Antineoplastics for treating Alzheimer's disease and dementia: Evidence from preclinical and observational studies.

As the world population ages, there will be an increasing need for effective therapies for aging-associated neurodegenerative disorders, which remain untreatable. Dementia due to Alzheimer's disease (AD) is one of the leading neurological diseases in the aging population. Current therapeutic approaches to treat this disorder are solely symptomatic, making the need for new molecular entities acting on the causes of the disease extremely urgent. One of the potential solutions is to use compounds that are already in the market. The structures have known pharmacokinetics, pharmacodynamics, toxicity profiles, and patient data available in several countries. Several drugs have been used successfully to treat diseases different from their original purposes, such as autoimmunity and peripheral inflammation. Herein, we divulge the repurposing of drugs in the area of neurodegenerative diseases, focusing on the therapeutic potential of antineoplastics to treat dementia due to AD and dementia. We briefly touch upon the shared pathological mechanism between AD and cancer and drug repurposing strategies, with a focus on artificial intelligence. Next, we bring out the current status of research on the development of drugs, provide supporting evidence from retrospective, clinical, and preclinical studies on antineoplastic use, and bring in new areas, such as repurposing drugs for the prion-like spreading of pathologies in treating AD.

Salting-Out-Assisted Liquid-Liquid Extraction Method for the Determination of Nicotine from Oral Traditional and Innovative Tobacco Products Using UPLC-MS/MS.

In this study, we developed and validated a novel method that allows for the extraction and quantitation of nicotine from a variety of commercially available oral tobacco products including loose and pouched traditional moist smokeless tobacco products, and oral tobacco-derived nicotine (OTDN) lozenges, gums, and pouches. The method employed an extraction technique consisting of salting-out assisted liquid-liquid extraction using sodium hydroxide and acetonitrile in conjunction with ultra-high pressure liquid chromatography coupled to mass spectrometry. Accurate quantitation was obtained using nicotine methyl-d3 isotopically labeled internal standard. Chromatographic separation of nicotine and nicotine methyl-d3 internal standard was achieved using a Waters Acquity C18 column (50 mm × 2.1 mm i.d., 2.5 µm) with 10 mM ammonium acetate buffer (pH = 10) and acetonitrile as mobile phase A and B, respectively. Using a gradient elution and a flow rate of 0.4 mL/min for 5 min runtime, nicotine eluted at 1.74 min. The method was validated according to ICH guidelines for all the sample types with an accuracy for nicotine within 89-109%. Repeatability and intermediate precision were both estimated to be ≤7% relative standard deviation (% RSD). This method is applicable for a wide range of traditional moist smokeless and OTDN tobacco products.

BaPreS: a software tool for predicting bacteriocins using an optimal set of features.

BACKGROUND: Antibiotic resistance is a major public health concern around the globe. As a result, researchers always look for new compounds to develop new antibiotic drugs for combating antibiotic-resistant bacteria. Bacteriocin becomes a promising antimicrobial agent to fight against antibiotic resistance, due to cases of both broad and narrow killing spectra. Sequence matching methods are widely used to identify bacteriocins by comparing them with the known bacteriocin sequences; however, these methods often fail to detect new bacteriocin sequences due to their high diversity. The ability to use a machine learning approach can help find new highly dissimilar bacteriocins for developing highly effective antibiotic drugs. The aim of this work is to develop a machine learning-based software tool called BaPreS (Bacteriocin Prediction Software) using an optimal set of features for detecting bacteriocin protein sequences with high accuracy. We extracted potential features from known bacteriocin and non-bacteriocin sequences by considering the physicochemical and structural properties of the protein sequences. Then we reduced the feature set using statistical justifications and recursive feature elimination technique. Finally, we built support vector machine (SVM) and random forest (RF) models using the selected features and utilized the best machine learning model to implement the software tool. RESULTS: We applied BaPreS to an established dataset and evaluated its prediction performance. Acquired results show that the software tool can achieve a prediction accuracy of 95.54% for testing protein sequences. This tool allows users to add new bacteriocin or non-bacteriocin sequences in the training dataset to further enhance the predictive power of the tool. We compared the prediction performance of the BaPreS with a popular sequence matching-based tool and a deep learning-based method, and our software tool outperformed both. CONCLUSIONS: BaPreS is a bacteriocin prediction tool that can be used to discover new highly dissimilar bacteriocins for developing highly effective antibiotic drugs. This software tool can be used with Windows, Linux and macOS operating systems. The open-source software package and its user manual are available at https://github.com/suraiya14/BaPreS .

Synthesis and Structure-Activity Relationship Studies of C(13)-Desmethylene-(-)-Zampanolide Analogs.

We describe the synthesis and biochemical and cellular profiling of five partially reduced or demethylated analogs of the marine macrolide (-)-zampanolide (ZMP). These analogs were derived from 13-desmethylene-(-)-zampanolide (DM-ZMP), which is an equally potent cancer cell growth inhibitor as ZMP. Key steps in the synthesis of all compounds were the formation of the dioxabicyclo[15.3.1]heneicosane core by an intramolecular HWE reaction (67-95 % yield) and a stereoselective aza-aldol reaction with an (S)-BINOL-derived sorbamide transfer complex, to establish the C(20) stereocenter (24-71 % yield). As the sole exception, for the 5-desmethyl macrocycle, ring-closure relied on macrolactonization; however, elaboration of the macrocyclization product into the corresponding zampanolide analog was unsuccessful. All modifications led to reduced cellular activity and lowered microtubule-binding affinity compared to DM-ZMP, albeit to a different extent. For compounds incorporating the reactive enone moiety of ZMP, IC50 values for cancer cell growth inhibition varied between 5 and 133 nM, compared to 1-12 nM for DM-ZMP. Reduction of the enone double bond led to a several hundred-fold loss in growth inhibition. The cellular potency of 2,3-dihydro-13-desmethylene zampanolide, as the most potent analog identified, remained within a ninefold range of that of DM-ZMP.

BPAGS: a web application for bacteriocin prediction via feature evaluation using alternating decision tree, genetic algorithm, and linear support vector classifier.

The use of bacteriocins has emerged as a propitious strategy in the development of new drugs to combat antibiotic resistance, given their ability to kill bacteria with both broad and narrow natural spectra. Hence, a compelling requirement arises for a precise and efficient computational model that can accurately predict novel bacteriocins. Machine learning's ability to learn patterns and features from bacteriocin sequences that are difficult to capture using sequence matching-based methods makes it a potentially superior choice for accurate prediction. A web application for predicting bacteriocin was created in this study, utilizing a machine learning approach. The feature sets employed in the application were chosen using alternating decision tree (ADTree), genetic algorithm (GA), and linear support vector classifier (linear SVC)-based feature evaluation methods. Initially, potential features were extracted from the physicochemical, structural, and sequence-profile attributes of both bacteriocin and non-bacteriocin protein sequences. We assessed the candidate features first using the Pearson correlation coefficient, followed by separate evaluations with ADTree, GA, and linear SVC to eliminate unnecessary features. Finally, we constructed random forest (RF), support vector machine (SVM), decision tree (DT), logistic regression (LR), k-nearest neighbors (KNN), and Gaussian naïve Bayes (GNB) models using reduced feature sets. We obtained the overall top performing model using SVM with ADTree-reduced features, achieving an accuracy of 99.11% and an AUC value of 0.9984 on the testing dataset. We also assessed the predictive capabilities of our best-performing models for each reduced feature set relative to our previously developed software solution, a sequence alignment-based tool, and a deep-learning approach. A web application, titled BPAGS (Bacteriocin Prediction based on ADTree, GA, and linear SVC), was developed to incorporate the predictive models built using ADTree, GA, and linear SVC-based feature sets. Currently, the web-based tool provides classification results with associated probability values and has options to add new samples in the training data to improve the predictive efficacy. BPAGS is freely accessible at https://shiny.tricities.wsu.edu/bacteriocin-prediction/.

UHPLC-MS/MS method for the simultaneous determination of nicotine and tobacco-specific nitrosamines NNN and NNK for use in preclinical studies.

A new method was developed and validated for the simultaneous determination of nicotine and tobacco-specific nitrosamines (TSNAs) 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N-nitrosonornicotine (NNN) in two different tests matrices: porcine buccal epithelium tissue and phosphate buffered saline (PBS) extracts of smokeless tobacco products. The novelty of this work is in the development of a liquid chromatography tandem mass spectrometry method that can provide simultaneous quantification of trace levels of TSNAs and high concentrations of nicotine in biological media. Precision, accuracy, and stability were evaluated during method validation to ensure the method was fit for purpose. Several sample preparation and extraction methods were evaluated to minimize matrix effects and maximize analyte recoveries. The method was accurate in the range of 81.1% - 117%; repeatability was estimated in the range of 1.5% - 13.6% across multiple concentrations. The linear regression correlation coefficient (R2) was greater than 0.9959 for all analytes, and the limit of detection (LOD) was determined for nicotine, NNK, and NNN at 1 ng/mL 0.005 ng/mL, and 0.006 ng/ mL, respectively. Our method was found to be appropriate for the analysis of nicotine, NNN, and NNK in the porcine buccal epithelium and PBS extracts of smokeless tobacco products.

Synthesis of Novel Glycolipid Mimetics of Heparan Sulfate and Their Application in Colorectal Cancer Treatment in a Mouse Model.

Heparan sulfate (HS) is a highly sulfated natural carbohydrate that plays crucial roles in cancer, inflammation, and angiogenesis. Heparanase (HPSE) is the sole HS degrading endoglycosidase that cleaves HS at structure-dependent sites along the polysaccharide chain. Overexpression of HPSE by cancer cells correlates with increased tumor size and enhanced metastasis. Previously we have shown that a tetramer HS mimetic is a potent HPSE inhibitor displaying remarkable anticancer activity in vivo. Building on that work, we report the synthesis and testing of a novel library of single entity trimer glycolipid mimetics that effectively inhibit HPSE at low nanomolar concentrations. A lipophilic arm was introduced to assess whether an improvement of pharmacokinetics and plasma residence time would offset the reduction in charge and multivalency. Preclinical tests in a mouse syngeneic model showed effective tumor growth inhibition by the tetramer but not the trimer glycomimetic.

Deep ancestry of collapsing networks of nomadic hunter-gatherers in Borneo.

Theories of early cooperation in human society often draw from a small sample of ethnographic studies of surviving populations of hunter-gatherers, most of which are now sedentary. Borneo hunter-gatherers (Punan, Penan) have seldom figured in comparative research because of a decades-old controversy about whether they are the descendants of farmers who adopted a hunting and gathering way of life. In 2018 we began an ethnographic study of a group of still-nomadic hunter-gatherers who call themselves Punan Batu (Cave Punan). Our genetic analysis clearly indicates that they are very unlikely to be the descendants of neighbouring agriculturalists. They also preserve a song language that is unrelated to other languages of Borneo. Dispersed travelling groups of Punan Batu with fluid membership use message sticks to stay in contact, co-operate and share resources as they journey between rock shelters and forest camps. Message sticks were once widespread among nomadic Punan in Borneo, but have largely disappeared in sedentary Punan villages. Thus the small community of Punan Batu offers a rare glimpse of a hunting and gathering way of life that was once widespread in the forests of Borneo, where prosocial behaviour extended beyond the face-to-face community, facilitating successful collective adaptation to the diverse resources of Borneo's forests.

Cultural drift, indirect minority influence, network structure, and their impacts on cultural change and diversity.

The present research investigates how psychological mechanisms and social network structures generate patterns of cultural change and diversity. The two psychological mechanisms studied here are cultural drift and indirect minority influence; the former is parameterized by an error rate ε) and the latter by a leniency threshold (λ). The patterns of cultural change are examined in terms of magnitude (small vs. large), speed (gradual vs. rapid), and frequency (frequent vs. rare). Diversity and polarization in a society are examined in terms of global cultural variation (inverse Simpson index) and local neighborhood difference (Hamming distance). Key findings are that in networks with high connectivity or local community structures (complete, scale-free, random, and modular networks) cultural drift can produce a rapid, large, and rare pattern of cultural change (punctuated equilibrium), whereas in lattice or small world networks, it produces a more gradual change pattern. Indirect minority influence robustly produces a gradual, small, and frequent pattern of cultural change (gradualism) across various network structures. When cultural change occurs in social networks that have a modular community structure, indirect minority influence generates a regime of cultural diversity whereas cultural drift generates a polarized regime. Finally, cultural drift and indirect minority influence generate distinct tipping points for social change in different network structures, but prediction of whether and when cultural change emerges is difficult at tipping points in both cases. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

ßIII-tubulin overexpression in cancer: Causes, consequences, and potential therapies.

Class III ß-tubulin (ßIII-tubulin) is frequently overexpressed in human tumors and is associated with resistance to microtubule-targeting agents, tumor aggressiveness, and poor patient outcome. Understanding the mechanisms regulating ßIII-tubulin expression and the varied functions ßIII-tubulin may have in different cancers is vital to assess the prognostic value of this protein and to develop strategies to enhance therapeutic benefits in ßIII-tubulin overexpressing tumors. Here we gather all the available evidence regarding the clinical implications of ßIII-tubulin overexpression in cancer, describe factors that regulate ßIII-tubulin expression, and discuss current understanding of the mechanisms underlying ßIII-tubulin-mediated resistance to microtubule-targeting agents and tumor aggressiveness. Finally, we provide an overview of emerging therapeutic strategies to target tumors that overexpress ßIII-tubulin.

A 6-month inhalation toxicology study in Apoe-/- mice demonstrates substantially lower effects of e-vapor aerosol compared with cigarette smoke in the respiratory tract.

Cigarette smoking is the major cause of chronic obstructive pulmonary disease. Considerable attention has been paid to the reduced harm potential of nicotine-containing inhalable products such as electronic cigarettes (e-cigarettes). We investigated the effects of mainstream cigarette smoke (CS) and e-vapor aerosols (containing nicotine and flavor) generated by a capillary aerosol generator on emphysematous changes, lung function, and molecular alterations in the respiratory system of female Apoe-/- mice. Mice were exposed daily (3 h/day, 5 days/week) for 6 months to aerosols from three different e-vapor formulations-(1) carrier (propylene glycol and vegetable glycerol), (2) base (carrier and nicotine), or (3) test (base and flavor)-or to CS from 3R4F reference cigarettes. The CS and base/test aerosol concentrations were matched at 35 µg nicotine/L. CS exposure, but not e-vapor exposure, led to impairment of lung function (pressure-volume loop area, A and K parameters, quasi-static elastance and compliance) and caused marked lung inflammation and emphysematous changes, which were confirmed histopathologically and morphometrically. CS exposure caused lung transcriptome (activation of oxidative stress and inflammatory responses), lipidome, and proteome dysregulation and changes in DNA methylation; in contrast, these effects were substantially reduced in response to the e-vapor aerosol exposure. Compared with sham, aerosol exposure (carrier, base, and test) caused a slight impact on lung inflammation and epithelia irritation. Our results demonstrated that, in comparison with CS, e-vapor aerosols induced substantially lower biological and pathological changes in the respiratory tract associated with chronic inflammation and emphysema.

The mixed kappa and delta opioid receptor agonist, MP1104, attenuates chemotherapy-induced neuropathic pain.

Effective treatments for chronic pain without abuse liability are urgently needed. One in 5 adults suffer chronic pain and half of these patients report inefficient treatment. Mu opioid receptor agonists (MOP), including oxycodone, tramadol and morphine, are often prescribed to treat chronic pain, however, use of drugs targeting MOP can lead to drug dependency, tolerance and overdose deaths. Kappa opioid receptor (KOP) agonists have antinociceptive effects without abuse potential; however, they have not been utilised clinically due to dysphoria and sedation. We hypothesise that mixed opioid receptor agonists targeting the KOP and delta opioid receptor (DOP) would have a wider therapeutic index, with the rewarding effects of DOP negating the negative effects of KOP. MP1104, an analogue of 3-Iodobenzoyl naltrexamine, is a novel mixed opioid receptor agonist with potent antinociceptive effects mediated via KOP and DOP in mice without rewarding or aversive effects. In this study, we show MP1104 has potent, long-acting antinociceptive effects in the warm-water tail-withdrawal assay in male and female mice and rats; and is longer acting than morphine. In the paclitaxel-induced neuropathic pain model in mice, MP1104 reduced both mechanical and cold allodynia and unlike morphine, did not produce tolerance when administered daily for 23 days. Moreover, MP1104 did not induce sedative effects in the open-field locomotor activity test, respiratory depression in mice using whole-body plethysmography, or have cross-tolerance with morphine. This data supports the therapeutic development of mixed opioid receptor agonists, particularly mixed KOP/DOP agonists, as non-addictive pain medications with reduced tolerance.

2D Hexagonal Boron Nitride-Coated Cotton Fabric with Self-Extinguishing Property.

Here, we report on the fabrication of flame retardant hydrophobic cotton fabrics based on the coating with two-dimensional hexagonal boron nitride (2D hBN) nanosheets. A simple one-step solution dipping process was used to coat the fabrics by taking advantage of the strong bonding between diethylenetriamine and hBN on the cotton surface. Exposure to direct flame confirmed the improvement of the flame retardant properties of the coated cotton fabrics. In turn, removal of the flame source revealed self-extinguishing properties. Molecular dynamics simulations indicate that hBN hinders combustion by reducing the rate at which oxygen molecules reach the cotton surface. This time-saving and one-step approach for the fabrication of flame-retardant cotton fabrics offers significant advantages over other, less efficient production methods.

Potential for Treatment of Neurodegenerative Diseases with Natural Products or Synthetic Compounds that Stabilize Microtubules.

No effective therapeutics to treat neurodegenerative diseases exist, despite significant attempts to find drugs that can reduce or rescue the debilitating symptoms of tauopathies such as Alzheimer's disease, Parkinson's disease, frontotemporal dementia, amyotrophic lateral sclerosis, or Pick's disease. A number of in vitro and in vivo models exist for studying neurodegenerative diseases, including cell models employing induced-pluripotent stem cells, cerebral organoids, and animal models of disease. Recent research has focused on microtubulestabilizing agents, either natural products or synthetic compounds that can prevent the axonal destruction caused by tau protein pathologies. Although promising results have come from animal model studies using brainpenetrant natural product microtubule-stabilizing agents, such as paclitaxel analogs that can access the brain, epothilones B and D, and other synthetic compounds such as davunetide or the triazolopyrimidines, early clinical trials in humans have been disappointing. This review aims to summarize the research that has been carried out in this area and discuss the potential for the future development of an effective microtubule stabilizing drug to treat neurodegenerative disease.

Method development and validation of dissolution testing for nicotine release from smokeless tobacco products using flow-through cell apparatus and UPLC-PDA.

Developing dissolution testing methods to measure the nicotine release profiles from smokeless tobacco products is valuable for product assessment and product-to-product comparisons. In this work, we developed a robust dissolution method to study the in vitro release of nicotine from smokeless tobacco products using the U.S. Pharmacopeia flow-through cell dissolution apparatus 4 (USP-4). We further developed and validated a sensitive Ultra Performance Liquid Chromatography coupled to Photodiode Array detector (UPLC-PDA) method for the accurate quantitation of the released nicotine into artificial saliva, which is our selected dissolution medium. We have successfully shown the applicability of the validated method by investigating the release profiles of nicotine from various commercial and CORESTA reference smokeless tobacco products [CRP 1.1 (Swedish-style snus pouch), CRP 2.1 (American-style loose moist snuff), CRP 4 (loose-leaf chewing tobacco) and CRP 4.1 (chopped loose-leaf chewing tobacco)]. Nicotine release profiles were analyzed by calculating the difference factor (f1) and similarity factor (f2) by adopting a methodology referenced in the Guidance for Industry from FDA's Center for Drug Evaluation and Research (CDER) and by fitting the release profile curves using a first order kinetic model. Nicotine release was found to be dependent on the form and cut of the smokeless tobacco products, with a slower release observed for snus and loose-leaf, compared to chopped and loose moist snuff smokeless tobacco. This dissolution methodology can be extended to measure and compare release of other constituents from smokeless tobacco products and has the potential for method standardization.

Possible transport evidence for three-dimensional topological superconductivity in doped ß-PdBi2.

Interest in topological states of matter burgeoned over a decade ago with the theoretical prediction and experimental detection of topological insulators, especially in bulk three-dimensional insulators that can be tuned out of it by doping. Their superconducting counterpart, the fully-gapped three-dimensional time-reversal-invariant topological superconductors, have evaded discovery in bulk intrinsic superconductors so far. The recently discovered topological metal ß-PdBi2 is a unique candidate for tunable bulk topological superconductivity because of its intrinsic superconductivity and spin-orbit-coupling. In this work, we provide experimental transport signatures consistent with fully-gapped 3D time-reversal-invariant topological superconductivity in K-doped ß-PdBi2. In particular, we find signatures of odd-parity bulk superconductivity via upper-critical field and magnetization measurements- odd-parity pairing can be argued, given the band structure of ß-PdBi2, to result in 3D topological superconductivity. In addition, Andreev spectroscopy reveals surface states protected by time-reversal symmetry which might be possible evidence of Majorana surface states (Majorana cone). Moreover, we find that the undoped bulk system is a trivial superconductor. Thus, we discover ß-PdBi2 as a unique bulk material that, on doping, can potentially undergo an unprecedented topological quantum phase transition in the superconducting state.

Macrophage phenotype bioengineered by magnetic, genetic, or pharmacologic interference.

In all eukaryotes, the cell shape depends on the actin filament cytoskeleton, which is regulated by the small GTPase RhoA. It is well known that the cell shape determines cell function and behavior. Inversely, any change in the cell behavior and/or function reverberates at the cell shape. In this review, we describe how mechanical/magnetic, genetic, or pharmacologic interference with the actin cytoskeleton enforces changes in cell shape and function and how such techniques can be used to control the phenotype and functions of immune cells such as macrophages and to develop novel anti-cancer and anti-rejection clinical therapies.

Synthesis of Bioactive Side-Chain Analogues of TAN-2483B.

The fungal metabolite TAN-2483B has a 2,6-trans-relationship across the pyran ring of its furo[3,4-b]pyran-5-one core, which has thwarted previous attempts at its synthesis. We have now developed a chiral pool approach to this core and prepared side-chain analogues of TAN-2483B. The synthesis relies on ring expansion of a reactive furan ring-fused dibromocyclopropane and alkynylation of the resulting pyran. The furan ring is constructed by palladium-catalysed carbonylative lactonisation. Various side-chains are appended through Wittig-type chemistry. The prepared analogues showed micromolar activity towards cancer cell lines HL-60, 1A9 and MCF-7 and certain human disease-relevant kinases, including Bruton's tyrosine kinase (Btk).

Kinetic understanding of nitrogen supply condition on biosynthesis of polyhydroxyalkanoate from benzoate by Pseudomonas putida KT2440.

Nitrogen supply is critical to the synthesis of intracellular PHA in various bacteria. However, the specific role of the nitrogen in synthesizing PHA from benzoate, a lignin model compound use for the study of bacteria catabolism of aromatics, is still not clear. In this study, two culture conditions were maintained for Pseudomonas putida KT2440 to produce PHA using benzoate as a carbon source. Under nitrogen-limited and surplus conditions, the accumulation of PHA was to 37.3% and 0.25% of cell dry weight, respectively. A model fit to the kinetics of biomass growth and PHA accumulation showed good agreement with data. GC-MS and NMR showed that PHA contained six hydroxyl fatty acid monomers under nitrogen-limited conditions, while two monomers were identified under nitrogen surplus conditions. The average molecular weight of PHA increased after the nitrogen source was exhausted. These results provide a promising strategy for optimization of lignin to PHA yields.