Mitigate cross-market competition caused by the risk of uncertainty and improve firm performance through business intelligence.

In the face of various risks and uncertainties including political instability, technological advancements, and natural disasters, businesses involved in cross-market activities are encountering a more competitive environment. This study investigates the relationship between competitive intensity, business intelligence, internal process efficiency, and the performance of small and medium-sized manufacturing enterprises in China. By incorporating the Technology-Organization-Environment (TOE) framework and Dynamic Capabilities Theory, a research model is developed to demonstrate that competitive intensity improves firms' performance through the utilization of business intelligence capabilities and internal process efficiency. Through the use of a structural equation model, data collected from 15 industrial parks in Henan province, China, involving 429 participants, was analyzed. The findings show a positive correlation between competitive intensity and business intelligence sensing capability (both internal and external). The impact of business intelligence sensing capability on the performance of small and medium-sized manufacturing enterprises is shown to be mediated through internal process efficiency. Our study reveals the mediating roles of business intelligence capability and internal process efficiency in improving organizational performance among Chinese small and medium-sized manufacturing enterprises. This research not only fills gaps in business intelligence research from a management perspective but also contributes to the literature on the interactions among competitive intensity, business intelligence, internal processes, and organizational performance. It also sheds light on the relationship between competitive intensity and organizational performance, offering insights for companies involved in cross-market activities. By highlighting the importance of business intelligence capabilities in adapting to environmental influences, this study offers practical guidance for enterprise digital transformation efforts.

Development of a physiologically based pharmacokinetic model for levetiracetam in patients with renal impairment to guide dose adjustment based on steady-state peak/trough concentrations.

Levetiracetam may cause acute renal failure and myoclonic encephalopathy at high plasma levels, particularly in patients with renal impairment. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict levetiracetam pharmacokinetics in Chinese adults with epilepsy and renal impairment and define appropriate levetiracetam dosing regimen.PBPK models for healthy subjects and epilepsy patients with renal impairment were developed, validated, and adapted. Furthermore, we predicted the steady-state trough and peak concentrations of levetiracetam in patients with renal impairment using the final PBPK model, thereby recommending appropriate levetiracetam dosing regimens for different renal function stages. The predicted maximum plasma concentration (Cmax), time to maximum concentration (Tmax), area under the plasma concentration-time curve (AUC) were in agreement (0.8 ≤ fold error ≤ 1.2) with the observed, and the fold error of the trough concentrations in end-stage renal disease (ESRD) was 0.77 - 1.22. The prediction simulations indicated that the recommended doses of 1000, 750, 500, and 500 mg twice daily for epilepsy patients with mild, moderate, severe renal impairment, and ESRD, respectively, were sufficient to achieve the target plasma concentration of levetiracetam.

Identification of key ferroptosis-related biomarkers in steroid-induced osteonecrosis of the femoral head based on machine learning.

BACKGROUND: This study was aimed to identify key ferroptosis-related biomarkers in steroid-induced osteonecrosis of the femoral head (SONFH) based on machine learning algorithm. METHODS: The SONFH dataset GSE123568 (including 30 SONFH patients and 10 controls) was used in this study. The differentially expressed genes (DEGs) were selected between SONFH and control groups, which were subjected to WGCNA. Ferroptosis-related genes were downloaded from FerrDb V2, which were then compared with DEGs and module genes. Two machine learning algorithms were utilized to identify key ferroptosis-related genes, and the underlying mechanisms were analyzed by GSEA. Correlation analysis between key ferroptosis-related genes and immune cells was analyzed by Spearman method. The drug-gene relationships were predicted in CTD. RESULTS: Total 2030 DEGs were obtained. WGCNA identified two key modules and obtained 1561 module genes. Finally, 43 intersection genes were identified as disease-related ferroptosis-related genes. After LASSO regression and RFE-SVM algorithms, 4 intersection genes (AKT1S1, BACH1, MGST1 and SETD1B) were considered as key ferroptosis-related gene. The 4 genes were correlated with osteoclast differentiation pathway. Twenty immune cells with significant differences were obtained between the groups, and the 4 key ferroptosis-related genes were correlated with most immune cells. In CTD, 41 drug-gene relationship pairs were finally obtained. CONCLUSIONS: The 4 key ferroptosis-related genes, AKT1S1, BACH1, MGST1 and SETD1B, were identified to play a critical role in SONFH progression through osteoclast differentiation and immunologic mechanisms. Additionally, all the 4 genes had good disease prediction effect and could act as biomarkers for the diagnosis and treatment of SONFH.

CCK2 receptor expression transforms non-tumorigenic human NCM356 colonic epithelial cells into tumor forming cells.

Expression of gastrin and cholecystokinin 2 (CCK(2)) receptor splice variants (CCK(2)R and CCK(2i4sv)R) are upregulated in human colonic adenomas where they are thought to contribute to tumor growth and progression. To determine the effects of ectopic CCK(2) receptor variant expression on colonic epithelial cell growth in vitro and in vivo, we employed the non-tumorigenic colonic epithelial cell line, NCM356. Receptor expression was induced using a retroviral expression vector containing cDNAs for either CCK(2i4sv)R or CCK(2)R. RT-PCR and intracellular Ca(2+) ([Ca(2+)](i)) imaging of RIE/CCK(2)R cells treated with conditioned media (CM) from NCM356 revealed that NCM356 cells express gastrin mRNA and secrete endogenous, biologically active peptide. NCM356 cells expressing either CCK(2)R or CCK(2i4sv)R (71 and 81 fmol/mg, respectively) grew faster in vitro, and exhibited an increase in basal levels of phosphorylated ERK (pERK), compared with vector. CCK(2) receptor selective antagonist, YM022, partially inhibited the growth of both receptor-expressing NCM356 cells, but not the control cells. Inhibitors of mitogen activated protein kinase pathway (MEK/ERK) or protein kinase C (PKC) isozymes partially inhibited the elevated levels of basal pERK and in vitro growth of receptor-expressing cells. Vector-NCM356 cells did not form tumors in nude mice, whereas, either CCK(2) receptor-expressing cells formed large tumors. Autocrine activation CCK(2) receptor variants are sufficient to increase in vitro growth and tumorigenicity of non-transformed NCM356 colon epithelial cells through a pathway involving PKC and the MEK/ERK axis. These findings support the hypothesis that expression of gastrin and its receptors in human colonic adenomas contributes to tumor growth and progression.

Evolution of HIV resistance mutations in patients maintained on a stable treatment regimen after virologic failure.

OBJECTIVE: We compared the rate of emergence of thymidine analogue mutations (TAMs) and major protease inhibitor mutations in adherent patients who remained on stable treatment with a thymidine analogue and/or protease inhibitor after the onset of virologic failure. DESIGN: Follow-up genotypic resistance testing was done using archived plasma obtained from patients having 0 or 1 TAM and/or 0 or 1 major protease inhibitor resistance mutation at the onset of virologic failure. RESULTS: The median duration of observed failure was 691 days. There were 41 thymidine analogue regimens and 34 protease inhibitor regimens; concomitant ritonavir was used 4 times. New major protease inhibitor mutations emerged more rapidly than did new TAMs (P = 0.0019); new TAMs emerged more rapidly in thymidine analogue regimens that did not include lamivudine (P = 0.0073). The emergence of TAMs and major protease inhibitor mutations did not differ if lamivudine was not part of the thymidine analogue regimen. The evolution of CD4 cell counts and plasma viral loads (pVLs) during virologic failure was similar regardless of whether or not a new TAM or major protease inhibitor mutations emerged or, for thymidine analogue-containing regimens, whether lamivudine was or was not used. CONCLUSIONS: Major protease inhibitor mutations arose more frequently and rapidly than did TAMs in patients with sustained virologic failure who received lamivudine.