Metagenomic perspectives on antibiotic resistance genes in tap water: The environmental characteristic, potential mobility and health threat.

As an emerging environmental contaminant, antibiotic resistance genes (ARGs) in tap water have attracted great attention. Although studies have provided ARG profiles in tap water, research on their abundance levels, composition characteristics, and potential threat is still insufficient. Here, 9 household tap water samples were collected from the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. Additionally, 75 sets of environmental sample data (9 types) were downloaded from the public database. Metagenomics was then performed to explore the differences in the abundance and composition of ARGs. 221 ARG subtypes consisting of 17 types were detected in tap water. Although the ARG abundance in tap water was not significantly different from that found in drinking water plants and reservoirs, their composition varied. In tap water samples, the three most abundant classes of resistance genes were multidrug, fosfomycin and MLS (macrolide-lincosamide-streptogramin) ARGs, and their corresponding subtypes ompR, fosX and macB were also the most abundant ARG subtypes. Regarding the potential mobility, vanS had the highest abundance on plasmids and viruses, but the absence of key genes rendered resistance to vancomycin ineffective. Generally, the majority of ARGs present in tap water were those that have not been assessed and are currently not listed as high-threat level ARG families based on the World Health Organization Guideline. Although the current potential threat to human health posed by ARGs in tap water is limited, with persistent transfer and accumulation, especially in pathogens, the potential danger to human health posed by ARGs should not be ignored.

Androgen receptor expression and clinical characteristics in breast cancer.

OBJECTIVE: To investigate the relationship between the expression of androgen receptor (AR) and clinical characteristics in breast cancer. PATIENTS AND METHODS: The clinical records of all 432 patients tested for AR in our institution between January 2020 and May 2023 were reviewed. Clinical characteristics, age, menopausal status, tumor node metastasis (TNM) stage, distant metastasis, pathological complete response (pCR), histopathological features histological grade, estrogen receptor (ER), progesterone receptor, Her-2, Ki-67, and molecular subtype were registered for all patients. RESULTS: About 377 (87.27%) of the 432 patients had AR expression. No significant difference in AR expression was found with age, menopausal status, TNM stage of primary tumor, or pCR. AR was positively and significantly associated with the histological grade, and recurrence. The AR expression was significantly related with molecular subtypes, including ER, PR Her-2, Ki67 and molecular subtype. ER (OR = 10.489, 95%CI: 5.470-21.569), PR (OR = 7.690, 95%CI: 3.974-16.129, Her-2 (OR = 10.489, 95%CI: 2.779-23.490 and tumor recurrence (OR = 0.110, 95%CI: 0.031-0.377 were significant independent risk factors affecting AR expression. CONCLUSIONS: AR expression can serve as a reliable basis for judging the clinical molecular types and poor prognosis for breast cancer. AR may be a novel biomarker and target in AR-positive breast cancer depending on significant difference in AR expression among different molecular types of breast cancer.

Loss of OsSPL8 Function Confers Improved Resistance to Glufosinate and Abiotic Stresses in Rice.

Weeds are among the most significant factors contributing to decreases in crop yield and quality. Glufosinate, a nonselective, broad-spectrum herbicide, has been extensively utilized for weed control in recent decades. However, crops are usually sensitive to glufosinate. Therefore, the development of glufosinate-resistant crops is crucial for effective weed management in agriculture. In this study, we characterized a SQUAMOSA promoter-binding-like (SPL) factor, OsSPL8, which acts as a negative regulator of glufosinate resistance by inhibiting the transcription of OsGS1;1 and OsGS2 and consequently reducing GS activity. Furthermore, the loss of OsSPL8 function enhanced tolerance to drought and salt stresses. Transcriptomic comparisons between the gar18-3 mutant and wild type revealed that OsSPL8 largely downregulates stress-responsive genes and upregulates growth-related genes. We demonstrated that OsSPL8 directly regulates OsOMTN6 and OsNAC17, which influence drought tolerance. In addition, OsSPL8 directly represses the expression of salt stress tolerance-related genes such as OsHKT1.1 and OsTPP1. Collectively, our results demonstrate that OsSPL8 is a negative regulator of both glufosinate resistance and abiotic stress tolerance.

Identification of AS1842856 as a novel small-molecule GSK3α/ß inhibitor against Tauopathy by accelerating GSK3α/ß exocytosis.

Glycogen synthase kinase-3α/ß (GSK3α/ß) is a critical kinase for Tau hyperphosphorylation which contributes to neurodegeneration. Despite the termination of clinical trials for GSK3α/ß inhibitors in Alzheimer's disease (AD) treatment, there is a pressing need for novel therapeutic strategies targeting GSK3α/ß. Here, we identified the compound AS1842856 (AS), a specific forkhead box protein O1 (FOXO1) inhibitor, reduced intracellular GSK3α/ß content in a FOXO1-independent manner. Specifically, AS directly bound to GSK3α/ß, promoting its translocation to the multivesicular bodies (MVBs) and accelerating exocytosis, ultimately decreasing intracellular GSK3α/ß content. Expectedly, AS treatment effectively suppressed Tau hyperphosphorylation in cells exposed to okadaic acid or expressing the TauP301S mutant. Furthermore, AS was visualized to penetrate the blood-brain barrier (BBB) using an imaging mass microscope. Long-term treatment of AS enhanced cognitive function in P301S transgenic mice by mitigating Tau hyperphosphorylation through downregulation of GSK3α/ß expression in the brain. Altogether, AS represents a novel small-molecule GSK3α/ß inhibitor that facilitates GSK3α/ß exocytosis, holding promise as a therapeutic agent for GSK3α/ß hyperactivation-associated disorders.

Effectiveness Assessment of Bispectral Index Monitoring Compared with Conventional Monitoring in General Anesthesia: A Systematic Review and Meta-Analysis.

Background and Objective. The Bispectral Index (BIS) is utilized to guide the depth of anesthesia monitoring during surgical procedures. However, conflicting results regarding the benefits of BIS for depth of anesthesia monitoring have been reported in numerous studies. The purpose of this meta-analysis and systematic review was to assess the effectiveness of BIS for depth of anesthesia monitoring. Search Methods. A systematic search of Ovid-MEDLINE, Cochrane, and PubMed was conducted from inception to April 20, 2023. Clinical trial registers and grey literature were also searched, and reference lists of included studies, as well as related review articles, were manually reviewed. Selection Criteria. The inclusion criteria were randomized controlled trials without gender or age restrictions. The control groups used conventional monitoring, while the intervention groups utilized BIS monitoring. The exclusion criteria included duplicates, reviews, animal studies, unclear outcomes, and incomplete data. Data Collection and Analysis. Two independent reviewers screened the literature, extracted data, and assessed methodological quality, with analyses conducted using R 4.0 software. Main Results. Forty studies were included. In comparison to the conventional depth of anesthesia monitoring, BIS monitoring reduced the postoperative cognitive dysfunction risk (RR = 0.85, 95% CI: 0.73∼0.99, P = 0.04), shortened the eye-opening time (MD = -1.34, 95% CI: -2.06∼-0.61, P < 0.01), orientation recovery time (MD = -1.99, 95% CI: -3.62∼-0.36, P = 0.02), extubation time (MD = -2.54, 95% CI: -3.50∼-1.58, P < 0.01), and postanesthesia care unit stay time (MD = -7.11, 95% CI: -12.67∼-1.55, P = 0.01) and lowered the anesthesia drug dosage (SMD = -0.39, 95% CI: -0.63∼-0.15, P < 0.01). Conclusion. BIS can be used to effectively monitor the depth of anesthesia. Its use in general anesthesia enhances the effectiveness of both patient care and surgical procedures.

Analysis of Factors Influencing Hospitalization Expenses of Patients with Gastric Cancer in Shanghai, 2014-2021: Based on Grey Relational Analysis and Structural Equation Modeling.

OBJECTIVES: This study analyzed the basic condition and the influencing factors of hospitalization costs of patients with gastric cancer in Shanghai from 2014 to 2021, so as to provide a scientific reference for promoting the reform of the medical and healthcare system. METHODS: The study data were obtained from the electronic medical record system of Shanghai Hospital. The grey relational analysis was applied to analyze the correlation strength of various expenses with hospitalization costs. The structural equation modeling was constructed to analyze the influences of factors on the hospitalization expenses, as well as the relationship between each factor. RESULTS: A total of 23 335 study subjects were included. The results of grey relational analysis showed that the total cost of drugs had the strongest correlation with hospitalization expenses, followed by material expenses and surgery cost, whereas those of others were lower. The results of the structural equation modeling showed that age had the greatest influence on hospitalization expenses with a path coefficient of 0.618. Other influencing factors included surgery history, length of stay, hospital level, gender, and medical insurance. CONCLUSIONS: The total cost of drugs had the strongest correlation with hospitalization expenses. Factors such as gender, age, and hospital level all affect the hospitalization expenses. In the future, it is necessary to take further measures to control the cost of drugs and constantly optimize the structure of hospitalization costs. Meanwhile, the reform of the medical and healthcare system should be deepened to reasonably regulate the medical behaviors and reduce the financial burden of patients.

Inhibition of PLA2G4A attenuated valproic acid- induced lysosomal membrane permeabilization and restored impaired autophagic flux: Implications for hepatotoxicity.

Valproic acid (VPA) has broad efficacy against several seizures but causes liver injury limiting its prolonged clinical use. Some studies have demonstrated that VPA-induced hepatotoxicity is characterized by microvesicular hepatic steatosis. However, novel detailed mechanisms to explain VPA-induced hepatic steatosis and experimentally rigorously validated protective agents are still lacking. In this study, 8-week-old C57BL/6J mice were gavaged with VPA (500 mg/kg/d) for 4 weeks to establish an in vivo model of VPA-induced chronic liver injury. Quantitative proteomic and non-targeted lipidomic analyses were performed to explore the underlying mechanisms of VPA-induced hepatotoxicity. As a result, VPA-induced hepatotoxicity is associated with impaired autophagic flux, which is attributed to lysosomal dysfunction. Further studies revealed that VPA-induced lysosomal membrane permeabilization (LMP), allows soluble lysosomal enzymes to leak into the cytosol, which subsequently led to impaired lysosomal acidification. A lower abundance of glycerophospholipids and an increased abundance of lysophospholipids in liver tissues of mice in the VPA group strongly indicated that VPA-induced LMP may be mediated by the activation of phospholipase PLA2G4A. Metformin (Met) acted as a potential protective agent attenuating VPA-induced liver dysfunction and excessive lipid accumulation. Molecular docking and cellular thermal shift assays demonstrated that Met inhibited the activity of PLA2G4A by directly binding to it, thereby ameliorating VPA-induced LMP and autophagic flux impairment. In conclusion, this study highlights the therapeutic potential of targeting PLA2G4A-mediated lysosomal dysfunction in VPA-induced hepatotoxicity.

Predicting human effort needed to correct auto-segmentations.

Medical image auto-segmentation techniques are basic and critical for numerous image-based analysis applications that play an important role in developing advanced and personalized medicine. Compared with manual segmentations, auto-segmentations are expected to contribute to a more efficient clinical routine and workflow by requiring fewer human interventions or revisions to auto-segmentations. However, current auto-segmentation methods are usually developed with the help of some popular segmentation metrics that do not directly consider human correction behavior. Dice Coefficient (DC) focuses on the truly-segmented areas, while Hausdorff Distance (HD) only measures the maximal distance between the auto-segmentation boundary with the ground truth boundary. Boundary length-based metrics such as surface DC (surDC) and Added Path Length (APL) try to distinguish truly-predicted boundary pixels and wrong ones. It is uncertain if these metrics can reliably indicate the required manual mending effort for application in segmentation research. Therefore, in this paper, the potential use of the above four metrics, as well as a novel metric called Mendability Index (MI), to predict the human correction effort is studied with linear and support vector regression models. 265 3D computed tomography (CT) samples for 3 objects of interest from 3 institutions with corresponding auto-segmentations and ground truth segmentations are utilized to train and test the prediction models. The five-fold cross-validation experiments demonstrate that meaningful human effort prediction can be achieved using segmentation metrics with varying prediction errors for different objects. The improved variant of MI, called MIhd, generally shows the best prediction performance, suggesting its potential to indicate reliably the clinical value of auto-segmentations.

Predicting the effort required to manually mend auto-segmentations.

Auto-segmentation is one of the critical and foundational steps for medical image analysis. The quality of auto-segmentation techniques influences the efficiency of precision radiology and radiation oncology since high- quality auto-segmentations usually require limited manual correction. Segmentation metrics are necessary and important to evaluate auto-segmentation results and guide the development of auto-segmentation techniques. Currently widely applied segmentation metrics usually compare the auto-segmentation with the ground truth in terms of the overlapping area (e.g., Dice Coefficient (DC)) or the distance between boundaries (e.g., Hausdorff Distance (HD)). However, these metrics may not well indicate the manual mending effort required when observing the auto-segmentation results in clinical practice. In this article, we study different segmentation metrics to explore the appropriate way of evaluating auto-segmentations with clinical demands. The mending time for correcting auto-segmentations by experts is recorded to indicate the required mending effort. Five well-defined metrics, the overlapping area-based metric DC, the segmentation boundary distance-based metric HD, the segmentation boundary length-based metrics surface DC (surDC) and added path length (APL), and a newly proposed hybrid metric Mendability Index (MI) are discussed in the correlation analysis experiment and regression experiment. In addition to these explicitly defined metrics, we also preliminarily explore the feasibility of using deep learning models to predict the mending effort, which takes segmentation masks and the original images as the input. Experiments are conducted using datasets of 7 objects from three different institutions, which contain the original computed tomography (CT) images, the ground truth segmentations, the auto-segmentations, the corrected segmentations, and the recorded mending time. According to the correlation analysis and regression experiments for the five well-defined metrics, the variety of MI shows the best performance to indicate the mending effort for sparse objects, while the variety of HD works best when assessing the mending effort for non-sparse objects. Moreover, the deep learning models could well predict efforts required to mend auto-segmentations, even without the need of ground truth segmentations, demonstrating the potential of a novel and easy way to evaluate and boost auto-segmentation techniques.

Systematic characterization of the expression, prognosis and immune characteristics of PLOD family genes in breast cancer.

BACKGROUND: The expression patterns and prognostic value of Procollagen-lysine, 2-oxoglutarate 5-dioxygenase (PLOD) family genes in breast cancer remain to be elucidated. METHODS: The expression levels, prognostic value, and biological function of PLODs were determined using Oncomine, cBioPortal, GEPIA, Timer, UALCAN, PrognoScan, GeneMANIA, Metascape, and breast cancer tissue microarrays. RESULTS: The expressions of PLOD1 and PLOD3 were upregulated in breast cancer tissues, indicating worse clinical stages. High expression levels of PLOD family genes were associated with worse disease-free survival and distant metastasis-free survival, while high expression levels of PLOD1 and PLOD3 were related to worse overall survival in all breast cancer patients. The levels of PLOD family genes were all significantly higher in the age ≤51 y group, HR-negative patients, and triple negative breast cancer (TNBC) patients. They are associated with tumor-infiltrating immune cells (TIICs), including CD4+ T cells, CD8+ T cells, B cells, macrophages, neutrophils, and dendritic cells. According to co-expression gene analysis and functional enrichment, they are associated with protein hydroxylation, collagen biosynthesis and modifying enzymes, collagen metabolism, RNA splicing, extracellular matrix organization, VEGFA-VEGFR2 signaling pathway, and skeletal system development. Immunohistochemistry showed that the expressions of all PLOD family genes were significantly elevated in breast cancer tissues. PLOD1 expression was positively correlated with ER, TNBC status, and tumor grade. PLOD2 expression was positively connected with Ki-67 status. PLOD3 expression was positively related with age and tumor grade. CONCLUSIONS: PLOD family genes are novel potential prognostic biomarkers for breast cancer, and targeting PLOD inhibitors might be an effective strategy for breast cancer therapy.

Puerarin modulates proliferation, inflammation and ECM metabolism in human nucleus pulposus mesenchymal stem cells via the lncRNA LINC01535.

Background: Intervertebral disc degeneration (IVDD) is a highly prevalent musculoskeletal disorder characterized by progressive destruction of the intervertebral disc, leading to chronic low back pain and disability. Emerging evidence suggests that dysregulation of ferroptosis, a recently discovered form of regulated cell death, participates in IVDD pathogenesis. Puerarin, a natural flavonoid compound from Pueraria lobata, has shown promise in modulating ferroptosis in various diseases. Methods: Human nucleus pulposus-derived mesenchymal stem cells (NPMSCs) were isolated and identified by flow cytometry. We investigated the effects of puerarin on human NPMSCs and examined the underlying molecular mechanisms. Results: Puerarin significantly promoted human NPMSC proliferation, as evidenced by the increased cell viability and colony formation ability. Furthermore, puerarin suppressed the expression of cyclooxygenase-2 and the proinflammatory cytokine interleukin-6 in NPMSCs, demonstrating the anti-inflammatory properties of the compound. Notably, puerarin attenuated ECM breakdown by downregulating the ECM-degrading enzymes MMP3, MMP13 and ADAMTS5, and it increased ECM component synthesis, including collagen type II and aggrecan, by NPMSCs. Moreover, puerarin inhibited ferroptosis in NPMSCs by modulating the expression of key ferroptosis-related genes, including ACSL4, PTGS2 and GPX4. Depletion of LINC01535 abolished the effects of puerarin on proliferation, inflammation and ECM metabolism, suggesting a key role of this lncRNA in mediating the effects of puerarin. Conclusion: Our findings show that puerarin promotes the proliferation of human NPMSCs and ECM synthesis by these cells. Furthermore, puerarin inhibits inflammation and ECM degradation by suppressing ferroptosis via LINC01535. These results provide insights into the molecular mechanisms underlying the therapeutic effects of puerarin in IVDD. Targeting ferroptosis and its regulatory factors, such as LINC01535, may have therapeutic potential for the treatment of IDD and other degenerative disorders of the intervertebral disc. Further studies are needed to uncover the translational potential of puerarin and its downstream targets in preclinical and clinical applications.

Optimization of traction parameters for lumbar scoliosis.

BACKGROUND: Scoliosis is a high incidence disease that endangers the physical and mental health of adolescents. Traction therapy, as a conservative treatment plan, is helpful to improve the recovery speed of patients by studying the influence of different traction factors on the therapeutic effect. METHODS: Based on the thin layer CT data of the lumbar spine of a 16-year-old patient with scoliosis, Mimics21.0 was used to extract the 3D digital model, and Geomagic Wrap2021 was used to perform the smooth surface. After that, SolidWorks was used to manually construct the structures, such as the intervertebral disc, and Ansys17.0 was used to add constraints, ligaments, and other features. Three-factor ANOVA was carried out after an orthogonal experiment that considered traction mode, traction angle, and traction force was finished. RESULTS: ① A three-dimensional biomechanical model of lumbar scoliosis was created. ② The model's correctness was confirmed by comparing it to the corpse and other finite element models, as well as by verifying it under a range of working settings. ③ Traction force (P = 0.000), traction angle (P = 0.000), the interaction between traction force and traction angle (P = 0.000), and the interaction between traction mode and traction angle (P = 0.045) were all significant. ④ The interaction between traction force and traction angle has the most significant effect on Cobb, and traction with a certain angle is better than traditional axial traction. ⑤ Traction mode is not significant, but the interaction between traction mode and traction angle is significant. CONCLUSIONS: A certain angle of traction can aid in improving outcomes and the traction force can be suitably decreased in the clinical formulation of the traction plan. The uniformity of correcting effect is more favorable when higher fixation techniques like positive suspension or traction bed traction are used, as opposed to overhanging traction.

Corrigendum: Association between napping and type 2 diabetes mellitus.

[This corrects the article DOI: 10.3389/fendo.2024.1294638.].

Robot-assisted retractor in spine surgery: Preliminary evaluation of its feasibility and two operation mode in beagles.

OBJECTIVE: To assess the feasibility of the robot-assisted retractor. To compare the muscle injury of the two operation modes, intermittent retraction mode and continuous retraction mode in the robot-assisted retractor to find a better robot operation mode. METHODS: A new robot-assisted retractor experimental platform was developed. Three incisions were made on the backs of three beagles. The robot-assisted retractor was used to retract the muscle on both sides of the incisions in intermittent retraction mode and continuous retraction mode, and the operation of the robot system was observed. The muscle samples were stained with hematoxylin-eosin (HE) to observe the muscle injury. The difference between the muscle injuries of the two groups was statistically compared using paired t test. RESULTS: The robot-assisted retractor can precisely retract to the specified position without malfunction or dangerous actions. Histologic evaluation showed that fewer muscle injury was found in the intermittent retraction mode group of the robot-assisted retractor compared to the continuous retraction mode group. CONCLUSION: The robot-assisted retractor offers a certain degree of feasibility and safety. The robot-assisted retractor is able to effectively reduce muscle injury with the intermittent retraction mode.

Association between napping and type 2 diabetes mellitus.

As the incidence of type 2 diabetes mellitus (T2DM) is increasing rapidly and its consequences are severe, effective intervention and prevention, including sleep-related interventions, are urgently needed. As a component of sleep architecture, naps, alone or in combination with nocturnal sleep, may influence the onset and progression of T2DM. Overall, napping is associated with an increased risk of T2DM in women, especially in postmenopausal White women. Our study showed that napping >30 minutes (min) increased the risk of T2DM by 8-21%. In addition, non-optimal nighttime sleep increases T2DM risk, and this effect combines with the effect of napping. For nondiabetic patients, napping >30 min could increase the risks of high HbA1c levels and impaired fasting glucose (IFG), which would increase the risk of developing T2DM later on. For diabetic patients, prolonged napping may further impair glycemic control and increase the risk of developing diabetic complications (e.g., diabetic nephropathy) in the distant future. The following three mechanisms are suggested as interpretations for the association between napping and T2DM. First, napping >30 min increases the levels of important inflammatory factors, including interleukin 6 and C-reactive protein, elevating the risks of inflammation, associated adiposity and T2DM. Second, the interaction between postmenopausal hormonal changes and napping further increases insulin resistance. Third, prolonged napping may also affect melatonin secretion by interfering with nighttime sleep, leading to circadian rhythm disruption and further increasing the risk of T2DM. This review summarizes the existing evidence on the effect of napping on T2DM and provides detailed information for future T2DM intervention and prevention strategies that address napping.

Accuracy and clinical characteristics of robot-assisted cervical spine surgery: a systematic review and meta-analysis.

PURPOSE: To evaluate the accuracy and feasibility of robot-assisted cervical screw placement and factors that may affect the accuracy. METHODS: A comprehensive search was made on PubMed, Embase, Cochrane Library, Web of Science, CNKI, and Wanfang Med for the selection of potential eligible literature. The outcomes were evaluated in terms of the relative risk (RR) or standardized mean difference (MD) and corresponding 95% confidence interval (CI). Subgroup analyses of the accuracy of screw placement at different cervical segments and with different screw placement approaches were performed. A comparison was made between robotic navigation and conventional freehand cervical screw placement. RESULTS: Six comparative cohort studies and five case series studies with 337 patients and 1342 cervical screws were included in this study. The perfect accuracy was 86% (95% CI, 82-89%) and the clinically acceptable rate was 98% (95% CI, 95-99%) in robot-assisted cervical screw placement. The perfect accuracy of robot-assisted C1 lateral mass screw placement was the highest (96%), followed by C6-7 pedicle screw placement (93%) and C2 pedicle screw placement (86%), and the lowest was C3-5 pedicle screw placement (75%). The open approach had a higher perfect accuracy than the percutaneous/intermuscular approach (91% vs 83%). Compared with conventional freehand cervical screw placement, robot-assisted cervical screw placement had a higher accuracy, a lower incidence of perioperative complications, and less intraoperative blood loss. CONCLUSION: With good collaboration between the operator and the robot, robot-assisted cervical screw placement is accurate and feasible. Robot-assisted cervical screw placement has a promising prospect.

Identification and validation of ferroptosis-related lncRNA signature in intervertebral disc degeneration.

Low back pain influences people of every age and is one of the major contributors to the global cost of illness. Intervertebral disc degeneration (IVDD) is a major contributor to low back pain, but its pathogenesis is unknown. Recently, ferroptosis has been shown to have a substantial role in modulating IVDD progression. However, the function of ferroptosis-related long non-coding RNAs (lncRNAs) has rarely been reported in IVDD. Consequently, the research was conducted to explore the ferroptosis-related lncRNA signature in the IVDD occurrence and development. We analyzed two datasets (GSE167199 and GSE167931) archived in the NCBI Gene Expression Omnibus (GEO) public database. We screened differentially expressed genes (DEGs) and differentially expressed lncRNAs (DELncs) in these datasets using the limma package. Ferroptosis-related genes (FRGs) were derived from the FerrDb V2 website and the intersection of DEGs and FRGs was considered as differentially expressed ferroptosis-related genes (DFGs). These genes were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Correlations between DFGs and DELncs were shown by Pearson test to determine differential expression of ferroptosis-related lncRNAs. The Pearson test showed that CPEB1-HTR2A-AS1 and ACSL3-DNAJC27-AS1 pairs had correlation coefficients over 0.9. Twenty ferroptosis-related lncRNAs were identified and validated in IVDD. Eight of these lncRNAs were upregulated in IVDD nucleus pulposus cells, including HTR2A-AS1, MIF-AS1, SLC8A1-AS1, LINC00942, DUXAP8, LINC00161, LUCAT1 and LINC01615. Twelve were downregulated in IVDD nucleus pulposus cells, including DNAJC27-AS1, H19, LINC01588, LINC02015, FLNC1, CARMN, PRKG1-AS1, APCDD1L-DT, LINC00839, LINC00536, LINC00710 and LINC01535. Eighteen of the 20 lncRNAs (excluding H19 and LUCAT1) were identified as ferroptosis-related lncRNAs for the first time and verified in IVDD. We have identified a ferroptosis-related lncRNA signature involved in IVDD and revealed a close relationship between CPEB1 and HTR2A-AS1, and between ACSL3 and DNAJC27-AS1. Our findings indicate that ferroptosis-related lncRNAs are a new target set for the early detection and therapy of IVDD.

Trajectories tracking of maternal and neonatal health in eastern China from 2010 to 2021: A multicentre cross-sectional study.

Background: China's fertility policy has dramatically changed in the past decade with the successive promulgation of the partial two-child policy, universal two-child policy and three-child policy. The trajectories of maternal and neonatal health accompanied the changes in fertility policy are unknown. Methods: We obtained data of 280 203 deliveries with six common pregnancy complications and thirteen perinatal outcomes between 2010 and 2021 in eastern China. The average annual percent change (AAPC) was calculated to evaluated the temporal trajectories of obstetric characteristics and adverse outcomes during this period. Then, the autoregressive integrated moving average (ARIMA) models were constructed to project future trend of obstetric characteristics and outcomes until 2027. Results: The proportion of advanced maternal age (AMA), assisted reproduction technology (ART) treatment, gestational diabetes mellitus (GDM), anaemia, thrombocytopenia, thyroid dysfunction, oligohydramnios, placental abruption, small for gestational age (SGA) infants, and congenital malformation significantly increased from 2010 to 2021. However, the placenta previa, large for gestational age (LGA) infants and stillbirth significantly decreased during the same period. The AMA and ART treatment were identified as independent risk factors for the uptrends of pregnancy complications and adverse perinatal outcomes. The overall caesarean section rate remained above 40%. Importantly, among multiparas, a previous caesarean section was found to be associated with a significantly reduced risk of hypertensive disorders of pregnancy (HDP), premature rupture of membranes (PROM), placenta previa, placental abruption, perinatal asphyxia, LGA infants, stillbirths, and preterm births. In addition, the ARIMA time series models predicted increasing trends in the ART treatment, GDM, anaemia, thrombocytopenia, postpartum haemorrhage, congenital malformation, and caesarean section until 2027. Conversely, a decreasing trend was predicted for HDP, PROM, and placental abruption premature, LGA infants, SGA infants, perinatal asphyxia, and stillbirth. Conclusions: Maternal and neonatal adverse outcomes became more prevalent from 2010 to 2021 in China. Maternal age and ART treatment were independent risk factors for adverse obstetric outcomes. The findings offered comprehensive trajectories for monitoring pregnancy complications and perinatal outcomes in China, and provided robust intervention targets in obstetric safety. The development of early prediction models and the implementation of prevention efforts for adverse obstetric events are necessary to enhance obstetric safety.

The use of artificial intelligence in the treatment of rare diseases: A scoping review.

With the increasing application of artificial intelligence (AI) in medicine and healthcare, AI technologies have the potential to improve the diagnosis, treatment, and prognosis of rare diseases. Presently, existing research predominantly focuses on the areas of diagnosis and prognosis, with relatively fewer studies dedicated to the domain of treatment. The purpose of this review is to systematically analyze the existing literature on the application of AI in the treatment of rare diseases. We searched three databases for related studies, and established criteria for the selection of retrieved articles. From the 407 unique articles identified across the three databases, 13 articles from 8 countries were selected, which investigated 10 different rare diseases. The most frequently studied rare disease group was rare neurologic diseases (n = 5/13, 38.46%). Among the four identified therapeutic domains, 7 articles (53.85%) focused on drug research, with 5 specifically focused on drug discovery (drug repurposing, the discovery of drug targets and small-molecule inhibitors), 1 on pre-clinical studies (drug interactions), and 1 on clinical studies (information strength assessment of clinical parameters). Across the selected 13 articles, we identified total 32 different algorithms, with random forest (RF) being the most commonly used (n = 4/32, 12.50%). The predominant purpose of AI in the treatment of rare diseases in these articles was to enhance the performance of analytical tasks (53.33%). The most common data source was database data (35.29%), with 5 of these studies being in the field of drug research, utilizing classic databases such as RCSB, PDB and NCBI. Additionally, 47.37% of the articles highlighted the existing challenge of data scarcity or small sample sizes.