Reflectance spectroscopy analysis and lithium content estimation in lithium-rich rocks and stream sediments: Insights from Tuanjie Peak, Western Kunlun, China.

Lithium, a rare metal of strategic importance, has garnered heightened global attention. This investigation delves into the laboratory visible-near infrared and short-wavelength infrared reflectance (VNIR-SWIR 350 nm-2500 nm) spectral properties of lithium-rich rocks and stream sediments, aiming to elucidate their quantitative relationship with lithium concentration. This research seeks to pave new avenues and furnish innovative technical solutions for probing sedimentary lithium reserves. Conducted in the Tuanjie Peak region of Western Kunlun, Xinjiang, China, this study analyzed 614 stream sediments and 222 rock specimens. Initial steps included laboratory VNIR-SWIR spectral reflectance measurements and lithium quantification. Following the preprocessing of spectral data via Savitzky-Golay (SG) smoothing and continuum removal (CR), the absorption positions (Pos2210nm, Pos1910nm) and depths (Depth2210, Depth1910) in the rock spectra, as well as the Illite Spectral Maturity (ISM) of the rock samples, were extracted. Employing both the Successive Projections Algorithm (SPA) and genetic algorithm (GA), wavelengths indicative of lithium content were identified. Integrating the lithium-sensitive wavelengths identified by these feature selection methods, A quantitative predictive regression model for lithium content in rock and stream sediments was developed using partial least squares regression (PLSR), support vector regression (SVR), and convolutional neural network (CNN). Spectral analysis indicated that lithium is predominantly found in montmorillonite and illite, with its content positively correlating with the spectral maturity of illite and closely related to Al-OH absorption depth (Depth2210) and clay content. The SPA algorithm was more effective than GA in extracting lithium-sensitive bands. The optimal regression model for quantitative prediction of lithium content in rock samples was SG-SPA-CNN, with a correlation coefficient prediction (Rp) of 0.924 and root-mean-square error prediction (RMSEP) of 0.112. The optimal model for the prediction of lithium content in stream sediment was SG-SPA-CNN, with an Rp and RMSEP of 0.881 and 0.296, respectively. The higher prediction accuracy for lithium content in rocks compared to sediments indicates that rocks are a more suitable medium for predicting lithium content. Compared to the PLSR and SVR models, the CNN model performs better in both sample types. Despite the limitations, this study highlights the effectiveness of hyperspectral technology in exploring the potential of clay-type lithium resources in the Tuanjie Peak area, offering new perspectives and approaches for further exploration.

Autophagy-targeting modulation to promote peripheral nerve regeneration.

Nerve regeneration following traumatic peripheral nerve injuries and neuropathies is a complex process modulated by diverse factors and intricate molecular mechanisms. Past studies have focused on factors that stimulate axonal outgrowth and myelin regeneration. However, recent studies have highlighted the pivotal role of autophagy in peripheral nerve regeneration, particularly in the context of traumatic injuries. Consequently, autophagy-targeting modulation has emerged as a promising therapeutic approach to enhancing peripheral nerve regeneration. Our current understanding suggests that activating autophagy facilitates the rapid clearance of damaged axons and myelin sheaths, thereby enhancing neuronal survival and mitigating injury-induced oxidative stress and inflammation. These actions collectively contribute to creating a favorable microenvironment for structural and functional nerve regeneration. A range of autophagy-inducing drugs and interventions have demonstrated beneficial effects in alleviating peripheral neuropathy and promoting nerve regeneration in preclinical models of traumatic peripheral nerve injuries. This review delves into the regulation of autophagy in cell types involved in peripheral nerve regeneration, summarizing the potential drugs and interventions that can be harnessed to promote this process. We hope that our review will offer novel insights and perspectives on the exploitation of autophagy pathways in the treatment of peripheral nerve injuries and neuropathies.

Solvothermal synthesis of PdCu nanorings with high catalytic performance for alcohol electrooxidation.

Two-dimensional (2D) Pd-based nanostructures with a high active surface area and a large number of active sites are commonly used in alcohol oxidation research, whereas the less explored ring structure made of nanosheets with large pores is of interest. In this study, we detail the fabrication of PdCu nanorings (NRs) featuring hollow interiors and low coordinated sites using a straightforward solvothermal approach. Due to increased exposure of active sites and the synergistic effects of bimetallics, the PdCu NRs exhibited superior catalytic performance in both the ethanol oxidation reaction (EOR) and the ethylene glycol oxidation reaction (EGOR). The mass activities of PdCu NRs for EOR and EGOR were measured at 7.05 A/mg and 8.12 A/mg, respectively, surpassing those of commercial Pd/C. Furthermore, the PdCu NRs demonstrated enhanced catalytic stability, maintaining higher mass activity levels compared to other catalysts during stability testing. This research offers valuable insights for the development of efficient catalysts for alcohol oxidation.

Clinical efficacy of unilateral laminotomy for bilateral decompression in the treatment of adjacent segment disease after lumbar fusion.

Objective: To assess the clinical impact of unilateral laminotomy for bilateral decompression (ULBD) in managing patients with adjacent vertebrae following lumbar fusion. Methods: A retrospective analysis was conducted on 21 patients, with a mean age of 67.4 years, who underwent ULBD for adjacent vertebra disease at our department from January 2021 to November 2023. We reviewed demographic data, surgical techniques, imaging studies, and patient-reported outcomes. The study compared Visual Analog Scale (VAS) scores, Numeric Rating Scale (NRS) scores, Japanese Orthopaedic Association (JOA) scores, Short Form-36 (SF-36) scores, and imaging outcomes before surgery, immediately post-surgery, and at 1 month, 6 months, and 12 months post-surgery. Results: Evaluation of 21 patients with adjacent segment disease (ASD) (13 males, 8 females; mean age 67.42 years) was performed with follow-ups at various intervals post-surgery. Postoperative VAS, NRS, JOA, and SF-36 scores showed significant improvements compared to preoperative scores. Immediately after surgery, there were significant improvements in NRS score (2.76 ± 0.70 vs. 3.71 ± 0.85, P < 0.05) and JOA score (15.38 ± 1.02 vs. 9.29 ± 1.01, P < 0.05) compared to preoperative scores. Similarly, at 12 months post-surgery, significant improvements were observed in NRS score (1.52 ± 0.51 vs. 3.71 ± 0.85, P < 0.05) and JOA score (25.0 ± 1.10 vs. 9.29 ± 1.01, P < 0.05) compared to preoperative scores. The clinical satisfaction rate was 95.0% among all patients, with postoperative imaging examinations revealing a significant decompression effect. No complications were reported among the surgical patients. Conclusions: This study suggests that endoscopic ULBD can be a safe and effective technique for managing symptomatic ASD, providing satisfactory clinical outcomes for patients with ASD. Endoscopic ULBD may serve as an alternative treatment option for ASD with lumbar stenosis.

Multiple myeloma segmentation net (MMNet): an encoder-decoder-based deep multiscale feature fusion model for multiple myeloma segmentation in magnetic resonance imaging.

Background: Patients with multiple myeloma (MM), a malignant disease involving bone marrow plasma cells, shows significant susceptibility to bone degradation, impairing normal hematopoietic function. The accurate and effective segmentation of MM lesion areas is crucial for the early detection and diagnosis of myeloma. However, the presence of complex shape variations, boundary ambiguities, and multiscale lesion areas, ranging from punctate lesions to extensive bone damage, presents a formidable challenge in achieving precise segmentation. This study thus aimed to develop a more accurate and robust segmentation method for MM lesions by extracting rich multiscale features. Methods: In this paper, we propose a novel, multiscale feature fusion encoding-decoding model architecture specifically designed for MM segmentation. In the encoding stage, our proposed multiscale feature extraction module, dilated dense connected net (DCNet), is employed to systematically extract multiscale features, thereby augmenting the model's sensing field. In the decoding stage, we propose the CBAM-atrous spatial pyramid pooling (CASPP) module to enhance the extraction of multiscale features, enabling the model to dynamically prioritize both channel and spatial information. Subsequently, these features are concatenated with the final output feature map to optimize segmentation outcomes. At the feature fusion bottleneck layer, we incorporate the dynamic feature fusion (DyCat) module into the skip connection to dynamically adjust feature extraction parameters and fusion processes. Results: We assessed the efficacy of our approach using a proprietary dataset of MM, yielding notable advancements. Our dataset comprised 753 magnetic resonance imaging (MRI) two-dimensional (2D) slice images of the spinal regions from 45 patients with MM, along with their corresponding ground truth labels. These images were primarily obtained from three sequences: T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and short tau inversion recovery (STIR). Using image augmentation techniques, we expanded the dataset to 3,000 images, which were employed for both model training and prediction. Among these, 2,400 images were allocated for training purposes, while 600 images were reserved for validation and testing. Our method showed increase in the intersection over union (IoU) and Dice coefficients by 7.9 and 6.7 percentage points, respectively, as compared to the baseline model. Furthermore, we performed comparisons with alternative image segmentation methodologies, which confirmed the sophistication and efficacy of our proposed model. Conclusions: Our proposed multiple myeloma segmentation net (MMNet), can effectively extract multiscale features from images and enhance the correlation between channel and spatial information. Furthermore, a systematic evaluation of the proposed network architecture was conducted on a self-constructed, limited dataset. This endeavor holds promise for offering valuable insights into the development of algorithms for future clinical applications.

Risk assessment of human-to-human transmission of severe fever with thrombocytopenia syndrome virus based on 10-year clustered analysis.

Background: Severe fever with thrombocytopenia syndrome (SFTS) is an acute infectious disease, which was first reported in 2009 in China. Previous studies have rarely quantitatively assessed the transmission and fatal risk of SFTS clusters. Methods: Epidemiological information regarding SFTS clusters in Yantai city of Shandong province during 2013-2022 was obtained from the National Public Health Emergency Event Surveillance System (PHEESS) for Disease Control and Prevention information system. The secondary attack rate (SAR) and relative risk (RR) were used to assess the risk of human-to-human transmission of SFTS. Results: A total of 20 SFTS clusters involving 51 laboratory-confirmed patients were reported between 2013 and 2022 in Yantai city, Shandong province. Most of the clusters occurred from May to October, and the patients were mainly distributed in four counties. Contact with blood or other fluids [RR = 14.06, 95% confidence interval (CI) = 3.29-70.65, p < 0.001] and using no personal protection equipment (PPE) [11.63% (10/86) vs. 2.22% (2/90), RR = 5.74, 95% CI = 1.17-55.44, p = 0.013] were significantly related with an increased risk of SFTS virus (SFTSV) transmission. Conclusion: Our study may provide direct guidance on health education and behavioral interventions for the accompanying relatives and personnel of SFTS patients, both during their hospital stay and upon returning home after discharge.

Unveiling the Hidden Responses: Metagenomic Insights into Dwarf Bamboo (Fargesia denudata) Rhizosphere under Drought and Nitrogen Challenges.

Dwarf bamboo (Fargesia denudata) is a crucial food source for the giant pandas. With its shallow root system and rapid growth, dwarf bamboo is highly sensitive to drought stress and nitrogen deposition, both major concerns of global climate change affecting plant growth and rhizosphere environments. However, few reports address the response mechanisms of the dwarf bamboo rhizosphere environment to these two factors. Therefore, this study investigated the effects of drought stress and nitrogen deposition on the physicochemical properties and microbial community composition of the arrow bamboo rhizosphere soil, using metagenomic sequencing to analyze functional genes involved in carbon and nitrogen cycles. Both drought stress and nitrogen deposition significantly altered the soil nutrient content, but their combination had no significant impact on these indicators. Nitrogen deposition increased the relative abundance of the microbial functional gene nrfA, while decreasing the abundances of nirK, nosZ, norB, and nifH. Drought stress inhibited the functional genes of key microbial enzymes involved in starch and sucrose metabolism, but promoted those involved in galactose metabolism, inositol phosphate metabolism, and hemicellulose degradation. NO3--N showed the highest correlation with N-cycling functional genes (p < 0.01). Total C and total N had the greatest impact on the relative abundance of key enzyme functional genes involved in carbon degradation. This research provides theoretical and technical references for the sustainable management and conservation of dwarf bamboo forests in giant panda habitats under global climate change.

Ir Doping Modulates the Electronic Structure of Flower-Shaped Phosphides for Water Oxidation.

Electrolysis of water to produce hydrogen is an efficient, clean, and environmentally friendly hydrogen production method with unlimited development prospects. However, its overall efficiency is hampered by the slow oxygen evolution reaction (OER) with complex electron transfer processes. Therefore, designing efficient and low-cost OER catalysts is the key to solving this problem. In this paper, Ir-doped Co2P/Fe2P (abbreviated as Ir-CoFeP/NF) was grown on nickel foam through the strategies of low amount noble-metal doping and mild phosphating. Phosphide derived from a floral metal-organic framework (MOF) exhibits regular three-dimensional (3D) morphology and large active area, avoiding the stacking of active sites. The addition of Ir can effectively adjust the electronic structure, change the position of the d-band center, and increase active sites, thus enhancing the catalytic activity. Hence, the optimized catalyst exhibits unexpected electrocatalytic OER activity with an ideal overpotential of 213 mV at 10 mA cm-2, as well as a low Tafel slope of 40.63 mV dec-1. Coupling with Pt/C for overall water splitting (OWS), the entire device only needs an ultralow cell voltage of 1.50 V to achieve a current density of 10 mA cm-2. Besides, the OWS can be maintained for more than 70 h. This study demonstrates the superiority of Ir-doped phosphide in accelerating water oxidation.

Metabolic regulation of the immune system in health and diseases: mechanisms and interventions.

Metabolism, including glycolysis, oxidative phosphorylation, fatty acid oxidation, and other metabolic pathways, impacts the phenotypes and functions of immune cells. The metabolic regulation of the immune system is important in the pathogenesis and progression of numerous diseases, such as cancers, autoimmune diseases and metabolic diseases. The concept of immunometabolism was introduced over a decade ago to elucidate the intricate interplay between metabolism and immunity. The definition of immunometabolism has expanded from chronic low-grade inflammation in metabolic diseases to metabolic reprogramming of immune cells in various diseases. With immunometabolism being proposed and developed, the metabolic regulation of the immune system can be gradually summarized and becomes more and more clearer. In the context of many diseases including cancer, autoimmune diseases, metabolic diseases, and many other disease, metabolic reprogramming occurs in immune cells inducing proinflammatory or anti-inflammatory effects. The phenotypic and functional changes of immune cells caused by metabolic regulation further affect and development of diseases. Based on experimental results, targeting cellular metabolism of immune cells becomes a promising therapy. In this review, we focus on immune cells to introduce their metabolic pathways and metabolic reprogramming, and summarize how these metabolic pathways affect immune effects in the context of diseases. We thoroughly explore targets and treatments based on immunometabolism in existing studies. The challenges of translating experimental results into clinical applications in the field of immunometabolism are also summarized. We believe that a better understanding of immune regulation in health and diseases will improve the management of most diseases.

Comparative Study on the Performance of Gel Grease for High-End Equipment Based on the Synergistic Effect of Friction-Reducing Agents.

In the field of high-end equipment, the synergistic effect of friction-reducing agents plays an important role in the performance study of gel grease. Exploring its tribological and rheological properties can not only significantly reduce the coefficient of friction of mechanical components and enhance its viscosity at high temperatures but also effectively reduce energy consumption, thus improving the service life of high-end equipment. In this study, Schaeffler Load 460 gel grease was mixed with polysiloxane viscosity modifier (PV611) and molybdenum dialkyl dithiocarbamate (RFM3000) according to (3:1, 1:1, and 1:3), and its tribological properties and rheological properties were investigated by the MRS-10G friction and wear tester, MCR302 rotational rheometer, and crossover test. Comparative analyses of tribological and rheological properties were carried out. The results showed that the average coefficient of friction of Schaeffler Load 460 grease was reduced by 57.2%, 60%, and 71.9%, respectively, with the addition of two different ratios of friction reducers; the average diameter of abrasive spots was reduced by 44.5%, 55.4%, and 61.3%; and the shear stress and viscosity were increased by 117.94 Pa and 1295.02 mPa∙s, respectively, compared with that of the original grease, which is a good example for the lubrication of gel grease in the high-end equipment industry. This study provides a new direction and idea for the lubrication research of gel grease in the high-end equipment industry.

The deubiquitinating enzyme USP11 regulates breast cancer progression by stabilizing PGAM5.

Breast cancer is common worldwide. Phosphoglycerate mutase 5 (PGAM5) belongs to the phosphoglycerate mutase family and plays an important role in many cancers. However, research on its role in breast cancer remains unclear. The present investigation highlights the significant expression of PGAM5 in breast cancer and its essential role in cell proliferation, invasion, apoptosis and the regulation of ferroptosis in breast cancer cells. Overexpression or knockdown of ubiquitin-specific protease 11 (USP11) promotes or inhibits the growth and metastasis of breast cancer cells, respectively, in vitro and in vivo. Mechanistically, USP11 stabilizes PGAM5 via de-ubiquitination, protecting it from proteasome-mediated degradation. In addition, the USP11/PGAM5 complex promotes breast cancer progression by activating iron death-related proteins, indicating that the synergy between USP11 and PGAM5 may serve as a predictor of disease outcome and provide a new treatment strategy for breast cancer.

Investigating the shared genetic architecture between depression and subcortical volumes.

Depression, a widespread and highly heritable mental health condition, profoundly affects millions of individuals worldwide. Neuroimaging studies have consistently revealed volumetric abnormalities in subcortical structures associated with depression. However, the genetic underpinnings shared between depression and subcortical volumes remain inadequately understood. Here, we investigate the extent of polygenic overlap using the bivariate causal mixture model (MiXeR), leveraging summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 14 subcortical volumetric phenotypes (N = 33,224). Additionally, we identify shared genomic loci through conditional/conjunctional FDR analyses. MiXeR shows that subcortical volumetric traits share a substantial proportion of genetic variants with depression, with 44 distinct shared loci identified by subsequent conjunctional FDR analysis. These shared loci are predominantly located in intronic regions (58.7%) and non-coding RNA intronic regions (25.4%). The 269 protein-coding genes mapped by these shared loci exhibit specific developmental trajectories, with the expression level of 55 genes linked to both depression and subcortical volumes, and 30 genes linked to cognitive abilities and behavioral symptoms. These findings highlight a shared genetic architecture between depression and subcortical volumetric phenotypes, enriching our understanding of the neurobiological underpinnings of depression.

High-concentration hydrogen inhalation mitigates sepsis-associated encephalopathy in mice by improving mitochondrial dynamics.

BACKGROUND: Sepsis-associated encephalopathy (SAE) is a neuronal injury with poor prognosis. Mitochondrial dysfunction is critical in SAE development, and hydrogen gas (H2) has a protective effect on septic mice. This study aimed to investigate the effect of high concentration (67%) of H2 on SAE and whether it is related to mitochondrial biogenesis and mitochondrial dynamics. METHODS: A mouse sepsis model was induced by cecal ligation and puncture. The mice inhalated 67% H2 for 1 h at 1 and 6 h post-surgery, respectively. The 7-day survival rate was recorded. Cognitive function was assessed using the Y-maze test and Morris water maze test. Serum inflammatory factors, antioxidant enzymes, as well as mitochondrial function indexes including mitochondrial membrane potential (MMP) and ATP in the hippocampal tissue were evaluated 24 h after surgery. Mitochondrial dynamic proteins (DRP1 and MFN2) and biosynthetic proteins (PGC-1α, NRF2, and TFAM) in the hippocampal tissue were detected. Moreover, the morphology of mitochondria was observed by transmission electron microscopy. RESULTS: Inhalation of 67% H2 improved the 7-day survival rates and recognition memory function of septic mice, alleviated brain antioxidant enzyme activity (SOD and CAT), and reduced serum proinflammatory cytokine levels. H2 inhalation also enhanced the expression of MFN2 and mitochondrial biogenesis-related factors (PGC-1α, NRF2, and TFAM) and decreased the expression of fission protein (DRP1), leading to improvement in mitochondrial function, as evidenced by MMP and ATP levels. CONCLUSIONS: Inhalation of high concentration (67%) of H2 in septic mice improved the survival rate and reduced neuronal injury. Its mechanism might be mediated by enhancing mitochondrial biogenesis and mitochondrial dynamics.

Age affects the association of red blood cell indices with efficacy of remote ischemic conditioning in patients with acute moderate ischemic stroke.

We conducted a post hoc analysis of Remote Ischemic Conditioning for Acute Moderate Ischemic Stroke (RICAMIS) to investigate whether red blood cell (RBC) indices are associated with efficacy of remote ischemic conditioning (RIC), and whether the association is affected by age. In this post hoc analysis, patients with RBC indices at admission were enrolled. RBC indices including RBC count, hematocrit (HCT), mean corpuscular volume (MCV), hemoglobin (HB), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC) were analyzed. According to the median of these RBC indices, eligible patients were divided into high and low groups, which were further subdivided into RIC and control subgroups. Primary endpoint was excellent functional outcome defined as a modified Rankin Scale score of 0-1 at 90 days, which was used to evaluate RIC efficacy. RIC efficacy as well as effect of age on RIC efficacy were analyzed across the high and low groups of different RBC indices, and the interaction effects of RBC indices on RIC efficacy were evaluated. A total of 1640 patients were enrolled in the final analysis. In overall patients, no significant interaction effects of RIC intervention by all RBC indices were found, although there was a trend in interaction effect of RIC intervention by MCH (p = 0.116). However, we found an effect of age on the association of MCH with RIC efficacy. In patients over 60 years old, MCH significantly affected RIC efficacy (p = 0.006) and RIC significantly produced a higher proportion of primary outcome in high MCH (72.6% vs. 59.1%, P < 0.001) vs. low MCH group (61.2% vs. 62%, P = 0.829), which was not identified in patients under 60 years old. Furthermore, RIC efficacy decreased with increasing age in patients with low MCH with significant interaction effect (p = 0.012), while RIC efficacy increased with increasing age in patients with high MCH although no significant interaction (p = 0.126). No significant interaction effects of RIC intervention by RBC count, HCT, MCV, HB, and MCHC were found regardless of age. This secondary analysis of RICAMIS suggested that RIC exhibited more obvious benefit in AIS patients over 60 years old with high MCH compared with those with low MCH group, but RBC count, HCT, MCV, HB, and MCHC were not associated with the efficacy of RIC treatment regardless of age.

Advances in Novel Biomaterial-Based Strategies for Spinal Cord Injury Treatment.

Spinal cord injury (SCI) is a highly disabling neurological disorder. Its pathological process comprises an initial acute injury phase (primary injury) and a secondary injury phase (subsequent chronic injury). Although surgical, drug, and cell therapies have made some progress in treating SCI, there is no exact therapeutic strategy for treating SCI and promoting nerve regeneration due to the complexity of the pathological SCI process. The development of novel drug delivery systems to treat SCI is expected to significantly impact the individualized treatment of SCI due to its unique and excellent properties, such as active targeting and controlled release. In this review, we first describe the pathological progression of the SCI response, including primary and secondary injuries. Next, we provide a concise overview of newly developed nanoplatforms and their potential application in regulating and treating different pathological processes of SCI. Then, we introduce the existing potential problems and future clinical application perspectives of biomedical engineering-based therapies for SCI.

Healthy Sleep Pattern, Metabolic Diseases, and Risk of Stroke: The Kailuan Cohort Study.

Background: Sleep complaints were reported to be associated with stroke, however, the evidence on the association between healthy sleep pattern and stroke risk in Chinese is limited. Objective: The aim of this study was to investigate the association between healthy sleep pattern and stroke in Chinese, and the influence of metabolic diseases on the association. Methods: A total of 11,851 participants from the Kailuan study in China without stroke at baseline were included. We calculated a healthy sleep score according to four sleep factors, and defined the low-risk groups as follows: no insomnia, no excessive daytime sleepiness, no frequent snoring, and sleep 7-8h/d. Each low-risk sleep factor was assigned a score of 1. Cox proportional hazard models were used to assess the association between healthy sleep score and stroke. Mediation analysis was used to estimate the role of metabolic diseases (obesity, diabetes, and hypertension) in the healthy sleep score-stroke association. Results: During a mean follow-up period of 7.7 years, 504 cases of stroke were identified. A higher healthy sleep score was associated with a lower risk of stroke in a dose-response manner (P-trend=0.03). The adjusted hazard ratio (HR) for participants with a healthy sleep score of 4 versus ≤2 was 0.75 (95% confidence interval [CI]: 0.56, 0.96). In addition, obesity, diabetes, and hypertension collectively explained 21.9% (95% CI: 17.2, 26.5) of the association between healthy sleep score and stroke. Conclusion: Adherence to healthy sleep pattern was associated with a lower risk of stroke, and the favorable association was partially mediated by metabolic diseases.

Unraveling multi-scale neuroimaging biomarkers and molecular foundations for schizophrenia: A combined multivariate pattern analysis and transcriptome-neuroimaging association study.

AIMS: Schizophrenia is characterized by alterations in resting-state spontaneous brain activity; however, it remains uncertain whether variations at diverse spatial scales are capable of effectively distinguishing patients from healthy controls. Additionally, the genetic underpinnings of these alterations remain poorly elucidated. We aimed to address these questions in this study to gain better understanding of brain alterations and their underlying genetic factors in schizophrenia. METHODS: A cohort of 103 individuals with diagnosed schizophrenia and 110 healthy controls underwent resting-state functional MRI scans. Spontaneous brain activity was assessed using the regional homogeneity (ReHo) metric at four spatial scales: voxel-level (Scale 1) and regional-level (Scales 2-4: 272, 53, 17 regions, respectively). For each spatial scale, multivariate pattern analysis was performed to classify schizophrenia patients from healthy controls, and a transcriptome-neuroimaging association analysis was performed to establish connections between gene expression data and ReHo alterations in schizophrenia. RESULTS: The ReHo metrics at all spatial scales effectively discriminated schizophrenia from healthy controls. Scale 2 showed the highest classification accuracy at 84.6%, followed by Scale 1 (83.1%) and Scale 3 (78.5%), while Scale 4 exhibited the lowest accuracy (74.2%). Furthermore, the transcriptome-neuroimaging association analysis showed that there were not only shared but also unique enriched biological processes across the four spatial scales. These related biological processes were mainly linked to immune responses, inflammation, synaptic signaling, ion channels, cellular development, myelination, and transporter activity. CONCLUSIONS: This study highlights the potential of multi-scale ReHo as a valuable neuroimaging biomarker in the diagnosis of schizophrenia. By elucidating the complex molecular basis underlying the ReHo alterations of this disorder, this study not only enhances our understanding of its pathophysiology, but also pave the way for future advancements in genetic diagnosis and treatment of schizophrenia.

Alginate oligosaccharides exert protective effects on hydrogen peroxide-induced senescence in H9C2 cardiomyocytes by regulating the redox state of cells.

Aging is a known independent risk factor for several cardiovascular diseases. Here, we evaluated potential effects and possible mechanisms through which alginate oligosaccharides (AOS) affect hydrogen peroxide (H2O2)-induced senescence in H9C2 cardiomyocytes. A series of AOS molecules, including oligoM, oligoG, M-5, and G-5, were investigated. AOS significantly decreased SA-ß-gal and DAPI-stained positive cells, downregulated p53 and p21 (aging-related markers) expression, and eventually protected H9C2 cells from H2O2-induced senescence. AOS decreased reactive oxygen species and malondialdehyde production, recovered mitochondrial function, and alleviated the oxidative stress state by regulating PGC-1α and NADPH oxidase subunit expression. Furthermore, AOS treatment restored the expression of antioxidant enzymes in senescent H9C2 cells. Thus, our results show in vitro evidence that AOS alleviate senescence in H9C2 cells by regulating the redox state; thus, AOS may be an effective therapeutic agent that could protect against cardiomyocyte senescence.

Decline in carbon emission intensity of global agriculture has stagnated recently.

Using global data for around 180 countries and territories and 170 food/feed types primarily derived from FAOSTAT, we have systematically analyzed the changes in greenhouse gas (GHG) emission intensity (GHGi) (kg CO2eq per kg protein production) over the past six decades. We found that, with large spatial heterogeneity, emission intensity decreased by nearly two-thirds from 1961 to 2019, predominantly in the earlier years due to agronomic improvement in productivity. However, in the most recent decade, emission intensity has become stagnant, and in a few countries even showed an increase, due to the rapid increase in livestock production and land use changes. The trade of final produced protein between countries has potentially reduced the global GHGi, especially for countries that are net importers with high GHGi, such as many in Africa and South Asia. Overall, a continuous decline of emission intensity in the future relies on countries with higher emission intensity to increase agricultural productivity and minimize land use changes. Countries with lower emission intensity should reduce livestock production and increase the free trade of agricultural products and improve the trade optimality.