You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Introduction {#s0005}
============

Interstitial cystitis (IC), a urinary tract infection, refers to the chronic inflammation and stress that disrupt the upper urinary tract functions. Pathological syndromes of IC may have urinary frequency, pain with urination, and dysuria, hematuria, hemorrhage [@b0005], [@b0010]. The common cause of infection is *Escherichia coli*. In addition, drug-induced hemorrhagic cystitis is another inflammation of the bladder [@b0015], [@b0020]. The main clinical therapy against IC is antibiotic medication by the time- and dose-dependent manners, such as nitrofurantoin, trimethoprim (uncomplicated case), phenazopyridine (complicated case) [@b0025]. However, a long-term treatment of antibiotics may induce drug resistance over time. Therefore, further development of candidate medication to treat IC is needed. Curcumol, isolated from *Rhizoma Curcumaeis*, is a bioactive component with potent pharmacological activities. And it is characterized with potential anti-inflammatory, anti-virus, anti-microbial, and anti-cancer effects [@b0030], [@b0035]. Increasing evidences has suggested that curcumol plays a potent inhibitory effect on the proliferation of human bladder cancer cells [@b0040]. However, the pharmacological study of curcumol against IC is limited presently. In addition to literature analysis, a predictive tool of network pharmacology can optimize and propose the main functional targets and molecular mechanisms of bioactive component against disease [@b0045]. Therefore, the current study used network pharmacology-analyzed bioinformatic data to uncover the main predictive targets, and correlative biological processes and signaling pathways of curcumol against IC. In parallel, the samples of clinical IC and curcumol-treated rats were collected and established to characterize the pathological and pharmacological biotargets, respectively. Together, the graphical abstract of this study design was demonstrated visibly in [Fig. 1](#f0005){ref-type="fig"}.Fig. 1This study used bioinformatic assays to predict the main biotargets and molecular pathways of curcumol against IC, followed by experimental validation.

Experimental {#s0010}
============

Identification of candidate targets of curcumol against IC {#s0015}
----------------------------------------------------------

All curcumol-associated functional targets were collected from the databases of PharmMapper (<http://lilab.ecust.edu.cn/pharmmapper/submit_file.php>) and Swiss Target Prediction (<http://www.swisstargetprediction.ch/index.php>). In addition, pathogenetic and therapeutic targets of IC were produced from the databases of DisGeNET (<http://www.disgenet.org/web/DisGeNET/menu/search?0>), Drugbank (<https://www.drugbank.ca/>), Therapeutic Target Database (<https://db.idrblab.org/ttd/>), respectively. Further, the curcumol-pharmacological targets were pooled with cystitis-pathologic targets before picking up the predictive targets of curcumol against IC.

Construction of PPI network and verification of main targets of curcumol against IC {#s0020}
-----------------------------------------------------------------------------------

The pooled targets of curcumol against IC were projected into FunRich_3.1.3 software (<http://www.funrich.org/>) to establish the target-functional proteins. And a PPI network of predictive targets was constructed. In addition, the identifiable data were further imported to Cytoscape (v3.6.1) (<https://cytoscape.org/>). The network analyzer setting was used to visualize the network targets of curcumol against IC based on topological parameters. The optimal targets were identified according to the maximum degree values.

Confirmation of biological processes and molecular pathways of curcumol against IC {#s0025}
----------------------------------------------------------------------------------

The Database for Annotation, Visualization and Integrated Discovery (DAVID) database (<https://david.ncifcrf.gov/home.jsp>) was used to extract the available biological functions related to core targets. These data were further introduced in the Omicshare Cloud Platform (<http://www.omicshare.com/tools/Home/Soft/gogsea>) to visualize the biological processes and signaling pathways from the core targets of curcumin anti-IC. And a p-value was used to plot advanced bubble diagrams of biological processes and signaling pathways.

Human designs {#s0030}
-------------

Adult male patients (n = 3) were diagnostically determined as IC through the biochemical, pathological, and medical imaging tests at Department of Urology Surgery. The serological data and clinical imaging were collected for further analyses. Additionally, IC samples of all these cases were surgically isolated during precancerous screening, followed by immunohistochemical and immunofluorescence stains. *All principles of this human study were conducted following the guidelines issued by Declaration of Helsinki* [@b0050].

Animal designs {#s0035}
--------------

Adult female Kunming mice were obtained from the Experimental Animal Unit of Guilin Medical University (Guilin, China). The mice were maintained in animal house under the controlled conditions of 22 ± 1 °C, around 60 ± 5% humidity, 12 altered hours in cycled light/dark. The mice were allowed to have filtered water and rodent chow freely. *The present study was authorized through Institutional Animal Care and Use Committee of the Guilin Medical University*. After acclimatization for at least one week, the anticancer drug-induced IC mice by cyclophosphamide (CPS) was established as previously described [@b0055]. Briefly, the fresh-prepared CPS solution were given to mice via oral gavage with 50 mg/kg in body weight every 3 days, followed by curcumol treatments (40 and 80 mg/kg; *w/w*) for consecutive 12 days. At the end of experiment, the serum and bladder samples from all mice were isolated for biochemical tests, and stains used for immunohistochemistry and immunofluorescence. For more details, all immunostaining procedures were referenced in previous description [@b0060].

Statistical analysis {#s0040}
====================

The blood results were expressed as mean ± standard deviation (SD). The mice data were assayed through statistical product and service solutions (SPSS) 19.0 software (IL, USA). Multiple comparisons were calculated by using the analysis of variance (ANOVA) with Tukey\'s post hoc test. The statistical significance was considered as *P* \< 0.05.

Results {#s0045}
=======

Candidate targets and identification of core targets {#s0050}
----------------------------------------------------

After bioinformatic assays, all 64 IC-pathogenic targets and 314 curcumol-therapeutic targets were screened. For further validation, 8 predictive targets were identified ultimately. A PPI network of curcumol against IC was constructed through assaying a function-related protein-protein interaction in these 8 functional targets. As shown in PPI network analysis, the hub network had 137 nodes and 449 edges with interactions and associations ([Fig. 2](#f0010){ref-type="fig"}). In topology parameters, the shorter path length and the larger median value indicated the more important targets. After calculation, 18 core targets were optimally obtained. According to the resultant visualization, the predictive targets of ERBB2, EGFR and PTK2 were the most important ([Fig. 3](#f0015){ref-type="fig"}).Fig. 2A PPI network was used to construct the targets of curcumol against IC (Red nodes) and functional related targets (Green nodes) before the main targets were identified and collected.Fig. 3After being analyzed, the main targets of curcumol against IC were identified and correlated. As a result, 3 top targets were representatively found as ERBB2, EGFR and PTK2 prior to further validation.

Biological function and signaling pathways of curcumol against IC {#s0055}
-----------------------------------------------------------------

As results, the top 20 biological function enrichments were obtained through DAVID database and omicshare cloud platform. As shown in [Fig. 4](#f0020){ref-type="fig"}, the results showed that the biological processes from the predictive targets of curcumol against IC were principally linked to regulating the ERBB2 signaling pathway, epidermal growth factor receptor (EGFR) signaling pathway, MAPK cascade, peptidyl-tyrosine phosphorylation, regulation of phosphatidylinositol 3-kinase signaling phosphatidylinositol phosphorylation (PI3-K), phosphatidylinositol-mediated signaling, negative regulation of apoptotic process, protein autophosphorylation, positive regulation of GTPase activity, signal transduction, peptidyl-tyrosine autophosphorylation, positive regulation of nitric oxide biosynthetic process, leukocyte migration, heart development, regulation of cell motility, positive regulation of phosphatidylinositol 3-kinase activity, positive regulation of apoptotic process, positive regulation of ERK1 and ERK2 cascade, Fc-epsilon receptor signaling pathway. In addition, the signaling pathways were chiefly involved in the Proteoglycans in cancer, ErbB signaling pathway, Endometrial cancer, Focal adhesion, Prolactin signaling pathway, Prostate cancer, Estrogen signaling pathway, Chemokine signaling pathway, Non-small cell lung cancer, Glioma, Chronic myeloid leukemia, Neurotrophin signaling pathway, Natural killer cell mediated cytotoxicity, Pathways in cancer, Bacterial invasion of epithelial cells, MicroRNAs in cancer, GnRH signaling pathway, PI3K-Akt signaling pathway, Bladder cancer, Thyroid hormone signaling pathway, respectively.Fig. 4After data analyses in DAVID tool, top 20 biological processes and signaling pathways of curcumol against IC were showed respectively prior to further bioinformatic discussion.

Case reports of patients with IC {#s0060}
--------------------------------

To reveal the clinical and histopathological characteristics of IC, human data and samples were used to assay. In urinary examination, these IC patients showed positive urinary protein, bacterial infection, and visible epithelial cell shedding ([Table 1](#t0005){ref-type="table"}). As shown in clinical computed tomography (CT) screening, chronic cystitis with urinary tract infection was observed. In addition, histopathological stains resulted in elevated intracellular expression of TNF-α in these IC sections. In order to characterize the predictive target of PTK2 in human samples, histopathological and immunofluorescent stains were conducted for further validation. As a result, the IC sections showed increased expressions of PTK2, p-PTK2^Tyr397^ in bladder tissues ([Fig. 5](#f0025){ref-type="fig"}).Table 1Clinical parameters of urinary tests in IC patients.Clinical indicatorsCase dataClinical standardsUPPositiveNegativepH6.5 ± 0.44.5--8.0RBC18702.1 ± 12366.940--16.1WBC88.9 ± 61.140--9.2EC10.63 ± 7.670--8.7CAST1.06 ± 1.010--2.25BACT9.87 ± 7.490--50X.TAL0 ± 00--10YLC45.2 ± 78.290--10SRC8.5 ± 8.860--3P.CAST0.46 ± 0.430--1Cond.12.77 ± 1.815--38Total155246 ± 99709.970--40,000[^2]Fig. 5Clinical characteristics of patients with IC. As results, medical CT scans showed urocystic lesions with chronic cystitis, urinary tract infection. Further, immunohistochemical staining showed visible expression of cellular TNF-α in IC sections. And the immunofluorescent stains displayed increased expressions of PTK2, p-PTK2^Tyr397^ in IC sections.

Experimental study of PTK2 targets in curcumol-treated mice {#s0065}
-----------------------------------------------------------

To further validate the predictive PTK2 targets of curcumol against IC *in vivo*, well-established CPS-induced IC in mice were used for experimental assays. As results, CPS-lesioned mice showed reduced body weights, and elevated contents of lactate dehydrogenase (LDH), IL-6, TNF-α in sera (*P* \< 0.05). Interestingly, high dose of curcumol treatment beneficially increased body mass, and lowered blood contents of LD, IL-6, TNF-α (*P* \< 0.05) ([Table 2](#t0010){ref-type="table"}). In histopathological observation with hematoxylin-eosin (HE) stains, CPS-lesioned mice exhibited morphological changes, inflammatory infiltration, and necrotic cells in bladder tissues. However, curcumol-treated mice showed reduced CPS-induced cytotoxicity in bladder cells, such as decreased necrotic cells and inflammatory lesions. Followed by immunohistochemical staining, CPS-lesioned bladders in mice resulted in increased intracellular expression of TNF-α, while curcumol-treated mice showed reduced endogenous TNF-α expression in bladder sections.Table 2Fundamental data of curcumol-treated CPS-lesioned mice.ParametersControlCPSCC40 + CPSCC80 + CPSBody mass (day 1)26.4 ± 0.826.5 ± 0.726.7 ± 0.826.4 ± 0.7Body mass (day 6)29.6 ± 0.924.2 ± 1.1[a](#tblfn1){ref-type="table-fn"}25.3 ± 0.927.6 ± 0.8Body mass (day 12)31.7 ± 1.521.8 ± 1.3[a](#tblfn1){ref-type="table-fn"}27.7 ± 0.928.8 ± 0.7[b](#tblfn2){ref-type="table-fn"}LDH (mmol/L)12.13 ± 0.4548.69 ± 1.59[a](#tblfn1){ref-type="table-fn"}33.66 ± 3.9523.70 ± 2.96[b](#tblfn2){ref-type="table-fn"}TNF-α (pg/mL)17.72 ± 1.6265.84 ± 7.59[a](#tblfn1){ref-type="table-fn"}41.05 ± 4.2831.21 ± 3.11[b](#tblfn2){ref-type="table-fn"}IL6 (pg/mL)11.65 ± 1.0646.47 ± 4.50[a](#tblfn1){ref-type="table-fn"}28.52 ± 4.4821.18 ± 2.12[b](#tblfn2){ref-type="table-fn"}[^3][^4][^5]

In addition, immunofluorescence staining was used to check intracellular expressions of PTK2, p-PTK2^Tyr397^. As results, CPS-lesioned mice showed elevated PTK2, p-PTK2^Tyr397^ expressions in bladder sections. After cotreatment with curcumol, the cellular expressions of PTK2, p-PTK2^Tyr397^ were down-regulated in comparison with those in CPS-lesioned controls ([Fig. 6](#f0030){ref-type="fig"}).Fig. 6Anti-IC activities of curcumol on CPS-lesioned mice. As showed in HE stains, CPS-lesioned mice resulted in morphological changes in bladder tissues. And increased expression of intracellular TNF-α in the bladder were observed in CPS-lesioned mice by using immunohistochemical stain. Interestingly, curcumol-treated mice showed bladder morphological improvement, and reduced TNF-α expression. As showed in immunofluorescence staining, CPS-lesioned mice resulted in elevated PTK2, p-PTK2^Tyr397^ expressions in bladder sections. However, down-regulated expressions of TNF-α, PTK2, p-PTK2^Tyr397^ in the bladder cells of curcumol-treated mice were observed, accompanied with ameliorative histomorphology in bladder tissues.

Discussion {#s0070}
==========

In this study, a bioactive component-target-disease network was constructed by using the network pharmacology-based bioinformatics. And resultant 18 core targets were identified through further analysis. According to the bioinformatic results, predictive ErbB2, EGFR and PTK2 were the most important targets of curcumol against IC. Tyrosine protein kinases (PTKs) are a group of functional enzymes that can catalyze the phosphorylation of substrate tyrosine residues, and these molecules play the key roles in cellular signaling pathways [@b0065], [@b0070]. It is believed that the parathyroid hormones (PTHs) signaling is mainly involved in cell growth and proliferation through modulating the PTKs-MAPK pathway [@b0075]. Mitogen-activated protein kinase (MAPK) functions as a "bridge" connecting extracellular stimuli and intracellular gene expression. It functionally regulates tumor growth and metastasis, as well as biologically participates in cell proliferation, differentiation and apoptosis through a series of effectors' activation and inactivation [@b0080], [@b0085]. The biomolecules of ErbB2, EGFR and PTK2 belong to PTK family. ErbB2 refers to one of the important oncogenes in the EGFR family, and it is a transmembrane protein with tyrosine kinase activity [@b0090], [@b0095]. EGFR is a receptor protein that distributes on the membrane of epithelial cells. When combined with ligands, EGFR activates the downstream signaling molecules and induces the biological effects, such as cell proliferation, differentiation and migration. In addition, EGFR plays a promotive role in transformation of malignant cells [@b0100], [@b0105]. PTK2, known as focal adhesion kinase (FAK), is a non-receptor protein tyrosine kinase located in the cytoplasm. Functionally, the activation of PTK2 is to promote the formation of tumor, and it also has other biological activities of regulating cellular apoptosis and stress [@b0110], [@b0115]. Recently, some studies have found that PTK2 is positively expressed in bladder cancer cells, and the over-expression of PTK2 facilitates the neoplastic cells to escape from apoptotic signals, gradually promoting tumor growth, metastasis [@b0120], [@b0125]. Interestingly, these functional molecular pathways from literature review were similarly proposed in this study. However, the experimental investigation of PTK2 in interstitial cystitis is not yet conducted. Based on bioinformatic findings, the current study predicted the core targets of curcumol against IC through a network pharmacology method. As a result, a key biotarget of PTK2 was representatively selected for further validation in human samples. In addition to positive detection of TNF-α expression in IC sections, intravesical PTK2, p-PTK2^Tyr397^ were markedly up-regulated through immunostaining. The activated PTK2 were positive correlation with cystitis conditions in urinary tests. These clinicopathological findings indicated that intracellular over-expression of PTK2 might be a key pathological promoter in development of IC. Further, PTK2 might be a potential therapeutic target for IC.

To further validate experimental study *in vivo*, CPS-induced IC mice were used to evaluate the pharmacological activities of curcumol against IC. As results, curcumol-treated mice showed reduced inflammatory cytokines (IL-6, TNF-α) in sera and suppressed intracellular cytotoxicity, characterized with down-regulated expressions of PTK2, p-PTK2^Tyr397^ in bladder cells. Therefore, this study can be reasoned that the anti-IC activities of curcumol might benefit from the anti-inflammatory effects through suppressing intravesical PTK2 and phosphorylation bioactivities.

Conclusions {#s0075}
===========

Collectively, these bioinformatic and experimental findings demonstrate that predictive targets of curcumol against IC may be mainly linked to inhibition of inflammation-associated pathways and inactivation of intracellular PTK2 activity in bladder cells. It highlights that bioinformatic method based on network pharmacology may predict the biological markers for IC screening and treating. Interestingly, PTK2 may be a potential biomarker for curcumol treating IC.

Conflict of interest {#s4565}
====================

*The authors have declared no conflict of interest.*

This study was supported by the National Natural Science Foundation of Guangxi Province (No. 2017GXNSFBA198049, 2018GXNSFAA281153), and the National Natural Science Foundation of China (No. 81660091).

Peer review under responsibility of Cairo University.

[^1]: These authors contributed equally to this work.

[^2]: Abbreviations: UP, urinary protein; RBC, red blood cell; WBC, white blood cell; EC, epithelial cells; CAST, cast; BACT, bacteria; X.TAL, crystallization; YLC, yeast cell; SRC, small round epithelial cells; P.CAST, pathological cast; Cond, conductivity; TOTAL, total count.

[^3]: Abbreviations: CPS, cyclophosphamide; LDH, lactate dehydrogenase; TNF-α, tumor necrosis factor α; IL-6, interleukin 6; CC40, 80, curcumol 40, 80 mg/kg. Note: when

[^4]: *P* \< 0.05 compared to control group.

[^5]: *P* \< 0.05 compared to CPS group.