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Abstract Background Compound inheritance of TBX6 accounts for approximately 10% of sporadic congenital scoliosis (CS) cases. Such cases are called TBX6-associated congenital scoliosis (TACS). TACS has been reported to have certain common clinical phenotypes. However, whether the surgical outcomes of TACS patients differ from those of other CS patients remains unclear. Methods We retrospectively searched for patients who were diagnosed with scoliosis. TACS was identified in genetic testing for CS. After propensity score matching, patients with TACS were matched with patients with NTACS according to sex, age, main curvature, classification, deformity location, surgical methods, fusion segment and number of fusions. We evaluated and compared the coronal and sagittal radiographic parameters before surgery, immediately after surgery, and at the final follow-up. Surgical information, including surgical method, fusion segment, blood loss and complications, was also compared and analyzed. Results Twenty-eight TACS patients were propensity score matched with 28 NTACS patients among 473 CS patients. The preoperative matching parameters mentioned in the Methods section were similar between the TACS group and the NTACS group. In the TACS group, the correction rate of the cranial compensatory curve (64.9 ± 18.6% vs. 51.2 ± 24.0%, P = 0.014) and the correction rate of the caudal compensatory curve (77.4 ± 12.5% vs. 65.4 ± 22.7%, P = 0.011) were significantly greater than those in the NTACS group, and the loss rate of correction of the cranial compensatory curve in the TACS group (0.6 ± 19.2% vs. 26.7 ± 50.8, P = 0.002) was significantly lower than that in the NTACS group. The total complication rate (7.2% vs. 14.3%) and incidence of adding-on (0 vs. 7.1%) were lower in the TACS group than in the NTACS group. There were no significant differences between the two groups in terms of blood loss, revision rate, other correction parameters, balance parameters or incidence of complications. Conclusions TACS patients had better surgical outcomes than NTACS patients, which means that genetic diagnosis of the TBX6 gene mutation in CS before surgery can help predict better surgical outcomes. The specific genetic mechanism is not yet clear and may be related to the relatively normal development of paravertebral tissues in TACS patients. Further research is needed. Level of evidence Leve: III.

Abstract Flowering is a critical step in the plant life cycle. Angelica sinensis (Oliv.) Diels is a medicinal crop whose root is a well-known herbal medicine used in Asia. Early flowering causes changes in secondary metabolic flow and results in the loss of medicinal quality. Based on untargeted metabolomics studies, quinic acid was identified as a metabolite present in significantly higher concentrations during the early-flowering stage in A. sinensis leaves. This metabolite was subsequently investigated as a potential marker for early bolting in A. sinensis under field conditions. Moreover, quinic acid was found to accelerate flowering in the model plant Arabidopsis thaliana. Importantly, the flowering time was delayed in the quinate dehydrogenase At mutant, and this delay was reversed by quinic acid. Quinic acid upregulated the expression of the GA20OX and GID1 receptors and downregulated the expression of the inhibitor DELLA, thereby affecting the levels of FT and LFY and accelerating plant flowering. Quinic acid also significantly changed the expression of genes such as LOX, JAZ1, MYC2 and MYC3 in the jasmonic acid pathway. The trends of GID1, DELLA (GAI) and LOX2 protein expression were essentially consistent with those at the transcription level. These results suggest that quinic acid may promote plant flowering primarily by regulating the expression of genes and proteins in the gibberellin and jasmonic acid pathways.

Abstract Little is known about the role of the protective effects of granulocyte colony-stimulating factor (G-CSF) in patients after radiotherapy. The aim of the present study was to explore the prophylactic effects of long-acting granulocyte colony-stimulating factor (G-CSF) on febrile neutropenia (FN) and myelosuppression in chemotherapy patients with gynecologic malignancies after pelvic radiotherapy. Patients voluntarily participated in a study group (long-acting G-CSF for all chemotherapy cycles) and a control group (short-acting G-CSF) after they were educated about G-CSF utilization. The incidences of FN and myelosuppression, as well as adverse events, were compared between the two groups. A regression model was used to determine the risk factors for FN and myelosuppression. From January 6, 2019, to August 22, 2019, 61 patients were included in the final analysis, with 286 chemotherapy cycles. There were 14 (23.0%) and 57 (77.0%) patients in the study and control groups, respectively. The study group had significantly fewer complete blood count tests, fewer outpatient clinic visits, fewer short-acting G-CSF doses, and lower incidences of FN and myelosuppression per chemotherapy cycle. According to the binary regression model, the use of long-acting G-CSF was the only factor associated with a decreased incidence of myelosuppression but not FN. The major adverse event related to G-CSF was mild bone pain. In conclusion, long-acting G-CSF may effectively reduce the incidence of FN and myelosuppression with mild adverse effects during chemotherapy after radiotherapy. Trial registration Registered at https://www.clinicaltrials.gov/ on January 4, 2019 (NCT03793205).

Abstract The most common method for visual object tracking involves feeding an image pair comprising a template image and search region into a tracker. The tracker uses a backbone to process the information in the image pair. In pure Transformer-based frameworks, redundant information in image pairs exists throughout the tracking process and the corresponding negative tokens consume the same computational resources as the positive tokens while degrading the performance of the tracker. Therefore, we propose to solve this problem using an adaptive dynamic sampling strategy in a pure Transformer-based tracker, known as ADSTrack. ADSTrack progressively reduces irrelevant, redundant negative tokens in the search region that are not related to the tracked objectand the effect of noise generated by these tokens. The adaptive dynamic sampling strategy enhances the performance of the tracker by scoring and adaptive sampling of important tokens, and the number of tokens sampled varies according to the input image. Moreover, the adaptive dynamic sampling strategy is a parameterless token sampling strategy that does not use additional parameters. We add several extra tokens as auxiliary tokens to the backbone to further optimize the feature map. We extensively evaluate ADSTrack, achieving satisfactory results for seven test sets, including UAV123 and LaSOT.

Abstract Background Maintaining iron homeostasis is crucial for preventing the development of colorectal cancer (CRC). However, Evidence regarding the correlation between serum iron status and CRC has been inconsistent. This population-based study aims to explore the potential association between serum iron status and CRC risk. Methods Using data from the National Health and Nutrition Examination Survey (NHANES) registry spanning from 2001 to 2020, a cross-sectional study involving 9504 participants was performed to assess the relationship between serum iron status and CRC risk. The study encompassed men and women of various racial backgrounds, aged 20 to 80, from across the United States. Participants’ characteristics were presented using mean or proportion. The possible risk factor for CRC was examined using both univariable and multivariable analysis. A logistic regression model was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of CRC in accordance with each quantile increment in serum iron item levels. Results After making full adjustment, our analysis did not reveal a statistically significant association between serum iron, ferritin, transferrin saturation (TSAT), total iron-binding capacity (TIBC) and the risk of CRC. While there was no statistically significant difference observed, an increasing ferritin concentration appeared to be associated with a decreased CRC risk when compared to the lowest quantile. Specifically, the ORs and 95% CIs for the second, third, and fourth quantiles (Q2, Q3, and Q4) versus the lowest quantile (Q1) were as follows: Q2 (vs. Q1) OR 0.403, 95% CI 0.063–2.568; Q3 (vs. Q1) OR 0.316, 95% CI 0.059–1.687; Q4 (vs. Q1) OR 0.250, 95% CI 0.050–1.258. However, this trend did not reach statistical significance (P for trend = 0.381). Conclusion Our analyze did not demonstrate a statistically significant correlation between serum iron status and the risk of CRC.

PURPOSE OF THE STUDY The purpose of this study was to minimize tourniquet-induced ischemia-reperfusion injury (IRI) in total knee arthroplasty (TKA) surgery using the remote ischemic preconditioning (RIPC) model, as well as to assess antioxidant balance with thioldisulfide homeostasis (TDH). The secondary goal is to evaluate the impact of RIPC on TKA clinical outcomes. MATERIAL AND METHODS Patients in the ASA I–III group who underwent elective TKA were enrolled in this prospective, randomized, double-blind clinical research. TDH parameters were measured individually in groups with (Group I) and without (Group K) RIPC at the following times: preoperative (T0), right before the pneumatic tourniquet was opened (T1), 1 (T2), 6 (T3), and 24 (T4) hours after it was opened. In addition, at 3-hour intervals, the postoperative pain level was assessed using a visual analog scale (VAS). RESULTS This study included 60 cases (Group K; n=30, Group I; n=30). Both groups had equal native thiol, total thiol, disulfide levels, disulfide/native thiol, disulfide/total thiol, and native thiol/total thiol ratios (p>0.05 for each). The change in native thiol, total thiol, and disulfide values at T0 and T4 periods, however, was not statistically significant for Group K (p=0.049, p=0.047, p=0.037, and p=0.217, p=0.191, p=0.220, respectively). At the 15th hour, VAS values in group I were considerably lower than in Group K (p=0.002). DISCUSSION This prospective, randomized, controlled trial examined how RIPC affected tourniquet-induced IRI-induced oxidative stress in TKA surgery. Lower native, total, and disulfide levels at each postoperative time point were significant. RIPC may reduce tourniquet-induced IRI-induced oxidative stress and TDH in TKA surgery. RIPC also reduced postoperative discomfort. CONCLUSIONS Our findings suggest that RIPC may protect against the oxidative stress caused by IRI during limb surgery with a tourniquet and improve postoperative clinical outcomes. [ABSTRACT FROM AUTHOR]

Abstract This paper proposes a control strategy for the variable boost characteristics of electronic hydraulic brake (EHB) systems based on the driving style in response to the nonlinear challenges faced by the EHB systems in intelligent driving under complex personalized requirements. Initially, the working principle of the active braking of the EHB-booster was analyzed, and equivalent dynamic models and Karnopp friction models were established. Subsequently, by identifying the displacement and velocity parameters of the brake pedal, three types of variable boost characteristics-sporty, comfortable, and standard-were designed to satisfy the requirements of different driving styles. Then, to address the nonlinear disturbances caused by the variable boost characteristics, a variable-gain multiclosed-loop control strategy that considers nonlinear friction and inertia compensation was developed. Finally, the proposed control strategy was tuned and verified through the AMESim and Simulink cosimulation platform and vehicle tests. The results demonstrate that the strategy exhibits excellent control performance under various braking conditions that match driving styles, with steady-state control errors within 0.1 Mpa, providing a feasible solution for the complex nonlinear problems faced by personalized implementation in higher-order intelligent driving.

Abstract Background The effects of restrictive versus liberal transfusion strategies in critically ill patients with traumatic brain injury (TBI) and anemia, particularly in adult patients with moderate to severe TBI, remain inconclusive. Therefore, this systematic review and meta-analysis aim to evaluate the comparative impact of restrictive and liberal red blood cell transfusion strategies among critically ill adult patients with moderate to severe TBI. Methods We conducted a search of PubMed, EMBASE, and the Cochrane Central Register of Controlled Trials from their inception through October 20, 2024, to identify randomized controlled trials that compared restrictive (transfusions at a hemoglobin level of ≤ 7 g/dL) and liberal (transfusions at a hemoglobin level of ≤ 9–10 g/dL) transfusion strategies in adult patients with TBI. The primary outcome was mortality, with secondary outcomes including an unfavorable neurological outcome at six months, as determined by the Glasgow Outcome Scale (GOS

Abstract Colorectal cancer (CRC) lymph node metastasis (LNM) is a crucial factor affecting the prognosis and treatment outcomes of CRC patients. It has been confirmed that altered glycosylation is a key event during CRC lymphatic metastases. Sialylation is one of the most significant glycosylation alterations in tumors. However, the predictive role of sialylation and sialylated protein in CRC remains elusive, especially in CRC-LNM. In this study, we explored and identified 1102 sialylated glycoproteins in CRC-LNM using metabolic labeling strategy and proteomics analysis. Combined with comprehensive analysis with bioinformatics and machine learning algorithms, we screened 25 prognostic sialylation-related genes (SRGs) to construct a new molecular phenotype (LRSRGs-Phenotype) and a prognostic SRG signature (LRSRGs-related Gene Signature) in CRC. Then, we further confirmed that patients in different phenotypes had different prognosis, molecular biological characteristics, immune cell infiltration and could be closely linked to three previously reported immune phenotypes: immune-excluded (Phenotype A), immune-desert (Phenotype B), and immune-inflamed (Phenotype C). Besides, we evaluated and validated the LRSRGs-related gene (ACADM, EHD4, FLOT1, GPC1, GSR, LRRC8A, NGFR, SDHB, and SEC61G) signature and found the risk score was an independent risk factor for CRC prognosis. CRC patients in different risk groups had different somatic mutation, tumor microenvironment and immunotherapy response. Finally, we also identified the potential therapeutic agents for CRC patients in different risk groups. In conclusion, we explored the key sialylated glycoproteins, which may play a key role in tumor LNM and clinical outcomes. And constructed the LRSRGs-phenotype and signature with prognostic and therapeutic predictive value in CRC, hoping to provide reliable scientific basis for future treatments in CRC patients.

Abstract The heterogeneity of Parkinson’s disease (PD) has been recognized in clinical, with patients categorized into distinct subsets based on motor phenotype, such as tremor-dominant PD (TD), postural instability and gait difficulty-dominant PD (PIGD) and mixed PD (Mix). Despite this categorization, the underlying mechanisms of this heterogeneity remain poorly understood, and there is no personalized effective treatment for each PD subtype. To address this, a rat model for PD subtypes was established by unilateral stereotaxic injection of 6-OHDA, followed by cluster analysis of behavioral data. The serum neurofilament light chain (NfL) and uric acid (UA) levels as well as alterations in brain autonomic activity in rats were consistent with clinical patients, and metabolomics results showed that more than 70% of the metabolites in the serum of different subtypes of PD rats and clinical patients appeared to be consistently altered. Further transcriptomic analysis by RNA-seq has elucidated that the development of PD subtypes is associated with altered gene expression in neurotransmitter, neuronal damage in the central or peripheral nervous system, and lipid metabolism. In addition, based on the subtype-specific differentially expressed genes, 25 potential drug candidates were identified. Notably, the Alox15 inhibitor baicalein showed a greater efficacy on Mix rats, highlighting the possibility of selecting targeted treatments for well-defined individuals.

Abstract Background Tobacco production faces ongoing challenges due to soil degradation, leading to a persistent decline in yield. Plant growth-promoting fungi (PGPF) have been recognized as an environmentally friendly agricultural strategy. However, many commercial PGPF products exhibit instability due to insufficient environmental compatibility. Results In this study, Penicillium sp. PQxj3 was isolated and assessed for its potential to enhance tobacco productivity under field conditions. The results demonstrated that Penicillium sp. PQxj3 treatment significantly promoted the tobacco growth and improved the crop yield. The height of tobacco in Penicillium sp. PQxj3 treatment group significantly increased by 50.19% and 24.05% compared with CK at exuberant and maturity period (P

Abstract Cryo-electron microscopy (cryo-EM) technique is widely used for protein structure determination. Current automatic cryo-EM protein complex modeling methods mostly rely on prior chain separation. However, chain separation without sequence guidance often suffers from errors caused by cross-chain interaction or noise densities, which would accumulate and mislead the subsequent steps. Here, we present EModelX, a fully automated cryo-EM protein complex structure modeling method, which achieves sequence-guiding modeling through cross-modal alignments between cryo-EM maps and protein sequences. EModelX first employs multi-task deep learning to predict Cα atoms, backbone atoms, and amino acid types from cryo-EM maps, which is subsequently used to sample Cα traces with amino acid profiles. The profiles are then aligned with protein sequences to obtain initial structural models, which yielded an average RMSD of 1.17 Å in our test set, approaching atomic-level precision in recovering PDB-deposited structures. After filling unmodeled gaps through sequence-guiding Cα threading, the final models achieved an average TM-score of 0.808, outperforming the state-of-the-art method. The further combination with AlphaFold can improve the average TM-score to 0.911. Analyzes conducted by comparing some EModelX-built models and PDB structures highlight its potential to improve PDB structures. EModelX is accessible at https://bio-web1.nscc-gz.cn/app/EModelX .

Abstract Evidence shows that inflammatory responses play an essential role in the development of brain metastases (BM). The goal of this meta-analysis was to critically evaluate the literature regarding the use of the neutrophil to lymphocyte ratio (NLR) to predict the prognosis of patients with BM to help clinicians institute early interventions and improve outcomes. We conducted systematic review and meta-analysis, utilizing data from prominent databases, including PubMed, Cochrane Library and China National Knowledge Infrastructure databases. Our inclusion criteria encompassed studies investigating the studies that assessed the association between NLR and overall survival (OS). We included 11 articles, with 2629 eligible patients, to evaluate the association between NLR and OS. High NLR was significantly associated with shorter OS, with a pooled hazard ratio (HR) of 1.82 (95% CI 1.57–2.11). Subgroup analysis revealed that this association was consistent across different regions, with HRs of 2.03 (95% CI 1.67–2.46) in Asian populations and 1.58 (95% CI 1.35–1.84) in non-Asian populations. Additionally, in a subgroup analysis based on NLR cut-off values, patients with NLR ≥ 3 had an HR of 1.69 (95% CI 1.46–1.96), while those with NLR

Purpose: To understand the broader genetic landscape of male breast cancer (MBC), focusing on the utility of genome sequencing (GS) beyond BRCA1/2 (HGNC: 1100, 1101) variants. Methods: Twenty-four patients with MBC underwent a multistep genetic analysis. Initial screening targeted BRCA1/2 variants followed by GS to identify pathogenic/likely pathogenic germline variants through a 3-tiered classification. Polygenic risk score analysis was further incorporated using a model for female breast cancer with 2666 noncancer controls. Exome sequencing was used to transition from germline to somatic investigations, assessing second-hit variant and mutational signatures. Results: The GS analysis unveiled previously unrecognized pathogenic/likely pathogenic germline variants in BARD1, ATR, BRIP1, and CHEK2 (HGNC: 952, 882, 20473, 16627) among 21 BRCA1/2-negative patients with MBC, elevating the diagnostic yield from 12.5% to 33.0% in all MBC. Elevated average polygenic risk score was noted compared with controls, with a significant correlation to early-onset MBC when combined with high-penetrance germline pathogenic variants (P = 1.10 × 10−4). Exome sequencing analysis further identified significant somatic oncogenic drivers and revealed a dominant mutational signature SBS3 across BRCA1/2-negative samples, reinforcing the contribution of omologous recombination deficiency underlying the MBC development. Conclusion: Our findings extended the MBC genetic spectrum beyond BRCA1/2 and highlighted the intricate interplay of monogenic and polygenic predispositions, presenting a comprehensive MBC genomic profile.

BackgroundAfter initial treatment, levothyroxine (LT4) administration is necessary for thyroid cancer patients to achieve target thyroid-stimulating hormone (TSH) levels. However, the clinical efficacy of weight-based LT4 dosing has been suboptimal, highlighting the need to identify factors influencing the attainment of desired TSH levels and guide personalized treatment.MethodsWe constructed a retrospective cohort comprising 215 patients diagnosed with thyroid cancer. The identification of factors influencing the attainment of expected TSH levels was accomplished through univariate and multivariate logistic regression analyses. Subsequently, we developed a nomogram based on these prognostic factors and performed internal validation using the bootstrap resampling method.ResultsUnivariate and multivariate logistic regression analyses were conducted to analyze the clinical and demographic parameters. A nomogram was constructed using bootstrap resampling to predict the risk of TSH suppression failure, which was validated. The nomogram demonstrated moderate discrimination in estimating the risk of TSH suppression failure, with a Hosmer-Lemeshow test p-value of 0.393 and a bootstrapped calibrated C-index of 0.757 (95% CI 0.687-0.814). The calibration curve indicated good consistency of the model, and decision curve analysis suggested that the nomogram had clinical utility.ConclusionGender, preoperative serum free thyroxine (FT4) levels, T stage, and body mass index exhibit independent associations with the expected level of TSH. The established nomogram effectively predicts the risk of TSH suppression failure. Further research is warranted to investigate how these factors can be utilized in developing a personalized LT4 dosage calculator.

Bone is one of the hardest tissues in the human body, but it can undergo microcracks under long-term and periodic mechanical loads. The Newton iterative method was used to calculate the steady state, and the effects of different inlet and outlet pressures, trabecular gap width and height, and microcrack’s depth and width on the fluid shear stress (FSS) were studied, and the gradient of FSS inside the microcrack was analyzed. The results show that the pressure difference and trabecular gap heigh are positively correlated with the FSS (the linear correlation coefficients R2 were 0.9768 and 0.96542, respectively). When the trabecular gap width was 100 μm, the peak of FSS decreased by 28.57% compared with 800 and 400 μm, and the gradient of FSS inside the microcrack was 0.1–0.4 Pa/mm. This study can help people more intuitively understand the internal fluid distribution of trabecular bone and provide a reliable theoretical basis for the subsequent construction of gradient FSS devices in vitro.

Abstract The blood–brain barrier is often altered in glioblastoma (GBM) creating a blood–brain–tumor barrier (BBTB) composed of pericytes. The BBTB affects chemotherapy efficacy. However, the expression signatures of BBTB‐associated pericytes remain unclear. We aimed to identify BBTB‐associated pericytes in single‐cell RNA sequencing data of GBM using pericyte markers, a normal brain pericyte expression signature, and functional enrichment. We identified parathyroid hormone receptor‐1 (PTH1R) as a potential marker of pericytes associated with BBTB function. These pericytes interact with other cells in GBM mainly through extracellular matrix–integrin signaling pathways. Compared with normal pericytes, pericytes in GBM exhibited upregulation of several ECM genes (including collagen IV and FN1), and high expression levels of these genes were associated with a poor prognosis. Cell line experiments showed that PTH1R knockdown in pericytes increased collagen IV and FN1 expression levels. In mice models, the expression levels of PTH1R, collagen IV, and FN1 were consistent with these trends. Evans Blue leakage and IgG detection in the brain tissue suggested a negative correlation between PTH1R expression levels and blood–brain barrier function. Further, a risk model based on differentially expressed genes in PTH1R+ pericytes had predictive value for GBM, as validated using independent and in‐house cohorts.

Sunlit and shaded components are commonly present in both airborne and satellite remote sensing images. In vegetated ecosystems, shaded component often result from sunlight being obstructed by topographic relief or canopy structures, and shaded component may impact plant growth, leaf photosynthesis, and ultimately carbon sequestration. To accurately estimate the fractional cover of the shaded and sunlit components, including both green and non-green vegetation within vegetated ecosystems, a novel method called the quasi-Hue-Saturation-Lightness (quasi-HSL) method is proposed in this study. Inspired by the RGB to HSL conversion, this method utilizes near-infrared, green, and red bands to compute hue (and normalized hue), saturation, and lightness. Subsequently, two indices, namely Hue-Lightness Index (HLI) and Saturation-Lightness Index (SLI), are introduced to construct a triangular space for estimating the fractional cover of the three components. Through unmanned aerial vehicle field experiments conducted in two forested areas, the accuracy of fractional cover estimation for three components reaches an R2 value of 0.50–0.67. Furthermore, this fractional cover estimation approach can be extended to a four-component estimation, including sunlit green vegetation, sunlit non-green vegetation, shaded green vegetation, and shaded non-green vegetation. With this detailed fractional cover estimation in vegetated area, the fractional vegetation coverage can be retrieved. Cross-validated with the fractional vegetation coverage retrieved by NDVI, the accuracy reaches R2 = 0.92. The advantages of the proposed method are (1) estimating fractional cover of shaded component without blue band, which is easily impacted by atmospheric conditions and sensor performance, and (2) differentiating the sunlit green and non-green vegetation components in the vegetated ecosystem.

This study is to investigate the therapeutical effect and mechanisms of human-derived adipose mesenchymal stem cells (ADSC) in relieving adriamycin (ADR)-induced nephropathy (AN). SD rats were separated into normal group, ADR group, ADR+Losartan group (20 mg/kg), and ADR + ADSC group. AN rats were induced by intravenous injection with adriamycin (8 mg/kg), and 4 d later, ADSC (2 × 105 cells/mouse) were administrated twice with 2 weeks interval time (i.v.). The rats were euthanized after the 6 weeks’ treatment. Biochemical indicators reflecting renal injury, such as blood urea nitrogen (BUN), neutrophil gelatinase alpha (NGAL), serum creatinine (Scr), inflammation, oxidative stress, and pro-fibrosis molecules, were evaluated. Results demonstrated that we obtained high qualified ADSCs for treatment determined by flow cytometry, and ADSCs treatment significantly ameliorated renal injuries in DN rats by decreasing BUN, Scr and NGAL in peripheral blood, as well as renal histopathological injuries, especially protecting the integrity of podocytes by immunofluorescence. Furthermore, ADSCs treatment also remarkably reduced the renal inflammation, oxidative stress, and fibrosis in DN rats. Preliminary mechanism study suggested that the ADSCs treatment significantly increased renal neovascularization via enhancing proangiogenic VEGF production. Pharmacodynamics study using in vivo imaging confirmed that ADSCs via intravenous injection could accumulate into the kidneys and be alive at least 2 weeks. In a conclusion, ADSC can significantly alleviate ADR-induced nephropathy, and mainly through reducing oxidative stress, inflammation and fibrosis, as well as enhancing VEGF production.

Background During the acute heart failure (AHF), acute kidney injury (AKI) is highly prevalent in critically ill patients. The occurrence of the latter condition increases the risk of mortality in patients with acute heart failure. The current research on the relationship between nutritional risk and the occurrence of acute kidney injury in patients with acute heart failure is very limited.Methods This retrospective cohort study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV, version 2.1) database. We included adult patients with AHF who were admitted to the intensive care unit in the study. Results: A total of 1310 critically ill patients with acute heart failure were included. The AUC of geriatric nutritional risk index (GNRI) (0.694) is slightly superior to that of controlling nutritional status (CONUT) (0.656) and prognostic nutritional index (PNI) (0.669). The Log-rank test revealed a higher risk of acute kidney injury in patients with high nutritional risk (p

Abstract Introduction Sepsis is a life-threatening condition that poses a globally high mortality rate. Identifying risk factors is crucial. Insulin resistance and the TYG index, associated with metabolic disorders, may play a role. This study explores their correlation with mortality in non-diabetic septic patients. Methods This retrospective cohort study used data from the MIMIC-IV (version 2.1) database, which includes over 50,000 ICU admissions from 2008 to 2019 at Beth Israel Deaconess Medical Center in Boston. We included adult patients with sepsis who were admitted to the intensive care unit in the study. The primary outcome was to evaluate the ability of TYG to predict death at 28-day of hospital admission in patients with sepsis. Results The study included 2213 patients with sepsis, among whom 549 (24.8%) died within 28 days of hospital admission. We observed a non-linear association between TYG and the risk of mortality. Compared to the reference group (lower TYG subgroup), the 28-day mortality increased in the higher TYG subgroup, with a fully adjusted hazard ratio of 2.68 (95% CI: 2.14 to 3.36). The area under the curve (AUC) for TYG was 67.7%, higher than for triglycerides alone (AUC = 64.1%), blood glucose (AUC = 62.4%), and GCS (AUC = 63.6%), and comparable to SOFA (AUC = 69.3%). The final subgroup analysis showed no significant interaction between TYG and each subgroup except for the COPD subgroup (interaction P-values: 0.076–0.548). Conclusion In our study, TYG can be used as an independent predictor for all-cause mortality due to sepsis within 28 days of hospitalization.

Abstract Chronic obstructive pulmonary disease(COPD) is a gradually worsening and fatal heterogeneous lung disease characterized by airflow limitation and increasingly decline in lung function. Currently, it is one of the leading causes of death worldwide. The consistent feature of COPD is airway inflammation. Several inflammatory factors are known to be involved in COPD pathogenesis; however, anti-inflammatory therapy is not the first-line treatment for COPD. Although bronchodilators, corticosteroids and roflumilast could improve airflow and control symptoms, they could not reverse the disease. The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) signaling pathway plays an important novel role in the immune system and has been confirmed to be a key mediator of inflammation during infection, cellular stress, and tissue damage. Recent studies have emphasized that abnormal activation of cGAS-STING contributes to COPD, providing a direction for new treatments that we urgently need to develop. Here, we focused on the cGAS-STING pathway, providing insight into its molecular mechanism and summarizing the current knowledge on the role of the cGAS-STING pathway in COPD. Moreover, we explored antagonists of cGAS and STING to identify potential therapeutic strategies for COPD that target the cGAS-STING pathway.

This study aimed to assess the neurotoxic effects of the novel psychoactive substance 4-hydroxy-N-methyl-N-isopropyltryptamine (4-HO-MiPT) on brain. By employing zebrafish as a model organism, the study applied a multifaceted approach, including the recording and analysis of spontaneous behavioral activities, identification of brain metabolic products via ultra-high performance liquid chromatography coupled with quadrupole-Orbitrap high resolution mass spectrometry (UHPLC-Q/Orbitrap HRMS), and examination of changes in the transcriptional level of target genes. Following the injection of 4-HO-MiPT, zebrafish exhibites a pronounced reduction in movement speed and range, indicating a significant alteration in locomotor activity. The subsequent analysis of brain metabolic products finds 37 differential metabolites, including 7 elevated and 30 reduced ones, alongside notable alterations in 6 metabolic pathways. Moreover, the examination of transcriptional level of key genes in zebrafish brain underscores a discernible decrease in transcriptional level of genes associated with the nervous system, implying a substantial impact on neuronal function and synaptic transmission. The experimental findings substantiate the neurotoxic effects of 4-HO-MiPT on the zebrafish brain, shedding light on its deleterious repercussions on both the nervous and immune systems. Furthermore, the perturbations observed in metabolic processes and behavioral responses emphasize the profound impact of 4-HO-MiPT exposure on fundamental physiological functions. The identification of potential carcinogenicity associated with 4-HO-MiPT further underscores the urgent need for comprehensive risk assessment and regulatory scrutiny. This study represents a crucial step towards unraveling the intricate neurotoxic mechanisms underlying 4-HO-MiPT exposure. The research has far-reaching implications, not only in advancing our understanding of the adverse health effects associated with novel psychoactive substances, but also in guiding the development of targeted interventions and regulatory strategies aiming at safeguarding public health and well-being. Continued exploration into the long-term consequences of 4-HO-MiPT exposure, alongside comprehensive toxicological evaluations, holds promise in mitigating its potential hazards and ensuring the safety of individuals and communities exposed to this emerging threat.

Abstract Under anthropogenic warming, future changes to climate variability beyond specific modes such as the El Niño-Southern Oscillation (ENSO) have not been well-characterized. In the Community Earth System Model version 2 Large Ensemble (CESM2-LE) climate model, the future change to sea surface temperature (SST) variability (and correspondingly marine heatwave intensity) on monthly timescales and longer is spatially heterogeneous. We examined these projected changes (between 1960–2000 and 2060–2100) in the North Pacific using a local linear stochastic-deterministic model, which allowed us to quantify the effect of changes to three drivers on SST variability: ocean “memory” (the SST damping timescale), ENSO teleconnections, and stochastic noise forcing. The ocean memory declines in most areas, but lengthens in the central North Pacific. This change is primarily due to changes in air-sea feedbacks and ocean damping, with the shallowing mixed layer depth playing a secondary role. An eastward shift of the ENSO teleconnection pattern is primarily responsible for the pattern of SST variance change.

Abstract The aim of the study was to analyze the change trend of serum ALP over time and identify factors influencing its levels in peritoneal dialysis patients. Then to investigate the impact of serum ALP changes on calcium and phosphorus metabolism in single peritoneal dialysis center utilizing repeated measurement data. A retrospective cohort study was conducted with a total follow-up duration of 30 months. Serum ALP and other biomarkers, including calcium (Ca), phosphorus (P), 25(OH)D, intact parathyroid hormone (iPTH), albumin(ALB), and hemoglobin(Hb) were measured every 3 months. The generalized estimation equation (GEE) was utilized to analyze the change trend of serum ALP over time, and to assess whether there were differences in changes over time between different genders and different primary disease groups. Additionally, factors influencing serum ALP levels were analyzed, and the impact of serum ALP changes on calcium and phosphorus metabolism was also explored. A total of 34 patients were included in the study. Serum ALP and other indicators were measured repeatedly, with a maximum of 8 times and a minimum of 4 times. The median of serum ALP values at all measurement times for all selected patients was 89 U/L. The GEE analysis revealed that serum ALP gradually increased with time, and patients in diabetes group increased faster than those in non-diabetes group. A positive correlation was observed between serum ALP and dialysis duration, also between serum ALP and hemoglobin. However, variations in serum ALP did not significantly affect serum corrected calcium, phosphorus, or iPTH concentrations. The serum ALP levels of peritoneal dialysis patients increase gradually over time, and the concentrations are influenced by dialysis duration. The changes in serum ALP values do not have a significant impact on serum calcium, phosphorus, and iPTH levels.

Abstract Objective Endovascular therapy (EVT) is the most successful treatment for patients with acute ischemic stroke (AIS) due to large vessel occlusion (LVO) in the anterior circulation. However, futile recanalization (FR) seriously affects the prognosis of these patients. The aim of this study was to investigate predictors of FR after EVT in patients with AIS. Method Patients diagnosed with AIS due to anterior circulation LVO and receiving EVT between June 2020 and October 2022 were prospectively enrolled. FR after EVT was defined as a poor 90-day prognosis (modified Rankin Scale [mRS] score ≥ 3) despite achieving successful reperfusion (modified Thrombolysis in Cerebral Infarction [mTICI] classification of 2b-3). All included patients were categorized into control group (mRS score

Abstract Heat shuttling phenomenon is characterized by the presence of a non-zero heat flow between two bodies without net thermal bias on average. It was initially predicted in the context of nonlinear heat conduction within atomic lattices coupled to two time-oscillating thermostats. Recent theoretical works revealed an analog of this effect for heat exchanges mediated by thermal photons between two solids having a temperature dependent emissivity. In this paper, we present the experimental proof of this effect using systems made with composite materials based on phase change materials. By periodically modulating the temperature of one of two solids we report that the system akin to heat pumping with a controllable heat flow direction. Additionally, we demonstrate the effectiveness of a simultaneous modulation of two temperatures to control both the strength and direction of heat shuttling by exploiting the phase delay between these temperatures. These results show that this effect is promising for an active thermal management of solid-state technology, to cool down solids, to insulate them from their background or to amplify heat exchanges.

Vaccination is a widely adopted measure to prevent diseases, but the process of immunization can induce a substantial stress response. This study aimed to investigate the impact of a combined Mycoplasma bovis-BoHV-1 vaccine on the upper respiratory tract microbiome and BRD-associated pathogens in calves, as well as to evaluate the effects of potential interventions. The results showed that the percentage of Pasteurella species in the upper respiratory tract was elevated in calves after vaccination without intervention, and Pasteurella multocida was activated and proliferated. Interestingly, none of the three interventions (Sodium selenite-vitamin E, Astragalus polysaccharide and Ceftiofur sodium) affected antibody production after immunization. The administration of sodium selenite-vitamin E and astragalus polysaccharide reduced serum levels of cortisol and malondialdehyde, increased glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD), and alleviated the proliferation of Pasteurella multocida. Furthermore, the use of ceftiofur sodium almost completely inhibited the proliferation of Pasteurella multocida induced by immune stress. These findings provide a reference for mitigating the negative impacts associated with vaccination and highlight the potential benefits of using targeted nutritional and antimicrobial interventions to optimize immune responses and maintain a stable respiratory microbiome in calves.

Accurately estimating fractional cover of vegetated ecosystems over large areas is essential for many scientific studies, including climate change, land cover and land use, etc. Taking both accuracy and large spatial coverage into account, different methods have been proposed, such as upscaling from high to low spatial resolution remote sensing images, and harmonized data from varied sources. In this work, a new method, called centroid-based endmember optimization (CEO), is proposed to assist endmember selection for fractional cover estimation using the triangular space method. The basic idea is to retrieve endmembers from a triangular space built on a fine spatial resolution image, then correct and apply them to a coarse spatial resolution image. The method is discussed and tested using Sentinel-2 MSI and Sentinel-3 OLCI images to estimate non-photosynthetic vegetation (NPV), photosynthetic vegetation (PV), and bare soil (BS) fractional cover. With CEO, the fractional cover of an OLCI image can be estimated more accurately, reducing the work of mosaicking MSI images to acquire fractional cover of the same large area. The premises that CEO can be applied effectively are: (1) the acquisition dates of the MSI and OLCI images are close, ensuring a similar land cover; and (2) the spatial overlap between the MSI and OLCI images covers enough NPV, PV, and BS endmembers. When taken the average fractional cover retrieved from an MSI image as truth value, the CEO method reduced the estimation difference to 0.7%, compared to the differences of 8.1% and 6.6% retrieved using uncorrected or incompletely corrected triangular space method of an OLCI image, respectively. In addition to the average fractional cover estimation, the histogram of fractional cover distribution also improved obviously. When applying CEO to a full OLCI image, two full MSI images covering different locations were used for fractional cover validation, which supported a robust estimation result.

White feces syndrome (WFS) is a multifactorial shrimp disease that can cause severe financial losses in Litopenaeus vannamei aquaculture industry. The balance of the intestinal microbiota substantially maintains the health of the host, and dysbiosis is closely associated with diverse diseases. In the present study, intestinal samples were collected from the healthy and WFS-infected shrimp in the same cultured pond to compare the differences in intestinal histology and physiological indices as well as composition and function of intestinal microbiota. The result of intestinal histology revealed that the normal intestinal structure suffered severe damage in WFS-infected shrimp. The expression of antioxidant and immune-related genes like autophagy proteins, antimicrobial peptides were significantly decreased in WFS-infected shrimp. Through the sequencing analysis of the 16S rRNA genes, it was observed that the composition and function of intestinal microbiota had undergone an enormous alteration in WFS-infected shrimp. At phylum level, the abundance of major phylum including Cyanobacteria, Chloroflexi, Patescibacteria and Desulfobacterota were significantly increased, whereas phyla Bacteroidota and Verrucomicrobiota were decreased in WFS-infected shrimp. At the genus level, Cyanobium PCC-6307 and PeM15 were overrepresented in WFS-infected shrimp, and Cyanobium PCC-6307 was a potentially toxic cyanobacteria that could produce cyanotoxins. Functional prediction of intestinal microbiota also revealed that nutrition-related pathways were generally decreased, but disease-related pathways were increased in WFS-infected shrimp. These results illustrated that WFS of Litopenaeus vannamei was closely associated with the composition disorders of intestinal microbiota and hypoimmunity. Additionally, the identified bacterial genus Cyanobium PCC-6307 can be a signature to evaluate the occurrence probability of WFS in shrimp ponds and provide theorical basis for optimal treatments and control methods.

In recent years, overwhelming evidence has emphasized the crucial role of inflammation in the pathogenesis of PD. However, the exact mechanisms by which inflammation damages dopaminergic neurons in PD are still unclear. Therefore, we generated a MPTP-induced PD mouse model and performed spatial transcriptomic sequencing to provide more insight into the process of PD development at specific brain regions. Our results indicate that the pathological changes of PD are mainly manifested in the midbrain, especially in the substantia nigra region, with significant reductions in oligodendrocytes and Agt-labeled astrocytes and an increase in Gfap-labeled astrocytes. Macrophages displayed an increasing trend in the PD environment, indicating a pattern of immune modulation induced by PD. Moreover, pathway analysis revealed significant impairments in ion migration ability, abnormal Ca2+ channels, cAMP signaling, and synaptic damage in PD. Significant downregulation of Mt1 and Mt2 and upregulation of Atp1b2, Gpi1, and Cox6a1 in PD further underscored the occurrence of intense inflammation and immune alterations. On the basis of these findings, we have validated the significant accumulation of Ca2+ in the midbrain tissue in the PD environment by measuring its content. Additionally, we have demonstrated a close association between the reduction of dopaminergic neurons, represented by the midbrain region, and ferroptosis by evaluating the iron content, malondialdehyde (MDA) levels, and the protein expression of GPX4 and TH in the tissue. We propose the hypothesis that PD-related inflammation and immune changes can induce neuronal and oligodendrocyte damage through the induction of ferroptosis, thereby further accelerating the progression of PD.

ABSTRACT Classical swine fever virus (CSFV), an obligate intracellular pathogen, hijacks cellular metabolism to evade immune surveillance and facilitate its replication. The precise mechanisms by which CSFV modulates immune metabolism remain largely unknown. Our study reveals that CSFV infection disrupts serine metabolism, which plays a crucial role in antiviral immunity. Notably, we discovered that CSFV infection leads to the deacetylation of PHGDH, a key enzyme in serine metabolism, resulting in autophagic degradation. This deacetylation impairs PHGDH’s enzymatic activity, reduces serine biosynthesis, weakens innate immunity, and promotes viral proliferation. Molecularly, CSFV infection induces the association of HDAC3 with PHGDH, leading to deacetylation at the K364 site. This modification attracts the E3 ubiquitin ligase RNF125, which facilitates the addition of K63-linked ubiquitin chains to PHGDH-K364R. Subsequently, PHGDH is targeted for lysosomal degradation by p62 and NDP52. Furthermore, the deacetylation of PHGDH disrupts its interaction with the NAD+ substrate, destabilizing the PHGDH-NAD complex, impeding the active site, and thereby inhibiting de novo serine synthesis. Additionally, our research indicates that deacetylated PHGDH suppresses the mitochondria-MAVS-IRF3 pathway through its regulatory effect on serine metabolism, leading to decreased IFN-β production and enhanced viral replication. Overall, our findings elucidate the complex interplay between CSFV and serine metabolism, revealing a novel aspect of viral immune evasion through the lens of immune metabolism.IMPORTANCEClassical swine fever (CSF) seriously restricts the healthy development of China’s aquaculture industry, and the unclear pathogenic mechanism and pathogenesis of classical swine fever virus (CSFV) are the main obstacle to CSF prevention, control, and purification. Therefore, it is of great significance to explore the molecular mechanism of CSFV and host interplay, to search for the key signaling pathways and target molecules in the host that regulate the replication of CSFV infection, and to elucidate the mechanism of action of host immune dysfunction and immune escape due to CSFV infection for the development of novel CSFV vaccines and drugs. This study reveals the mechanism of serine metabolizing enzyme post-translational modifications and antiviral signaling proteins in the replication of CSFV and enriches the knowledge of CSFV infection and immune metabolism.

BackgroundThe differentiation of hematopoietic cells is significantly affected by cell metabolic activity. However, despite increasing interest in this field, there has been no comprehensive investigation of the metabolic functions of human hematopoietic cells during specific phases of differentiation. Thus, this study was conducted to develop a method for comparing hematopoietic cell lineage differentiation based on the metabolic functions of the cell. The metabolic activity of human umbilical cord-derived hematopoietic cells was examined during various phases of differentiation, specifically, hematopoietic stem cells (HSCs), hematopoietic progenitor cells, and differentiated blood cells. This approach was used to develop comprehensive metabolic maps corresponding to the different stages.ResultsHSCs were found to have robust fatty acid (FA) synthesis, FA oxidation, pentose phosphate pathway (PPP) activity, and glucose uptake, shown by their significantly higher expression of ACAC, CPT1A, G6PD, and GLUT1 as compared to differentiated pluripotent progenitor cells, common myeloid progenitors, megakaryocyte erythroid progenitors, lympho-myeloid primed progenitors, and granulocyte-macrophage progenitor cell populations. In monocytic differentiation, higher levels of ACAC, ASS1, ATP5A, CPT1A, G6PD, GLUT1, IDH2, PRDX2, and HK1 protein expression were evident in classical and intermediate monocytes relative to non-classical monocytes, consistent with high anabolic and catabolic levels. Compared with myelocytes and mature cells, the meta-myelocyte and pro-myelocyte populations of granulocytes show significantly elevated levels of ACAC, ASS1, ATP5A, CPT1A, G6PD, IDH2, PRDX2, and HK. In contrast to naïve and regulatory B cells, pro-B cells had higher levels of oxidative phosphorylation, while regulatory B cells showed greater PPP activity, glucose uptake, and tricarboxylic acid cycle activity. The analyses of T cells also indicated significantly higher ACAC, ASS1, ATP5A, CPT1A, G6PD, GLUT1, IDH2, PRDX2, and HK1 expression levels in CD4+ populations compared with CD8+ populations.ConclusionsThe results provide comprehensive analytical methods and reference values for future systematic studies into the metabolic functions of various cord blood-derived hematopoietic cell populations in different pathological or physiological conditions. These findings could also contribute to research on the connection between cellular metabolism and cancer or aging.

IntroductionScoliosis is a pathological spine structure deformation, predominantly classified as “idiopathic” due to its unknown etiology. However, it has been suggested that scoliosis may be linked to polygenic backgrounds. It is crucial to identify potential Adolescent Idiopathic Scoliosis (AIS)-related genetic backgrounds before scoliosis onset.MethodsThe present study was designed to intelligently parse, decompose and predict AIS-related variants in ClinVar database. Possible AIS-related variant records downloaded from ClinVar were parsed for various labels, decomposed for Dinucleotide Compositional Representation (DCR) and other traits, screened for high-risk genes with statistical analysis, and then learned intelligently with deep learning to predict high-risk AIS genotypes.ResultsResults demonstrated that the present framework is composed of all technical sections of data parsing, scoliosis genotyping, genome encoding, machine learning (ML)/deep learning (DL) and scoliosis genotype predicting. 58,000 scoliosis-related records were automatically parsed and statistically analyzed for high-risk genes and genotypes, such as FBN1, LAMA2 and SPG11. All variant genes were decomposed for DCR and other traits. Unsupervised ML indicated marked inter-group separation and intra-group clustering of the DCR of FBN1, LAMA2 or SPG11 for the five types of variants (Pathogenic, Pathogeniclikely, Benign, Benignlikely and Uncertain). A FBN1 DCR-based Convolutional Neural Network (CNN) was trained for Pathogenic and Benign/ Benignlikely variants performed accurately on validation data and predicted 179 high-risk scoliosis variants. The trained predictor was interpretable for the similar distribution of variant types and variant locations within 2D structure units in the predicted 3D structure of FBN1.DiscussionIn summary, scoliosis risk is predictable by deep learning based on genomic decomposed features of DCR. DCR-based classifier has predicted more scoliosis risk FBN1 variants in ClinVar database. DCR-based models would be promising for genotype-to-phenotype prediction for more disease types.

When fetuses are exposed to abnormally high levels of glucocorticoids in utero, irreversible damage to neuronal synaptogenesis occurs, leading to long-term cognitive and emotional behavioral abnormalities after birth. In this study, we investigated how maternal exposure to a novel environmental pollutant—synthetic glucocorticoid dexamethasone—affects offspring cognitive and emotional behaviors enduringly. We noted that offspring subjected to maternal dexamethasone exposure (MDE) displayed cognitive and emotional neurobehavioral deficits beginning in infancy, and these impairments persisted into adulthood. The principal mechanism involves MDE-induced damage to hippocampal neuronal synapse formation in the offspring, primarily due to a cholesterol deficiency which destabilizes neuronal membranes, thereby affecting normal synapse formation and ultimately leading to cognitive and emotional deficiencies. Specifically, we demonstrated abnormal activation of glucocorticoid receptors in hippocampal astroglial cells of MDE offspring, which triggers changes in the miR-450a-3p/HAT1/ABCG1 signaling axis, causing impaired cholesterol efflux in astroglial cells and insufficient cholesterol supply to neurons, further impairing synaptogenesis. This research not only underscores the significant impact of prenatal environmental pollutants on long-term health outcomes in offspring but also broadens our understanding of how prenatal exposure to glucocorticoids affects brain development in the progeny, providing new insights for interventions in neurodevelopmental and psychiatric disorders of fetal origin.

The effective integration of ecosystem services (ESs) and urban growth simulation is crucial for spatial planning decisions that support sustainable and high-quality development. Interactions (i.e., trade-offs, synergies, and irrelevance) generally exist among ESs, however, few studies have been done on the methodology for simulating urban growth that optimizes the synergistic effect of ESs. In this study, the Wuhan metropolitan area was taken as the research area. Four key ESs in 2000, 2010, and 2020: water yield (WY), carbon storage (CS), habitat quality (HQ), and soil retention (SR) were evaluated by using the InVEST model. Then the ordered weighted averaging (OWA) method was applied to optimally allocate ESs trade-offs and identify ecological priority protection areas (EPPAs). Finally, the PLUS model was used to simulate urban growth scenarios under different levels of ESs protection constraints and propose spatial planning strategies. The results revealed the following. (1) From 2000 to 2020, the three ESs (i.e., WY, CS, and HQ) exhibited the spatial distribution pattern with high in the east and low in the west, and higher in the woodland than in built-up areas, except SR, which remained at a weak level throughout the region. (2) During the 20 years, SR and the other three ESs, HQ and CS showed a synergistic relationship; WY exhibited a very weak trade-off with HQ; and WY and CS changed from a very weak trade-off to a weak synergy. (3) Seven ecosystem service patterns (ESPs) were generated, and ESP 5 was compared as the ideal option. The weights of SR, WY, CS, and HQ in this pattern were 0.063, 0.187, 0.313, and 0.437, respectively. (4) By 2030, the built-up areas will exhibit edge expansion and interconnection development trends, with the high-constraint ecological protection scenario as the most compact mode, and the spatial structure of “two districts, one axis, four cities as one” is consistent with the development tendency. Our findings can help to enrich the method of urban growth management oriented by ecological protection, and provide a scientific basis for ecological environment restoration and land use spatial planning practices.

In recent years, China has gradually begun restoring native salt marsh vegetation such as Suaeda salsa (S. salsa) in coastal wetlands that were damaged by the long-term invasion of Spartina alterniflora. Chlorophyll content (Cab), an important indicator of vegetation health, necessitates extensive and long-term monitoring using Sentinel-2. However, due to the influence of betacyanin (Beta), S. salsa exhibits different phenotypes (red and green) under various stress conditions, making remote sensing mechanism studies of this unique vegetation more challenging. In particular, satellite multispectral images are significantly affected by soil background in mixed pixels, making it imperative to mitigate this influence. This study explores the applicability of a recently proposed spectral separation of soil and vegetation (3SV) in Sentinel-2 multispectral and S. salsa vegetation from a remote sensing mechanism perspective, and further improves it. Additionally, a comparative analysis was conducted on the effectiveness of combining 3SV with several mainstream chlorophyll-sensitive indices. The advantages of machine learning algorithms were leveraged to develop a high-precision hybrid semi-empirical model for estimating Cab in different S. salsa phenotypes. The research findings indicate that: (1) The 3SV algorithm, adjusted with slope compensation and B2 and B4 bands, is applicable to green S. salsa scenarios. For red S. salsa scenarios, further adjustment using B2 and B3 bands and coverage fraction is required. (2) The MTCI, MRENDVI, MND, and MNDRE indices combined best with the modified 3SV, significantly reducing the RMSE of the semi-empirical models, especially under wet soil conditions with soil fraction fsoil

Novel Psychoactive Substances (NPS) derived from tryptamines has been detected in aquatic environments, leading to environmental toxicology concerns. However, the specific toxicological mechanism, underlying these NPS, remains unclear. In our previous work, we used 5-Methoxy-N-isopropyl-N-methyltryptamine (5-MeO-MiPT) as the representative drug for NPS, and found that, 5-MeO-MiPT led to obvious behavioral inhibition and oxidative stress responses in zebrafishes model. In this study, Zebrafish were injected with varying concentrations of 5-MeO-MiPT for 30 days. RNA-seq, qPCR, metabolomics, and histopathological analyses were conducted to assess gene expression and tissue integrity. This study confirms that 5-MeO-MiPT substantially influences the transcription and expression of 13 selected genes, including ucp1, pet100, grik3, and grik4, mediated by the Gαq/11-PLCβ signaling pathway. We elucidate the molecular mechanism that 5-MeO-MiPT can inhibit DAG-Ca2+/Pkc/Erk, Pkc/Pla2/PLCs and Ca2+/Camk Ⅱ/NMDA, while enhance Ca2+/Creb. Those secondary signaling pathways may be the mechanisms mediating 5-MeO-MiPT inhibiting normal behavior in zebrafish. These findings offer novel insights into the toxicological effects and addiction mechanisms of 5-MeO-MiPT. Moreover, it presents promising avenues for investigating other tryptamine-based NPS and offers a new direction for diagnosing and treating liver-brain pathway-related diseases.

Background Bone fractures are a common medical issue worldwide, causing a serious economic burden on society. In recent years, the application of artificial intelligence (AI) in the field of fracture has developed rapidly, especially in fracture diagnosis, where AI has shown significant capabilities comparable to those of professional orthopedic surgeons. This study aimed to review the development process and applications of AI in the field of fracture using bibliometric analysis, while analyzing the research hotspots and future trends in the field. Materials and methods Studies on AI and fracture were retrieved from the Web of Science Core Collections since 1990, a retrospective bibliometric and visualized study of the filtered data was conducted through CiteSpace and Bibliometrix R package. Results A total of 1063 publications were included in the analysis, with the annual publication rapidly growing since 2017. China had the most publications, and the United States had the most citations. Technical University of Munich, Germany, had the most publications. Doornberg JN was the most productive author. Most research in this field was published in Scientific Reports . Doi K's 2007 review in Computerized Medical Imaging and Graphics was the most influential paper. Conclusion AI application in fracture has achieved outstanding results and will continue to progress. In this study, we used a bibliometric analysis to assist researchers in understanding the basic knowledge structure, research hotspots, and future trends in this field, to further promote the development of AI applications in fracture.

The Monoamine Oxidase-A (MAOA) EcoRV polymorphism (rs1137070) is a unique synonymous mutation (c.1409 T > C) within the MAOA gene, which plays a crucial role in Maoa gene expression and function. This study aimed to explore the relationship between the mouse Maoa rs1137070 genotype and differences in MAOA gene expression. Mice carrying the CC genotype of rs1137070 exhibited a significantly lower Maoa expression level, with an odds ratio of 2.44 compared to the T carriers. Moreover, the wild-type TT genotype of MAOA demonstrated elevated mRNA expression and a longer half-life. We also delved into the significant expression and structural disparities among genotypes. Furthermore, it was evident that different aspartic acid synonymous codons within Maoa influenced both MAOA expression and enzyme activity, highlighting the association between rs1137070 and MAOA. To substantiate these findings, a dual-luciferase reporter assay confirmed that GAC was more efficient than GAT binding. Conversely, the synonymous mutation altered Maoa gene expression in individual mice. An RNA pull-down assay suggested that this alteration could impact the interaction with RNA-binding proteins. In summary, our results illustrate that synonymous mutations can indeed regulate the downregulation of gene expression, leading to changes in MAOA function and their potential association with neurological-related diseases.

Background: Long non-coding RNAs (lncRNAs) are implicated in a variety of regulatory functions within tumors, yet their specific roles in glioma remain underexplored. Methods: We extracted glioma patient data from The Cancer Genome Atlas and UCSC Xena database for analysis using R, focusing on genomic characterization, biological enrichment, immune evaluation, and the development of a predictive model employing machine learning techniques. Additionally, we conducted cell culture and proliferation assays. Results: Our analysis revealed that the lncRNA SLC16A1-AS1 plays a pivotal role in glioma pathogenesis and prognosis. We observed that abnormal expression of SLC16A1-AS1 varied with tumor grade, IDH mutation status, and histological type, correlating with worse survival outcomes. Genomically, SLC16A1-AS1 was associated with Tumor Mutational Burden and other prognostic biomarkers. The expression of this lncRNA was also linked to the activation of critical biological pathways and appeared to modulate the immune microenvironment, enhancing the presence of immune cells and checkpoints, which may be predictive of immunotherapy outcomes. Our predictive model, constructed from genes associated with SLC16A1-AS1, accurately forecasted glioma prognosis, strongly correlating with survival and treatment responses. In vitro experiments further demonstrated that SLC16A1-AS1 significantly influences glioma cell proliferation, invasion, and migration, underscoring its role in tumor aggression and its potential as a therapeutic target. Conclusions: This study underscores the significant influence of SLC16A1-AS1 on glioma progression and prognosis, with its expression correlating with tumor traits and immune responses. The findings highlight the potential of targeting SLC16A1-AS1 in therapeutic strategies aimed at mitigating glioma aggressiveness.