Structural and functional characteristics of pectins from three cultivars of apple (Malus pumila Mill.) pomaces.

This study aimed to investigate the chemical composition, structural properties, and biological properties of pectin polysaccharides (AP-FS, AP-QG, and AP-HG) isolated from different varieties of apple pomace. Based on the methylation and nuclear magnetic resonance analyses, the structure of AP-FS was determined to be composed of an α-1,4-linked homogalacturonan backbone that exhibited high levels of O-6 methylation. All pectins exhibit potent inhibitory activity against human colon cancer and human liver cancer cells, along with immunostimulatory effects. Among them, AP-FS exhibited the highest activity level. Finally, we further investigated the underlying mechanism behind the effect of AP-FS on RAW 264.7 cells using proteomics analysis. Our findings revealed that AP-FS triggers RAW 264.7 macrophage activation via NOD-like receptor (NLR), NF-κB, and mitogen-activated protein kinase (MAPK) signaling pathways. Therefore, our research contributes to a better understanding of the structure-function relationship among apple pectins, and AP-FS has the potential to be applied to dietary supplements targeting immunomodulation.

Particulate matter pollution, polygenic risk score and mosaic loss of chromosome Y in middle-aged and older men from the Dongfeng-Tongji cohort study.

Mosaic loss of chromosome Y (mLOY) is the most common somatic alteration as men aging and may reflect genome instability. PM exposure is a major health concern worldwide, but its effects with genetic factors on mLOY has never been investigated. Here we explored the associations of PM2.5 and PM10 exposure with mLOY of 10,158 males measured via signal intensity of 2186 probes in male-specific chromosome-Y region from Illumina array data. The interactive and joint effects of PM2.5 and PM10 with genetic factors and smoking on mLOY were further evaluated. Compared with the lowest tertiles of PM2.5 levels in each exposure window, the highest tertiles in the same day, 7-, 14-, 21-, and 28-day showed a 0.005, 0.006, 0.007, 0.007, and 0.006 decrease in mLRR-Y, respectively (all P < 0.05), with adjustment for age, BMI, smoking pack-years, alcohol drinking status, physical activity, education levels, season of blood draw, and experimental batch. Such adverse effects were also observed in PM10-mLOY associations. Moreover, the unweighted and weighted PRS presented significant negative associations with mLRR-Y (both P < 0.001). Participants with high PRS and high PM2.5 or PM10 exposure in the 28-day separately showed a 0.018 or 0.019 lower mLRR-Y level [ß (95 %CI) = -0.018 (-0.023, -0.012) and - 0.019 (-0.025, -0.014), respectively, both P < 0.001], when compared to those with low PRS and low PM2.5 or PM10 exposure. We also observed joint effects of PM with smoking on exacerbated mLOY. This large study is the first to elucidate the impacts of PM2.5 exposure on mLOY, and provides key evidence regarding the interactive and joint effects of PM with genetic factors on mLOY, which may promote understanding of mLOY development, further modifying and increasing healthy aging in males.

Theabrownin as a Potential Prebiotic Compound Regulates Lipid Metabolism via the Gut Microbiota, Microbiota-Derived Metabolites, and Hepatic FoxO/PPAR Signaling Pathways.

The dysregulation of lipid metabolism poses a significant health threat, necessitating immediate dietary intervention. Our previous research unveiled the prebiotic-like properties of theabrownin. This study aimed to further investigate the theabrownin-gut microbiota interactions and their downstream effects on lipid metabolism using integrated physiological, genomic, metabolomic, and transcriptomic approaches. The results demonstrated that theabrownin significantly ameliorated dyslipidemia, hepatic steatosis, and systemic inflammation induced by a high-fat/high-cholesterol diet (HFD). Moreover, theabrownin significantly improved HFD-induced gut microbiota dysbiosis and induced significant alterations in microbiota-derived metabolites. Additionally, the detailed interplay between theabrownin and gut microbiota was revealed. Analysis of hepatic transcriptome indicated that FoxO and PPAR signaling pathways played pivotal roles in response to theabrownin-gut microbiota interactions, primarily through upregulating hepatic Foxo1, Prkaa1, Pck1, Cdkn1a, Bcl6, Klf2, Ppara, and Pparg, while downregulating Ccnb1, Ccnb2, Fabp3, and Plin1. These findings underscored the critical role of gut-liver axis in theabrownin-mediated improvements in lipid metabolism disorders and supported the potential of theabrownin as an effective prebiotic compound for targeted regulation of metabolic diseases.

Dynamic genomic changes in methotrexate-resistant human cancer cell lines beyond DHFR amplification suggest potential new targets for preventing drug resistance.

BACKGROUND: Although DHFR gene amplification has long been known as a major mechanism for methotrexate (MTX) resistance in cancer, the early changes and detailed development of the resistance are not yet fully understood. METHODS: We performed genomic, transcriptional and proteomic analyses of human colon cancer cells with sequentially increasing levels of MTX-resistance. RESULTS: The genomic amplification evolved in three phases (pre-amplification, homogenously staining region (HSR) and extrachromosomal DNA (ecDNA)). We confirm that genomic amplification and increased expression of DHFR, with formation of HSRs and especially ecDNAs, is the major driver of resistance. However, DHFR did not play a detectable role in the early phase. In the late phase (ecDNA), increase in FAM151B protein level may also have an important role by decreasing sensitivity to MTX. In addition, although MSH3 and ZFYVE16 may be subject to different posttranscriptional regulations and therefore protein expressions are decreased in ecDNA stages compared to HSR stages, they still play important roles in MTX resistance. CONCLUSION: The study provides a detailed evolutionary trajectory of MTX-resistance and identifies new targets, especially ecDNAs, which could help to prevent drug resistance. It also presents a proof-of-principal approach which could be applied to other cancer drug resistance studies.

Treatment of abdominal pain due to deficiency syndrome of the spleen and stomach with Bian stone plus TCM iontophoresis: A case report.

RATIONALE: Bian stone ironing and rubbing traditional Chinese medicine penetration method is based on the theory of regulating the middle and restoring balance. By using Bian stone to heat, ironing, and rubbing, pushing and rubbing in the epigastric area can regulate the spleen and stomach, restore the normal function of the middle jiao qi movement and the functions of the five organs. Bian stone hot ironing can harmonize stomach qi, nourish qi and assist yang, clear the internal organs and clear turbidity, regulate intestinal qi circulation, and promote qi stagnation. PATIENT CONCERNS: The VAS score for stomach pain is 6 points, and the SAS score is moderate anxiety, which seriously affects sleep and daily life. DIAGNOSES: epigastric pain, spleen, and stomach deficiency cold syndrome. INTERVENTIONS: Easy to digest diet, Western medicine provides famotidine acid inhibiting and protecting gastric mucosa, and mosapride promoting gastrointestinal peristalsis medication treatment; Traditional Chinese Medicine provides oral administration of Huangqi Jianzhong Tang and traditional Chinese medicine techniques such as Bianchi Ironing and Moxibustion for treatment. OUTCOMES: The patient's symptoms of stomach pain have significantly improved, with a decrease in the epigastric pain score to 0, improved anxiety, reduced fatigue, improved sleep, improved epigastric fullness, unobstructed bowel movements, and improved quality of life. The patient is very satisfied. LESSONS: The method of using Bian stone ironing and rubbing traditional Chinese medicine to treat stomach pain caused by the spleen and stomach deficiency cold can alleviate the symptoms of stomach pain in patients, and the improvement of symptoms shows a gradual increase, with significant effects. At the same time, it significantly improves patient anxiety and fatigue symptoms and can increase the sample size in future work to further clarify its clinical effects.

Derived energy storage systems from Brayton cycle.

Various energy storage systems (ESS) can be derived from the Brayton cycle, with the most representative being compressed air energy storage and pumped thermal electricity storage systems. Although some important studies on above ESS are reported, the topological structure behind those systems (i.e., derivations of the Brayton cycle) has not been studied, and the underlying thermodynamic ideas still need to be further explored. This paper first introduces the topological structure and the symmetry of ESS and their based Brayton cycles. The formation method of ESS based on paths and separation points is specified. It is found that round-trip path can form ESS directly. Then various ESS formed are compared. Finally, the synergistic effect and gain principle of thermal cycle and ESS are revealed. This work helps to reveal the intrinsic relationship between thermal cycles and ESS, understand the general laws behind ESS, and guide the combination of thermal cycles and ESS.

Distribution and Drug Resistance of Common Pathogens Causing Lower Respiratory Tract Infection in Xinjiang Region.

Objective: This study aims to analyze the composition and distribution of pathogenic bacteria in lower respiratory tract infections (LRTI) and their antimicrobial resistance patterns in a hospital in Xinjiang, to guide more effective antibiotic selection and inform clinical management. Methods: We retrospectively analyzed 545 strains isolated from various clinical specimens like sputum and blood, collected between June 2020 and June 2023, using the LIST system. The strains were subjected to drug resistance testing, and statistical analyses included t tests and Chi-square tests. Results: Among gram-negative bacilli, Acinetobacter baumannii dominated, accounting for 32.11%, followed by Pseudomonas aeruginosa, accounting for 18.35%. Among gram-positive bacteria, thrombin-negative staphylococcus was at the top of the list, followed by Staphylococcus aureus. Among Acinetobacter baumannii (AB), carbapenem-resistant Acinetobacter baumannii plays a dominant role. The sensitivity rate of these strains to tigecycline and amikacin could reach more than 80%. The sensitivity of Pseudomonas aeruginosa (PA) to piperacillin, gentamicin, imipenem, meropenem, ciprofloxacin and levofloxacin ranged from 50% to 80%. It is worth mentioning that the sensitivity rate of PA to amikacin, cefoperazone, and tobramycin exceeded 80%. Amikacin was more than 60% sensitive to carbapenem, ß-lactam inhibitors, tigecycline, quinolones, and aminoglycosides of ESBL producing Klebsiella pneumoniae. Among gram-positive coccus, methicillin-resistant coagulase-negative staphylococcus was 100% sensitive to duration, e, tigecycline, and vancomycin. In addition, the susceptibility rate of these strains to rifampicin and linezolid was greater than 70%. Conclusions: In patients with lower respiratory tract infection (LRTI) in a hospital in Xinjiang, the most common pathogenic bacteria are gram-negative bacilli, mainly Acinetobacter baumannii and Pseudomonas aeruginosa. Both resistant and non-resistant strains showed sensitivity to amikacin and tigecycline. Additionally, staphylococcus accounted for half of the total number of gram-positive bacteria, among which methicillin-resistant strains were more sensitive to vancomycin and linezolid.

SeFilter-DIA: Squeeze-and-Excitation Network for Filtering High-Confidence Peptides of Data-Independent Acquisition Proteomics.

Mass spectrometry is crucial in proteomics analysis, particularly using Data Independent Acquisition (DIA) for reliable and reproducible mass spectrometry data acquisition, enabling broad mass-to-charge ratio coverage and high throughput. DIA-NN, a prominent deep learning software in DIA proteome analysis, generates peptide results but may include low-confidence peptides. Conventionally, biologists have to manually screen peptide fragment ion chromatogram peaks (XIC) for identifying high-confidence peptides, a time-consuming and subjective process prone to variability. In this study, we introduce SeFilter-DIA, a deep learning algorithm, aiming at automating the identification of high-confidence peptides. Leveraging compressed excitation neural network and residual network models, SeFilter-DIA extracts XIC features and effectively discerns between high and low-confidence peptides. Evaluation of the benchmark datasets demonstrates SeFilter-DIA achieving 99.6% AUC on the test set and 97% for other performance indicators. Furthermore, SeFilter-DIA is applicable for screening peptides with phosphorylation modifications. These results demonstrate the potential of SeFilter-DIA to replace manual screening, providing an efficient and objective approach for high-confidence peptide identification while mitigating associated limitations.

Association of systemic inflammation index with psoriasis risk and psoriasis severity: A retrospective cohort study of NHANES 2009 to 2014.

To investigate the association of systemic inflammation index (SII) with psoriasis risk and psoriasis severity. This is a retrospective cohort study based on data from the National Health and Nutrition Examination Survey database from 2009 to 2014. The psoriasis information was obtained from the questionnaire data, and the SII was calculated as neutrophil × platelet/lymphocyte. We performed matching by controlling age and gender to reach a 1:2 ratio for better statistical power. Weighted logistic regression analysis, subgroup analysis, restricted cubic spline analysis, and threshold analysis were used to evaluate the association of SII with psoriasis risk. Besides, mediation analysis was conducted to assess the possible regulatory path. Finally, the receiver operating characteristic curve was plotted to analyze the predictive value of SII for psoriasis severity. The study involved 16,466 participants including 16,020 no-psoriasis participants and 446 psoriasis participants. After matching, psoriasis and non-psoriasis individuals were 446 and 892, respectively. SII was significantly higher in the psoriasis group than the non-psoriasis group (P < .05). Additionally, white blood cells and monocytes were significantly linked to psoriasis risk and SII scores (P < .05). Besides, SII elevation was an independent predictor for upregulated psoriasis risk (P < .05). There was a nonlinear relationship between SII and psoriasis risk (P nonlinear < .05), which was not mediated by white blood cells and monocytes. Unexpectedly, SII had no significance in predicting SII severity (P > .05). SII can independently predict psoriasis risk but has no impact on psoriasis severity. Further, SII serves as a potential and robust biomarker for identifying high-risk psoriasis individuals.

The interaction effects of zinc and polygenic risk score with benzo[a]pyrene exposure on lung cancer risk: A prospective case-cohort study among Chinese populations.

The relationship of exposure to benzo [a]pyrene (BaP) with lung cancer risk has been firmly established, but whether this association could be modified by other environmental or genetic factors remains to be explored. To investigate whether and how zinc (Zn) and genetic predisposition modify the association between BaP and lung cancer, we performed a case-cohort study with a 5.4-years median follow-up duration, comprising a representative subcohort of 1399 participants and 359 incident lung cancer. The baseline concentrations of benzo [a]pyrene diol epoxide-albumin adduct (BPDE-Alb) and Zn were quantified. We also genotyped the participants and computed the polygenic risk score (PRS) for lung cancer. Our findings indicated that elevated BPDE-Alb and PRS were linked to increased lung cancer risk, with the HR (95%CI) of 1.54 (1.36, 1.74) per SD increment in ln-transformed BPDE-Alb and 1.27 (1.14, 1.41) per SD increment in PRS, but high plasma Zn level was linked to a lower lung cancer risk [HR (95%CI) per SD increment in ln-transformed Zn = 0.77 (0.66, 0.91)]. There was evidence of effect modification by Zn on BaP-lung cancer association (P for multiplicative interaction = 0.008). As Zn concentrations increased from the lowest to highest tertile, the lung cancer risk per SD increment in ln-transformed BPDE-Alb decreased from 2.07 (1.48, 2.89) to 1.45 (1.03, 2.05) to 1.33 (0.90, 1.95). Additionally, we observed a significant synergistic interaction of BPDE-Alb and PRS [RERI (95%CI) = 0.85 (0.03, 1.67)], with 42% of the incident lung cancer cases among individuals with high BPDE-Alb and high PRS attributable to their additive effect [AP (95%CI) = 0.42 (0.14, 0.69)]. This study provided the first prospective epidemiological evidence that Zn has protective effect against BaP-induced lung tumorigenesis, whereas high genetic risk can enhance the harmful effect of BaP. These findings may provide novel insight into the environment-environment and environment-gene interaction underlying lung cancer development, which may help to develop prevention and intervention strategies to manage BaP-induced lung cancer.

AttnPep: A Self-Attention-Based Deep Learning Method for Peptide Identification in Shotgun Proteomics.

In shotgun proteomics, the proteome search engine analyzes mass spectra obtained by experiments, and then a peptide-spectra match (PSM) is reported for each spectrum. However, most of the PSMs identified are incorrect, and therefore various postprocessing software have been developed for reranking the peptide identifications. Yet these methods suffer from issues such as dependency on distribution, reliance on shallow models, and limited effectiveness. In this work, we propose AttnPep, a deep learning model for rescoring PSM scores that utilizes the Self-Attention module. This module helps the neural network focus on features relevant to the classification of PSMs and ignore irrelevant features. This allows AttnPep to analyze the output of different search engines and improve PSM discrimination accuracy. We considered a PSM to be correct if it achieves a q-value <0.01 and compared AttnPep with existing mainstream software PeptideProphet, Percolator, and proteoTorch. The results indicated that AttnPep found an average increase in correct PSMs of 9.29% relative to the other methods. Additionally, AttnPep was able to better distinguish between correct and incorrect PSMs and found more synthetic peptides in the complex SWATH data set.

Macro CD5L+ deteriorates CD8+T cells exhaustion and impairs combination of Gemcitabine-Oxaliplatin-Lenvatinib-anti-PD1 therapy in intrahepatic cholangiocarcinoma.

Intratumoral immune status influences tumor therapeutic response, but it remains largely unclear how the status determines therapies for patients with intrahepatic cholangiocarcinoma. Here, we examine the single-cell transcriptional and TCR profiles of 18 tumor tissues pre- and post- therapy of gemcitabine plus oxaliplatin, in combination with lenvatinib and anti-PD1 antibody for intrahepatic cholangiocarcinoma. We find that high CD8 GZMB+ and CD8 proliferating proportions and a low Macro CD5L+ proportion predict good response to the therapy. In patients with a poor response, the CD8 GZMB+ and CD8 proliferating proportions are increased, but the CD8 GZMK+ proportion is decreased after the therapy. Transition of CD8 proliferating and CD8 GZMB+ to CD8 GZMK+ facilitates good response to the therapy, while Macro CD5L+-CD8 GZMB+ crosstalk impairs the response by increasing CTLA4 in CD8 GZMB+. Anti-CTLA4 antibody reverses resistance of the therapy in intrahepatic cholangiocarcinoma. Our data provide a resource for predicting response of the combination therapy and highlight the importance of CD8+T-cell status conversion and exhaustion induced by Macro CD5L+ in influencing the response, suggesting future avenues for cancer treatment optimization.

Mediation of association between benzo[a]pyrene exposure and lung cancer risk by plasma microRNAs: A Chinese case-control study.

Epidemiologic studies have reported the positive relationship of benzo[a]pyrene (BaP) exposure with the risk of lung cancer. However, the mechanisms underlying the relationship is still unclear. Plasma microRNA (miRNA) is a typical epigenetic biomarker that was linked to environment exposure and lung cancer development. We aimed to reveal the mediation effect of plasma miRNAs on BaP-related lung cancer. We designed a lung cancer case-control study including 136 lung cancer patients and 136 controls, and measured the adducts of benzo[a]pyrene diol epoxide-albumin (BPDE-Alb) and sequenced miRNA profiles in plasma. The relationships between BPDE-Alb adducts, normalized miRNA levels and the risk of lung cancer were assessed by linear regression models. The mediation effects of miRNAs on BaP-related lung cancer were investigated. A total of 190 plasma miRNAs were significantly related to lung cancer status at Bonferroni adjusted P < 0.05, among which 57 miRNAs showed different levels with |fold change| > 2 between plasma samples before and after tumor resection surgery at Bonferroni adjusted P < 0.05. Especially, among the 57 lung cancer-associated miRNAs, BPDE-Alb adducts were significantly related to miR-17-3p, miR-20a-3p, miR-135a-5p, miR-374a-5p, miR-374b-5p, miR-423-5p and miR-664a-5p, which could in turn mediate a separate 42.2%, 33.0%, 57.5%, 36.4%, 48.8%, 32.5% and 38.2% of the relationship of BPDE-Alb adducts with the risk of lung cancer. Our results provide non-invasion biomarker candidates for lung cancer, and highlight miRNAs dysregulation as a potential intermediate mechanism by which BaP exposure lead to lung tumorigenesis.

Serial circulating tumor DNA profiling predicts tumor recurrence after liver transplantation for liver cancer.

BACKGROUND: Minimal residual disease (MRD) is proposed to be responsible for tumor recurrence. The role of circulating tumor DNA (ctDNA) to detect MRD, monitor recurrence, and predict prognosis in liver cancer patients undergoing liver transplantation (LT) remains unrevealed. METHODS: Serial blood samples were collected to profile ctDNA mutational changes. Baseline ctDNA mutational profiles were compared with those of matched tumor tissues. Correlations between ctDNA status and recurrence rate (RR) and recurrence-free survival (RFS) were analyzed, respectively. Dynamic change of ctDNA was monitored to predict tumor recurrence. RESULTS: Baseline mutational profiles of ctDNA were highly concordant with those of tumor tissues (median, 89.85%; range 46.2-100%) in the 74 patients. Before LT, positive ctDNA status was associated with higher RR (31.7% vs 11.5%; p = 0.001) and shorter RFS than negative ctDNA status (17.8 vs 19.4 months; p = 0.019). After LT, the percentage of ctDNA positivity decreased (17.6% vs 47.0%; p < 0.001) and patients with positive ctDNA status had higher RR (46.2% vs 21.3%; p < 0.001) and shorter RFS (17.2 vs 19.2 months; p = 0.010). Serial ctDNA profiling demonstrated patients with decreased or constant negative ctDNA status had lower RR (33.3% vs 50.0%; p = 0.015) and favorable RFS (18.2 vs 15.0 months, p = 0.003) than those with increased or constant positive ctDNA status. Serial ctDNA profiling predicted recurrence months ahead of imaging evidence and serum tumor biomarkers. CONCLUSIONS: ctDNA could effectively detect MRD and predict tumor recurrence in liver cancer patients undergone LT.

DNA methylation aging signatures of multiple metals exposure and their mediation effects in metal-associated mortality: Evidence from the Dongfeng-Tongji cohort study.

Humans were exposed to multiple metals, but the impact of metals on DNA methylation-age (DNAm-age), a well-recognized aging measure, remains inconclusive. This study included 2942 participants from the Dongfeng-Tongji cohort. We detected their plasma concentrations of 23 metals and determined their genome-wide DNA methylation using the Illumina Human-MethylationEPIC BeadChip. Five DNAm-age acceleration indexes (DAIs), including HannumAge-Accel, HorvathAge-Accel, PhenoAge-Accel, GrimAge-Accel (residual from regressing corresponding DNAm-age on chronological age) and DNAm-mortality score (DNAm-MS), were separately calculated. We found that each 1-unit increase in ln-transformed copper (Cu) was associated with a separate 1.02-, 0.83- and 0.07-unit increase in PhenoAge-Accel, GrimAge-Accel, and DNAm-MS (all FDR<0.05). Each 1-unit increase in ln-transformed nickel (Ni) was associated with a 0.34-year increase in PhenoAge-Accel, while each 1-unit increase in ln-transformed strontium (Sr) was associated with a 0.05-unit increase in DNAm-MS. The Cu, Ni and Sr showed joint positive effects on above three DAIs. PhenoAge-Accel, GrimAge-Accel, and DNAm-MS mediated a separate 6.5%, 12.3%, 6.0% of the positive association between Cu and all-cause mortality; GrimAge-Accel mediated 14.3% of the inverse association of selenium with all-cause mortality. Our findings revealed the effects of Cu, Ni, Sr and their co-exposure on accelerated aging and highlighted mediation roles of DNAm-age on metal-associated mortality.

Development and validation of a nomogram to predict cardiac death after radiotherapy for esophageal cancer.

Background: Patients frequently die from cardiac causes after radiotherapy for esophageal cancer. Early detection of cardiac death risk in these patients is crucial to improve clinical decision-making and prognosis. Thus, we modeled the risk of cardiac death after irradiation for esophageal cancer. Methods: A retrospective analysis of 37,599 esophageal cancer cases treated with radiotherapy in the SEER database between 2000 and 2018 was performed. The selected cases were randomly assigned to the model development group (n = 26,320) and model validation group (n = 11,279) at a ratio of 7:3. We identified the risk factors most commonly associated with cardiac death by least absolute shrinkage and selection operator regression analysis (LASSO). The endpoints for model development and validation were 5- and 10-year survival rates. The net clinical benefit of the models was evaluated by decision curve analysis (DCA) and concordance index (C-index). The performance of the models was further assessed by creating a receiver operating characteristic curve (ROC) and calculating the area under the curve (AUC). Kaplan-Meier (K-M) survival analysis was performed on the probability of death. Patients were classified according to death probability thresholds. Five- and ten-year survival rates for the two groups were shown using K-M curves. Results: The major risk factors for cardiac death were age, surgery, year of diagnosis, sequence of surgery and radiotherapy, chemotherapy and a number of tumors, which were used to create the nomogram. The C-indexes of the nomograms were 0.708 and 0.679 for the development and validation groups, respectively. DCA showed the good net clinical benefit of nomograms in predicting 5- and 10-year risk of cardiac death. The model exhibited moderate predictive power for 5- and 10-year cardiac mortality (AUC: 0.833 and 0.854, respectively), and for the development and validation cohorts (AUC: 0.76 and 0.813, respectively). Conclusions: Our nomogram may assist clinicians in making clinical decisions about patients undergoing radiotherapy for esophageal cancer based on early detection of cardiac death risk.

CCL2 Potentiates Inflammation Pain and Related Anxiety-Like Behavior Through NMDA Signaling in Anterior Cingulate Cortex.

Previous studies have shown that the C-C motif chemokine ligand 2 (CCL2) is widely expressed in the nervous system and involved in regulating the development of chronic pain and related anxiety-like behaviors, but its precise mechanism is still unclear. This paper provides an in-depth examination of the involvement of CCL2-CCR2 signaling in the anterior cingulate cortex (ACC) in intraplantar injection of complete Freund's adjuvant (CFA) leading to inflammatory pain and its concomitant anxiety-like behaviors by modulation of glutamatergic N-methyl-D-aspartate receptor (NMDAR). Our findings suggest that local bilateral injection of CCR2 antagonist in the ACC inhibits CFA-induced inflammatory pain and anxiety-like behavior. Meanwhile, the expression of CCR2 and CCL2 was significantly increased in ACC after 14 days of intraplantar injection of CFA, and CCR2 was mainly expressed in excitatory neurons. Whole-cell patch-clamp recordings showed that the CCR2 inhibitor RS504393 reduced the frequency of miniature excitatory postsynaptic currents (mEPSC) in ACC, and CCL2 was involved in the regulation of NMDAR-induced current in ACC neurons in the pathological state. In addition, local injection of the NR2B inhibitor of NMDAR subunits, Ro 25-6981, attenuated the effects of CCL2-induced hyperalgesia and anxiety-like behavior in the ACC. In summary, CCL2 acts on CCR2 in ACC excitatory neurons and participates in the regulation of CFA-induced pain and related anxiety-like behaviors through upregulation of NR2B. CCR2 in the ACC neuron may be a potential target for the treatment of chronic inflammatory pain and pain-related anxiety.

Associations of multiple plasma metals with osteoporosis: findings from the Dongfeng-Tongji cohort.

With the aging population, osteoporosis has become a more prevalent public health issue. Existing researches have indicated significant relations of single metal exposure with osteoporosis (e.g., lead, copper, and zinc), whereas the evidence regarding the joint association of metal mixtures with osteoporosis remain limited and inconclusive. A total of 4924 participants from the Dongfeng-Tongji cohort were included in the present study. Plasma levels of 23 metals were determined by inductively coupled plasma mass spectrometry, and the presence of osteoporosis was defined as a bone mineral density T-score ≤ - 2.5. We applied stepwise regression, plasma metal score, and quantile g-computation model to evaluate the association between plasma metal mixtures and osteoporosis risk. Of the 4924 participants, the prevalence of osteoporosis was 10.9% (N = 265) in males and 27.5% (N = 684) in females. In the multiple-metals model, arsenic was positively associated with osteoporosis in males, while zinc was positively associated with osteoporosis in females. Comparing extreme quartiles, the multivariate-adjusted ORs of osteoporosis were 2.20 (95% CI, 1.29, 3.79; P-trend = 0.006) for arsenic in males and 2.16 (95% CI, 1.44, 3.23; P-trend < 0.001) for zinc in females. The plasma metal score was significantly and positively associated with a higher risk of osteoporosis, with ORs (95% CI) comparing extreme quartiles were 5.00 (95% CI, 3.36, 7.65; P-trend < 0.001) in males and 1.76 (95% CI, 1.35, 2.29; P-trend < 0.001) in females. Furthermore, the results of quantile g-computation revealed a consistent positive trend of metal mixtures with risk of osteoporosis and suggested the dominant role of arsenic in males and zinc in females, respectively. Our findings highlighted the importance of controlling metal mixtures exposure for the prevention of osteoporosis in the middle-aged and elder population. Further prospective studies in larger populations are warranted to confirm our findings.