A deep learning based encoder-decoder model for speed planning of autonomous electric truck platoons.

Electric truck platooning offers a promising solution to extend the range of electric vehicles during long-haul operations. However, optimizing the platoon speed to ensure efficient energy utilization remains a critical challenge. The existing research on implementing data-driven solutions for truck platooning remains limited and implementing first principles solution is still a challenge. However, recognizing the resemblance of truck platoon data to a time series serves as a compelling motivation to explore suitable analytical techniques to address the problem. This paper presents a novel deep learning approach using a sequence-to-sequence encoder-decoder model to obtain the speed profile to be followed by an autonomous electric truck platoon considering various constraints such as the available state of charge (SOC) in the batteries along with other vehicles and road conditions while ensuring that the platoon is string stable. To ensure that the framework is suitable for long-haul highway operation, the model has been trained using various known highway drive cycles. Encoder-decoder models were trained and hyperparameter tuning was performed for the same. Finally, the most suitable model has been chosen for the application. For testing the entire framework, drive cycle/speed prediction corresponding to different desired SOC profiles has been presented. A case study showing the relevance of the proposed framework in predicting the drive cycle on various routes and its impact on taking critical policy decisions during the planning of electric truck platoons has also been presented. This study would help to efficiently plan the feasible routes for electric trucks considering multiple constraints such as battery capacity, expected discharge rate, charging infrastructure availability, route length/travel time, and other on-road operating conditions while also maintaining stability.

Uncovering Novel Protein Partners of Inducible Nitric Oxide Synthase in Human Testis.

Peroxidative damage to human spermatozoa has been shown to be the primary cause of male infertility. The possible role of nitric oxide (NO) in affecting sperm motility, capacitation, and acrosome reaction has been reported, too. The overproduction of NO by the enzyme inducible nitric oxide synthase (iNOS) could be responsible as it has been implicated in the pathogenesis of many diseases. There have been many studies on regulating iNOS function in various tissues, especially by protein-protein interaction; however, no study has looked for iNOS-interacting proteins in the human testis. Here, we have reported the identification of two proteins that interact with iNOS. We initially undertook a popular yeast two-hybrid assay to screen a human testis cDNA library in yeast using an iNOS-peptide fragment (amino acids 181-335) as bait. We verified our data using the mammalian chemiluminescent co-IP method; first, employing the same peptide and, then, a full-length protein co-expressed in HEK293 cells in addition to the candidate protein. In both cases, these two protein partners of iNOS were revealed: (a) sperm acrosome-associated 7 protein and (b) retinoblastoma tumor-suppressor binding protein.

A potential function for MicroRNA-124 in normal and pathological bone conditions.

Cells produce short single-stranded non-coding RNAs (ncRNAs) called microRNAs (miRNAs), which actively regulate gene expression at the posttranscriptional level. Several miRNAs have been observed to exert significant impacts on bone health and bone-related disorders. One of these, miR-124, is observed in bone microenvironments and is conserved across species. It affects bone cell growth and differentiation by activating different transcription factors and signaling pathways. In-depth functional analyses of miR-124 have revealed several physiological and pathological roles exerted through interactions with other ncRNAs. Deciphering these RNA-mediated signaling networks and pathways is essential for understanding the potential impacts of dysregulated miRNA functions on bone biology. In this review, we aim to provide a comprehensive analysis of miR-124's involvement in bone physiology and pathology. We highlight the importance of miR-124 in controlling transcription factors and signaling pathways that promote bone growth. This review reveals therapeutic implications for the treatment of bone-related diseases.

Design of PI3K-mTOR Dual Inhibitors for Ovarian Cancer: Are We on the Right Track?

Ovarian cancer is one of the most familiar kinds of gynecological cancer seen in women. Though it is not as familiar as breast cancer, the survival rate for ovarian cancer is very low when compared with breast cancer. Even after being one among the familiar types, to date, there are no proper treatments available for ovarian cancer. All the treatments that are present currently show a high rate of recurrence after the treatment. Therefore, treating this silent killer from the roots is the need of the hour. PI3K/AKT/m- TOR pathway is one of the pathways that get altered during ovarian cancer. Studies are already going on for the inhibition of PI3K and mTOR separately. Efforts have been made to inhibit either PI3K or mTOR separately earlier. However, due to its side effects and resistance to the treatments available, current studies are based on the inhibition of PI3K and mTOR together. Inhibition of PI3K and mTOR simultaneously reduces the chances of negative feedback, thus decreasing the toxicity. This review contains the evolution of PI3K and mTOR drugs that are approved by the FDA and are in the trials for different cancer types, including Ovarian cancer. In this article, how a molecular targeted therapy can be made successful and free from toxicity for treating ovarian cancer is discussed. Therefore, this review paves the way for finding an effective scaffold rather than the clinical part. The scaffold thus selected can be further modified and synthesized in the future as dual PI3K/mTOR inhibitors specifically for OC.

Neural harmony: revolutionizing thyroid nodule diagnosis with hybrid networks and genetic algorithms.

In the contemporary world, thyroid disease poses a prevalent health issue, particularly affecting women's well-being. Recognizing the significance of maternal thyroid (MT) hormones in fetal neurodevelopment during the first half of pregnancy, this study introduces the HNN-GSO model. This groundbreaking hybrid approach, utilizing the MT dataset, integrates ResNet-50 and Artificial Neural Network (ANN) within a Glow-worm Swarm Optimization (GSO) framework for optimal parameter tuning. With a comprehensive methodology involving dataset preprocessing and Genetic Algorithm (GA) for feature selection, our model leverages ResNet-50 for feature extraction and ANN for classification tasks. Implemented in Python, the HNN-GSO model outperforms existing models, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), ResNet, GoogleNet, and ANN, achieving an impressive accuracy rate of 98%. This success underscores the effectiveness of our approach in complex classification tasks within machine learning (ML) and pattern recognition, specifically tailored to the Thyroid Ultrasound Images (TUI) Dataset. To provide a comprehensive understanding of performance, additional statistical measures such as precision, recall, and F1 score were considered. The HNN-GSO model consistently outperformed competitors across these metrics, showcasing its superiority in MT classification. The HNN-GSO model seamlessly combines ResNet-50's feature extraction, ANN's classification robustness, and GSO's optimization for unparalleled performance. This research offers a promising framework for advancing ML methodologies, enhancing accuracy, and efficiency in classification tasks related to MT health.

Ligated Pd-Catalyzed Aminations of Aryl/Heteroaryl Halides with Aliphatic Amines under Sustainable Aqueous Micellar Conditions.

Sustainable technology for constructing Pd-catalyzed C-N bonds involving aliphatic amines is reported. A catalytic system that relies on low levels of recyclable precious metal, a known and commercially available ligand, and a recyclable aqueous medium are combined, leading to a newly developed procedure. This new technology can be used in ocean water with equal effectiveness. Applications involving highly challenging reaction partners constituting late-stage functionalization are documented, as is a short but efficient synthesis of the drug naftopidil. Comparisons with existing aminations highlight the many advances being offered.

Predictive performance of population pharmacokinetic models of imatinib in chronic myeloid leukemia patients.

BACKGROUND AND AIM: Chronic myeloid leukemia is a myeloproliferative neoplasm associated with the specific chromosomal translocation known as the Philadelphia chromosome. Imatinib is a potent BCR-ABL tyrosine kinase inhibitor, which is approved as the first line therapy for CML patients. There are various population pharmacokinetic studies available in the literature for this population. However, their use in other populations outside of their cohort for the model development has not been evaluated. This study was aimed to perform the predictive performance of the published population pharmacokinetic models for imatinib in CML population and propose a dosing nomogram. METHODS: A systematic review was conducted through PubMed, and WoS databases to identify PopPK models. Clinical data collected in adult CML patients treated with imatinib was used for evaluation of these models. Various prediction-based metrics were used for assessing the bias and precision of PopPK models using individual predictions. RESULTS: Eight imatinib PopPK model were selected for evaluating the model performance. A total of 145 plasma imatinib samples were collected from 43 adult patients diagnosed with CML and treated with imatinib. The PopPK model reported by Menon et al. had better performance than all other PopPK models. CONCLUSION: Menon et al. model was able to predict well for our clinical data where it had the relative mean prediction error percentage ≤ 20%, relative median absolute prediction error ≤ 30% and relative root mean square error close to zero. Based on this final model, we proposed a dosing nomogram for various weight groups, which could potentially help to maintain the trough concentrations in the therapeutic range.

Chitosan nanocarriers for non-coding RNA therapeutics: A review.

Non-coding RNA (ncRNA)-based therapies entail delivering ncRNAs to cells to regulate gene expression and produce proteins that combat infections, cancer, neurological diseases, and bone abnormalities. Nevertheless, the therapeutic potential of these ncRNAs has been limited due to the difficulties in delivering them to specific cellular targets within the body. Chitosan (CS), a biocompatible cationic polymer, interacts with negatively charged RNA molecules to form stable complexes. It is a promising biomaterial to develop nanocarriers for ncRNA delivery, overcoming several disadvantages of traditional delivery systems. CS-based nanocarriers can protect ncRNAs from degradation and target-specific delivery by surface modifications and intracellular release profiles over an extended period. This review briefly summarizes the recent developments in CS nanocarriers' synthesis and design considerations and their applications in ncRNA therapeutics for treating various diseases. We also discuss the challenges and limitations of CS-based nanocarriers for ncRNA therapeutics and potential strategies for overcoming these challenges.

Glioma arising in the setting of mismatch repair deficiency-rare or are we missing it?

Germline mutations in mismatch repair (MMR) genes (MLH1, MSH2, MSH6, PMS2) can be mono-allelic or biallelic, resulting in a Lynch syndrome (LS) or constitutional mismatch repair deficiency (CMMRD) syndrome respectively. Glioma arising in the setting of MMR deficiency is uncommon. We describe two pediatric patients with high-grade glioma (HGG) and associated MMR protein deficiency. On histomorphology both cases showed HGG with astrocytic morphology and prominent multinucleated tumor cells. On immunohistochemistry, the first case was negative for IDH1 p.R132H showed loss of ATRX and p53 positivity. The second case was positive for IDH1 p.R132H and p53, but showed retained expression of ATRX. The histomorphology in both cases and additionally IDH mutation with retained ATRX in the second case, prompted us to test for MMR protein deficiency which was carried out by immunohistochemistry (IHC). One case revealed an immunostaining pattern suggestive of CMMRD while the other was suggestive of LS. Both the cases showed good response to surgery and radio-chemotherapy in the follow-up available. Our cases highlight the importance of testing for MMR proteins by simple IHC, in the setting of appropriate clinical scenario, histopathological and immunohistochemical findings. The recognition of these tumors is extremely important to guide further treatment and prompt family screening.

Oncofertility awareness among primary care physicians in India.

BACKGROUND: Primary care physicians not only coordinate referrals to oncology services but can play a crucial role in successful fertility preservation referrals in cancer-diagnosed patients. Hence, it is important to assess their knowledge and attitudes towards fertility preservation. METHODS: An eighteen-item oncofertility survey was administered to primary care physicians between May 2019 to September 2020.  Results: A total of forty-six responses were received and analysed. About 60% of primary care physicians did not have adequate knowledge about available fertility preservation options and only 26-32% were aware of international guidelines recommending fertility preservation in cancer patients.  Conclusions: Imparting awareness and knowledge of fertility preservation and its options to primary care physicians could enable an integrated cancer care model while also facilitating successful oncofertility referrals in countries like India.

Quantitative Differences in Rumen Epithelium Proteins in Lambs Fed Wheat, Perennial Wheat, or Perennial Wheat plus Lucerne.

The value of crops such as perennial wheat (PW) for grain and grazing compared to conventional wheat (W), or the addition of lucerne to PW (PWL) is still being determined. This research sought to determine if these diets were associated with changes in the membranebound proteins that transport nutrients in the rumen epithelium (RE). Crossbred ewes (Poll Dorset × Merino) were fed W, PW, or PWL (50:50) fresh-cut forage ad libitum for 4 weeks. Average daily gain (ADG; p < 0.001) was highest in the W-fed lambs compared to the PW and PWL. Metabolisable energy intake (MEI) was higher in lambs fed W (p < 0.001) compared to PW and PWL. In pairwise comparisons of the PW and PWL diet group we found protein abundance was significantly (p < 0.05, FDR < 0.05, Benjamini p < 0.05) different in fatty acid metabolism, oxidative phosphorylation, and biosynthesis of cofactors pathways. There were not any differences in protein abundance related to nutrient transport or energy metabolism in the RE between W- vs. PW- and W- vs. PWL-fed lambs. However, in the PW- vs. PWL-fed lambs, there was a difference in the level of proteins regulating the metabolism of fatty acids and energy production in the mitochondria of the rumen epithelium.

A sustainable, efficient, and potentially cost-effective approach to the antimalarial drug candidate MMV688533.

A 6-step synthesis of the antimalarial drug candidate MMV688533 is reported. Key transformations carried out under aqueous micellar conditions include two Sonogashira couplings and amide bond formation. Compared with the first-generation manufacturing process reported by Sanofi, the current route features ppm levels of palladium loading, less material input, less organic solvent, and no traditional amide coupling reagents. The overall yield is improved ten-fold, from 6.4% to 67%.

Bacillus velezensis (strains A6 & P42) as a potential biocontrol agent against Klebsiella variicola, a new causal agent of soft rot disease in carrot.

Bacterial soft rot is one of the most devastating diseases and a major constraint encountered during carrot farming. Biological agents are the best eco-friendly alternatives to agrochemicals to manage soft rot disease to ensure environmental sustainability. In this study, about eight isolates of bacterial pathogen causing soft rot in carrots were collected from Karnataka, India. Based on the 16S rRNA sequencing the pathogen isolates causing soft rot of carrot were identified as Klebsiella variicola. The morphological characteristics of K. variicola was investigated under scanning electron microscopy. The pathogenicity assay showed that all eight isolates were pathogenic to the carrot. An in vitro and in planta assay of two novel strains of Bacillus velezensis (A6 and P42) against K. variicola indicated that both strains had strong antagonistic activity against all the pathogen strains. Furthermore, the volatile bioactive compounds produced by A6 and P42 strains were analyzed in GC-MS, which revealed the presence of 10 and 6 bioactive compounds in their culture filtrate, respectively, with antibacterial and antifungal properties. The present study suggests that both A6 and P42 strains of B. velezensis were antagonistic to K. variicola and can be used as biocontrol agents to manage soft rot diseases of carrot under field conditions.

Generation methods, stability, detection techniques, and applications of bulk nanobubbles in agro-food industries: a review and future perspective.

Nanobubble (NB) technologies have received considerable attention for various applications due to their low cost, eco-friendliness, scale-up potential, process control, and unique physical characteristics. NB stands for nanoscopic gaseous cavities, typically <1 µm in diameter. NBs can exist on surfaces (surface or interfacial NBs) and be dispersed in a bulk liquid phase (bulk NBs). Compared to the microbubbles, NBs exhibit high specific surface area, negative surface charge, and better adsorption. Bulk NBs can be generated by hydrodynamic/acoustic cavitation, electrolysis, water-solvent mixing, nano-membrane filtration, and so on. NBs exhibit extraordinary longevity compared to microbubbles, prompting the interest of the scientific community aiming for potential applications including medicine, agriculture, food, wastewater treatment, surface cleaning, and so on. Based on the limited amount of research work available regarding the influence of NBs on food matrices, further research, however, needs to be done to provide more insights into its applications in food industries. This review provides an overview of the generation methods for NBs, techniques to evaluate them, and a discussion of their stability and several applications in various fields of science were discussed. However, recent studies have revealed that, despite the many benefits of NB technologies, several NB generating approaches are still limited in their application in specific agro-food industries. Further study should focus on process optimization, integrating various NB generation techniques/combining with other emerging technologies in order to achieve rapid technical progress and industrialization of NB-based technologies.HighlightsNanobubbles (NBs) are stable spherical entities of gas within liquid and are operationally defined as having diameters less than 1 µm.Currently, various reported theories still lack the ability to explain the evidence and stability of NBs in water, numerous NB applications have emerged due to the unique properties of NBs.NB technologies can be applied to various food and dairy products (e.g. yogurt and ice cream) and other potential applications, including agriculture (e.g. seed germination and plant growth), wastewater treatment, surface cleaning, and so on.

Potential Drug-Drug Interactions Between Anti-Cancer Drugs and Other Medications in Lung Cancer Patients: A Retrospective Study.

BACKGROUND: Cancer patients are more vulnerable to developing drug-drug interactions as multiple medications are administered concomitantly with cytotoxic agents to treat the underlying comorbidities. These drug-drug interactions often receive less medical attention and consequently are associated with adverse clinical outcomes. OBJECTIVE: We intended to comprehensively characterize the drug-drug interactions among anticancer drugs and other concomitantly prescribed drugs in hospitalized lung cancer patients. METHODS: A retrospective, observational, single-centre study was conducted on lung cancer inpatients from the medical records department of Kasturba Hospital, Manipal, India. Drug-drug interactions were identified using the drug interaction checkers of two drug information databases, Micromedex and Epocrates. These drug-drug interactions were categorized based on the source from which they were identified, mechanism, severity/significance, adverse consequences, and management strategies required. RESULTS: Among 196 patients, 555 drug-drug interactions were identified in 185 patients using Micromedex and Epocrates. Based on the mechanism of action, 74% and 22% of the drug-drug interactions were classified as pharmacodynamic and pharmacokinetic respectively. 112 drug-drug interactions were recorded from Micromedex alone, while 549 interactions were found using Epocrates. The oral chemotherapeutic drug gefitinib was found to be associated with the highest number of drug-drug interactions. CONCLUSION: Drug-drug interactions were highly prevalent among hospitalized lung cancer patients. Structured screening and monitoring for these potentially clinically relevant drug-drug interactions by oncologists in collaboration with clinical pharmacists should be carried out prior to initiation and during anticancer treatment to prevent adverse clinical outcomes.

Randomized Control Study of the Effects of Turmeric Mouthwash on Oral Health Status, Treatment-Induced Mucositis, and Associated Oral Dysfunctions Among Patients With Head and Neck Cancer.

BACKGROUND: Oral mucositis is the most severe and debilitating adverse effect of cancer treatment, resulting in inadequate nutritional intake, treatment disruptions, and dose alteration, leading to increased hospital costs and decreased tumor control. OBJECTIVE: The aim of this study was to determine the effectiveness of turmeric mouthwash on oral health status and onset and severity of treatment-induced oral mucositis and associated oral dysfunctions among head and neck cancer patients. METHODS: A randomized controlled design was adopted (CTRI/2018/06/014367). Turmeric mouthwash was administered to the experimental group (n = 46) and benzydamine mouthwash was given to the control group (n = 46). Oral health status and mucositis were graded using the Oral Health Assessment Tool and the World Health Organization oral toxicity criteria, respectively. Oral dysfunctions were measured by a patient-reported oral mucositis symptom scale and xerostomia short-form inventory. All outcome variables were measured weekly during the entire course of radiation therapy. RESULTS: Both groups were comparable with regard to their demographic and outcome variables ( P > .05). The incidence of intolerable mucositis in the control group was 100% compared with 17.8% in the experimental group. Repeated-measures analysis of variance demonstrated significant differences in the onset and severity of oral mucositis ( P = .001), oral health status ( P = .001), and oral dysfunctions ( P = .001) between the experimental and control groups. CONCLUSION: Turmeric mouthwash was effective in reducing the severity of oral mucositis and associated oral dysfunctions as compared with benzydamine mouthwash. IMPLICATIONS: Use of turmeric, a nontoxic and cost-effective intervention, can be an alternative to the traditional management of oral mucositis.

A 1-Pot Synthesis of the SARS-CoV-2 Mpro Inhibitor Nirmatrelvir, the Key Ingredient in Paxlovid.

A newly devised route to the Pfizer drug nirmatrelvir is reported that reduces the overall sequence to a 1-pot process and relies on a commercially available, green coupling reagent, T3P. The overall yield of the targeted material, isolated as its MTBE solvate, is 64%.

A sustainable synthesis of the SARS-CoV-2 Mpro inhibitor nirmatrelvir, the active ingredient in Paxlovid.

Pfizer's drug for the treatment of patients infected with COVID-19, Paxlovid, contains most notably nirmatrelvir, along with ritonavir. Worldwide demand is projected to be in the hundreds of metric tons per year, to be produced by several generic drug manufacturers. Here we show a 7-step, 3-pot synthesis of the antiviral nirmatrelvir, arriving at the targeted drug in 70% overall yield. Critical amide bond-forming steps utilize new green technology that completely avoids traditional peptide coupling reagents, as well as epimerization of stereocenters. Likewise, dehydration of a primary amide to the corresponding nitrile is performed and avoids use of the Burgess reagent and chlorinated solvents. DFT calculations for various conformers of nirmatrelvir predict that two rotamers about the tertiary amide would be present with an unusually high rotational barrier. Direct comparisons with the original literature procedures highlight both the anticipated decrease in cost and environmental footprint associated with this route, potentially expanding the availability of this important drug worldwide.

Endogenous protein interactomes resolved through immunoprecipitation-coupled quantitative proteomics in cell lines.

Immunoprecipitation (IP) of endogenously expressed proteins is one of the most biologically relevant techniques to identify protein-protein interactions. We describe an adaptable IP protocol reliant on a specific antibody to the target protein. We detail a quantitative proteomics workflow for the unbiased identification of co-immunoprecipitating proteins, known collectively as an interactome. This includes protocols for the tryptic digestion, Tandem Mass Tag labeling and fractionation of peptides, and their identification and quantification using liquid chromatography-mass spectrometry including computational and statistical analysis. For complete details on the use and execution of this protocol, please refer to Johnson et al. (2020).