Correlation Analysis Research Articles

Study on the mechanisms of acupuncture combined with paroxetine in the treatment of mild to moderate depression based on DNA methylation analysis.

To explore the therapeutic effect of acupuncture combined with paroxetine for mild to moderate depression and the regulatory role of brain derived neurotrophic factor (BDNF) in patients based on DNA methylation. A total of 66 patients with mild to moderate depression who met the inclusion and exclusion criteria were randomly divided into an observation (acupuncture+medication) group and a control (medication) group, with 33 patients in each group, and other 25 healthy volunteers were taken as the healthy group. The patients of the control group were treated by oral administration of paroxetine 20 mg/d for 4 weeks. The patients of the observation group were treated by acupuncture stimulation of Zhongwan (CV12), Qihai (CV6), Zusanli (ST36), Sanyinjiao (SP6), Shangxing (GV23), Shuigou (GV26), Shaoshang (LU11), Yinbai (SP1) and Daling (PC7) (for 20 min, 3 times a week for 4 weeks) on the basis of medication treatment (the same as that of the control group). Before treatment, 2 and 4 weeks of treatment, and 2 weeks of follow-up, the therapeutic effect was assessed using Hamilton Depression Scale 17 (HAMD-17). The SPSS25.0 software was used to form a randomized grouping and to randomly select 25 patients from the observation group and 25 patients from the control group for blood collecting and data analysis. The blood samples were taken for assaying serum BDNF content and the methylation degree of BDNF gene promotor I with ELISA and MassARRAY techniques, respectively. 1) In comparison with those before treatment, the total score of HAMD-17, sleep disorder factor score, and anxiety somatization factor score of both the observation and control groups were significantly decreased after 2 and 4 weeks of treatment, and 2 weeks of follow-up (P<0.05), except sleep disorder factor score in the control group after 2 weeks of the treatment. Compared with the same time-points of the control group, the HAMD-17 total score and sleep disorder factor score of the observation group were decreased after 2 and 4 weeks of treatment, and 2 weeks of follow-up (P<0.05), while the anxiety somatization factor score was evidently decreased after 2 weeks of treatment (P<0.05). 2) Following 2 weeks of treatment, the total effective rate and markedly effective rate of the observation group were 80%(24/30)and 36.67% (11/30), respectively, being significantly higher than those ［(26.67% and 0 %)］ of the control group. After 4 weeks of treatment, the markedly effective rate of the observation group was 70.00% (21/30), being significantly higher than that 40% (12/30) of the control group (P<0.05), while the total effective rates of the observation and control groups were the same (100%). 3) Before the treatment, comparison among the healthy, observation and control groups showed no statistical significance in the methylation degree of each site (CpG1.2, CpG5.6, CpG8.9, CpG26, CpG27, CpG31, and CpG33.34) of BDNF gene promotor I, while after 4 weeks of the treatment, the methylation degree of CpG31 was considerably lower in the observation group than in the control group (P<0.05). 4) Before the treatment, the contents of serum BDNF of both observation and control group had no significant difference, but were evidently lower than that of the healthy group (P<0.05). Compared with that before treatment, the serum BDNF contents in both observation and control groups were significantly increased after the treatment (P<0.05), and was significantly higher in the observation group than in the control group (P<0.05). 5) The correlation analysis showed a negative correlation between the BDNF protein content and HAMD-17 score (correlation coefficient ρ=-0.686, P<0.01). Acupuncture may have an antidepressant role by decreasing CpG31 methylation of BDNF and increasing the serum content of BDNF protein in patients with depression. In addition, acupuncture combined with paroxetine has more advantages in treating mild to moderate depression than oral paroxetine alone, and can improve sleep disorders and anxiety somatization symptoms more quickly.

Crosstalk between skeletal muscle ratio and cholesterol metabolism disorders: a cross-section study

BackgroundDysfunction of cholesterol metabolism may be associated with low skeletal muscle mass. This study aimed to explore the relationship between skeletal muscle mass and cholesterol metabolic disorders in adults.MethodsThe data of a total of 5949 people with complete medical history data, biochemical data and body composition analysis were recruited. According to the serum cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL) and nonHDL, the population was divided into a disorder group and a normal group. Independent sample t tests, chi-square tests, Pearson's correlation analyses and binary logistic regression analyses were used to study the effect of body composition on abnormal cholesterol metabolism. According to BMI and sex, the population was divided into different subgroups, and binary logistic regression analysis was used to study the effect of the skeletal mass ratio on cholesteral metabolic disorders in different subgroups.ResultsThere were significant differences in sex, alcohol consumption, body weight, BMI, skeletal muscle mass index (SMI) [total skeletal muscle mass (kg)/height 2 (m2)] and skeletal muscle mass ratio (SMR) [total skeletal muscle mass (kg)/weight (kg) *100] between the disorder group (hypercholesterolemia, hyper-LDL, lower-HDL and hyper-nonHDL) and the normal group. Pearson correlation analysis revealed that the SMR was negatively correlated, while the SMI was positively correlated with cholesterol metabolic disorders in both sexes. The overweight group was older and had a greater SMI, abnormal cholesteral metabolism ratio and lower SMR than the normal-weight group. In the normal-weight group, the SMR was an independent protective factor against different kinds of cholesteral metabolic disorders in both sexes, while the SMI was a risk factor. In the overweight subgroup, the protective effect on HDL and nonHDL metabolism remained in the male subgroup but disappeared in the female subgroup. However, the SMI was an independent risk factor for different kinds of cholesteral metabolic disorders in both sexes.ConclusionsSMR was an independent protective factor against cholesterol metabolic disorders in both males and females, especially in the normal weight group. SMI was an independent risk factor, especially in the overweight group.

Identification and functionalization of thyrotropin receptor antibodies (TRAb) with different antigenic epitopes.

One of the sensitive markers for autoimmune thyroid disease (AITD) clinical identification is TRAb. To quickly distinguish TRAb with distinct antigenic epitopes, a straightforward and uncomplicated technique has not yet been created. To search for molecular diagnostic targets for different types of AITD (Graves' disease (GD), Graves' orbitopathy (GO), GD with III degree goiter (GD(3)), Hypothyroidism combined with positive TRAb (HT(TRAb+))) as molecular diagnostic targets. Following action on thyroid cells, differential genes (DEGs) generated by TRAb with distinct antigenic epitopes were detected and identified by RNA-seq, bioinformatics analysis, and RT-qPCR in the serum of AITD patients. Using the EdU assay, the effect of co-culturing thyroid cells with different antigenic TRAb epitopes on the cells' capacity to proliferate was investigated. Bioinformatics analysis and RT-qPCR validation identified one GD key gene (AHSG), two GO key genes (ADRA1D and H2BC18), two GD(3) key genes (SOCS1 and CYBB), and one HT (TRAb+) key gene (MASP2). Correlation analysis and ROC curves showed that the above genes could be used as molecular diagnostic targets for different types of AITD. Finally, EdU results showed that TRAb inhibited thyroid cell proliferation in the HT (TRAb+) group compared with the normal control group, while the remaining three groups promoted thyroid cell proliferation, with a statistically significant difference (P < 0.05). We identified six key genes for different types of AITD, which have diagnostic value for different types of AITD. Meanwhile, we found that TRAb of different antigenic epitopes in AITD have different biological functions.

Altered static and dynamic functional network connectivity in individuals with subthreshold depression: a large-scale resting-state fMRI study.

Dynamic functional network connectivity (dFNC) is an expansion of static FNC (sFNC) that reflects connectivity variations among brain networks. This study aimed to investigate changes in sFNC and dFNC strength and temporal properties in individuals with subthreshold depression (StD). Forty-two individuals with subthreshold depression and 38 healthy controls (HCs) were included in this study. Group independent component analysis (GICA) was used to determine target resting-state networks, namely, executive control network (ECN), default mode network (DMN), sensorimotor network (SMN) and dorsal attentional network (DAN). Sliding window and k-means clustering analyses were used to identify dFNC patterns and temporal properties in each subject. We compared sFNC and dFNC differences between the StD and HCs groups. Relationships between changes in FNC strength, temporal properties, and neurophysiological score were evaluated by Spearman's correlation analysis. The sFNC analysis revealed decreased FNC strength in StD individuals, including the DMN-CEN, DMN-SMN, SMN-CEN, and SMN-DAN. In the dFNC analysis, 4 reoccurring FNC patterns were identified. Compared to HCs, individuals with StD had increased mean dwell time and fraction time in a weakly connected state (state 4), which is associated with self-focused thinking status. In addition, the StD group demonstrated decreased dFNC strength between the DMN-DAN in state 2. sFNC strength (DMN-ECN) and temporal properties were correlated with HAMD-17 score in StD individuals (all p < 0.01). Our study provides new evidence on aberrant time-varying brain activity and large-scale network interaction disruptions in StD individuals, which may provide novel insight to better understand the underlying neuropathological mechanisms.

Perceived organizational support for strengths use and its impact on nurses' job performance: The mediating roles of control beliefs about stress and optimism.

This study explores how perceived organizational support for strengths use influences nurses' job performance, specifically examining the mediating effects of control beliefs about stress and optimism. Identifying factors that enhance job performance is crucial in the demanding field of nursing. Previous research has highlighted the positive impact of perceived organizational support for strengths use on job performance. Conducted between May and October 2023, this study involved 653 nurses from various hospital settings across three Chinese provinces. A combination of convenience and snowball sampling methods ensured a representative sample. Questionnaires distributed via an online platform measured variables including perceived organizational support for strengths use, control beliefs about stress, optimism, and job performance. Data analysis utilized SPSS-25 and the PROCESS macro, with correlation and regression analyses examining the relationships between perceived organizational support for strengths use, control beliefs about stress, optimism, and job performance. Perceived organizational support for strengths use positively correlates with control beliefs about stress, optimism, and job performance. Control beliefs about stress and optimism serve as mediators in the relationship between perceived organizational support for strengths use and job performance, both independently and sequentially, with optimism being the more potent mediator. This study demonstrates that control beliefs about stress and optimism independently and sequentially mediate the relationship between perceived organizational support for strengths use and job performance among nurses. This research underscores the importance of creating a work environment that leverages nurses' strengths and fosters their ability to manage stress and maintain optimism in the face of workplace challenges. Such an environment can significantly enhance job performance and overall well-being among nurses.

TGFβ2 Promotes the Construction of Fibrotic and Immunosuppressive Tumor Microenvironment in Pancreatic Adenocarcinoma: A Comprehensive Analysis.

Pancreatic adenocarcinoma (PAAD) was characterized by dense fibrotic stroma and immunosuppressive tumor microenvironment (TME). TGFβ signaling pathways are highly activated in human cancers. However, the role of TGFβ2 in TME of PAAD remains to be elucidated. In this study, we showed that TGFβ2 was expressed at a relatively high level in PAAD tissues or cancer cells. Moreover, its high expression predicted unfavorable prognosis. In PAAD, gene set enrichment analysis showed that TGFβ2 correlated positively with leukocyte transendothelial migration, but negatively with aerobic metabolism, including oxidative phosphorylation. Results in Tumor and Immune System Interaction Database showed that TGFβ2 correlated with the infiltration of tumor-associated macrophages (TAMs), which could be attributed to that TGFβ2 promote CCL2 expression in PAAD. Moreover, correlation analysis showed that TGFβ2 could trigger cancer-associated fibroblasts (CAFs) activation in PAAD. The drug sensitivity analysis may indicate that patients with TGFβ2 high expression have higher sensitivity to chemotherapeutics, but the sensitivity to targeted drugs is still controversial. TGFβ2 could promote expansion of CAFs and infiltration of TAMs, thus participating in the construction of a fibrotic and immunosuppressive TME in PAAD. Targeting TGFβ2 could be a promising therapeutic approach, which needs to be elucidated by clinical and experimental evidences.

Effect of Soil Tillage Systems and Crop Seasonality on the Sediment Geochemical Properties Transferred into a Headwater: A Case of Study in Tobacco Plantation

ABSTRACT The global impacts of agricultural land conversion on soil erosion and pollution, particularly in tobacco cultivation areas, are well-recognized as significant contributors to soil degradation. These areas are identified as hotspots for environmental concerns due to practices that lead to increased erosion and pollution. From this perspective, this case of study explores fine sediment samples from two areas with tobacco cultivation under different tillage systems and seasonal variations, transport into a headwater, and evaluates, on a local scale: (1) the impact of tillage systems on the geochemical signature of sediments; (2) if whether crop seasonality affects these sediment geochemical signatures. The Conventional Ridge Tillage (CRT) system involves extensive soil exposure and machinery for soil management, while the Mulch Ridge Tillage (MRT) system prioritizes soil conservation and relies on herbicides for weed control. The analytical methodology used to assess the sample element characteristics was Energy Dispersive X-ray Fluorescence (EDXRF). It was applied on the twenty fine sediments (ten of harvest and ten of inter-harvest season of tobacco) to quantitatively assess their inorganic composition. Additionally, Pearson correlation analysis, Hierarchical Cluster Analysis (HCA), and Principal Component Analysis (PCA) were applied on the EDXRF data to highlight the similarities and, thus, providing information to assess the complex data clustering patterns. As a result, the sediment compositions from the two studied soil systems are not similar. The PCA showed that the CRT sediments are characterized by the P, S, K, Ca, and Mn content, presenting a geochemical signature related to manure and fertilizer compared to the MRT, which is correlated with Al, Ti, Fe, Cu, and Zn contents, exhibiting a geochemical signature characterized by the natural soil composition. Therefore, the sediment geochemical signatures might be affected by two phases in the study area: a) tillage system characteristics and b) seasonal soil erosion. These findings underscore the importance of managing soil nutrients to mitigate soil pollution and nutrient exportation to aquatic systems. Moreover, the results emphasize the recommendations for sustainable agricultural practices in tobacco-growing areas to protect environmental quality.

A study on the related influencing factors of the quality of bowel preparation and the compliance of middle-aged and elderly patients for colonoscopy.

Quality of bowel preparation and patient compliance are among the most important indicators to assess the quality of colonoscopy. To investigate the independent factors associated with the quality of bowel preparation in subjects undergoing colonoscopy and its impact on compliance. A total of 329 patient records were collected and were divided into an adequate bowel preparation group (272 cases) and an inadequate bowel preparation group (57 cases), or a compliant group (260 cases) and a non-compliant group (69 cases), based on bowel preparation quality or compliance. The quality of bowel preparation is evaluated using the Boston Bowel Preparation Scale. The comfort level of subjects during bowel preparation is assessed using the Kolcaba General Comfort Questionnaire (GCQ). Subjects' compliance was assessed according to a self-developed compliance questionnaire. Prediction analyses were conducted to identify factors associated with the quality of bowel preparation and compliance. Age, bowel preparation duration, history of bowel inadequacy, and laxative dosage showed statistical differences between the adequate and inadequate bowel preparation groups (P < 0.05). Age, bowel preparation duration, and laxative dosage were independent influencing factors of bowel preparation quality. Correlation analysis showed that GCQ scores was significantly negatively correlated with age, bowel preparation duration, laxative dose, defecation frequency, and colonoscopy duration (r < 0, P < 0.05), and positively correlated with sleep duration (r > 0, P < 0.05). In addition, age, gender, bowel preparation duration, and laxative dosage showed statistical differences between the compliant and non-compliant groups (P < 0.05). Logistic regression analysis revealed that age, bowel preparation duration, and laxative dosage were independent influencing factors of bowel preparation compliance. Age and bowel preparation duration were independent influencing factors for bowel preparation adequacy and compliance. Age, bowel preparation duration, and laxative dosage are independent influencing factors for bowel preparation adequacy and compliance among patients undergoing colonoscopy at the First Affiliated Hospital, School of Medicine, Zhejiang University. It is recommended that a one-day low-residue diet combined with a 2000 mL laxative dosage be used as the bowel preparation protocol for the general colonoscopy population.

Integrative analysis of transcriptome and phytohormones reveals new genes network involved in shoot apical meristem development in maize under blue and red light

Blue and red light play a significant role in regulating transcriptional expression, phytohormone levels, and gene signal network reconstruction in the shoot apical meristem. To further elucidate the effects of red and blue light on transcriptional characteristics and phytohormone expression, and to explore signaling pathways and novel genes, we conducted comparative experiments under different light quality treatments. The results are as follows: a total of 22,327 genes were found to be effectively expressed, with a considerable number of alternative splicing events occurring concurrently. Furthermore, 1063 differentially expressed genes were identified, primarily associated with transcriptional variations resulting from the transition from blue light to red light. These differentially expressed genes are predominantly involved in KEGG annotations related to photosynthesis, DNA replication and carbon metabolism. The findings from targeted metabolism analysis reveal significant variations in 45 phytohormones, including ABA, auxin, CK, ETH, GA, JA, and SA. Correlation analysis between transcription and metabolism further indicates that IAA.Glc, IAA.Glu, TRP, mT9G, and GA53 show the strongest correlation with differentially expressed genes, with genes ssu1, ssu2, pep1, me3, and hsp90 displaying a significant relationship. Additionally, in the protein–protein interaction network, three novel genes (LOC100286132, LOC100510780, and LOC103653934) were identified as significant responding to the regulation of blue and red light. Following protein function analysis, the proteins were provisionally identified as ubiquitin conjugating enzyme-like, OXIDATIVE STRESS 3LIKE 2-like, and Ribosomal L 18p/L5e, respectively. Conclusively, it is depicted that the most significant impact of transitions between red light, blue light, and two light qualities lies in the transcriptional process of shot apical meristem of the C4 plant maize. This process is intricately linked to nitrogen availability, carbon dioxide assimilation capacity, and the stimulatory effects of auxin, cytokinin, and gibberellin. The expression of the putative L 18/L5e in blue and BTR light conditions may enhance transcript and synthesis capabilities of ribosome.

Correlation Analysis and Predictive Model Construction of Metabolic Syndrome, Complete Blood Count-Derived Inflammatory Markers, and Overall Burden of Cerebral Small Vessel Disease

BackgroundThe high burden of cerebral small vessel disease (CSVD) on neuroimaging is a significant risk factor for stroke, cognitive dysfunction, and emotional disorders. Currently, there is a lack of studies investigating the correlation between metabolic syndrome (MetS), complete blood count-derived inflammatory markers, and total CSVD burden. This study aims to evaluate the total CSVD imaging load using machine learning (ML) algorithms and to explore further the relationship between MetS, complete blood count-derived inflammatory markers, and CSVD load. MethodsWe included CSVD patients from Xijing Hospital (2012-2022). Univariate and lasso regression analyses identified variables linked to CSVD neuroimaging burden. Six ML models predicted CSVD burden based on MetS and inflammatory markers. Model performance was evaluated using ROCauc, PRauc, DCA, and calibration curves. The SHAP method validated model interpretability. The best-performing model was selected to develop a web-based calculator using the Shiny package. ResultsThe Logistic regression model outperformed others in predicting CSVD burden. The model incorporated MetS, neutrophil-to-lymphocyte ratio (NLR), homocysteine (Hcy), age, smoking status, cystatin C (CysC), uric acid (UA), and prognostic nutritional index (PNI). ConclusionMetS, NLR, Hcy and CSVD high load were positively correlated, and the Logistic regression model could accurately predict the total CSVD load degree.

Probabilistic ductile deformation limit state prediction of monolithic exterior shear keys based on quantile regression machine learning techniques

Shear strength and ductile deformation capacity of monolithic exterior shear keys play important roles on the seismic behavior of highway bridges. Improving the ductility of the shear key through reasonable design could effectively restrict superstructure displacement and minimize damage to pier columns. However, most existing studies primarily focus on evaluating the shear strength and damage mechanisms of shear keys, with limited attention given to analytical models for assessing ductile deformation capacity. To this end, this study proposes a method that combines quantile regression and machine learning techniques to predict the ductile deformation limit states of shear keys. The proposed numerical modeling method for shear keys is validated using the experimental data on lateral load-displacement curves. On this basis, Latin hypercubic sampling and joint simulation are utilized to establish the ductile deformation limit state database. The ductile deformation limit states of shear keys are characterized by their lateral displacements in three distinct damage states. The main influencing factors of each limit states are investigated by correlation analysis. Three quantile regression machine learning models are trained and constructed to conduct point and interval prediction for the ductile deformation limit states. All three models, particularly the Gaussian process quantile regression model, are proven to demonstrate exceptional prediction accuracy and uncertainty quantification. Experimental data validation confirms that these models outperform the prediction accuracy of existing simplified models.

Associations Between Drug Overdose Mortality and Recovery Ecosystems in the United States: A County-Level Analysis Using a Novel Index.

Communities with robust recovery ecosystems could reduce negative outcomes associated with substance use disorders (SUDs) and facilitate the recovery process. This cross-sectional study examined the relationship between drug overdose mortality rates in the United States and the strength of county-level recovery ecosystems, as measured by the Recovery Ecosystem Index (REI). The REI assesses the strength of county-level recovery ecosystems in the United States. Comprised of 14 indicators across 3 component classes, overall and component scores ranging from "one" (strongest) to "five" (weakest) were calculated for each county using standardized values of the indicators. County-level analyses included: (1) correlational analyses between drug overdose mortality rates (n = 2076) and REI scores (overall score and by component); and (2) quadrant analysis (n = 2076), dividing counties based on their drug overdose mortality rates and overall REI scores. Drug overdose mortality rates were inversely related to REI overall, SUD treatment component, and continuum of SUD support component scores, indicating that lower (stronger) scores corresponded to higher rates. Conversely, REI infrastructure and social component scores were positively related to rates. Counties were relatively evenly distributed across quadrants, with 26% (n = 537) with a strong REI score and high overdose mortality rate, 24% (n = 489) with a strong REI score and low overdose mortality rate, 20% (n = 409) with a weak REI and high overdose mortality rate, and 31% (n = 641) with a weak REI and low overdose mortality rate. REI scores were generally inversely associated with drug overdose mortality rates in US counties, suggesting that communities have stronger recovery systems and services as the burden of SUD increases. Given relative variation in the scale of drug overdose mortality and strength of recovery ecosystems among counties, results could guide the identification of communities where the need for expanded recovery systems and services may be particularly critical.

Natural Health Community Program and Well-Being: An Uncontrolled Study of Women Survivors of Domestic Violence.

The purpose of this study was to evaluate a local natural healing service program and to explore how engagement in natural healing services related to the well-being of survivors of domestic violence. Using longitudinal secondary data, we conducted t-tests, regression, and correlation analysis on three measures (hope, distress, and empowerment) that were completed by the participants (N = 31). We provided evidence of the positive impact of a community-based natural healing services program on the well-being of survivors of domestic violence, specifically their sense of hope. This research represents the potential for natural healing services provided at the community level.

Olfactory-chemical establishment using odour wheels and fingerprints to manage odor pollution for the petrochemical industry

The odor nuisance may cause major environmental issues, so identifying the odor characteristics is important for odor management and traceability in the petrochemical industry. In this study, odour wheels and fingerprints were applied to manage odor pollution in the petrochemical industry. First, the odor profile method and portable electronic nose evaluation were applied to analyze the flavour sensory profiles of five upstream and downstream petrochemical plants, in order to grasp the odor natures of plants. Second, 375 organized and unorganized samples of 5 plants were analyzed by gas chromatography-mass spectrometry (GC–MS) technology, and a total of 583 odorants were obtained, including sulfur compounds, alcohols, esters, aldehydes, ketones, acids, alkanes, alkenes, halogenated hydrocarbons, aromatic hydrocarbons, nitrogen compounds, and other compounds. Third, the key odorants were identified by gas chromatography-olfactory (GC-O) and odor activity value (OAV) analysis. Fourth, the fingerprint spectras were developed by the identification of key odorants and process sources through principal component analysis. For plant A, 21 odorants were confirmed, including naphthalene, 1-methylnaphthalene, 2-methylnaphthalene, 1-methylindene, and 2-methylindene. Methyl methacrylate, acetophenone, isobutene, 4-vinyl-1-cyclohexene, acrylonitrile, and styrene were key element for plant B. The fingerprint factor of plant C had 20 odorants, including methanol, butanol, 2-ethylhexanol, acetic acid, and ammonia. And there were 21 odorants for plant D and 14 odorants for plant E, respectively, with similar substance types, including 2-ethyl-2-hexenal, 3-methyl-4-heptanone, isobutyl butyrate, and 1,2,3,5-tetraethylbenzene. Finally, the odor wheels were established by the correlation analysis between odorants and malodor, and compounds in fingerprint spectra weaker related to malodor of plants were removed. Hence, the characteristic odorants of each plant were further clarified, and the odors were associated with compounds, achieving rapid diagnosis and traceability of odor pollution in the petrochemical park. This provided new ideas and technical methods for odor pollution monitoring and identification.

DDD-costs have a strong influence on antibacterial drug prescription in Germany: a differentiated correlation analysis from 1985 to 2022.

Antibacterial drugs are vital in modern medicine, and understanding the factors influencing their prescriptions is essential for maintaining their effectiveness and accessibility. This study investigates the hypothesis that costs significantly impact the prescriptions of antibacterial drugs, a factor previously underrecognized. To investigate this, we conducted correlation analyses on defined daily dose (DDD-) prescriptions and DDD-costs for the 15 most prescribed antibacterial drugs in Germany in 2022, using data from the Arzneimittelverordnungsreport (Drug Prescription Report)(1985-2022). The analysis focused on the periods 1985-2022, 1985-2011, and 2012-2022. Our findings revealed significant correlations between DDD-prescriptions and -costs for nearly all drugs over the entire period (1985-2022), with strong negative correlations for amoxicillin (- 0.941), cefuroxime axetil (- 0.900), clindamycin (- 0.800), nitrofurantoin (- 0.895), and cefaclor (- 0.819). From 1985 to 2011, only significant negative correlations were observed. In 2012-2022, significant correlations included both negative and positive, with strong positive correlations for ciprofloxacin (0.950) and clarithromycin (0.962). Overall, DDD-costs showed a persistent and strong correlation with DDD-prescriptions, particularly in the earlier period. This influence appears to diminish slightly in recent years, suggesting other factors might become more significant as DDD-costs plateau. Notably, amoxicillin, amoxicillin clavulanic acid, and nitrofurantoin consistently exhibited strong cost-prescription correlations throughout the entire period. While correlation does not imply causation, the significant and strong correlations, coupled with logical explanations, support the hypothesis that costs area primary factor in prescribing patterns. Further research is needed to establish causality and examine other potential systemic factors affecting antibacterial drug prescriptions.

Predicting the Prognosis and Immunotherapeutic Response of Triple-Negative Breast Cancer by Constructing a Prognostic Model Based on CD8+ T Cell-Related Immune Genes

ObjectiveTriple-negative breast cancer (TNBC) poses a significant challenge for treatment efficacy. CD8+ T cells, which are pivotal immune cells, can be effectively analyzed for differential gene expression across diverse cell populations owing to rapid advancements in sequencing technology. By leveraging these genes, our objective was to develop a prognostic model that accurately predicts the prognosis of patients with TNBC and their responsiveness to immunotherapy. MethodsSample information and clinical data of TNBC were sourced from The Cancer Genome Atlas and METABRIC databases. In the initial stage, we identified 67 differentially expressed genes associated with immune response in CD8+ T cells. Subsequently, we narrowed our focus to three key genes, namely CXCL13, GBP2, and GZMB, which were used to construct a prognostic model. The accuracy of the model was assessed using the validation set data and receiver operating characteristic (ROC) curves. Furthermore, we employed various methods, including Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, immune infiltration, and correlation analyses with CD274 (PD-L1) to explore the model's predictive efficacy in immunotherapeutic responses. Additionally, we investigated the potential underlying biological pathways that contribute to divergent treatment responses. ResultsWe successfully developed a model capable of predicting the prognosis of patients with TNBC. The areas under the curve (AUC) values for the 1-, 3-, and 5-year survival predictions were 0.618, 0.652, and 0.826, respectively. Employing this risk model, we stratified the samples into high- and low-risk groups. Through KEGG enrichment analysis, we observed that the high-risk group predominantly exhibited enrichment in metabolism-related pathways such as drug and chlorophyll metabolism, whereas the low-risk group demonstrated significant enrichment in cytokine pathways. Furthermore, immune landscape analysis revealed noteworthy variations between (PD-L1) expression and risk scores, indicating that our model effectively predicted the response of patients to immune-based treatments. ConclusionOur study demonstrates the potential of CXCL13, GBP2, and GZMB as prognostic indicators of clinical outcomes and immunotherapy responses in patients with TNBC. These findings provide valuable insights and novel avenues for developing immunotherapeutic approaches targeting TNBC.

Correlation analysis between serum free triiodothyronine and C-peptide-based insulin resistance index in euthyroid adults

Objective: To explore the correlation between serum free triiodothyronine (FT3) and C-peptide-based insulin resistance index (HOMA2 IR-CP) in euthyroid adults. Methods: A cross-sectional study. The clinical data of euthyroid adult participants who underwent physical examination in the Second Medical Center of Chinese PLA General Hospital from January to December in 2019 were retrospectively analyzed. According to the HOMA2 IR-CP level, the participants were divided into HOMA2 IR-CP>2.18 group (n=3 463) and HOMA2 IR-CP≤2.18 group (n=8 204). Univariate Pearson correlation analysis and multivariate logistic regression analysis were used to analyze the correlation between FT3 and HOMA2 IR-CP. The interaction model was used to analyze the interaction between FT3 and related factors, and the dose-response relationship between continuity variable FT3 and HOMA2 IR-CP was explored by using restricted cubic spline plots. Results: A total of 11 667 euthyroid adult participants aged (50.7±10.0)years were recruited according to the inclusion and exclusion criteria, with 7 756 males and 3 911 females. The proportion of males, body mass index, systolic blood pressure, glycated hemoglobin A1c, fasting plasma glucose, triglyceride, hemoglobin, alanine aminotransferase and FT3 levels in HOMA2 IR-CP>2.18 group were significantly higher than those in HOMA2 IR-CP≤2.18 group (all P<0.05). The levels of low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and free thyroxine in HOMA2 IR-CP>2.18 group were lower than those in HOMA2 IR-CP≤2.18 group (all P<0.001). Univariate Pearson correlation analysis showed that FT3 was associated with HOMA2 IR-CP (r=0.21, P<0.001). Multivariate logistic regression analysis suggested an association between FT3 and HOMA2 IR-CP after adjusting for confounding factors(Pfor trend<0.001). Subgroup analysis showed an association between FT3 and HOMA2 IR-CP in different subgroups of gender, age and glucose metabolism status (Pfor trend<0.05). Multiplication interaction analysis suggested that there was an interaction between FT3 and age (Pinteraction<0.001). Restricted cubic spline model analysis demonstrated that the correlation between FT3 and HOMA2 IR-CP was linear (Poverall<0.001, Pnonlinear=0.479). Conclusions: There is a correlation between serum FT3 and HOMA2 IR-CP in euthyroid adults. With the increase of FT3 level, insulin resistance increases gradually.

The brain-protective mechanism of fecal microbiota transplantation from young donor mice in the natural aging process via exosome, gut microbiota, and metabolomics analyses

The natural aging process is accompanied by changes in exosomes, gut microbiota, and metabolites. This study aimed to reveal the anti-aging effect and mechanisms of fecal microbiota transplantation (FMT) from young donors on the natural aging process in mice by analyzing exosomes, gut microbiota, and metabolomics. Aging-relevant telomeric length, oxidative stress indexes in brain tissue, and serum cytokine levels were measured. Flow analysis of T-regulatory (Treg), CD4+, and CD8+ cells was performed, and the expression levels of aging-related proteins were quantified. High-throughput sequencing technology was used to identify differentially expressed serum exosomal miRNAs. Fecal microbiota was tested by 16S rDNA sequencing. Changes in fecal metabolites were analyzed by UPLC-Q-TOF/MS. The results indicated that the expression of mmu-miR-7010-5p, mmu-miR-376b-5p, mmu-miR-135a-5p, and mmu-miR-3100-5p by serum exosomes was down-regulated and the abundance of opportunistic bacteria (Turicibacter, Allobaculum, Morganella.) was decreased, whereas the levels of protective bacteria (Akkermansia, Muribaculaceae, Helicobacter.) were increased after FMT. Metabolic analysis identified 25 potential biomarkers. Correlation analysis between the gut microbiota and metabolites suggested that the relative abundance of protective bacteria was positively correlated with the levels of spermidine and S-adenosylmethionine. The study indicated that FMT corrected brain injury due to aging via lipid metabolism, the metabolism of cofactors and vitamins, and amino acid metabolism.

Elucidation of anti-pneumonia pharmacodynamic material basis and potential mechanisms of Xiebai San by combining spectrum–efficacy relationship and surface plasmon resonance

Ethnopharmacological relevanceXiebai San (XBS), a classic Chinese prescription, has been used for the clinical treatment of pneumonia-related diseases for thousands of years. However, the anti-pneumonia pharmacodynamic material basis of XBS and its underlying mechanisms remain unclear. Aim of the studyThis study aimed to comprehensively investigate and verify the anti-pneumonia pharmacodynamic material basis and mechanisms of XBS. Materials and methodsThis study explored the anti-pneumonia activity and key pneumonia targets of XBS in lipopolysaccharide (LPS)-induced zebrafish and RAW264.7 cells in vivo and in vitro through transcriptomics, western blotting, and reverse transcription–quantitative polymerase chain reaction (RT–qPCR). The chemical fingerprint of XBS was established using high-performance liquid chromatography, and the similarities and areas of characteristic peaks of 15 batches of XBS were analyzed. Based on the spectrum–efficacy relationship, the potential anti-inflammatory components were screened according to their peak areas and efficacy using principal component analysis (PCA), bivariate correlation, and partial least squares regression analysis. Active components that bind to core targets were further screened based on surface plasmon resonance (SPR). The binding mode of proteins and components was simulated via molecular docking, which enabled the identification of the primary active components of XBS, thereby elucidating its anti-pneumonia properties. Finally, the anti-inflammatory activities of these components were verified in vitro. ResultsXBS decreased neutrophil aggregation in zebrafish and nitric oxide (NO) secretion in RAW264.7 cells as well as suppressed the release of downstream inflammatory cytokines such as iNOS, TNF-α, IL-1β, IL-18, and CXCL10 related to TNF and JAK–STAT signaling pathways. The phosphorylation of IκBα, Akt, and Stat3 was alleviated after XBS in cells. The fingerprint similarities of 15 batches of XBS ranged from 0.381 to 0.994, with a large difference. A total of 15 characteristic peaks were identified, and the relative standard deviation of their peak areas ranged from 24.1% to 70.7%. The results of in vitro anti-inflammatory activities of 15 batches of XBS showed that all samples inhibited the expression levels of NO and nine inflammatory markers. The anti-inflammatory index of 15 batches of XBS was determined to be 0.69–0.96 based on transformation of the anti-inflammatory rate and composite index method via PCA. The spectrum–efficacy relationship model of 15 characteristic peak areas and the anti-inflammatory index showed that 7 main potential active components were related to the anti-inflammatory activity of XBS. Moreover, four components (mulberroside A, isoquercitrin, liquiritigenin, and glycyrrhizic acid) screened based on SPR had different affinities toward TNFR1, Akt1, and Stat3 proteins, and the binding modes were elucidated via molecular docking. Finally, in LPS-induced RAW264.7 cells, all four active components (at a concentration of 60 μM) significantly inhibited the expression levels of NO and inflammatory markers. ConclusionsBased on the comprehensive strategy of spectrum–efficacy relationship and SPR, mulberroside A, isoquercitrin, liquiritigenin, and glycyrrhizic acid were identified as the primary pharmacodynamic active components involved in the anti-pneumonia activity of XBS and were found to intervene in TNF and JAK–STAT signaling pathways.

Examining audiologist candidates' self-esteem and professional self-esteem

BackgroundSelf-esteem is an individual's perception of themselves. Professional self-esteem is defined as the individual's perception of worthiness regarding their preferred profession. The research aims to examine the relationship between the self-esteem and professional self-esteem of Audiology department students and raise awareness of this issue.Material and MethodIn our study, 532 students in the Audiology undergraduate department were included. Professional Self-Esteem and Self-Esteem questionnaires were delivered to the students online via Google Forms, using snowball sampling, in social media groups of the Audiology undergraduate students. Data were analyzed using Spearman correlation analysis, Mann Whitney U, and Kruskal Wallis Test. p < 0.05 was accepted as significance value.ResultsAccording to the results, it has been observed that there is a weak and significant positive correlation between the professional self-esteem of the audiologist candidates and their total self-esteem scores (p < 0.05). Self-esteem and professional self-esteem scores of those who chose the profession willingly were significantly higher than those who did not choose the profession willingly (p < 0.05). As the grade level increased, professional self-esteem decreased significantly (p < 0.05). There was no significant difference between the scores in both scales according to income, university type, and gender (p > 0.05).ConclusionAs a result, it was observed that as the self-esteem of the audiologist candidates increased, their professional self-esteem increased. Also, as the class level increased, their professional self-esteem decreased.