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Abstract Many archetypal and emerging classes of small-molecule therapeutics form covalent protein adducts. In vivo, both the resulting conjugates and their off-target side-conjugates have the potential to elicit antibodies, with implications for allergy and drug sequestration. Although β-lactam antibiotics are a drug class long associated with these immunological phenomena, the molecular underpinnings of off-target drug-protein conjugation and consequent drug-specific immune responses remain incomplete. Here, using the classical β-lactam penicillin G (PenG), we probe the B and T cell determinants of drug-specific IgG responses to such conjugates in mice. Deep B cell clonotyping reveals a dominant murine clonal antibody class encompassing phylogenetically-related IGHV1, IGHV5 and IGHV10 subgroup gene segments. Protein NMR and x-ray structural analyses reveal that these drive structurally convergent binding modes in adduct-specific antibody clones. Their common primary recognition mechanisms of the penicillin side-chain moiety (phenylacetamide in PenG)—regardless of CDRH3 length—limits cross-reactivity against other β-lactam antibiotics. This immunogenetics-guided discovery of the limited binding solutions available to antibodies against side products of an archetypal covalent inhibitor now suggests future potential strategies for the ‘germline-guided reverse engineering’ of such drugs away from unwanted immune responses.

A three-dimensional simulation model of the electromechanical control system was built using the fuzzy control proportional–integral–derivative (PID) adjustment algorithm after an automatic electromechanical control system based on programmable logic controller (PLC) technology was optimized to achieve the practical use of electromechanical program control. First, the hardware of the electromechanical control system is discussed and designed. The findings demonstrate the viability of the mechanical and electrical integration PLC program optimization solution based on three-dimensional (3D) model. The system has a higher control and management efficiency, which is 30% greater than that of the conventional system. The mechatronic manufacturing system’s continuous operation efficiency enhancement can significantly lower the investment costs and boost the financial gains of industrial organizations. Traditional systems have a control and management efficiency of around 30%, but automatic electromechanical control systems based on PLC technology and created using 3D models have a control and management efficiency between 60 and 70%.

To ensure the safe functioning of lifting equipment, a data mining-based optimization study of a crane failure predictive control system is provided. To diagnose lifting machinery faults, the system employs decision tree categorization. Using association rules, a correlation study of hoisting machinery defect and failure was performed. When the minimal confidence and support degree are entered, a total of 244 instances of 18 frequent itemset A9 (safety protection device) may be obtained, indicating that lifting machinery does not perform well in this category. A6 (main parts) and A9 appeared a total of 98 times, with support and confidence of 29.4 and 35.6, respectively, indicating that the main parts can detect that the safety protection device is also having problems. A7 (electrical control system) and A9 appeared a total of 67 times, with support and confidence of 20.1 and 27.3, respectively, indicating that the electrical control system can detect that the safety protection device is also having problems; the correlation between them was also quite large. The system’s feasibility and efficacy shows that it has some application value.

With the wide popularization of Internet of Things (IoT) technology, the design and implementation of intelligent speech equipment have attracted more and more researchers’ attention. Speech recognition is one of the core technologies to control intelligent mechanical equipment. An industrial IoT sensor-based broadcast speech recognition and control system is presented to address the issue of integrating a broadcast speech recognition and control system with an IoT sensor for smart cities. In this work, a design approach for creating an intelligent voice control system for the Robot operating system (ROS) is provided. The speech recognition control program for the ROS is created using the Baidu intelligent voice software development kit, and the experiment is run on a particular robot platform. ROS makes use of communication modules to implement network connections between various system modules, mostly via topic-based asynchronous data transmission. A point-to-point network structure serves as the communication channel for the many operations that make up the ROS. The hardware component is mostly made up of the main controller’s motor driving module, a power module, a WiFi module, a Bluetooth module, a laser ranging module, etc. According to the experimental findings, the control system can identify the gathered sound signals, translate them into control instructions, and then direct the robot platform to carry out the necessary actions in accordance with the control instructions. Over 95% of speech is recognized. The control system has a high recognition rate and is simple to use, which is what most industrial controls require. It has significant implications for the advancement of control technology and may significantly increase production and life efficiency.

To optimize the mechanical arm target capture and classification of the open multiple-view (MV) visualization program, the open MV visualization programming and deep learning detection method combined with the different capture strategies of robotic arm, a method to extend the research is proposed. For the proposed sorting robot’s multi-cargo grasping, the analysis required to detect a wide variety of goods in a storage environment that lacks color or structural features uniformly. On the basis of SSD target detection method regression, the object’s 3D position information is reconstructed by default preselected cell selection. 3D coordinate accuracy of binocular navigation system was verified as 8% when the target cargo location distance is more than 5 cm, and binoculars matching success rate is 89.7%. The success rate of Sorting and hoarding is increased from 6% to 85% by adding a change to the scoring points of the target products of uneven quality, with this we have achieved efficient and accurate import.

Internet of Things (IoT) gadgets are very attractive globally, and IoT facilities are universal. Their progress has not been ignored, and the number of invaders and outbreaks on IoT and facilities is growing. Because cyber-assaults are zero-trust to the IoT, and the IoT is deeply ingrained in our lives and culture, we must embrace a comprehensive Zero-Trust strategy for cyber defense. As a result, the new model is no longer vulnerable to fear and outbreak on the IoT structure. In this article, an effort is made to categorize threat types and analyze and explain invaders and assaults on IoT gadgets and facilities.

The speed sensor fusion of urban rail transit train speed ranging based on deep learning builds a user-friendly structure but it in-turn increases the risk of traffic that significantly challenges its safety and transportation efficacy. In order to improve the operation safety and transportation efficiency of urban rail transit trains, a train speed ranging system based on embedded multi-sensor information is proposed in this article. The status information of the train is acquired by the axle speed sensor and the Doppler radar speed sensor; however, the query transponder collects the status information of the train, and is used in the embedded system. Various other modules like adaptive correction, idling/sliding detection and compensation of speed transition/sliding are used in the proposed methodology to reduce the vehicle speed positioning errors due to factors such as wheel wear, idling, sliding, and environment. The results show that the running time of the train is 1000s, the output period of the axle speed sensor is 0.005s and the accelerometer output period is 0.01s. The output cycle of doppler radar is observed to be 0.1s, the output cycle of the transponder is 1s and the fusion period of the main filter is observed as 1s. The train speed ranging system of the embedded multi-sensor information fusion system proposed in this article can effectively improve the accuracy of the train speed positioning.

In synthetic aperture radar (SAR) image segmentation field, regional algorithms have shown great potential for image segmentation. The SAR images have a multiplicity of complex texture, which are difficult to be divided as a whole. Existing algorithm may cause mixed super-pixels with different labels due to speckle noise. This study presents the technique based on organization evolution (OEA) algorithm to improve ISODATA in pixels. This approach effectively filters out the useless local information and successfully introduces the effective information. To verify the accuracy of OEA-ISO data algorithm, the segmentation effect of this algorithm is tested on SAR image and compared with other techniques. The results demonstrate that the OEA-ISO data algorithm is 10.16% more accurate than the WIPFCM algorithm, 23% more accurate than the K-means algorithm, and 27.14% more accurate than the fuzzy C-means algorithm in the light-colored farmland category. It can be seen that the OEA-ISO data algorithm introduces the pixel block strategy, which successfully reduces the noise interference in the image, and the effect is more obvious when the image background is complex.

Recently, researchers are investing more fervently in fault diagnosis area of electrical machines. The users and manufacturers of these various efforts are strong to contain diagnostic features in software for improving reliability and scalability. Internet of Things (IoT) has grown immensely and contributing for the development of recent technological advancements in industries, medical and various environmental applications. It provides efficient processing power through cloud, and presents various new opportunities for industrial automation by implementing IoT and industrial wireless sensor networks. The process of regular monitoring enables early detection of machine faults and hence beneficial for Industrial automation by providing efficient process control. The performance of fault detection and its classification by implementing machine-learning algorithms highly dependent on the amount of features involved. The accuracy of classification will adversely affect by the dimensionality features increment. To address these problems, the proposed work presents the extraction of relevant features based on oriented sport vector machine (FO-SVM). The proposed algorithm is capable for extracting the most relevant feature set and hence presenting the accurate classification of faults accordingly. The extraction of most relevant features before the process of classification results in higher classification accuracy. Moreover it is observed that the lesser dimensionality of propose process consumes less time and more suitable for cloud. The experimental analysis based on the implementation of proposed approach provides and solution for the monitoring of machine condition and prediction of fault accurately based on cloud platform using industrial wireless sensor networks and IoT service.

With the technological evolutionary advent, a vision-based approach presents the remote measuring approach for the analysis of vibration. The structure vibration test and model parameter identification in the detection of the structure of the bridge evaluation occupies the important position. The bridge structure to operate safely and reliably is ensured, according to the geological data of qixiashan lead-zinc mine and engineering actual situation, with the aid of international mining software Surpac. To build the 3D visualization model of the application of visualization in mine production are discussed. The results show that the final solid model of -425 stope can accurately display the spatial form of each layer of stope through rotation, amplification and movement. The proposed system is effectually able to perform cutting, volume calculation and roaming in any direction, which has certain guiding significance for mine production management. An accuracy value of 98.75%, the sensitivity of 99%, specificity of 99.64% and PPV of 99.89% are achieved using the proposed 3D modelling and visualization algorithm for vibration signal processing and management.

Covalent conjugation of endogenous protein complexes offers many opportunities for fundamental and clinical research. Based on a bacterial protein domain that forms a reactive anhydride in the presence of Ca2+, the authors here develop a system that enables the covalent capture of endogenous binding partners.

Centre of advanced pharmaceutical education have developed 15 subsets of competencies required to be competent pharmacist and able to provide optimum care. These competencies were further categorized; Level 1 intermediate, Level 2 efficient, and Level 3 professional. These competencies are cross-mapped to achieve desirable outcomes. Where personal and professional development skills incorporate knowledge, for being a holistic pharmacist. In healthcare education curriculums, active learning tools such as simulation-based patient cases and other innovative learning activities are used to teach clinical skills, patient assessments, and pharmacotherapy concepts. The advance team-based learning technique for the development of stepwise understanding of disease management (simple-complex cases) and students can communicate and collaborate for the critical thinking and decision-making process. Many studies showed the positive impact of the peer teaching on the students; enhanced their academic performance, increase the cognitive congruence, and allows the students to share their own learning struggles to come up with solutions to overcome these challenges. Pharmacy is a healthcare professional required intensive training and professional skills to provide optimum care to patients. The emerging clinical role of pharmacy focused on the patient-centered model, comprehensive assessment, and teaching methods are required to fulfill the professional competencies.

The corona virus disease-19 (COVID-19) pandemic has affected the entire world causing huge economic losses and considerable morbidity and mortality. Considering the explosive growth of the pandemic repurposing existing medicines may be cost-effective and may be approved for use in COVID-19 faster. Researchers and medical practitioners worldwide have explored the use of chloroquine and hydroxychloroquine, in few occasions combined with the macrolide antibiotic azithromycin, for COVID-19 treatment. These two drugs are economic and easily available, and hence gained attention as a potential option for COVID-19 management. As per the available evidence, the outcomes of treatments with these medications are conflicting from both the efficacy and safety (predominantly cardiac related) perspectives. Currently, multiple studies are underway to test the safety and efficacy of these medications and more results are expected in the near future. The retina, the endocrine system (with risk of hypoglycemia), the musculoskeletal system, the hematological system, and the neurological system may also be affected. The use of these drugs is contraindicated in patients with arrhythmias, known hypersensitivity, and in patients on amiodarone. In addition to the published literature, personal communication with doctors treating COVID-19 patients seems to suggest the drugs may be effective in reducing symptoms and hastening clinical recovery. The literature evidence is still equivocal and further results are awaited. There has been recent controversy including retraction of articles published in prestigious journals about these medicines. Their low cost, long history of use, and easy availability are positive factors with regard to use of these drugs in COVID-19.

African trypanosome infections can persist for years, but immune evasion mechanisms are not fully understood. Here, Macleod et al. identify a trypanosome receptor for mammalian factor H, a negative regulator of the alternative complement pathway, that increases parasite transmission to tsetse flies.

Background: This study was aimed to describe the choice of Surgical Antimicrobial Prophylaxis at a tertiary-level care hospital in United Arab Emirates. It also associated the choice between two leading antimicrobials for the SAP to the site of surgery.Methods: A descriptive drug use evaluation was performed retrospectively to study choices of antimicrobials in surgical antibiotic prophylaxis. An analytical cross-sectional study design was used to develop a hypothesis regarding the choice of ceftriaxone. Data were collected from the medical records of Hospital from July 2020 to December 2020. Results were presented in numbers and percentages.Results: SAP data were collected from 199 patients, of which 159 were clean or clean-contaminated. Dirty surgeries (18) needed a higher level of antimicrobials as there were infections to be treated. For other surgeries with no infection, overuse of antimicrobials was found regarding the choice of antimicrobials. Surgical antibiotic Prophylaxis was administered within the recommended time prior to surgeries. Ceftriaxone was preferred over cefuroxime in all types of surgeries based on the timing of Surgical Antibiotic Prophylaxis, wound classification, and the surgical site. A statistically significant association for choice of ceftriaxone over cefuroxime was found regarding surgical sites (p-value

Introduction. Coronavirus disease 2019 (COVID-19) can progress to severe respiratory compromise and lead to mortality due to induction of cytokine storm. Tocilizumab (TCZ) is approved by the FDA for the treatment of cytokine release syndrome (CRS). This study aims to analyze the outcomes among patients who received TCZ in the United Arab Emirates. Methods. A retrospective cohort study was conducted among COVID-19 patients who received TCZ in a tertiary care hospital from May 2020 to August 2021. For analysis, patients were divided into two groups based on survival and clinical improvement. Results. Overall, 80% of patients receiving TCZ were discharged by day 28. There was a gradual improvement in oxygen requirements in our patients with a majority of them on room air by day 28. Age more than 50 years (P=0.034) and comorbidities such as cardiovascular disease (CVD) (P=0.002) and renal insufficiency (P=0.013) were significantly associated with mortality. Discussion. In our analysis, patients who were mechanically ventilated at the time of administration of TCZ had a significantly higher risk of death by day 28. In both survived and improved groups, younger patients had better outcomes than older patients. Patients who received TCZ earlier during therapy from the onset of symptoms had better survival outcomes. There was only one death among 14 patients who received vaccination. There was no significant difference in mortality among patients with comorbidities such as diabetes, hypertension, dyslipidemia, obesity, and pulmonary diseases, hypothesizing that administration of TCZ improves the outcomes in COVID-19 patients with these comorbidities.

Decades of excessive use of readily available antibiotics has generated a global problem of antibiotic resistance and, hence, an urgent need for novel antibiotic solutions. Bacteriocins are protein-based antibiotics produced by bacteria to eliminate closely related competing bacterial strains.

Objective The objective was to compare the efficacy of azithromycin and clarithromycin in combination with beta-lactams to treat community-acquired pneumonia among hospitalized adults. Methods Five databases (PubMed, Google Scholar, Trip, Medline, and Clinical Key) were searched to identify randomized clinical trials with patients exposed to azithromycin or clarithromycin in combination with a beta-lactam. All articles were critically reviewed for inclusion in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results Seven clinical trials were included. The treatment success rate for azithromycin–beta-lactam after 10 to 14 days was 87.55% and that for clarithromycin–beta-lactam after 5 to 7 days of therapy was 75.42%. Streptococcus pneumoniae was commonly found in macrolide groups, with 130 and 80 isolates in the clarithromycin-based and azithromycin-based groups, respectively. The length of hospital stay was an average of 8.45 days for patients receiving a beta-lactam–azithromycin combination and 7.25 days with a beta-lactam–clarithromycin combination. Conclusion Macrolide inter-class differences were noted, with a higher clinical success rate for azithromycin-based combinations. However, a shorter length of hospital stay was achieved with a clarithromycin–beta-lactam regimen. Thus, a macrolide combined with a beta-lactam should be chosen using susceptibility data from the treating facility.

Abstract Background Sentinel node biopsy (SNB) is the standard procedure for axillary staging in patients with clinically lymph node negative invasive breast cancer. Completion axillary lymph node dissection (c-ALND) may not be necessary for all patients as a significant number of patients have no further metastases in non-sentinel nodes (non-SN) and c-ALND may not improve survival. The first aim of our study is to identify clinicopathological determinants associated with non-SN metastases. The second aim is to determine the impact of the number of sentinel node (SN) with macro-metastases and the type of SN metastases on metastatic involvement in non-SN. Methods This is a retrospective study of 602 patients with primary invasive breast cancer operated on with SNB and c-ALND in Lund and Malmö during 2008–2013. All these patients had micro- and/or macro-metastases in SNs. Information was retrieved from the national Information Network for Cancer Care (INCA). The risk of metastases to non-SNs were analyzed in relation to clinicopathological determinants such as age, screening mammography, tumour size, tumour type, histological grade, estrogen status, progesterone status, HER2 status, multifocality and lymphovascular invasion. Additionally, we compared the association between the number of the SN and the type of metastases in SN with the risk of metastases to non-SNs. Binary logistic regression was used, yielding odds ratios (OR) with 95% confidence intervals (CI). Results We found that 211 patients (35%) had metastases in non-SNs and 391 patients (65%) had no metastases in non-SNs. Lobular type (18%) of breast cancer (1.73; 1.0 1-2.97) and multifocal (31.3%) tumours (2.20; 1.41–3.44) had a high risk of non-SNs metastases. As compared to only micro-metastases, the presence of macro-metastases in SNs was associated with a high risk of metastases to non-SNs (4.91; 3.01–8.05). The number of SN with macro-metastases, regardless of the number of SNs removed by surgery, increases the risk of finding non-SNs with metastases. The total number of SN removed by surgery had no impact on diagnosis of metastases in non-SNs. No statistically significant associations were observed regarding other studied determinants. Conclusion We conclude in the present study that lobular cancer and multifocal tumours were associated with a high risk of non-SN involvement. The presence of the macro-metastases in SNs and the number of SN with macro-metastases has a positive association with presence of metastases in non-SNs. The total number of SNs removed by surgery had no impact on finding metastases in non-SNs. These factors may be valuable considering whether or not to omit c-ALND.

Purpose: To study the prescribing pattern of antibiotics in outpatients and emergency departments in the Gulf region. To compare the appropriateness of prescriptions and antibiotics commonly prescribed for respiratory tract infection.Method: The search was limited to the years 2008–2020, and articles had to be in English. Articles were searched from various resources and evaluated using PRISMA. Forty-one articles were selected and screened, and in the end, 17 articles were included in the study. All articles were selected from the gulf region of six countries: UAE, Saudi Arabia, Qatar, Oman, Yemen, and Bahrain. Only primary literature were included. Inpatient and literature from other countries outside the gulf region were excluded.Result: Penicillins, cephalosporins, and macrolides are highly useful antibiotics for respiratory tract infections. Ceftriaxone IV is recommended in acute respiratory tract infection if therapy with penicillin fails. Most of the antibiotic prescriptions in Gulf countries are inappropriate. Inappropriate antibiotic prescribing in the gulf region varies from place to place and reaches a maximum of 80%. Antibiotics may be prescribed with the wrong dosage or frequency and inappropriate guidelines. Penicillins are prescribed at about 50–60%; the most common penicillins prescribed are amoxicillin and co-amoxiclave. Cephalosporins are prescribed at about 30%, and the most common are third-generation. Macrolides are prescribed at about 17–20%, and the most common macrolides are azithromycin and clarithromycin. Fluoroquinolones are prescribed at about 10–12%, of which levofloxacin and ciprofloxacin are more commonly prescribed with metronidazole at 10%.Conclusion: It is suggested that the antibiotic-prescribing pattern in outpatient and emergency departments in the Gulf region are highly inappropriate and need improvement through education, following guidelines, annual vaccination, and stewardship programs; the most prescribed antibiotic is amoxicillin/co-amoxiclave, and the most often encountered infection in outpatients is acute respiratory tract infection.

APC/C-mediated proteolysis of cyclin B and securin promotes anaphase entry, inactivating CDK1 and permitting chromosome segregation, respectively. Reduction of CDK1 activity relieves inhibition of the CDK1-counteracting phosphatases PP1 and PP2A-B55, allowing wide-spread dephosphorylation of substrates. Meanwhile, continued APC/C activity promotes proteolysis of other mitotic regulators. Together, these activities orchestrate a complex series of events during mitotic exit. However, the relative importance of regulated proteolysis and dephosphorylation in dictating the order and timing of these events remains unclear. Using high temporal-resolution proteomics, we compare the relative extent of proteolysis and protein dephosphorylation. This reveals highly-selective rapid proteolysis of cyclin B, securin and geminin at the metaphase-anaphase transition, followed by slow proteolysis of other substrates. Dephosphorylation requires APC/C-dependent destruction of cyclin B and was resolved into PP1-dependent categories with unique sequence motifs. We conclude that dephosphorylation initiated by selective proteolysis of cyclin B drives the bulk of changes observed during mitotic exit.

Pharmaceutical education has extensive integration of courses from life sciences to technology application and drug discovery to clinical trials. Pharmacy students are capable of diverse career selection due to acquired competencies during professional education. However, there is always a lack of real-time research exposure to pharmacy students at the undergraduate level. Therefore, the purpose is to design an effective research series that provides first-hand research experience to pharmacy students during 2–4 years of PharmD studies. The course design and delivery focused on three elements, namely, quality assurance, curriculum requirement, and assessment method. The outcomes of the course series are consistent with the emerging research skills and evidence-based practitioner role. The series and multilevel of course sequels comprising from knowledge – comprehension – argument – to – synthesis of research article. Students are expected to conduct independent research project under the supervision of college faculty. This will help them to develop and advance research skills for lifelong learning. The scholarly pathway series will develop critical appraisal skills to argue/support/value the literature and develop competency for evidence-based medicines. It will be highly beneficial to develop critical thinking, professionalism, and research skills among pharmacy students.

Abstract Background Axillary lymph node status is one of the most important prognostic factors for breast cancer. The aim of this study was to determine predictive factors for metastasis to sentinel node (SN) in primary invasive breast cancer. Method This is a study of 3979 patients with primary breast cancer during 2008–2013 in Malmö and Lund scheduled for surgery and included in the information retrieved from Information Network for Cancer Care (INCA). The final study population included 2552 patients with primary invasive breast cancer. The risk of metastases to SN were examined in relation to potential clinicopathological factors such as age, screening mammography, tumor size, tumor type, histological grade, estrogen status, progesterone status, Her-2 status, multifocality, and lymphovascular invasion. Binary logistic regression was used; adjusted analyses yielded odds ratio (OR) with 95% confidence interval. Results Tumors detected by mammography screening were less likely to be associated with metastases to SN compared to those not found by mammography screening (0.63; 0.51–0.80). Negative hormonal status for estrogen associated with lower risk for SN metastases compared to tumor with positive estrogen status (0.64; 0.42–0.99). Tumors with a size more than 20 mm had higher risk to metastasize to SN (1.84; 1.47–2.33) compared to tumors less than 20 mm. Multifocality (1.90; 1.45–2.47) and lymphovascular invasion (3.74; 2.66–5.27) were also strong predictive factors for SN metastases. Conclusion SN metastasis is less likely to occur in women with invasive breast cancer diagnosed by screening mammogram. Tumors with negative estrogen status are associated with low risk for SN metastases. Tumors larger than 20 mm, multifocality, or lymphovascular invasion are also factors associated with high risk for SN metastases.

Background: X chromosome inactivation in mammals is regulated by the non-coding (nc) RNA, Xist, which represses the chromosome from which it is transcribed. High levels of the N6-methyladenosine (m6A) RNA modification occur within Xist exon I, close to the 5’ end of the transcript, and also further 3’, in Xist exon VII. The m6A modification is catalysed by the METTL3/14 complex that is directed to specific targets, including Xist, by the RNA binding protein RBM15/15B. m6A modification of Xist RNA has been reported to be important for Xist–mediated gene silencing. Methods: We use CRISPR/Cas9 mediated mutagenesis to delete sequences around the 5’ m6A region in interspecific XX mouse embryonic stem cells (mESCs). Following induction of Xist RNA expression, we assay chromosome silencing using allelic RNA-seq and Xist m6A distribution using m6A-seq. Additionally, we use Xist RNA FISH to analyse the effect of deleting the 5’ m6A region on the function of the endogenous Xist promoter. We purify epitope tagged RBM15 from mESCs, and then apply MS/MS analysis to define the RBM15 interactome. Results: We show that a deletion encompassing the entire Xist 5’ m6A region results in a modest reduction in Xist-mediated silencing, and that the 5’ m6A region overlaps essential DNA elements required for activation of the endogenous Xist promoter. Deletion of the Xist A-repeat, to which RBM15 binds, entirely abolishes deposition of m6A in the Xist 5’ m6A region without affecting the modification in exon VII. We show that in mESCs, RBM15 interacts with the m6A complex, the SETD1B histone modifying complex, and several proteins linked to RNA metabolism. Conclusions: Our findings support that RBM15 binding to the Xist A-repeat recruits the m6A complex to the 5’ Xist m6A region and that this region plays a role in Xist-mediated chromosome silencing.

Neuronal differentiation is a multistep process that shapes and re-shapes neurons by progressing through several typical stages, including axon outgrowth, dendritogenesis, and synapse formation. To systematically profile proteome dynamics throughout neuronal differentiation, we took cultured rat hippocampal neurons at different developmental stages and monitored changes in protein abundance using a combination of stable isotope labeling and high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS). Almost one third of all 4,500 proteins quantified underwent a more than 2-fold expression change during neuronal differentiation, indicating extensive remodeling of the neuron proteome. To highlight the strength of our resource, we studied the neural-cell-adhesion molecule 1 (NCAM1) and found that it stimulates dendritic arbor development by promoting actin filament growth at the dendritic growth cone. We anticipate that our quantitative map of neuronal proteome dynamics is a rich resource for further analyses of the many identified proteins in various neurodevelopmental processes.

Counteracting oxidative stress is essential in all organisms. Here, the authors outline a mechanism used by actinomycete bacteria in which oxidation of zinc-binding RsrA blocks its interaction with σR by sequestering hydrophobic residues used to bind σRwithin its own core.

RNA-binding proteins (RBPs) play a crucial role in regulating RNA function and fate. However, the full complement of RBPs has only recently begun to be uncovered through proteome-wide approaches such as RNA interactome capture (RIC). RIC has been applied to various cell lines and organisms, including plants, greatly expanding the repertoire of RBPs. However, several technical challenges have limited the efficacy of RIC when applied to plant tissues. Here, we report an improved version of RIC that overcomes the difficulties imposed by leaf tissue. Using this improved RIC method in Arabidopsis leaves, we identified 717 RBPs, generating a deep RNA-binding proteome for leaf tissues. While 75% of these RBPs can be linked to RNA biology, the remaining 25% were previously not known to interact with RNA. Interestingly, we observed that a large number of proteins related to photosynthesis associate with RNA in vivo, including proteins from the four major photosynthetic supercomplexes. As has previously been reported for mammals, a large proportion of leaf RBPs lack known RNA-binding domains, suggesting unconventional modes of RNA binding. We anticipate that this improved RIC method will provide critical insights into RNA metabolism in plants, including how cellular RBPs respond to environmental, physiological and pathological cues.

Summary: Termination of RNA polymerase II (Pol II) transcription is a key step that is important for 3′ end formation of functional mRNA, mRNA release, and Pol II recycling. Even so, the underlying termination mechanism is not yet understood. Here, we demonstrate that the conserved and essential termination factor Seb1 is found on Pol II near the end of the RNA exit channel and the Rpb4/7 stalk. Furthermore, the Seb1 interaction surface with Pol II largely overlaps with that of the elongation factor Spt5. Notably, Seb1 co-transcriptional recruitment is dependent on Spt5 dephosphorylation by the conserved PP1 phosphatase Dis2, which also dephosphorylates threonine 4 within the Pol II heptad repeated C-terminal domain. We propose that Dis2 orchestrates the transition from elongation to termination phase during the transcription cycle by mediating elongation to termination factor exchange and dephosphorylation of Pol II C-terminal domain. : Timely and efficient transcription termination is essential for release of functional mRNAs as well as for Pol II recycling. Kecman et al. demonstrate that the conserved PP1 phosphatase Dis2 regulates transcription termination in fission yeast by mediating elongation to termination factor exchange and by dephosphorylating Pol II C-terminal domain. Keywords: RNA polymerase II, C-terminal domain, CTD, PP1 phosphatase, transcription termination, CTD phosphorylation, Spt5, CTD interacting domain, CID

An MS/MS based analytical strategy was followed to solve the complete sequence of two new peptides from frog (Odorrana schmackeri) skin secretion. This involved reduction and alkylation with two different alkylating agents followed by high resolution tandem mass spectrometry. De novo sequencing was achieved by complementary CID and ETD fragmentations of full-length peptides and of selected tryptic fragments. Heavy and light isotope dimethyl labeling assisted with annotation of sequence ion series. The identified primary structures are GCD[I/L]STCATHN[I/L]VNE[I/L]NKFDKSKPSSGGVGPESP-NH2 and SCNLSTCATHNLVNELNKFDKSKPSSGGVGPESF-NH2, i.e. two carboxyamidated 34 residue peptides with an aminoterminal intramolecular ring structure formed by a disulfide bridge between Cys2 and Cys7. Edman degradation analysis of the second peptide positively confirmed the exact sequence, resolving I/L discriminations. Both peptide sequences are novel and share homology with calcitonin, calcitonin gene related peptide (CGRP) and adrenomedullin from other vertebrates. Detailed sequence analysis as well as the 34 residue length of both O. schmackeri peptides, suggest they do not fully qualify as either calcitonins (32 residues) or CGRPs (37 amino acids) and may justify their classification in a novel peptide family within the calcitonin gene related peptide superfamily. Smooth muscle contractility assays with synthetic replicas of the S–S linked peptides on rat tail artery, uterus, bladder and ileum did not reveal myotropic activity.

An affinity purification-mass spectrometry (AP-MS) method was employed to identify novel substrates of the SCFβTrCP ubiquitin ligase. A FLAG-HA tagged version of the F-box protein βTrCP2, the substrate recognition subunit of SCFβTrCP, was used as bait. βTrCP2 wild type and the two mutants βTrCP2-R447A and βTrCP2-ΔF were expressed and purified from HEK293T cells to be able to discriminate between potential substrates of SCFβTrCP and unspecific binders. Affinity-purified samples were analyzed by mass spectrometry-based proteomics, applying ultra-high performance liquid chromatography (UHPLC) coupled to high-resolution tandem mass spectrometry. The raw mass spectrometry data have been deposited to the PRIDE partner repository with the identifiers PXD001088 and PXD001224. The present dataset is associated with a research resource published in T.Y. Low, M. Peng, R. Magliozzi, S. Mohammed, D. Guardavaccaro, A.J.R. Heck, A systems-wide screen identifies substrates of the SCFβTrCP ubiquitin ligase. Sci. Signal. 7 (2014) rs8–rs8, 10.1126/scisignal.2005882.

Quantitative and qualitative protein characteristics are regulated at genomic, transcriptomic, and posttranscriptional levels. Here, we integrated in-depth transcriptome and proteome analyses of liver tissues from two rat strains to unravel the interactions within and between these layers. We obtained peptide evidence for 26,463 rat liver proteins. We validated 1,195 gene predictions, 83 splice events, 126 proteins with nonsynonymous variants, and 20 isoforms with nonsynonymous RNA editing. Quantitative RNA sequencing and proteomics data correlate highly between strains but poorly among each other, indicating extensive nongenetic regulation. Our multilevel analysis identified a genomic variant in the promoter of the most differentially expressed gene Cyp17a1, a previously reported top hit in genome-wide association studies for human hypertension, as a potential contributor to the hypertension phenotype in SHR rats. These results demonstrate the power of and need for integrative analysis for understanding genetic control of molecular dynamics and phenotypic diversity in a system-wide manner.

[This corrects the article DOI: 10.1371/journal.pbio.1000539.].

Abstract Protein post‐translational modifications (PTMs) represent important regulatory states that when combined have been hypothesized to act as molecular codes and to generate a functional diversity beyond genome and transcriptome. We systematically investigate the interplay of protein phosphorylation with other post‐transcriptional regulatory mechanisms in the genome‐reduced bacterium Mycoplasma pneumoniae. Systematic perturbations by deletion of its only two protein kinases and its unique protein phosphatase identified not only the protein‐specific effect on the phosphorylation network, but also a modulation of proteome abundance and lysine acetylation patterns, mostly in the absence of transcriptional changes. Reciprocally, deletion of the two putative N‐acetyltransferases affects protein phosphorylation, confirming cross‐talk between the two PTMs. The measured M. pneumoniae phosphoproteome and lysine acetylome revealed that both PTMs are very common, that (as in Eukaryotes) they often co‐occur within the same protein and that they are frequently observed at interaction interfaces and in multifunctional proteins. The results imply previously unreported hidden layers of post‐transcriptional regulation intertwining phosphorylation with lysine acetylation and other mechanisms that define the functional state of a cell.

Wnt signaling maintains the undifferentiated state of intestinal crypt progenitor cells by inducing the formation of nuclear TCF4/β-catenin complexes. In colorectal cancer, activating mutations in Wnt pathway components cause inappropriate activation of TCF4/β-catenin-driven transcription. Despite the passage of a decade after the discovery of TCF4 and β-catenin as the molecular effectors of the Wnt signal, few transcriptional activators essential and unique to the regulation of this transcription program have been found. Using proteomics, we identified the leukemia-associated Mllt10/Af10 and the methyltransferase Dot1l as Tcf4/β-catenin interactors in mouse small intestinal crypts. Mllt10/Af10-Dot1l, essential for transcription elongation, are recruited to Wnt target genes in a β-catenin-dependent manner, resulting in H3K79 methylation over their coding regions in vivo in proliferative crypts of mouse small intestine in colorectal cancer and Wnt-inducible HEK293T cells. Depletion of MLLT10/AF10 in colorectal cancer and Wnt-inducible HEK293T cells followed by expression array analysis identifies MLLT10/AF10 and DOT1L as essential activators to a large extent dedicated to Wnt target gene regulation. In contrast, previously published β-catenin coactivators p300 and BRG1 displayed a more pleiotropic target gene expression profile controlling Wnt and other pathways. tcf4, mllt10/af10, and dot1l are co-expressed in Wnt-driven tissues in zebrafish and essential for Wnt-reporter activity. Intestinal differentiation defects in apc-mutant zebrafish can be rescued by depletion of Mllt10 and Dot1l, establishing these genes as activators downstream of Apc in Wnt target gene activation in vivo. Morpholino-depletion of mllt10/af10-dot1l in zebrafish results in defects in intestinal homeostasis and a significant reduction in the in vivo expression of direct Wnt target genes and in the number of proliferative intestinal epithelial cells. We conclude that Mllt10/Af10-Dot1l are essential, largely dedicated activators of Wnt-dependent transcription, critical for maintenance of intestinal proliferation and homeostasis. The methyltransferase DOT1L may present an attractive candidate for drug targeting in colorectal cancer.

The molecular basis for the interaction of insulin granules with the cortical cytoskeleton of pancreatic β-cells remains unknown. We have proposed that binding of the granule protein ICA512 to the PDZ domain of β2-syntrophin anchors granules to actin filaments and that the phosphorylation/dephosphorylation of β2-syntrophin regulates this association. Here we tested this hypothesis by analyzing INS-1 cells expressing GFP-β2-syntrophin through the combined use of biochemical approaches, imaging studies by confocal and total internal reflection fluorescence microscopy as well as electron microscopy. Our results support the notion that β2-syntrophin restrains the mobility of cortical granules in insulinoma INS-1 cells, thereby reducing insulin secretion and increasing insulin stores in resting cells, while increasing insulin release upon stimulation. Using mass spectrometry, in vitro phosphorylation assays and β2-syntrophin phosphomutants we found that phosphorylation of β2-syntrophin on S75 near the PDZ domain decreases its binding to ICA512 and correlates with increased granule motility, while phosphorylation of S90 has opposite effects. We further show that Cdk5, which regulates insulin secretion, phosphorylates S75. These findings provide mechanistic insight into how stimulation displaces insulin granules from cortical actin, thus promoting their motility and exocytosis.

The evolutionarily conserved Ccr4-Not and Bur1/2 kinase complexes are functionally related in Saccharomyces cerevisiae. In this study, we further explore the relationship between the subunits Not4p and Bur2p.First, we investigated the presence of post-translational modifications on the Ccr4-Not complex. Using mass spectrometry analyses we identified several SP/TP phosphorylation sites on its Not4p, Not1p and Caf1p subunits. Secondly, the influence of Not4p phosphorylation on global H3K4 tri-methylation status was examined by immunoblotting. This histone mark is severely diminished in the absence of Not4p or of Bur2p, but did not require the five identified Not4p phosphorylation sites. Thirdly, we found that Not4p phosphorylation is not affected by the kinase-defective bur1-23 mutant. Finally, phenotypic analyses of the Not4p phosphomutant (not4S/T5A) and bur2Delta strains showed overlapping sensitivities to drugs that abolish cellular stress responses. The double-mutant not4S/T5A and bur2Delta strain even revealed enhanced phenotypes, indicating that phosphorylation of Not4p and BUR2 are active in parallel pathways for drug tolerance.Not4p is a phospho-protein with five identified phosphorylation sites that are likely targets of a cyclin-dependent kinase(s) other than the Bur1/2p complex. Not4p phosphorylation on the five Not4 S/T sites is not required for global H3K4 tri-methylation. In contrast, Not4p phosphorylation is involved in tolerance to cellular stresses and acts in pathways parallel to BUR2 to affect stress responses in Saccharomyces cerevisiae.

In the present work, La+3- substituted Co-ferrites of chemical composition CoLa0.06Fe1.94O4 (x = 0.06) was prepared applying the co-precipitation method and prepared samples was annealed at different temperatures such as 700-1200 °C for 6 h with step interval of 100 °C. The uniqueness of this work is that only x= 0.06 sample to study the effect of cubic spinel microstructure at different annealed temperatures was selected. The prepared samples were characterized by X-ray diffraction (XRD) technique, Scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FTIR) and VSM. The XRD and FTIR techniques confirm the spinel ferrite structure. The average crystallite size was found 26.5 nm to 106 nm by using Scherer's formula. When the temperature was increased, average crystallite size also increased. SEM images showed that the size of grain increased with increase of annealing temperature and confirmed the particle size as analysed by XRD. EDX spectra clarified the presence of elements in the samples by showing their respective characteristics peaks of Co, O, La, and as per prepared composition. From M-H loop, the obtained values of Ms = 59.74 emu/g and coercivity = 700 Oe showed that prepared magnetic samples may be applied as magnetic recording media. [ABSTRACT FROM AUTHOR]

Smart wearable devices detection and recording of people's everyday activities is critical for health monitoring, helping persons with disabilities, and providing care for the elderly. Most of the research that is being conducted uses a machine learning-based methodology; however, these approaches frequently have issues with high computing resource consumption, burdensome training data gathering, and restricted scalability across many contexts. This research suggests a behaviour detection technology based on multi-source sensing and logical reasoning to address these problems. In order to realize the natural fusion of signal processing and logical reasoning in behavior recognition research, this work designs a lightweight behavior recognition solution using the pertinent theories of ontology reasoning in classical artificial intelligence. Machine learning technology is also employed for behavior recognition using the same data set. Once the best model has been chosen, the cross-person recognition results after testing and modification of parameters are 90.8% and 92.1%, respectively. This technology was used to create a behaviour recognition system, and several tests were run to assess how well it worked. The findings demonstrate that the suggested strategy achieves over 90% recognition accuracy for 11 different daily activities, including jogging, walking, and stair climbing. Additionally, the suggested strategy dramatically minimises the quantity of user-provided training data needed in comparison to machine learning-based behaviour identification techniques., Competing Interests: Declarations. Competing interests: This research does not involve any human or animal participation. Ethical consent: Informed Consent was obtained from all the participants involved in the study. Bioethics and guidelines: The protocol was approved by Model Institute of Engineering and Technology Review Board in accordance with the relevant guidelines of the Model Institute of Engineering and Technology, Jammu, J&K, India., (© 2024. The Author(s).)

Context: The emergence of pan-resistant bacteria requires the development of new antibiotics and antibiotic potentiators., Objective: This review identifies antibacterial phenolic compounds that have been identified in Asian and Pacific Angiosperms from 1945 to 2023 and analyzes their strengths and spectra of activity, distributions, molecular masses, solubilities, modes of action, structures-activities, as well as their synergistic effects with antibiotics, toxicities, and clinical potential., Methods: All data in this review was compiled from Google Scholar, PubMed, Science Direct, Web of Science, and library search; other sources were excluded. We used the following combination of keywords: 'Phenolic compound', 'Plants', and 'Antibacterial'. This produced 736 results. Each result was examined and articles that did not contain information relevant to the topic or coming from non-peer-reviewed journals were excluded. Each of the remaining 467 selected articles was read critically for the information that it contained., Results: Out of ∼350 antibacterial phenolic compounds identified, 44 were very strongly active, mainly targeting the cytoplasmic membrane of Gram-positive bacteria, and with a molecular mass between 200 and 400 g/mol. 2-Methoxy-7-methyljuglone, [6]-gingerol, anacardic acid, baicalin, vitexin, and malabaricone A and B have the potential to be developed as antibacterial leads., Conclusions: Angiosperms from Asia and the Pacific provide a rich source of natural products with the potential to be developed as leads for treating bacterial infections.

Competing Interests: Declaration of Competing Interest None.

The prevalence of brain tumor disorders is currently a global issue. In general, radiography, which includes a large number of images, is an efficient method for diagnosing these life-threatening disorders. The biggest issue in this area is that it takes a radiologist a long time and is physically strenuous to look at all the images. As a result, research into developing systems based on machine learning to assist radiologists in diagnosis continues to rise daily. Convolutional neural networks (CNNs), one type of deep learning approach, have been pivotal in achieving state-of-the-art results in several medical imaging applications, including the identification of brain tumors. CNN hyperparameters are typically set manually for segmentation and classification, which might take a while and increase the chance of using suboptimal hyperparameters for both tasks. Bayesian optimization is a useful method for updating the deep CNN's optimal hyperparameters. The CNN network, however, can be considered a "black box" model because of how difficult it is to comprehend the information it stores because of its complexity. Therefore, this problem can be solved by using Explainable Artificial Intelligence (XAI) tools, which provide doctors with a realistic explanation of CNN's assessments. Implementation of deep learning-based systems in real-time diagnosis is still rare. One of the causes could be that these methods don't quantify the Uncertainty in the predictions, which could undermine trust in the AI-based diagnosis of diseases. To be used in real-time medical diagnosis, CNN-based models must be realistic and appealing, and uncertainty needs to be evaluated. So, a novel three-phase strategy is proposed for segmenting and classifying brain tumors. Segmentation of brain tumors using the DeeplabV3+ model is first performed with tuning of hyperparameters using Bayesian optimization. For classification, features from state-of-the-art deep learning models Darknet53 and mobilenetv2 are extracted and fed to SVM for classification, and hyperparameters of SVM are also optimized using a Bayesian approach. The second step is to understand whatever portion of the images CNN uses for feature extraction using XAI algorithms. Using confusion entropy, the Uncertainty of the Bayesian optimized classifier is finally quantified. Based on a Bayesian-optimized deep learning framework, the experimental findings demonstrate that the proposed method outperforms earlier techniques, achieving a 97 % classification accuracy and a 0.98 global accuracy., Competing Interests: Declaration of Competing Interest All authors declared no conflict of interest in this work., (Copyright © 2024 Elsevier B.V. All rights reserved.)