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Using pebble and fibre in an epoxy matrix, the mechanical, dynamic, and thermal characteristics of a composite were examined. Tensile, flexural, impact, and interlaminar shear strengths are experimentally determined. In this study, we compare the mechanical performance of carbon fibre composites composed entirely of conventional epoxy (NE). The results of a comparative investigation using 15 and 20% carbon fibre in an epoxy matrix are presented. Additional categories for compressive strength and damping ratio were defined based on this performance. The epoxy resin was combined with carbon fibre (15 wt% and 20 wt%) in a unidirectional arrangement and manufactured with different fillers like pebble. The goal of this research is to better understand the bonding mechanisms between damping materials and the resin matrix in order to increase interfacial bonding performance. This information is required for both selecting the appropriate material for applications and developing a composite construction using that material.

Background and study aims The Bethesda ERCP Skill Assessment Tool (BESAT) is a video-based assessment tool of technical endoscopic retrograde cholangiopancreatography (ERCP) skill with previously established validity evidence. We aimed to assess the discriminative validity of the BESAT in differentiating ERCP skill levels. Methods Twelve experienced ERCP practitioners from tertiary academic centers were asked to blindly rate 43 ERCP videos using the BESAT. ERCP videos consisted of native biliary cannulation and sphincterotomy and were recorded from 10 unique endoscopists of various ERCP experience (from advanced endoscopy fellow to > 10 years of ERCP experience). Inter-rater reliability, discriminative validity, and internal structure validity were subsequently assessed. Results The BESAT was found to reliably differentiate between endoscopists of varying levels of ERCP experience with experienced ERCPists scoring higher than novice ERCPists in 11 of 13 (85%) instrument items. Inter-rater reliability for BESAT items ranged from good to excellent (intraclass correlation range: 0.86 to 0.93). Internal structure validity was assessed with item-total correlations ranging from 0.53 to 0.83. Conclusions Study findings demonstrate that the BESAT, a video-based ERCP skill assessment tool, has high inter-rater reliability and has discriminative validity in differentiating novice from expert ERCP skill. Further investigations are needed to determine the role of video-based assessment in improving trainee learning curves and patient outcomes.

Abstract The global crisis of antimicrobial resistance (AMR) necessitates the development of broad-spectrum antibacterial drugs effective against multi-drug resistant (MDR) pathogens. BWC0977, a Novel Bacterial Topoisomerase Inhibitor (NBTI) selectively inhibits bacterial DNA replication via inhibition of DNA gyrase and topoisomerase IV. BWC0977 exhibited a minimum inhibitory concentration (MIC90) of 0.03–2 µg/mL against a global panel of MDR Gram-negative bacteria including Enterobacterales and non-fermenters, Gram-positive bacteria, anaerobes and biothreat pathogens. BWC0977 retains activity against isolates resistant to fluoroquinolones (FQs), carbapenems and colistin and demonstrates efficacy against multiple pathogens in two rodent species with significantly higher drug levels in the epithelial lining fluid of infected lungs. In healthy volunteers, single-ascending doses of BWC0977 administered intravenously ( https://clinicaltrials.gov/study/NCT05088421 ) was found to be safe, well tolerated (primary endpoint) and achieved dose-proportional exposures (secondary endpoint) consistent with modelled data from preclinical studies. Here, we show that BWC0977 has the potential to treat a range of critical-care infections including MDR bacterial pneumonias.

Background and objectives: Bacterial DNA topoisomerases are unique in maintaining the DNA topology for cell viability. Mycobacterium tuberculosis (MTB) DNA gyrase, a sole type II topoisomerase has a larger scope as a target for developing novel therapeutics. In this study, an effort was made towards the design and synthesis of benzothiazinone-piperazine hybrid analogues to obtain the possibility of it to lead development through the molecular hybridization technique. Methods: A five-step scheme was followed to obtain a series of 36 benzothiazinone-piperazine derivatives and to evaluate them for Mtb DNA gyrase inhibition, antimycobacterial and cytotoxicity studies. Results: Compound N-(4-chlorophenyl)-4-(6-nitro-4-oxo-4H-benzo[e][1,3]thiazin-2-yl)piperazine-1-carbothioamide (18) showed greater inhibitory potential with an IC50 of 0.51±0.16 μM in the DNA supercoiling assay of Mtb with a moderate anti-tubercular activity of 4.41 μM. The compound even passed the safety profile of eukaryotic cell cytotoxicity with a 1.81% inhibition in the RAW 264.7 cell line at 100 μM concentration. Conclusions: This study describes the discovery of benzothiazinone as gyrase inhibitors with potent Mtb MIC and inhibitory profiles of the gyrase enzyme with less cytotoxic effect. Furthermore, it is believed that this class of compounds has the potential to be further developed as an anti-TB drug candidate.

Introduction: Mycobacterium marinum has emerged as a suitable species for induction of tuberculosis-like disease in zebrafish, and various zebrafish models (larval and adult) for drug screening have been proposed in the literature. It is believed that an adult zebrafish model is more useful in drug screening because, apart from assessment of efficacy, one can obtain data on dosage, pharmacokinetics and overall health improvement. This study suggests a simple, cost-effective and resource-efficient protocol for screening of anti-tuberculosis drugs. Methods: The parameters used for assessment of infection as well as anti-bacterial response were: (a) bacterial count; and (b) body weight change. An optimization study was conducted to establish the concentration of bacteria required to produce a reproducible phenotype of tuberculosis (TB). A negative control (Amoxicillin) and anti-mycobacterial drugs (Isoniazid, Rifampicin, Moxifloxacin, Ethambutol and Isoniazid+Rifampicin) were used for validation of the protocol. All the drugs were administered orally. Results: An intra-peritoneal inoculation of 0.75 million bacteria/fish was optimized for the model. All the anti-tuberculosis drugs showed efficacy in this model, whereas the negative control did not show any signs of reversing the parameters of M. marinum infection. Discussion: Adult zebrafish model of M. marinum-induced tuberculosis has not been fully exploited as a drug screening tool. In the present report, a protocol is suggested that is simple, reproducible and resource-efficient for screening of anti-tuberculosis agents. This protocol is an attempt to refine the published protocols and use this model as a surrogate model of human TB for the purpose of drug screening.

Background and objectives: The objective of this study is to synthesize and evaluate 1-(4-chlorophenyl)-4-(4-hydroxy-3-methoxy-5-nitrobenzylidene) pyrazolidine-3,5-dione (CD59) analogues to establish structure–activity relationship and mechanism of action. Methods: Thirty analogues of reported antitubercular CD59 were prepared by two-step synthetic protocols and characterized. The compounds were evaluated for in vitro activities against Mycobacterium tuberculosis (MTB), cytotoxicity against RAW 264.7 cells. The molecules were also evaluated for three mycobacterial enzymes to study the mechanism of action. Results: Among the compounds, 4-(2-bromobenzylidene)-1-(4-chlorophenyl)pyrazolidine-3,5-dione (4k) was found to be the most active compound in vitro with MICs of 4.13 μM against log-phase culture of MTB and also non-toxic up to 50 μM. Conclusions: Amongst all, the compounds 4g, 3i and 3n were most active against the enzymes MTB Pantothenate synthetase, lysine amino transferase and Alanine dehydrogenase, respectively. Further screening of these molecules was required in the in vitro dormant MTB models.

Abstract Aldo-keto reductase 1C3 (AKR1C3) is a protein upregulated in prostate cancer, hematological malignancies, and other cancers where it contributes to proliferation and chemotherapeutic resistance. Androgen receptor splice variant 7 (ARv7) is the most common mutation of the AR receptor that confers resistance to clinical androgen receptor signalling inhibitors in castration-resistant prostate cancer. AKR1C3 interacts with ARv7 promoting stabilization. Herein we report the discovery of the first-in-class AKR1C3 Proteolysis-Targeting Chimera (PROTAC) degrader. This first-generation degrader potently reduced AKR1C3 expression in 22Rv1 prostate cancer cells with a half-maximal degradation concentration (DC50) of 52 nM. Gratifyingly, concomitant degradation of ARv7 was observed with a DC50 = 70 nM, along with degradation of the AKR1C3 isoforms AKR1C1 and AKR1C2 to a lesser extent. This compound represents a highly useful chemical tool and a promising strategy for prostate cancer intervention.

IntroductionThe marine microalga Isochrysis galbana is prolific producer of fucoxanthin, which is a xanthophyll carotenoid with substantial global market value boasting extensive applications in the food, nutraceutical, pharmaceutical, and cosmetic industries. This study presented a novel integrated experimental approach coupled with machine learning (ML) models to predict the fucoxanthin content in I. galbana by altering the type and concentration of phytohormone supplementation, thus overcoming the multiple methodological limitations of conventional fucoxanthin quantification.MethodsA novel integrated experimental approach was developed, analyzing the effect of varying phytohormone types and concentrations on fucoxanthin production in I. galbana. Morphological analysis was conducted to assess changes in microalgal structure, while growth rate and fucoxanthin yield correlations were explored using statistical analysis and machine learning models. Several ML models were employed to predict fucoxanthin content, with and without hormone descriptors as variables.ResultsThe findings revealed that the Random Forest (RF) model was highly significant with a high R2 of 0.809 and RMSE of 0.776 when hormone descriptors were excluded, and the inclusion of hormone descriptors further improved prediction accuracy to R2 of 0.839, making it a useful tool for predicting the fucoxanthin yield. The model that fitted the experimental data indicated methyl jasmonate (0.2 mg/L) as an effective phytohormone. The combined experimental and ML approach demonstrated rapid, reliable, and cost-efficient prediction of fucoxanthin yield.DiscussionThis study highlights the potential of machine learning models, particularly Random Forest, to optimize parameters influencing microalgal growth and fucoxanthin production. This approach offers a more efficient alternative to conventional methods, providing valuable insights into improving fucoxanthin production in microalgal cultivation. The findings suggest that leveraging diverse ML models can enhance the predictability and efficiency of fucoxanthin production, making it a promising tool for industrial applications.

Despite a record number of clinical studies investigating various anti-myeloma treatments, the 5-year survival rate for multiple myeloma (MM) patients in the US is only 55%, and almost all patients relapse. Poor patient outcomes demonstrate that myeloma cells are “born to survive” which means they can adapt and evolve following treatment. Thus, new therapeutic approaches to combat survival mechanisms and target treatment resistance are required. Importantly, Mcl-1, anti-apoptotic protein, is required for the development of MM and treatment resistance. This study looks at the possibility of KS18, a selective Mcl-1 inhibitor, to treat MM and overcome resistance. Our investigation demonstrates that KS18 effectively induces cell death in MM by dual regulatory mechanisms targeting the Mcl-1 protein at both transcriptional and post-translational levels. Specifically, KS18 suppresses Mcl-1 activation via STAT-3 pathway and promotes Mcl-1 phosphorylation/ubiquitination/proteasome-dependent protein degradation (UPS). Significantly, KS18 triggered caspase-dependent apoptosis in MM patient samples and bortezomib-resistant cells, synergizing with venetoclax to boost apoptosis. KS18 promises to overcome bortezomib and venetoclax resistance and re-sensitize myeloma cells to chemotherapy. Furthermore, the study shows the tremendous impact of KS18 in inhibiting colony formation in bortezomib-resistant cells and demonstrates significant tumor shrinkage in KS18-treated NSG mice without notable toxicity signs after 4 weeks of therapy with a single acceptable dose each week, indicating its powerful anti-neoplastic and anti-resistance characteristics. This study strongly implies that KS18 may treat MM and provide new hope to patients who are experiencing recurrence or resistance.

Abstract Objective The purpose of this study was to examine the association between lifestyle factors and body weight in a nationally representative sample of US adults and to evaluate the association between a novel “Healthy Habits Composite Score (HHCS)” and risk of obesity. Methods This cross‐sectional study included data from 4870 adults who participated in the 2017–2018 National Health and Nutrition Examination Survey (NHANES). The HHCS was developed based on 4 factors: diet, physical activity, sedentary time, and sleep, all of which were measured during the NHANES. A “healthy lifestyle” was defined as meeting ≥3 of the 4 established criteria. Data analysis was conducted using SAS 9.4 and procedures to account for the complex survey design. All models were adjusted for age, sex, race, household income, and education. Results Adults with obesity had significantly lower dietary quality (48.8 ± 0.6 vs. 53.2 ± 0.9) and reported significantly more sedentary time (∼1 h more; 356.3 ± 7.0 vs. 301.4 ± 8.3 min) than lean adults, both p

The incidence of type 2 diabetes mellitus (T2DM) has increased in our society in recent decades as the population ages, and this trend is not expected to revert. This is the same for the incidence of the main neurodegenerative disorders, including the two most common ones, which are, Alzheimer’s and Parkinson’s disease. Currently, no pharmacological therapies have been developed to revert or cure any of these pathologies. Interestingly, in recent years, an increased number of studies have shown a high co-morbidity between T2DM and neurodegeneration, as well as some common molecular pathways that are affected in both types of diseases. For example, while the etiopathology of T2DM and neurodegenerative disorders is highly complex, mitochondrial dysfunction has been broadly described in the early steps of both diseases; accordingly, this dysfunction has emerged as a plausible molecular link between them. In fact, the prominent role played by mitochondria in the mammalian metabolism of glucose places the physiology of the organelle in a central position to regulate many cellular processes that are affected in both T2DM and neurodegenerative disorders. In this collaborative review, we critically describe the relationship between T2DM and neurodegeneration; making a special emphasis on the mitochondrial mechanisms that could link these diseases. A better understanding of the role of mitochondria on the etiopathology of T2DM and neurodegeneration could pave the way for the development of new pharmacological therapies focused on the regulation of the physiology of the organelle. These therapies could, ultimately, contribute to increase healthspan.

Motility of pathogenic protozoa depends on flagella (synonymous with cilia) with axonemes containing nine doublet microtubules (DMTs) and two singlet microtubules. Microtubule inner proteins (MIPs) within DMTs influence axoneme stability and motility and provide lineage-specific adaptations, but individual MIP functions and assembly mechanisms are mostly unknown. Here, we show in the sleeping sickness parasite Trypanosoma brucei, that FAP106, a conserved MIP at the DMT inner junction, is required for trypanosome motility and functions as a critical interaction hub, directing assembly of several conserved and lineage-specific MIPs. We use comparative cryogenic electron tomography (cryoET) and quantitative proteomics to identify MIP candidates. Using RNAi knockdown together with fitting of AlphaFold models into cryoET maps, we demonstrate that one of these candidates, MC8, is a trypanosome-specific MIP required for parasite motility. Our work advances understanding of MIP assembly mechanisms and identifies lineage-specific motility proteins that are attractive targets to consider for therapeutic intervention.

A heterogenous Palladium anchored Resorcinol-formaldehyde-hyperbranched PEI mesoporous catalyst, made by one-pot synthesis, was used successfully for in situ Suzuki-Miyaura cross coupling synthesis of anticancer prodrug PP-121 from iodoprazole and boronic ester precursors. The mesoporous catalyst with the non-cytotoxic precursors were tested in 2D in vitro model with excellent cytocompatibility and a strong suppression of PC3 cancer cell proliferation, underscored by 50% reduction in PC3 cells viability and 55% reduction in cell metabolism activity and an enhanced rate of early and late apoptosis in flow cytometry, that was induced only by successful in situ pro drug PP121 synthesis from the precursors. The 3D gelatin methacrylate hydrogel encapsulated in vitro cell models underscored the results with a 52% reduction in cell metabolism and underscored apoptosis of PC3 cells when the Pd anchored catalyst was combined with the precursors. In situ application of Suzuki-Miyaura cross coupling of non-cytotoxic precursors to cancer drug, along with their successful encapsulation in an injectable hydrogel could be applied for tumor point drug delivery strategies that can circumvent deleterious side effects and poor bioavailability chemotherapy routes with concomitant enhanced efficacy.

Multiple Myeloma (MM) is a malignant expansion of plasma cells in the bone marrow (BM), resulting in a disease characterized by symptoms of end organ damage from light chain secretion, crowding of the BM, and bone lesions. Although the past two decades have been characterized by numerous novel therapies emerging, the disease remains incurable due to intrinsic or acquired drug resistance. A major player in MM's drug resistance arises from its intimate relationship with the BM microenvironment (BMME). Through stress-inducing conditions, soluble messengers, and physical adhesion to BM elements, the BMME activates numerous pathways in the myeloma cell. This not only propagates myeloma progression through survival and growth signals, but also specific mechanisms to circumvent therapeutic actions. In this review, we provide an overview of the BMME, the role of individual components in MM survival, and various therapy-specific resistance mechanisms reported in the literature.

BackgroundThere is increasing interest in using patient-generated health data (PGHD) to improve patient-centered care during pregnancy. However, little research has examined the perspectives of patients and providers as they report, collect, and use PGHD to inform obstetric care. ObjectiveThis study aims to explore the perspectives of patients and providers about the use of PGHD during pregnancy, including the benefits and challenges of reporting, collecting, and using these data, as well as considerations for expanding the use of PGHD to improve obstetric care. MethodsWe conducted one-on-one interviews with 30 pregnant or postpartum patients and 14 health care providers from 2 obstetrics clinics associated with an academic medical center. Semistructured interview guides included questions for patients about their experience and preferences for sharing PGHD and questions for providers about current processes for collecting PGHD, opportunities to improve or expand the collection of PGHD, and challenges faced when collecting and using this information. Interviews were conducted by phone or videoconference and were audio recorded, transcribed verbatim, and deidentified. Interview transcripts were analyzed deductively and inductively to characterize and explore themes in the data. ResultsPatients and providers described how PGHD, including physiologic measurements and experience of symptoms, were currently collected during and between in-person clinic visits for obstetric care. Both patients and providers reported positive perceptions about the collection and use of PGHD during pregnancy. Reported benefits of collecting PGHD included the potential to use data to directly inform patient care (eg, identify issues and adjust medication) and to encourage ongoing patient involvement in their care (eg, increase patient attention to their health). Patients and providers had suggestions for expanding the collection and use of PGHD during pregnancy, and providers also shared considerations about strategies that could be used to expand PGHD collection and use. These strategies included considering the roles of both patients and providers in reporting and interpreting PGHD. Providers also noted the need to consider the unintended consequences of using PGHD that should be anticipated and addressed. ConclusionsAcknowledging the challenges, suggestions, and considerations voiced by patients and providers can inform the development and implementation of strategies to effectively collect and use PGHD to support patient-centered care during pregnancy.

The integration of intelligent systems in various industries has led to notable advancements in energy resource utilization. Power Line Communication (PLC) is widely used in the power industry for transmitting telemetry, speech, and protective tripping commands. While Wi-Fi has limitations in remote control and monitoring applications due to cost and power consumption, Wireless Sensor Networks (WSNs) face challenges like transmission errors and data losses. Developing a scalable WSN architecture is crucial, especially in the presence of excessive network coverage or non-line-of-sight situations. Challenges persist despite efforts to enhance WSN connectivity, and conflicts with wireless local area networks (WLANs) in the 2.4 GHz ISM band lead to issues like packet losses and interference. To address these issues, the proposal suggests integrating WSN with PLC technology to create a resilient utility network. The research introduces a Master-Slave system using frequency-shift keying (FSK) based PLC modules for effective management and supervision of the intelligent utility network, with scalability for diverse industrial intelligence applications.

The posit number system aims to be a drop-in replacement of the existing IEEE floating-point standard. Its properties- tapered precision and high dynamic range, allow a smaller size posit to almost match the performance of a much larger size floating-point in representing decimals. This becomes especially useful for performing error-tolerant tasks like deep learning inference computation where low latency and area are a priority. Recent research has found that the performance of deep neural network models saturates beyond a certain level of accuracy of multipliers used for convolutions. Therefore, the extra hardware cost of developing precise arithmetic circuits for such applications becomes an unnecessary overhead. This paper explores approximate posit multipliers in the convolutional layers of deep neural networks and attempts to find an ideal balance between hardware utilization and inference accuracy. Posit multiplication involves several steps, with the mantissa multiplication step utilizing maximum hardware resources. To mitigate this, a posit multiplier circuit using an approximate hybrid-radix Booth encoding for mantissa multiplication and techniques such as truncation and bit masking based on input regime size are proposed. In addition, a novel Booth encoding control scheme to prevent unnecessary bits from switching has been devised to reduce dynamic power dissipation. Compared to existing literature, these optimizations have contributed to a 23% decrease in power dissipation in the mantissa multiplication stage. Further, a novel area and energy-efficient decoder architecture have also been developed with an 11% reduction in dynamic power dissipation and area compared to existing decoders. Overall, the proposed < 16, 2 > posit multiplier offers a 14% reduction in the PDP over the existing approximate posit multiplier designs. The proposed < 16, 2 > multiplier also achieves over 90% accuracy in inferencing deep learning models such as ResNet20, VGG-19 and DenseNet.

This article is devoted to deduce the expression of the Green's function related to a general constant coefficients fractional difference equation coupled to Dirichlet conditions. In this case, due to the points where some of the fractional operators are applied, we are in presence of an implicit fractional difference equation. So, due to such a property, it is more complicated to calculate and manage the expression of the Green's function than in the explicit case studied in a previous work of the authors. Contrary to the explicit case, where it is shown that the Green's function is constructed as finite sums, the Green's function constructed here is an infinite series. This fact makes necessary to impose more restrictive assumptions on the parameters that appear in the equation. The expression of the Green's function will be deduced from the Laplace transform on the time scales of the integers. We point out that, despite the implicit character of the considered equation, we can have an explicit expression of the solution by means of the expression of the Green's function. These two facts are not incompatible. Even more, this method allows us to have an explicit expression of the solution of an implicit problem. Finally, we prove two existence results for nonlinear problems, via suitable fixed point theorems.

In this paper, we consider a fourth-order three-point boundary value problem. Despite the fact that the corresponding Green’s function changes its sign on the square of its definition, we obtain the existence of at least one positive and decreasing solution under some suitable conditions. The results are based on the classical Krasosel’skii’s fixed point theorem in cones. Then, we impose some sufficient conditions that allow us to deduce nonexistence results. In the end, some examples are given in order to illustrate our main results.