Risk factors of using late-autophagy inhibitors: Aspects to consider when combined with anticancer therapies.

Cancer resistance to therapy is still an unsolved scientific and clinical problem. In 2022, the hallmarks of cancer have been expanded to include four new features, including cellular senescence. Therapy-induced senescence (TIS) is a stressor-based response to conventional treatment methods, e.g. chemo- and radiotherapy, but also to non-conventional targeted therapies. Since TIS reinforces resistance in cancers, new strategies for sensitizing cancer cells to therapy are being adopted. These include macroautophagy as a potential target for inhibition due to its potential cytoprotective role in many cancers. The mechanism of late-stage autophagy inhibitors is based on blockage of autophagolysosome formation or an increase in lysosomal pH, resulting in disrupted cargo degradation. Such inhibitors are relevant candidates for increasing anticancer therapy effectiveness. In particular, 4-aminoquoline derivatives: chloroquine/hydroxychloroquine (CQ/HCQ) have been tested in multiple clinical trials in combination with senescence-inducing anti-cancer drugs. In this review, we summarize the properties of selected late-autophagy inhibitors and their role in the regulation of autophagy and senescent cell phenotype in vitro and in vivo models of cancer as well as treatment response in clinical trials on oncological patients. Additionally, we point out that, although these compounds increase the effectiveness of treatment in some cases, their practical usage might be hindered due to systemic toxicity, hypoxic environment, dose- ant time-dependent inhibitory effects, as well as a possible contribution to escaping from TIS.

A Multisensor Device Intended as an IoT Element for Indoor Environment Monitoring.

This work presents a multisensor device which is intended as an element of IoT for indoor environment (IE) monitoring. It is a portable, small-size, lightweight, energy-efficient direct-reading instrument. The device has an innovative design and construction. It offers real-time measurements of a wide spectrum of physical and chemical quantities (light intensity, temperature, relative humidity, pressure, CO2 concentration, content of volatile organic compounds including formaldehyde, NO2, and particulate matter), data storage (microSD; server as an option), transmission (WiFi; GSM and Ethernet as options), and visualization (smartphone application; PC as an option). Commercial low-cost sensors were utilized, which have been arranged in the individual sensing modules. In the case of gas sensors, dynamic exposure was chosen to ensure a minimum response time. The MQTT protocol was applied for data transmission and communication with other devices, as well as with the user. The multisensor device can collect huge amounts of data about the indoor environment to provide the respective information to the IoT. The device can be configured to control actuators of various auxiliary devices and equipment including external systems used for ventilation, heating, and air conditioning. The prototype is fully operational. The exemplary results of IE monitoring were shown.

Co-Dependency of IAQ in Functionally Different Zones of Open-Kitchen Restaurants Based on Sensor Measurements Explored via Mutual Information Analysis.

High-quality indoor air is essential in open-kitchen restaurants for ensuring a healthy workplace and comfortable conditions for visitors. In this study, indoor air quality interdependence between the kitchen and the dining zones in open-kitchen restaurants was analyzed. The method was based on measurements of selected air parameters using a sensor technique and mutual information (MI) analysis. A long-term approach (based on a several-hour time series) and a short-term approach (based on a several-minute time series) were applied. This study involved four open-kitchen restaurants. The indoor conditions were represented by the temperature, relative humidity, CO2 concentration, and content of the total volatile organic compounds (TVOC) in the air. The MI analyses showed that the long-term co-dependence of the indoor conditions between the kitchen and the dining zones was smaller during business hours (MI = 0.12 ÷ 0.40) compared to night hours (MI = 0.24 ÷ 0.58). The ranking of the long-term MI values for the individual air parameters was MICO2 (0.34) ≅ MIT (0.34) > MIRH (0.28) > MITVOC (0.23). The short-term interdependencies were smaller during night hours (median MI = 0.01 ÷ 0.56) compared to business hours (MI = 0.23 ÷ 0.61). Additionally, the short-term MI was subject to high temporal variability. The ranking of the short-term MI values for the individual air parameters was MICO2 (0.48) > MIT (0.46) > MIRH (0.37) > MITVOC (0.26). Due to the weak and highly variable co-dependence of the air parameters between the kitchen and dining areas, multi-zone monitoring of air parameters with an emphasis on TVOC measurements is recommended to ensure proper indoor conditions in open-kitchen restaurants. The presented approach may be applied to design indoor air quality monitoring and ventilation systems not only in open-kitchen restaurants but also in other interiors with functionally different zones.

Aerosol penetration study for FFP2 half masks regarding protection against diesel particles in underground mines.

Filtering facepieces (FFP), mainly class FFP2 particle half masks (EN 149:2001#x02009;+ A1:2009), are commonly used in European mines to protect workers from respirable dust, especially from particulate matter (PM) with a diameter of 4 µm or less (PM4). The aerosol associated with diesel exhaust (DE) is dominated by submicrometer particles (with a diameter of less than 1 µm) and nanoparticles (size in the range between 10 and 500 nm). In the European Union (EU), the occupational exposure level (OEL) for DE has been defined in terms of elemental carbon (EC) concentration. Based on measurements in underground mines, on average, 60% of EC associated with PM4 was contained in PM with a diameter of 1 µm or less (PM1). Particle number size distribution (PNSD) of PM1 showed that the most numerous were particles in the size range of 20 to 300 nm. Four popular types of certified FFP2 half masks were tested for penetration. Brand new and thermally conditioned masks of each type were included in the study. NaCl aerosol in the particle size range of 7 to 270 nm was used for tests. Filtration efficiencies of 98.5% (median) or higher were achieved. Aerosol penetration was a function of particle size. Maximum penetration was observed between 20 and 60 nm, depending on the type of mask. During filtration, aerosol characteristics changed. Nanoparticles ranging in size from 7 to about 60 nm were removed to a very limited extent. The change was more noticeable for brand-new masks compared to the thermally conditioned ones. Usually, aerosol penetration through thermally conditioned masks was lower and more consistent. It was confirmed that the half masks of the FFP2 class are capable of filtering submicrometer aerosol in particle size range 7 to 270 nm with an efficiency exceeding 96% and can contribute to achieving compliance with the OEL for DE in the mining sector.

Genome-engineering technologies for modeling and treatment of cystic fibrosis.

Cystic fibrosis (CF) is an autosomal recessive disease caused by defects in the CF transmembrane conductance regulator (CFTR) protein. Due to the genetic nature of the disease, interventions in the genome can target any underlying alterations and potentially provide permanent disease resolution. The current development of gene-editing tools, such as designer nuclease technology capable of genome correction, holds great promise for both CF and other genetic diseases. In recent years, Cas9-based technologies have enabled the generation of genetically defined human stem cell and disease models based on induced pluripotent stem cells (iPSC). In this article, we outline the potential and possibilities of using CRISPR/Cas9-based gene-editing technology in CF modeling.

The Gas Sensing Drone with the Lowered and Lifted Measurement Platform.

A serious factor that limits the environmental applications of drones is the disturbance of the air pollution concentration field by the drone propulsion system. This work presents a gas-sensing drone offering measurements that are unaffected by this phenomenon. The novel development was based on the idea that, during measurements, the sensing device should be spatially separated from a zone influenced by the drone's rotors. To attain this goal, special equipment was designed that allows one to undock and lower the sensing device for measurement, lift it and dock for flight. The field experiments demonstrated the full functionality of the developed system and its superiority compared to a sensing platform mounted at the bottom of the drone. Higher measurement sensitivity and resolution were attained by lowering the sensing platform to the measurement point. This solution minimizes the rotor flow effect, ground effect, and pollution concentration field flattening. The test in real conditions confirmed that the designed construction assures drone stability. The presented technology may be an important step in developing effective mobile measurement tools that allow one to reach poorly accessible or dangerous places and perform measurements at a low cost and with high efficiency.

Comparison of static and dynamic exposures to air pollution, noise, and greenness among seniors living in compact-city environments.

GPS technology and tracking study designs have gained popularity as a tool to go beyond the limitations of static exposure assessments based on the subject's residence. These dynamic exposure assessment methods offer high potential upside in terms of accuracy but also disadvantages in terms of cost, sample sizes, and types of data generated. Because of that, with our study we aim to understand in which cases researchers need to use GPS-based methods to guarantee the necessary accuracy in exposure assessment. With a sample of 113 seniors living in Barcelona (Spain) we compare their estimated daily exposures to air pollution (PM2.5, PM10, NO2), noise (dB), and greenness (NDVI) using static and dynamic exposure assessment techniques. Results indicate that significant differences between static and dynamic exposure assessments are only present in selected exposures, and would thus suggest that static assessments using the place of residence would provide accurate-enough values across a number of exposures in the case of seniors. Our models for Barcelona's seniors suggest that dynamic exposure would only be required in the case of exposure to smaller particulate matter (PM2.5) and exposure to noise levels. The study signals to the need to consider both the mobility patterns and the built environment context when deciding between static or dynamic measures of exposure assessment.

The Detection of Activities Occurring Inside Quick Service Restaurants That Influence Air Quality.

Our attention was focused on the identification of activities affecting air quality, which occur in quick-service restaurants (QSR). The work was based on a measurement study of selected kebab stores in the Polish city of Wroclaw. It demonstrated that activities taking place in kebabs altered air quality. The associated changes in air parameters such as temperature, relative humidity, CO2 concentration, and the content of volatile organic compounds could be detected by utilizing a simple, multi-sensor device. In the measurement data, there were identified multidimensional patterns, which proved to be specific for the following categories of activities: Night Hours, Outlet Preparation, Food Preparation, Operation Hours, and Cleaning. Their occurrence was recognized by pattern recognition methods with a true positive rate greater than 99%. We demonstrated that the recognition may be based on measurements performed in various locations within the kebab store. Although patterns of the individual categories of activities largely varied between kebab stores, a similar performance of recognition was achieved for all restaurants. The obtained results entitled us to conclude that it is possible to detect activities of QSR, which influenced air quality, with the application of sensor technique and pattern recognition. The proposed approach may be applied to this type of object in general.

Beehive Air Sampling and Sensing Device Operation in Apicultural Applications-Methodological and Technical Aspects.

The basis of effective beekeeping is the information about the state of the bee colony. A rich source of respective information is beehive air. This source may be explored by applying gas sensing. It allows for classifying bee colony states based on beehive air measurements. In this work, we discussed the essential aspects of beehive air sampling and sensing device operation in apicultural applications. They are the sampling method (diffusive vs. dynamic, temporal aspects), sampling system (sample probe, sampling point selection, sample conditioning unit and sample delivery system) and device operation mode ('exposure-cleaning' operation). It was demonstrated how factors associated with the beehive, bee colony and ambient environment define prerequisites for these elements of the measuring instrument. These requirements have to be respected in order to assure high accuracy of measurement and high-quality information. The presented results are primarily based on the field measurement study performed in summer 2020, in three apiaries, in various meteorological conditions. Two exemplars of a prototype gas sensing device were used. These sensor devices were constructed according to our original concept.

The Effectiveness of Varroa destructor Infestation Classification Using an E-Nose Depending on the Time of Day.

Honey bees are subject to a number of stressors. In recent years, there has been a worldwide decline in the population of these insects. Losses raise a serious concern, because bees have an indispensable role in the food supply of humankind. This work is focused on the method of assessment of honey bee colony infestation by Varroa destructor. The approach allows to detect several categories of infestation: "Low", "Medium" and "High". The method of detection consists of two components: (1) the measurements of beehive air using a gas sensor array and (2) classification, which is based on the measurement data. In this work, we indicate the sensitivity of the bee colony infestation assessment to the timing of measurement data collection. It was observed that the semiconductor gas sensor responses to the atmosphere of a defined beehive, collected during 24 h, displayed temporal variation. We demonstrated that the success rate of the bee colony infestation assessment also altered depending on the time of day when the gas sensor array measurement was done. Moreover, it was found that different times of day were the most favorable to detect the particular infestation category. This result could indicate that the representation of the disease in the beehive air may be confounded during the day, due to some interferences. More studies are needed to explain this fact and determine the best measurement periods. The problem addressed in this work is very important for scheduling the beekeeping practices aimed at Varroa destructor infestation assessment, using the proposed method.

Physical activity benefits of attending a senior center depend largely on age and gender: a study using GPS and accelerometry data.

BACKGROUND: Senior centers offer important opportunities for physical activity and social interaction. Seniors who visit a senior center regularly can gain physical activity from transportation and from specific activities offered within the senior center. However, there is very little knowledge regarding the specific physical activity gains obtained from regular visits to senior centers, and no effort has been made to use device-based measures of physical activity to test the potential physical activity benefits of attending a senior center. METHODS: To fill this gap, the present study examined the physical activity patterns of 227 seniors living in the Barcelona Metropolitan Area in Spain. Using GPS and Accelerometer 7-day tracking data, and GIS measures we assessed the light physical activity and moderate-to-vigorous intensity physical activity (MVPA) benefits of attending the senior center on a weekly and daily basis. RESULTS: Seniors who attended a senior center at least once a week did not accumulate significantly more daily physical activity (211.6 min; 95% CI 196.6; 226.6) than seniors without any visit 215.9 min; 95% CI 202.7; 229). However, on a day-to-day basis, it was found that visiting a senior center had positive effects in physical activity and was associated with less sedentary time among younger participants in general (- 18.2 daily min 95% CI - 33.2;-3.3 p = 0.016) and among older female participants in particular (- 19.7 daily min 95% CI -21.06;-18.5 p = 0.011). CONCLUSIONS: The benefits of attending senior centers in terms of physical activity should not be viewed as universal, but rather as contingent to the demographics of the user, and the type of activity that the visit is replacing.

Detecting varroosis using a gas sensor system as a way to face the environmental threat.

Colony Collapse Disorder (CCD) is an environmental threat on a global scale due to the irreplaceable role of bees in crop pollination. Varroa destructor (V.d.), a parasite that attacks honeybee colonies, is one of the primary causes of honey bee population decline and the most serious threat to the beekeeping sector. This work demonstrates the possibility of quantitatively determining bee colony infestation by V.d. using gas sensing. The results are based on analysing the experimental data acquired for eighteen bee colonies in field conditions. Their infestation rate was in the 0 to 24.76% range. The experimental data consisted of measurements of beehive air with a semiconductor gas sensor array and the results of bee colony V.d. infestation assessment using a flotation method. The two kinds of data were collected in parallel. Partial Least Square regression was applied to identify the relationship between the highly multivariate measurement data provided by the gas sensor array and the V.d. infestation rate. The quality of the developed quantitative models was very high, as demonstrated by the coefficient of determination exceeding R2 = 0.99. Moreover, the prediction error was <0.6% for V.d. infestation rate predictions based on the measurement data that was unknown to the model. The presented work has considerable novelty. To our knowledge, the ability to determine the V.d. infestation rate of bee colony quantitatively based on beehive air measurements using a semiconductor gas sensor array has not been previously demonstrated.

Temperature and Rain Moderate the Effect of Neighborhood Walkability on Walking Time for Seniors in Barcelona.

Walking is the most accessible form for seniors to engage in daily light or moderate physical activity. Walking activity depends on both individual and environmental factors, the latter including how walkable a given setting is. Recent papers have pointed at the relevance of also considering meteorological conditions in relation to the walking behavior of older adults. This paper explores the combined effect of neighborhood walkability, temperature and rain on daily walking time among seniors residing in Barcelona. Daily walking time was extracted from 7-day GPS (Global Positioning System) devices and accelerometer data of 227 seniors residing in the Barcelona Metropolitan Region (Spain). Temperature and rain data were extracted from official governmental weather stations. Mixed-effects linear regression models were adjusted to test the combined association between weather and walkability on daily walking time. Neighborhood walkability is positively associated with walking time among seniors, while rain generally deters it. Additionally, this study demonstrates that temperature and rain modify the effect of residential walkability on senior walking activity: low temperatures are particularly associated with lower walking activity among those residing in low walkable areas, while the presence of rain presents a negative association with walking time in high walkable environments. The combined effect of walkability and weather should be considered both in design actions that aim at improving walking infrastructure and also in prevention programs aimed at encouraging daily walking among seniors.

Gas Sensor Array and Classifiers as a Means of Varroosis Detection.

The study focused on a method of detection for bee colony infestation with the Varroa destructor mite, based on the measurements of the chemical properties of beehive air. The efficient detection of varroosis was demonstrated. This method of detection is based on a semiconductor gas sensor array and classification module. The efficiency of detection was characterized by the true positive rate (TPR) and true negative rate (TNR). Several factors influencing the performance of the method were determined. They were: (1) the number and kind of sensors, (2) the classifier, (3) the group of bee colonies, and (4) the balance of the classification data set. Gas sensor array outperformed single sensors. It should include at least four sensors. Better results of detection were attained with a support vector machine (SVM) as compared with the k-nearest neighbors (k-NN) algorithm. The selection of bee colonies was important. TPR and TNR differed by several percent for the two examined groups of colonies. The balance of the classification data was crucial. The average classification results were, for the balanced data set: TPR = 0.93 and TNR = 0.95, and for the imbalanced data set: TP = 0.95 and FP = 0.53. The selection of bee colonies and the balance of classification data set have to be controlled in order to attain high performance of the proposed detection method.

Diffusive and subdiffusive dynamics of indoor microclimate: a time series modeling.

The indoor microclimate is an issue in modern society, where people spend about 90% of their time indoors. Temperature and relative humidity are commonly used for its evaluation. In this context, the two parameters are usually considered as behaving in the same manner, just inversely correlated. This opinion comes from observation of the deterministic components of temperature and humidity time series. We focus on the dynamics and the dependency structure of the time series of these parameters, without deterministic components. Here we apply the mean square displacement, the autoregressive integrated moving average (ARIMA), and the methodology for studying anomalous diffusion. The analyzed data originated from five monitoring locations inside a modern office building, covering a period of nearly one week. It was found that the temperature data exhibited a transition between diffusive and subdiffusive behavior, when the building occupancy pattern changed from the weekday to the weekend pattern. At the same time the relative humidity consistently showed diffusive character. Also the structures of the dependencies of the temperature and humidity data sets were different, as shown by the different structures of the ARIMA models which were found appropriate. In the space domain, the dynamics and dependency structure of the particular parameter were preserved. This work proposes an approach to describe the very complex conditions of indoor air and it contributes to the improvement of the representative character of microclimate monitoring.

Application of a sensor system for determining the kind and quantity of two component VOC mixtures in air after the use of solvents.

This work aims at estimating the ability of a sensor system to recognize the type and to determine the concentration of organic compounds emitted from solvents. The measuring system used in the experiment consisted of a sensor array and a unit for data analysis. Commercially available sensors (Figaro, TGS) were used as a basis for the construction of the first of the two elements. The second element utilized Discriminant Function Analysis (DFA) and Multiple Linear Regression (MLR). The investigated gas samples consisted of air mixed with variable amounts of two organic compounds. One of the two compounds was intended to have a dominant influence on the sensors' response. Depending on this substance, two groups of gaseous mixtures were considered. In the first one, hexane was the major compound. The choice of this particular group of chemical compositions was inspired by practical problems related to various applications of extraction solvents. In the case of the second group of gas mixtures, the prevailing compound was toluene. This type of mixture, on the other hand, is related to the use of paints. The data analysis unit was designed to achieve the following two goals: in the first place, to recognize binary gas mixtures and secondly, to determine the concentrations of VOCs in them. The data analysis was based on steady-state sensor responses. Our study demonstrates that the sensor system may be employed for classifying and quantitatively determining volatile organic compounds released into air as a result of the use of solvents. The presented solution proves the concept in the case of binary mixtures of VOCs.

[The influence of interleukin-6 and tumor necrosis factor alpha gene polymorphisms on bone mineral density in postmenopausal women]. / Wplyw polimorfizmu genu interleukiny-6 i czynnika martwicy nowotworu alpha na gestosc mineralna kosci kobiet po menopauzie.

UNLABELLED: Proinflammatory cytokines, interleukin-6 (IL-6) and tumor necrosis factor alpha (TNF-alpha), involved into osteoclastogenesis and responsible for bone resorption process, participate in the pathogenesis of the osteoporosis. In vitro studies have shown that single nucleotide polymorphisms of IL-6 and TNF-alpha genes could influence the transcription process of the genes and the cytokines level. AIM: Assessment of the influence of IL-6 and TNF-alpha gene polymorphisms on bone mineral density (BMD) and evaluation of their connection with osteoporosis prevalence in women from Wielkopolska region. MATERIAL AND METHODS: In the group of 267 postmenopausal women (average age 58.5+/-5.9 years, average age of last period 49.8+/-3.9 years) bone mineral density in lumbar spine (L2-L4) was performed using dual energy X-ray absorptiometry (DXA). Genotypes frequencies were determined by polymerase chain reaction with restriction fragment length polymorphism (PCR/RFLP) using restriction enzymes Lwe I and Faq I, respectively. The connection between the polymorphisms of investigated genes and body mass index, age of menarche and menopause and length of reproductive age had been analyzed as well. RESULTS: No statistically significant association was found between examined genetic factors and the value of bone mineral density in the investigated group of postmenopausal women. The frequencies of investigated genotypes were in compliance with Hardy-Weinberg equilibrium. The correspondence between evaluated clinical parameters and IL-6 i TNF-alpha genotypes frequencies has not been proven. CONCLUSIONS: The -174G/C polymorphism in the IL-6 and -308G/A polymorphism in TNF-alpha genes have no influence on bone mineral density value (BMD) in the investigated population of women from Wielkopolska region.

SECM visualization of the spatial variability of enzyme-polymer spots. 3. Enzymatic feedback mode.

The responses of a PQQ-GDH entrapped in a polymer structure to mixtures of glucose and maltose were evaluated. Each compound was considered in the concentration range of 0-0.2 mM. Imaging was performed at constant height in the enzymatic feedback mode of scanning electrochemical microscopy (SECM). The enzyme-polymer spot was discretized into 15 x 15 mum(2) substructures which were treated as independent individual microsensors. The response surfaces of the individual microsensors were approximated with a linear regression model. The coefficients in the derived equations represent contributions from topography, glucose concentration, maltose concentration, and the competition of glucose and maltose for the same active site of PQQ-GDH to the measured signal. The ratio of glucose and maltose contributions to the current at the SECM tip was constant for all microsensors and it was predominantly determined by the ratio of the turnover rates of both analytes in the PQQ-GDH catalyzed reaction. Using the difference between these coefficients, it was possible to select the microsensors within the overall enzyme-polymer spot that provided the best data for quantifying glucose and maltose by the artificial neural network used. The quantification of glucose and maltose was successful, except when the contributions from the components of the mixture were n (g)=k n units of glucose and simultaneously n (m)= 1.86(1-k)n units of maltose, for each constant n > 0 and k E <0,1>.