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Abstract This study investigates mechanical properties, durability performance, non-destructive testing (NDT) characteristics, environmental impact evaluation, and advanced machine learning (ML) modelling techniques employed in the analysis of high-strength self-compacting concrete (HSSCC) incorporating varying supplementary cementitious materials (SCMs) to develop sustainable building construction. The findings from the fresh characteristics test indicate that mixes’ optimal flowability and passing qualities can be achieved using different concentrations of marble powder (MP) alongside a consistent amount of silica fume (SF) and fly ash (FA). Moreover, the incorporation of 10% MP along with 10% FA and 20% SF in HSSCC significantly improved the compressive strength by 14.68%, while the splitting tensile strength increased by 15.59% compared to the reference mix at 56 days. While random forest (RF), gradient boosting (GB), and their ensemble models exhibit strong coefficient correlation (R2) values, the GB model demonstrates more precision, indicating reliable predicted outcomes of the mechanical properties. Following subsequent testing, it has been demonstrated that incorporating SCMs improves the NDT properties of HSSCC and enhances its durability. The finer MP, SF, and FA particles enhanced microstructural performance by minimizing voids and cracks while improving the C–H–S bond. As noticed by its lower CO2-eq per MPa for SCMs, the HSSCC mix with up to 15% MP inclusion increased mechanical strength while reducing the environmental footprint, making it an eco-friendly concrete alternative.

This paper examines the impact of Industry 4.0 on organizational communication, exploring the opportunities and challenges presented by this revolutionary paradigm shift. The study employs a qualitative research methodology, drawing on academic literature, case studies, and in-depth interviews with national and international organizations. By evaluating the importance of effective communication in the Internet of Things (IoT) era, the paper assesses the opportunities and identifies the challenges of Industry 4.0 in organizational communication. The study delves into the complex relationship between technology and communication, outlining best practices for implementing communication tools and artificial intelligence (AI) in Industry 4.0. Effective communication is crucial for success in Industry 4.0, as it enables individuals to collaborate effectively and share ideas, leading to improved decision-making and problem-solving. However, information overload, miscommunication, and isolation risks must be mitigated to ensure effective communication. Investing in employee training and development, establishing clear communication protocols, and balancing virtual and face-to-face communication can help organizations manage these risks effectively. Mitigating the risks associated with organizational communication in Industry 4.0 is crucial to ensure that organizations can successfully leverage the opportunities presented by this era of digitalization. Recommendations include adopting cybersecurity measures, streamlining communication processes, protecting personal information, ensuring clarity and transparency, regularly updating data security measures, and promoting inclusive communication to overcome social barriers and ensure sustainable organizational communication.

Since the world's population is rising continuously, more cultivable land is being utilized for their dwellings. As a result, the amount of food supply is decreasing day by day. In order to address the food shortage, a proper plan and technological breakthroughs is must. Tomato is a kind of vegetable which has the healthy ingredients and essential for our daily food list. The proposed system suggests an IoT based tomato cultivation and pest management system, with the help of deep learning methods. In the IoT implementation, camera module and moisture sensor are used to collect images of tomato plant, soil condition respectively. Based on the moisture content, the water pump will supply the water when it necessary. Besides, the real-time images of tomato leaf will be sent to the server to identify and classify natural enemies like various insect species. In the proposed system seven types of pests are identified with the help of ten deep learning models like InceptionV3, Xception, InceptionResNetV2, MobileNet, MobileNetV2, MobileNetV3Large, MobileNetV3Small, DenseNet121, DenseNet169, DenseNet201. This study has trained with leaves and insects separately to identify whether an image from a tomato plant is insectoid or not. 458 images of pests and 912 images of leaves are utilized in the proposed architecture. The accuracy of classifying insects or leaves using DenseNet201 is 100 ​%. The highest accuracy of 94 ​% is obtained to classify the different insects using the DenseNet201 model.

ObjectiveThis study aims to clinically and genetically assess 30 unrelated consanguineous Pakistani families from various ethnic backgrounds, all exhibiting features of neurodevelopmental disorders (NDDs).MethodsWe conducted clinical, genetic, biochemical, and molecular analyses on 30 consanguineous families with NDDs enrolled from various regions of Pakistan. The likely molecular causes of primary microcephaly and NDDs were identified. Detailed clinical investigations and molecular diagnoses were performed using whole exome sequencing (WES) of the proband, followed by Sanger sequencing for validation and segregation in the available family members of the affected families.ResultsWES identified likely disease-causing homozygous variants in 30 unrelated consanguineous families. Six families presented newly described variants in known NDD-related genes: ABAT (c.1439 T > G; p.Phe480Cys) [OMIM613163], SLC12A6 (c.2865_2865insT; p.Glu955Asnfs*5) [OMIM 218000], SHANK3 (c.1305-3_1,305-2delTT; p.Gln29-_Gly305del) [OMIM 606232], BCKDK (c.356_356insC; p.Gly119Alafs*24) [OMIM 614923], DDHD2 (c.2065G > T; p.Asp689Tyr) [OMIM 615033], ERCC2 (c.1255G > A; p.Glu419Lys) [OMIM 610756]. Additionally, 12 families had previously reported disease-causing variants associated with different types of NDDs: ATRX (c.109C > T; p.Arg37*) [OMIM 309580], GPR56 [ADGRG1] (c.1423C > T; p.Arg475*) [OMIM 606854], NAGLU (c.1694G > A; p.Arg565Gln) [OMIM 252920], DOLK (c.3G > A; p.Met1Ile) [OMIM 610768], GPT2 (c.815C > T; p.Ser272Leu) [OMIM 616281], DYNC1I2 (c.607 + 1G > A; p.?) [OMIM 618492], FBXL3 (c.885delT; p.Leu295Phefs25*) [OMIM 606220], LINGO1 (c.869G > A; p.Arg290His) [OMIM 618103], and ASPM (c.3978G > A; Trp1326*, c.9557C > G; p.Ser3186*, c.6994C > T; p.Arg2332*) [OMIM 608716]. All the identified variants showed segregation compatible with autosomal recessive inheritance.ConclusionIn the present study, we observed a high frequency of ASPM variants in the genetic analysis of 30 consanguineous families exhibiting features of NDDs, particularly those associated with autosomal recessive primary microcephaly. These findings contribute to studies on genotype–phenotype correlation, genetic counseling for families, and a deeper understanding of human brain function and development.

The innovative utilization of sugarcane bagasse ash (SCBA) in producing lightweight concrete (LWC) needs to be explored experimentally and quantification with machine learning approaches. Therefore, this study aims to investigate fresh, mechanical and microstructural characteristics and machine learning modeling of incorporating SCBA as a partial substitute of cement. In this investigation, OPC was replaced partially by the weight of SCBA in the proportion of 0 %, 5 %, 10 %, 15 %, and 20 %. The influences of SCBA on the fresh characteristics of concrete were investigated through tests of the slump, compacting factor, Kelly ball, k-slump, density, and air content. In addition, for hardened properties compressive, splitting tensile, flexural strength, and static modulus of elasticity were tested at 7 and 28 days. Furthermore, a microstructural characteristic was carried out for varying content of SCBA. Different machine learning (ML) predictive models were performed utilizing artificial neural network (ANN) and random forest (RF), to predict the fresh and mechanical attributes of the LWC. It was noticed that the workability value of fresh concrete was enhanced almost by 40 % to 50 % with the incorporation of SCBA content. The hardened test results revealed that a mixture having SCBA up to 10 % content SCBA resulted in nearly 10 % to 30 % better performance to satisfy the requirement of LWC. Regarding the sustainability assessment, the less embodied CO2 (eCO2) is produced in SCBA mixes, whereas it is also economically beneficial to produce SCBA mixes. Models' efficacy was evaluated including mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination (R2). The maximum R2 and minimum RMSE came across for RF (0.989 and 1.393, respectively) which provides the well estimation of the model.

Abstract Multi‐walled carbon nanotubes (MWCNTs) were successfully synthesized and functionalized by chemical vapour deposition and acid reflux methods, respectively. Chitosan (CTS) was prepared by a chemical extraction method from waste prawn shells. Various weight fractions of functionalized multi‐walled carbon nanotubes (f‐MWCNTs) have been used as reinforcing agent in CTS biopolymer matrix. Fourier transform infrared spectroscopy analysis was done, which confirms the presence of absorption bands of the various functional groups of chitin, CTS, and MWCNTs. Raman spectra revealed the quality of MWCNTs, the extent of their functionalization, and the quality of nanocomposites. The X‐ray diffraction analysis showed the distinctive peaks for f‐MWCNTs’ and also revealed the formation of CTS/f‐MWCNTs nanocomposites. Transmission Electron Microscopy (TEM) analysis also exhibited that the CTS/f‐MWCNTs nanoparticles have a well‐defined crystalline structure. The highest coercivity and magnetization (Ms) of the CTS/5%f‐MWCNTs nanocomposite are 602 Oe and 0.1202 emu/g, respectively that have been enhanced by 3.83 and 5.27 times compared to the pure CTS respectively. It showed that the conductivity is getting higher with the addition of f‐MWCNTs in the CTS matrix. CTS/5% f‐MWCNTs composites exhibit the highest conductivity than other composites and the conductivity of CTS/5% f‐MWCNTs composite is 4.0×10−4 S/m.

This research aims to assess the rheological and mechanical characteristics of Self-compacting concrete (SCC) incorporating waste tire rubber aggregates (WRTA) as an interim substitute for coarse aggregates. However, the standard experimental modeling approach has significant obstacles when it comes to overcoming the nonlinearity and environmental susceptibility of concrete parts. Therefore, linear regression (LR) and extreme gradient boosting (XGBoost) were used as two standard single machine learning (ML) models to predict the aforementioned rubberized SCC features. In this study, conventional coarse aggregates were supplanted with WRTA at 0%, 5%, 10%, and 20% to uncover the optimal proportion of coarse aggregates substituting rubber. To find the optimum amount of WRTA to use as a substitute, the study follows the impacts of rubber on the self-compacting rubberized concrete's (SCRC) rheological and mechanical characteristics. The consequences on fresh properties were investigated by the slump flow, J-ring, and V-funnel tests, while compressive and splitting tensile strengths tests were conducted to assess mechanical properties. Increasing WRTA test outputs indicated a deterioration in workability and hardened qualities. While a 10% swapping ratio is deemed feasible for producing SCRC, optimal results were achieved by reducing environmental impacts and efficiently managing a significant volume of rubber tire waste with a 5% substitution of rubber within the coarse aggregates. The research findings indicated a noticeable decrease in fresh properties as the WRTA content increased. Notably, after 28 days, a 10% WRTA substitution led to a 34% reduction in compressive strength and a 28% decrease in splitting tensile strength, satisfying ACI standards. Furthermore, XGBoost demonstrated superior predictive performance with the highest R2 values, outperforming the LR model and affirming its efficacy in delivering more accurate predictions.

Soft robotic manipulators consisting of serially stacked segments combine actuation and structure in an integrated design. This design can be miniaturised while providing suitable actuation for potential applications that may include endoluminal surgery and inspections in confined environments. The control of these robots, however, remains challenging, due to the difficulty in accurately modelling the robots, in coping with their redundancies, and in solving their full inverse kinematics. In this work, we explore a hybrid approach to control serial soft robotic manipulators that combines machine learning (ML) to estimate the inverse kinematics with closed-loop control to compensate for the remaining errors. For the ML part, we compare various approaches, including both kernel-based learning and more general neural networks. We validate the selected ML model experimentally. For the closed-loop control part, we first explore Jacobian formulations using both synthetic models and numerical approximations from experimental data. We then implement integral control actions using both these Jacobians, and evaluate them experimentally. In an experimental validation, we demonstrate that the hybrid control approach achieves setpoint regulation in a robot with six inputs and four outputs.

Sustainable practices in the construction sector have become a major issue due to the overuse of natural raw materials. Industrial by-products like fly ash (FA), silica fume (SF), and marble powder (MP) incorporation in concrete production will be assessed in this paper in terms of fresh, mechanical, and microstructural states. Consequently, this study proposes an in-depth investigation of SCMs applied with varied substitute cement amounts, looking at components like MP, SF, and FA. The impacts on fresh characteristics of HSSCC were assessed using slump flow, V-funnel time, T50 time, L-box ratio, and J-ring slump flow. Compressive, flexural, and splitting tensile strength tests were performed to analyze the mechanical properties. Energy-dispersive X-ray spectroscopy (EDS) and scanning electron microscope (SEM) techniques were used for the microstructural examination of HSSCC. It has been found that SCMs, including MP, FA, and SF, may enhance the characteristics of concrete. The slump flow values, which indicate the flowability and filling ability of HSSCC, were improved by a maximum of 9.6 % for 20 % SF and 10 % for both FA and MP replacement. The most promising outcomes on the basis of mechanical operation were gained by using SF, MP, and FA in HSSCC at respective percentages of 20 %, 10 %, and 10 %. This mixture revealed an increase in compressive strength of a maximum of 15 % at 56 days compared to the control mixture, which contained 10 % MP. However, the excessive addition of MP negatively impacted the strength of the concrete. The EDS examination illustrated that the ‘Ca’ to ‘Si’ proportion in HSSCC significantly affects the emergence of strength. This study will enlighten users during the preparation of high-strength self-compacting concrete (HSSCC) by replacing ordinary Portland cement (OPC) with different available supplementary cementitious material (SCM) combinations.

OBJECTIVES/GOALS: Full Spectrum Town Halls (FSTH) were organized to bring together patients, scientists, clinicians, advocates and others interested in Hidradenitis Suppurative (HS) – stakeholders across the spectrum of translational research – to infuse patient experiences and voices into designing HS research METHODS/STUDY POPULATION: The Rockefeller University (RU), Clinical Directors Network (CDN), and the HS Foundation organized three hybrid in-person/online HS FSTHs (2018-2023). The 2018 event focused on patients, describing the current state of HS knowledge and new research into HS biology (T2, T3). Patients shared lived experiences in testimonials and a panel discussion. Advocates described community and mental health resources (T4). The 2021 event returned research results (T2, T3) to the community and updates about treatments in the pipeline (T4). The 2023 FSTH targeted clinicians (T4) addressing a critical translational gap in HS care and presenting best practices in diagnosis, surgical, and medical treatments. RESULTS/ANTICIPATED RESULTS: Impact on science: FSTH attendees joined a Community Engagement Studio providing feedback used to refine study variables/procedures. Attendees joined research studies that advanced understanding HS mechanisms of disease, clinical course and treatment.Impact on patient experience: Participants appreciated having a forum to hear/share experiences of shame, mistrust, misdiagnosis and hope. Feedback improved practices for privacy, consenting, and returning study results. Impact on clinical practice and care: FSTH raised awareness of stigma, need for respect and empathy, and advanced learning about in disease mechanisms, effective biologics, importance of epithelial tunnels and surgical care. DISCUSSION/SIGNIFICANCE: HS is a stigmatizing, poorly understood disease. FSTHs fostered bidirectional learning among scientists, clinicians, patients and other stakeholders. Patients engaged with researchers to improve research design and participate in mechanistic and therapeutic clinical research, advancing the field.

Rising natural resource consumption leads to increased hazardous gas emissions, necessitating the concrete industry's focus on sustainable alternatives like palm oil fuel ash (POFA) to replace cement. Also, advanced machine learning (ML) techniques can uncover previously unreported insights about the effects of POFA that may be missing from the literature. Hence, this study investigates the influence of varying concentrations of POFA on fresh and mechanical characteristics with quantifying ML approaches and microstructural performance, as well as the environmental impact of structural concrete. For this, cement substitutions of 5 %, 15 %, 25 %, 35 %, and 45 % (by weight of cement) were utilized. POFA enhanced the overall concrete workability, with slump increments ranging from approximately 9 %–55 % and compacting factor increments of 4 %–12 %. Mechanical performance of POFA concrete improved up to 25 % replacement levels, with the highest enhancements observed in compressive (4.5 %), splitting tensile (36 %), and flexural (31 %) strength, for the mix containing 15 % POFA. The finer particle size of POFA improved microstructural performance by reducing porosity, aligning with the enhanced mechanical strength. The environmental impact of POFA was assessed by measuring eCO2 emissions, revealing a potential reduction of up to 44 %. Incorporating 5 %–15 % POFA yielded ideal mechanical performance results, significantly enhancing sustainability and cost-effectiveness. Regarding the ML approach, it can be observed that a low regression coefficient (R2) contrasts sharply with the higher R2 values for the random forest (RF) and the ensemble model, indicating satisfactory precision prediction with experimental results.

Rapid urbanization creates a demand to expand the cities where using pile foundation became a recurrent practice. To ensure sustainability of projects pile load tests are important but may not be always feasible in terms of costing, on-site constrains etc. In this circumstance numerical analysis is a good alternate to estimate precise pile load capacity rather than conventional conservative approaches. This research illustrates the pile group efficiency fluctuation due to pile diameter, spacing, pile number and orientation in prescribed sandy soils. Using the conventional method the individual pile capacities are calculated for a constant depth with variable diameters and soil profiles. For simulating the piles, geometric models of sandy soils with sufficient boundaries are generated in PLAXIS 3D FOUNDATION software where the parameters of pile and soil components are considered as per predetermined values from reliable references. The analysis results have thoroughly been scrutinized by plotting several graphs at different aspects. The outcomes indicate that the conventional pile spacing i.e. 2.5D to 3.5D has an insignificant effect on pile group efficiency, irrespective to pile diameter and soil type. It also exhibits that the increment of pile number significantly decreases pile group efficiency for diameters of 600mm, 800mm, 1000mm and 1200mm in sandy soils. With a few exceptions as the diameter of the pile increases, the group efficiency decreases. The arrangement of piles in group has minor impact on pile group efficiency which enhances onsite flexibility. It is expected that these outcomes will facilitate the practicing engineers for efficient solutions.

Bearings are critical components in modern manufacturing, yet they are prone to failures in induction machines. Detecting these faults early can reduce repair costs. To achieve efficient and accurate fault detection, we explore vibration-based analysis. Traditional methods rely on manual feature extraction, which is time-consuming. In contrast, our work leverages deep learning, particularly convolutional neural networks, to automatically extract fault features from raw data. We investigate various image sizes (16 × 16, 32 × 32, 64 × 64, 128 × 128, 256 × 256) and their performance in bearing fault diagnosis. Our convolutional neural networks-based approach is compared to traditional methods such as support vector machine, nearest neighbors, and artificial neural networks. Results demonstrate the superior performance of our data-driven fault diagnosis using convolutional neural networks.

Smart home is a habitation that has been outfitted with technological solutions that are intended to provide people with services that are suited to their needs. The purpose of this article is to perform a systematic assessment of the latest smart home literature and to conduct a survey of research and development conducted in this field. In addition to presenting a complete picture of the current smart home system’s (SHS) development and characteristics, this paper provides a deep insight into latest hardware and trends. The research then moves on to a detailed discussion of some of the important services provided by the SHS and its advantages. The paper also statistically discusses the current and future research trends in the SHS, followed by a detailed portrayal of the difficulties and roadblocks in implementing them. The comprehensive overview of the SHS presented in this paper will help designers, researchers, funding agencies, and policymakers have a bird’s-eye view of the overall concept, attributes, technological aspects, and features of modern SHSs.

In this article, we propose a variational approach for fusion of two coregistered high-resolution panchromatic (HRP) and low-resolution multispectral (LRM) images to reach the high-resolution multispectral (HRM) one, i.e., pan-sharpening. In this fusion technique, there is a tradeoff between structural information of an HRP image and spectral information of LRM one. To reconstruct the HRM image, which benefits from the best characteristics of both images, we consider several fidelity terms. The structural fidelity term is used to transfer structural information of an HRP image to HRM one, and a spectral fidelity term is utilized to preserve spectral consistency between HRM and LRM images throughout the fusion process. To reduce the spectral distortion occurred due to the discrepancy between intensity values of HRP and LRM images, a novel spatial-spectral fidelity term is designed to keep the intensity ratio between multispectral and panchromatic pixels in the high-resolution space as the same as the low-resolution space. Moreover, the total variation (TV) regularization term is employed as a prior to promote the sparseness of gradient in HRM bands. These fidelity terms were formulated in a convex optimization problem. However, the structural and TV terms made this optimization problem nondifferentiable. Therefore, we developed an efficient majorization-minimization algorithm for solving the optimization problem. The proposed method applied to three datasets, acquired by WorldView-3, Deimos-2, and QuickBird satellites. To assess the effectiveness of the proposed method, visual analysis, as well as quantitative comparison to various pan-sharpening methods, was carried out. The experimental results suggested that the proposed method outperformed the competitors visually and quantitatively.

INTRODUCTION: Chronic Kidney Disease refers to the slow, progressive deterioration of kidney functions. However, the impairment is irreversible and imperceptible up until the disease reaches one of the later stages, demanding early detection and initiation of treatment in order to ensure a good prognosis and prolonged life. In this aspect, machine learning algorithms have proven to be promising, and points towards the future of disease diagnosis. OBJECTIVES: We aim to apply different machine learning algorithms for the purpose of assessing and comparing their accuracies and other performance parameters for the detection of chronic kidney disease. METHODS: The ‘chronic kidney disease dataset’ from the machine learning repository of University of California, Irvine, has been harnessed, and eight supervised machine learning models have been developed by utilizing the python programming language for the detection of the disease. RESULTS: A comparative analysis is portrayed among eight machine learning models by evaluating different performance parameters like accuracy, precision, sensitivity, F1 score and ROC-AUC. Among the models, Random Forest displayed the highest accuracy of 99.75%. CONCLUSION: We observed that machine learning algorithms can contribute significantly to the domain of predictive analysis of chronic kidney disease, and can assist in developing a robust computer-aided diagnosis system to aid the healthcare professionals in treating the patients properly and efficiently.

Background: Smartphone and social media use are an integral part of our daily life. Currently, the impact of excessive smartphone and social media use during the COVID-19 pandemic is poorly understood. The present study aimed to investigate problematic smartphone use (PSPU) and problematic social media use (PSMU) among Bangladeshi college and university students during the COVID-19 pandemic.Methods: A cross-sectional study was carried out involving 5,511 Bangladeshi college and university students (male: 58.9%; mean age: 21.2 years [SD = 1.7]; age range: 18–25) during the social-distancing in the COVID-19 pandemic (July 2020). A self-reported survey containing questions regarding socio-demographic, lifestyle, and home quarantine activities along with four psychometric scales was completed by participants.Results: The mean scores of PSPU and PSMU were 20.8 ± 6.8 (out of 36) and 14.7 ± 4.8 (out of 30). Based on a hierarchical regression analysis, PSPU and PSMU were positively associated with lower age, poor sleep, social media use, watching television, anxiety, and depression. Additionally, PSMU was linked to being female, living with nuclear family, having urban residence, irregular physical exercise, poor engagement with academic studies, and avoiding earning activities, whilst being male, being married, living with lower-income family, and alcohol consumption were linked to PSMU.Conclusions: The findings indicate that PSPU and PSMU were linked to poor psychological well-being (i.e., anxiety and depression) and other factors (especially lower age, poor sleep) during the pandemic, further suggesting the need for interventions including virtual awareness programs among college and university students.

Advancement in electricity is the key ingredient that can actively take part in alleviating poverty and drastically improve the socio-economic status of the people of Bangladesh. The incorporation of renewable energy sources would help the country meet the energy requirement as well as contribute positively towards building a sustainable planet. The paper has extensively discussed the potential aspects of renewable energy resources in Bangladesh and how the Internet of Things can facilitate the implementation of intermittent sources. The regulatory and socio-economic aspects of the renewable energy industry have been explored and sustainable solutions will be discussed to fast-track the process of integrating various renewable energy sources in the power grid to meet the energy demand. The paper discusses the challenges associated with the RE integration in Bangladesh’s power mix and tries to mitigate it through the IoT. Besides that, an RE map for Bangladesh along with prospective power network has also been discussed in this work.

Attraction of Ephestia cautella (Walker) moths towards some food sources (date, wheat flour, wheat bran, peanut seeds and peanut shells) was tested in olfactometer (choice-test). The most favorite food for both male and female moths was date, followed by wheat flour, peanut seeds, wheat bran and peanut shells. Attraction of E. cautella male and female moths towards the extracted odours of the tested food was studied. The most attractive extracted food odour to E. cautella male and mated female moths was date (34 and 58%), respectively, at 0.1 ml concentration. Wheat flour odour had moderate attractant activity (30 and 44%), respectively, at 0.1 ml concentration. Peanut seeds odour had also moderate attractant activity (24 and 38%) at 0.02 ml concentration. In the olfactometer, wheat bran odour was the least attractive odour to E. cautella females, while, it was insignificant attractive response to the male moths. Neither males nor females were significantly attracted to peanut shells odour. [ABSTRACT FROM AUTHOR]

In the present study, the design and synthesis of novel coumarin derivatives 8a-h, 11a-d and 16a-c as potential selective inhibitors for the tumor associated human carbonic anhydrase isoforms (hCA IX and XII) was reported. All the newly synthesized derivatives showed potent to mild activity against the targeted CA IX (K I  = 0.08-9.57 µM), with selectivity indices over CA I (SI = 2.0-21.9) and over CA II (SI = 1.1-15.7). They showed similar activities against CA XII (K I  = 0.06-9.48 µM) with selectivity indices over CA I (SI = 1.4-21.2) and CA II (SI = 0.9-15.5). Compound 16b featuring sulfonamide function possessed promising inhibitory activities against the targeted isoforms CA IX and XII with K I values of 0.08 and 0.06 µM, respectively. Interestingly, it was found that using compound 16b at a nontoxic concentration as an adjuvant with Doxorubicin against MCF-7 cells enhanced the cytotoxicity under hypoxia by almost 3.5 folds; IC 50 decreased from 25.74 to 7.43 µM. Therefore, compound 16b restored the cytotoxicity of Doxorubicin against MCF-7 cells under hypoxia, almost as normoxia. Furthermore, flow cytometry analysis of a combination treatment of compound 16b and Doxorubicin to the MCF7 cell line revealed an increase in cell cycle arrest at the G2/M phase and a more efficient apoptotic effect than Doxorubicin alone. Furthermore, compound 16b showed no cytotoxicity against normal breast MCF-10A cell line (IC 50  = 296.25 µM)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Diabetes mellitus is a chronic metabolic disorder characterized by improper expression/function of a number of key enzymes that can be regarded as targets for anti-diabetic drug design. Herein, we report the design, synthesis, and biological assessment of two series of thiazolidinone-based sulfonamides 4a-l and 5a-c as multitarget directed ligands (MTDLs) with potential anti-diabetic activity through targeting the enzymes: α-glucosidase and human carbonic anhydrase (hCA) II. The synthesized sulfonamides were evaluated for their inhibitory activity against α-glucosidase where most of the compounds showed good to potent activities. Compounds 4d and 4e showed potent inhibitory activities (IC 50  = 0.440 and 0.3456 μM), comparable with that of the positive control (acarbose; IC 50  = 0.420 μM). All the synthesized derivatives were also tested for their inhibitory activities against hCA I, II, IX, and XII. They exhibited different levels of inhibition against these isoforms. Compound 4d outstood as the most potent one against hCA II with Ki equals to 7.0 nM, more potent than the reference standard (acetazolamide; Ki = 12.0 nM). In silico studies for the most active compounds within the active sites of α-glucosidase and hCA II revealed good binding modes that can explain their biological activities. MM-GBSA refinements and molecular dynamic simulations were performed on the top-ranking docking pose of the most potent compound 4d to confirm the formation of stable complex with both targets. Compound 4d was screened for its in vivo antihyperglycemic efficacy by using the oral glucose tolerance test. Compound 4d decreased blood glucose level to 217 mg/dl, better than the standard acarbose (234 mg/dl). Hence, this revealed its synergistic mode of action on post prandial hyperglycemia and hepatic gluconeogenesis. Thus, these benzenesulfonamide thiazolidinone hybrids could be considered as promising multi-target candidates for the treatment of type II diabetes mellitus., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Masson SAS. All rights reserved.)

Four new series 7a-e, 8a-e, 9a-e, and 10a-e of 7-aryl-3-substituted pyrazolo[1,5-a]pyrimidines were synthesized and tested for their RTK and STK inhibitory activity. Compound 7d demonstrated potent enzymatic inhibitory activity against TrkA and ALK2 with IC 50 0.087and 0.105 μM, respectively, and potent antiproliferative activity against KM12 and EKVX cell lines with IC 50 0.82 and 4.13 μM, respectively. Compound 10e showed good enzyme inhibitory activity against TrkA, ALK2, c-KIT, EGFR, PIM1, CK2α, CHK1, and CDK2 in submicromolar values. Additionally 10e revealed antiproliferative activity against MCF7, HCT116 and EKVX with IC 50 3.36, 1.40 and 3.49 μM, respectively; with good safety profile. Moreover, 10e showed cell cycle arrest at the G1/S phase and G1 phase in MCF7 and HCT116 cells with good apoptotic effect. Molecular docking studies were fulfilled for compound 10e and illustrated good interaction with the hot spots of the active site of the tested enzymes., Competing Interests: Declaration of competing interest The authors have declared no conflict of interest, (Copyright © 2023 Elsevier Masson SAS. All rights reserved.)

Background: Breastfeeding behaviors are strongly influenced by self-efficacy. This research aimed to determine the effect of breastfeeding counseling based on the Ready Set Baby (RSB) education program on self-efficacy and breastfeeding performance in adolescent mothers., Methods: In 2022, a parallel randomized clinical trial was carried out in Hamadan city's comprehensive health centers, involving 64 pregnant teenagers. The block randomization method was employed to divide the participants into two groups. The data collection instruments were a demographic characteristics questionnaire, a breastfeeding self-efficacy questionnaire, and the Bristol breastfeeding checklist. Three individual counseling sessions during pregnancy were conducted based on the "RSB" program. The ANCOVA was used for comparing groups. The statistical analyst was blinded to the group assignment., Results: The study included 64 participants with a mean age of 16.97(1.30) years, data from 60 participants were analyzed. The demographic and clinical characteristics of the two groups were relatively similar (P > 0.05). Following the intervention, self-efficacy and breastfeeding performance scores were measured and adjusted for confounding factors. The mean scores for self-efficacy were 116.03(20.64) and 100.02(20.64) (P < 0.005), with effect size 0.77 [MD = 16.01 (95% CI: 5.34,26.67)], and the mean scores for breastfeeding performance were 6.30(2.07) and 4.12(2.07) (P < 0.002), with effect size 1.05 [MD = 2.18 (95% CI: 1.11,3.24)] in the intervention and control groups, respectively., Conclusions: The Ready Set Baby education program's breastfeeding counseling for primiparous adolescent pregnant women significantly boosted their self-efficacy and performance in breastfeeding. Given the crucial role of breastfeeding in ensuring the well-being of both mother and child, further research is imperative to identify suitable and impactful interventions that can encourage breastfeeding practices among adolescents., Trial Registration: The trial protocol of this study has been registered in Iranian Registry of Clinical Trials at 08/09/2021. The registration reference is IRCT20200530047596N3., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Nonsteroidal anti-inflammatory drugs represent one of the most popularly used classes of drugs. However, their long-term administration is associated with various side effects including gastrointestinal ulceration. One of the major reasons of NSAIDs ulcerogenicity is direct damage of the epithelial lining cells by the acidic moieties present in many drugs. Another drawback for this acidic group is its rapid metabolism and clearance through Phase II conjugation. Three series of thiophene and thienopyrimidine derivatives were designed and synthesized as nonacidic anti-inflammatory agents. In vivo testing of their analgesic activity indicated that compounds 2b and 7a-d showed higher PI values than that of the positive control drugs, indomethacin and celecoxib. The latter compounds 2b and 7a-d were subjected to further anti-inflammatory activity testing where they showed comparable percentage edema inhibition to that of indomethacin and celecoxib. Compounds 2b, 7a, 7c, and 7d inhibited PGE2 synthesis by 61.10%-74.54% (71.47% for indomethacin, and 80.11% for celecoxib). The same compounds inhibited the expression of rat mPGES-1 and cPGES3 by 74%-83% (77% for indomethacin, and 82% for celecoxib) and 48%-70% (62% for indomethacin, and 70% for celecoxib), respectively. The stability of the most active compound 2b in Nonenzymatic gastrointestinal fluids and in human plasma was tested. Additionally, studying the metabolic stability of compound 2b in S9 rat liver fraction showed that it displayed a slow in vitro clearance with half-life time 1.5-fold longer than indomethacin. The metabolites of 2b were predicted via UPLC-MS/MS. In silico ADMET profiling study was also included., (© 2022 Wiley Periodicals LLC.)

Fluoroquinolones are a class of antibacterial agents used clinically to treat a wide array of bacterial infections. Although being potent, susceptibility to CNS side effects limits their use. It was observed that improvements in absorption, activity and side effects were achieved via modifications at the N atom of the C7 of the side chain. To meet the increasing demand for development of new antibacterial agents, nineteen novel ciprofloxacin-sulfonamide hybrid molecules were designed, synthesized and characterized by IR, 1 H NMR and 13 C NMR as potential antibacterial agents with dual DNA gyrase/topoisomerase IV inhibitory activity. Most of the synthesized compounds showed significant antibacterial activity that was revealed by testing their inhibitory activity against DNA gyrase, DNA topoisomerase IV as well as their minimum inhibitory concentration against Staphylococcus aureus. Six ciprofloxacin-sulfonamide hybrids (3f, 5d, 7a, 7d, 7e and 9b) showed potent inhibitory activity against DNA topoisomerase IV, compared to ciprofloxacin (IC50: 0.55 μM), with IC50 range: 0.23-0.44 μM. DNA gyrase was also efficiently inhibited by five ciprofloxacin-sulfonamide hybrids (3f, 5d, 5e, 7a and 7d) with IC50 range: 0.43-1.1 μM (IC50 of ciprofloxacin: 0.83 μM). Compounds 3a and 3b showed a marked improvement in the antibacterial activity over ciprofloxacin against both Gram-positive and Gram-negative pathogens, namely, Staphylococcus aureus Newman and Escherichia coli ATCC8739, with MIC = 0.324 and 0.422 μM, respectively, that is 4.2-fold and 3.2-fold lower than ciprofloxacin (MIC = 1.359 μM) against the Gram-positive Staphylococcus aureus, and MIC = 0.025 and 0.013 μM, respectively, that is 10.2-fold and 19.6-fold lower than ciprofloxacin (MIC = 0.255 μM) against the Gram-negative Escherichia coli ATCC8739. Also, the most active compounds showed lower CNS and convulsive side effects compared to ciprofloxacin with a concomitant decrease in GABA expression., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 Elsevier Masson SAS. All rights reserved.)

New coumarin derivatives 9a-f, 10a-e, and 11a-f were synthesized and evaluated for their cytotoxic activity against a human breast cancer cell line (MCF-7). All compounds exhibited good activity in the nanomolar range, using doxorubicin and erlotinib as positive controls. The most active compound 9d with IC 50 of 21 nM was tested against the HCT-116, HepG-2, A549, and SGC-7901 cell lines, with IC 50 values of 0.021, 0.170, 0.028, and 0.11 µM, respectively. Compound 9d was further investigated for its ability to suppress the expression of epidermal growth factor receptor (EGFR). Compound 9d decreased the concentration of EGFR by 87%, using erlotinib as a positive control. A docking study revealed similar or higher scores than for erlotinib and similar binding poses providing interactions with the hinge region of the tyrosine kinase (TK). Besides the effect on expression, this in silico investigation predicts the possibility of direct binding between the new coumarin derivatives and the EGFR TK. Moreover, computational calculation for ADME properties for the most active compounds 9d, 9e, 10c, and 11c revealed the expected high gastrointestinal tract absorption, moderate water solubility with no central nervous system toxicity, and druglikeness., (© 2021 Deutsche Pharmazeutische Gesellschaft.)

In the present study, we report the design and synthesis of novel CAN508 sulfonamide-based analogues (4, 8a-e, 9a-h and 10a-e) as novel carbonic anhydrase (CA) inhibitors with potential CDK inhibitory activity. A bioisosteric replacement approach was adopted to replace the phenolic OH of CAN508 with a sulfamoyl group to afford compound 4. Thereafter, a ring-fusion approach was utilized to furnish the 5/5 fused imidazopyrazoles 8a-e which were subsequently expanded to 6/5 pyrazolopyrimidines 9a-h and 10a-e. All the synthesized analogues were evaluated for their inhibitory activity toward isoforms hCA I, II, IX and XII. The target tumor-associated isoforms hCA IX and XII were effectively inhibited with K I s ranges 6-67.6 and 10.1-88.6 nM, respectively. Furthermore, all compounds were evaluated for their potential CDK2 and 9 inhibitory activities. Pyrazolopyrimidines 9d, 9e and 10b displayed weak CDK2 inhibitory activity (IC 50  = 6.4, 8.0 and 11.6 μM, respectively), along with abolished CDK9 inhibitory activity. This trend suggested that pyrazolopyrimidine derivatives merit further optimization to furnish more effective CDK2 inhibitor lead. On account of their excellent activity and selectivity towards hCA IX and XII, pyrazolopyrimidines 10 were evaluated for their anti-proliferative activity toward breast cancer MCF-7 and MDA-MB-468 cell lines under normoxic and hypoxic conditions. The most potent anti-proliferative agents 10a, 10c and 10d significantly increased cell percentage at sub-G1 and G2-M phases with concomitant decrease in the S phase population in MCF-7 treated cells. Finally, a docking study was undertaken to investigate the binding mode for the most selective hCA IX and XII inhibitors 10a-e, within hCA II, IX and XII active sites., (Copyright © 2020 Elsevier Masson SAS. All rights reserved.)

In the presented work, we report the design and synthesis of different new sets of triazolopyrimidine-based (9a-d) and triazole-based (11a-h, 13a-c, 15a,b, 17a,b and 21a-g) benzenesulfonamides. The newly synthesized sulfonamides were assessed for their inhibitory activities toward four human (h) metalloenzyme carbonic anhydrase (CA, EC 4.2.1.1) isoforms; hCA I, II, IX and XII. The four examined isoforms were inhibited by the prepared sulfonamides (9a-d, 11a-h, 13a-c, 15a,b, 17a,b and 21a-g) in variable degrees with K I s ranges: 94.4-4953.5 nM for hCA I, 6.9-837.6 nM for hCA II, 3.3-85.0 nM for hCA XI, and 4.4-105.0 nM for hCA XII. In particular, sulfonamides 11e, 21a and 21e emerged as single-digit nanomolar hCA IX and hCA XII inhibitors. Interestingly, triazolopyrimidine-based sulfonamide 9d and triazole-based sulfonamide 21e were found to be the most selective hCA IX inhibitors over hCA I (SI = 100.85 and 210.58, respectively) and hCA II (SI = 18.54 and 38.36, respectively). Thereafter, sulfonamides 9d and 21e were docked into the active site of CAs II, IX and XII, then poses showing the best scoring values and favorable binding interactions were subjected to a MM-GBSA based refinement and, limited to CA IX and XII, to a cycle of 100 ns molecular dynamics., (Copyright © 2019 Elsevier Masson SAS. All rights reserved.)

Aim: Nonsteroidal anti-inflammatory drugs are expansively used worldwide. However, their prolonged administration is associated with serious side effects, especially gastrointestinal ulceration. Materials & methods: New ibuprofen derivatives hybridized with H 2 S- or NO-donating moieties were synthesized and evaluated for their anti-inflammatory activity and ulcerogenic effect. COX-1/COX-2 isozymes selectivity test for the most promising derivatives was performed. Molecular docking studies were performed. Results: Most of the compounds showed promising anti-inflammatory activity comparable to that of ibuprofen (% edema inhibition = 76.6 and ulcer index = 21.26) with much better gastrointestinal tract tolerance (ulcer indices ranging from 0 to 14.67), especially compound 2 -H 2 S donor- (% edema inhibition = 75.5 and ulcer index = 11.75) and compound 16 -NO donor- (% edema inhibition = 65.4 and ulcer index = 8.66).

Herein we report the design and synthesis of three different sets of novel benzenesulfonamides (5a-e, 7a-e and 10a-d) incorporating hydrophilic/hydrophobic tails by hydrazido or hydrazino linkers. The newly synthesized benzenesulfonamides were examined in vitro for their inhibitory activity towards four human (h) carbonic anhydrase (hCA, EC 4.2.1.1) isoforms, hCA I, II, IX and XII using a stopped-flow CO 2 hydrase assay. All these isoforms were inhibited by the sulfonamides (5a-e, 7a-e and 10a-d) with variable degrees in the following K I ranges: 76.8-357.4 nM for hCA I, 8.2-94.6 nM for hCA II, 2.0-46.3 nM for hCA XI, and 8.3-88.3 nM for hCA XII. The sulfonamide 7d exhibited potent anti-proliferative activity against breast MCF-7 cancer cell line under both normoxic and hypoxic conditions with IC 50 values equal 3.32 ± 0.06 and 8.53 ± 0.32 μM, respectively, which are comparable to the reference drug doxorubicin (IC 50  = 2.36 ± 0.04 and 8.39 ± 0.25 μM, respectively). Furthermore, 7d was screened for cell cycle disturbance and apoptosis induction in MCF-7 cells. It was found to persuade cell cycle arrest at G2-M stage as well as to alter the Sub-G1 phase, also, 7d resulted in a significant increase in the percent of annexinV-FITC positive apoptotic cells from 1.03 to 18.54%. Molecular docking study was carried out for 7d within the hCA IX and hCA XII active sites to rationalize the obtained inhibition results., (Copyright © 2019 Elsevier Masson SAS. All rights reserved.)

Introduction: Left ventricular diastolic dysfunction, which is prevalent in end-stage renal disease, predicts morbidity and mortality among affected patients. The aim of this study was to evaluate diastolic function changes in end-stage renal disease patients before as well as 3 and 6 months after kidney transplantation., Methods and Materials: This longitudinal study from November 2008 to November 2009, enrolled 27 consecutive kidney transplant patients. Systolic and diastolic blood pressures and echocardiograghic parameters such as ejection fraction, left ventricular mass, and diastolic functions were measured before, as well as 3 and 6 months after transplantation. Data were analyzed by repeated-measure analysis of variance and Friedman tests using SPSS version 18., Results: The mean patients age was 39.47 ± 12.27 years with 55.6% males. The mean systolic and diastolic blood pressure and left ventricular mass decreased significantly in the first 3 (125.44 ± 11.35, 78.51 ± 6.32, 141.94 ± 3.32) and 6 months (121.48 ± 10.63, 72.96 ± 4.21, 138.25 ± 3.12) after renal transplantation compared to the values before the procedure (136.77 ± 14.09, 81.92 ± 9.01, 158.30 ± 3.58 respectively; P < .05). The left ventricular ejection fraction increased significantly at 3 (63.00 ± 6.49) and 6 months (66.11 ± 5.87) compared with preoperative (62.48 ± 5.74; P < .05). Step mean diastolic function also decreased significantly at 3 (1.94) and 6 months (1.81) compared with before transplantation (2.24; P < .05)., Conclusion: According to our findings, transplantation can correct ejection fraction and systolic and diastolic blood pressure and lead to regression of left ventricular hypertrophy. Diastolic function was improved after transplantation., (Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.)