Effect of Cationic Groups on the Selectivity of Ternary Antimicrobial Polymers.

Antimicrobial polymers (AMPs) have emerged as a promising approach to combat multidrug-resistant pathogens. Developed from binary polymers, which contain cationic and hydrophobic groups, ternary polymers are enhanced by adding neutral hydrophilic monomers to improve their biocompatibility. Cationic groups have attracted significant attention owing to their pivotal role in AMPs. Although many studies have investigated the effect of cationic groups on antimicrobial activity of binary AMPs, there is a lack of comprehensive and systematic evaluation for ternary AMPs. Therefore, a library of 31 statistical amphiphilic ternary polymers containing different cationic groups, including primary amine, guanidine, and sulfonium groups is prepared to investigate the impact of cationic groups on antimicrobial activity and biocompatibility. It is shown that the cationic balance appears to be a critical factor influencing polymers' antibacterial activity and selectivity. The results reveal that the polymers that have the ratio of the cationic groups ranging between 50% and 60%, coupled with a cationic/hydrophobic ratio in the range of [1.4-2] and an appropriate neutral hydrophilic/hydrophobic balance, exhibited the highest selectivity toward mammalian cells. This study elucidates a structure-property-performance relationship for ternary AMPs, which contributes to the development of AMPs capable of selectively targeting gram-negative pathogens.

Synthesis of glycyrrhetinic acid-modified liposomes to deliver Murrayafoline A for treatment of hepatocellular carcinoma.

Hepatocellular carcinoma is a common type of cancer associated with a high mortality rate. Among several bioactive compounds, Murrayafoline A (MuA) has been proved as a bio substance that exhibits great potentials in treating liver cancer. In order to overcome the high cytotoxicity and low solubility of MuA, a delivery system based on nanocarriers is necessary to deliver MuA towards the desired target. In the present study, 18ß-glycyrrhetinic acid (GA), which is known as a ligand for liver targeting, was used to construct the cholesterol-poly (ethylene glycol)-glycyrrhetinic acid (GA-PEG-Chol) conjugate and liposome for MuA administration. The compound was then examined for therapeutic efficacy and safety in HUVEC and HepG2 cells in 2D and 3D cell cultures. Results have shown that MuA-loaded liposomes had IC50 value of 2 µM in HepG2 and had the cytosolic absorption of 8.83 ± 0.97 ng/105 cells, while The IC50 value of MuA-loaded liposomes in HUVEC cell lines was 15 µM and the the cytosolic absorption was recorded as 3.62 ± 0.61 cells. The drug test on the 3D cancer sphere platform of the HepG2 cancer sphere showed that MuA-loaded GA liposomes had the highest efficacy at a concentration of 100 µg/mL. In short, these results suggest that MuA-loaded GA liposomes have the potential for maintenance drug delivery and liver targeting.

Simple and Rapid Method of Microwell Array Fabrication for Drug Testing on 3D Cancer Spheroids.

Three-dimensional (3D) cell culture systems are becoming increasingly popular due to their ability to mimic the complex process of angiogenesis in cancer, providing more accurate and physiologically relevant data than traditional two-dimensional (2D) cell culture systems. Microwell systems are particularly useful in this context as they provide a microenvironment that more closely resembles the in vivo environment than traditional microwells. Poly(ethylene glycol) (PEG) microwells are particularly advantageous due to their bio-inertness and the ability to tailor their material characteristics depending on the PEG molecular weight. Although there are several methods available for microwell fabrication, most of them are time-consuming and expensive. The current study utilizes a low-cost laser etching technique on poly(methyl methacrylate) materials followed by molding with PDMS to produce microwells. The optimal conditions for making concave microwells are an engraving parameter speed of 600 mm/s, power of 20%, and a design diameter of the microwell of 0.4 mm. The artificial tumor achieved its full size after 7 days of cell growth in a microwell system, and the cells developed drugs through a live/dead assay test. The results of the drug testing revealed that the IC50 value of zerumbone-loaded liposomes in HepG2 was 4.53 pM, which is greater than the IC50 value of zerumbone. The HepG2 cancer sphere's 3D platform for medication testing revealed that zerumbone-loaded liposomes were very effective at high doses. These findings generally imply that zerumbone-loaded liposomes have the capacity to target the liver and maintain medication delivery.

Ethnic minority women's empowerment in agriculture in the central region of Viet Nam.

Gender inequality and women's empowerment are two closely related issues. While the gender inequality index has been assessed by different studies, that of women's empowerment remained limited. In the present work, we attempted to evaluate the women's empowerment index by comparing it with the male partner's empowerment index in the same household. We used the Women's Empowerment in Agriculture Index (WEAI) as a framework for reference. A questionnaire was designed to interview 300 people including both men and women in the same ethnic minority household in central Vietnam. The difference in the empowerment level between men and women was assessed through five-component empowerment indicators: agricultural participation, resource ownership, financial control, social organizations participation, and time usage. The results showed that up to 70% of women were disempowered compared to only 15% of men. The binary logistic model revealed the age at first marriage, the level of children's education, education level, distance to the nearest urban area, and the number of children were associated with women's empowerment; whereas age, income, and the level of gender awareness did not show any correlation.

The Utilization of Machine Learning Algorithms for Assisting Physicians in the Diagnosis of Diabetes.

This paper investigates the use of machine learning algorithms to aid medical professionals in the detection and risk assessment of diabetes. The research employed a dataset gathered from individuals with type 2 diabetes in Ninh Binh, Vietnam. A variety of classification algorithms, including Decision Tree Classifier, Logistic Regression, SVC, Ada Boost Classifier, Gradient Boosting Classifier, Random Forest Classifier, and K Neighbors Classifier, were utilized to identify the most suitable algorithm for the dataset. The results of the present study indicate that the Random Forest Classifier algorithm yielded the most promising results, exhibiting a cross-validation score of 0.998 and an accuracy rate of 100%. To further evaluate the effectiveness of the selected model, it was subjected to a testing phase involving a new dataset comprising 67 patients that had not been previously seen. The performance of the algorithm on this dataset resulted in an accuracy rate of 94%, especially the study's notable finding is the algorithm's accurate prediction of the probability of patients developing diabetes, as indicated by the class 1 (diabetes) probabilities. This innovative approach offers a meticulous and quantifiable method for diabetes detection and risk evaluation, showcasing the potential of machine learning algorithms in assisting clinicians with diagnosis and management. By communicating the diabetes score and probability estimates to patients, the comprehension of their disease status can be enhanced. This information empowers patients to make informed decisions and motivates them to adopt healthier lifestyle habits, ultimately playing a crucial role in impeding disease progression. The study underscores the significance of leveraging machine learning in healthcare to optimize patient care and improve long-term health outcomes.

Lower Extremity Nerve Conduction Abnormalities in Vietnamese Patients with Type 2 Diabetes: A Cross-Sectional Study on Peripheral Neuropathy and Its Correlation with Glycemic Control and Renal Function.

Peripheral neuropathy is a common complication of type 2 diabetes mellitus (T2DM) that results in nerve conduction abnormalities. This study aimed to investigate the parameters of nerve conduction in lower extremities among T2DM patients in Vietnam. A cross-sectional study was conducted on 61 T2DM patients aged 18 years and older, diagnosed according to the American Diabetes Association's criteria. Data on demographic characteristics, duration of diabetes, hypertension, dyslipidemia, neuropathy symptoms, and biochemical parameters were collected. Nerve conduction parameters were measured in the tibial and peroneal nerves, including peripheral motor potential time, response amplitude M, and motor conduction speed, as well as sensory conduction in the shallow nerve. The study found a high rate of peripheral neuropathy among T2DM patients in Vietnam, with decreased conduction rate, motor response amplitude, and nerve sensation. The incidence of nerve damage was highest in the right peroneal nerve and left peroneal nerve (86.7% for both), followed by the right tibial nerve and left tibial nerve (67.2% and 68.9%, respectively). No significant differences were found in the rate of nerve defects between different age groups, body mass index (BMI) groups, or groups with hypertension or dyslipidemia. However, a statistically significant association was found between the rate of clinical neurological abnormalities and the duration of diabetes (p < 0.05). Patients with poor glucose control and/or decreased renal function also had a higher incidence of nerve defects. The study highlights the high incidence of peripheral neuropathy among T2DM patients in Vietnam and the association between nerve conduction abnormalities and poor glucose control and/or decreased renal function. The findings underscore the importance of early diagnosis and management of neuropathy in T2DM patients to prevent serious complications.

Fabrication of a Low-Cost Microfluidic Device for High-Throughput Drug Testing on Static and Dynamic Cancer Spheroid Culture Models.

Drug development is a complex and expensive process from new drug discovery to product approval. Most drug screening and testing rely on in vitro 2D cell culture models; however, they generally lack in vivo tissue microarchitecture and physiological functionality. Therefore, many researchers have used engineering methods, such as microfluidic devices, to culture 3D cells in dynamic conditions. In this study, a simple and low-cost microfluidic device was fabricated using Poly Methyl Methacrylate (PMMA), a widely available material, and the total cost of the completed device was USD 17.75. Dynamic and static cell culture examinations were applied to monitor the growth of 3D cells. α-MG-loaded GA liposomes were used as the drug to test cell viability in 3D cancer spheroids. Two cell culture conditions (i.e., static and dynamic) were also used in drug testing to simulate the effect of flow on drug cytotoxicity. Results from all assays showed that with the velocity of 0.005 mL/min, cell viability was significantly impaired to nearly 30% after 72 h in a dynamic culture. This device is expected to improve in vitro testing models, reduce and eliminate unsuitable compounds, and select more accurate combinations for in vivo testing.

A low-cost, flexible extruder for liposomes synthesis and application for Murrayafoline A delivery for cancer treatment.

Liposomal encapsulation is a drug delivery strategy with many advantages, such as improved bioavailability, ability to carry large drug loads, as well as controllability and specificity towards various targeted diseased tissues. Currently, most preparation techniques require an additional extrusion or filtering step to obtain monodisperse liposomes with the size of less than 100 nm. In this study, a compact liposome extruder was designed at a cost of $4.00 and used to synthesize liposome suspensions with defined particle size and high homogeneity for Murrayafoline A (Mu-A) loading and release. The synthesized MuA-loaded liposomes displayed a biphasic drug release and remained stable under the storage condition of 4°C. They also significantly reduced the viability of HepG2 cells in the cancer spheroids by 25%. The low-cost, flexible liposome extruder would allow the researchers to study liposomes and their applications in a cost-effective manner.

Cyclodextrin glycosyltransferase-treated germinated brown rice flour improves the cytotoxic capacity of HepG2 cell and has a positive effect on type-2 diabetic mice.

Germinated brown rice (GBR) consists of bioactive compounds (BCs) that are very useful for diabetes treatment. Modified GBR-based flour (MGBRF) was produced by modifying the starch in GBR with 0, 299.19, 598.38, and 897.57 U/ml of cyclodextrin glycosyltransferase (CGTase) for 1 hr and then spray-dried to examine its antidiabetic and cytotoxic effects. The results showed that the slowly digestible starch and resistant starch by modifying the starch in GBR with 598.38 U/ml of CGTase were 55.8% and 5.92% corresponding to the increase of γ-amino butyric acid (GABA) and ferulic acid (FA) with 4.31 ± 0.68 mg/ml and 3.10 ± 0.02 mg/ml, respectively. The extract from MGBRF showed strong cytotoxic capacity against HepG2. Furthermore, the in vivo study revealed the stability of the glycemic index (GI) by consuming MGBRF with significant impacts on diabetes. These results suggest that MGBRF through the action of CGTase plays a major role in antidiabetes and HepG2 cell product value addition. PRACTICAL APPLICATIONS: GBR consists of BCs that are useful for diabetes and cancer treatment. However, when using this or GBR-based products, it is difficult to evaluate the effect of functional properties, especially for diabetes and/or cancer diseases due to high starch content. Therefore, the modification of starch to limit digestible starch, increase SDS and RS as well as to enhance the effect of BCs on diabetes and cytotoxic activity on cancer cell should be studied before producing various based products from GBR. The results in this study indicated that CGTase increased BCs without any glycosides BCs in the extract. The MGBRF changed to higher RS and SDS while increasing the BCs. The extract of MGBRF showed strong cytotoxic activity against HepG2 cell and a positive effect on type 2-diabetic mice. Hence, this study produces new information for effective use of GBR-based food as a functional food.

Optimization of Sample Preparation for Detection of 10 Phthalates in Non-Alcoholic Beverages in Northern Vietnam.

A novel method was developed for the sensitive, cheap and fast quantitation of 10 phthalates in non-alcoholic beverages by liquid⁻liquid extraction (LLE) combined with gas chromatography tandem mass spectrometry (GC-MS/MS). The best results were obtained when n-hexane was used as extraction solvent. A central composite design (CCD) was applied to select the most appreciated operating condition. The method performance was evaluated according to the SANTE/11945/2015 guidelines and was linear in the 0.1 to 200 µg/L range for 10 phthalate compounds, with r² > 0.996 and individual residuals <15%. Repeatability (RSDr), within-laboratory reproducibility (RSDwr), and the trueness range were from 2.7 to 9.1%, from 3.4 to 14.3% and from 91.5 to 118.1%, respectively. The limit of detection (LOD) was between 0.5 to 1.0 ng/L and the limit of quantitation (LOQ) was between 1.5 to 3.0 ng/L for all 10 compounds. The developed method was successfully applied to the analysis of non-alcoholic beverages.

Investigating Glioblastoma Angiogenesis Using A 3D in Vitro GelMA Microwell Platform.

Angiogenesis is an indispensable mechanism in physiological and pathological development of tumors that requires an adequate blood supply. Therefore, understanding the angiogenesis mechanism of tumors has become an important research area to develop reliable and effective therapies for the treatment of tumors. Although several in vivo and in vitro models were developed and used to study the underlying mechanism of angiogenesis, they showed limited success. Therefore, there is an urgent need to build a stable and cost-effective three-dimensional (3D) in vitro angiogenesis model to investigate the tumor formation. In this study, we designed a 3D in vitro angiogenesis model based on gelatin methacrylate (GelMA) hydrogel microwells to mimic an in vivo-like microenvironment for co-cultured glioblastoma and endothelial cells. Our results confirmed the in vitro formation of microtubules during the angiogenic process. We believe that our cost-effective platform can be used for the high-throughput screening of anti-angiogenesis drugs and even for the development of better treatment strategies.

TNP-470 Reduces Glioblastoma Angiogenesis in Three Dimensional GelMA Microwell Platform.

Tumor angiogenesis is a promising target for cancer treatment, because severing the supply of oxygen and nutrients to tumors halts tumor growth. Unfortunately, many anticancer drugs, including angiogenesis inhibitors, fail in clinical trials, despite showing high efficiency during in vitro and in vivo experiments. This inconsistency from in vitro and in vivo experiments to clinical trials represents a major obstacle in drug development and cancer treatment. Therefore, we set out to demonstrate how our rapid, stable, easy-to-use three-dimensional (3-D) in vitro angiogenesis model can be used to investigate tumor formation and implement drug screening. In this study, we utilized a 3-D in vitro angiogenesis model, based on gelatin methacrylate (GelMA) hydrogel microwells, to mimic the native microenvironment of tumor angiogenesis. Using this model, we were able to quantify the immigration of endothelial cells into a cancer spheroid during the angiogenic process. Next, we tested the anti-angiogenic effect of the angiogenesis inhibitor, TNP-470, on the cancer spheroids in the model. Based on our results, we believe that this novel in vitro system can be widely used for the high-throughput screening of other anti-angiogenic drugs, and could contribute to the development of personalized medicine in the future.

Engineering a Brain Cancer Chip for High-throughput Drug Screening.

Glioblastoma multiforme (GBM) is the most common and malignant of all human primary brain cancers, in which drug treatment is still one of the most effective treatments. However, existing drug discovery and development methods rely on the use of conventional two-dimensional (2D) cell cultures, which have been proven to be poor representatives of native physiology. Here, we developed a novel three-dimensional (3D) brain cancer chip composed of photo-polymerizable poly(ethylene) glycol diacrylate (PEGDA) hydrogel for drug screening. This chip can be produced after a few seconds of photolithography and requires no silicon wafer, replica molding, and plasma bonding like microfluidic devices made of poly(dimethylsiloxane) (PDMS). We then cultured glioblastoma cells (U87), which formed 3D brain cancer tissues on the chip, and used the GBM chip to perform combinatorial treatment of Pitavastatin and Irinotecan. The results indicate that this chip is capable of high-throughput GBM cancer spheroids formation, multiple-simultaneous drug administration, and a massive parallel testing of drug response. Our approach is easily reproducible, and this chip has the potential to be a powerful platform in cases such as high-throughput drug screening and prolonged drug release. The chip is also commercially promising for other clinical applications, including 3D cell culture and micro-scale tissue engineering.