Double-barrier membranes: coupling hydrophilic coatings with biocidal Ag-MOFs for sustainable (bio)fouling mitigation and biofilm inhibition

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Operating Room Scheduling in Teaching Hospitals

Operating room scheduling is an important operational problem in most hospitals. In this paper, a novel mixed integer programming (MIP) model is presented for minimizing Cmax and operating room idle times in hospitals. Using this model, we can determine the allocation of resources including operating rooms, surgeons, and assistant surgeons to surgeries, moreover the sequence of surgeries within operating rooms and the start time of them. The main features of the model will include the chronologic curriculum plan for training residents and the real-life constraints to be observed in teaching hospitals. The proposed model is evaluated against some real-life problems, by comparing the schedule obtained from the model and the one currently developed by the hospital staff. Numerical results indicate the efficiency of the proposed model compared to the real-life hospital scheduling, and the gap evaluations for the instances show that the results are generally satisfactory

Influence of Salicylic Acid and Citric Acid on the Growth, Biochemical Characteristics and Essential Oil Content of Thyme (Thymus vulgaris L.)

This study was conducted to determine the effect of foliar salicylic acid (SA) and citric acid (CA) applications on growth, biochemical characteristics and essential oil content of thyme (Thymus vulgaris L.) grown under field conditions. Salicylic acid (0.5 and 1 mM) and citric acid (5 and 10 mM) were applied three times during the vegetation at 15 day intervals. Results revealed that foliar application of SA and CA significantly enhanced the vegetative characters i.e. fresh and dry weight of thyme as well as pigments (chlorophyll a and carotenoids) content and essential oil production (1.3 fold as compared to control). There was a positive correlation between fresh and dry weights, chlorophyll a and essential oil. Citric acid treatment especially at 10 mM decreased malondialdehyde (MDA) content. According to our results, applications SA at rate of 0.5-1 or CA at 5 mM should be recommended in order to improve yield and essential oil production in thyme

Polyelectrolyte Complex Hollow Fiber Membranes Prepared via Aqueous Phase Separation

Hollow fiber (HF) membrane geometry is the preferred choice for most commercial membrane operations. Such fibers are conventionally prepared via the non-solvent-induced phase separation technique, which heavily relies on hazardous and reprotoxic organic solvents such as N-methyl pyrrolidone. A more sustainable alternative, i.e., aqueous phase separation (APS), was introduced recently that utilizes water as a solvent and non-solvent for the production of polymeric membranes. Herein, for the first time, we demonstrate the preparation of sustainable and functional HF membranes via the APS technique in a dry-jet wet spinning process. The dope solution comprising poly(sodium 4-styrenesulfonate) (PSS) and polyethyleneimine (PEI) at high pH along with an aqueous bore liquid is pushed through a single orifice spinneret into a low pH acetate buffer coagulation bath. Here, PEI becomes charged resulting in the formation of a polyelectrolyte complex with PSS. The compositions of the bore liquid and coagulation bath were systematically varied to study their effect on the structure and performance of the HF membranes. The microfiltration-type membranes (permeability ∼500 to 800 L·m–2·h–1·bar–1) with complete retention of emulsion droplets were obtained when the precipitation rate was slow. Increasing the concentration of the acetate buffer in the bath led to the increase in precipitation rate resulting in ultrafiltration-type membranes (permeability ∼12 to 15 L·m–2·h–1·bar–1) having molecular weight cut-offs in the range of ∼7.8–11.6 kDa. The research presented in this work confirms the versatility of APS and moves it another step closer to large-scale use

Adherence to a Paleolithic Diet in Combination With Lifestyle Factors Reduces the Risk for the Presence of Non-Alcoholic Fatty Liver Disease: A Case-Control Study

BackgroundEvidence suggests the role of changing traditional lifestyle patterns, such as Paleolithic, to the modern lifestyle in the incidence and epidemic of chronic diseases. The purpose of this study was to investigate the associations between the Paleolithic diet (PD) and the Paleolithic-like lifestyle and the risk of non-alcoholic fatty liver disease (NAFLD) among an adult population.Materials and MethodsThis case-control study was carried out among 206 patients with NAFLD and 306 healthy subjects aged >18 years. PD score was evaluated using a validated 168-item quantitative food frequency questionnaire. In addition, to calculate the Paleolithic-like lifestyle score, the components of physical activity, body mass index (BMI), and smoking status of the participants were combined with the score of the PD.ResultsThe mean PD and Paleolithic-like lifestyle scores were 38.11 ± 5.63 and 48.92 ± 6.45, respectively. After adjustment for potential confounders, higher scores of adherence to the PD diet conferred a protection for the presence of NAFLD [odds ratio (OR): 0.53; 95% confidence interval (CI): 0.28–0.98; P for trend = 0.021]. Furthermore, PD and healthy lifestyle habits were negatively associated with NAFLD (OR = 0.42, 95% CI 0.23–0.78; P for trend = 0.007).ConclusionOur data suggest that the PD alone and in combination with lifestyle factors was associated with decreased risk of NAFLD in a significant manner in the overall population. However, prospective studies are needed to further investigate this association

Predkliničke studije [61Cu]ATSM kao PET radiofarmaka za snimanje fibrosarkoma

[61Cu]diacetyl-bis(N4-methylthiosemicarbazone) ([61Cu]ATSM) was prepared using in house-made diacetyl-bis(N4-methylthiosemicarbazone) (ATSM) ligand and [61Cu]CuCl2 produced via the natZn(p,x)61Cu (180 μA proton irradiation, 22 MeV, 3.2 h) and purified by a ion chromatography method. [61Cu]ATSM radiochemical purity was >98%, as shown by HPLC and RTLC methods. [61Cu]ATSM was administered into normal and tumor bearing rodents for up to 210 minutes, followed by biodistribution and co-incidence imaging studies. Significant tumor/non-tumor accumulation was observed either by animal sacrification or imaging. [61Cu]ATSM is a positron emission tomography (PET) radiotracer for tumor hypoxia imaging.[61Cu]diacetil-bis(N4-metiltiosemikarbazon) ([61Cu]ATSM) dobiven je iz liganda diacetil-bis(N4-metiltiosemikarbazona) (ATSM) pripravljenog u vlastitom laboratoriju i [61Cu]CuCl2 dobivenog iz natZn(p,x)61Cu (180 μA protonskim zračenjem, 22 MeV, 3.2 h). [61Cu]ATSM je čišćen ionskom kromatografijom. Prema HPLC i RTLC radiokemijska čistoća bila je > 98%. [61Cu]ATSM je davan zdravim glodavcima i glodavcima s tumorom tijekom 210 minuta te je praćena biodistribucija. Žrtvovanjem testiranih životinja te snimanjem primijećena je značajna razlika u akumulaciji [61Cu]ATSM u tumorskom tkivu u odnosu na zdravo tkivo. [61Cu]ATSM je pogodan za dijagnostiku hipoksije tumora pozitron emisijskom tomografijom (PET)

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Holistic Utility Satisfaction in Cloud Data Centre Network Using Reinforcement Learning

Cloud computing leads to efficient resource allocation for network users. In order to achieve efficient allocation, many research activities have been conducted so far. Some researchers focus on classical optimisation theory techniques (such as multi-objective optimisation, evolutionary optimisation, game theory, etc.) to satisfy network providers and network users’ service-level agreement (SLA) requirements. Normally, in a cloud data centre network (CDCN), it is difficult to jointly satisfy both the cloud provider and cloud customer’ utilities, and this leads to complex combinatorial problems, which are usually NP-hard. Recently, machine learning and artificial intelligence techniques have received much attention from the networking community because of their capability to solve complicated networking problems. In the current work, at first, the holistic utility satisfaction for the cloud data centre provider and customers is formulated as a reinforcement learning (RL) problem with a specific reward function, which is a convex summation of users’ utility functions and cloud provider’s utility. The user utility functions are modelled as a function of cloud virtualised resources (such as storage, CPU, RAM), connection bandwidth, and also, the network-based expected packet loss and round-trip time factors associated with the cloud users. The cloud provider utility function is modelled as a function of resource prices and energy dissipation costs. Afterwards, a Q-learning implementation of the mentioned RL algorithm is introduced, which is able to converge to the optimal solution in an online and fast manner. The simulation results exhibit the enhanced convergence speed and computational complexity properties of the proposed method in comparison with similar approaches from the joint cloud customer/provider utility satisfaction perspective. To evaluate the scalability property of the proposed method, the results are also repeated for different cloud user population scenarios (small, medium, and large)

Carboxymethyl cellulose-agar biocomposite film activated with summer savory essential oil as an antimicrobial agent

Carboxymethyl cellulose (CMC)-agar biocomposite film was developed by a solvent casting method and the effects of summer savory essential oil (SSEO) at 0.5, 1.0 and 1.5% v/v on antimicrobial, microstructural, mechanical and optical properties as well as water sensitivity of the films were studied. Results showed that incorporation of SSEO into the biocomposite film developed active films with good antimicrobial agent growth inhibition activity against Gram-positive bacteria (S.\ua0aureus,\ua0B.\ua0cereus\ua0and\ua0L.\ua0monocytogenes) and less powerfully against Gram-negative bacteria (E.\ua0coli). Addition of the SSEO at 1.0 and 1.5% increased microstructural heterogeneity of the films and hence significantly (p < 0.05) increased water vapor permeability of the films while reducing their tensile strength. In contrast, mechanical flexibility and surface hydrophobicity of the films was significantly (p < 0.05) improved as a function of SSEO addition. The active films showed substantially lower swelling ratio compared to the CMC-agar film when 1.5% SSEO was added, but the transparency of the films was reduced. Finally, the results showed that SSEO can act as an antimicrobial agent in combination with CMC-agar film. However, it modifies properties of the film depending on the applied concentration