A prediction model based on artificial intelligence techniques for disintegration time and hardness of fast disintegrating tablets in pre-formulation tests.

BACKGROUND: The pharmaceutical industry is continually striving to innovate drug development and formulation processes. Orally disintegrating tablets (ODTs) have gained popularity due to their quick release and patient-friendly characteristics. The choice of excipients in tablet formulations plays a critical role in ensuring product quality, highlighting its importance in tablet creation. The traditional trial-and-error approach to this process is both expensive and time-intensive. To tackle these obstacles, we introduce a fresh approach leveraging machine learning and deep learning methods to automate and enhance pre-formulation drug design. METHODS: We collected a comprehensive dataset of 1983 formulations, including excipient names, quantities, active ingredient details, and various physicochemical attributes. Our study focused on predicting two critical control test parameters: tablet disintegration time and hardness. We compared a range of models like deep learning, artificial neural networks, support vector machines, decision trees, multiple linear regression, and random forests. RESULTS: A 12-layer deep neural network, as a form of deep learning, surpassed alternative techniques by achieving 73% accuracy for disintegration time and 99% for tablet hardness. This success underscores its efficacy in predicting complex pharmaceutical factors. Such an approach streamlines the drug formulation process, reducing iterations and material consumption. CONCLUSIONS: Our findings highlight the deep learning potential in pharmaceutical formulations, particularly for tablet hardness prediction. Future work should focus on enlarging the dataset to improve model effectiveness and extend its application in pharmaceutical product development and assessment.

Breast cancer prediction using different machine learning methods applying multi factors.

OBJECTIVE: Breast cancer (BC) is a multifactorial disease and is one of the most common cancers globally. This study aimed to compare different machine learning (ML) techniques to develop a comprehensive breast cancer risk prediction model based on features of various factors. METHODS: The population sample contained 810 records (115 cancer patients and 695 healthy individuals). 45 attributes out of 85 were selected based on the opinion of experts. These selected attributes are in genetic, biochemical, biomarker, gender, demographic and pathological factors. 13 Machine learning models were trained with proposed attributes and coefficient of attributes and internal relationships were calculated. RESULT: Compared to other methods random forest (RF) has higher performance (accuracy 99.26%, precision 99%, and area under the curve (AUC) 99%). The results of assessing the impact and correlation of variables using the RF method based on PCA indicated that pathology, biomarker, biochemistry, gene, and demographic factors with a coefficient of 0.35, 0.23, 0.15, 0.14, and 0.13 respectively, affected the risk of BC (r2 = 0.54). CONCLUSION: Breast cancer has several risk factors. Medical experts use these risk factors for early diagnosis. Therefore, identifying related risk factors and their effect can increase the accuracy of diagnosis. Considering the broad features for predicting breast cancer leads to the development of a comprehensive prediction model. In this study, using RF technique a breast cancer prediction model with 99.3% accuracy was developed based on multifactorial features.

Surface-modified cationic liposomes with a matrix metalloproteinase-degradable polyethylene glycol derivative improved doxorubicin delivery in murine colon cancer.

PEGylation is a commonly used approach to prolong the blood circulation time of cationic liposomes. However, PEGylation is associated with the "PEG dilemma", which hinders binding and uptake into tumor cells. The cleavable PEG products are a possible solution to this problem. In the current research, doxorubicin-loaded cationic liposomes (Dox-CLs) surface-conjugated with a matrix metalloproteinase-2 (MMP-2)-sensitive octapeptide linker-PEG derivative were prepared and compared to non-PEGylated and PEGylated CLs in terms of size, surface charge, drug encapsulation and release, uptake, in vivo pharmacokinetics, and anticancer efficacy. It was postulated that PEG deshielding in response to the overexpressed MMP-2 in the tumor microenvironment increases the interaction of protected CLs with cellular membranes and improves their uptake by tumor cells/vasculature. MMP2-responsive Dox-CLs had particle sizes of ∼115-140 nm, surface charges of ∼+25 mV, and encapsulation efficiencies of ∼85-95%. In vitro cytotoxicity assessments showed significantly enhanced uptake and cytotoxicity of PEG-cleavable CLs compared to their non-cleavable PEG-coated counterparts or Caelyx®. Also, the chick chorioallantoic membrane assay showed great antiangiogenesis ability of Dox-CLs leading to target and prevent tumor neovascularization. Besides, in vivo studies showed an effective therapeutic efficacy of PEG-cleavable Dox-CLs in murine colorectal cancer with negligible hematological and histopathological toxicity. Altogether, our results showed that MMP2-responsive Dox-CLs could be served as a promising approach to improve tumor drug delivery and uptake.

The comparison of biodistribution of glutathione PEGylated nanoliposomal doxorubicin formulations prepared by pre-insertion and post-insertion methods for brain delivery in normal mice.

Several obstacles limit the efficacy of brain tumour treatment, most notably the blood-brain barrier (BBB), which prevents the brain uptake of the majority of accessible medicines due to tight junctions. The presence of glutathione (GSH) receptors on the BBB surface has been demonstrated in numerous papers; consequently, products containing glutathione as a targeting ligand coupled with nanoliposomes are used to enhance drug delivery across the BBB. Here, the 5% pre-inserted PEG2000-GSH PEGylated liposomal doxorubicin was conducted according to 2B3-101 being tested in clinical trials. In addition, PEGylated nanoliposomal doxorubicin connected to the spacer-GSH targeting ligand (GSGGCE) and the PEG3400 was conducted using post-insertion method. Next, in vivo biodistribution of the produced formulations was tested on healthy mice to see if GSGGCE, as the targeted ligand, could cross the BBB compared to 5% pre-inserted PEG2000-GSH and Caelyx® . Compared to the pre-inserted formulation and Caelyx® , the post-inserted formulations' concentration was lower in the heart and higher in brain tissues, resulting in boosting the brain concentration of accumulated doxorubicin with fewer possible side effects, including cardiotoxicity. In comparison to the pre-insertion procedure, the post-insertion method is easier, faster, and more cost-effective. Moreover, employing PEG3400 and the post-insertion approach in the PEG3400-GSGGCE liposomal formulations was found to be effective in crossing the BBB.

The role of size in PEGylated liposomal doxorubicin biodistribution and anti-tumour activity.

The size of nanoliposome-encapsulated drugs significantly affects their therapeutic efficacy, biodistribution, targeting ability, and toxicity profile for the cancer treatment. In the present study, the biodistribution and anti-tumoral activity of PEGylated liposomal Doxorubicin (PLD) formulations with different sizes were investigated. First, 100, 200, and 400 nm PLDs were prepared by remote loading procedure and characterised for their size, zeta potential, encapsulation efficacy, and release properties. Then, in vitro cellular uptake and cytotoxicity were studied by flow cytometry and MTT assay, and compared with commercially available PLD Caelyx® . In vivo studies were applied on BALB/c mice bearing C26 colon carcinoma. The cytotoxicity and cellular uptake tests did not demonstrate any statistically significant differences between PLDs. The biodistribution results showed that Caelyx® and 100 nm liposomal formulations had the most doxorubicin (Dox) accumulation in the tumour tissue and, as a result, considerably suppressed tumour growth compared with 200 and 400 nm PLDs. In contrast, larger nanoparticles (200 and 400 nm formulations) had more accumulation in the liver and spleen. This study revealed that 90 nm Caelyx® biodistribution profile led to the stronger anti-tumour activity of the drug and hence significant survival extension, and showed the importance of vesicle size in the targeting of nanoparticles to the tumour microenvironment for the treatment of cancer.

Docetaxel in combination with metformin enhances antitumour efficacy in metastatic breast carcinoma models: a promising cancer targeting based on PEGylated liposomes.

OBJECTIVES: Metformin has been shown to kill cancer stem-like cells in genetically various types of breast carcinoma. With the aim to simultaneously eradicate the bulk population of tumour cells and the rare population of cancer stem-like cells in breast cancer tissues, we used the combination chemotherapy of docetaxel (DTX) with metformin (MET). Furthermore, we introduce an active loading method based on ammonium sulphate 250 mM (SA) for encapsulating docetaxel into liposomes. METHODS: Docetaxel and metformin encapsulated into PEGylated liposomes with two different methods based on remote or passive loading methods, respectively. The size and surface charge of the liposomes were characterized. DTX content in the nanoliposomes was measured by the high-performance liquid chromatography method. The drug release profiles were evaluated in phosphate-buffered dextrose 5% with the pH of 6.5 and 7.4. We examined the antitumour activity of Taxotere (TAX), and liposomal formulation of DTX and MET as a monotherapy or combination therapy. The biodistribution of liposomes was also investigated using 99mTc hexamethyl propylene amine oxime method in BALB/c mice bearing 4T1 breast carcinoma tumours. KEY FINDINGS: The final formulations were prepared according to the best physicochemical characteristics which were HSPC/mPEG2000-DSPE/Chol (DTX liposomes) and HSPC/DPPG/mPEG2000-DSPE/Chol (MET liposomes), at molar ratios of 85/5/10 and (55/5/5/35), respectively. In vivo experiments showed that when free or liposomal metformin used in combination with liposomal docetaxel, they prolonged median survival time (MST) from 31 in the control group to 46 days, which demonstrates their promising effects on the survival of the 4T1 breast carcinoma mice models. Moreover, combination therapies could significantly increase life span in comparison with phosphate-buffered saline (PBS) and Taxotere groups at the same dose. Furthermore, in the combination therapy study, treatment with DTX liposomes prepared by ammonium sulphate 250 mM buffer alone resulted in similar therapeutic efficacy to combination therapy. The biodistribution study exhibited significant accumulation of DTX liposomes in the tumours due to the Enhanced Permeability and Retention effect. CONCLUSIONS: This study also showed that metformin-based combinatorial chemotherapies have superior efficacy versus their corresponding monotherapy counterparts at same doses. The findings confirm that liposomes based on ammonium sulphate 250 mM could be as a promising formulation for efficient DTX delivering and cancer targeting and therefore merit further investigations.

Redox-sensitive doxorubicin liposome: a formulation approach for targeted tumor therapy.

In this study redox-sensitive (RS) liposomes manufactured using 10,10'-diselanediylbis decanoic acid (DDA), an organoselenium RS compound, to enhance the therapeutic performance of doxorubicin (Dox). The DDA structure was confirmed by 1H NMR and LC-MS/MS. Various liposomal formulations (33 formulations) were prepared using DOPE, Egg PC, and DOPC with Tm Ë‚ 0 and DDA. Some formulations had mPEG2000-DSPE and cholesterol. After extrusion, the external phase was exchanged with sodium bicarbonate to create a pH gradient. Then, Dox was remotely loaded into liposomes. The optimum formulations indicated a burst release of 30% in the presence of 0.1% hydrogen peroxide at pH 6.5, thanks to the redox-sensitive role of DDA moieties; conversely, Caelyx (PEGylated liposomal Dox) showed negligible release at this condition. RS liposomes consisting of DOPE/Egg PC/DDA at 37.5 /60/2.5% molar ratio, efficiently inhibited C26 tumors among other formulations. The release of Dox from RS liposomes in the TME through the DDA link fracture triggered by ROS or glutathione is seemingly the prerequisite for the formulations to exert their therapeutic action. These findings suggest the potential application of such intelligent formulations in the treatment of various malignancies where the TME redox feature could be exploited to achieve an improved therapeutic response.

Preparation, characterization, and biodistribution of glutathione PEGylated nanoliposomal doxorubicin for brain drug delivery with a post-insertion approach.

Objectives: Brain cancer treatments have mainly failed due to their inability to cross the blood-brain barrier. Several studies have confirmed the presence of glutathione (GSH) receptors on BBB's surface, as a result, products like 2B3-101, which contain over 5% pre-inserted GSH PEGylated liposomal doxorubicin, are being tested in clinical trials. Here we conducted the PEGylated nanoliposomal doxorubicin particles that are covalently attached to the glutathione using the post-insertion technique. Compared with the pre-insertion approach, the post-insertion method is notably simpler, faster, and more cost-effective, making it ideal for large-scale pharmaceutical manufacturing. Materials and Methods: The ligands of the DSPE PEG(2000) Maleimide-GSH were introduced in the amounts of 25, 50, 100, 200, and 400 on the available Caelyx. Following physicochemical evaluations, animal experiments such as biodistribution, fluorescence microscopy, and pharmacokinetics were done. Results: In comparison with Caelyx, the 200L and 400L treatment arms were the most promising formulations. We showed that nanocarriers containing 40 times fewer GSH micelles than 2B3-101 significantly increased blood-brain barrier penetrance. Due to the expressed GSH receptors on tissues as an endogenous antioxidant, doxorubicin will likely concentrate in the liver, spleen, heart, and lung in comparison with Caelyx, according to other tissue analyses. Conclusion: The post-insertion technique was found a successful approach with more pharmaceutical aspects for large-scale production. Moreover, further investigations are highly recommended to determine the efficacy of 5% post-inserted GSH targeted nanoliposomes versus 2B3-101 as a similar formulation with a different preparation method.

Nanocarriers Call the Last Shot in the Treatment of Brain Cancers.

Our brain is protected by physio-biological barriers. The blood-brain barrier (BBB) main mechanism of protection relates to the abundance of tight junctions (TJs) and efflux pumps. Although BBB is crucial for healthy brain protection against toxins, it also leads to failure in a devastating disease like brain cancer. Recently, nanocarriers have been shown to pass through the BBB and improve patients' survival rates, thus becoming promising treatment strategies. Among nanocarriers, inorganic nanocarriers, solid lipid nanoparticles, liposomes, polymers, micelles, and dendrimers have reached clinical trials after delivering promising results in preclinical investigations. The size of these nanocarriers is between 10 and 1000 nm and is modified by surface attachment of proteins, peptides, antibodies, or surfactants. Multiple research groups have reported transcellular entrance as the main mechanism allowing for these nanocarriers to cross BBB. Transport proteins and transcellular lipophilic pathways exist in BBB for small and lipophilic molecules. Nanocarriers cannot enter via the paracellular route, which is limited to water-soluble agents due to the TJs and their small pore size. There are currently several nanocarriers in clinical trials for the treatment of brain cancer. This article reviews challenges as well as fitting attributes of nanocarriers for brain tumor treatment in preclinical and clinical studies.

Decision fusion in healthcare and medicine: a narrative review.

OBJECTIVE: To provide an overview of the decision fusion (DF) technique and describe the applications of the technique in healthcare and medicine at prevention, diagnosis, treatment and administrative levels. BACKGROUND: The rapid development of technology over the past 20 years has led to an explosion in data growth in various industries, like healthcare. Big data analysis within the healthcare systems is essential for arriving to a value-based decision over a period of time. Diversity and uncertainty in big data analytics have made it impossible to analyze data by using conventional data mining techniques and thus alternative solutions are required. DF is a form of data fusion techniques that could increase the accuracy of diagnosis and facilitate interpretation, summarization and sharing of information. METHODS: We conducted a review of articles published between January 1980 and December 2020 from various databases such as Google Scholar, IEEE, PubMed, Science Direct, Scopus and web of science using the keywords decision fusion (DF), information fusion, healthcare, medicine and big data. A total of 141 articles were included in this narrative review. CONCLUSIONS: Given the importance of big data analysis in reducing costs and improving the quality of healthcare; along with the potential role of DF in big data analysis, it is recommended to know the full potential of this technique including the advantages, challenges and applications of the technique before its use. Future studies should focus on describing the methodology and types of data used for its applications within the healthcare sector.

Development of a stable and high loaded liposomal formulation of lapatinib with enhanced therapeutic effects for breast cancer in combination with Caelyx®: In vitro and in vivo evaluations.

Lapatinib, a dual tyrosine kinase inhibitor, has poor water solubility, which results in poor and incomplete absorption from the gastrointestinal tract. To overcome this obstacle, we designed a stable and high-loaded liposomal formulation encapsulating lapatinib and examined its therapeutic efficacy in vitro and in vivo on TUBO and 4T1 cell lines. We also assessed the impact of liposomal lapatinib on the extent of the tumor and spleen-infiltrating lymphocytes and the autophagy and apoptosis gene expression within the tumor site. Our results showed that liposomal lapatinib inhibits cell proliferation and significantly induces autophagy and apoptosis compared to control groups. Moreover, when it used in combination with liposomal doxorubicin, it extended the time to end from 22.4 ± 3.5 in the control group to 40 days in the TUBO cell line and from 29.2 ± 1.7 to 38.6 ± 2.2 days in 4T1 triple-negative breast cancer cell line, which reveals its promising effects on the survival of tumor-bearing mice. Our results indicated the need for further evaluations to understand liposomal lapatinib's potential effects on autophagy, apoptosis, and particularly on immune system cells.

Association between vitamin D supplementation or serum vitamin D level and susceptibility to SARS-CoV-2 infection or COVID-19 including clinical course, morbidity and mortality outcomes? A systematic review.

OBJECTIVE: To systemically review and critically appraise published studies of the association between vitamin D supplementation or serum vitamin D level and susceptibility to SARS-CoV-2 infection or COVID-19, including clinical course, morbidity and mortality outcomes. DESIGN: Systematic review. DATA SOURCES: MEDLINE (OVID), Embase (OVID), Cochrane Central Register of Controlled Trials, MedRxiv and BioRxiv preprint databases. COVID-19 databases of the WHO, Cochrane, CEBM Oxford and Bern University up to 10 June 2020. STUDY SELECTION: Studies that assessed vitamin D supplementation and/or low serum vitamin D in patients acutely ill with, or at risk of, severe betacoronavirus infection (SARS-CoV, MERS-CoV, SARS-CoV-2). DATA EXTRACTION: Two authors independently extracted data using a predefined data extraction form and assessed risk of bias using the Downs and Black Quality Assessment Checklist. RESULTS: Searches elicited 449 papers, 59 studies were eligible full-text assessment and 4 met the eligibility criteria of this review. The four studies were narratively synthesised and included (1) a cross-sectional study (n=107) suggesting an inverse association between serum vitamin D and SARS-CoV-2; (2) a retrospective cohort study (348 598 participants, 449 cases) in which univariable analysis showed that vitamin D protects against COVID-19; (3) an ecological country level study demonstrating a negative correlation between vitamin D and COVID-19 case numbers and mortality; and (4) a case-control survey (n=1486) showing cases with confirmed/probable COVID-19 reported lower vitamin D supplementation. All studies were at high/unclear risk of bias. CONCLUSION: There is no robust evidence of a negative association between vitamin D and COVID-19. No relevant randomised controlled trials were identified and there is no robust peer-reviewed published evidence of association between vitamin D levels and severity of symptoms or mortality due to COVID-19. Guideline producers should acknowledge that benefits of vitamin D supplementation in COVID-19 are as yet unproven despite increasing interest.

Preparation and characterization of PEGylated liposomal Doxorubicin targeted with leptin-derived peptide and evaluation of their anti-tumor effects, in vitro and in vivo in mice bearing C26 colon carcinoma.

Employing targeting ligands on the surface of liposomes has the great potential to improve therapeutic efficacy and decreases off-target effects of liposomal formulations. In the present study, a leptin-derived peptide (Lp31) was evaluated to optimize the therapeutic efficacy of PEGylated liposomal Doxorubicin (PLD, Caelyx®). Leptin is an appetite regulatory hormone that is secreted into the blood circulation by the adipose tissue and it functions via its over expressed receptors (Ob-R) in a wide variety of cancers. Lp31, as targeting ligand, was conjugated to Maleimide-PEG2000-DSPE and then post-inserted into Caelyx. The anti-tumor activity and therapeutic efficacy of leptin modified Caelyx were evaluated and compared with Caelyx. The in vitro experiments demonstrated enhanced cytotoxicity and cellular uptake of Lp31-targeted Caelyx in C26 cell line compared to Caelyx. In BALB/c mice bearing C-26 murine carcinoma, Lp31 modified Caelyx groups exhibited significantly higher doxorubicin concentration at tumor tissue. Furthermore, Lp31 modified Caelyx at the dose of 10 mg/kg resulted in significant tumor growth inhibition and enhanced survival time compared to Caelyx. According to these results, the novel Lp31-liposomal doxorubicin offers great promise for the treatment of colon cancer and merits further investigation.

Anti-epithelial cell adhesion molecule RNA aptamer-conjugated liposomal doxorubicin as an efficient targeted therapy in mice bearing colon carcinoma tumor model.

To overcome the lack of selectivity and nonspecific biodistribution of drugs in the body, targeted delivery of chemotherapeutic agents with aptamers is a very effective method. In this strategy, aptamers could be specifically identified and attach to targeted molecules on the cancerous cells and deliver the chemotherapeutic agents to desired tissue with minimal or no damage to the normal cells. In this study, we designed anti-epithelial cell adhesion molecule (EpCAM) RNA aptamer conjugated PEGylated liposomal doxorubicin (ER-lip) to investigate its in vitro and in vivo anticancer abilities. Data showed that EpCAM aptamer was able to enhance cell uptake and cytotoxic effects of Dox in C26 cell line. The biodistribution study indicated that ER-lip enhanced the tumor accumulation of Dox compared to Caelyx. Also, double staining of isolated tumor cells with anti-CD44-PE-cy5 and anti-EpCAM Cy-7 antibodies indicated that tumor cells expressed a high level of EpCAM+ CD44+ cells (p ≤ .001) compared to cultured C26 cell line. in vivo results showed that ER-lip promoted survival and reduced tumor growth rate in animal model compared to Caelyx. In conclusion, these results suggested that the ER-lip could be served as promising formulation for the treatment of cancers with the high expression of EpCAM.

Home quarantine is a useful strategy to prevent the coronavirus outbreak: Identifying the reasons for non-compliance in some Iranians.

INTRODUCTION: The coronavirus outbreak has become a worrying issue and some people refuse to stay at home. Therefore, this study aims to identify the reasons behind some Iranian people's refusal to stay at home to prevent further virus transmission. METHOD: This cross-sectional study was conducted on postgraduate students in Iran. A questionnaire was designed based on 50 experts' opinions by using the Delphi method and 203 students completed the designed questionnaire in telegram groups. RESULTS: 35% of participants were upper 30 years of age, 70.4% were female, 74.4% had no coronavirus infection among their relatives, and 54.7% of them were Ph.D. candidates. The relations between "unclear accountability of events by some officials" and age as well as "failure to provide dissenting viewpoints and critical comments" and age were statistically significant (p = 0.027، p = 0.014). Moreover the relation between coronavirus infected relative and "persistent beliefs" was statistically significant (p = 0.014). The Chi-square test showed that gender, degree, resident and education province did not affect questions answering. The greatest agreement with questions is as following: lack of real situation understanding; 89.7%, people's livelihoods, and lack of government planning for low-income groups support; 86.7%, lack of people's knowledge concerning the coronavirus; 80.8%, lack of communicative educations for crisis situations; 79.8%, false assurance as well as minimizes the risks; 78.3%. CONCLUSION: Identifying the non-compliance factors with health recommendations can guide health care providers and managers to implementation of beneficial intervention.

COVID-19 in cardiac arrest and infection risk to rescuers: A systematic review.

BACKGROUND: There may be a risk of COVID-19 transmission to rescuers delivering treatment for cardiac arrest. The aim of this review was to identify the potential risk of transmission associated with key interventions (chest compressions, defibrillation, cardiopulmonary resuscitation) to inform international treatment recommendations. METHODS: We undertook a systematic review comprising three questions: (1) aerosol generation associated with key interventions; (2) risk of airborne infection transmission associated with key interventions; and (3) the effect of different personal protective equipment strategies. We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and the World Health Organization COVID-19 database on 24th March 2020. Eligibility criteria were developed individually for each question. We assessed risk of bias for individual studies, and used the GRADE process to assess evidence certainty by outcome. RESULTS: We included eleven studies: two cohort studies, one case control study, five case reports, and three manikin randomised controlled trials. We did not find any direct evidence that chest compressions or defibrillation either are or are not associated with aerosol generation or transmission of infection. Data from manikin studies indicates that donning of personal protective equipment delays treatment delivery. Studies provided only indirect evidence, with no study describing patients with COVID-19. Evidence certainty was low or very low for all outcomes. CONCLUSION: It is uncertain whether chest compressions or defibrillation cause aerosol generation or transmission of COVID-19 to rescuers. There is very limited evidence and a rapid need for further studies. Review registration: PROSPERO CRD42020175594.

Targeting the leptin receptor: To evaluate therapeutic efficacy and anti-tumor effects of Doxil, in vitro and in vivo in mice bearing C26 colon carcinoma tumor.

Leptin is an appetite regulatory hormone that is secreted into the blood circulation by the adipose tissue and it functions via its over expressed receptors (Ob-R) in a wide variety of cancers. In the present study, the function of a leptin-derived peptide (LP16, 91-110 of Leptin) was investigated as a targeting ligand to decorate PEGylated liposomal doxorubicin (PLD, Doxil®) surface and the anti-tumor activity and therapeutic efficacy of Doxil in C26 (Colon Carcinoma) tumor model were also evaluated. As a result of this, Doxil with different LP16 peptide density (25, 50, 100 and 200 peptide on the surface of each liposome) was successfully prepared and characterized. In vitro results showed significant enhanced cytotoxicity and cellular binding and uptake of LP16-targeted Doxil formulations (LP16-Doxil) in C26 cells as compared to Doxil. In BALB/c mice bearing C26 murine carcinoma, at a dose of 15 mg/kg, LP16-Doxil groups (100 ligand) significantly suppressed the growth of the tumor and showed higher inclination to tumor as compared to non-targeted Doxil. This study revealed that the potential of LP16 peptide targeting increased the therapeutic efficacy of Doxil and highlighted the importance of optimizing the ligand density to maximize the targeting ability of the nanocarriers and merits further investigations.

Dual-porosity poroviscoelasticity and quantitative hydromechanical characterization of the brain tissue with experimental hydrocephalus data.

Hydromechanical brain models often involve constitutive relations which must account for soft tissue deformation and creep, together with the interstitial fluid movement and exchange through capillaries. The interaction of rather unknown mechanisms which produce, absorb, and circulate the cerebrospinal fluid within the central nervous system can further add to their complexity. Once proper models for these phenomena or processes are selected, estimation of the associated parameters could be even more challenging. This paper presents the results of a consistent, coupled poroviscoelastic modeling and characterization of the brain tissue as a dual-porosity system. The model draws from Biot's theory of poroviscoelasticity, and adopts the generalized Kelvin's rheological description of the viscoelastic tissue behavior. While the interstitial space serves as the primary porosity through which the bulk flow of the interstitial fluid occurs, a secondary porosity network comprising the capillaries and venous system allows for its partial absorption into the blood. The correspondence principle is used in deriving a time-dependent analytical solution to the proposed model. It allows for identical poroelastic formulation of the original poroviscoelastic problem in the Laplace transform space. Hydrocephalus generally refers to a class of medical conditions which share the ventricles enlargement as a common feature. A set of published data from induced hydrocephalus and follow-up perfusion of cats' brains is used for quantitative characterization of the proposed model. A selected portion of these data including the ventricular volume and rate of fluid absorption from the perfused brain, together with the forward model solution, is utilized via an inverse problem technique to find proper estimations of the model parameters. Results show significant improvement in model predictions of the experimental data. The convoluted and coupled solution results are presented through the time-dependent plots of the ventricular volume undergoing the perfusion experiment. The plots demonstrate the intricate interplay of viscous and poroelastic diffusive time scales, and their competition in reaching the steady state response of the system.

General solutions to poroviscoelastic model of hydrocephalic human brain tissue.

Hydrocephalus is a well-known disorder of brain fluidic system. It is commonly associated with complexities in cerebrospinal fluid (CSF) circulation in brain. In this paper, hydrocephalus and shunting surgery which is used in its treatment are modeled. Brain tissues are considered to follow a poroviscoelastic constitutive model in order to address the effects of time dependence of mechanical properties of soft tissues and fluid flow hydraulics. Our solution draws from Biot's theory of poroelasticity, generalized to account for viscoelastic effects through the correspondence principle. Geometrically, the brain is conceived to be spherically symmetric, where the ventricles are assumed to be a hollow concentric space filled with cerebrospinal fluid. A generalized Kelvin model is considered for the rheological properties of brain tissues. The solution presented is useful in the analysis of the disorder of hydrocephalus as well as the treatment associated with it, namely, ventriclostomy surgery. The sensitivity of the solution to various factors such as aqueduct blockage level and trabeculae stiffness is thoroughly analyzed using numerical examples. Results indicate that partial aqueduct stenosis may be a cause of hydrocephalus. However, only severe occlusion of the aqueduct can cause a significant increase in the ventricle and brain's extracellular fluid pressure. Ventriculostomy shunts are commonly used as a remedy to hydrocephalus. They serve to reduce the ventricular pressure to the normal level. However, sensitivity analysis on the shunt's fluid deliverability parameter has shown that inappropriate design or selection of design shunt may cause under-drainage or over-drainage of the ventricles. Excessive drainage of CSF may increase the normal tensile stress on trabeculae. It can cause rupture of superior cerebral veins or damage to trabeculae or even brain tissues which in turn may lead to subdural hematoma, a common side-effect of the surgery. These Post-Surgery Reaction (PSR) patterns might occur on much larger time scales than those of the surgery itself, depending on the flow conductivity parameters of the brain. The viscoelastic effects can be significant contingent on the long term tissue moduli and their contrast with the initial ones.