Synthesis, kinetic studies, and QSAR of dinucleoside polyphosphate derivatives as human AK1 inhibitors.

Adenylate kinase (AK) plays a crucial role in the metabolic monitoring of cellular adenine nucleotide homeostasis by catalyzing the reversible transfer of a phosphate group between ATP and AMP, yielding two ADP molecules. By regulating the nucleotide levels and energy metabolism, the enzyme is considered a disease modifier and potential therapeutic target for various human diseases, including malignancies and inflammatory and neurodegenerative disorders. However, lacking approved drugs targeting AK hinders broad studies on this enzyme's pathological importance and therapeutic potential. In this work, we determined the effect of a series of dinucleoside polyphosphate derivatives, commercially available (11 compounds) and newly synthesized (8 compounds), on the catalytic activity of human adenylate kinase isoenzyme 1 (hAK1). The tested compounds belonged to the following groups: (1) diadenosine polyphosphates with different phosphate chain lengths, (2) base-modified derivatives, and (3) phosphate-modified derivatives. We found that all the investigated compounds inhibited the catalytic activity of hAK1, yet with different efficiencies. Three dinucleoside polyphosphates showed IC50 values below 1 µM, and the most significant inhibitory effect was observed for P1-(5'-adenosyl) P5-(5'-adenosyl) pentaphosphate (Ap5A). To understand the observed differences in the inhibition efficiency of the tested dinucleoside polyphosphates, the molecular docking of these compounds to hAK1 was performed. Finally, we conducted a quantitative structure-activity relationship (QSAR) analysis to establish a computational prediction model for hAK1 modulators. Two PLS-regression-based models were built using kinetic data obtained from the AK1 activity analysis performed in both directions of the enzymatic reaction. Model 1 (AMP and ATP synthesis) had a good prediction power (R2 = 0.931, Q2 = 0.854, and MAE = 0.286), while Model 2 (ADP synthesis) exhibited a moderate quality (R2 = 0.913, Q2 = 0.848, and MAE = 0.370). These studies can help better understand the interactions between dinucleoside polyphosphates and adenylate kinase to attain more effective and selective inhibitors in the future.

Trinucleotide mRNA Cap Analogue N6-Benzylated at the Site of Posttranscriptional m6Am Mark Facilitates mRNA Purification and Confers Superior Translational Properties In Vitro and In Vivo.

Eukaryotic mRNAs undergo cotranscriptional 5'-end modification with a 7-methylguanosine cap. In higher eukaryotes, the cap carries additional methylations, such as m6Am─a common epitranscriptomic mark unique to the mRNA 5'-end. This modification is regulated by the Pcif1 methyltransferase and the FTO demethylase, but its biological function is still unknown. Here, we designed and synthesized a trinucleotide FTO-resistant N6-benzyl analogue of the m6Am-cap-m7GpppBn6AmpG (termed AvantCap) and incorporated it into mRNA using T7 polymerase. mRNAs carrying Bn6Am showed several advantages over typical capped transcripts. The Bn6Am moiety was shown to act as a reversed-phase high-performance liquid chromatography (RP-HPLC) purification handle, allowing the separation of capped and uncapped RNA species, and to produce transcripts with lower dsRNA content than reference caps. In some cultured cells, Bn6Am mRNAs provided higher protein yields than mRNAs carrying Am or m6Am, although the effect was cell-line-dependent. m7GpppBn6AmpG-capped mRNAs encoding reporter proteins administered intravenously to mice provided up to 6-fold higher protein outputs than reference mRNAs, while mRNAs encoding tumor antigens showed superior activity in therapeutic settings as anticancer vaccines. The biochemical characterization suggests several phenomena potentially underlying the biological properties of AvantCap: (i) reduced propensity for unspecific interactions, (ii) involvement in alternative translation initiation, and (iii) subtle differences in mRNA impurity profiles or a combination of these effects. AvantCapped-mRNAs bearing the Bn6Am may pave the way for more potent mRNA-based vaccines and therapeutics and serve as molecular tools to unravel the role of m6Am in mRNA.

Management and conservation implications of cryptic population substructure for two commercially exploited fishes (Merluccius spp.) in southern Africa.

Genomic information can aid in the establishment of sustainable management plans for commercially exploited marine fishes, aiding in the long-term conservation of these resources. The southern African hakes (Merluccius capensis and M. paradoxus) are commercially valuable demersal fishes with similar distribution ranges but exhibiting contrasting life histories. Using a comparative framework based on Pool-Seq genome-wide SNP data, we investigated whether the evolutionary processes that shaped extant patterns of diversity and divergence are shared among these two congeneric fishes, or unique to each one. Our findings revealed that M. capensis and M. paradoxus show similar levels of genome-wide diversity, despite different census sizes and life-history features. In addition, M. capensis shows three highly structured geographic populations across the Benguela Current region (one in the northern Benguela and two in the southern Benguela), with no consistent genome-environment associations detected. In contrast, although population structure and outlier analyses suggested panmixia for M. paradoxus, reconstruction of its demographic history suggested the presence of an Atlantic-Indian Ocean subtle substructuring pattern. Therefore, it appears that M. paradoxus might be composed by two highly connected populations, one in the Atlantic and one in the southwest Indian Ocean. The reported similar low levels of genomic diversity, as well as newly discovered genetically distinct populations in both hake species can thus assist in informing and improving conservation and management plans for the commercially important southern African Merluccius.

Long-term in vivo degradation of Mg-Zn-Ca elastic stable intramedullary nails and their influence on the physis of juvenile sheep.

The use of bioresorbable magnesium (Mg)-based elastic stable intramedullary nails (ESIN) is highly promising for the treatment of pediatric long-bone fractures. Being fully resorbable, a removal surgery is not required, preventing repeated physical and psychological stress for the child. Further, the osteoconductive properties of the material support fracture healing. Nowadays, ESIN are exclusively implanted in a non-transphyseal manner to prevent growth discrepancies, although transphyseal implantation would often be required to guarantee optimized fracture stabilization. Here, we investigated the influence of trans-epiphyseally implanted Mg-Zinc (Zn)-Calcium (Ca) ESIN on the proximal tibial physis of juvenile sheep over a period of three years, until skeletal maturity was reached. We used the two alloying systems ZX10 (Mg-1Zn-0.3Ca, in wt%) and ZX00 (Mg-0.3Zn-0.4Ca, in wt%) for this study. To elaborate potential growth disturbances such as leg-length differences and axis deviations we used a combination of in vivo clinical computed tomography (cCT) and ex vivo micro CT (µCT), and also performed histology studies on the extracted bones to obtain information on the related tissue. Because there is a lack of long-term data regarding the degradation performance of magnesium-based implants, we used cCT and µCT data to evaluate the implant volume, gas volume and degradation rate of both alloying systems over a period of 148 weeks. We show that transepiphyseal implantation of Mg-Zn-Ca ESIN has no negative influence on the longitudinal bone growth in juvenile sheep, and that there is no axis deviation observed in all cases. We also illustrate that 95 % of the ESIN degraded over nearly three years, converging the time point of full resorption. We thus conclude that both, ZX10 and ZX00, constitute promising implant materials for the ESIN technique.

Cognitive CAPTCHA Password Reminder.

In recent years, the number of personal accounts assigned to one business user has been constantly growing. There could be as many as 191 individual login credentials used by an average employee, according to a 2017 study. The most recurrent problems associated with this situation faced by users are the strength of passwords and ability to recall them. Researchers have proven that "users are aware of what constitutes a secure password but may forgo these security measures in terms of more convenient passwords, largely depending on account type". Reusing the same password across multiple platforms or creating one with dictionary words has also been proved to be a common practice amongst many. In this paper, a novel password-reminder scheme will be presented. The goal was that the user creates a CAPTCHA-like image with a hidden meaning, that only he or she can decode. The image must be in some way related to that individual's memory or her/his unique knowledge or experience. With this image, being presented each time during logging in, the user is asked to associate a password consisting of two or more words and a number. If the image is selected properly and strong association with a person's visual memory has been linked to it, the chances of recalling a lengthy password he/she created should not present a problem.

Steganography in IoT: Information Hiding with Joystick and Touch Sensors.

This paper describes a multi-secret steganographic system for the Internet-of-Things. It uses two user-friendly sensors for data input: thumb joystick and touch sensor. These devices are not only easy to use, but also allow hidden data entry. The system conceals multiple messages into the same container, but with different algorithms. The embedding is realized with two methods of video steganography that work on mp4 files, namely, videostego and metastego. These methods were chosen because of their low complexity so that they may operate smoothly in environments with limited resources. It is possible to replace the suggested sensors with others that offer similar functionality.

Linguistic methods in healthcare application and COVID-19 variants classification.

One of the most important goals of modern medicine is prevention against pandemic and civilization diseases. For such tasks, advanced IT infrastructures and intelligent AI systems are used, which allow supporting patients' diagnosis and treatment. In our research, we also try to define efficient tools for coronavirus classification, especially using mathematical linguistic methods. This paper presents the ways of application of linguistics techniques in supporting effective management of medical data obtained during coronavirus treatments, and possibilities of application of such methods in classification of different variants of the coronaviruses detected for particular patients. Currently, several types of coronavirus are distinguished, which are characterized by differences in their RNA structure, which in turn causes an increase in the rate of mutation and infection with these viruses.

Protein Tyrosine Phosphatase Biochemical Inhibition Assays.

Disturbance of the dynamic balance between protein tyrosine phosphorylation and dephosphorylation, modulated by protein tyrosine kinases (PTKs) and protein tyrosine phosphatases (PTPs), is known to be crucial for the development of many human diseases. The discovery of agents that restore this balance has been the subject of many drug research efforts, most of which have focused on tyrosine kinase inhibitors (TKIs), resulting in the development of more than 50 FDA-approved TKIs during the past two decades. More recently, accumulating evidence has suggested that members of the PTP superfamily are also promising drug targets, and efforts to discover tyrosine phosphatase inhibitors (TPIs) have increased dramatically. Here, we provide protocols for determining the potency of TPIs in vitro. We focus on the use of fluorescence-based substrates, which exhibit a dramatic increase in fluorescence emission when dephosphorylated by the PTP, and thus allow setting up highly sensitive and miniaturized phosphatase activity assays using 384-well or 1536-well microplates and a continuous (kinetic) assay format. The protocols cover PTP specific activity assays, Michaelis-Menten kinetics, dose-response inhibition assays, and dose-response data analysis for determining IC 50 values. Potential pitfalls are also discussed. While advanced instrumentation is utilized for compound spotting and liquid dispensing, all the assays can be adapted to existing equipment in most laboratories. Assays are described for selected PTP drug targets, including SHP2 ( PTPN11 ), PTP1B ( PTPN1 ), STEP ( PTPN5 ), and VHR ( DUSP3 ). However, all protocols are applicable to members of the PTP enzyme family in general. Graphical abstract.

Imaging the human brain on oral contraceptives: A review of structural imaging methods and implications for future research goals.

Worldwide over 150 million women use oral contraceptives (OCs), which are the most prescribed form of contraception in both the United States and in European countries. Sex hormones, such as estradiol and progesterone, are important endogenous hormones known for shaping the brain across the life span. Synthetic hormones, which are present in OCs, interfere with the natural hormonal balance by reducing the endogenous hormone levels. Little is known how this affects the brain, especially during the most vulnerable times of brain maturation. Here, we review studies that investigate differences in brain gray and white matter in women using OCs in comparison to naturally cycling women. We focus on two neuroimaging methods used to quantify structural gray and white matter changes, namely structural MRI and diffusion MRI. Finally, we discuss the potential of these imaging techniques to advance knowledge about the effects of OCs on the brain and wellbeing in women.

Substrate-Based Design of Cytosolic Nucleotidase IIIB Inhibitors and Structural Insights into Inhibition Mechanism.

Cytosolic nucleotidases (cNs) catalyze dephosphorylation of nucleoside 5'-monophosphates and thereby contribute to the regulation of nucleotide levels in cells. cNs have also been shown to dephosphorylate several therapeutically relevant nucleotide analogues. cN-IIIB has shown in vitro a distinctive activity towards 7-mehtylguanosine monophosphate (m7GMP), which is one key metabolites of mRNA cap. Consequently, it has been proposed that cN-IIIB participates in mRNA cap turnover and prevents undesired accumulation and salvage of m7GMP. Here, we sought to develop molecular tools enabling more advanced studies on the cellular role of cN-IIIB. To that end, we performed substrate and inhibitor property profiling using a library of 41 substrate analogs. The most potent hit compounds (identified among m7GMP analogs) were used as a starting point for structure-activity relationship studies. As a result, we identified several 7-benzylguanosine 5'-monophosphate (Bn7GMP) derivatives as potent, unhydrolyzable cN-IIIB inhibitors. The mechanism of inhibition was elucidated using X-ray crystallography and molecular docking. Finally, we showed that compounds that potently inhibit recombinant cN-IIIB have the ability to inhibit m7GMP decay in cell lysates.

Steganography in IoT: Information Hiding with APDS-9960 Proximity and Gestures Sensor.

This article describes a steganographic system for IoT based on an APDS-9960 gesture sensor. The sensor is used in two modes: as a trigger or data input. In trigger mode, gestures control when to start and finish the embedding process; then, the data come from an external source or are pre-existing. In data input mode, the data to embed come directly from the sensor that may detect gestures or RGB color. The secrets are embedded in time-lapse photographs, which are later converted to videos. Selected hardware and steganographic methods allowed for smooth operation in the IoT environment. The system may cooperate with a digital camera and other sensors.

Fluorinated Phosphoadenosine 5'-Phosphosulfate Analogues for Continuous Sulfotransferase Activity Monitoring and Inhibitor Screening by 19F NMR Spectroscopy.

Sulfotransferases (STs) are ubiquitous enzymes that participate in a vast number of biological processes involving sulfuryl group (SO3) transfer. 3'-phosphoadenosine 5'-phosphosulfate (PAPS) is the universal ST cofactor, serving as the "active sulfate" source in cells. Herein, we report the synthesis of three fluorinated PAPS analogues that bear fluorine or trifluoromethyl substituents at the C2 or C8 positions of adenine and their evaluation as substitute cofactors that enable ST activity to be quantified and real-time-monitored by fluorine-19 nuclear magnetic resonance (19F NMR) spectroscopy. Using plant AtSOT18 and human SULT1A3 as two model enzymes, we reveal that the fluorinated PAPS analogues show complementary properties with regard to recognition by enzymes and the working 19F NMR pH range and are attractive versatile tools for studying STs. Finally, we developed an 19F NMR assay for screening potential inhibitors against SULT1A3, thereby highlighting the possible use of fluorinated PAPS analogues for the discovery of drugs for ST-related diseases.

The Effects of Peripheral Inflammation on the Brain-A Neuroimaging Perspective.

ABSTRACT: In the field of neuropsychiatry, neuroinflammation is one of the prevailing hypotheses to explain the pathophysiology of mood and psychotic disorders. Neuroinflammation encompasses an ill-defined set of pathophysiological processes in the central nervous system that cause neuronal or glial atrophy or death and disruptions in neurotransmitter signaling, resulting in cognitive and behavioral changes. Positron emission tomography for the brain-based translocator protein has been shown to be a useful tool to measure glial activation in neuropsychiatric disorders. Recent neuroimaging studies also indicate a potential disruption in the choroid plexus and blood-brain barrier, which modulate the transfer of ions, molecules, toxins, and cells from the periphery into the brain. Simultaneously, peripheral inflammatory markers have consistently been shown to be altered in mood and psychotic disorders. The crosstalk (i.e., the communication between peripheral and central inflammatory pathways) is not well understood in these disorders, however, and neuroimaging studies hold promise to shed light on this complex process. In the current Perspectives article, we discuss the neuroimaging insights into neuroimmune crosstalk offered in selected works. Overall, evidence exists for peripheral immune cell infiltration into the central nervous system in some patients, but the reason for this is unknown. Future neuroimaging studies should aim to extend our knowledge of this system and the role it likely plays in symptom onset and recurrence.

Privacy preserving IoT-based crowd-sensing network with comparable homomorphic encryption and its application in combating COVID19.

IoT-based crowd-sensing network, which aims to achieve data collection and task allocation to mobile users, become more and more popular in recent years. This data collected by IoT devices may be private and directly transmission of these data maybe incur privacy leakage. With the help of homomorphic encryption (HE), which supports the additive and/or multiplicative operations over the encrypted data, privacy preserving crowd-sensing network is now possible. Until now several such secure data aggregation schemes based on HE have been proposed. In many cases, ciphertext comparison is an important step for further secure data processing. However efficient ciphertext comparison is not supported by most such schemes. In this paper, aiming at enabling ciphertext comparison among multiple users in crowd-sensing network, with Lagrange's interpolation technique we propose comparable homomorphic encryption (CompHE) schemes. We also prove our schemes' security, and the performance analysis show our schemes are practical. We also discuss the applications of our IoT based crowd-sensing network with comparable homomorphic encryption for combatting COVID19, including the first example of privacy preserving close contact determination based on the spatial distance, and the second example of privacy preserving social distance controlling based on the spatial difference of lockdown zones, controlled zones and precautionary zones. From the analysis we see our IoT based crowd-sensing network can be used for contact tracing without worrying about the privacy leakage. Compared with the existing CompHE schemes, our proposals can be collusion resistance or secure in the semi-honest model while the previous schemes cannot achieve this easily. Our schemes only need 4 or 5 modular exponentiation when implementing the most important comparison algorithm, which are better than the existing closely related scheme with advantage of 50% or 37.5%.

Novel N7-Arylmethyl Substituted Dinucleotide mRNA 5' cap Analogs: Synthesis and Evaluation as Modulators of Translation.

Dinucleotide analogs of the messenger RNA cap (m7GpppN) are useful research tools and have potential applications as translational inhibitors or reagents for modification of in vitro transcribed mRNAs. It has been previously reported that replacing the methyl group at the N7-position with benzyl (Bn) produces a dinucleotide cap with superior properties. Here, we followed up on this finding by synthesizing 17 novel Bn7GpppG analogs and determining their structure-activity relationship regarding translation and translational inhibition. The compounds were prepared in two steps, including selective N7-alkylation of guanosine 5'-monophosphate by arylmethyl bromide followed by coupling with imidazole-activated GDP, with total yields varying from 22% to 62%. The compounds were then evaluated by determining their affinity for eukaryotic translation initiation factor 4E (eIF4E), testing their susceptibility to decapping pyrophosphatase, DcpS-which is most likely the major cellular enzyme targeting this type of compound-and determining their translation inhibitory properties in vitro. We also synthesized mRNAs capped with the evaluated compounds and tested their translational properties in A549 cells. Our studies identified N7-(4-halogenbenzyl) substituents as promising modifications in the contexts of either mRNA translation or translational inhibition. Finally, to gain more insight into the consequences at the molecular level of N7-benzylation of the mRNA cap, we determined the crystal structures of three compounds with eIF4E.

Cognitive Based Authentication Protocol for Distributed Data and Web Technologies.

The objective of the verification process, besides guaranteeing security, is also to be effective and robust. This means that the login should take as little time as possible, and each time allow for a successful authentication of the authorised account. In recent years, however, online users have been experiencing more and more issues with recalling their own passwords on the spot. According to research done in 2017 by LastPass on its employees, the number of personal accounts assigned to one business user currently exceeds 191 profiles and keeps growing. Remembering these many passwords, especially to applications which are not used every week, seems to be impossible without storing them either on paper, in a password manager, or saved in a file somewhere on a PC. In this article a new verification model using a Google Street View image as well as the user's personal experience and knowledge will be presented. The purpose of this scheme is to assure secure verification by creating longer passwords as well as delivering a 'password reminder' already embedded into the login scheme.

Substrate Specificity of SARS-CoV-2 Nsp10-Nsp16 Methyltransferase.

The ongoing COVID-19 pandemic exemplifies the general need to better understand viral infections. The positive single-strand RNA genome of its causative agent, the SARS coronavirus 2 (SARS-CoV-2), encodes all viral enzymes. In this work, we focused on one particular methyltransferase (MTase), nsp16, which, in complex with nsp10, is capable of methylating the first nucleotide of a capped RNA strand at the 2'-O position. This process is part of a viral capping system and is crucial for viral evasion of the innate immune reaction. In light of recently discovered non-canonical RNA caps, we tested various dinucleoside polyphosphate-capped RNAs as substrates for nsp10-nsp16 MTase. We developed an LC-MS-based method and discovered four types of capped RNA (m7Gp3A(G)- and Gp3A(G)-RNA) that are substrates of the nsp10-nsp16 MTase. Our technique is an alternative to the classical isotope labelling approach for the measurement of 2'-O-MTase activity. Further, we determined the IC50 value of sinefungin to illustrate the use of our approach for inhibitor screening. In the future, this approach may be an alternative technique to the radioactive labelling method for screening inhibitors of any type of 2'-O-MTase.

Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification.

Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level. Among the different approaches aiming to study white matter abnormalities at the subject level, normative modeling analysis takes a step towards subject-level predictions by identifying affected brain locations in individual subjects based on extreme deviations from a normative range. Here, we leveraged a large harmonized diffusion MRI dataset from 512 healthy controls and 601 individuals diagnosed with schizophrenia, to study whether normative modeling can improve subject-level predictions from a binary classifier. To this aim, individual deviations from a normative model of standard (fractional anisotropy) and advanced (free-water) dMRI measures, were calculated by means of age and sex-adjusted z-scores relative to control data, in 18 white matter regions. Even though larger effect sizes are found when testing for group differences in z-scores than are found with raw values (p < .001), predictions based on summary z-score measures achieved low predictive power (AUC < 0.63). Instead, we find that combining information from the different white matter tracts, while using multiple imaging measures simultaneously, improves prediction performance (the best predictor achieved AUC = 0.726). Our findings suggest that extreme deviations from a normative model are not optimal features for prediction. However, including the complete distribution of deviations across multiple imaging measures improves prediction, and could aid in subject-level classification.

Federated Compressed Learning Edge Computing Framework with Ensuring Data Privacy for PM2.5 Prediction in Smart City Sensing Applications.

The sparse data in PM2.5 air quality monitoring systems is frequently happened on large-scale smart city sensing applications, which is collected via massive sensors. Moreover, it could be affected by inefficient node deployment, insufficient communication, and fragmented records, which is the main challenge of the high-resolution prediction system. In addition, data privacy in the existing centralized air quality prediction system cannot be ensured because the data which are mined from end sensory nodes constantly exposed to the network. Therefore, this paper proposes a novel edge computing framework, named Federated Compressed Learning (FCL), which provides efficient data generation while ensuring data privacy for PM2.5 predictions in the application of smart city sensing. The proposed scheme inherits the basic ideas of the compression technique, regional joint learning, and considers a secure data exchange. Thus, it could reduce the data quantity while preserving data privacy. This study would like to develop a green energy-based wireless sensing network system by using FCL edge computing framework. It is also one of key technologies of software and hardware co-design for reconfigurable and customized sensing devices application. Consequently, the prototypes are developed in order to validate the performances of the proposed framework. The results show that the data consumption is reduced by more than 95% with an error rate below 5%. Finally, the prediction results based on the FCL will generate slightly lower accuracy compared with centralized training. However, the data could be heavily compacted and securely transmitted in WSNs.

Smaller subcortical volumes and enlarged lateral ventricles are associated with higher global functioning in young adults with 22q11.2 deletion syndrome with prodromal symptoms of schizophrenia.

The 22q11.2 deletion syndrome (22q11DS) is a developmental genetic syndrome associated with a 30% risk for developing schizophrenia. Lateral ventricles and subcortical structures are abnormal in this syndrome as well as in schizophrenia. Here, we investigated whether these structures are related in young adults with 22q11DS with and without prodromal symptoms (PS) for schizophrenia and whether abnormalities in volumes are associated with global functioning. MR images were acquired on a 3T scanner from 51 individuals with 22q11DS and 30 healthy controls (mean age: 21±2 years). Correlations were performed to evaluate the relationship between ventricular and subcortical volumes, with Global Assessment of Functioning (GAF) and Premorbid Adjustment Scale (PAS) in each group. Lateral ventricular volumes correlated negatively with subcortical volumes in individuals with 22q11DS. In individuals with 22q11DS with PS only, GAF correlated positively with volumes of the lateral ventricles and negatively with subcortical volumes. PAS correlated negatively with lateral ventricle volumes, and positively with volumes of subcortical structures. The results suggest a common neurodevelopmental mechanism related to the growth of these brain structures. Further, the ratio between the volumes and clinical measures could potentially be used to characterize individuals with 22q11DS and those from the general population for the risk of the development of schizophrenia.