This work intends to present a study on relations between a Lie algebra called dispersion operators algebra, linear canonical transformation and a phase space representation of quantum mechanics that we have introduced and studied in previous works. The paper begins with a brief recall of our previous works followed by the description of the dispersion operators algebra which is performed in the framework of the phase space representation. Then, linear canonical transformations are introduced and linked with this algebra. A multidimensional generalization of the obtained results is given.

Human activities (e.g., exploitation, utilization, and conservation) exert substantial impact on forest ecological functions (FEF). The human influence on FEF significantly varies across developmental stages, which are attributed to the temporal and spatial in nature. This study evaluates some notable FEF indices (FEFI) in the 448 counties within the Yellow River basin (YRB) using panel data from the Seventh to Ninth National Forest Inventory. Data analysis involves employing the residual trends, geographical and temporal weighted regression. Results indicate that, firstly, the overall forest ecological function in the YRB is moderate to inferior, with superior FEF in counties endowed with more natural forest resources. Afforestation demonstrates a short-term improvement, but its effectiveness diminishes over time. Secondly, the positive spatial correlation is stronger among counties, characterized by both high-high and low-low agglomeration effects. Scattered planting, simple stand structure, and concentrated harvesting of forests at the identical stand ages hinder the formation of complex and large-scale FEF agglomerations. Thirdly, significant spatial-temporal differences exist in the impact of human activities on FEF. In the upper reaches of the basin, increased vegetation coverage through agricultural and forestry production benefited FEF, however, some over-exploitation of forests and grasslands is observed there. In the middle reaches, the economic development, expanding population and the greening activities help to improve FEF effectively, but excessive water using in agricultural production brought more difficulties to FEF improvement. In the lower reaches of the basin, improved wastelands and forest protection positively influence FEF. This study recommends that county governments should prioritize forest management with multi-species and multi-layered complex forests. Each county should define its position in regional development and ecological protection, considering the potential impacts on neighboring regions. This holistic approach promotes more effective integrated regional management.

Green spaces localized in cities create favourable environmental conditions for Ixodes ricinus, the most widespread and important vector of tick-borne pathogens in Central Europe. In this study, we described the prevalence of Borrelia burgdorferi s.l. and Babesia species found in mono- and double infections among I. ricinus ticks occurring in urban areas of the city of Poznań, west-central Poland. Two tick groups were examined: (i) a group of 1,029 host-seeking ticks (460 nymphs, 289 females, and 280 males and (ii) a group of 1,268 engorged female ticks removed from 1,115 tick-infested animals, dogs and cats. The overall prevalence of B. burgdorferi s.l. found in host-seeking ticks was almost two-fold higher in comparison to ticks derived from pets (8.7 vs. 4.7%, respectively, χ2 test, P = 0.001). Borrelia afzelii and B. garinii were the most prevalent species both in ticks from vegetation (3.7% and 3.7%, respectively) and from pets (3.7% and 0.6%, respectively). Babesia infections were slightly more common in feeding ticks compared to those from vegetation (6.0 vs. 4.7%, respectively), however, the difference was not significant. Three Babesia species including Ba. microti, Ba. venatorum and Ba. canis were identified. Babesia canis and Ba. microti were the most prevalent in host-seeking (2.6% and 1.4%, respectively) and feeding ticks (2.8% and 2.2%, respectively), whereas Ba. venatorum was the rarest piroplasm. All Ba microti obtained sequences (n=42) were identical to Ba. microti genotype "Jena/Germany" that is considered as pathogenic to humans. Furthermore, the sequences of Ba. venatorum (n=17) were identical with those isolated from patients in Italy, Austria and Poland. Altogether, out of 121 Babesia-positive ticks, 19.8% were simultaneously infected with B. burgdorferi s.l. spirochetes. We found similar prevalences of co-infections in host-seeking (1.1%) as well as in feeding ticks (1.0%). In the first group, Ba. canis prevailed in coinfections (73%), mostly with B. afzelii and B. garinii, in the second group, Babesia microti dominated with B. afzelii (92.7%). This is the first finding documenting the co-occurrence of both pathogens in ticks from companion animals. The detection of Ba. microti and Ba. venatorum sequences identical to strains pathogenic to humans as well as predominance of LB spirochetes, B. afzelii and B. garinii in I. ricinus from vegetation and animals indicates that there is a potential risk of acquiring human babesiosis and/or Lyme borreliosis in urban areas of the city of Poznań. Although, the overall risk of encountering a Ba. microti and B. burgdorferi s.l. co-infected tick was low (1.0%), the potential for more severe clinical symptoms and complications deserves notice. A relatively high infection rates of Ba. canis in dog-derived ticks (3.2%) and in host-seeking ticks (2.6%), suggests that I. ricinus could potentially be involved in the circulation of this piroplasm in areas, where the competent vector, Dermacentor reticulatus is absent or rare.

"Public legal information from all countries and international institutions is part of the common heritage of humanity. Maximizing access to this information promotes justice and the rule of law". In accordance with the aforementioned declaration on Free Access to Law by Legal information institutes of the world, a plethora of legal information is available through the Internet, while the provision of legal information has never before been easier. Given that law is accessed by a much wider group of people, the majority of whom are not legally trained or qualified, diversification techniques, should be employed in the context of legal information retrieval, as to increase user satisfaction. We address diversification of results in legal search by adopting several state of the art methods from the web search, network analysis and text summarization domains. We provide an exhaustive evaluation of the methods, using a standard data set from the Common Law domain that we subjectively annotated with relevance judgments for this purpose. Our results i) reveal that users receive broader insights across the results they get from a legal information retrieval system, ii) demonstrate that web search diversification techniques outperform other approaches (e.g., summarization-based, graph-based methods) in the context of legal diversification and iii) offer balance boundaries between reinforcing relevant documents or sampling the information space around the legal query.

This review provides a comprehensive and updated information on chalcones, presenting their sources, methods of identification and properties putting emphasis on applications in agricultural industry. Vast exploitation of synthetic pesticides led to the weed and pest resistance issue, causing economic loss but more importantly health risk due to pesticide overuse. Because one of the aim of the European Green Deal 2030 is the Farm to Fork strategy which targets on reducing by 50% the use of chemical pesticides by 2030, and push towards natural pesticides which are more environmentally friendly and restore natural resources, chalcones and their derivatives seem to fit perfectly. They have herbicidal, fungicidal, bactericidal and antiviral properties. Moreover, chalcones are naturally occurring substances, known for their favorable health effect for years, working on many areas. This review is complementary to the previous ones describing chalcones use in agriculture, updates them but additionally shows methods of detection.

Keywords: olfactory rehabilitation; chronic pain; fMRI;

Abstract: Background: Intensity modulated radiotherapy (IMRT) is still a standard of care for radiotherapy in locally advanced head and neck cancer (LA-HNSCC). Simultaneous integrated boost (SIB) and moderate hypofractionation offer an opportunity for individual dose painting and a reduction in overall treatment time. We present retrospective data on toxicity and locore-gional control of a patient cohort with LA-HNSCC treated with an IMRT-SIB concept in compar-ison to normofractionated 3D-conformal radiotherapy (3D-RT) after a long-term follow-up. Methods: Between 2012 and 2014, n=67 patients with HNSCC (stages III/IV without distant me-tastases) were treated with IMRT-SIB either definitively (single/total doses: 2.2/66 Gy, 2.08/62.4 Gy, 1.8/54 Gy in 30 fractions) or in the postoperative setting (2.08/62.4 Gy, 1.92/57.6 Gy, 1.8/54 Gy). These patients' clinical courses were matched (for sex, primary, and treatment concept) as part of a matched-pair analysis with patients treated before mid-2012 with normofractionated 3D-CRT (definitive: 2/50 Gy followed by a sequential boost up to 70 Gy; postoperative: 2/60-64 Gy). Chemotherapy/ immunotherapy was given concomitantly in both groups in the definitive situation (postoperative dependent on risk factors). The primary endpoints were acute and late toxicity; the secondary endpoint was locoregional control (LRC). Results: Sixty-seven patients treated with IMRT-SIB (n = 20 definitive, n = 47 adjuvant) were matched with 67 patients treated with 3D-RT. There were minor imbalances between the groups concerning nonmatching variables such as extracapsular extension (ECE) and chemotherapy in IMRT-SIB. Significantly less toxicity was found in favor of IMRT-SIB concerning dysphagia, ra-diation dermatitis, xerostomia, fibrosis, and lymphedema. After a median follow-up of 63 months, the median LRC was not reached (IMRT-SIB) vs. 69.5 months (3D-RT) (p=0.63). Conclusions: This moderately hypofractionated IMRT-SIB concept was shown to be feasible with less toxicity than conventional 3D-RT in this long-term follow-up observation.

Photovoltaic (PV) technologies are developing rapidly as a result of their ability to reduce energy consumption from conventional sources as well as the growth of global energy expenditures. Nevertheless, several impact categories during the PV panel life cycle occur and some principal sectors are affected. These impact categories are assessed by applying life cycle analysis (LCA) techniques through various software programs, databases and methods. Such analyses of energy technologies are crucial, as they can reveal the occurrence of hazardous emissions at distinct life cycle stages. In the present paper, a PV panel impact assessment through life cycle analysis is carried out. More precisely, a combination of PV technologies—monocrystalline, multicrystalline, copper indium gallium selenide (CIGS), amorphous, and ribbon—is studied. The impact categories of ozone depletion, human toxicity, particulate matter, ionising radiation, photochemical ozone formation, acidification, eutrophication, and ecotoxicity, as well as the sectors of human health, ecosystem quality, and environment, are assessed using the openLCA software, the ecoinvent database, the eco-indicator 99, IMPACT 2002+, ReCiPe, and TRACI methods.

Many fundamental molecular techniques (PCR, Microarray, Southern and northern hybridization, siRNA, CRISPR/Cas9 etc.) developed so far shows errors. I wish to highlight these molecular techniques are developed on basis of Watson-Crick DNA model, ignoring the concept of parallel stranded DNA. Through this opinion article, I wish to highlight specificity and accuracy of these molecular techniques can be enhanced by considering both parallel and anti parallel hybridization of DNA. Hopefully my views will also solve issue of irreproducibility in life science research.

The increasing availability of longitudinal data (repeated numerical observations of same units at different times) requires the development of flexible techniques to automatically detect common errors in such data. Besides obvious and easily identifiable cases, such as missing or out-of-range data, large longitudinal dataset often present problems not easily traceable by the techniques used for generic datasets. In particular, elusive and baffling problems are i) inversion of one or more values from one unit to another; ii) anomalous jumps in the series of values, iii) errors in the timing of the values due to a recalculation operated by the data providers to compensate previous errors. This work proposes a statistical-mathematical approach based on a system of indicators that is able to capture the complexity of the described problems by working at the formal level, regardless of the specific meaning of the data. The proposed approach identifies suspect erroneous data and is applicable in a variety of contexts. We implement this approach in a relevant database of European Higher Education institutions (ETER) by analyzing Total academic staff, that is one of the most important variables, used in empirical analysis as proxy of size and also considered by policy makers at European level.

Detecting and monitoring changes in soil salinity through remote sensing provides an opportunity for field assessment in regions where on-site measurements are limited. This investigation, carried out in Siwa Oasis, Egypt, aimed to assess the efficacy of several soil salinity indices derived from Landsat 5 and 7 satellite images. To achieve this, 56 on-site ground measurements were utilized for evaluation purposes. The study aimed to improve the correlation between EC and index values and explore the relationship between salinity and changes in land cover. Eleven spectral indices were calculated for nine scenes captured in different months from August to December. The first approach involved stacking the data to identify the index with the strongest correlation with ground EC values, without the need for complex analysis or EC value ranging. In the second approach, the ground EC measurements were classified into seven different salinity categories, and the correlation coefficient was calculated between each index and each salinity category. The third approach analyzed the data temporally, considering different salinity levels. Lastly, a spatial correlation analysis was conducted between EC and index values in the fourth scenario. The initial approach revealed a weak correlation due to substantial variation in EC values. However, the SI index demonstrated the highest correlation coefficient of 0.38. In the second scenario, the S2 index exhibited the highest correlation of 0.96 for moderate salinity samples. The third scenario showed that the S1 index achieved the highest correlation value of 0.99 for moderately saline areas. In the fourth scenario, the SI index exhibited the strongest correlation among all four ponds with correlation coefficients of 0.23, 0.23, 0.18, and 0.61. Notably, the correlations observed in the second and third scenarios demonstrated higher correlation coefficients compared to both the first and fourth scenarios. The study highlighted significant variations in EC levels related to land cover types and pond elevation. Additionally, remote sensing methods detected a 48% increase in total vegetated area over 17 years, showing the potential of remote sensing techniques in salinity monitoring for expanding agriculture and improving land management.

Patients with metastatic epidural spinal cord compression (MESCC) and favorable survival prognoses may benefit from radiation doses exceeding 10 x 3.0 Gy. In a multi-center phase 2 trial, patients receiving 15 x 2.633 Gy (41.6 Gy10) or 18 x 2.333 Gy (43.2 Gy10) were evaluated for local progression-free survival (LPFS), motor/sensory functions, ambulatory status, pain, distress, toxicity, and overall survival (OS). They were compared (propensity score adjusted Cox regression) to a historical control group (N=266) receiving 10 x 3.0 Gy (32.5 Gy10). In the phase 2-cohort, 50 (of 62 planned) patients were evaluable for LPFS. Twelve-month rates of LPFS and OS were 96.8% and 69.9%, respectively. Motor and sensory functions improved in 56% and 57.1% of patients, and 94.0% were ambulatory following radiotherapy. Pain and distress decreased in 84.4% and 78.0% of patients. Ten and two patients experienced grade 2 and 3 toxicities, respectively. Phase 2 patients showed significantly better LPFS than the control group (p = 0.039) and a trend for improved motor function (p = 0.057). Ambulatory and OS rates were not significantly different. Radiotherapy with 15 x 2.633 Gy or 18 x 2.333 Gy was well tolerated and appeared superior to 10 x 3.0 Gy.

This paper explores the capability of various machine learning algorithms, including Random Forests and advanced gradient boosting techniques such as XGBoost, LightGBM, and CatBoost, to predict customer churn in the telecommunications sector. For this analysis, a dataset available to the public was employed. The performance of these algorithms was assessed using recognized metrics, including Accuracy, Precision, Recall, F1-score, and the Receiver Operating Characteristic Area Under Curve (ROC AUC). These metrics were evaluated at different phases: subsequent to data preprocessing and feature selection; following the application of SMOTE and ADASYN sampling methods; and after conducting hyperparameter tuning on the data that had been adjusted by SMOTE and ADASYN. The outcomes underscore the notable efficiency of upsampling techniques such as SMOTE and ADASYN in addressing the imbalance inherent in customer churn prediction. Notably, the application of random grid search for hyperparameter optimization did not significantly alter the results, which remained comparatively unchanged. The algorithms' performance post- ADASYN application marginally surpassed that observed after SMOTE application. Remarkably, LightGBM achieved an exceptional F1-score of 89% and an ROC AUC of 95% subsequent to the ADASYN sampling technique. This underlines the effectiveness of advanced boosting algorithms and upsampling methods like SMOTE and ADASYN in navigating the complexities of imbalanced datasets and intricate feature interdependencies.

Brain is the most complex organ in the human body and it is divided into two hemispheres - left and right hemispheres. Left hemisphere is responsible for control of right side of our body whereas right hemisphere is responsible for control of left side of our body. Brain image segmentation from different neuroimaging modalities is one of the important parts in clinical diagnostic tools. Neuroimaging based digital imagery generally contain noise, inhomogeneity, aliasing artifacts, and orientational deviations. Therefore, accurate segmentation of brain images is a very difficult task. However, the development of accurate segmentation of brain images is very important and crucial for a correct diagnosis of any brain related diseases. One of the fundamental segmentation tasks is to identify and segment inter-hemispheric fissure/mid-sagittal plane, which separate the two hemispheres of the brain. Moreover, the symmetric/asymmetric analyses of left and right hemispheres of brain structures are important for radiologists to analyze diseases such as Alzheimer's, Autism, Schizophrenia, Lesions and Epilepsy. Therefore, in this paper we have analyzed the existing computational techniques used to find brain symmetric/asymmetric analysis in various neuroimaging techniques (MRI/CT/PET/SPECT), which are utilized for detecting various brain related disorders.

BUB1 is overexpressed in most human solid cancers including breast cancer. Higher BUB1 levels are associated with poor prognosis especially in patients with triple-negative breast cancer (TNBC). Women with TNBC often develop resistance to chemotherapy and radiotherapy, which are still the mainstay of treatment for TNBC. Our previous studies demonstrated that BUB1 kinase inhibitor (BAY1816032) reduced tumor cell proliferation and significantly enhanced radiotherapy efficacy in TNBC. In this study, we evaluated the effectiveness of BAY1816032 with a PARP inhibitor (olaparib), platinum agent (cisplatin), and microtubule poison (paclitaxel) alone or in combination with radiotherapy using cytotoxicity and clonogenic survival assays. BUB1 inhibitor sensitized BRCA1/2 wild-type SUM159 and MDA-MB-231 cells to olaparib, cisplatin and paclitaxel synergistically (combination index; CI

Non-targeted effects (NTE) such as bystander effects or genomic instability have been known for many years but their significance for radiotherapy or medical diagnostic radiology are far from clear. Central to the issue are reported differences in response of normal and tumour tissues to signals from directly irradiated cells. This review will discuss possible mechanisms and implications of these different responses and will then discuss possible new therapeutic avenues suggested by the analysis. Finally, the importance of NTE for diagnostic radiology and nuclear medicine which stems from the dominance of NTE in the low dose region of the dose response curve will be presented. Areas such as second cancer induction and microenvironment plasticity will be discussed.

Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

In the era of mounting water scarcity, particularly in arid regions, the agricultural sector is striving to optimize the water resource management practices. Treated wastewater (TWW) has emerged as a viable alternative to freshwater for irrigation, offering a sustainable solution to water conservation. However, ensuring the safety and quality of TWW is paramount to safeguard for both crop health and environmental integrity. Electrical conductivity (EC), a critical factor in assessing TWW suitability for irrigation, can significantly impact crop yields and soil health since it is directly linked to the concentration of dissolved salts and ions. Therefore, this study delves into the development of advanced predictive models for EC assessment by employing supervised machine learning (ML) techniques like the Support Vector Regression (SVR), Adaptive Network-based Fuzzy Inference System (ANFIS), and Multiple Linear Regression (MLR). The TWW samples collected from Al-Qatif area, Saudi Arabia were assessed in the lab through a sensor-based real-time monitoring system integrated with Internet of Things (IoT) network and a multiprobe device. The key water quality parameters assessed involved, temperature (T), pH, Oxidation Reduction Potential (ORP), Resistivity (RES), Total Dissolved Solids (TDS), Salinity and Turbidity which served as the foundation for these models, given their profound influence on and their anticipated impact on EC levels. Following feature selection, two distinct model combinations were identified for the SVR, ANFIS and MLR models. Furthermore, to evaluate prediction performance, four statistical criteria, including coefficient of determination (R²), correlation coefficient (R), mean square error (MSE), and root mean square error (RMSE), were employed. Overall, the comparative performance results proved that ANFIS-M2 indicated the strongest predictive capability with the R² value of 0.99572 and 0.75145 and the RMSE values of 0.00965 and 0.01134, respectively in both calibration and verification stages.

This study presents the utilization of the Microwave InfraRed Thermography (MIRT) technique to identify and analyze the defects in the carbon-fiber-reinforced polymer (CFRP) composite rein-forcement of concrete specimens. At first, a set of the numerical models was created, comprising of the broadband pyramidal horn antenna and the analyzed specimen. The utilization the system operating at a power of 1000W in a continuous mode, operating at frequency of 2.45 GHz was analyzed. The specimen under examination comprised a compact concrete slab that was covered with an adhesive layer, thereafter, topped with a layer of CFRP. An air gap represented a defect at the interface between the concrete and CFRP within the adhesive layer. In the modelling stage the study investigated three separate scenarios: a sample with no defects, a sample with a defect located at the center, and a sample with a numerous additional random defects located at the rim of the CFRP matte, to analyze the effect of the natural reinforcement degradation in this area. The next phase of the study involved conducting experiments to confirm the results obtained from nu-merical modeling. In the experiments the concrete sample aged for 10 years with the defect in the center and naturally developed defects at the CFRP rim was used. The study employed numerical modeling to explore the phenomenon of microwave heating in complex structures. The aim was to assess the chosen antenna design and identify the most effective experimental setup. These con-clusions were subsequently confirmed through experimentation. The observations made during the heating process were particularly remarkable, since they deviated from earlier studies that solely conducted measurements of the sample post-heating phase. The findings demonstrate that MIRT has the capacity to be employed as a technique for detecting flaws in concrete structures reinforced with CFRP.

Densely urbanized areas, with a low percentage of green vegetation, are highly exposed to Heat Waves (HW) which nowadays are increasing in terms of frequency and intensity also in the middle-latitude regions, due to ongoing Climate Change (CC). Their negative effects may combine with those of the UHI (Urban Heat Island), a local phenomenon where air temperatures in the compact built up cores of towns increase more than those in the surrounding rural areas, with significant impact on the quality of urban environment, on citizens health and energy consumption and transport, as it has occurred in the summer of 2003 on France and Italian central-northern areas. In this context this work aims at designing and developing a methodology based on aero-spatial remote sensing (EO) at medium-high resolution and most recent GIS techniques, for the extensive characterization of the urban fabric response to these climatic impacts related to the temperature within the general framework of supporting local and national strategies and policies of adaptation to CC. Due to its extension and variety of built-up typologies, the municipality of Rome was selected as test area for the methodology development and validation. First of all, we started by operating through photointerpretation of cartography at detailed scale (CTR 1: 5000) on a reference area consisting of a transect of about 5x20 km, extending from the downtown to the suburbs and including all the built-up classes of interest. The reference built-up vulnerability classes found inside the transect were then exploited as training areas to classify the entire territory of Rome municipality. To this end, the satellite EO HR (High Resolution) multispectral data, provided by the Landsat sensors were used within a on purpose developed "supervised" classification procedure, based on data mining and “object-classification” techniques. The classification results were then exploited for implementing a calibration method, based on a typical UHI temperature distribution, derived from MODIS satellite sensor LST (Land Surface Temperature) data of the summer 2003, to obtain an analytical expression of the vulnerability model, previously introduced on a semi-empirical basis.

Conventional MRI sequences are standard methods to monitor patients with brain tumors but have significant limitations especially after irradiation. Currently, the role of FET-PET in radiotherapy of glioblastoma is emerging, starting from target definition, response assessment and in distinguishing progression from post-irradiation changes. Recently a PET RANO criteria have been published providing optimal strategy for treatment evaluation with amino-acid PET. Earlier, a PET/RANO group reported contribution of PET imaging to radiotherapy planning and monitoring in glioma patients. Also, increasing evidence have showed advantages of amino-acid PET vs. RANO MRI for prediction of overall survival. In this narrative review we aimed to summarize published data on FET-PET based treatment response assessment to radiotherapy and focused on details in protocols.

This study investigates whether a chronotherapeutic treatment of hepatocellular carcinoma (HCC) may improve treatment efficacy and mitigate side effects on healthy liver (HL). HCC was induced in Per2::luc mice which were irradiated at four time points of the day. Proliferation and DNA-double strand breaks were investigated in irradiated and non-irradiated organotypic slice culture (OSC) and ex vivo samples by detection of Ki67 and γ-H2AX. OSC proved useful to determine dose-dependent effects on proliferation and DNA damage but appeared unsuited to test the chronotherapeutic approach. Irradiation of ex vivo samples was most effective at the proliferation peaks in HCC at ZT02 (early inactivity phase) and ZT20 (late activity phase). Irradiation effects on HL were minimal at ZT20. Ex vivo samples revealed disruption in daily variation and down-regulation of all investigated clock genes except Per1 in non-irradiated HCC as compared with HL. Irradiation affected rhythmic clock gene expression in HL and HCC at all ZTs except at ZT20. Irradiation at ZT20 had no effect on total leukocyte numbers. Our results indicate ZT20 as the optimal time point for irradiation of HCC in mice. Translational studies are now needed to evaluate whether the late activity phase is the optimal time point for irradiation of HCC in man.

After reviewing cancer theories, cancer treatment development histories, randomized clinical trial's performance, cancer treatment strategy, trial follow-up times, and conducting numerous simulations using existing data, the authors found: (1) medical treatments come with three to four lethal factors: treatment side-effects, emotional distress and chronic dress, lack of exercises or physical inactivity, and excessive nutrition in some cases; (2) clinical trial exaggerates the benefits of fast-acting treatments and underestimates the slow-delivering adverse side effects as a result of statistical averaging, interfering effects of personal lifestyle factors, and insufficient follow-up times; (3) the benefits of medical treatments are limited by chain comparison, where surgery sets up a negative standard relative to the best way for resolving cancer; (4) the strategy of destroying the tumor is unworkable; (5) medical treatments can turn natural cancer growth curve into approximately doubly exponential curve; (6) multiple factor non-medical measures are much more powerful than medical treatments in controlling cancer growth and metastasis rates; and (7) cancer early diagnosis and over treatments are bad strategies that have great adverse impacts on cancer patients. Based on huge increases in cancer growth rate constants, substantial of loss of organ functional capacity, and severe systemic aging-like cellular damages, the authors concluded that medical treatments promote cancer growth and metastasis rates and shorten patient lives in most cases, and the claimed benefits are caused by triple biases of clinical trials. The authors believe that the better strategy for ending the global cancer epidemic is abandoning clinical trails as the research model, changing caner treatment strategy from killing cancer cells to slowing down cancer growth rates by using multiple factors optimization approach in personalized medicine.

N6-methyladenosine (M6A) modification is the most abundant internal chemical modification on RNA molecules in eukaryotes and can affect mRNA metabolism and regulate RNA transcription, nuclear export, splicing, degradation, translation, ets, and has a significant impact on various aspects of physiology or pathobiology. Radiotherapy is the most common measure of tumor treatment, variety of cellular intrinsic mechanisms affect the responses of cells to ionizing radiation (IR) and effectiveness of cancer radiotherapy. In this review, we summarize and discuss the recent advances about the roles and mechanisms of RNA M6A methylation in cellular responses to radiation-induced DNA damage response, and outcomes of cancer radiotherapy. Insights into the RNA M6A methylation in radiation biology may facilitate the improvement of therapeutic strategies for cancer radiotherapy as well as radioprotection on normal tissues.

Natural language Processing (NLP) has significantly transformed in the last decade, especially in the field of Language Modeling. Large Language Models (LLMs) have achieved SOTA performances on Natural Language Understanding (NLU) and Natural Language Generation (NLG) tasks by learning language representation in self-supervised ways. This paper provides a comprehensive survey to capture the progression of advances in Language Models. In this paper, we examine the different aspects of Language Models, which started with a few million parameters but have reached the size of a trillion in a very short time. We also look at how these LLMs transitioned from task-specific to task-independent to task-and-language-independent architectures. This paper extensively discusses different pre-training objectives, benchmarks, and transfer learning methods used in LLMs. It also examines different fine-tuning and In-Context learning techniques used in downstream tasks. It also explores how LLMs can perform well across many domains and datasets if sufficiently trained on a large and diverse dataset. Next, it discusses how, over time, the availability of cheap computational power and large datasets have improved LLM’s capabilities and raised new challenges. As part of our study, we also inspect LLMs from the lens of scalability to see how their performance is affected by the model’s depth, width, and data size. Lastly, we provide an empirical comparison of existing trends and techniques and a comprehensive analysis of where the field of LLM currently stand.

There are several challenges on how to attain energy efficiency while maintaining balance among factors affecting energy consumption such as power rating and temperature setpoints of cooling units, room temperature and humidity, and indoor air quality (IAQ). A real-time energy and IAQ monitoring system were installed in an educational building to profile the operational power consumption of inverter-based air condition unit (ACU) installed in each room. Polynomial curve and neural fitting regression analysis were applied to the real-time power consumption, indoor temperature and humidity, and carbon dioxide (CO2) level data. The derived models were able to provide the stabilizing indoor thermal and air conditions of the room to reach steady state ACU power consumption. These collected data and calculated parameters can be used to define rules in automating control of cooling appliances for an efficient energy utilization. The regression approaches, using real-time data, have determined the influence of indoor heat conditions and carbon dioxide levels on ACU power consumption. These parameters were utilized to establish consistent values for temperature, humidity, and carbon dioxide levels under stable settings of inverter-based air conditioning units.

A novel means of applying radiotherapy in cancer treatment is the application of the radiation dose at a very high intensity for a very short time, FLASH radiotherapy (FLASH-RT). This technique involves exposure of tumors to >40 Gy/s, usually for less than one second. Studies conducted in cell and preclinical models suggest that FLASH-RT seems less damaging to normal tissues from adverse effects, relative to the same overall dose of radiation administered in conventional therapy (CONV-RT) which involves administration of lower levels of radiation repeated intermittently over a protracted period. In contrast, the susceptibility of tumor tissues to FLASH-RT is not diminished relative to CONV-RT. Within solid tumors both modes of dispensation of radiation produce an equivalent degree of cell damage. This differential between normal and malignant material has been found in isolated tissues, animal studies, and more recently in clinical trials. However, the classical radiation concept is that high energy linear transfer radiation (LET) is more damaging than the equivalent total dose of low LET. Thus, the susceptibility of cells should be greater to short-term exposure to high LET. This article discusses the potential reasons that may account for this discrepancy. While the relative protection given to untransformed tissues by FLASH-RT relative to tumor tissue is a major step forward in radiation therapy of cancer, the processes that lie behind this phenomenon are incompletely understood and are considered here.

Purpose Radiotherapy is integral in the management of hematological malignancies (HM). Standard radiotherapy dose fractionation regimens range between 20-50 Gy in 10-25 fractions over 2-5 weeks. This study presents the outcomes of patients with HM treated with hypofractionation radiotherapy (HFRT) during the COVID-19 pandemic. Methods Patients (N=36) were treated with HFRT between January 2020 and September 2022. The outcomes measured were the overall response rate (ORR), freedom from local progression (FFLP), and overall survival (OS). Results Median follow-up was 13.2 months. Thirty-three patients (92%) had non-Hodgkin (NHL) or Hodgkin lymphoma (HL). Eighteen patients (50%) had aggressive and 9 (25%) had indolent NHL. Nineteen patients (53%) presented with stage I/II and 15(42%) with stage III/IV disease. Twenty-five (69.4%) and eleven (30%) received consolidative and definitive RT, respectively. Twenty patients (56%) received treatment to the neck and/or thorax, and 9 (25%) to the abdomen or pelvis. Total dose ranged from 18 to 42.5 Gy in 6-17 fractions/ 2.67-5 Gy per fraction. Median dose in 2 Gy fractions for an alpha/beta (α/β) ratio of 10 amounted to 39 Gy (SD ± 13.86), and 43.6 Gy (SD ± 12) for an α/β of 3. The most commonly used fractionation scheme was 39 Gy in 13 fractions. ORR was 94.4% for the entire cohort, and 100, 94.4, and 83.3% for indolent NHL, aggressive NHL, and HL patients. Two-year FFLP was 76% (95% CI: 34-93%) for the entire cohort, and 100, 87 (95%CI: 56.4-96.5%) and 42% (95% CI: 1.1-84.3%) for the indolent NHL, aggressive NHL, and HL patients. Two-year OS for the entire cohort was 80% (95% CI:59.9-90.5%), and 100, 66.1 (95% CI: 36.4-84.4%) and 100% for the indolent NHL, aggressive NHL, and HL patients. Only one patient presented with grade two pulmonary toxicity. Conclusion HFRT in HM provides excellent local control without any increase in toxicity.

Uveal melanoma represents the most prevalent form of primary malignant intraocular tumor in adults. Historically, enucleation was considered the gold-standard approach in the treatment of uveal melanoma. Nowadays, radiotherapy is the most commonly used therapy, aiming at a better quality of life. However, radiotherapy can result in several ocular complications, some of which may be vision-threatening. Radiation-induced dry eye, scleral necrosis, cataract, rubeosis iridis, neovascular glaucoma, radiation retinopathy and maculopathy and optic neuropathy are the most common. This article aims to summarize the current literature on the ocular complications after radiotherapy, their clinical features, risk factors and management strategies. A thorough understanding is crucial for ophthalmologists and oncologists to provide optimal patient care, improve visual outcomes, and minimize long-term complications.

The impact of sex in the development of long-term toxicities affecting the quality of life of cancer survivors has not been investigated experimentally. To address this issue, a series of neurologic and cardiologic endpoints were used to investigate sex-based differences triggered by paclitaxel treatment and radiotherapy exposure. Male and female WT mice were treated with Paclitaxel (150 and 300 mg/kg) administered weekly over 6 weeks or exposed to 19 Gy cardiac irradiation. Cohorts were analyzed for behavioral and neurobiologic endpoints to assess systemic toxicity of paclitaxel or cardiovascular endpoints to assess radiotherapy toxicity. Interestingly, female WT mice exhibited enhanced tolerance compared to male WT mice regardless of the treatment regimen. To provide insight into the possible sex-specific protective mechanisms, rhoB deficient animals and elderly mice (22 months) were used with a focus on the possible contribution of sex hormones including estrogen. RhoB deficiency and advanced age had no impact on neurocognitive impairment induced by Paclitaxel but reversed the cardioprotection was observed in females after radiotherapy. Conversely, rhoB deficiency protected males from radiation toxicity. In sum, rhoB was identified as a molecular determinant driving estrogen dependent cardioprotection in female mice, whereas neuroprotection was not sex-hormone dependent. To our knowledge, this study revealed for the first time sex- and organ-specific responses to paclitaxel and radiotherapy.

Because data on the fungal gut community structure of African children are scarce, we aimed to describe by reanalysing rRNA ITS1 and ITS2metabarcoding data from a study designed to assess the influence of microbiota in malaria susceptibility in Malian children from the Dogon country. More specifically, we aimed to establish the core gut mycobiome and compare the gut fungal community structure of breastfed children, aged 0-2 years, with other age groups. Briefly, DNA was extracted from 296 children’s stool samples. Both rRNA ITS1 and ITS2 genomic barcodes were amplified and subjected to Illumina MiSeq sequencing. The ITS2 barcode generated 1,975,320 reads and 532 operational taxonomic units (OTUs), while the ITS1 barcode generated 647,816 reads and 532 OTUs. The alpha diversity was significantly higher by using the ITS1 compared to the ITS2 barcode (p

In recent years, the field of radiotherapy has witnessed remarkable advancements with the integration of artificial intelligence (AI) technologies into clinical practice. Traditionally, radiotherapy treatment planning has been a labor-intensive process, requiring meticulous manual segmentation and optimization. With the advent of AI, particularly deep learning algorithms, the accuracy and efficiency of target delineation and organ-at-risk segmentation have significantly improved. AI-driven algorithms analyze voluminous medical imaging data, enabling rapid and precise contouring, thus expediting the planning phase and reducing inter-observer variability. Furthermore, AI's role extends to treatment plan optimization, where it intelligently explores vast parameter spaces to generate optimal plans tailored to individual patients. This not only saves dosimetrists' time but also enhances plan quality by accounting for complex anatomical variations and personalized clinical goals. In the realm of treatment delivery, AI-powered real-time image guidance enhances the accuracy of patient positioning, ensuring precise radiation targeting. Adaptive radiotherapy, enabled by AI, allows on-the-fly plan modifications in response to anatomical changes, significantly improving treatment accuracy in scenarios like tumor shrinkage or weight loss. Beyond planning and delivery, AI algorithms contribute to outcome prediction by analyzing historical patient data and treatment responses. This predictive capability aids clinicians in making informed decisions and refining treatment strategies for better prognoses. Despite the revolutionary potential, challenges remain in seamlessly integrating AI into clinical workflows. Ethical considerations, data privacy, and algorithm interpretability necessitate cautious implementation. Additionally, fostering interdisciplinary collaboration between AI experts and radiation oncologists is imperative to harness the technology's full potential. This paper explores the impact of AI in four key areas of radiotherapy: automated segmentation, dosimetric and machine quality assurance, adaptive radiation therapy, and clinical outcome prediction.

The role of postmastectomy radiotherapy and regional nodal irradiation after radical mastectomy is defined in high-risk patients with locally advanced tumors, positive margins, and unfavorable biology. The benefit of postmastectomy radiotherapy in intermediate-risk patients (T3N0 tumors) remains a matter of controversy. It has been demonstrated that radiotherapy after breast-conserving surgery lowers the locoregional recurrence rate compared with surgery alone and improves the overall survival rate. In patients with 4 or more positive lymph nodes or extracapsular extension regional lymph node irradiation is indicated regardless of the surgery type (breast-conserving surgery or mastectomy). Despite the consensus that patients with more than 3 positive lymph nodes should be treated with radiotherapy, there is a controversy regarding the recommendations for patients with one to three involved lymph nodes. In patients with N0 disease with negative findings on axillary surgery, there is a trend to administer regional lymph node irradiation in patients with a high risk of recurrence. In patients treated with neoadjuvant systemic therapy and mastectomy, adjuvant radiotherapy should be administered in case of clinical stage III and/or ≥ypN1. In patients treated with neoadjuvant systemic therapy and breast-conserving surgery, postoperative radiotherapy is indicated irrespective of pathological response.

Background: Optimal hypofractionated schedule of post-prostatectomy radiotherapy remains to be established. We evaluated treatment outcomes and toxicity of the moderately hypofractionated post-prostatectomy radiotherapy in 16 daily fractions delivered with IMRT/VMAT. The treatment schedule selection was motivated by limited technology resources. Methods: One hundred consecutive M0 patients with post-prostatectomy radiotherapy were evaluated. Radiotherapy indication was adjuvant (ART) in 19%, early salvage (eSRT) in 46% and salvage (SRT) in 35%. The dose prescription for prostate bed PTV was 52.8 Gy in 16 fractions of 3.3 Gy. The Common Terminology Criteria v.4 for Adverse Events scale was used for toxicity grading. Results: The median follow-up was 61 months. Five-year biochemical recurrence-free survival (bRFS) was 78.6%, distant metastases-free survival was 95.7% and overall survival was 98.8%. Treatment indication was the only significant factor for 5-year bRFS in multivariate analysis which was 84.6% vs. 67.6% for ART or eSRT vs. SRT respectively (HR 0.15, 95% CI 0.05–0.47, p=0.001). Acute GI toxicity grade 2 was recorded in 24%, grade 3 in 2% and acute GU toxicity grade 2 in 10% and no grade 3. Cumulative rate of late GI toxicity grade ≥2 was observed in 9% and late GU toxicity grade ≥2 in 16%. Conclusion: Observed results confirmed efficacy and acceptable toxicity of post-prostatectomy hypofractionated radiotherapy in 16 daily fractions.

This review highlights normal and tumor tissue vasculature, immunological changes, and phenotypic alterations (VIP model) as fundamental in abscopal interaction. In the stereotactic body radiotherapy (SBRT) and immunotherapy era, we are moving toward “immunological radiation planning,” i.e., radiation scheduling with abscopal effect as a vital endpoint as well. Towards this end, this manuscript presents specific diagrammatic tumor models to optimize the outcome of abscopal response in SBRT, based on the principle of the four R’s - Repair, Redistribution, Repopulation, and Reoxygenation of radiotherapy. The article highlights the importance of restricting the dose of SBRT to < 10 Gy per fraction, appropriate use of dose painting, and concomitant/delayed SBRT boost potential. Current literature indicates that immunotherapy should not precede but follow SBRT within seven days. Included is the review of integrating “cyclical” antiangiogenics, immune adjuvants/immune-metabolites as abscopal effect enhancers with SBRT. The importance of proton, carbon-ion SBRT is dealt with briefly. Proposed six fundamental requirements for augmentation of the abscopal cascade are listed. The existing exploratory results need to develop a definitive strategy amidst complex interactions in SBRT, immunotherapy, immune-adjuvants, & abscopal effects. We now have enough literature evidence to convert “abscopal by chance” to “abscopal by design” by harmonized combinatorial approach.

The standard care for metastatic breast cancer (MBC) is systemic therapies with imbrication of focal treatment for symptoms. Recently, thanks to implementation of radiological and metabolic exams and development of new target therapies, oligometastatic and oligoprogressive settings are even more common, paving the way to a paradigm change of focal treatments role. In fact, according to immunophenotype, radiotherapy can be considered with radical intent in these settings of patients. The aim of this literature review is to analyse available clinical data on prognosis of bone metastases from breast cancer and benefits of available treatments for developing a practical guide for clinicians.

In a hyperconnected society, computer networks play a pivotal role in all activities that permeate our daily lives. In the context of smart cities, theses networks play a pivotal role in enhancing urban efficiency and sustainability. The continuous flow of packets in these networks poses security challenges, from personal data leakage to service unavailability. Anomaly-based methods are commonly used to detect network attacks. In this context, Software-Defined Networking (SDN) emerges as a solution for anomaly detection in network traffic, facilitating comprehensive, real-time analyses and dynamic adaptation to changes. This study aims to present a systematic review of feature selection techniques and evaluate the effectiveness of attribute selection with a multi-class classifier in network anomaly detection. The objective of this paper is to inspire future research and identify trade-offs among these techniques for detecting Denial of Service (DoS) attacks. Based on the findings, the analysis of the entire dataset yields superior results in terms of precision (99%), but using the output of OneR, although resulting in a slight loss of precision compared to the complete dataset, presents the highest precision among other studied techniques, indicating a trade-off between precision and processing time efficiency.

Background: Emerging data indicate that radiotherapy can modulate antitumour immune responses. Regulatory T cells (Tregs) are a key immunosuppressive subpopulation of interest. We aimed to evaluate the impact of conventional fractionated radiotherapy on circulating Treg levels in melanoma patients and to determine the correlation between these changes and survival. Understanding radiotherapy–immunity interactions may facilitate personalized combination therapies. Methods: Peripheral blood samples from 32 melanoma patients were analysed to quantify Tregs before and 1-3 months after regional lymph node radiotherapy using flow cytometry. Tregs were characterized as CD4+/CD25+/CD127-. Total CD4+ T cells were also evaluated. Changes were compared to those in a control group of 30 tumor-free patients. Overall survival was correlated with T-cell subset dynamics induced by radiotherapy. Results: At baseline, the median percentage of Tregs was not significantly lower in melanoma patients than in controls (7.4% vs 8.32%, p=0.17). Radiotherapy markedly increased the median Treg count to 10.01% (p=0.0008), with a concomitant increase in total CD4+ cells (to 11.71%, p=0.001), indicating systemic expansion. Patients exhibiting coordinated increases in Treg and CD4+ T cells after treatment had a significantly improved prognosis compared with nonresponders (median OS 27.8 vs 13.1 months, p=0.001). Conclusions: Our study demonstrated the significant effects of standard fractionated radiotherapy on systemic Treg levels in melanoma patients. Radiation-induced changes in T-cell subset proportions hold prognostic value. Monitoring of circulating lymphocyte subsets could facilitate personalized combination therapies.

The benefit of adjuvant radiotherapy (RT) after radical hysterectomy in patients with cervical cancer remains controversial. The aim of this study was to determine the impact on survival of adjuvant RT according to the Sedlis criteria. Patients with early-stage cervical cancer who underwent radical hysterectomy between 2005 and 2022 at a single tertiary institution were included. A multivariate analysis was performed to determinate if RT was an independent prognostic factor for recurrence or death. We also analyzed whether there was a statistically significant difference in overall survival (OS) between patients who met only one or two Sedlis criteria, depending on whether they received adjuvant RT or not. In this retrospective study 121 patients were included of whom 48(39.7%) received adjuvant RT due to the presence of unfavorable pathological findings. In multivariate analysis, RT was not found to be a statistically significant prognostic factor for OS (p=0.584) or disease-free survival (DFS) (p=0.559). When comparing patients who met one or two Sedlis criteria, there were no statistically significant differences in OS between RT and no adjuvant treatment in either group. Since the selection of patients with cervical cancer eligible for surgery is becoming more accurate, adjuvant RT might not be necessary for patients with intermediate-risk factors.

Introduction The outcome of radiotherapy (RT) for prostate cancer (PCA) depends on the delivered dose. While the evidence for dose-escalated RT up to 80 Gy is well established, there have been only few studies examining dose escalation above 80 Gy. We initiated the presented study to assess the safety of dose escalation up to 84 Gy. Patients and methods In our retrospective analysis, we included patients who received dose-escalated RT for PCA at our institution between 2016 and 2021. We evaluated acute genitourinary (GU) and gastrointestinal (GI) toxicity as well as late GU and GI toxicity. Results A total of 86 patients could be evaluated, of whom 24 patients had received 80 Gy and 62 patients had received 84 Gy (35 without pelvis- and 27 with pelvis-radiotherapy). Regarding acute toxicities, no adverse events > grade 2 occurred. 12.5% of patients treated with 80Gy, in 25.7% of patients treated with 84 Gy excluding pelvis, and in 51.9% of patients treated with 84Gy including pelvis suffered from Grade 2 GU acute toxicity (80 Gy versus 84 Gy: p=0.186; with pelvis versus without pelvis: p=0.032). Grade 2 GI toxicity occurred in 12.5% of patients irradiated with 80Gy, in 14.3% of patients treated with 84 Gy excluding pelvis, and in 12.9% of patients treated with 84Gy including pelvis (80 Gy versus 84 Gy: p=0.582; with pelvis versus without pelvis: p=0.510).GU late toxicity of grade ≥ 2 occurred in 4.2% of patients treated with 80 Gy, in 7.1% of patients treated with 84 Gy excluding pelvic RT, and in 18.2% of patients treated with 84 Gy including pelvic RT (logrank-test p=0.237). 8.3% of patients treated with 80 Gy, in 3.6% of patients treated with Gy excluding pelvic RT, and in 0% of patients treated with 84 Gy including pelvic RT suffered from GI late toxicity of grade ≥ 2(logrank-test p=0.358). Conclusion We were able to show that dose-escalated RT in PCA up to 84 Gy is feasible and safe without asubstantial increase in toxicity. Further follow up is needed to assess survival.

Glioblastoma (GBM), the most common and aggressive primary brain tumor in adults, remains one of the least treatable cancers. Current standard of care—combining surgical resection, radiation, and alkylating chemotherapy—results in a median survival of only 15 months. Despite decades of investment and research into the development of new therapies, most candidate anti-glioma compounds fail to translate into effective treatments in clinical trials. One key issue underlying this failure of therapies that work in pre-clinical models to generate meaningful improvement in human patients is the profound mismatch between drug discovery systems—cell cultures and mouse models—and the actual tumors they are supposed to imitate. Indeed, current strategies that evaluate the effects of novel treatments on GBM cells in vitro fail to account for a wide range of factors known to influence tumor growth. These include secreted factors, the brain’s unique extracellular matrix, circulatory structures, the presence of non-tumor brain cells, and nutrient sources available for tumor metabolism. While mouse models provide a more realistic testing ground for potential therapies, they still fail to account for the full complexity of tumor-microenvironment interactions, as well as the role of the immune system. Based on the limitations of current models, researchers have begun to develop and implement novel culture systems that better recapitulate the complex reality of brain tumors growing in situ. A rise in the use of patient derived cells, creative combinations of added growth factors and supplements, may provide a more effective proving ground for the development of novel therapies. This review will summarize and analyze these exciting developments in 3D culturing systems. Special attention will be paid to how they enhance the design and identification of compounds that increase the efficacy of radiotherapy, a bedrock of GBM treatment.

Radiotherapy is the primary treatment modality for non-metastatic nasopharyngeal carcinoma (NPC) across all TNM-stages. Locoregional control rates have been impressive even from the 2D-radiotherapy (RT) era, except when the ability to deliver optimal dose coverage to the tumor is compromised. However, short- and long-term complications following head and neck RT are potentially debilitating, and thus, there had been much research investigating technological advances in RT delivery over the past decades, with the primary goal of limiting normal tissue damage. On this note, with a plateau in gains of therapeutic ratio by modern RT techniques, future advances have to be focused on individualization of RT, both in terms of dose prescription and delineation of target volumes. In this review, we analyzed the guidelines and evidence related to contouring methods, and dose prescription for early and locoregionally-advanced (LA-) NPC. Next, with the preference for induction chemotherapy (IC) in patients with LA-NPC, we assessed the evidence concerning radiotherapy adaptations guided by IC response, as well as functional imaging and contour changes during treatment. Finally, we discussed on RT individualization that is guided by EBV DNA assessment, and its importance in the era of combinatorial immune checkpoint blockade therapy with RT.

The objective of this study was to analyze the mental workload using EEG and eye tracking data and classify it using machine learning algorithms. The machine learning model was developed based on the simultaneous recording of eye tracking and EEG measurements during the experimental process. The experiments involved 15 university students, consisting of 7 women and 8 men. Throughout the experiments, the researchers utilized the n-back memory task and the NASA-Task Load Index (TLX) subjective rating scale to assess various levels of mental workload. The findings revealed that as the task difficulty increased, there was an increase in the diameter of both the right and left pupils, the number of fixations, the number and duration of saccades, and the number and duration of blinks. Conversely, variables related to fixation duration decreased. The EEG results indicated that theta power in the prefrontal, frontal, and front central regions increased with task difficulty. Additionally, alpha power increased in the frontal regions but decreased in the temporal, parietal, and occipital regions as the task became more challenging. Furthermore, low beta power significantly decreased in almost all brain regions as the task difficulty increased. In terms of the four-class classification problem, the mental workload level can be predicted with an accuracy rate of 76.59% using 34 selected features. This study has made a significant contribution to the literature by presenting a four-class mental workload estimation model that utilizes different machine learning algorithms.

High pressure crystallization technique has been successfully used to prepare an elusive form II of a non-steroidal anti-inflammatory drug, Mefenamic acid. Single crystal of form II was grown at 0.3 GPa from an 4:1 methanol/ ethanol mixture as a solvent using Diamond Anvil Cell. Comparison of crystal structures show that the efficient packing of MA molecules in Form II results from the structural flexibility of MA acid molecules. Compression studies performed on the single crystal of form I resulted in 14 % decrease of unit cell volume up to 2.5 GPa. No phase transition was observed up to this pressure. A reconstructive phase transition is required to induce conformational changes in the structure, which is confirmed by crystallization at high pressure results.

This review aims to consolidate varied information regarding Port Scanning, and examine the tools, techniques, and detection algorithms used. It explores TCP SYN, Full TCP, UDP, and stealth scans, and shows their functions and abilities. Paired with these techniques, it also shows the tools that they can be used by, such as NMap, Zmap, and MASSCAN. It discusses the various detection techniques such as Signature and Anomaly based detection, and discusses the real world impact of this technology, while commenting on the legal and ethical issues posed.

In this work we introduce an end-to-end multi-modal neural network to segment the Gross Tumor Volume (GTV) from 3D-CBCT’s during radiotherapy. We improve the tumor segmentation by using a U-net which takes additional information such as the tumor mask generated at the planning phase along with the CBCT volume. The mask contains relevant information about the tumor’s location and can guide the model to use this knowledge appropriately to give a better prediction. This technique could become an alternative to produce segmentation masks of GTV in CBCT automatically during radiotherapy as in the traditional RT-pipeline, they are not segmented. We have evaluated our model on a dataset of 82 patients who have undergone radiotherapy. We compare the results of registered target volumes from planning CT as mask seed with 2 different types of multi-modal architectures. Our model shows a DSC of 0.706±0.002 with Late Fusion and 0.702±0.015 with Early Fusion using the GTV Mask. The performance of the two models on this mask is similar, so we perform further experiments with different types of masks which suggest that Late Fusion model produces a better segmentation of the tumor than the Early Fusion model. We also provide an ablation study consisting of a single modality U-net and a metric based on the Planning CT mask registration. It indicates a clear advantage of using our model to produce segmentation for this type of imaging.

Immunotherapy with stereotactic body radiotherapy (SBRT), low-dose antiangiogenics, immune adjuvants, nanomedicine, or other combinations will likely play a lead role in managing malignancies soon. Presently, its benefit extends to about 12% to 20% of patients, in the background of possible recurrence eventually and the toxicities, including in non-responders. Stereotactic body radiotherapy (SBRT) not only eliminates the indexed lesions, but recently, the evidence is accumulating about its systemic abscopal effects. It needs to be evolved to a dependable in situ therapeutic vaccine production and to activate short- and long-term memory immune lymphocytes. The in-situ immune cascade happens with the ability of SBRT to generate Tumor-specific neoantigens and neoepitopes, which enhance the activation of antigen-presenting cells, invoke and restore the competence of Tumor-infiltrating lymphocytes, resulting in cancer cell lysis. This cell lysis, in turn, can generate further neoantigens and epitopes, imparting a virtuous cycle that is the hallmark of effective vaccines. Additionally, SBRT can synergistically enhance the other in situ vaccination strategies, concurrent in vitro vaccines or nanomedicines, making it a primary tool for sensitizing even the “cold” tumors for immunotherapy. The present proposed hypotheses, primarily based on a preclinical literature review, focus on the critical aspects of the in-situ vaccination generation capability of SBRT when used in pulsed, cyclical, or intermittent endothelial-sparing single dose schedules along with immunotherapy and other supportive measures. This schedule is categorized as in situ vaccine dose (ISVD) radiotherapy (RT) (distinguishable from the standard therapeutic SBRT schedule) in metastatic cancer settings after standard /first-line therapies.

Due to the rapid development of unmanned aerial vehicles (UAVs) communication technology, UAVs are gradually competing with primary users (PUs) for spectrum resources. Cognitive radio (CR) is a promising solution to meet the needs. Cooperative spectrum sensing (CSS) is considered as an effective method to detect the PU signal and identify available spectrum resources for UAVs in a cognitive UAV network (CUAVN). However, the cooperative mode among multiple UAVs may incur a high overhead, resulting in performance degradation. Therefore, we introduce a differential sequential 1 (DS1), which incorporates a differential mechanism and leverages the sequential idea based on the classical voting rule to enhance cooperative performance and efficiency. In view of this, we formulate three scenarios to characterize the PU activity and introduce a multi-slot cooperative mode within a single UAV to realize cooperative gain. Further, only the information change about the PU status is sequentially calculated in DS1, and combined with a sequential idea, the efficiency of the voting rule is greatly improved. Moreover, the application of support vector machines (SVM) in dynamic selection enables the selection of the most suitable voting rule based on diverse sensing parameters. This dynamic selection process ensures optimal performance and efficiency by adapting the voting rule to the specific characteristics of the given scenario. Finally, simulation results demonstrate that the superiority of our proposal with respect to the detection performance, sample size and the energy efficiency is evident, which proves the high performance of the proposed policy.

Physicians often label anatomical structure sets in Digital Imaging and Communications in Medicine (DICOM) images with nonstandard names. As these names vary widely, the standardization of the nonstandard names in the Organs at Risk (OARs), Planning Target Volumes (PTVs), and 'Other' organs inside the area of interest is a vital problem. Prior works considered traditional machine learning approaches on structure sets with moderate success. This paper presents integrated deep learning methods applied to structure sets by integrating the multimodal data compiled from the radiotherapy centers administered by the US Veterans Health Administration (VHA) and the Department of Radiation Oncology at Virginia Commonwealth University (VCU). The de-identified radiation oncology data collected from VHA and VCU radiotherapy centers have 16,290 prostate structures. Our method integrates the heterogeneous (textual and imaging) multimodal data with Convolutional Neural Network (CNN)-based deep learning approaches like CNN, Visual Geometry Group (VGG) network, and Residual Network (ResNet). Our model presents improved results in prostate (RT) structure name standardization. Evaluation of our methods with macro-averaged F1 Score shows that our deep learning model with single-modal textual data usually performs better than the previous studies. We also experimented with various combinations of multimodal data (masked images, masked dose) besides textual data. The models perform well on the textual data alone, while the addition of imaging data shows that deep neural networks can achieve improved performance using information present in the other modalities. Additionally, using masked images and masked doses along with text leads to an overall performance improvement with the various CNN-based architectures than using all the modalities together. Undersampling the majority class leads to further performance enhancement. The VGG network on the masked image-dose data combined with CNNs on the text data performs the best and establishes the state-of-the-art in this domain.

Background: We aimed to assess the risk of chemotherapy- and radiotherapy-related cognitive impairment in colorectal cancer patients. Methods: We randomly selected 40% of colorectal cancer patients from Korean National Health Insurance Database (NHID), 2004-2018 (N=148,848). Patients with one or more ICD-10 diagnostic codes for dementia or mild cognitive impairment was defined as cognitive impairment cases. Patients who were aged 18 or younger, diagnosed with cognitive impairment before colorectal cancer (N=8,225) and did not receive primary resection (N=45,320) were excluded. The effects of each chemotherapy agent on cognitive impairment were estimated. We additionally estimated the effect of radiotherapy in rectal cancer patients. Time-dependent competing risk Cox regression was conducted to estimate overall and age-specific hazard ratios (HR) separately for colon and rectal cancer. Results: In colon cancer, capecitabine and irinotecan was associated with higher cognitive im-pairment, while 5-fluorouracil was not. In rectal cancer, no chemotherapy agents increased the risk of cognitive impairment, nor did radiotherapy. Hazardous association of irinotecan was estimated larger in elderly patients compared with younger counterparts. Conclusion: Heterogeneous associations between various chemotherapy agents and cognitive impairment were observed. Elderly patients were more vulnerable to possible adverse cognitive effects. Radiotherapy did not increase the risk of cognitive impairment.

Background: Radiotherapy plays an important role in the management and survival of patients with breast cancer. The aim of this study was to examine the association between age, comorbidities and use of radiotherapy in this population. Methods: Patients diagnosed with breast cancer from 2004–2013 were identified from the American College of Surgeons National Cancer Database (NCDB). Follow-up time was measured from the date of diagnosis (baseline) to the date of death or censoring. Adjusted hazard ratios (aHR) and 95% confidence intervals (95%CI) were used as the measure of association. Results: Independently of comorbidities and other important outcome-related factors, patients >65 years of age who received radiotherapy survived significantly longer than those who did not receive radiotherapy (aHR = 0.53, 95%CI = 0.52–0.54). However, as women aged, those with comorbidities were less likely to receive RT (adjusted P-trend by age <0.0001). Conclusions: The development of decision-making tools to assist clinicians, and older women with breast cancer and comorbidities, are needed to facilitate personalized treatment plans regarding RT. This is particularly relevant as the population ages and the number of women with breast cancer is expected to increase in the near future.

The phytophagous insect pests were vectors and could transmit the majority of the phytoviruses to their host plants. The orders of Hemiptera and Thysanoptera were the most common vectors of phytoviruses. The orders Orthoptera, Dermaptera, Coleoptera, Lepidoptera, Diptera, Thysanoptera, and Hemiptera were also the vectors of phytoviruses. Furthermore, aphids, whiteflies, cicadas, spittlebugs, leafhoppers, planthoppers, assassin bugs, plant bugs, stink bugs, lygaeid bugs, and thrips were among the most phytophagous insects that vector and transmit phytoviruses to healthy plants. The occurrence of a single species of these phytophagous insects resulted in one or more phytoviruses in general, and the Hemipteran order, in particular, vectored a lot of phytoviruses species. This review manuscript is focused on vectors of phytoviruses, techniques for their detection, and future directions. It will play a vital role in exploring scientific information concerning the interactions of phytoviruses and vector insects, the effect of phytoviruses on host behavior, mediators of phytoviruses transmission, persistent phytoviruses, some other insect vectors of the phytopathogen, mechanisms of host plant resistance against phytoviruses, and techniques of phytoviruses detection, as well as some important points to be considered in the future sustainably.

Biocontainment techniques for genetically modified yeasts (GMYs) are pivotal due to the importance of these organisms for biotechnological processes and also due to the design of new yeast strains by using synthetic biology tools and technologies. Due to the large genetic modifications that many yeast strains display, it is highly desirable to avoid the leakage of GMY cells into natural environments and, consequently, the spread of synthetic genes and circuits by horizontal or vertical gene transfer mechanisms within the microorganisms. Moreover, it is also desirable to avoid that patented yeast gene technologies spread outside the production facility. In this review, it was evaluated the different biocontainment technologies currently available for GMYs. Interestingly, uniplex-type biocontainment approaches (UTBAs), which relies on nutrient auxotrophies induced by gene mutation or deletion, or the expression of simple kill switches apparatus, are still the major biocontainment approaches still in use with GMY. While bacteria like Escherichia coli account for advanced biocontainment technologies based on synthetic biology and multiplex-type biocontainment approaches (MTBAs), GMYs are distant from this scenario due to many reasons. Thus, a comparison of different UTBAs and MTBAs applied for GMY and genetically engineered microorganisms (GEMs) was made, indicating the major advances of biocontainment techniques for GMYs.

This research paper describes the social engineering concepts, techniques, and security countermeasures. This research aims to study various social engineering techniques to find the best countermeasures that would help to reduce social engineering attacks.

Metabolomics is now considered to be a wide-ranging, sensitive and practical approach to acquire useful information on the composition of a metabolite pool present in any organism, including plants. Investigating metabolomic regulation in plants is essential to understand their adaptation, acclimation and defense response to environmental stresses through the production of numerous metabolites. Moreover, metabolomics can be easily applied for the phenotyping of plants; and thus, it has great potential to be used in molecular breeding and genome editing programs to develop superior next generation crops. This review describes the recent analytical tools and techniques available to study plants metabolome, along with their significance of sample preparation using targeted and non-targeted method. Advanced analytical tools, like gas chromatography-mass spectrometry (GC-MS), liquid chromatography mass-spectroscopy (LC-MS), capillary electrophoresis-mass spectrometry (CE-MS), fourier transform ion cyclotron resonance-mass spectrometry (FTICR-MS) and matrix-assisted laser desorption/ionization (MALDI) have speed up metabolic profiling in plants. Further, we deliver a complete overview of bioinformatics tools and plant metabolome database that can be utilized to advance our knowledge to plant biology.

As of not long ago, understanding the administrative conduct of cells has been sought after through autonomous investigation of the transcriptome or the proteome. In view of the focal creed, it was commonly accepted that there exist an immediate correspondence between mRNA records and produced protein articulations. In any case, late examinations have demonstrated that the relationship among's mRNA and Protein articulations can be low because of different factors, for example, unique half lives and post record apparatus. In this manner, a joint investigation of the transcriptomic and proteomic information can give valuable experiences that may not be translated from singular examination of mRNA or protein articulations. This article audits the current significant methodologies for joint investigation of transcriptomic and proteomic information. We order the various methodologies into eight primary classes dependent on the underlying calculation and last investigation objective. We further present analogies with different spaces and talk about the current exploration issues around there.

Wireless communication has proliferated due to the colossal augmentation of smart phones, mobile phones, tablets and laptops etc. Multimedia applications such as live videos, audios, still images, animated graphics and live communications all requires accompaniments of quality of service (QoS) as well as reliable end-to-end transfer of data. Information about the availability of resources in channel is must in order to improve the QoS. QoS can be determined in terms of capacity of channel, available bandwidth (ABW), and bulk transfer capacity (BTC). Bandwidth availability is a key check for improving the QoS in a network. The performance of a multimedia application is directly affected by the bandwidth availability. One of the most important QoS characteristic is ABW at a wireless route and it can be demarcated as least unused capacity of links instituting a network route. Since now there have been many bandwidth estimation techniques are available in the literature to increase the network performance. Bandwidth estimation techniques have been arranged into three leading classifications: i) Active probing bandwidth estimation techniques, ii) Passive bandwidth estimation technique and iii) Model based bandwidth estimation techniques. Each of these techniques are briefly discussed in this paper.

Berberis vulgaris L. (Berberidaceae) is a shrub that has been widely used in European folk medicine as an anti-inflammatory and antimicrobial agent. The purpose of our study was to elucidate the mechanisms of antiproliferative action of the plant’s methanolic root extract (BVR) against colon cancer cells. Cytotoxicity and pro-apoptotic activity were determined in human colon adenocarcinoma cell lines (LS180 and HT-29) and control colon epithelial CCD841 CoN cells. According to the MTT assay, after 48 h of cell exposure, the IC50 values were as follows: 4.3; 46.1 and 50.2 µg/mL for LS180, HT-29, and CCD841 CoN cells, respectively, showing the greater sensitivity of cancer cells to BVR. The Cell Death Detection ELISAPLUS kit demonstrated that BVR induced programmed cell death only against HT-29 cells. RT-qPCR with relative quantification method showed significant changes in the expression of genes related to apoptosis in both colon cancer cell lines. The genes BCL2L1 (126.84-366.66%), BCL2L2 (277.08-330.12%), CASP3 (180.36-261.36%) and CASP9 (158.08-213.46%) had significantly elevated expression, while BCL2 (23.08-52.06%) had reduced expression. Furthermore, in a panel of antioxidant tests, BVR showed positive effects (63.93±0.01, 122.92±0.01, and 220.29±0.02 mg Trolox equivalents (TE)/g in the DPPH•, ABTS•+ and ORAC assays, respectively). In the lipoxygenase (LOX) inhibition test, BVR revealed 62,60±0.87% of enzyme inhibition. The chemical composition of BVR was determined using UHPLC-UV-CAD-MS/MS analysis and confirmed the presence of several known alkaloids, including berberine, as well as other alkaloids and two derivatives of hydroxycinnamic acid (ferulic and sinapic acid hexosides). This is the first such extensive assessment of the biological activity of BVR. The results are very promising and encourage for the use of BVR as a comprehensive chemopreventive agent (anti-inflammatory, antioxidant, and pro-apoptotic) in colorectal cancer.

This study employs Geographic Information System (GIS) techniques to evaluate the walkability of Onaizah City, which serves as a representative model for a Saudi city situated in the Qassim region, north of the capital city, Riyadh. The goal is to evaluate how easily pedestrians can navigate the street network and identify areas that excel or need improvement in terms of walkability. The results offer insights for planning and development supporting sustainable initiatives. Approach; The study involves integrating GIS data, such as street layouts, land use patterns, and demographic information. By analyzing factors like integration values and choice values within the street network the study gauges’ walkability aspects. Furthermore, correlation analysis explores how spatial arrangements, influence walkability. By studying the case of a medium-sized Saudi city, which can then be applied to several Saudi cities. Cost distance analysis and cost-back correlation calculations are employed to determine pedestrian routes. Findings and Discussion; Through GIS techniques the study effectively assesses the walkability of Onaizah City by identifying three walking paths with lengths of (1401m, 1283m, and 1507m). The study reveals pedestrians' actual city distance. Weighted criteria assign 40% to heritage sites, 30% to green spaces, and 15% each to mosques/commercial sites. Preserving access to heritage sites and incorporating areas enhance walkability. Conclusion: Study enhances walkability understanding, offering data-driven planning suggestions. Urban planners prioritize pedestrian connectivity, considering GIS effectiveness and physical environment importance. Findings support walkability research and sustainable urban development.

Radiotherapy for cancer has been known to affect the responses of immune cells, especially those of CD8+ T cells that play a pivotal role in anti-tumor immunity. Clinical success of immune checkpoint inhibitors led to an increasing interest into the ability of radiation to modulate CD8+ T cell responses. Recent studies that carefully analyzed the CD8+ T cell responses following radiotherapy suggest the beneficial roles of radiotherapy on anti-tumor immunity. In addition, numerous clinical trials that evaluate the efficacy of combining radiotherapy with immune checkpoint inhibitors are undergoing. In this review, we summarize the current status of knowledge regarding the changes of CD8+ T cells following radiotherapy from various preclinical and clinical studies. Furthermore, key biologic mechanisms that underlie such modulation, including both direct and indirect effects, are described. Lastly, we discuss the current evidence and essential considerations for harnessing radiotherapy as a combination partner for immune checkpoint inhibitors.

Climate simulations in West Africa have been attributed with large uncertainties. Global climate projections are not consistent with changes in observations at the regional or local level of the Niger basin, making management of hydrological projects in the basin uncertain. This study evaluates the potential of using the quantile mapping bias correction to improve the Coupled Model Intercomparison Project (CMIP5) outputs for use in hydrology impact studies. Rainfall and temperature projections from 8 CMIP5 Global Climate Models (GCM) were bias corrected using the quantile mapping approach. Impacts of climate change was evaluated with bias corrected rainfall, temperature and potential evapotranspiration (PET). The IHACRES hydrological model was adapted to the Niger basin and used to simulate impacts of climate change on discharge under present and future conditions. Bias correction significantly improved the accuracy of rainfall and temperature simulations compared to observations. Nash coefficient (NSE) for monthly rainfall comparisons of 8 GCMs to the observed was improved by bias correction from 0.69 to 0.84. The standard deviations among the 8 GCM rainfall data were significantly reduced from 0.13 to 0.03. Increasing rainfall, temperature, PET and river discharge were projected for all GCMs used in this study under the RCP8.5 scenario. These results will help improving projections and contribute to the development of sustainable climate change adaptation strategies.

We performed electronic research for articles published in PubMed, MEDLINE, and ScienceDirect databases from January 2004 to January 2023. The systematic review of twenty (20) peer-reviewed articles about dosimetric parameters and eight (8) articles about clinical outcomes confirmed the dosimetric advantages of ART through better target coverage and Organs at Risk (OARs) sparing, with subsequent benefits on decreased toxicity and improved clinical outcome, specifically local control of the disease. ART replanning is a sustainable strategy for minimizing toxicity by improving normal tissue sparing. Furthermore, it enhances target volume coverage by correctly determining the specific amount of dose to be delivered to the tumor. In conclusion, this review confirms that ART benefits dosimetric, clinical/therapeutic, and toxicity outcomes.

Cardiopulmonary resuscitation (CPR) is a widely practiced lifesaving skill. Conventional CPR is based on manual chest compressions and delivering mouth-to-mouth breaths. There has been advancement in biomedical technology over the last few decades which has led to the introduction of new techniques and devices in CPR as well. In light of these advancements, we propose SMEAR (Standard, Mechanical, ECMO Assisted, Augmented virtual and Remote) classification system to provide structured overview from traditional to novel methods and devices. The standard or Manual CPR, widely practiced by the general public during out-of-hospital cardiac arrests, combines active chest compressions with or without mouth breathing. However, to enhance CPR’s efficacy, various mechanical devices have been developed, encompassing Active Chest Compression, Passive Decompression, and those integrated with Automated External Defibrillators. Feedback sensor-equipped devices, include the Metronome, Accelerometer, Barometer, and Triaxial Field Induction. Mechanical devices, classified by their compression mechanisms, can be isolated – like the Piston-driven, Load-distributing, and Active Compression-Decompression (ACD) – or combined, as in ACD-ITV (Impedance Threshold Device), ACD-IAC (Interposed Abdominal Compression), and ACD-ITV-EECP (Enhanced External Counter Pulsation). Beyond mechanics, Extracorporeal CPR offers veno-arterial Extracorporeal Membrane Oxygenation in refractory cardiac arrest and can improve outcomes. Augmented Virtual Reality usage in training and provision of CPR is at the early stages. It has the potential of expanded usage in training public to provide high-quality CPR. A provider can be remotely guided step by step via telephone or smartphone applications, ensuring continuous support until professional assistance arrives.

As the COVID-19 pandemic has caused enormous damage to society, economy and public health security, it is crucial to combat the epidemic and allocate social and health resources effectively. Global optimization algorithms are extensively used in many domains to find optimal solutions to complex problems. Thus, a survey of three typical global optimizations applied on the COVID-19 pandemic is timely. This article is structured into three typical global optimization algorithms - Genetic Algorithm, Particle Swarm Optimization, and Cat Swarm Optimization - and summarizes the framework models and practical applications, as well as other optimization methods that may be applied to COVID-19. Finally, current unresolved challenges and future research opportunities to be explored are summarized.

More than 50% of patients with non-small cell lung cancer (NSCLC) are treated with radiotherapy (RT) during different phases of treatment. However, radiation pneu-monitis (RP) and resistance often lead to RT failure in NSCLC patients. JWA, a tumor suppressor gene, is known to enhance DNA damage in gastric cancer cells while protect normal cells from DNA damage induced by cisplatin. Recently, we have re-ported that JWA agonist compound 4 (JAC4) effectively protects intestinal epithelium from RT triggered damage in mice. However, the potential synergistic and attenuated effects of JAC4 in chest RT of lung cancer are not been illuminated. The aim of this study was to investigate the effects of JAC4 on the radiotoxicities of both NSCLC and normal lung tissue. CCK-8 and colony formation assays showed that JAC4 played a bidirectional role in radiation-treated SPCA-1 and BEAS-2B cells. Western blotting and immunofluorescence assays showed that JAC4 in combination with RT increased DNA damage and apoptosis in SPCA-1 cells, while the opposite effect was observed in BEAS-2B cells. Mechanistically, JAC4 inhibited homologous recombination repair (HR) and non-homologous end joining (NHEJ) in SPCA-1 cells, but not in normal cells. JAC4 increased antioxidant capacity, and reduced oxidative stress and inhibited nu-clear factor Kappa-B (NF-κB, P65) translocation to the nucleus in BEAS-2B cells. Im-portantly, the bidirectional roles of JAC4 on RT were reversed by siJWA in both SPCA-1 and BEAS-2B cells. Finally, the bidirectional effects of JAC4 in combination with RT were further validated in NSCLC xenograft model mice. In conclusion, JAC4 enhanced effect of RT on tumor growth while alleviated RP and lung injury. Our re-sults may provide new strategy for optimizing RT regimen for NSCLC.

Background: Approximately 75% of all head and neck cancer patients are treated with radiotherapy (RT). RT to the oral cavity results in acute and late adverse events which can be severe and detrimental to a patient’s quality of life and function. The purpose of this study was to explore associations between RT dose to a defined oral cavity organ at risk (OAR) avoidance structure, provider and patient reported outcomes (PROs), opioid use, and hospitalization. Methods: This was a retrospective analysis of prospectively obtained outcomes using multivariable modeling. The study included 196 patients treated with RT involving the oral cavity for a head and neck tumor. A defined oral cavity OAR avoidance structure was used in all patients for RT treatment planning. Validated PROs were collected prospectively. Opioid use and hospitalization were abstracted electronically from medical records. Results: Multivariable modeling revealed the mean dose to the oral cavity OAR was significantly associated with opioid use (p=0.0082) and hospitalization (p=0.0356) during and within 30 days of completing RT. Conclusion: The findings of this study may be valuable in RT treatment planning for patients with tumors of the head and neck region to reduce the need for opioid use and hospitalization during treatment.

(1) Background: The prediction of cervical lesions evolution is a challenge for clinicians. The prospective study aimed to determine and compare the predictive accuracy of cytology, HPV genotyping, and p16/Ki67 dual staining alone or in combination with personal risk factors for the prediction of progression, regression or persistence of cervical lesions in human papillomavirus (HPV)-infected patients; (2) Methods: This prospective study included HPV-positive patients with or without cervical lesions that underwent follow-up. Descriptive statistics and sensitivity analysis for individual or combined index tests were used for data analysis; (3) Results: The highest predictive performance for the progression of cervical lesions was achieved by a model that comprised a Pap smear suggestive of high-grade squamous intraepithelial lesion (HSIL), the presence of 16/18 HPV strains, a positive p16/Ki67 dual staining result along with the presence of at least 3 clinical risk factors, which had a sensitivity (Se) of 74.42%, a specificity of 97.92%, an area under the receiver operating curve (AUC) of 0.961, and an accuracy of 90.65%. The prediction of cervical lesions regression or persistence was modest; (4) Conclusions: Multiple testing or new biomarkers should be used to improve HPV-positive patient surveillance, especially for cervical lesion regression or persistence prediction.

The incidence and mortality of cervical cancer are high in Romania compared to other European countries, particularly for locally advanced cervical cancer cases, which are predominant at the time of diagnosis. Widely accepted therapeutic guidelines indicate that the treatment for locally advanced cervical cancer consists of concurrent chemoradiotherapy (total dose 85-90Gy at point A), with surgery not being necessary as it does not lead to improved survival and results in significant additional morbidity. In Romania, the treatment for locally advanced cervical cancer differs, involving lower-dose chemotherapy (total dose 60-65Gy at point A), followed by surgery which, under these circumstances, ensures better local control. In this regard, we attempted to evaluate the role and necessity of surgery in Romania, considering that in our study, residual lesions were found in 55.84% of cases on resected specimens, especially in cases with unfavorable histology (adenocarcinoma and adenosquamous carcinoma). This type of surgery was associated with significant morbidity (28.22%) in our study. The recurrence rate was 24.21% for operated patients compared to 62% for non-operated patients receiving suboptimal concurrent chemotherapy alone. In conclusion, In Romania, surgery will continue to play a predominant role until radiotherapy achieves the desired effectiveness for local control.

Radiotherapy, also known as radiation therapy, is a treatment modality based on the use of high energy rays or radioactive substances, to damage tumoral cells and halt their growth and division. It is an effective tool for treating cancer of different kinds for more than 100 years with remarkable outcomes for cancer patients. This technique is characterised by notable technological innovations and methodologies, enhanced precision and effectiveness. Initially, precision and efficacy of radiotherapy are improved by technological advancements, such as the development of linear accelerators and brachytherapy. As a result, Radiotherapy has transformed the prognosis for cancer patients enhancing survival rates and improving quality of life. Also, it offers targeted and personalized treatment with advancements in imaging techniques such as Intensity-Modulated Radiation Therapy (IMRT) and Stereotactic Body Radiation Therapy (SBRT) and innovations like Image-Guided Radiation Therapy (IGRT), Adaptive Radiotherapy (ART) and Artificial Intelligence (AI). Additionally, techniques like proton therapy result in reduced side effects and collateral damage. Although, among the challenges and future perspectives we note the issue of affordability and accessibility. Ongoing research into immunotherapy and nanotechnology and their synergy with radiation therapy shows potential for further improving treatment outcomes. In conclusion, the evolution of radiotherapy has been a transformative journey, reshaping the prognosis and outcomes for cancer patients.

This narrative review aims to summarize evidence regarding the current utilization and future applications of neuromodulation in patients with headaches, with special attention paid to migraine and chronic cluster headache. We performed a narrative review of the literature to identify studies that detail the effectiveness of neuromodulation therapies in the treatment of headache syndromes. The literature was refined to predominantly focus on systematic reviews published in the last year that have the most robust reporting of research done on this topic. Patients with headache face several challenges, including medication overuse, cost burden, non-compliance to medications due to inability to tolerate side effects, or treatments that are ineffective. Neuromodulation is an emerging field that encompasses implantable and non-implantable technologies that intervene on the signaling and perception of pain. In recent years, this technology has been used as an analgesic, and has been shown to be effective for treatment-resistant headache, particularly when used in patients with migraine and chronic cluster headache.

The efficiency with which an integer may be factored into its prime factors determines several public key cryptosystems′ security in use today. Although there is a quantum-based technique with a polynomial time for integer factoring, on a traditional computer, there is no polynomial time algorithm. We investigate how to enhance the wheel factoring technique in this paper. Current wheel factorization algorithms rely on a very restricted set of prime integers as a base. In this study, we intend to adapt this notion to rely on a greater number of prime integers, resulting in a considerable improvement in the execution time. The experiments on composite numbers n reveal that the proposed algorithm improves on the existing wheel factoring algorithm by about 75%

This paper first introduces the main classification of brain diseases and the main causes of these diseases. It is followed by wavelet analysis, which is a mathematical function or wave-like pattern used to transform data, which can decompose the signal into different wavelet functions, each of which is related to a specific scale or frequency. Wavelet analysis has been applied in many fields such as image processing, data analysis and engineering. In addition, wavelet is also used in the analysis of biological signals. Wavelet analysis breaks down brain signals, such as EEG or fMRI data, into various frequency components at different scales. Wavelet analysis provides time-frequency localization. Pattern recognition can be enhanced by isolating salient features in the data. Wavelet denoising can effectively separate noise from underlying brain signals. Wavelet denoising usually adopts threshold method. Wavelet analysis can enhance pattern recognition by isolating salient features in the data. Researchers can train machine learning models based on these wavelet-derived features to recognize specific patterns associated with different neurological disorders. Wavelet analysis can track these changes by continuously evaluating the frequency content of the neuroimage data over time. Through continuous efforts, wavelet theory and technology have become valuable tools in the field of neuroscience and brain disease research.

GNSS receivers are nowadays commonly used in monitoring applications, e.g., in estimating crustal and infrastructure deformations. This is basically due to the recent improvements in GNSS instruments and methodologies that allow high precision positioning, 24 h availability and semiautomatic data processing. In this paper, GNSS estimated deformations on a dam structure have been analyzed and compared with pendulum data. This study has been carried out for the Eleonora D’Arborea (Cantoniera) dam, which is in the Sardinia Island. Time series of pendulum and GNSS over a time span of 2.5 years have been aligned so to be comparable. Analytical models fitting these time series have been estimated and compared. Those models were able to properly fit pendulum data and GNSS data, with standard deviation of residuals smaller than one millimeter. This encouraging results led to the conclusion that GNSS technique can be profitably applied to dam monitoring allowing a denser description, both in space and time, of the dam displacements than the one based on pendulum observations.

Osteopontin (OPN)-CD44 signaling plays an important role in promoting tumor progression and metastasis. In cancer, OPN and CD44 overexpression is a marker of aggressive disease and poor prognosis, and correlates with therapy resistance. In this study, we aimed to evaluate the association of single nucleotide polymorphisms (SNPs) in the OPN and CD44 genes with clinical outcomes in 307 non-small cell lung cancer (NSCLC) patients treated with radiotherapy or chemoradiotherapy. The potential impact of the variants on plasma OPN levels was also inves-tigated. Multivariate analysis showed that OPN rs11730582 CC carriers had a significantly in-creased risk of death (p = 0.029), while the CD44 rs187116 A allele correlated with reduced risk of locoregional recurrence (p = 0.016) in the curative treatment subset. The rs11730582/rs187116 combination was associated with an elevated risk of metastasis in these patients (p = 0.016). Fur-thermore, the OPN rs1126772 G variant alone (p = 0.018) and in combination with rs11730582 CC (p = 7x10-5) was associated with poor OS in the squamous cell carcinoma subgroup. The rs11730582 CC, rs187116 GG and rs1126772 G, as well as their respective combinations, were in-dependent risk factors for unfavorable treatment outcomes. The impact of rs11730582-rs1126772 haplotypes on OS was also observed. These data suggest that OPN and CD44 germline variants may predict treatment effects in NSCLC.

Cytokines are mediators of inflammation that could lead to fibrosis. The aim was to monitor cytokine levels in saliva and serum after locally fractionated radiotherapy of the head and neck in mice and investigate associations with salivary gland fibrosis and hyposalivation. C57BL/6 mice were randomized to sham or X-ray irradiation of 66 Gy in 10 fractions over 5 days. Blood and saliva were collected on day -7, 5, 35, 80 and 105 with following cytokine analysis. The harvested submandibular salivary gland was assessed for presence of fibrosis. Decision tree regression analysis was used to investigate whether cytokine levels could predict late endpoints in terms of hyposalivation or fibrosis. Significant formation of fibrosis in gland tissue and reduced saliva production was found after irradiation. The pro-inflammatory cytokines IL-1α, TNF, TIMP1, G-CSF, KC and MIP-1α showed increased levels in saliva in irradiated mice and strong correlation with late endpoints. The decision tree analysis largely separated controls from irradiated animals with IL-1α being the strongest predictor. Pro-inflammatory cytokines in saliva, but not in serum, were associated with late endpoints. This indicates that cytokine expression in saliva is a good biomarker for local salivary gland damage with IL-1α as the strongest single predictor.

Currently, in a context of biorefinery and bioeconomy, lignocellulosic biomass is increasingly used to produce biofuels, biochemicals and value-added products. Microwaves and ultrasounds are emerging techniques that enable efficient and environmentally more sustainable routes in the transformation of lignocellulosic biomass. This review is divided into four parts. In Part I, the theoretical foundations of microwaves and ultrasounds are revisited. Dielectric constants for biomass, factors that influence pre-treatment, are some of the subjects addressed. In Part II, the effects that these technologies have on lignocellulosic biomass (on the size and surface area of the particle; on the content of lignin, hemicellulose and cellulose; on the crystallinity index of cellulose; on the effect of solubilization of organic matter; on hydrolysis and reduction of sugars) are analyzed. In Part III, emphasis is given on how microwaves and ultrasounds can contribute to the achievement of value-added products. In this context, several examples of liquefactions and extractions are presented. Part IV describes examples of sonocatalysis of lignocellulosic biomass to obtain value-added products such as for instancethe production of furfural, which is significantly reduced by ultrasound.

Medical image analysis is an important branch in the field of medicine, which mainly uses image processing and analysis techniques to interpret and diagnose medical image data. Medical image data helps doctors to effectively observe and diagnose patients' body structures, tissues and lesions. Medical image analysis has been an important research area in the medical field, and it is important for disease diagnosis, treatment planning, and condition monitoring. In recent years, the rapid development of deep learning and computer vision technologies has contributed greatly to the automation, multimodal data fusion, real-time application, and accuracy improvement of medical image analysis. In addition, the development of deep learning has given rise to some new research areas in medical image analysis, such as Generative Adversarial Networks (GANs) for synthetic medical images, self-supervised learning for unsupervised feature learning, and neural network interpretability. In this paper, we will introduce some optimisation methods for medical images which are effective in improving the accuracy, efficiency and reliability of medical image analysis.

In the face of escalating cybercriminal sophistication, an innovative approach to network anomaly detection has been pursued in this longitudinal study, integrating computational data analytics in a geographic, organizational, and behavioral context. A data-driven scoring mechanism was employed to systematically analyze and correlate source countries of IP addresses and organization-associated Autonomous System (AS) Numbers (ASN) with network anomalies. Significant correlations between certain countries, specific organizations, and high behavior scores were identified through the data analytics. An increase in connection requests was also found to be linked with elevated behavior scores. Validated by cross-validation techniques, these findings emphasize the necessity for continuous model recalibration. The transformative role of integrative data analytics in cybersecurity is underscored, paving the way for the development of more sophisticated, context-aware anomaly detection systems. Specifically, the analysis underscores the need for organizations to adopt a proactive and adaptive approach to cybersecurity that can keep pace with the evolving threat landscape.

Pain is frequently reported during cancer disease, and still remains poorly controlled in 40% of patients. Recent developments in oncology have helped to better control pain. Targeted treatments may cure cancer disease and significantly increase survival. Thereby, a novel population of patients (cancer survivors) has emerged, also enduring chronic pain (27.6% moderate to severe pain). The present review discuss the different options currently available to manage pain in (former) cancer patients in the light of progress made in the last decade. Major progress in the field are recent development of a chronic cancer pain taxonomy now included in International Classification of Diseases (ICD-11) and update of WHO analgesic ladder. Until recently, cancer pain management has mostly relied on pharmacotherapy, opioids being considered as mainstay. The opioids crisis has prompted the reassessment of opioids use, both in cancer patients and cancer survivors. The review focuses on the current utilization of opioids, on the neuropathic pain component often neglected and on techniques and non-pharmacological strategies available which help to personalize patient’s treatment. Cancer pain management is now closer to the management of chronic non-cancer pain i.e. “an integrative pain care” aiming to improve patient’s quality of life.

Alzheimer’s and Parkinson's diseases (AD and PD) are amongst top of the prevalent neurodegenerative disease. One-third of PD patients are diagnosed with dementia, a pre-symptom of AD, but the underlying mechanism is elusive. Amyloid beta (Aβ) and α-synuclein are two of the most investigated proteins, whose pathological aggregation and spreading are crucial to the pathogenesis of AD and PD, respectively. Transcriptomic studies of the mammalian central nervous system shed light on gene expression profiles at molecular levels, regarding the complexity of neuronal morphologies and electrophysiological inputs/outputs. In the last decade, the booming of the single-cell RNA sequencing technique helped to understand gene expression patterns, alternative splicing, novel transcripts, and signal pathways in the nervous system at single-cell levels, providing insight for molecular taxonomy and mechanistic targets of the degenerative nervous system. Here, we re-visited the cell-cell transmission mechanisms of Aβ and α-synuclein in medi-ating disease propagation, and summarized recent single-cell transcriptome sequencing from different perspectives and discussed its understanding of neurodegenerative diseases.

Breast and prostate cancer lead incidence rankings in Chile, with obesity and overweight as important risk factors involved in prognosis. Nutritional interventions have shown to be beneficial therapies in patients with cancer, improving anthropometric and biochemical measurements. This study investigates the feasibility and effectiveness of Calorie Restriction and Time-Restricted Feeding in overweight or obese patients undergoing curative radiotherapy for breast and prostate cancer. The research was conducted as a prospective, interventional, non-randomized clinical trial, involving 27 participants, of whom 23 completed the study. Findings indicate that both interventions are feasible and effective. Notably, Time-Restricted Feeding demonstrated superior adherence and more significant improvements in weight loss and metabolic parameters. A mean weight reduction of 3.6 kg and waist circumference decrease of 4.9 cm was observed across participants. Serum levels of glucose, insulin, LDL, HDL and TG showed an average reduction, indicating positive metabolic changes. Results suggest that Time-Restricted Feeding could be a superior beneficial dietary intervention for cancer patients undergoing radiotherapy, due to its ease of adherence and positive impact on metabolic health. This research contributes to the growing evidence on the role of nutritional interventions in cancer treatment and underscores the need for more extensive studies to validate these findings.

(1) Background: Treatment of male stress incontinence in patients with prostate cancer treated with radical prostatectomy and adjuvant pelvic radiation is a therapeutic challenge. The efficacy and safety of the adjustable trans-obturator male system (ATOMS) in these patients is not well established, despite the general belief that outcomes are worse than in patients without radiation. (2) Methods: Retrospective multicenter study evaluating patients treated with silicone-covered scrotal port (SSP) ATOMS implant after radical prostatectomy and radiotherapy in nine different institutions between 2016 and 2022. The primary endpoint was dry patient rate, defined as pad-test ≤20 mL/day. The secondary endpoints were complication rate (defined using Clavien-Dindo classification), device removal and self-perceived satisfaction using the Patient Global Impression of Improvement (PGI-I) scale. Wilcoxon rank sum test, Fisher’s exact test and logistic regression were performed using stepwise method with a 0.15 entry and 0.1 stay criteria. (3) Results: 223 patients fulfilled criteria for inclusion, 12 (5.4%) had received salvage prostatectomy after radiation and 27 (12.1%) previous devices for stress incontinence. After ATOMS adjustment, 95 patients (42.6%) were dry and 36 (16.1%) had complications of any grade (grade I, n=20; grade II, n=11; grade III, n=5) during the first 3 months postoperatively. At a mean 36 ± 21 months follow-up the device was explanted in 26 (11.7%) patients. Regarding self-perceived satisfaction with the implant, 105 of 125 patients (84%) considered themselves satisfied (PGI-I 1 to 3). In univariate analysis dryness was associated to younger age (p=.06), primary prostatectomy (p=.08), no previous incontinence surgery (p=.02), absence of overactive bladder symptoms (p=.04), absence of bladder neck stricture (p=.001), no need of surgical revision (p=.008) and lower baseline incontinence severity (p=.0003). Multivariate analysis identified absence of surgical revision (p=.018), absence of bladder neck stricture (p=.05), primary prostatectomy (p=.07) and baseline incontinence severity (p&lt;.0001) were independent predictors of dryness. A logistic regression model was proposed and internally validated. (4) Conclusions: ATOMS is an efficacious and safe alternative to treat male incontinence after radical prostatectomy and adjuvant radiotherapy. Factors predictive of dryness are identified in this complex scenario to allow better patient selection.

In the wake of increasing digital fraud, this paper introduces an innovative application of Artificial Intelligence (AI) in detecting fraudulent activities across finance, healthcare, and e-commerce sectors. It presents a detailed analysis of machine learning methodologies, specifically focusing on the advantages of supervised, unsupervised, and deep learning techniques. The paper addresses the challenges such as data imbalance, model interpretability, and ethical implications in AI-based fraud detection. It also discusses the necessity of high-quality datasets and advocates for the integration of traditional and advanced machine learning methods to enhance accuracy and adaptability in fraud identification. However, it acknowledges the limitations including computational demands and overfitting risks. The study underscores the importance of collaborative efforts between AI experts and industry professionals to develop ethical, efficient, and reliable AI solutions for fraud detection.

Abstract: Botnets pose a grave cybersecurity threat, enabling widescale malicious activities through networks of compromised devices. Detecting botnets is challenging given their frequent use of evasion techniques like encryption. Traditional signature-based methods fail against modern botnets capable of zero-day attacks. This paper surveys recent advances applying machine learning for botnet detection based on analysis of network traffic payloads, flows, DNS data, and hybrid feature fusion. Core machine learning models include support vector machines, neural networks, random forests, and deep learning architectures, which extract patterns to separate benign and botnet behaviors automatically. Results demonstrate machine learning's capabilities in identifying heterogeneous botnets using artefacts in network streams. However, challenges remain around limited labeled data, real-time streaming, adversarial evasion, and model interpretability. Promising directions involve semi-supervised learning, adversarial training, scalable analytics, and explainable AI to address these gaps. Beyond the technical aspects, responsible development and deployment of botnet detection systems raise ethical considerations around privacy, transparency, and accountability. With diligent cross-disciplinary collaboration, machine learning promises enhanced, generalizable, and trustworthy techniques to combat the serious threat posed by continuously evolving botnets across the digital ecosystem.

The study aimed to manage and to analyse the results of the laboratory tests, routinallypractice for hepatitis C diagnosis, using blood tests. Statistical analysis of this study results, was performed using the laboratory informatic system. The results of the study are substantial and intricate reffering to comparision between two methods concretlly ELISA method (Enzyme-Linked Immunosorbent Assay) and chemiluminescence methods and their results. Good to know our opinion that RT-PCR technique, it is considered proper for the diagnosis of HCV ( Hepatitis C virus).

Significant progress has made in pattern recognition technology. However, one obstacle that has not yet overcome is the recognition of words in the Brahmi script, specifically the recognition of characters, compound characters, and word because of complex structure. For this kind of complex pattern recognition problem, it is always difficult to decide which feature extraction and classifier would be the best choice. Moreover, it is also true that different feature extraction and classifiers offer complementary information about the patterns to be classified. Therefore, combining feature extraction and classifiers, in an intelligent way, can be beneficial compared to using any single feature extraction. This study proposed the combination of HOG +zonal density with SVM to recognize the Brahmi words. Keeping these facts in mind, in this paper, information provided by structural and statistical based features are combined using SVM classifier for script recognition (word-level) purpose from the Brahmi words images. Brahmi word dataset contains 6,475 and 536 images of Brahmi words of 170 classes for the training and testing, respectively, and the database is made freely available. The word samples from the mentioned database are classified based on the confidence scores provided by support vector machine (SVM) classifier while HOG and zonal density use to extract the features of Brahmi words. Maximum accuracy suggested by system is 95.17% which is better than previously suggested studies.

Layered superconductors are attractive because some of them show high critical temperatures. While their crystal structures are similar, those compounds are composed of many elements. Compounds with many elements tend to be incongruent melting compounds, thus, their single crystals cannot be grown via the melt-solidification process. Hence, these single crystals have to be grown below the decomposition temperature, and then the flux method, a very powerful tool for the growth of these single crystals with incongruent melting compounds, is used. This review shows the flux method for single-crystal growth technique by self-flux, chloride-based flux, and HPHT (high-pressure and high-temperature) flux method for many-layered superconductors: high-T_c cuprate, Fe-based and BiS₂-based compounds.

To get more data concerning the influence of fertilizers (organic and mineral) on different forage plants existing in North-eastern Romanian grassland, the mass fractions of 14 essential, enzymatic, or considerd toxic elements was determined by Instrumental Neutron Activation Analysis together with the amount of crude proteins, ash, fibres as well as ether fact extract. Final results showed a significant variance of the content of analysed elements on organic as well as on mineral fertilized experimental plots, i.e. the content increased in 24% of plots, decreased in 23%, and remained unchanged in 45% while in 8% of plots their content was below the detection limits, as the case of Se. At the same time, an increase content of crude protein and ether extract was evidenced in fertilized grasses for all applied fertilizers while other global indicators such as neutral and acid fibre of sufuric lignin content decreased, suggesting significant higher nutritional values of fertilized forage plant.

This paper explores the utilization of ensemble models and learning analytics techniques to predict student academic performance. With the advent of educational big data, institutions are increasingly leveraging advanced analytics to gain insights into student learning patterns and optimize educational outcomes. Ensemble models, which combine the predictive power of multiple algorithms, offer a robust approach to enhance prediction accuracy. The performance of the ensemble models was analyzed and compared using the Open University Learning Analytics Dataset, which consists of sources such as demographic information, historical performance data, and engagement metrics for 23,344 students. The evaluation of various ensemble models across different classification scenarios revealed that the proposed stacking model consistently emerges as the best-performing model, excelling in both multi-class and binary classification tasks.

Entropion is a condition characterized by the total or partial inversion of the eyelid margin, resulting in contact between the outer skin and the corneal or conjunctival surface, and sometimes both. This condition can affect various animals, including horses, pigs, goats, sheep, rabbits, felines, and particularly canines. It typically manifests in the lower lid's lateral portion but can affect any part of the lid. This contact between eyelashes or facial hair and the cornea or conjunctiva leads to severe irritation, causing self-inflicted trauma, as evidenced by clinical signs of pain, irritation, ulcerations, and vision loss. Entropion can be classified as primary (congenital or developmental) or secondary (spastic and scarring). Diagnosis relies on clinical signs, the animal's history, and its breed. It's essential to assess the degree of entropion in the dog without applying topical anesthesia. This study conducts a literature review on surgical techniques for correcting various types of entropion in canines.

Airborne virus, such as COVID-19, caused pandemics all over the world. Virus-containing particles produced by infected individuals are suspended in the air for extended periods of time, actually results in viral aerosols and the spread of infectious diseases. Aerosol collection and detection devices are essential for limiting the spread of airborne virus diseases. This review provides an overview of the primary mechanisms and enhancement techniques for collecting and detecting airborne viruses. Indoor virus detection strategies for scenarios with varying ventilations are also summarized based on the excellent performance of existing advanced comprehensive devices. This review provides guidance for the development of future aerosol detection devices and aids in the control of airborne transmission diseases, such as COVID-19, monkeypox, and other airborne transmission viruses.

The low water solubility of any pharmacoactive molecules limits their pharmacological potential but the solubility parameter cannot compromise, so different approaches are employed to enhance their bioavailability. Pharmaceutically active molecules with low solubility convey a higher risk of failure for drug innovation and development. Pharmacokinetics, pharmacodynamics, and several other parameters, such as drug distribution, protein binding and absorption, are majorly affected by their solubility. Among all pharmaceutical dosage forms, the oral dosage forms cover more than 50 %, and the drug molecule should be water-soluble. For good therapeutic activity by the drug molecule on the target site, solubility and bioavailability are crucial factors. The pharmaceutical industry screening programs identified that around 40% of new chemical entities (N.C.E.s) face various difficulties at the formulation and development step. These pharmaceuticals are attributed to their less solubility and bioavailability. The bioavailability and drug solubility enhancement are significant challenges in the area of pharmaceutical formulations. According to the Classification of Biopharmaceutics, Class II and IV drugs (APIs) exhibits poor solubility, lower bioavailability, and less dissolution. Various technologies are discussed in this article to improve the solubility of the poorly water-soluble drug, for example, complexation of active molecules, utilization of emulsion formation, micelles, microemulsions, cosolvents, polymeric micelles preparation, particle size reduction technologies, pharmaceutical salts, prodrugs, solid-state alternation technique, soft gel technology, drug nanocrystals, solid dispersion methods, crystal engineering techniques and nanomorph technology. This review mainly describes several other advanced methodologies for solubility and bioavailability enhancement, such as crystal engineering, micronization, solid dispersions, nano sizing, use of cyclodextrins, solid lipid nanoparticles, colloidal drug delivery systems and drug conjugates, by some appropriate research reports.

The main focus of this paper is to analyze and discuss the secure software development practices currently being adopted in the industry along with their significance, as well as to identify the challenges faced by developers when undertaking measures and techniques in writing secure software. It is a well-known fact that software security has been the top priority of many software companies such as Google and Facebook to thwart attackers and protect user data in this world full of cybercriminals. Understanding how most software companies in the industry operate to ensure security helps developers to identify strengths and weaknesses in their current security frameworks. Hence, by researching into previous literature and papers that are relevant to the topic and by conducting an interview with a professional in the field, this paper provides insights on the most popular secure software development framework and practices in the world as well as problems faced by companies when adopting these practices. Several security practices and activities that are required to create secure software are discovered alongside the problems that arise when companies are trying to apply these practices. This paper also proposes a few solutions that can be used to resolve these problems, which can be easily understood and implemented by software companies to transition into a truly secure software development environment.

Potato is a starchy, tuberous crop from the perennial Solanum tuberosum having high nutritional values. This paper is the first analytical approach to quantify Pt and Rh in vegetal food. In this study a total of 38 different potatoes samples produced in Europe and one in Australia were investigated. Determinations of Pt and Rh in potatoes samples were carried out by Differential Pulse Voltammetry (DPV/a) for platinum and by Adsorptive Stripping Voltammetry (AdSV) for Rh using standard addition procedure. Because no certified reference potatoes containing platinum and rhodium are available, we used addition standard method. The quantification limits for Pt and Rh are 0.007 and 0.0008 μg Kg−1 respectively. Considering all the potatoes samples, concentrations of Pt and Rh vary in the ranges from 0.007 to 109 μg Kg−1 (sample n° 6 potatoes grown in Sicily) and from 0.0008 to 0.030 μg Kg−1 (sample n°23 of potatoes grown in Emilia Romagna) respectively. For both metals, in many cases the concentrations fall near the quantification limit. In all the samples, platinum is always more abundant than rhodium and their ratio meanly is 14500, which is much greater than that of the earth's crust (about 100).

Byers Peninsula is considered one of the largest ice-free areas in Maritime Antarctica. Since 2006, the Spanish Polar Program has taken part in a large number of environmental studies involving effects of climate changes in lives cycles, limnology and microbiology. Soils from maritime Antarctica are generally weakly developed and have chemical, physical and morphological characteristics strongly influenced by the parent material. However, biological activity during the short Antarctic summer promotes intense transference of nutrients and organic matter in areas occupied by different species of birds and marine mammals. To mapping and monitoring those areas with high biological occupation, could be very useful to have models of edaphic properties prepared from satellite images. In this approach, Deep Learning and Linear Regression models of soil properties and spectral indexes as explicative variables were performed. We training models of soil properties closely related to biological activity such as Dissolved Organic Carbon (DOC) and the iron fraction associated with organic matter (Fe). We tested the best approach to model the spatial distribution of DOC, Fe and pH by training models of Linear Regression and Deep Learning over Sentinel2 and WorldView2 images. The most robust models were used to track possible areas with ornithogenic soils as well as areas of the Byers Peninsula that could support the highest biological development.

Aims. Bone metastases have an incidence of up to 75% in metastatic breast cancer, thanks to the evolution of imaging we can identify them in the oligometastatic phase. With the introduction of target therapies and increasingly effective conjugated antibodies, it is increasingly common to treat patients with radiotherapy although asymptomatic (if single or ≤5 bone lesions). Volumes and doses in this setting do not yet have a clear guidelines. In this study, the aim is to administer to the macroscopically evident disease an ablative dose that favors the local control of disease. Aim of this retrospective analysis is to evaluate the outcome of pts receiving SIB for treatment of bone metastases. Material and Methods. A retrospective analysis including mBC patients (pts) undergone RT on bone metastases was conducted for pts treated between January 2014 and January 2022. Primary endpoint was freedom from local progression (FFLP). Rate of disease progression after radiotherapy (DP-AR) and overall survival (OS) were secondary endpoints. Subgroup analysis (age, immunophenotype, line of therapy) were performed. Results. Among 954 mBC who underwent radiotherapy for metastases, 85 pts underwent SIB-IMRT with a boost on macroscopic lesion of 8-6 Gy in 5 fr. Mean follow up was 41 months (6-61.5 m). Nineteen pts had single bone metastase (22.4%), 20 pts were oligometastatic (23,5%), 46 pts were plurimetastatic (54,1%). FFLP was 17 months (95% CI 3.2-61.5 m). Only 6 pts (7%) had local relapse on SIB-IMRT site during follow up. DP-AR was 13,2 m (95% CI 3.1-56.9 m). OS was 82,7 m (95% CI 10.6-343 m). Local-relapse was not associated with age, immunophenotype or sistemic line ongoing. Among secondary outcomes, DP-AR resulted associated to immunophenotype (p 0.002). DP-AR and OS were not significantly associated with local relapse (respectively p 0.148 and p 0.4). Conclusions. Pts with breast tumor can be treated with SIB-IMRT on bone metastases with a 93% of local control at 17 months from radiotherapy. Further data are needed to individuate pts who can benefit of dose-escalation and also sinergic effect with systemic therapies to possibly increase DP-AR.

The clinical significance of carbon-ion radiotherapy (CIRT) for adenocarcinoma (AC) of the uterine cervix has been assessed in several single-institutional studies. To validate the significance, we conducted a multi-institutional survey of CIRT for locally advanced AC (LAAC) of the uterine cervix. We retrospectively analyzed the clinical outcomes of patients with stage IIB–IVA LAAC of the uterine cervix who underwent chemo-CIRT or CIRT alone between April 2010 and April 2016. Patients received 74.4 Gy (relative biological effectiveness [RBE]) in 20 fractions of CIRT or 55.2 Gy (RBE) in 16 fractions of CIRT plus 3 sessions of brachytherapy. Patients aged ≤70 years with adequate bone marrow and organ function were administered cisplatin weekly (40 mg/m2 per week for up to 5 weeks). Fifty-five patients were enrolled in this study. The median follow-up period was 67.5 months. The 5-year overall survival (OS) and local control (LC) rates were 68.6% and 65.2%, respectively. Multivariate analysis showed that the initial tumor response within 6 months was significantly associated with LC and OS. The present study represents promising outcomes of CIRT or chemo-CIRT for LAAC of the uterine cervix, especially in the cases showing initial rapid regression of the tumor.

Background: In trials using normofractionated regimen, the radiation-induced lymphocyte apoptosis (RILA) and the chromosomal damage assays (CDA) have shown prognostic roles of radiation-induced adverse events. The main objectives here were to validate RILA and CDA in extreme and moderate hypofractionation regimens for breast (FAST) and prostate (CHHiP) cancers. Methods: Blood samples were collected from 400 volunteers included in FAST and CHHiP trials. The primary endpoints (PE) were first change in photographic breast appearance and first grade ≥2 RTOG bladder or bowel toxicity (BBT) in FAST and CHHiP, respectively. The secondary endpoints was first grade ≥2 breast clinical changes (BCC) in FAST and BBT using different scales in CHHiP. Results: 103 FAST and 297 CHHiP patients with lab and clinical data were included. In FAST trial, no significant association of RILA with the primary endpoint was observed. A significant association of higher RILA levels with lower risk of any RIAE was found. The risk of developing grade ≥2 RIAE decreased significantly for patients with RILA≥24% compared to those with RILA≤16% with a HR of 0.50 (95%CI 0.25-1.00, p=0.012). Concerning chromosomic aberrations, no significant associations were found with change in photographic breast appearance nor with the secondary endpoint of any RIAE. In CHHiP trial, a decreased risk of grade≥2 RTOG bladder or bowel RIAE was observed for increasing values of RILA (HR 0.97, 95%CI 0.94-1.01, p=0.11) but did not reach statistical significance. Concerning chromosomic aberrations, we found significant association of higher levels of micronuclei per cell with lower risk of gr2+ RTOGAE (p=0.021 for trend test across tertiles; p=0.023 for upper vs lower tertile). Conclusions: This study is the first to evaluate RILA and CDA as predictors of late effects after breast and prostate RT in the “hypofractionation” era. Development of toxicity biomarkers whatever the RT fractionation are urgently needed.

This literature review investigates the importance of simulation and measurement techniques in the development of transmission lines and antennas, which are crucial to the reliability and efficiency of communication system. It emphasizes the necessity of exact measurement and computational approaches for simulating complicated electromagnetic process, which help to optimize designs before physical prototypes are built. The review examines a variety of research articles that offer innovative solutions to improving accuracy in antenna design, scalability and cost challenges in antenna measurements, and crosstalk measurement methods. It also explores how these methodologies affect antenna design parameters such as gain, bandwidth, and radiation patterns, emphasizing the importance of correct modeling to ensure the performance of transmission lines and antennas in modern communication system. The review serves as a valuable reference for guiding future research and technological advancements in these fields.

Studies have found critical software malfunctions responsible for some of the worst accidents in recent times. These malfunctions are often only minor defects that snowball into large problems; a few lines of code is all it takes. Complexity, safety, quality, and resilience are among the key attributes defining a software’s operational success. There are many leading factors for complexity, such as increases in the product size, the rate of requirement changes, and the number and type of stakeholders, and failure to manage these issues efficiently always has the same consequence, i.e., massive failure and sometimes technological catastrophe. This work analyzes some of the architecture, design, and implementation guidelines used as detection and mitigation techniques. It also discusses the safety considerations, as considering how the steam industry has handled safety issues could offer some guidance for ensuring safety. Complexity in such systems also causes some of the worst side effects from the quality auditor's perspective. While failures in the software are hard to predict, one of the most significant ways of showing preparedness is practicing software resilience. New mitigation areas, such as the fragility spectrum and failure obviation, and their usage for building a safer system are analyzed. Also discussed are various architecture styles in practice and the dramatic effect human factors can have on the success of the software being developed.