Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective:To investigate the efficacy and mechanism of botulinum toxin type A (BTX-A) combined with static progressive stretching (SPS) in the treatment of traumatic knee stiffness in rats.Methods:Forty healthy male SD rats aged 8 weeks and weighing 220-300 g, were randomly divided into blank control group ( n=8) and model groups ( n=28) (including injury group, BTX-A group, SPS group and BTX-A+SPS group, with 7 in each group). Hlidebrand′s method was used to construct a traumatic knee stiffness model, with the following main steps: destruction of the joint capsule, Kirschner wire fixation, joint drilling, and removal of the internal fixation at 4 weeks. The blank control group did not receive any treatment and could move freely in the cage. The injury group moved freely after successful modeling. On the day of internal fixation removal, BTX-A was injected into the joint cavity in group BTX-A, SPS treatment was started in the SPS group, BTX-A was injected into the joint cavity and SPS treatment was started in the BTX-A+SPS group. The treatments lasted 16 days. The range of motion (ROM) and joint stiffness were measured before treatment and at 16 days after treatment. At 16 days after treatment, knee joint tissue was collected and the rats were sacrificed, and the articular capsule fibrous tissue proliferation was observed by HE and Masson staining. The expression levels of phosphorylated (p)-Smad2, Smad2, p-Smad3, Smad3, Smad4, transforming growth factor-β1 (TGF-β1), collagen type I, collagen type III, and α-smooth actin (α-SMA) were determined by Western blot. The ratio of phosphorylated protein to total protein was calculated to reflect the phosphorylation level. Results:(1) ROM: Before treatment, the ROM in the blank control group was significantly higher than that in the other groups ( P<0.05), with no significant difference in ROM among the other groups ( P>0.05). At 16 days after treatment, ROM in the injury group, BTX-A group, SPS group, and BTX-A+SPS group was lower than that in the blank control group ( P<0.05), among which ROM in the BTX-A+SPS group was significantly higher than that in the injury group, BTX-A group, and SPS group ( P<0.05). At 16 days after treatment, there was no significant difference in ROM before and after treatment in the blank control group ( P>0.05), and ROM in the other groups was significantly increased compared with that before treatment ( P<0.01). (2) Joint stiffness: At 16 days after treatment, the joint stiffness levels in the injury group, the BTX-A group, and the SPS group were (0.95±0.24)N·cm/°, (0.86±0.22)N·cm/°, and (0.65±0.09)N·cm/° respectively, which were significantly lower than (0.36±0.03)N·cm/° in the blank control group ( P<0.05). The joint stiffness level of the BTX-A+SPS group was (0.49±0.04)N·cm/°, which was not significantly different from that in the blank control group ( P>0.05), but was significantly lower than those in the injury group, BTX-A group, and SPS group ( P<0.05). (3) Fibrous tissue proliferation: at 16 days after treatment, the joint capsular structure in the blank control group was complete and clear, the fibers were arranged in order, and there was no obvious fibrous tissue proliferation. The pathological changes in the injury group were the most serious, with a large number of synovial fibrous tissue proliferation, significantly increased blood vessels in the tissue, and inflammatory cell infiltration. Compared with the SPS group and BTX-A group, the lesions in BTX-A+SPS group were milder, with only slight increase in the number of synovial cells but no obvious vascular proliferation or lymphocytes, and the overall lesions were the least severe. (4) Protein expression: the ratios of p-Smad2/Smad2 in the injury group, BTX-A group and SPS group were 1.552±0.234, 1.328±0.272 and 1.194±0.277 respectively, which were higher than 0.794±0.082 in the blank control group ( P<0.05). The ratio of p-Smad2/Smad2 in the BTX-A+SPS group was 1.013±0.123, which was not significantly different from those in the blank control group, BTX-A group or SPS group ( P>0.05), but was lower than that in the injury group ( P<0.05). At 16 days after treatment, the p-Smad3/Smad3 ratios in the injury group, BTX-A group, SPS group and BTX-A+SPS group were 2.272±0.309, 1.664±0.285, 1.381±0.276 and 1.003±0.060 respectively, which were higher than 0.515±0.051 in the blank control group ( P<0.05). The p-Smad3/Smad3 ratio in the BTX-A+SPS group was significantly lower than those in the injury group, BTX-A group and SPS group ( P<0.05). At 16 days after treatment, the level of Smad4 in the injury group (1.001±0.015) was higher than 0.294±0.076 in the blank control group ( P<0.05). However, there was no significant difference between the BTX-A group (0.664±0.051), SPS group (0.833±0.045), BTX-A+SPS group (0.467±0.068) or the blank control group ( P>0.05). The level of Smad4 in the BTX-A+SPS group was significantly lower than those in the injury group, BTX-A group and SPS group ( P<0.05). At 16 days after treatment, the level of TGF-β1 in the injury group (1.004±0.407) was higher than 0.269±0.122 in the blank control group ( P<0.05), while there was no significant difference between the BTX-A group (0.564±0.194), SPS group (0.422±0.086) and BTX-A+SPS group (0.347±0.161) and the blank control group ( P>0.05). The level of TGF-β1 in the BTX-A+SPS group was significantly lower than those in the injury group, BTX-A group and SPS group ( P<0.05). At 16 days after treatment, the level of type I collagen in the injury group was 0.999±0.170, higher than 0.299±0.139 in the blank control group ( P<0.05), while there was no significant difference between the BTX-A group (0.542±0.278), SPS group (0.561±0.165), and BTX-A+SPS group (0.537±0.045) and the blank control group ( P>0.05). The level of collagen type I in the BTX-A+SPS group was significantly lower than those in the injury group, BTX-A group, and SPS group ( P<0.05). At 16 days after treatment, the level of type III collagen in the injury group was 1.002±0.126, higher than 0.239±0.106 in the blank control group ( P<0.05), while there was no significant difference between the BTX-A group (0.661±0.062), SPS group (0.595±0.062), and BTX-A+SPS group (0.504±0.269) and the blank control group ( P>0.05). The level of collagen type III in the BTX-A+SPS group was significantly lower than those in the injury group, BTX-A group, and SPS group ( P<0.05). At 16 days after treatment, the level of α-SMA in the injury group was 0.998±0.074, higher than 0.130±0.023 in the blank control group ( P<0.05), while there was no significant difference between the BTX-A group (0.358±0.060), SPS group (0.432±0.230), and BTX-A+SPS group (0.293±0.135) and the blank control group ( P>0.05). The level of α-SMA in the BTX-A+SPS group was significantly lower than those in the injury group, BTX-A group and SPS group ( P<0.05). Conclusions:Compared with single treatment, the combination of BTX-A and SPS demonstrates significantly greater efficacy in the treatment of traumatic knee stiffness in rats. This combined approach not only enhances joint mobility and elasticity but also effectively inhibits joint capsule fibrosis. The underlying mechanism may involve the further suppression of TGF-β1 expression in the joint capsule, leading to reduced phosphorylation levels of Smad2 and Smad3. This, in turn, inhibits the binding of Smad2 and Smad3 to the Smad4 receptor, ultimately downregulating the expression of the downstream proteins of the TGF-β/Smad signaling pathway, such as collagen type I, collagen type III and α-SMA.

This study was aimed at identifying the pathogenic bacteria responsible for the death of a young tiger at the Fujian Meihua Mountain South China Tiger Breeding Research Institute.Tissue samples from the lungs,liver,and intestines of the deceased tiger were collected,and the bacteria were cultured inasterile environment.The bacterial strains were characterized according to their morphological and molecular biological properties,including assessment of virulence genes and antibiotic resistance genes,mouse lethality tests,and antibiotic susceptibility evaluations.A predominant bacterial strain isolated from the liver of the deceased tiger was identified as enterotoxigenic Escherichia coli(ETEC)strain Tiger22513F.Phylogenetic analysis of the 16S rRNA gene revealed that the Tiger22513F strain exhibited close genetic similarity to the reference strain ETEC(MF919609.1),with 99.9%nucleotide similarity,and resided on the same evolutionary branch.The Tiger22513F strain contained 11 antibiotic resistance genes(tetA,sul1,sul3,cmlA,floR,blaTEM,blaSHV,blaCMY-2,qnrA,qnrS,and qnrD)along with five virulence genes(VT1,fyuA,tsh,iucD,and ST).Mouse lethality tests indicated significant pathogenicity toward mice,affecting primarily the lungs,liver,and intestines.Antibiotic susceptibility testing demonstrated that this strain exhibited resistance to various classes of beta-lactam antibiotics,as well as quinolones and aminoglycosides.This investigation successfully isolated a multi-drug resistant enterotoxigenic Escherichia coli strain with pronounced pathogenicity from the liver of a deceased tiger;thus providing valuable scientific insights for clinical diagnosis,as well as prevention and control measures,against ETEC infections in South China tigers.

Background: Intradermal microdroplet injections of botulinum toxin type-A (BoNT/A) effectively ameliorate rosacea-related angiogenesis, but the mechanism remains unclear. Objective: To explore the anti-angiogenesis of BoNT/A in the rosacea-like mouse model and to measure the secretion of vascular endothelial growth factor (VEGF) by mast cells. Methods: A rosacea-like mouse model was induced by LL37 in both Mas-related G-proteincoupled receptor B2 conditional knockout (MrgprB2 −/− ) mice and wild-type (WT) mice, then treated with BoNT/A and/or Apatinib. The abundance of endothelial cells and mast cells in mouse skin was determined using dual immunofluorescence staining. The VEGF levels in supernatants and cell lysates of laboratory of allergic disease 2 (LAD2) mast cells were assessed using reverse transcription quantitative polymerase chain reaction, western blots, and enzyme-linked immunosorbent assay. The effect of conditioned medium (CM) collected from LAD2 on human umbilical vein endothelial cells (HUVECs) was determined using tube formation assays. The number of proliferative cells was confirmed using the 5-ethynyl-2’-deoxyuridine incorporation assays.The effect of BoNT/A on the internalization of Mas-related G-protein-coupled receptor X2 (MRGPRX2) was detected using flow cytometry and immunofluorescence staining. Results: LL37-induced rosacea-like skin manifestations were significantly alleviated in MrgprB2 −/− mice compared to WT controls. BoNT/A mitigated the LL37-induced secretion of VEGF by LAD2. The CM from BoNT/A-treated LAD2 inhibited HUVEC proliferation and tube formation. The LAD2 cells co-treated with LL37 and BoNT/A exhibited dramatically enhanced MRGPRX2 internalization. Conclusion BoNT/A enhances LL37-mediated MRGPRX2 internalization in mast cells, thereby reducing VEGF secretion and neovascularization and improving facial flushing symptom in rosacea.

[Objective] To analyse and predict the tendencies of using erythrocyte blood in Changsha based on the autoregressive integrated moving average (ARIMA) model, long short-term memory (LSTM) and ARIMA-LSTM combination model, so as to provide reliable basis for designing a feasible and effective blood inventory management strategy. [Methods] The data of erythrocyte usage from hospitals in Changsha between January 2012 and December 2023 were collected, and ARIMA model, LSTM model and ARIMA-LSTM combination model were established. The actual erythrocyte consumption from January to May 2024 were used to assess and verify the prediction effect of the models. The extrapolation prediction accuracy of the models were tested using two evaluation indicators: mean absolute percentage error (MAPE) and root mean square error (RMSE), and then the prediction performance of the model was compared. [Results] The RMSE of LSTM model, optimal model ARIMA(1,1,1)(1,1,1)12 and ARIMA-LSTM combination model were respectively 5 206.66, 3 096.43 and 2 745.75, and the MAPE were 18.78%,11.54% and 9.76% respectively, which indicated that the ARIMA-LSTM combination model was more accurate than the ARIMA model and LSTM model, and the prediction results was basically consistent with the actual situation. [Conclusion] The ARIMA-LSTM model can better predict the clinical erythrocyte consumption in Changsha in the short term.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective:To investigate the expression of Artemin (ARTN) in malignant peripheral nerve sheath tumor (MPNST), its effect on the malignant behavior of MPNST cells, and its signaling pathway.Methods:Fifty-one MPNST paraffin embedded tissues through surgical resection at Tianjin Medical University Cancer Hospital from January 1995 to November 2011 were collected, the expression of the ARTN protein was detected by immunohistochemistry, and the relationship between the ARTN protein expression and the clinical pathological characteristics and prognosis were analyzed. In human MPNST cell lines ST-8814 (NF-1) and STS26T(sporadic), ARTN overexpression and low expression cell lines were constructed by transfecting ARTN overexpression plasmids and ARTN small interfering RNA (siRNA), respectively. The expression of ARTN mRNA was detected by real time quantitative polymerase chain reaction (RT-qPCR), the expression of the ARTN protein and Phosphoinositide 3-kinase(PI3K)/Akt signaling pathway related proteins were detected by Western blot. CCK-8 assay was used to detect cell proliferation ability, and cell invasion assay was used to detect cell invasion ability. The pathway proteins that interacted with ARTN were searched in the STRING database, and the functional pathways were clarified by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The PI3K/Akt pathway specific inhibitor LY294002 was used to block the PI3K/Akt pathway of ST-8814 and STS26T cells to observe the changes in cell proliferation and invasion.Results:Among the 51 MPNST tissue specimens, 22 cases showed a high expression of the ARTN protein and 29 cases showed a low expression of the protein. Higher expressions of the ARTN protein was associated with larger tumor diameters and disease progression (recurrence or metastasis) (both P＜0.05). The median disease-free survival (DFS) of patients with a low expression of the ARTN protein was 26.2 months, and the median overall survival (OS) was 66.9 months. The median DFS and median OS of patients with a high expression of the ARTN protein were 10.7 months and 53.8 months, respectively. The log rank test results showed that the progression free survival rate of patients with a high expression of the ARTN protein was worse than that of patients with a low expression ( P=0.027), but the difference in overall survival rate between the two groups was not statistically significant ( P=0.790), which was also confirmed by Cox regression analysis. The CCK-8 assay results showed that after 48 hours of transfection, the absorbance ( A) values of ST-8814 and STS26T cells in the ARTN overexpression group were 1.35±0.01 and 1.10±0.02, respectively, which were higher than those in the empty plasmid control group (1.05±0.01 and 0.78±0.01, both P＜0.01), while the A values of ST-8814 and STS26T cells in the ARTN siRNA group were 0.35±0.01 and 0.61±0.01, respectively, which were lower than those in the control siRNA group (0.74±0.01 and 1.10±0.04, both P＜0.01). The results of cell invasion assay showed that the number of transmembrane cells in ST-8814 and STS26T cells overexpressing ARTN was (29.67±2.08) and (31.67±2.08), respectively, which were higher than those in the empty plasmid control group [(20.00±1.00) and (24.33±1.15), both P＜0.01]. The number of transmembrane cells in ST-8814 and STS26T cells in the ARTN siRNA group were (14.00±2.00) and (19.33±1.53), respectively, which were lower than those in the control siRNA group [(19.33±2.52) and (23.33±0.58), both P＜0.05].The KEGG results showed that ARTN is associated with multiple tumor signaling pathways, especially the PI3K/Akt signaling pathway. Western blot results showed that overexpression of ARTN upregulated the expression of p-PI3K and p-Akt proteins in ST-8814 and STS26T cells (both P＜0.01).After knocking down ARTN expression, the expression of p-PI3K and p-Akt proteins was significantly down regulated (both P＜0.01). LY294002 could significantly inhibit the effect of ARTN overexpression on ST-8814 and STS26T cells after blocking the PI3K/Akt pathway. The A values of ST-8814 and STS26T cells in the ARTN overexpression+LY294002 group were 1.09±0.06 and 0.82±0.01, respectively, which were lower than those in the ARTN overexpression group (1.50±0.01 and 1.29±0.01, respectively, both P＜0.01). The numbers of transmembrane cells in the cell invasion assay were 16.67±3.21 and 19.67±2.31, respectively, which were also lower than those in the ARTN overexpression group (29.67±2.08 and 31.67±2.08, respectively, both P＜0.01). Conclusions:In MPNST, a high expression of the ARTN protein was associated with larger tumor size, disease progression, and worse DFS. ARTN promotes the proliferation and invasion of MPNST cells through the PI3K/Akt signaling pathway.