolism. Based on the evidence in this review, melatonin will play a more important role in the diagnosis, prevention and treatment of postmenopausal osteoporosis.

Phosphaturic mesenchymal tumor in right thigh: 2 cases report and literature review.

Background: Phosphaturic mesenchymal tumor (PMT) is a very rare tumor of bone and soft tissue that has no specific clinical manifestations. Here we present 2 cases of PMT in the right thigh, including comparatively adequate immunohistochemistry. Case Presentation: We described 2 cases of PMT in the right thigh with manifestations of hypophosphatemia. PET-CT examination showed that both patients had lesions with increased expression of somatostatin receptors in the right thigh. Bland cells and dirty calcified stroma were exhibited under the microscope. And immunohistochemical detection of FGF-23 was positive. Conclusions: PMT is a very uncommon tumor for which diagnosis and treatment are often delayed. Considering the importance of surgery for the treatment of this disease, a full understanding of its clinicopathological features will facilitate the diagnosis of this disease.