Prognostic signature and immune efficacy of m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is the main type of primary liver cancer, and its related death ranks third worldwide. The curative methods and progress prediction markers of HCC are not sufficient enough. Nevertheless, little progress has been made in the signature of m1A-, m5C-, m6A-, m7G-, and DNA methylation of HCC. Results: We calibrated a risk gene signature model that can be used to categorize HCC patients based on univariate, multivariate, and LASSO Cox regression analysis. This gene signature classified the patients into high- and low-risk subgroups. Patients in the high-risk group showed significantly reduced overall survival (OS) compared with patients in the low-risk group. The gene set variation analysis (GSVA), immune infiltration, and immunotherapy response were analyzed. The results demonstrated that an immunosuppressive environment was exited and the high-risk group had higher sensitivity to 5-fluorouracil, cisplatin, sorafenib, tamoxifen, and epirubicin. These results indicated personalized therapy should be taken into consideration. Conclusions: Our findings enriched our understanding of the molecular heterogeneity, tumor microenvironment (TME), and drug susceptibility of HCC. m1A-, m5C-, m6A-, m7G-, and DNA methylation-related regulators may be promising biomarkers for future research.

Laser Interference Additive Manufacturing: Mask Bundle Shape Bionic Shark Skin Structure.

Here, we explored a new manufacturing strategy that uses the mask laser interference additive manufacturing (MLIAM) technique, which combines the respective strengths of laser interference lithography and mask lithography to efficiently fabricate across-scales three-dimensional bionic shark skin structures with superhydrophobicity and adhesive reduction. The phenomena and mechanisms of the MLIAM curing process were revealed and analyzed, showing the feasibility and flexibility. In terms of structural performance, the adhesive force on the surface can be tuned based on the growth direction of the bionic shark skin structures, where the maximum rate of the adhesive reduction reaches about 65%. Furthermore, the evolution of the directional diffusion for the water droplet, which is based on the change of the contact angle, was clearly observed, and the mechanism was also discussed by the models. Moreover, no-loss transportations were achieved successfully using the gradient adhesive force and superhydrophobicity on the surface by tuning the growth direction and modifying by fluorinated silane. Finally, this work gives a strategy for fabricating across-scale structures on micro- and nanometers, which have potential application in bioengineering, diversional targeting, and condenser surface.

Deep Learning Enhanced Label-Free Action Potential Detection Using Plasmonic-Based Electrochemical Impedance Microscopy.

Measuring neuronal electrical activity, such as action potential propagation in cells, requires the sensitive detection of the weak electrical signal with high spatial and temporal resolution. None of the existing tools can fulfill this need. Recently, plasmonic-based electrochemical impedance microscopy (P-EIM) was demonstrated for the label-free mapping of the ignition and propagation of action potentials in neuron cells with subcellular resolution. However, limited by the signal-to-noise ratio in the high-speed P-EIM video, action potential mapping was achieved by averaging 90 cycles of signals. Such extensive averaging is not desired and may not always be feasible due to factors such as neuronal desensitization. In this study, we utilized advanced signal processing techniques to detect action potentials in P-EIM extracted signals with fewer averaged cycles. Matched filtering successfully detected action potential signals with as few as averaging five cycles of signals. Long short-term memory (LSTM) recurrent neural network achieved the best performance and was able to detect single-cycle stimulated action potential successfully [satisfactory area under the receiver operating characteristic curve (AUC) equal to 0.855]. Therefore, we show that deep learning-based signal processing can dramatically improve the usability of P-EIM mapping of neuronal electrical signals.

Correlation of fluid-attenuated inversion recovery sequence vascular hyperintensity in magnetic resonance with collateral circulation and short-term clinical prognosis in acute ischemic stroke.

Background: Accurately assessing the prognosis of patient with large-scale cerebral infarction caused by acute middle cerebral artery (MCA) occlusion in the early stages of onset can help clinicians to actively and effectively intervene, thus reducing mortality and disability rates. This study set out to investigate the predictive value of fluid-attenuated inversion recovery vascular hyperintensity (FVH) on collateral circulation and clinical prognosis. Methods: The clinical data of 70 patients admitted to The First People's Hospital of Lianyungang from January 2018 to December 2021 with acute cerebral infarction due to occlusion of the proximal end of the M1 segment in the MCA were retrospectively collected. All patients had their first onset of disease and did not receive thrombolytic therapy at the time of onset. Subsequently, they underwent endovascular thrombectomy for treatment. The FVH and collateral vessel scores were derived according to patients' fluid-attenuated in version recovery (FLAIR) sequence and time-of-flight magnetic resonance angiography images. Based on the 90-day Modified Rankin Scale (mRS), patients were allocated to a good prognosis group (mRS ≤2) and a poor prognosis group (mRS =3-6). The correlation between the FVH and collateral vessel scores was assessed using the Spearman rank correlation test. Pearson correlation coefficient analysis was used to assess the correlation between FVH and the 90-day mRS together with the infarct size. Univariate analysis, multivariate binary logistic regression analysis, and receiver operating characteristic (ROC) curve analysis were adopted to identify those factors potentially. associated with the prognosis of patients with acute ischemic stroke (AIS). Results: Out of 70 patients with acute unilateral MCA occlusion (MCAO) who met the inclusion criteria, 62 showed positive FVH sign. These 62 patients were divided into a good prognosis group (n=32) and a poor prognosis group (n=30) based on the mRS score 90 days after discharge. The Spearman rank correlation test indicated that FVH was positively correlated with collateral vessel grade (Spearman rho =0.865; P<0.001); meanwhile, Pearson correlation coefficient analysis indicated that FVH score had moderate negative correlation with 90-day mRS score (r=-0.605; P<0.001). The results of multivariate binary logistic regression analysis indicated that collateral vessel grade and FVH score may be associated with the prognosis of patients with AIS, and the area under the curve (AUC) of FVH score was larger than collateral vessel grade (AUC =0.738). Conclusions: There was a positive correlation between FVH score and collateral vessel grade, and FVH score could indicate collateral circulation. FVH score was negatively correlated with 90-day mRS score and infarct volume and thus can predict clinical prognosis.

Metabolic features of adolescent major depressive disorder: A comparative study between treatment-resistant depression and first-episode drug-naive depression.

Major depressive disorder (MDD) is a psychiatric illness that can jeopardize the normal growth and development of adolescents. Approximately 40% of adolescent patients with MDD exhibit resistance to conventional antidepressants, leading to the development of Treatment-Resistant Depression (TRD). TRD is associated with severe impairments in social functioning and learning ability and an elevated risk of suicide, thereby imposing an additional societal burden. In this study, we conducted plasma metabolomic analysis on 53 adolescents diagnosed with first-episode drug-naïve MDD (FEDN-MDD), 53 adolescents with TRD, and 56 healthy controls (HCs) using hydrophilic interaction liquid chromatography-mass spectrometry (HILIC-MS) and reversed-phase liquid chromatography-mass spectrometry (RPLC-MS). We established a diagnostic model by identifying differentially expressed metabolites and applying cluster analysis, metabolic pathway analysis, and multivariate linear support vector machine (SVM) algorithms. Our findings suggest that adolescent TRD shares similarities with FEDN-MDD in five amino acid metabolic pathways and exhibits distinct metabolic characteristics, particularly tyrosine and glycerophospholipid metabolism. Furthermore, through multivariate receiver operating characteristic (ROC) analysis, we optimized the area under the curve (AUC) and achieved the highest predictive accuracy, obtaining an AUC of 0.903 when comparing FEDN-MDD patients with HCs and an AUC of 0.968 when comparing TRD patients with HCs. This study provides new evidence for the identification of adolescent TRD and sheds light on different pathophysiologies by delineating the distinct plasma metabolic profiles of adolescent TRD and FEDN-MDD.

Stability in change: building a stable ecological security pattern in Northeast China under climate and land use changes.

Climate change and land use change caused by human activities have a profound impact on ecological security. Simulating the spatio-temporal changes in ecosystem service value and ecological security patterns under different carbon emission scenarios in the future is of great significance for formulating sustainable development policies. This study quantified the four major ecosystem services (habitat quality, water retention, soil erosion, and carbon storage) in Northeast China (NC), identified ecological source areas, and constructed a stable ecological security pattern. The results show that the spatial patterns of soil erosion, carbon storage, water retention, and habitat quality, the four major ecosystem services in NC, are relatively stable in the next 30 years, and there is no significant difference from the current spatial pattern distribution. The SSP1-2.6 carbon emission scenario is a priority model for the development of NC in the next 30 years. In this carbon emission scenario, the NC has the largest ecological resources (191,177 km2) and the least comprehensive resistance value (850.006 × 10-4). At the same time, the relative resistance of the corridor in this scenario is the smallest, and the area of the mandatory reserve pinch points is the least. The ecological corridors in the SSP1-2.6 scenario form a network distribution among the ecological sources, connecting several large ecological sources as a whole. This study fills the knowledge gap in building a stable ecological security pattern in NC under the background of global change, and provides a scientific basis for the decision-making of regional ecological security and land resource management.

Optimizing Coreopsis tinctoria Flower Extraction and Inhibiting CML Activity: Box-Behnken Design.

BACKGROUND: Chronic myelogenous leukemia (CML) is an uncommon type of cancer of the bone marrow associated with high mortality. Although several effective therapies have been developed to reduce symptoms in patients with CML, many of these methods are associated with side effects. Coreopsis tinctoria Nutt. (C. tinctoria) is a natural medicinal material that possesses antioxidant and anticancer activities. Yet, its effect in treating leukemia has still not been fully explored. OBJECTIVE: To optimize the C. tinctoria flower extraction process and investigate whether these extracts can impair CML cell survival. METHODS: The extraction process of C. tinctoria was optimized by the Box-Behnken design response surface method. K562 cells were treated with different volumes (0, 10, 25, 50, and 100 µL) of C. tinctoria flower extracts. The effect of C. tinctoria extract on cell morphology and cell apoptosis was assessed by light microscopy, laser confocal microscopy, and flow cytometry. RESULTS: We established the following optimized C. tinctoria flower extraction conditions: temperature of 84.4 °C, extraction period of 10 mins, solid-liquid ratio of 1:65, and times 4. These conditions were applied for C. tinctoria flower extraction. Pre-incubation of extracts prepared under the aforementioned optimal conditions with K562 cells induced cell cytotoxicity and cell apoptosis. CONCLUSION: C. tinctoria flower extracts exert obvious anti-leukemia effects in vitro and may be a potential drug candidate for leukemia treatment.

Me-LLaMA: Foundation Large Language Models for Medical Applications.

Recent advancements in large language models (LLMs) such as ChatGPT and LLaMA have hinted at their potential to revolutionize medical applications, yet their application in clinical settings often reveals limitations due to a lack of specialized training on medical-specific data. In response to this challenge, this study introduces Me-LLaMA, a novel medical LLM family that includes foundation models - Me-LLaMA 13/70B, along with their chat-enhanced versions - Me-LLaMA 13/70B-chat, developed through continual pre-training and instruction tuning of LLaMA2 using large medical datasets. Our methodology leverages a comprehensive domain-specific data suite, including a large-scale, continual pre-training dataset with 129B tokens, an instruction tuning dataset with 214k samples, and a new medical evaluation benchmark (MIBE) across six critical medical tasks with 12 datasets. Our extensive evaluation using the MIBE shows that Me-LLaMA models achieve overall better performance than existing open-source medical LLMs in zero-shot, few-shot and supervised learning abilities. With task-specific instruction tuning, Me-LLaMA models outperform ChatGPT on 7 out of 8 datasets and GPT-4 on 5 out of 8 datasets. In addition, we investigated the catastrophic forgetting problem, and our results show that Me-LLaMA models outperform other open-source medical LLMs in mitigating this issue. Me-LLaMA is one of the largest open-source medical foundation LLMs that use both biomedical and clinical data. It exhibits superior performance across both general and medical tasks compared to other open-source medical LLMs, rendering it an attractive choice for medical AI applications. We release our models, datasets, and evaluation scripts at: https://github.com/BIDS-Xu-Lab/Me-LLaMA.

Research progress on the mechanism of acupuncture on type â ¡ diabetes mellitus. / é’ˆåˆºæ²»ç–—â ¡åž‹ç³–å°¿ç— æ•ˆåº”æœºåˆ¶ç ”ç©¶è¿›å±•.

Acupuncture is an effective measure for treating type 2 diabetes mellitus (T2DM). Many studies have shown that acupuncture can reduce blood glucose in patients with T2DM, but its mechanism is still unclear. This review summarized the mechanism of acupuncture on T2DM, the mechanisms of acupuncture in treating T2DM is related to improving insulin resistance, regulating inflammation, promoting insulin secretion, improving lipid metabolism disorders, resisting oxidative stress, improving obesity, controlling intestinal flora, and regulating the nervous system. At the same time, this review also points out the lack of current relevant research and the future research directions to provide a reference for further exploring the mechanism of acupuncture hypoglycemic action.

Regulatory mechanism of vulnerability disclosure behavior considering security crowd-testing: An evolutionary game analysis.

The security crowd-testing regulatory mechanism is a vital means to promote collaborative vulnerability disclosure. However, existing regulatory mechanisms have not considered multi-agent responsibility boundaries and stakeholders' conflicts of interest, leading to their dysfunction. Distinguishing from previous research on the motivations and constraints of ethical hacks' vulnerability disclosure behaviors from a legal perspective, this paper constructs an evolutionary game model of SRCs, security researchers, and the government from a managerial perspective to propose regulatory mechanisms promoting tripartite collaborative vulnerability disclosure. The results show that the higher the initial willingness of the three parties to choose the collaborative strategy, the faster the system evolves into a stable state. Regarding the government's incentive mechanism, establishing reward and punishment mechanisms based on effective thresholds is essential. However, it is worth noting that the government has an incentive to adopt such mechanisms only if it receives sufficient regulatory benefits. To further facilitate collaborative disclosure, Security Response Centers (SRC) should establish incentive mechanisms including punishment and trust mechanisms. Additionally, publicity and training mechanisms for security researchers should be introduced to reduce their revenue from illegal participation, which promotes the healthy development of security crowd-testing. These findings contribute to improving SRCs' service quality, guiding security researchers' legal participation, enhancing the government's regulatory effectiveness, and ultimately establishing a multi-party collaborative vulnerability disclosure system.

Predictors of Global Disparities in COVID-19 Vaccination Coverage - 219 Countries and Territories, December 2020-July 2022.

What is already known about this topic?: The significant disparities in global coronavirus disease 2019 (COVID-19) vaccine coverage hamper the pace of epidemic control. There is a need to better understand the factors contributing to disparities in COVID-19 vaccination rates across countries. What is added by this report?: This report revealed significant associations between vaccination coverage and various country-level indicators. Better pandemic preparedness, higher levels of trust, and a lower proportion of young population aged 0-14 were strongly correlated with higher COVID-19 vaccination coverage. What are the implications for public health practices?: Our findings emphasize the need for enhanced pandemic preparedness and governance, coupled with building trust in government and healthcare systems. It also needs to address the hesitancy of vaccinating children and adolescents aged 0-14 as the vaccination campaign progresses.

Inactivation of Myostatin Delays Senescence via TREX1-SASP in Bovine Skeletal Muscle Cells.

The myostatin (MSTN) gene also regulates the developmental balance of skeletal muscle after birth, and has long been linked to age-related muscle wasting. Many rodent studies have shown a correlation between MSTN and age-related diseases. It is unclear how MSTN and age-associated muscle loss in other animals are related. In this study, we utilized MSTN gene-edited bovine skeletal muscle cells to investigate the mechanisms relating to MSTN and muscle cell senescence. The expression of MSTN was higher in older individuals than in younger individuals. We obtained consecutively passaged senescent cells and performed senescence index assays and transcriptome sequencing. We found that senescence hallmarks and the senescence-associated secretory phenotype (SASP) were decreased in long-term-cultured myostatin inactivated (MT-KO) bovine skeletal muscle cells (bSMCs). Using cell signaling profiling, MSTN was shown to regulate the SASP, predominantly through the cycle GMP-AMP synthase-stimulator of antiviral genes (cGAS-STING) pathway. An in-depth investigation by chromatin immunoprecipitation (ChIP) analysis revealed that MSTN influenced three prime repair exonuclease 1 (TREX1) expression through the SMAD2/3 complex. The downregulation of MSTN contributed to the activation of the MSTN-SMAD2/3-TREX1 signaling axis, influencing the secretion of SASP, and consequently delaying the senescence of bSMCs. This study provided valuable new insight into the role of MSTN in cell senescence in large animals.

Effects of 15% Azelaic Acid Gel in the Management of Post-Inflammatory Erythema and Post-Inflammatory Hyperpigmentation in Acne Vulgaris.

INTRODUCTION: The aim of this study was to assess the efficacy and safety of 15% azelaic acid (AzA) gel in treating acne-induced post-inflammatory erythema (PIE) and post-inflammatory hyperpigmentation (PIH). The effects of 15% AzA gel on acne, skin barrier function, and quality of life were also evaluated. METHODS: A total of 72 patients with mild to moderate acne were enrolled in a randomized, double-blind, placebo-controlled trial. Patients were divided into two groups: patients in the AzA group applied 15% AzA gel twice daily for 12 weeks, and those in the placebo group applied AzA-free gel. Clinical evaluations using non-invasive skin detection technologies, including VISIA skin analysis, dermoscopy, and skin physiological function tests, were performed at 0, 4, 8, and 12 weeks. Main outcome measures included the post-acne hyperpigmentation index (PAHPI), melanin, hemoglobin, individual typology angle, water content, transepidermal water loss, and sebum. Investigator Global Assessment) and Dermatology Life Quality Index (DLQI) assessments were conducted at weeks 0 and 12. Adverse reactions were recorded. RESULTS: Of the 72 patients at study initiation, 60 completed the trial. At 8 and 12 weeks, patients in the AzA group showed significantly reduced PAHPI for PIE lesions compared to baseline and patients receiving placebo (P < 0.05). Patients in both groups exhibited reduced PIH lesions at weeks 8 and 12 that differed significantly from baseline (P < 0.05). Hemoglobin content decreased significantly in AzA-treated PIE lesions compared to those treated with placebo at week 12 (P < 0.05). Melanin content decreased significantly in AzA-treated PIH lesions at week 12 (P < 0.05). The AzA group showed higher improvement in DLQI (P < 0.05), and greater overall satisfaction (P < 0.05) compared to placebo. CONCLUSION: The results indicate that 15% AzA gel effectively improved acne-induced PIE and PIH with minimal adverse reactions, making it a viable clinical application. In the study population, it had no adverse effects on skin barrier function and contributed positively to acne improvement and patient quality of life. TRIAL REGISTRATION: This study was registered with the Chinese Clinical Trial Registry (ChiCTR.org.cn) under the identifier ChiCTR2300076959. The registration date was 25 October 2023, retrospectively registered.

The familial transmission of suicide and non-suicidal self-injury in different income levels in town.

BACKGROUND: Prior researches have established that suicide and non-suicidal self-injury (NSSI) exhibit familial transmission patterns. However, the extent to which these patterns vary across different income levels remains unclear, as well as the specific factors that influence them. This study aimed to explore these questions. METHODS: We analyzed data from 13,988 parent-child pairs in Chongqing, China, where the children were aged from 7 to 12 years old. Six income levels were considered, and the children's depression and anxiety symptoms were assessed using standardized scales (the Center for Epidemiological Studies Depression Scale for Children, [CES-DC], and the Screen for Child Anxiety Related Emotional Disorders [SCARED], respectively). Binary logistic regression analysis was employed to examine the transmission of suicide and NSSI across different income levels. RESULTS: Familial transmission of suicide was significant difference in all income levels except the highest, while familial transmission of NSSI was significant difference in all income levels except the lowest. Notably, in both low- and high-income levels, suicide and NSSI transmissions primarily occurred among male children, mothers with higher education, and children who spent long time with their mothers. Additionally, the transmissions were mediated partially or entirely by children's depression and anxiety symptoms. LIMITATIONS: Future studies should investigate the separate effects of fathers' and mothers' suicide and NSSI histories on familial transmission patterns. CONCLUSION: The familial transmissions of suicide and NSSI exhibited distinct patterns across different income levels.

Association of pulsatility index with total burden of cerebral small vessel disease and cognitive impairment.

OBJECTIVE: This study investigated the correlation between the pulsatility index (PI) of the middle cerebral artery with the total burden of cerebral small vessel disease and cognitive impairment. METHOD: Information on patients hospitalized in the Department of Neurology was collected retrospectively. These patients had complete clinical and laboratory data. The middle cerebral artery PI was measured using transcranial Doppler, a Mini-Mental State Examination (MMSE) was used to assess cognitive function, and the total cerebral small vessel disease burden was assessed using magnetic resonance imaging. Patients were grouped according to their scores for total imaging burden of cerebral small vessel disease and cognitive function. Logistic regression analysis assessed the association between the PI, total imaging burden, and cognitive impairment. Spearman analysis was used to evaluate the correlation between the PI and total imaging burden and cognitive impairment, and receiver operating characteristic (ROC) curves were used to determine the predictive value of the PI for cognitive function. RESULTS: The PI was higher in the cognitive impairment (CI) group than in the no-CI group. Binary logistic regression analysis showed that increased PI was an independent risk factor for CI (OR = 1.582; 95% CI: 1.043-2.401; p = .031) and total imaging burden (OR = 1.842; 95% CI: 1.274-2.663; p = .001). Spearman analysis found that the PI correlated negatively with the MMSE score (r = -.627, p < .001). ROC curve analysis showed the PI predicted CI with an area under the curve of 0.784. The PI combined with the total imaging burden predicted CI in cerebral small vessel disease with an area under the curve of 0.832. CONCLUSION: An increased PI was associated with CI and a high imaging burden in cerebral small vessel disease patients. The PI combined with the total burden score shows a high predictive value for CI.

Sulfur vacancy-rich bismuth sulfide nanowire derived from CAU-17 for radioactive iodine capture in complex environments: Performance and intrinsic mechanisms.

Effective capture and immobilization of volatile radioiodine from the off-gas of post-treatment plants is crucial for nuclear safety and public health, considering its long half-life, high toxicity, and environmental mobility. Herein, sulfur vacancy-rich Vs-Bi2S3@C nanocomposites were systematically synthesized via a one-step solvothermal vulcanization of CAU-17 precursor. Batch adsorption experiments demonstrated that the as-synthesized materials exhibited superior iodine adsorption capacity (1505.8 mg g-1 at 200 °C), fast equilibrium time (60 min), and high chemisorption ratio (91.7%), which might benefit from the nanowire structure and abundant sulfur vacancies of Bi2S3. Furthermore, Vs-Bi2S3@C composites exhibited excellent iodine capture performance in complex environments (high temperatures, high humidity and radiation exposure). Mechanistic investigations revealed that the I2 capture by fabricated materials primarily involved the chemical adsorption between Bi2S3 and I2 to form BiI3, and the interaction of I2 with electrons provided by sulfur vacancies to form polyiodide anions (I3-). The post-adsorbed iodine samples were successfully immobilized into commercial glass fractions in a stable form (BixOyI), exhibiting a normalized iodine leaching rate of 3.81 × 10-5 g m-2 d-1. Overall, our work offers a novel strategy for the design of adsorbent materials tailed for efficient capture and immobilization of volatile radioiodine.

Aminoselenation and Dehydroaromatization of Cyclohexanones with Anilines and Diselenides.

A three-component cascade reaction involving cyclohexanones, anilines, and diaryl diselenides under metal-free conditions is reported. The ortho-selenation of cyclohexanones with diaryl diselenides, followed by sequential dehydroaromatization with anilines, enables the preparation of a variety of o-selanyl anilines in moderate to excellent yields. This innovative transformation is notable for its excellent tolerance of functional groups and is suitable for the late-stage modification of complex pharmaceuticals.

Application and mechanism of carbonate material in the treatment of heavy metal pollution: a review.

Among the many heavy metal pollution treatment agents, carbonate materials show strong flexibility and versatility by virtue of their high adsorption capacity for heavy metals and the characteristics of multiple and simple modification methods. It shows good potential for development. This review summarizes the application of carbonate materials in the treatment of heavy metal pollution according to the research of other scholars. It mainly relates to the application of surface-modified, activated, and nano-sized carbonate materials in the treatment of heavy metal pollution in water. Natural carbonate minerals and composite carbonate minerals solidify and stabilize heavy metals in soil. Solidification of heavy metals in hazardous waste solids is by MICP. There are four aspects of calcium carbonate oligomers curing heavy metals in fly ash from waste incineration. The mechanism of treating heavy metals by carbonate in different media was discussed. However, in the complex environment where multiple types of pollutants coexist, questions on how to maintain the efficient processing capacity of carbonate materials and how to use MICP to integrate heavy metal fixation and seepage prevention in solid waste base under complex and changeable natural environment deserve our further consideration. In addition, the use of carbonate materials for the purification of trace radioactive wastewater and the safe treatment of trace radioactive solid waste are also worthy of further exploration.

Dysregulations of amino acid metabolism and lipid metabolism in urine of children and adolescents with major depressive disorder: a case-control study.

RATIONALE: The mechanisms underlying major depressive disorder (MDD) in children and adolescents are unclear. Metabolomics has been utilized to capture metabolic signatures of various psychiatric disorders; however, urinary metabolic profile of MDD in children and adolescents has not been studied. OBJECTIVES: We analyzed urinary metabolites in children and adolescents with MDD to identify potential biomarkers and metabolic signatures. METHODS: Here, liquid chromatography-mass spectrometry was used to profile metabolites in urine samples from 192 subjects, comprising 80 individuals with antidepressant-naïve MDD (AN-MDD), 37 with antidepressant-treated MDD (AT-MDD) and 75 healthy controls (HC). We performed orthogonal partial least squares discriminant analysis to identify differential metabolites and employed logistic regression and receiver operating characteristic analysis to establish a diagnostic panel. RESULTS: In total, 143 and 71 differential metabolites were identified in AN-MDD and AT-MDD, respectively. These were primarily linked to lipid metabolism, molecular transport, and small molecule biochemistry. AN-MDD additionally exhibited dysregulated amino acid metabolism. Compared to HC, a diagnostic panel of seven metabolites displayed area under the receiver operating characteristic curves of 0.792 for AN-MDD, 0.828 for AT-MDD, and 0.799 for all MDD. Furthermore, the urinary metabolic profiles of children and adolescents with MDD significantly differed from those of adult MDD. CONCLUSIONS: Our research suggests dysregulated amino acid metabolism and lipid metabolism in the urine of children and adolescents with MDD, similar to results in plasma metabolomics studies. This contributes to the comprehension of mechanisms underlying children and adolescents with MDD.

The S100 family is a prognostic biomarker and correlated with immune cell infiltration in pan-cancer.

BACKGROUND: The S100 protein family is a group of small molecular EF-hand calcium-binding proteins that play critical roles in various biological processes, including promotion of growth, metastasis and immune evasion of tumor. However, the potential roles of S100 protein family expression in tumor microenvironment (TME) cell infiltration in pan-cancer remain elusive. METHODS: Herein, we conducted a comprehensive assessment of the expression patterns of the S100 protein family in pan-cancer, meticulously examining their correlation with characteristics of TME cell infiltration. The S100 score was constructed to quantify S100 family expression patterns of individual tumors. RESULTS: The S100 family was a potent risk factor in many cancers. Clustering analysis based on the transcriptome patterns of S100 protein family identified two cancer clusters with distinct immunophenotypes and clinical characteristics. Cluster A, with lower S100 expression, exhibited lower immune infiltration, whereas, Cluster B, with higher S100 expression, featured higher immune infiltration. Interestingly, Cluster B had a poorer prognosis, likely due to an immune-excluded phenotype resulting from stromal activation. The analysis revealed robust enrichment of the TGFb and EMT pathways in the cohort exhibiting high S100 score, alongside a positive correlation between the S100 score and Treg levels, suggesting the manifestation of an immune-excluded phenotype in this group. Moreover, S100 families were associated with the prognosis of 22 different cancers and a noteworthy association was observed between high S100 score and an unfavorable response to anti-PD-1/L1 immunotherapy. Consistent findings across two independent immunotherapy cohorts substantiated the advantageous therapeutic outcomes and clinical benefits in patients displaying lower S100score. CONCLUSION: Our analysis demonstrated the role of S100 family in formation of TME diversity and complexity, enabling deeper cognition of TME infiltration characterization and the development of personalized immunotherapy strategies targeting S100 family for unique tumor types.