When an antigen stimulates the immune system, specific T regulatory (Treg) and T effector (Teff) subpopulations develop from naïve T cells. The Treg cell population will produce the memory Treg (mTreg) cells against that specific antigen. An inappropriate homeostatic balance among Teff, Treg and mTreg cells can direct the immune system toward either cancer or autoimmunity. When cancer is present, Treg cells suppress anti-tumor immunity, and, when cancer is absent, Treg cells play the beneficial role of preventing the development of autoimmunity. In this review, we analyze Treg responses after SARS-CoV-2 mRNA vaccination and find distinct pathological responses under differing conditions. In cancer patients, the degree of disease progression depends on the cancer status at the time of vaccination and the type of cancer treatment they receive concurrently. We hypothesize that migration of circulating dendritic cells and mTreg cells back to the thymus accelerates thymic involution, a direct cause of immunosenescence. In summary, the Treg responses produced after mRNA vaccination and the subsequent mRNA-encoded SARS-CoV-2 spike protein expression may lead to a harmful influence on the immune system of vaccinees, and subsequent accelerated development of cancer and autoimmune disease. These mechanisms are consistent with both epidemiological findings and case reports.

Rationale Solvent-free sample preparation offers some advantages over solvent-based techniques, such as improved accuracy, reproducibility, and sensitivity of MALDI analysis. However, little or no information is available on the application of solvent-free techniques for the MALDI analysis of polymer blends. Methods Solvent-free sample preparation by ball milling was applied with varying sample-to-matrix ratios for MALDI-TOF MS analysis of various polymers, including polystyrenes (PS), polymethyl methacrylates (PMMA), and polyethylene glycols (PEG). The peak intensity ratios were compared with those obtained after using the conventional dried droplet sample preparation method. In addition, solvent-assisted milling was also applied to improve sample homogeneities. Results Depending on the sample preparation method used, different peak intensity ratios were found, showing varying degrees of suppression of the signal intensities of higher mass polymers. Ball milling for up to 30 minutes was required to achieve constant intensity ratios indicating homogenous mixtures. The use of wet-assisted grinding to improve the homogeneity of the blend was found to be disadvantageous as it caused partial degradation and mass-dependent segregation of the polymers in the vials. Conclusions The results clearly show that solvent-free sample preparation must be carefully considered when applied to synthetic polymer blends, as it may cause additional problems with regard to homogeneity and stability of the blends.

The end-product concentration and productivity are critical issues in economic competition between biotechnological commercials and the chemical engineering industry. The prominent contradiction between high-titer products and the large-scale oxygen demand for aerobic biocatalysis leads to hyperviscosity, mass transport bottleneck in [dynamically changing](javascript:;) polyphase biosystems, and severe foaming problems. In this study, an intensification strategy for the whole-cell catalytic preparation of high-titer xylonic acid by Gluconobacter oxydans in a sealed-compressed oxygen supply bioreactor is propose. Multi-scale control factors are quantitatively studied to determine the biochemical parameter thresholds, and theoretically calculated the optimal production performance based on threshold effect. Finally, 650.8 g/L xylonic acid is obtained with a maximum productivity of 41.7 g/L/h with a catalytic performance of 95.8%, compared with the theoretical calculations. The intensification strategy for the oxygen transfer threshold effect overcome the stubborn obstacles of obligate aerobic catalysis, while providing a sustainable value-added pathway for fermentative lignocellulose.

Sedentary, inadequate sleep and exercise can affect human health. Artificial intelligence (AI) and Internet of thing (IoT) creates the Artificial Intelligence of Things (AIoT), providing the possibility to solve these problems. This paper presents a novel approach to monitor various human behaviors for AIoT-based health management using triboelectric nanogenerator (TENG) sensors. The insole with solely one TENG sensor, creating a most simplified system that utilizes machine learning (ML) for personalized motion monitoring, encompassing identity recognition and gait classification. A cushion with 12 TENG sensors achieves real-time identity and sitting posture recognition with accuracy rates of 98.86% and 98.40%, respectively, effectively correcting sedentary behavior. Similarly, a smart pillow, equipped with 15 sensory channels, detects head movements during sleep, identifying 8 sleep patterns with 96.25% accuracy. Ultimately, constructing an AIoT-based health management system to analyzes these data, displaying health status through human-machine interfaces, offering the potential to help individuals maintain good health.

Genetic diversity can modulate a population’s response to a changing environment and plays a critical role in its ecological function. While multiple processes act to maintain genetic diversity, sexual recruitment remains the primary driving force. At its southern edge-of-range, warming sea surface temperatures have resulted in shifts to a mixed-annual life-history strategy in the eelgrass (Zostera marina). Given that mating systems are intimately linked to standing levels of genetic variation, understanding the scope of sexual recruitment illuminates the processes that shape genetic diversity. To that end, developing seeds on flowering Z. marina shoots were genotyped from three meadows in Topsail, North Carolina. In all meadows, levels of multiple mating were high, with shoots pollinated by an average of 8 sires (range: 3 – 16). The number of fertilized seeds (i.e., reproductive success) varied significantly across sires (range: 1 – 25) and was positively correlated with both individual heterozygosity and self-fertilization. Outcrossing rates were high (approx. 70%) and varied across spathes. The reliance on sexual recruitment was also evident among sampled shoots, as no clones were detected and kinship among shoots was low. Given the role that genetic diversity plays in enhancing resistance to and resilience from ecological disturbance, disentangling the links between life-history, sexual reproduction and genetic structure will aid in informing the management and conservation of this key foundation species.

The construction sector is a significant contributor to global greenhouse gas emissions, resource depletion, and environmental degradation. Therefore, sustainable development in the construction sector is essential to reduce its environmental impact. Geopolymer materials have attracted particular attention offering technical properties similar to those of Portland cementitious materials with a much lower CO 2 emission and lower environmental impact. Their use as clean insulating materials seems promising due to their excellent thermal and mechanical properties. Moreover, natural fibers, such as bamboo, flax, hemp, and jute, can be used as reinforcement within the geopolymer matrix, providing additional benefits such as improved tensile and flexural strength, reduced density, and improved thermal and acoustic insulation properties. Hence, this review paper aims to explore the raw materials and manufacturing conditions involved in the formation of compact and porous geopolymer materials. In addition, the various factors affecting the properties of geopolymer materials are critically discussed and compared with those of Portland cementitious materials. Moreover, the impact of many variables, including fiber size, fiber orientation, and fiber content on the performance of natural fiber-reinforced geopolymer composites are highlighted, providing insights for future research developments.

Emotional knowledge (EK) refers to the ability to identify and understand emotions. EK is seldom explored in toddlerhood, when many of its facets begin to develop, nor in the context of online assessments. To address this gap, a sample of 98 toddlers (age:18-36-months, 55 female and 43 male) and their mothers (Mage= 32.5 years; 89.8% Caucasian) participated in this exploratory study investigating child and maternal characteristics associated with toddlers’ receptive and expressive EK abilities, which were evaluated using an online modified version of the Affective Knowledge Task (AKT). Results support the feasibility of assessing toddler EK online, as most of the toddlers (68.3%) were able to partially complete the task. Stronger receptive and expressive EK were both associated with older child age, yet receptive abilities were inversely related to maternal depression severity. Methodological strengths and suggestions are discussed to facilitate research including online assessments with younger cohorts.

Aim: Family function affects college students’ psychotic experience and what behaviors they have or have produced in daily life, and the corresponding effects of these behaviors. Through the problems reflected in the research institute, to create a family environment suitable for the physical and mental health of college students, to provide reference for the prevention of mental illness, promote the healthy growth of college students, the comprehensive development to lay a family foundation. Methods: Family functioning was assessed by the Family Function Rating Scale (FAD) and psychotic experiences were investigated in 715 college students by the Propsychotic Scale (PQ). With higher scores for all dimensions of family function, it indicates worse family function and worse psychotic experience. Establish the decision tree model and the path analysis model, find out the core factors affecting the psychotic experience, and clarify the direct or indirect influence of each factor on the psychotic experience. Results: In this study, 40 students were less than 2, accounting for 5.5% of the total; 672 students were less than 3, accounting for 91.7% of the total; 3 students were more than or equal to 3, accounting for 0.4% of the total; this indicates that the family function of college students is poor. The scores of the psychotic experience of college students all exceeded the assessed value, and the new experience of mental illness was more serious. Family function overall is a negative predictor of the psychotic experience. Decision tree and path analysis show that the role and emotional involvement dimensions in family function may be the core factors affecting the psychotic experience. Conclusion: Exploring the extent to which family functioning affects new experiences of psychosis helps to develop and target interventions to mitigate the increased risk of psychotic experiences among college students.

This article addresses the dynamic business environment, where enterprises grapple with diverse maintenance strategies, necessitating strategic decisions for integration. The focus is on innovative strategies that enhance both Reliability and robustness, ensuring sustained viability and a strategic advantage. Introducing a new criterion integrating the long-term expected maintenance cost rate, the standard deviation of the Maintenance cost per renewal cycle (MCPRC), and the relative weight of the cost variability, the study employs a rigorous Monte Carlo simulation approach using Matlab 1,2. The exploration begins with an overview of cost criteria in scholarly literature, providing a foundation for subsequent evaluation methodologies in maintenance strategies. Spotlighting the Inspection Cost, the article analyzes Reliability and Robustness metrics in Condition-Based Maintenance (CBM) and Time-Based Maintenance (TBM) strategies 3,4. The conclusion synthesizes theoretical foundations, methodological intricacies, and practical implications, emphasizing the enduring significance of insights for the nuanced optimization of TBM and CBM strategies in industrial maintenance.

Background: Recent advances in cancer genome analysis and the practice of precision medicine have made it possible to identify fractions with rare genetic alterations. EGFR-amplified cancers are known to be rare fractions across organs and have a poor prognosis. The use of anti-EGFR antibody for EGFR-amplified cancers has been promising, but the evidence is not yet clear. Case: In this report, we describe the case of a 48-year-old man diagnosed with advanced gallbladder cancer. The patient was administered Gemcitabine plus Cisplatin, followed by S-1 monotherapy; however, disease progression was observed after two cycles of each regimen. Comprehensive genomic profiling test revealed EGFR-amplification, and the patient was treated with combination therapy with the anti-EGFR antibody Necitumumab, Gemcitabine, and Cisplatin. After two cycles of treatment, showed a reduction in tumor size, and the treatment response was evaluated as partial response. On day 90, after five cycles of treatment, tumor progression was confirmed. In addition, after disease progression, liquid biopsy revealed acquired pathogenic gene alterations suggesting anti-EGFR antibody resistance. Conclusions: This report supports the clinical benefit of anti-EGFR antibody for EGFR-amplified biliary tract cancers and the importance of genomic analysis in personalized therapy and drug resistance research.

High frequency heart rate variability (HRV) is a vagally-mediated physiological index reflecting parasympathetic activity that has been linked to emotion regulation capacity. However, very limited research has examined associations of physiological indices of regulation such as HRV with emotional functioning in daily life. The few studies that exist have small samples sizes and typically focus on only a narrow aspect of emotion regulation or emotional functioning. In this study, we examined associations between HRV assessed in the laboratory and emotional/mental health functioning in daily life using a 7-day ecological momentary assessment design in 303 adult community participants. We hypothesized that higher resting HRV would be associated with higher positive affect, lower negative affect, less affective variability, greater wellbeing, fewer depressive and idiographic [person-specific] symptoms, greater use of engagement emotion regulation strategies, and less use of avoidance emotion regulation strategies, as assessed in daily life. Results revealed that higher resting HRV in the laboratory was significantly associated with lower negative affect and less frequent use of avoidance emotion regulation strategies in daily life, although only avoidance strategies remained significant when both were included in the same model. We also observed a trend association, such that idiographic symptoms in daily life were associated with lower resting HRV. Theoretical and clinical implications are discussed, including the association of HRV with negatively-valenced, rather than positively-valenced, daily life experiences.

The docking of an acyl carrier protein (ACP) domain with a downstream ketosynthase (KS) domain in each module of a polyketide synthase (PKS) helps ensure accurate biosynthesis. If the polyketide chain bound to the ACP has been properly modified by upstream processing enzymes and is compatible with gatekeeping residues in the KS tunnel, a transacylation reaction can transfer it from the 18.1-Å phosphopanthetheinyl arm of the ACP to the reactive cysteine of the KS. AlphaFold-Multimer predicts a general interface for these transacylation checkpoints. Half of the solutions obtained for 50 ACP/KS pairs show the KS motif TxLGDP forming the first turn of an a-helix, as in reported structures, while half show it forming a type I b-turn not previously observed. Solutions with the latter conformation may represent how these domains are relatively positioned during the transacylation reaction, as the entrance to the KS active site is relatively open and the phosphopantetheinylated ACP serine and the reactive KS cysteine are relatively closer - 17.2 Å vs. 20.9 Å, on average. To probe the predicted interface, 20 mutations were made to KS surface residues within the model triketide lactone synthase P1- P6- P7. The activities of these mutants are consistent with the proposed interface.

Biological control is an element of an integrated pest management approach by restoring or maintaining biodiversity and associated ecosystem services. Introducing flowering plants into crop management may promote the top-down pest suppression by natural enemies and reduce the reliance on pesticide use. Sage (Salvia farinacea Cav.) and marigold (Tagetes erecta L.) were planted in tea gardens in this paper to investigate the effect of sage and marigold, that of different layouts on the pest and natural enemy populations in tea gardens. It was found that sage and marigold, the checkerboard planting layout could consistently increase the population of natural enemies such as spiders, coccinellids, ladybird beetles, flower bugs, etc., and suppress the population of major pests (aphids, thrips, whiteflies, etc.) in tea gardens. At the same time, it was also found that the pests did not show significant tropism when flower plants and tea trees were present simultaneously, suggesting that flower plants may mask the ability of the host plant to achieve protection of the target crop. Additionally, the content composition of tea leaves, such as tea polyphenols and free amino acids, was significantly improved in the treated area planted with sage compared to the blank treatment group. Thus, it suggests that planting sage and marigold in tea gardens are not only a good measure to regulate the population density of natural enemies and pests, but also can have a positive impact on tea quality.

Artificial Intelligence (AI) has become widely used emerging technology for solving real world problems. With learning based approach, machine learning (ML) models are capable of learning from data and predict future possibilities. This kind of application of ML in education domain has far reaching benefits. The problem identified in academic institutions is that there is lack of AI based solutions to predict students’ academic achievement. Traditional approaches are efficient but fail in achieving more comprehensive analysis of data due to the bulk of historical data going unprocessed. There is need for AI based solution to help mentors to predict student performance in advance and take necessary steps. However, it is a challenging problem to be addressed due to complexities involved in arriving at decision making. To solve this problem, in this paper, we proposed a framework known as Intelligent Academic Achievement Prediction Framework (IAAPF). This framework has underlying ML models and Long Short Term Memory (LSTM) based deep learning model for students’ academic performance prediction. The framework predicts students’ academic performance early in terms of “low” or “high” which leads to required intelligence to mentors. We proposed two algorithms to realize IAAPF.

Power system unreliability tracing model allocates the system’s reliability index to individual components, identifying potential weaknesses. This study expands its scope by considering the impact of storage resources. Unreliable factors leading to load shedding are categorized into two groups: objective factors inherent to the component and insufficient storage resources. The latter requires a retrospective analysis of other components that caused unreliability previously. When allocating responsibility for load shedding at a certain time, it begins by allocating it among components based on differences between fixed expected output and actual supply. Expected output insufficiency is considered the unreliable factor. This insufficiency due to insufficient storage resources is then decomposed into segments, each caused by excessive output in earlier instances of the same component. The expected output excess is attributed to the expected output insufficiency of other components in previous times, for which responsibility has been allocated to each component. Consequently, the expected output insufficiency at a particular time can be traced back based on a temporal recursive model, with the load shedding further allocated to components before that time. Case studies based on several systems demonstrate that the proposed model’s allocation results are reasonable and more accurate than the traditional model.

Ventricular Arrhythmia Mortality in Patients with Heart Failure in the United States: Are There Differences Based on Race and Geography?Min Choon Tan MD1,2, Yong Hao Yeo MBBS3, Boon Jian San MBBS4, Justin Z. Lee MD5, Kamala Tamirisa MD6, Yong-Mei Cha MD7, Luis R. Scott MD2, Dan Sorajja MD2, Andrea M. Russo MD81 Department of Internal Medicine, New York Medical College at Saint Michael’s Medical Center, Newark, NJ, USA2 Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, AZ, USA3 Department of Internal Medicine/Pediatrics, William Beaumont University Hospital, Royal Oak, MI, USA4 AIMST University, Malaysia5 Department of Cardiovascular Medicine, Cleveland Clinic, Cleveland, OH, USA6 Texas Cardiac Arrhythmia, Dallas, TX, USA7 Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA8 Department of Cardiovascular Medicine, Cooper University Health System/Cooper Medical School of Rowan University, Camden, NJ, USADisclosures: All authors have no relationships relevant to the contents of this paper to disclose.Ethical approval: Not requiredFunding: This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectorsWord Count: 780Corresponding author:Andrea M. Russo MDDepartment of Cardiovascular Medicine,Cooper University Health System/Cooper Medical School of Rowan University1 Cooper Plaza,Camden, New Jersey 08103russo-andrea@cooperhealth.eduThe progression of heart failure (HF) is associated with detrimental myocardial structural changes, predisposing HF patients to an increased risk of ventricular arrhythmia (VA) events [1]. The evolving landscape in HF management as well as innovative approaches to VA like catheter ablation and neuromodulation, may impact morbidity and mortality. However, real-world data assessing the VA-related mortality trends among patients with HF remain scarce.The Centers for Disease Control and Prevention’s Wide-Ranging Online Data for EpidemiologicResearch (CDC WONDER) is a publicly available online database containing public health data, including mortality data. Death certificate data from CDC WONDER were analyzed from 1999 to2020 for VA-related mortality with comorbid HF among the U.S. population aged ≥ 25 years usingICD-10 codes. Ventricular arrhythmias included ventricular tachycardia (VT) (I47.2) and ventricularfibrillation (VF) (I49.0) as the underlying primary cause of death. Heart failure (I11.0, I13.0, I13.2,I50) was stated as a contributing cause of death. Age-adjusted mortality rates (AAMR) per 1,000,000individuals were calculated by standardizing VA-related mortality with comorbid HF to the 2000 U.S.census population. The trends were determined over time by estimating the annual percent change(APC) using the Joinpoint regression program. Given the deidentified and publicly available data,institutional review board approval was not required.Between 1999 and 2020, a total of 3,514 deaths related to VA with comorbid HF were identified.Overall, there was an increase in annual trends for the AAMR from 0.62 (95% CI, 0.50 - 0.73) in1999 to 1.06 (95% CI, 0.94 - 1.19) in 2020, with an APC of 3.39 (95% CI, 2.07, 4.73) (CentralIllustration) .When stratified by sex, cumulative AAMR was higher in males than females (1.09 [95% CI, 1.04-1.13] vs. 0.49 [95% CI, 0.47-0.52]). Both males and females had a similar increase in AAMR over the22 years; however, the AAPC was higher among males (4.30 [95% CI, 2.88-5.74] vs. 1.64 [95% CI,0.18-3.12]). When stratified by race, African American individuals had the highest AAMR (1.24 [95% CI, 1.14-1.35]), while the AAMR for White, Hispanic and Asian individuals were 0.72 (95% CI, 0.69-0.75), 0.40 (95% CI, 0.33-0.47), and 0.23 (95% CI, 0.16-0.32) respectively. The AAMR was higher in rural regions than in urban regions (0.81 [95% CI, 0.75-0.88] vs. 0.70 [95% CI, 0.68-0.73]). When AAMRs were compared between census regions of the U.S., the South region had the highest AAMR (0.86 [95% CI, 0.81-0.90]), followed by the Midwest (0.80 [95% CI, 0.75-0.85]), Northeast (0.62 [95%CI, 0.57-0.67]), and West region (0.56 [95% CI, 0.51-0.61]).This study provides crucial insight into VA-related mortality temporal trends and disparities among patients with comorbid HF. Despite advances in VA and HF management algorithms, our study revealed a 71% increase in AAMR in VA-related mortality with comorbid HF from 1999 to 2020. The observed growth in AAMR could be attributed to the rising use of cardiac implantable electronic devices, leading to increased recognition of VA as a terminal event [2]. Alternatively, more effective emergency medical services or greater availability of automatic external defibrillators may help to identify VT or VF as the initial rhythm recorded (rather than asystole or pulseless electrical activity). Our study raises the hypothesis that more diligent management of VA, including timely implantation of cardiac defibrillator devices and VT ablation could have an impact on this population.Our study demonstrates disparities in mortality trends, where American Africans and rural regionsrecorded higher AAMR. These may be potentially attributed to structural racism, conscious andunconscious biases, and the heightened socioeconomic challenges and access to medical care, presentin rural areas [3]. Limited or delayed access to complex tertiary care may impact mortality followingthe occurrence of sustained VA. Patients who live in rural or disadvantaged regions may not haveaccess to subspecialty referrals (such as electrophysiology or HF specialists) and may have delayed orlimited access to primary prevention therapies such as implantable cardioverter defibrillators orcardiac resynchronization therapy that may otherwise favorably influence outcomes. This highlightsthe need to address the potential causes of these inequalities and implement a focused policy thatincorporates the concept of social determinants of health to narrow the gap.There are several limitations in our study. First, due to the nature of death certificate data, an accurate assessment of the cause of death cannot be determined. Second, the database has no information at individual levels, such as comorbidity, ejection fraction, duration of diseases, and medical treatments, which are essential confounders for mortality.In conclusion, our study reveals an increase in VA-related mortality with comorbid HF, withdisparities seen in African Americans and rural regions. It underscores the pressing necessity for actions to facilitate the translation of treatment advancements into tangible improvements in mortality outcomes and healthcare inequalities.

EP Rounds

A Patient with Eosinophilic Gastroenteritis Presenting with Severe Abdominal Pain

Quantifying water use of various water consumers is an essential part of sustainable water management. Annual evapotranspirartion (ET) of plantation forests often exceeds that of dryland agriculture, which in South Africa and South Australia has resulted in restrictions on plantation development. In the latter case, water licenses are issued to commercial forestry plantations to account for higher ET compared to dryland pasture. Unlike irrigated crops, it is not practicable to measure water use of plantations directly and so a set of ‘deemed’ average water use rates has been applied based on species and depth to groundwater. Since the ‘deemed’ rates were calculated in 2013, additional plot-scale measurements of annual ET from plantations < 2 years old and post-canopy closure have been used to quantify various components of evapotranspiration (ET). This has enabled development of two empirical ET models for plantations in the region, and facilitated an advanced understanding of the effect of plantations on hydrological processes, particularly in relation to groundwater use. In this study, we applied these models to estimate rotation-averaged annual ET and net groundwater impacts (net groundwater extraction plus recharge reduction compared to pasture) of plantations, driven by climate and groundwater depth, for comparison with the deemed rates. The modelling suggests that the groundwater impacts of plantations vary in space and time and that the deemed rates over-estimate these impacts, on average. Accounting for variation in the effects of climate on the various components of ET, both spatially and temporally, may allow for more flexible rules for water resource allocation than using the current rule-of-thumb approach.

IoT EMBEDDED SYSTEMS IN HEALTHCARE 2 I.Introduction…………………………………………………………………………………………...4 A. Overview of IoT embedded systems B. Importance of identity access management in health data security C. Research focus: Exploring the intersection of IoT and identity access management in healthcare II. Understanding IoT Embedded Systems……………………………………….…………………...7 A. Definition and characteristics of IoT embedded systems B. Applications of IoT embedded systems in healthcare C. Challenges and vulnerabilities in IoT embedded systems III. Identity Access Management (IAM) in Healthcare……………………………………………..10 A. Definition and principles of IAM B. Importance of IAM in securing health data C. Current IAM practices in healthcare IV. Security Concerns in Healthcare Data…………………………………………..….…………...13 A. Overview of security threats and risks in healthcare data B. Consequences of security breaches in healthcare C. Need for enhanced security measures V. The Intersection: IoT Embedded Systems and IAM in Healthcare………………...…………...15 A. Potential benefits of integrating IoT and IAM in healthcare B. Challenges and limitations in implementing IAM in IoT embedded systems C. Case studies and examples of existing implementations VI. Proposed Framework for Enhanced Health Data Security…………………….………....…...18 A. Design considerations for integrating IAM into IoT embedded systems B. Implementation strategies for securing health data using IoT and IAM

Great advances have been made in the knowledge of development and regulatory approval of medicinal product containing genetically Modified cells. Although a guideline has been available in the EU since 2012, the current updated version provides a useful guide to developers and professionals involved in the regulatory process of these medicines. This article presents the main issues communicated in that guidance, the regulators' insights and a commentary from the academic developers' point of view.

Falls can result in severe injuries and even mortality among individuals of all age groups. Hence, numerous wearable sensor-based fall monitoring systems are being developed to provide assistance. Fall detection and activity tracking have been partially successful using smartwatches, smartphones, and specialized devices. However, a comprehensive solution that combines sensor data from different brands in a single model and performs fall detection with high accuracy and at a satisfactory level has not been encountered. This study aims to bridge this research gap by combining data from two different brands of IMUs (inertial measurement units) that incorporate accelerometers, magnetometers, and gyroscopes, in order to create a hybrid dataset. To achieve accurate predictions on data from both brands, machine learning (ML) models were trained using ML algorithms. The first dataset was obtained from 14 volunteers using a commercially available activity tracking system called Motion Trackers Wireless (MTw). The second dataset was collected from 30 volunteers using a custom-designed Activity Tracking Device (ATD) specifically developed for detecting falls and daily-life activities. In both cases, the sensors from the respective brands were positioned on the waist to capture data related to falls and daily-life activities. The data was organized using a time-series style to reveal relational effect of the sequential falling data. During the modelling, ten different classifiers trained, and classification was performed on unseen data using the data splitting method. The Extra Tree algorithm emerged as the most successful model, achieving an accuracy of 99.54%, precision of 99.18%, recall of 99.79%, and an F-score of 99.49% on the hybrid dataset constructed from the MTw and ATD datasets. This study demonstrates hybrid dataset to create a successful system with high accuracy and low false alarm rates using inertial sensor data from various brands.

Relapsed refractory leukaemia represents a difficult to treat population of patients. The balance between perceived benefit and potential side effects along with the significant financial burden of managing multidrug resistant sepsis are factors which determine the choice of salvage regimen. Here we present our experience with the combination of Fludrabine, Cytarabine, GCSF with Bortezomib. The morphological complete response rate was 58.% with 50% of the patients achieving complete remission. With only three patients requiring ICU admission during the period of care. 66.6% of the patients went on to undergo successful hematopoietic stem cell transplantation. Thus, proving to be a possible, safer alternative to other salvage regimens

DNA ligases catalyze bond formation in the backbone of nucleic acids via the formation of a phosphodiester bond between adjacent 5’ phosphates and 3’ hydroxyl groups on one strand of the duplex. While DNA ligases preferentially ligate single breaks in double stranded DNA (dsDNA), they are capable of ligating a multitude of other nucleic acids substrates like blunt-ended dsDNA, TA overhangs, short overhangs and various DNA-RNA hybrids. Here we report a novel DNA ligase from Chronobacter phage CR 9 (AZ R2D Ligase) with an unexpected DNA-to-RNA ligation activity. The R2D ligase shows excellent efficiency when ligating DNA to either end of RNA molecules using a DNA template. Furthermore, we show that DNA can be ligated simultaneously to both the 5’ and 3’ ends of microRNA-like molecules in a single reaction mixture. Abortive adenylated side product formation is suppressed at lower ATP concentrations and the ligase reaction reaches near completion when ligating RNA to DNA or DNA to RNA. The ligation of a DNA strand to the 5’-PO4 end of RNA is unique among the commercially available ligases and may facilitate novel workflows in microRNA analysis, RNA sequencing and in the preparation of chimeric guide DNA-RNA for gene editing applications.