To ascertain the nuances and probe potential explanations, we compared and contrasted the CSR reporting of Chinese and American pharmaceutical companies. Our model selection process involved the top 500 pharmaceutical companies, selected from Torreya's (a global investment bank) ranking of the world's 1000 most valuable pharmaceutical companies. Following this, we collected the 2020 corporate social responsibility reports from 97 Chinese and 94 American pharmaceutical corporations. To analyze these reports, software including ROST Content Mining 60 and Gephi 092 was utilized. Analysis of Chinese and American pharmaceutical corporate social responsibility reports resulted in the creation of a high-frequency word list, a semantic network diagram, and a high-frequency word centrality scale. Environmental protection information received particular attention in the corporate social responsibility reports of Chinese pharmaceutical companies, which employed a two-pronged structure focusing on two key themes. American pharmaceutical companies delivered a presentation on corporate social responsibility information disclosures. This presentation utilized a humanistic care perspective and structured itself around three centers and two themes. Corporate social responsibility reporting may differ between Chinese and American pharmaceutical companies due to variations in strategic development, regulatory compliance requirements, varying societal expectations, and contrasting ideas of corporate responsibility. This study proposes strategies for Chinese pharmaceutical enterprises to improve their corporate social responsibility (CSR) at three crucial levels: policy decisions, internal management, and social interactions.

The study's background and goals focus on the unresolved questions regarding escitalopram's applicability and the impediments to its use in patients suffering from functional gastrointestinal disorders (FGIDs). The study aimed to explore the usability, safety profile, efficacy, and limitations of escitalopram in the management of FGIDs in the Saudi community. intracameral antibiotics The patients and methods section described 51 participants treated with escitalopram for irritable bowel syndrome (n=26), functional heartburn (n=10), globus sensation (n=10), or a combination of these conditions (n=5). Before and after treatment, we measured disease severity changes using the irritable bowel syndrome severity scoring system (IBS-SSS), the GerdQ questionnaire, and the Glasgow-Edinburgh Throat Scale (GETS). A median age of 33 years was observed, encompassing a 25th-75th percentile range of 29-47 years, and 26 individuals (50.98%) were male. Side effects were observed in 41 patients (8039%), but the vast majority of these side effects were deemed to be mild in nature. Xerostomia (2353%), nausea/vomiting (2157%), drowsiness/fatigue/dizziness (549%) and weight gain (1765%) were the most prevalent side effects. Treatment resulted in a marked reduction in IBS-SSS scores, from an initial value of 375 (255-430) to 90 (58-205) post-treatment, with statistical significance (p < 0.0001). A statistically significant difference in GerdQ score was observed between pre-treatment (12, 10-13) and post-treatment (7, 6-10) measurements, with a p-value of 0.0001. The GETS score exhibited a noteworthy change, decreasing from 325 (21-46) prior to treatment to 22 (13-31) following treatment, a statistically significant alteration (p = 0.0002). Thirty-five patients declined the prescribed medications, and an additional seven patients ceased their medication regimen. Hesitancy towards taking psychiatric medications, combined with a lack of trust in their effectiveness for functional disorders, possibly contributed to the low compliance rates (n = 15). Ultimately, escitalopram demonstrates potential as a secure and effective intervention for functional gastrointestinal ailments. Addressing factors contributing to non-compliance may lead to enhanced treatment results.

Through a meta-analytical approach, this study explored whether curcumin could prevent myocardial ischemia/reperfusion (I/R) injury in animal models. Methodological studies, spanning from the databases' inception to January 2023, were systematically culled from the following databases: PubMed, Web of Science, Embase, China's National Knowledge Infrastructure (CNKI), Wan-Fang database, and VIP. In order to establish methodological quality, the SYRCLE's RoB tool was used. In cases of substantial heterogeneity, sensitivity and subgroup analyses were carried out. A funnel plot was employed to evaluate publication bias. In this meta-analysis, 37 animal studies involving 771 animals were evaluated. The quality of methodology within these studies spanned from 4 to 7. Results showed a substantial improvement in myocardial infarction size following curcumin treatment, reflected by a standardized mean difference (SMD) of -565; this was accompanied by a 95% confidence interval (CI) of -694 to -436; a statistically significant p-value (p < 0.001); and a high level of heterogeneity (I2 = 90%). selleck products The stability and reliability of the results were demonstrated through sensitivity analysis of infarct size. Nevertheless, the funnel plot exhibited asymmetry. Species variations, animal model types, dose amounts, administration procedures, and treatment lengths were included in the subgroup analysis. The results indicated a statistically notable difference in the effects between the subgroups, reflecting the impact of varying doses. Furthermore, curcumin treatment enhanced cardiac function, reduced myocardial injury enzyme levels, and mitigated oxidative stress in animal models of myocardial ischemia-reperfusion injury. The funnel plot highlighted a publication bias phenomenon affecting creatine kinase and lactate dehydrogenase measurements. A meta-analytic approach was employed to examine the collective effects of inflammatory cytokines and apoptosis indices, as our final step. Treatment with curcumin, as the results suggest, resulted in a decrease in both serum inflammatory cytokine levels and the myocardial apoptosis index. The meta-analysis findings underscore curcumin's potential for effectively treating myocardial I/R injury in animal models. Further investigation and confirmation of this conclusion are imperative, requiring large animal model studies and human clinical trials. The registration of the systematic review, with identifier CRD42022383901, is documented on the platform https//www.crd.york.ac.uk/prospero/.

Exploring the potential efficacy of a medication is a valid approach to drug development, potentially accelerating the process and minimizing the financial burden. Several recently proposed computational drug repositioning methods now utilize multi-feature learning for the prediction of potential target-drug associations. GMO biosafety Despite the abundant information in scientific publications, translating it into improved drug-disease association predictions presents a considerable obstacle. By combining data from public databases and literary semantic features, we developed a novel drug-disease association prediction method called Literature Based Multi-Feature Fusion (LBMFF). It effectively incorporates known drugs, diseases, side effects, and associated targets. Employing a pre-trained and fine-tuned BERT model, semantic information from literary texts was extracted to determine the similarity between works. A graph convolutional network with an attention mechanism was subsequently applied to the constructed fusion similarity matrix, revealing the embedded representations of drugs and diseases. In drug-disease association prediction, the LBMFF model excelled, yielding an AUC value of 0.8818 and an AUPR value of 0.5916. Across the same test datasets, Discussion LBMFF demonstrated superior predictive capability, with relative performance gains of 3167% and 1609% over the second-best results, when benchmarked against single feature techniques and seven cutting-edge prediction methods. Case studies have empirically demonstrated that LBMFF can identify fresh correlations, thus enhancing the speed of drug discovery. The LBMFF benchmark dataset and source code are accessible via the GitHub repository: https//github.com/kang-hongyu/LBMFF.

In women, breast cancer stands as the first malignant tumor, and its occurrence is progressively rising annually. Although chemotherapy is a widely used approach in treating breast cancer, the capacity of breast cancer cells to resist these drugs is a considerable impediment to achieving successful breast cancer therapy. At present, the study of reversing drug resistance in solid tumors, such as breast cancer, demonstrates peptides as advantageous owing to their high selectivity, effective tissue penetration, and good biocompatibility. Studies have shown that certain peptides can circumvent the resistance of tumor cells to chemotherapy, thereby effectively controlling the growth and spread of breast cancer cells. We examine how different peptides overcome breast cancer resistance by influencing cancer cell apoptosis, inducing non-apoptotic cancer cell death mechanisms, inhibiting cancer cell DNA repair, improving the tumor microenvironment, hindering drug efflux, and promoting drug uptake. A comprehensive analysis of peptide-mediated strategies for reversing breast cancer drug resistance is presented herein, with the anticipation that these peptides will be instrumental in achieving clinical breakthroughs in chemotherapy treatment and improving patient survival.

Artemether, the O-methyl ether prodrug of dihydroartemisinin, is a foundational first-line antimalarial drug in the management of malaria infections. Significant challenges arise in determining artemether due to its extensive in vivo metabolism to its active form, DHA. The current investigation achieved accurate DHA identification and estimation via mass spectrometric analysis, implemented using a high-resolution liquid chromatography/electrospray ionization-mass spectrometry (LC/ESI-MS) LTQ Orbitrap hybrid mass spectrometer. Plasma samples from healthy volunteers were used to prepare spiked plasma, which was then extracted using a 1 mL solution composed of dichloromethane and tert-methyl.