The experiment was carried out during October 2022 to January 2023 at Mae Hea Agricultural Research, Demonstration and Training Center, Faculty of Agriculture, Chiang Mai University, Chiang Mai Province, Thailand; latitude: 18° 44′ 36″ North, Longitude: 98° 57′ 50″ East, and an al-titude 304 msl. Evaporative greenhouse, 9.6 x 40 square meters, with 8 planting troughs was prepared, Sensors and Internet of Things (IoT) system were installed to monitor continuously vital parameters, collect data, and send timely alerts to facilitate problem resolution. The data were displayed via IoT platform dashboard. An average air temperature, light intensity, media moisture and CO2 concentration in the greenhouse during 4 months was 21.1 ◦C, 12,948 Lux, 2 kPa and 495 ppm, respectively. The average maximum temperature in the evaporative greenhouse was 29.6 ◦C, which 4.2 ◦C lower than outside; 33.8 ◦C. Root-zone cooling of the strawberry planting was de-signed as factorial 3x4 in completely randomized design (CRD). Factor A was the short-day strawberry cultivars: 1) “Pharachatan 88” 2) “Pharachatan 80” and 3) “Akihime”. Factor B was the root-zone cooling treatments: 1) normal water dripping (NWD) 2) cold water dripping (CWD) 3) cold water dripping + cold water piping (CWD+CWP) and 4) normal water dripping + cold water piping (NWD+CWP). The results revealed that there was an interaction between the two factors on canopy width, leave width, crown diameter, number of flowers, fruit qualities and fruit color, whereas plant height, leaves length, SPAD and number of inflorescences were not affected by the interaction between the two factors. Four months after the experiment, the root-zone cooling treatments had no effect on chlorophyll contents, whereas “Pharachatan 80” had lower chlorophyll content than others. The CWD+CWP treatment could reduce 2 °C of root-zone temperature and leading to promote vegetative and reproductive growth in strawberry plants. Anyhow, without the root-zone cooling treatment, “Akihime”and “Pharachatan 88” still could produce flowers and yield, but “Pharachatan 80” could not. Furthermore, “Akihime” seemed appreciable in flowering, TSS and yield as compared to others.

Valsartan (Val) is an important antihypertensive medication with side effects such as dizziness and angioedema. These constraints are due to the low oral bioavailability and relatively short half-life. The goal here is to incorporate Val into a mixed micelles system that can enhance transdermal delivery. Thin-film hydration and micro-phase separation were used to produce Val-loaded mixed micelle systems. A variety of factors, including surfactant type and drug-to-surfactant ratio, were optimized to produce micelles with low size and high Val entrapment efficiency (EE). The size, polydispersity index (PDI), zeta-potential, and drug entrapment efficiency of the prepared micelles were all measured. The drug release profiles in vitro were assessed using dialysis bags, and the permeation through abdominal rat skin was assessed using a Franz diffusion cell. All formulations had high EE levels exceeding 90% and low particle charges. The micellar sizes ranged from 107.6 to 191.7nm, with average PDI values of 0.3. The in vitro release demonstrated a uniform slow rate that lasted one week with varying extents. F7 demonstrated a significant (P < 0.01) transdermal efflux of 68.84 ± 3.96 µg/cm2/h through rat skin when compared to the control. As a result, the enhancement factor was 16.57. Val-loaded mixed micelles were successfully prepared using two simple methods with high reproducibility, and extensive transdermal delivery was demonstrated in the absence of any aggressive skin modifying enhancers.

Breast cancer is the most widespread malignancy in women from corner to corner of the world. Nanostructured lipid carrier (NLC) proved its efficacy in the treatment of cancer. NLC loaded with Imatinib (IMA) (NANIMA) was prepared and evaluated for in vitro efficacy in MCF-7 breast cancer cells. Hot homogenization method was used for the preparation of NANIMAs. Aqueous solution of surfactants (hot) was mixed with molten mixture of stearic acid and sesame oil (hot) under homogenization. The prepared NANIMAs were characterized and evaluated for size, polydispersity index, zeta potential, encapsulation efficiency, release studies, stability studies and MTT assay (cytotoxicity studies). The optimized NANIMA revealed particle size of 104.63 ± 9.55 d.nm, PdI of 0.227 ± 0.06 and EE of 99.79 ± 0.03. All NANIMAs revealed slow and sustained release behaviour. The surfactants used in the preparation of NANIMAs exhibited their effects on particle size, zeta potential, encapsulation efficiency, stability studies and release studies. The cytotoxicity studies unveiled 8.75 times increase in cytotoxicity for optimized NANIMA (IC50 = 6 µM) when compared with IMA alone (IC50 = 52.5 µM) on MCF-7 breast cancer cells. After this, NLC containing IMA possibly will be employed for the cure of breast cancer. A lesser amount of IMA loaded NLC will be sufficient than IMA alone for the treatment of breast cancer. Moreover, the patient will exhibit not as much of adverse effects as in case of IMA alone. Consequently, NANIMA could prove to be useful for effective therapeutic outcome in breast cancer treatment.

Background and aims: Only one cohort study exists on the incidence of the risk of malnutrition (RM) in older adults, though numerous cross-sectional –and that cohort research– have reported several risk factors associated with the prevalence and incidence of this condition. However, alterations of body composition and impaired physical performance as exposition variables of RM have not been explored. This study assessed the incidence of RM and determined its association with excess fat mass, low total lean tissue, gait speed, and handgrip strength as exposition variables for RM in community-dwelling older adults. Methods: This is a secondary analysis in older adults (≥60 years old) derived from the study “Frailty, dynapenia, and sarcopenia in Mexican adults (FraDySMex)” a prospective cohort project conducted from 2014 to 2019 in Mexico City. At baseline, volunteers underwent body composition analysis and physical performance tests. Several covariates were identified through comprehensive geriatric assessment. At baseline and follow-up, RM was assessed using the long form of the mini nutritional assessment (MNA-LF) scale. Associations between the exposition variables and RM were assessed by multiple logistic regression. Results: The cohort included 241 subjects. Average age was 75.6±7.8 years; 83.4% were women. The mean follow-up period was 4.1 years, during which 28.6% of subjects developed RM. This condition was less likely to occur in subjects with excess fat mass index, even after adjusting for several covariates. RM was also more likely to occur in subjects with low total lean tissue index, according to both an unadjusted model and after adjusting for the corresponding variables. Regarding the association between RM and gait speed, RM was also more likely to occur in subjects with low gait speed according to both the unadjusted and adjusted models. Similar results were found for RM in relation to low handgrip strength; however, after adjusting for the associated covariates, models 1 and 2 no longer reached the level of significance. Conclusion: The risk of malnutrition diagnosed by MNA-LF was significantly less likely to occur among subjects with excess fat mass, but possibility was significantly higher in those with low total lean tissue and low gait speed after 4.1 years of follow-up in community-dwelling older adults. These results highlight that excess fat mass, low total lean tissue, and low gait speed are first than risk of malnutrition and not vice versa.

Background: The oldest old people (≥ 85 years) represent the fastest growing age group in Western populations. Knowledge on early outcomes of acute ischemic stroke (AIS) in very old female patients remains limited. Methods: We assessed gender differences and female-specific clinical data and in-hospital mortality in very old patients with AIS. Acute cerebral infarction was diagnosed in 506 very old female patients from a total of 4,600 acute cerebrovascular infarctions available in an ongoing 24-year hospital stroke data bank. A comparative analysis of vital status at discharge (alive versus dead) was performed in terms of cardiovascular risk factors, clinical data, and early outcomes. Results: The overall in-hospital mortality rate was 20.4%. In multivariate analysis, sudden onset, altered level of consciousness, and neurological, respiratory, cardiological or hemorrhagic complications, and lacunar infarcts appeared to be independent predictors of in-hospital mortality. Conclusions: Female patients ≥85 years with AIS are an unfavorable subgroup of stroke patients with a high risk of early mortality, which may be due to comorbidity, stroke subtype distribution, and higher frequency of medical complications. However, the presence of lacunar infarcts showed a significant protective effect.

Delay in data transmission is one of key performance indicators (KPIs) of a network. The planning and project value of delay in network management is of crucial importance for the optimal allocation of network resources and their performance focuses. To create optimal solutions, predictive models, which are currently most often based on machine learning (ML), are used. This paper aims to investigate the training, testing and selection of the best predictive delay model for a VoIP service in an Long Term Evolution (LTE) network using three ML techniques - Neural Networks (NN), Support Vector Machines (SVM) and k-Nearest Neighbors (k-NN). The space of model input variables is optimized by dimensionality reduction techniques: RReliefF algorithm, Backward selection via the recursive feature elimination algorithm and the Pareto 80/20 rule. A three-segment road in the geo-space between the cities of Banja Luka (BL) and Doboj (Db) in the Republic of Srpska (RS), Bosnia and Herzegovina (BiH), covered by the cellular network (LTE) of the M:tel BL operator was chosen for the case study. The results show that, in all three optimization approaches, the k-NN model is selected as the best solution. For the RReliefF optimization algorithm, the best model has 6 inputs and minimum relative error (RE), RE=0.109; for the Backward selection via the recursive feature elimination algorithm, the best model has 4 inputs and RE=0.041; and for the Pareto 80/20 rule, the best model has 11 inputs and RE= 0.049. The comparative analysis of the results concludes that according to observed criteria for the selection of the final model, the best solution is an approach to optimizing the number of predictors based on the Backward selection via the recursive feature elimination algorithm.

Thirteen benzylethylenearyl ureas and one carbamate have been designed, synthesized and biologically evaluated as regards their antiproliferative activity on tumor cell lines HEK-293 and A-549 and on the immune and endothelial Jurkat T cells and HMEC-1, respectively. A relationship between the structure of the synthetic compounds and their antiproliferative activity has been established. Compounds C.1, C.3, C.12 and C.14 were chosen for further biological studies in order to determine their potential as oncoimmunomodulating agents. Some compounds exhibited significant inhibitory effects on both total PD-L1 and VEGFR-2 in HT-29 cell line, showing urea C.12 active against both targets. Some compounds could reduce more than 50% of cancer living cells, compared to non-treated ones, when assessed in co-cultures using HT-29 and THP-1 cells. In addition, these compounds showed no effect on the immune cell viability and significantly reduce CD11b expression, which is a promising target for immune modulation in anti-cancer therapies.